From 40495491e0a42e591a415b2208c507adeed23975 Mon Sep 17 00:00:00 2001 From: bhumikasudarshani-cmd Date: Fri, 17 Apr 2026 08:03:47 +0000 Subject: [PATCH 1/2] benchmark: replace Array constructor with literal and fix formatting --- .eslintignore | 2 +- .../check_pr_issue_references.lock.yml | 8 +- .../workflows/generate_monthly_changelog.yml | 2 +- .github/workflows/git_note_amend_message.yml | 2 +- .../workflows/git_note_filter_packages.yml | 2 +- .github/workflows/lint_autofix.yml | 2 +- .github/workflows/lint_changed_files.yml | 43 +- .github/workflows/lint_random_files.yml | 4 +- .github/workflows/markdown_equations.yml | 2 +- .github/workflows/markdown_pkg_urls.yml | 2 +- .../workflows/markdown_related_packages.yml | 2 +- .github/workflows/markdown_tocs.yml | 2 +- .github/workflows/merge_ready_prs.yml | 2 +- .github/workflows/namespace_declarations.yml | 2 +- .github/workflows/namespace_exports.yml | 2 +- .github/workflows/pr_merge_develop.yml | 2 +- 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.../poisson/benchmark/benchmark.generic.js | 3 +- .../benchmark/benchmark.float32.factory.js | 3 +- .../randu/benchmark/benchmark.float32.js | 3 +- .../benchmark/benchmark.float64.factory.js | 3 +- .../randu/benchmark/benchmark.float64.js | 3 +- .../benchmark/benchmark.generic.factory.js | 3 +- .../randu/benchmark/benchmark.generic.js | 3 +- .../benchmark/benchmark.float32.assign.js | 3 +- .../benchmark/benchmark.float32.factory.js | 3 +- .../rayleigh/benchmark/benchmark.float32.js | 3 +- .../benchmark/benchmark.float64.assign.js | 3 +- .../benchmark/benchmark.float64.factory.js | 3 +- .../rayleigh/benchmark/benchmark.float64.js | 3 +- .../benchmark/benchmark.generic.assign.js | 3 +- .../benchmark/benchmark.generic.factory.js | 3 +- .../rayleigh/benchmark/benchmark.generic.js | 3 +- .../t/benchmark/benchmark.float32.assign.js | 3 +- .../t/benchmark/benchmark.float32.factory.js | 3 +- .../array/t/benchmark/benchmark.float32.js | 3 +- .../t/benchmark/benchmark.float64.assign.js | 3 +- 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3 +- .../unary-factory/benchmark/benchmark.js | 5 +- .../benchmark/benchmark.length.js | 3 +- .../tools/unary/benchmark/benchmark.assign.js | 3 +- .../unary/benchmark/benchmark.generate.js | 3 +- .../array/tools/unary/benchmark/benchmark.js | 5 +- .../benchmark/benchmark.float32.assign.js | 3 +- .../benchmark/benchmark.float32.factory.js | 3 +- .../triangular/benchmark/benchmark.float32.js | 3 +- .../benchmark/benchmark.float64.assign.js | 3 +- .../benchmark/benchmark.float64.factory.js | 3 +- .../triangular/benchmark/benchmark.float64.js | 3 +- .../benchmark/benchmark.generic.assign.js | 3 +- .../benchmark/benchmark.generic.factory.js | 3 +- .../triangular/benchmark/benchmark.generic.js | 3 +- .../benchmark/benchmark.float32.assign.js | 3 +- .../benchmark/benchmark.float32.factory.js | 3 +- .../uniform/benchmark/benchmark.float32.js | 3 +- .../benchmark/benchmark.float64.assign.js | 3 +- .../benchmark/benchmark.float64.factory.js | 3 +- .../uniform/benchmark/benchmark.float64.js | 3 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.../iter/chisquare/benchmark/benchmark.js | 3 +- .../random/iter/cosine/benchmark/benchmark.js | 3 +- .../discrete-uniform/benchmark/benchmark.js | 3 +- .../random/iter/erlang/benchmark/benchmark.js | 3 +- .../iter/exponential/benchmark/benchmark.js | 3 +- .../random/iter/f/benchmark/benchmark.js | 3 +- .../iter/frechet/benchmark/benchmark.js | 3 +- .../random/iter/gamma/benchmark/benchmark.js | 3 +- .../iter/geometric/benchmark/benchmark.js | 3 +- .../random/iter/gumbel/benchmark/benchmark.js | 3 +- .../hypergeometric/benchmark/benchmark.js | 3 +- .../improved-ziggurat/benchmark/benchmark.js | 3 +- .../iter/invgamma/benchmark/benchmark.js | 3 +- .../iter/kumaraswamy/benchmark/benchmark.js | 3 +- .../iter/laplace/benchmark/benchmark.js | 3 +- .../random/iter/levy/benchmark/benchmark.js | 3 +- .../iter/logistic/benchmark/benchmark.js | 3 +- .../iter/lognormal/benchmark/benchmark.js | 3 +- .../minstd-shuffle/benchmark/benchmark.js | 3 +- .../random/iter/minstd/benchmark/benchmark.js | 3 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.../f/benchmark/benchmark.throughput.js | 11 +- .../streams/frechet/benchmark/benchmark.js | 7 +- .../frechet/benchmark/benchmark.throughput.js | 11 +- .../streams/gamma/benchmark/benchmark.js | 7 +- .../gamma/benchmark/benchmark.throughput.js | 11 +- .../streams/geometric/benchmark/benchmark.js | 7 +- .../benchmark/benchmark.throughput.js | 11 +- .../streams/gumbel/benchmark/benchmark.js | 7 +- .../gumbel/benchmark/benchmark.throughput.js | 11 +- .../hypergeometric/benchmark/benchmark.js | 7 +- .../benchmark/benchmark.throughput.js | 11 +- .../improved-ziggurat/benchmark/benchmark.js | 7 +- .../benchmark/benchmark.throughput.js | 11 +- .../streams/invgamma/benchmark/benchmark.js | 7 +- .../benchmark/benchmark.throughput.js | 11 +- .../kumaraswamy/benchmark/benchmark.js | 7 +- .../benchmark/benchmark.throughput.js | 11 +- .../streams/laplace/benchmark/benchmark.js | 7 +- .../laplace/benchmark/benchmark.throughput.js | 11 +- .../streams/levy/benchmark/benchmark.js | 7 +- .../levy/benchmark/benchmark.throughput.js | 11 +- .../streams/logistic/benchmark/benchmark.js | 7 +- .../benchmark/benchmark.throughput.js | 11 +- .../streams/lognormal/benchmark/benchmark.js | 7 +- .../benchmark/benchmark.throughput.js | 11 +- .../minstd-shuffle/benchmark/benchmark.js | 7 +- .../benchmark/benchmark.throughput.js | 11 +- .../streams/minstd/benchmark/benchmark.js | 7 +- .../minstd/benchmark/benchmark.throughput.js | 11 +- .../streams/mt19937/benchmark/benchmark.js | 7 +- .../mt19937/benchmark/benchmark.throughput.js | 11 +- .../negative-binomial/benchmark/benchmark.js | 7 +- .../benchmark/benchmark.throughput.js | 11 +- .../streams/normal/benchmark/benchmark.js | 7 +- .../normal/benchmark/benchmark.throughput.js | 11 +- .../pareto-type1/benchmark/benchmark.js | 7 +- .../benchmark/benchmark.throughput.js | 11 +- .../streams/poisson/benchmark/benchmark.js | 7 +- .../poisson/benchmark/benchmark.throughput.js | 11 +- .../streams/randi/benchmark/benchmark.js | 7 +- .../randi/benchmark/benchmark.throughput.js | 11 +- .../streams/randn/benchmark/benchmark.js | 7 +- .../randn/benchmark/benchmark.throughput.js | 11 +- .../streams/randu/benchmark/benchmark.js | 7 +- .../randu/benchmark/benchmark.throughput.js | 11 +- .../streams/rayleigh/benchmark/benchmark.js | 7 +- .../benchmark/benchmark.throughput.js | 11 +- .../random/streams/t/benchmark/benchmark.js | 7 +- .../t/benchmark/benchmark.throughput.js | 11 +- .../streams/triangular/benchmark/benchmark.js | 7 +- .../benchmark/benchmark.throughput.js | 11 +- .../streams/uniform/benchmark/benchmark.js | 7 +- .../uniform/benchmark/benchmark.throughput.js | 11 +- .../streams/weibull/benchmark/benchmark.js | 7 +- .../weibull/benchmark/benchmark.throughput.js | 11 +- .../benchmark/benchmark.float32.broadcast.js | 3 +- .../arcsine/benchmark/benchmark.float32.js | 3 +- .../benchmark/benchmark.float64.broadcast.js | 3 +- .../benchmark.float64.broadcast.options.js | 3 +- .../arcsine/benchmark/benchmark.float64.js | 3 +- .../benchmark/benchmark.float64.options.js | 3 +- .../benchmark/benchmark.generic.broadcast.js | 3 +- .../arcsine/benchmark/benchmark.generic.js | 3 +- .../benchmark/benchmark.float32.broadcast.js | 3 +- .../bernoulli/benchmark/benchmark.float32.js | 3 +- .../benchmark/benchmark.float64.broadcast.js | 3 +- .../bernoulli/benchmark/benchmark.float64.js | 3 +- .../benchmark/benchmark.generic.broadcast.js | 3 +- .../bernoulli/benchmark/benchmark.generic.js | 3 +- .../benchmark/benchmark.float32.broadcast.js | 3 +- .../beta/benchmark/benchmark.float32.js | 3 +- .../benchmark/benchmark.float64.broadcast.js | 3 +- .../benchmark.float64.broadcast.options.js | 3 +- .../beta/benchmark/benchmark.float64.js | 3 +- .../benchmark/benchmark.float64.options.js | 3 +- .../benchmark/benchmark.generic.broadcast.js | 3 +- .../beta/benchmark/benchmark.generic.js | 3 +- .../benchmark/benchmark.float32.broadcast.js | 3 +- .../betaprime/benchmark/benchmark.float32.js | 3 +- .../benchmark/benchmark.float64.broadcast.js | 3 +- .../benchmark.float64.broadcast.options.js | 3 +- .../betaprime/benchmark/benchmark.float64.js | 3 +- .../benchmark/benchmark.float64.options.js | 3 +- .../benchmark/benchmark.generic.broadcast.js | 3 +- .../betaprime/benchmark/benchmark.generic.js | 3 +- .../benchmark/benchmark.float32.broadcast.js | 3 +- .../chi/benchmark/benchmark.float32.js | 3 +- .../benchmark/benchmark.float64.broadcast.js | 3 +- .../chi/benchmark/benchmark.float64.js | 3 +- .../benchmark/benchmark.generic.broadcast.js | 3 +- .../chi/benchmark/benchmark.generic.js | 3 +- .../benchmark/benchmark.float32.broadcast.js | 3 +- .../chisquare/benchmark/benchmark.float32.js | 3 +- .../benchmark/benchmark.float64.broadcast.js | 3 +- .../chisquare/benchmark/benchmark.float64.js | 3 +- .../benchmark/benchmark.generic.broadcast.js | 3 +- .../chisquare/benchmark/benchmark.generic.js | 3 +- .../benchmark/benchmark.float32.broadcast.js | 3 +- .../cosine/benchmark/benchmark.float32.js | 3 +- .../benchmark/benchmark.float64.broadcast.js | 3 +- .../benchmark.float64.broadcast.options.js | 3 +- .../cosine/benchmark/benchmark.float64.js | 3 +- .../benchmark/benchmark.float64.options.js | 3 +- .../benchmark/benchmark.generic.broadcast.js | 3 +- .../cosine/benchmark/benchmark.generic.js | 3 +- .../benchmark/benchmark.float32.broadcast.js | 3 +- .../benchmark/benchmark.float32.js | 3 +- .../benchmark/benchmark.float64.broadcast.js | 3 +- .../benchmark.float64.broadcast.options.js | 3 +- .../benchmark/benchmark.float64.js | 3 +- .../benchmark/benchmark.float64.options.js | 3 +- .../benchmark/benchmark.generic.broadcast.js | 3 +- .../benchmark/benchmark.generic.js | 3 +- .../benchmark/benchmark.int32.broadcast.js | 3 +- .../benchmark/benchmark.int32.js | 3 +- .../benchmark/benchmark.float32.broadcast.js | 3 +- .../benchmark/benchmark.float32.js | 3 +- .../benchmark/benchmark.float64.broadcast.js | 3 +- .../benchmark/benchmark.float64.js | 3 +- .../benchmark/benchmark.generic.broadcast.js | 3 +- .../benchmark/benchmark.generic.js | 3 +- .../benchmark/benchmark.float32.broadcast.js | 3 +- .../gamma/benchmark/benchmark.float32.js | 3 +- .../benchmark/benchmark.float64.broadcast.js | 3 +- .../benchmark.float64.broadcast.options.js | 3 +- .../gamma/benchmark/benchmark.float64.js | 3 +- .../benchmark/benchmark.float64.options.js | 3 +- .../benchmark/benchmark.generic.broadcast.js | 3 +- .../gamma/benchmark/benchmark.generic.js | 3 +- .../benchmark/benchmark.float32.broadcast.js | 3 +- .../geometric/benchmark/benchmark.float32.js | 3 +- .../benchmark/benchmark.float64.broadcast.js | 3 +- .../geometric/benchmark/benchmark.float64.js | 3 +- .../benchmark/benchmark.generic.broadcast.js | 3 +- .../geometric/benchmark/benchmark.generic.js | 3 +- .../benchmark/benchmark.float32.broadcast.js | 3 +- .../invgamma/benchmark/benchmark.float32.js | 3 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.../@stdlib/stats/strided/dmskmin/README.md | 2 +- .../@stdlib/stats/strided/dmskrange/README.md | 2 +- .../@stdlib/stats/strided/dnancount/README.md | 290 +++++ .../strided/dnancount/benchmark/benchmark.js | 111 ++ .../dnancount/benchmark/benchmark.native.js | 120 ++ .../dnancount/benchmark/benchmark.ndarray.js | 111 ++ .../benchmark/benchmark.ndarray.native.js | 120 ++ .../strided/dnancount/benchmark/c/Makefile | 146 +++ .../dnancount/benchmark/c/benchmark.length.c | 209 ++++ .../stats/strided/dnancount/binding.gyp | 170 +++ .../stats/strided/dnancount/docs/repl.txt | 89 ++ .../strided/dnancount/docs/types/index.d.ts | 92 ++ .../strided/dnancount/docs/types/test.ts | 157 +++ .../strided/dnancount/examples/c/Makefile | 146 +++ .../strided/dnancount/examples/c/example.c | 38 + .../stats/strided/dnancount/examples/index.js | 37 + .../stats/strided/dnancount/include.gypi | 53 + .../include/stdlib/stats/strided/dnancount.h | 45 + .../stats/strided/dnancount/lib/dnancount.js | 52 + 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+- .../benchmark/benchmark.native.js | 3 +- .../benchmark/benchmark.ndarray.js | 3 +- .../benchmark/benchmark.ndarray.native.js | 3 +- .../@stdlib/stats/strided/dpcorrwd/README.md | 347 ++++++ .../strided/dpcorrwd/benchmark/benchmark.js | 104 ++ .../dpcorrwd/benchmark/benchmark.native.js | 109 ++ .../dpcorrwd/benchmark/benchmark.ndarray.js | 104 ++ .../benchmark/benchmark.ndarray.native.js | 109 ++ .../strided/dpcorrwd/benchmark/c/Makefile | 146 +++ .../dpcorrwd/benchmark/c/benchmark.length.c | 209 ++++ .../stats/strided/dpcorrwd/binding.gyp | 170 +++ .../stats/strided/dpcorrwd/docs/repl.txt | 112 ++ .../strided/dpcorrwd/docs/types/index.d.ts | 103 ++ .../stats/strided/dpcorrwd/docs/types/test.ts | 249 ++++ .../strided/dpcorrwd/examples/c/Makefile | 146 +++ .../strided/dpcorrwd/examples/c/example.c | 45 + .../stats/strided/dpcorrwd/examples/index.js | 34 + .../stats/strided/dpcorrwd/include.gypi | 53 + .../include/stdlib/stats/strided/dpcorrwd.h | 45 + 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+- .../drange/benchmark/benchmark.ndarray.js | 3 +- .../benchmark/benchmark.ndarray.native.js | 3 +- .../stats/strided/dsem/benchmark/benchmark.js | 3 +- .../dsem/benchmark/benchmark.native.js | 3 +- .../dsem/benchmark/benchmark.ndarray.js | 3 +- .../benchmark/benchmark.ndarray.native.js | 3 +- .../strided/dsemch/benchmark/benchmark.js | 3 +- .../dsemch/benchmark/benchmark.native.js | 3 +- .../dsemch/benchmark/benchmark.ndarray.js | 3 +- .../benchmark/benchmark.ndarray.native.js | 3 +- .../strided/dsempn/benchmark/benchmark.js | 3 +- .../dsempn/benchmark/benchmark.native.js | 3 +- .../dsempn/benchmark/benchmark.ndarray.js | 3 +- .../benchmark/benchmark.ndarray.native.js | 3 +- .../strided/dsemtk/benchmark/benchmark.js | 3 +- .../dsemtk/benchmark/benchmark.native.js | 3 +- .../dsemtk/benchmark/benchmark.ndarray.js | 3 +- .../benchmark/benchmark.ndarray.native.js | 3 +- .../strided/dsemwd/benchmark/benchmark.js | 3 +- .../dsemwd/benchmark/benchmark.native.js | 3 +- 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lib/node_modules/@stdlib/stats/strided/snancount/test/test.snancount.js create mode 100644 lib/node_modules/@stdlib/stats/strided/snancount/test/test.snancount.native.js diff --git a/.eslintignore b/.eslintignore index 0203f7e1345c..d12b55493cbd 100644 --- a/.eslintignore +++ b/.eslintignore @@ -30,7 +30,7 @@ reports/ # Node.js # ########### /node_modules/ -!/**/node_modules/* + # Git # ####### diff --git a/.github/workflows/check_pr_issue_references.lock.yml b/.github/workflows/check_pr_issue_references.lock.yml index fa1ac6f40ef8..be6d42926cc8 100644 --- a/.github/workflows/check_pr_issue_references.lock.yml +++ b/.github/workflows/check_pr_issue_references.lock.yml @@ -56,7 +56,7 @@ jobs: secret_verification_result: ${{ steps.validate-secret.outputs.verification_result }} steps: - name: Setup Scripts - uses: github/gh-aw-actions/setup@71cfb3cbe2002225f9d5afa180669fff36b86ea2 # v0.61.2 + uses: github/gh-aw-actions/setup@cb2bf21eadb070848fd3fe6edfa4a5af2e73e93a # v0.61.2 with: destination: ${{ runner.temp }}/gh-aw/actions - name: Generate agentic run info @@ -264,7 +264,7 @@ jobs: output_types: ${{ steps.collect_output.outputs.output_types }} steps: - name: Setup Scripts - uses: github/gh-aw-actions/setup@71cfb3cbe2002225f9d5afa180669fff36b86ea2 # v0.61.2 + uses: github/gh-aw-actions/setup@cb2bf21eadb070848fd3fe6edfa4a5af2e73e93a # v0.61.2 with: destination: ${{ runner.temp }}/gh-aw/actions - name: Set runtime paths @@ -840,7 +840,7 @@ jobs: total_count: ${{ steps.missing_tool.outputs.total_count }} steps: - name: Setup Scripts - uses: github/gh-aw-actions/setup@71cfb3cbe2002225f9d5afa180669fff36b86ea2 # v0.61.2 + uses: github/gh-aw-actions/setup@cb2bf21eadb070848fd3fe6edfa4a5af2e73e93a # v0.61.2 with: destination: ${{ runner.temp }}/gh-aw/actions - name: Download agent output artifact @@ -951,7 +951,7 @@ jobs: process_safe_outputs_temporary_id_map: ${{ steps.process_safe_outputs.outputs.temporary_id_map }} steps: - name: Setup Scripts - uses: github/gh-aw-actions/setup@71cfb3cbe2002225f9d5afa180669fff36b86ea2 # v0.61.2 + uses: github/gh-aw-actions/setup@cb2bf21eadb070848fd3fe6edfa4a5af2e73e93a # v0.61.2 with: destination: ${{ runner.temp }}/gh-aw/actions - name: Download agent output artifact diff --git a/.github/workflows/generate_monthly_changelog.yml b/.github/workflows/generate_monthly_changelog.yml index e382eb7b3ecc..47b12df5e887 100644 --- a/.github/workflows/generate_monthly_changelog.yml +++ b/.github/workflows/generate_monthly_changelog.yml @@ -106,7 +106,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/git_note_amend_message.yml b/.github/workflows/git_note_amend_message.yml index 39a1b8afd176..74d036a289d1 100644 --- a/.github/workflows/git_note_amend_message.yml +++ b/.github/workflows/git_note_amend_message.yml @@ -120,7 +120,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/git_note_filter_packages.yml b/.github/workflows/git_note_filter_packages.yml index 41812622487d..704343aca584 100644 --- a/.github/workflows/git_note_filter_packages.yml +++ b/.github/workflows/git_note_filter_packages.yml @@ -129,7 +129,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/lint_autofix.yml b/.github/workflows/lint_autofix.yml index d56e90b1b132..5e24bed3e8e9 100644 --- a/.github/workflows/lint_autofix.yml +++ b/.github/workflows/lint_autofix.yml @@ -161,7 +161,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/lint_changed_files.yml b/.github/workflows/lint_changed_files.yml index c5da1b28f6f3..9cba3c45d358 100644 --- a/.github/workflows/lint_changed_files.yml +++ b/.github/workflows/lint_changed_files.yml @@ -75,7 +75,7 @@ jobs: # Restore cache if up-to-date: - name: 'Restore cache if up-to-date' # Pin action to full length commit SHA - uses: actions/cache/restore@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 # v5.0.3 + uses: actions/cache/restore@668228422ae6a00e4ad889ee87cd7109ec5666a7 # v5.0.4 id: cache with: path: | @@ -138,7 +138,7 @@ jobs: # Save cache after editorconfig-checker binary has been downloaded: - name: 'Save cache after editorconfig-checker binary has been downloaded' if: always() && steps.cache.outputs.cache-hit != 'true' - uses: actions/cache/save@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 # v5.0.3 + uses: actions/cache/save@668228422ae6a00e4ad889ee87cd7109ec5666a7 # v5.0.4 with: path: ${{ github.workspace }}/node_modules key: ${{ steps.cache.outputs.cache-primary-key }} @@ -274,7 +274,7 @@ jobs: # Pin action to full length commit SHA uses: r-lib/actions/setup-r@6f6e5bc62fba3a704f74e7ad7ef7676c5c6a2590 # v2.11.4 with: - r-version: '4.2.0' + r-version: '4.3.3' # Lint R files: - name: 'Lint R files' @@ -341,6 +341,43 @@ jobs: make lint-typescript-declarations-files FILES="${files}" fi + # Lint TypeScript declarations test files: + - name: 'Lint TypeScript declarations test files' + if: success() || failure() + run: | + # Determine root directory: + root=$(git rev-parse --show-toplevel) + + # Define the path to ESLint configuration file for linting TypeScript tests: + eslint_typescript_tests_conf="${root}/etc/eslint/.eslintrc.typescript.tests.js" + + # Get changed files: + changed_files=$(echo "${{ steps.changed-files.outputs.files }}" | tr ' ' '\n') + + # Get directly changed `test.ts` files: + files=$(echo "${changed_files}" | grep '/docs/types/test\.ts$' | tr '\n' ' ' | sed 's/ $//') + + # Also get `test.ts` files corresponding to changed `index.d.ts` files... + declaration_files=$(echo "${changed_files}" | grep '/docs/types/.*\.d\.ts$' | sed 's/ $//') + if [[ -n "${declaration_files}" ]]; then + while IFS= read -r decl_file; do + # Only process index.d.ts files (skip other .d.ts files) + if [[ "${decl_file}" == */index.d.ts ]]; then + # Replace `index.d.ts` with `test.ts` to get the test file path: + test_file="${decl_file%index.d.ts}test.ts" + + # Check if the test file exists and isn't already in the list: + if [[ -f "${test_file}" ]] && [[ ! " ${files} " =~ [[:space:]]${test_file}[[:space:]] ]]; then + files="${files} ${test_file}" + fi + fi + done <<< "${declaration_files}" + fi + + if [[ -n "${files}" ]]; then + make lint-typescript-declarations-files FILES="${files}" ESLINT_TS_CONF="${eslint_typescript_tests_conf}" + fi + # Lint license headers: - name: 'Lint license headers' if: success() || failure() diff --git a/.github/workflows/lint_random_files.yml b/.github/workflows/lint_random_files.yml index 03666d36eea8..80946001ac9a 100644 --- a/.github/workflows/lint_random_files.yml +++ b/.github/workflows/lint_random_files.yml @@ -374,7 +374,7 @@ jobs: # Pin action to full length commit SHA uses: r-lib/actions/setup-r@6f6e5bc62fba3a704f74e7ad7ef7676c5c6a2590 # v2.11.4 with: - r-version: '4.2.0' + r-version: '4.3.3' # Lint R files: - name: 'Lint R files' @@ -573,7 +573,7 @@ jobs: - name: 'Import GPG key to sign commits' if: ${{ github.event.inputs.fix == 'true' }} && ( success() || failure() ) # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/markdown_equations.yml b/.github/workflows/markdown_equations.yml index 9659a1910523..11ed079c31ca 100644 --- a/.github/workflows/markdown_equations.yml +++ b/.github/workflows/markdown_equations.yml @@ -99,7 +99,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/markdown_pkg_urls.yml b/.github/workflows/markdown_pkg_urls.yml index 8e1611252e6f..03ab56c91be9 100644 --- a/.github/workflows/markdown_pkg_urls.yml +++ b/.github/workflows/markdown_pkg_urls.yml @@ -111,7 +111,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/markdown_related_packages.yml b/.github/workflows/markdown_related_packages.yml index acf28e8dbf32..f1a3777f1449 100644 --- a/.github/workflows/markdown_related_packages.yml +++ b/.github/workflows/markdown_related_packages.yml @@ -108,7 +108,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/markdown_tocs.yml b/.github/workflows/markdown_tocs.yml index b49d93d7f9b2..15cf624cee4b 100644 --- a/.github/workflows/markdown_tocs.yml +++ b/.github/workflows/markdown_tocs.yml @@ -110,7 +110,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/merge_ready_prs.yml b/.github/workflows/merge_ready_prs.yml index 5c88ee1522f5..f11dc5ca07e9 100644 --- a/.github/workflows/merge_ready_prs.yml +++ b/.github/workflows/merge_ready_prs.yml @@ -49,7 +49,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/namespace_declarations.yml b/.github/workflows/namespace_declarations.yml index 62dac30e1d4f..dbad891ab426 100644 --- a/.github/workflows/namespace_declarations.yml +++ b/.github/workflows/namespace_declarations.yml @@ -94,7 +94,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/namespace_exports.yml b/.github/workflows/namespace_exports.yml index a112221c5420..0f6a3313f6ec 100644 --- a/.github/workflows/namespace_exports.yml +++ b/.github/workflows/namespace_exports.yml @@ -117,7 +117,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/pr_merge_develop.yml b/.github/workflows/pr_merge_develop.yml index 0b5d48fcc37d..fa123410f52f 100644 --- a/.github/workflows/pr_merge_develop.yml +++ b/.github/workflows/pr_merge_develop.yml @@ -89,7 +89,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/pr_rebase_develop.yml b/.github/workflows/pr_rebase_develop.yml index 52c527699cf8..684e3edfab23 100644 --- a/.github/workflows/pr_rebase_develop.yml +++ b/.github/workflows/pr_rebase_develop.yml @@ -90,7 +90,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/publish_coverage_pr.yml b/.github/workflows/publish_coverage_pr.yml index 3897aad3e2b0..2c4eeedf01a0 100644 --- a/.github/workflows/publish_coverage_pr.yml +++ b/.github/workflows/publish_coverage_pr.yml @@ -53,7 +53,7 @@ jobs: - name: 'Download PR metadata' id: download-metadata # Pin action to full length commit SHA - uses: actions/download-artifact@70fc10c6e5e1ce46ad2ea6f2b72d43f7d47b13c3 # v8.0.0 + uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1 with: name: pr-metadata path: pr-metadata/ @@ -110,7 +110,7 @@ jobs: - name: 'Download coverage artifacts' id: download-coverage # Pin action to full length commit SHA - uses: actions/download-artifact@70fc10c6e5e1ce46ad2ea6f2b72d43f7d47b13c3 # v8.0.0 + uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1 with: name: coverage-artifacts path: artifacts/ @@ -180,7 +180,7 @@ jobs: - name: 'Import GPG key to sign commits' if: steps.download-coverage.outcome == 'success' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/run_affected_benchmarks.yml b/.github/workflows/run_affected_benchmarks.yml index 557830ce68ae..9a6a9a0b83f6 100644 --- a/.github/workflows/run_affected_benchmarks.yml +++ b/.github/workflows/run_affected_benchmarks.yml @@ -91,7 +91,7 @@ jobs: # Cache dependencies: - name: 'Cache dependencies' # Pin action to full length commit SHA - uses: actions/cache@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 # v5.0.3 + uses: actions/cache@668228422ae6a00e4ad889ee87cd7109ec5666a7 # v5.0.4 id: cache with: path: | diff --git a/.github/workflows/run_affected_examples.yml b/.github/workflows/run_affected_examples.yml index 263448cd0195..e2ea282631bb 100644 --- a/.github/workflows/run_affected_examples.yml +++ b/.github/workflows/run_affected_examples.yml @@ -88,7 +88,7 @@ jobs: # Cache dependencies: - name: 'Cache dependencies' # Pin action to full length commit SHA - uses: actions/cache@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 # v5.0.3 + uses: actions/cache@668228422ae6a00e4ad889ee87cd7109ec5666a7 # v5.0.4 id: cache with: path: | diff --git a/.github/workflows/run_affected_tests.yml b/.github/workflows/run_affected_tests.yml index 3e47485c817e..f75ab32f8370 100644 --- a/.github/workflows/run_affected_tests.yml +++ b/.github/workflows/run_affected_tests.yml @@ -123,7 +123,7 @@ jobs: # Cache dependencies: - name: 'Cache dependencies' # Pin action to full length commit SHA - uses: actions/cache@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 # v5.0.3 + uses: actions/cache@668228422ae6a00e4ad889ee87cd7109ec5666a7 # v5.0.4 id: cache with: path: | diff --git a/.github/workflows/run_tests_coverage.yml b/.github/workflows/run_tests_coverage.yml index 5ee3143ea928..c6a50a5a09c3 100644 --- a/.github/workflows/run_tests_coverage.yml +++ b/.github/workflows/run_tests_coverage.yml @@ -100,7 +100,7 @@ jobs: # Cache dependencies: - name: 'Cache dependencies' # Pin action to full length commit SHA - uses: actions/cache@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 # v5.0.3 + uses: actions/cache@668228422ae6a00e4ad889ee87cd7109ec5666a7 # v5.0.4 id: cache with: path: | @@ -263,7 +263,7 @@ jobs: - name: 'Import GPG key to sign commits' if: steps.check-changed.outputs.skip == 'false' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/run_tests_coverage_pr.yml b/.github/workflows/run_tests_coverage_pr.yml index 47505aadb85d..a121a8bf3bb4 100644 --- a/.github/workflows/run_tests_coverage_pr.yml +++ b/.github/workflows/run_tests_coverage_pr.yml @@ -93,7 +93,7 @@ jobs: # Cache dependencies: - name: 'Cache dependencies' # Pin action to full length commit SHA - uses: actions/cache@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 # v5.0.3 + uses: actions/cache@668228422ae6a00e4ad889ee87cd7109ec5666a7 # v5.0.4 id: cache with: path: | diff --git a/.github/workflows/terminal.yml b/.github/workflows/terminal.yml index d50dc83cc04e..05652535d4ba 100644 --- a/.github/workflows/terminal.yml +++ b/.github/workflows/terminal.yml @@ -80,7 +80,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/update_cli_permissions.yml b/.github/workflows/update_cli_permissions.yml index 83ead730ad00..0c83e9a43d9d 100644 --- a/.github/workflows/update_cli_permissions.yml +++ b/.github/workflows/update_cli_permissions.yml @@ -86,7 +86,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/update_contributors.yml b/.github/workflows/update_contributors.yml index 7e99d2c07ced..da79bbc6ec17 100644 --- a/.github/workflows/update_contributors.yml +++ b/.github/workflows/update_contributors.yml @@ -93,7 +93,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/update_error_databases.yml b/.github/workflows/update_error_databases.yml index a85d3e7a75d7..92ed022d03aa 100644 --- a/.github/workflows/update_error_databases.yml +++ b/.github/workflows/update_error_databases.yml @@ -147,7 +147,7 @@ jobs: - name: 'Import GPG key to sign commits' if: steps.check_changes.outputs.has_changes == 'true' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/update_math_scaffold_databases.yml b/.github/workflows/update_math_scaffold_databases.yml index 539ae4f7cbc1..181eea992482 100644 --- a/.github/workflows/update_math_scaffold_databases.yml +++ b/.github/workflows/update_math_scaffold_databases.yml @@ -112,7 +112,7 @@ jobs: - name: 'Import GPG key to sign commits' if: steps.check_changes.outputs.has_changes == 'true' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/update_package_meta_data.yml b/.github/workflows/update_package_meta_data.yml index 0e81772b01eb..cca3b4c2ad5c 100644 --- a/.github/workflows/update_package_meta_data.yml +++ b/.github/workflows/update_package_meta_data.yml @@ -97,7 +97,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/update_pr_copyright_years.yml b/.github/workflows/update_pr_copyright_years.yml index 327340773220..16107ccf1514 100644 --- a/.github/workflows/update_pr_copyright_years.yml +++ b/.github/workflows/update_pr_copyright_years.yml @@ -128,7 +128,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/update_repl_docs.yml b/.github/workflows/update_repl_docs.yml index 5b2ca37def1f..17bd3d4df2f2 100644 --- a/.github/workflows/update_repl_docs.yml +++ b/.github/workflows/update_repl_docs.yml @@ -102,7 +102,7 @@ jobs: # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA - uses: crazy-max/ghaction-import-gpg@e89d40939c28e39f97cf32126055eeae86ba74ec # v6.3.0 + uses: crazy-max/ghaction-import-gpg@2dc316deee8e90f13e1a351ab510b4d5bc0c82cd # v7.0.0 with: gpg_private_key: ${{ secrets.STDLIB_BOT_GPG_PRIVATE_KEY }} passphrase: ${{ secrets.STDLIB_BOT_GPG_PASSPHRASE }} diff --git a/.github/workflows/windows_test_npm_install.yml b/.github/workflows/windows_test_npm_install.yml index 2b70267419ab..106a6cd8f253 100644 --- a/.github/workflows/windows_test_npm_install.yml +++ b/.github/workflows/windows_test_npm_install.yml @@ -155,7 +155,7 @@ jobs: # Install MSYS2: - name: 'Install MSYS2' # Pin action to full length commit SHA - uses: msys2/setup-msys2@4f806de0a5a7294ffabaff804b38a9b435a73bda # v2.30.0 + uses: msys2/setup-msys2@cafece8e6baf9247cf9b1bf95097b0b983cc558d # v2.31.0 with: # Set the MSYS system: msystem: MINGW64 diff --git a/docs/migration-guides/mathjs/package.json b/docs/migration-guides/mathjs/package.json index c2e382e4adb2..4d4db648f9dc 100644 --- a/docs/migration-guides/mathjs/package.json +++ b/docs/migration-guides/mathjs/package.json @@ -31,7 +31,7 @@ "url": "https://github.com/stdlib-js/stdlib/issues" }, "dependencies": { - "mathjs": "^14.7.0" + "mathjs": "^15.2.0" }, "devDependencies": {}, "engines": {}, diff --git a/etc/r/requirements.txt b/etc/r/requirements.txt index 1cbc269e46f9..2f422e21a8d0 100644 --- a/etc/r/requirements.txt +++ b/etc/r/requirements.txt @@ -1,5 +1,9 @@ +car +distr +jsonlite lintr +MASS microbenchmark -jsonlite +pracma +statmod VGAM -distr diff --git a/lib/node_modules/@stdlib/_tools/lint/pkg-json-names/test/test.lint.js b/lib/node_modules/@stdlib/_tools/lint/pkg-json-names/test/test.lint.js index 77e0346c205b..d3ab578d487b 100644 --- a/lib/node_modules/@stdlib/_tools/lint/pkg-json-names/test/test.lint.js +++ b/lib/node_modules/@stdlib/_tools/lint/pkg-json-names/test/test.lint.js @@ -25,6 +25,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); var isObjectArray = require( '@stdlib/assert/is-object-array' ); var contains = require( '@stdlib/assert/contains' ); +var lint = require( './../lib/lint.js' ); // FIXTURES // @@ -35,8 +36,6 @@ var missingNamePath = join( __dirname, 'fixtures', 'missing-name.json' ); var wrongScopePath = join( __dirname, 'fixtures', 'wrong-scope.json' ); var nameMismatchPath = join( __dirname, 'fixtures', 'name-mismatch.json' ); -var lint = require( './../lib/lint.js' ); - // TESTS // diff --git a/lib/node_modules/@stdlib/_tools/lint/pkg-json/test/fixtures/invalid.json b/lib/node_modules/@stdlib/_tools/lint/pkg-json/test/fixtures/invalid.json index a9b4f29cf8bf..4a3533ea2482 100644 --- a/lib/node_modules/@stdlib/_tools/lint/pkg-json/test/fixtures/invalid.json +++ b/lib/node_modules/@stdlib/_tools/lint/pkg-json/test/fixtures/invalid.json @@ -1,3 +1,3 @@ { - "name": "beep + "name": "beep } diff --git a/lib/node_modules/@stdlib/_tools/scaffold/math-strided-real-typed-mskunary/data/docs/types/index__d__ts.txt b/lib/node_modules/@stdlib/_tools/scaffold/math-strided-real-typed-mskunary/data/docs/types/index__d__ts.txt index 62676200b397..17c511c1ee70 100644 --- a/lib/node_modules/@stdlib/_tools/scaffold/math-strided-real-typed-mskunary/data/docs/types/index__d__ts.txt +++ b/lib/node_modules/@stdlib/_tools/scaffold/math-strided-real-typed-mskunary/data/docs/types/index__d__ts.txt @@ -35,8 +35,8 @@ interface Routine { * @returns `y` * * @example - * var {{TYPED_ARRAY_CTOR}} = require( `@stdlib/array/{{TYPED_ARRAY_DTYPE}}` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var {{TYPED_ARRAY_CTOR}} = require( '@stdlib/array/{{TYPED_ARRAY_DTYPE}}' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var x = new {{TYPED_ARRAY_CTOR}}( [ {{X_VALUES_LEN_5}} ] ); * var m = new Uint8Array( [ {{MASK_VALUES_LEN_5}} ] ); @@ -63,8 +63,8 @@ interface Routine { * @returns `y` * * @example - * var {{TYPED_ARRAY_CTOR}} = require( `@stdlib/array/{{TYPED_ARRAY_DTYPE}}` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var {{TYPED_ARRAY_CTOR}} = require( '@stdlib/array/{{TYPED_ARRAY_DTYPE}}' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var x = new {{TYPED_ARRAY_CTOR}}( [ {{X_VALUES_LEN_5}} ] ); * var m = new Uint8Array( [ {{MASK_VALUES_LEN_5}} ] ); @@ -89,8 +89,8 @@ interface Routine { * @returns `y` * * @example -* var {{TYPED_ARRAY_CTOR}} = require( `@stdlib/array/{{TYPED_ARRAY_DTYPE}}` ); -* var Uint8Array = require( `@stdlib/array/uint8` ); +* var {{TYPED_ARRAY_CTOR}} = require( '@stdlib/array/{{TYPED_ARRAY_DTYPE}}' ); +* var Uint8Array = require( '@stdlib/array/uint8' ); * * var x = new {{TYPED_ARRAY_CTOR}}( [ {{X_VALUES_LEN_5}} ] ); * var m = new Uint8Array( [ {{MASK_VALUES_LEN_5}} ] ); @@ -100,8 +100,8 @@ interface Routine { * // y => <{{TYPED_ARRAY_CTOR}}>[ {{EXPECTED_LEN_5}} ] * * @example -* var {{TYPED_ARRAY_CTOR}} = require( `@stdlib/array/{{TYPED_ARRAY_DTYPE}}` ); -* var Uint8Array = require( `@stdlib/array/uint8` ); +* var {{TYPED_ARRAY_CTOR}} = require( '@stdlib/array/{{TYPED_ARRAY_DTYPE}}' ); +* var Uint8Array = require( '@stdlib/array/uint8' ); * * var x = new {{TYPED_ARRAY_CTOR}}( [ {{X_VALUES_LEN_5}} ] ); * var m = new Uint8Array( [ {{MASK_VALUES_LEN_5}} ] ); diff --git a/lib/node_modules/@stdlib/_tools/scaffold/math-strided-real-typed-unary-by/data/docs/types/index__d__ts.txt b/lib/node_modules/@stdlib/_tools/scaffold/math-strided-real-typed-unary-by/data/docs/types/index__d__ts.txt index 77c3920bd1d8..ca95875549a8 100644 --- a/lib/node_modules/@stdlib/_tools/scaffold/math-strided-real-typed-unary-by/data/docs/types/index__d__ts.txt +++ b/lib/node_modules/@stdlib/_tools/scaffold/math-strided-real-typed-unary-by/data/docs/types/index__d__ts.txt @@ -91,7 +91,7 @@ interface Routine { * @returns destination array * * @example - * var {{TYPED_ARRAY_CTOR}} = require( `@stdlib/array/{{TYPED_ARRAY_DTYPE}}` ); + * var {{TYPED_ARRAY_CTOR}} = require( '@stdlib/array/{{TYPED_ARRAY_DTYPE}}' ); * * function accessor( v ) { * return v; @@ -120,7 +120,7 @@ interface Routine { * @returns destination array * * @example - * var {{TYPED_ARRAY_CTOR}} = require( `@stdlib/array/{{TYPED_ARRAY_DTYPE}}` ); + * var {{TYPED_ARRAY_CTOR}} = require( '@stdlib/array/{{TYPED_ARRAY_DTYPE}}' ); * * function accessor( v ) { * return v; @@ -148,7 +148,7 @@ interface Routine { * @returns destination array * * @example -* var {{TYPED_ARRAY_CTOR}} = require( `@stdlib/array/{{TYPED_ARRAY_DTYPE}}` ); +* var {{TYPED_ARRAY_CTOR}} = require( '@stdlib/array/{{TYPED_ARRAY_DTYPE}}' ); * * function accessor( v ) { * return v; @@ -161,7 +161,7 @@ interface Routine { * // out => <{{TYPED_ARRAY_CTOR}}>[ {{EXPECTED_LEN_5}} ] * * @example -* var {{TYPED_ARRAY_CTOR}} = require( `@stdlib/array/{{TYPED_ARRAY_DTYPE}}` ); +* var {{TYPED_ARRAY_CTOR}} = require( '@stdlib/array/{{TYPED_ARRAY_DTYPE}}' ); * * function accessor( v ) { * return v; diff --git a/lib/node_modules/@stdlib/_tools/scaffold/math-strided-real-typed-unary/data/docs/types/index__d__ts.txt b/lib/node_modules/@stdlib/_tools/scaffold/math-strided-real-typed-unary/data/docs/types/index__d__ts.txt index 381379d8bf7b..eda20e169bb9 100644 --- a/lib/node_modules/@stdlib/_tools/scaffold/math-strided-real-typed-unary/data/docs/types/index__d__ts.txt +++ b/lib/node_modules/@stdlib/_tools/scaffold/math-strided-real-typed-unary/data/docs/types/index__d__ts.txt @@ -33,7 +33,7 @@ interface Routine { * @returns `y` * * @example - * var {{TYPED_ARRAY_CTOR}} = require( `@stdlib/array/{{TYPED_ARRAY_DTYPE}}` ); + * var {{TYPED_ARRAY_CTOR}} = require( '@stdlib/array/{{TYPED_ARRAY_DTYPE}}' ); * * var x = new {{TYPED_ARRAY_CTOR}}( [ {{X_VALUES_LEN_5}} ] ); * var y = new {{TYPED_ARRAY_CTOR}}( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); @@ -56,7 +56,7 @@ interface Routine { * @returns `y` * * @example - * var {{TYPED_ARRAY_CTOR}} = require( `@stdlib/array/{{TYPED_ARRAY_DTYPE}}` ); + * var {{TYPED_ARRAY_CTOR}} = require( '@stdlib/array/{{TYPED_ARRAY_DTYPE}}' ); * * var x = new {{TYPED_ARRAY_CTOR}}( [ {{X_VALUES_LEN_5}} ] ); * var y = new {{TYPED_ARRAY_CTOR}}( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); @@ -78,7 +78,7 @@ interface Routine { * @returns `y` * * @example -* var {{TYPED_ARRAY_CTOR}} = require( `@stdlib/array/{{TYPED_ARRAY_DTYPE}}` ); +* var {{TYPED_ARRAY_CTOR}} = require( '@stdlib/array/{{TYPED_ARRAY_DTYPE}}' ); * * var x = new {{TYPED_ARRAY_CTOR}}( [ {{X_VALUES_LEN_5}} ] ); * var y = new {{TYPED_ARRAY_CTOR}}( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); @@ -87,7 +87,7 @@ interface Routine { * // y => <{{TYPED_ARRAY_CTOR}}>[ {{EXPECTED_LEN_5}} ] * * @example -* var {{TYPED_ARRAY_CTOR}} = require( `@stdlib/array/{{TYPED_ARRAY_DTYPE}}` ); +* var {{TYPED_ARRAY_CTOR}} = require( '@stdlib/array/{{TYPED_ARRAY_DTYPE}}' ); * * var x = new {{TYPED_ARRAY_CTOR}}( [ {{X_VALUES_LEN_5}} ] ); * var y = new {{TYPED_ARRAY_CTOR}}( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); diff --git a/lib/node_modules/@stdlib/_tools/scaffold/math-strided-unary/data/docs/types/index__d__ts.txt b/lib/node_modules/@stdlib/_tools/scaffold/math-strided-unary/data/docs/types/index__d__ts.txt index 297782ef3408..18d0acdbb530 100644 --- a/lib/node_modules/@stdlib/_tools/scaffold/math-strided-unary/data/docs/types/index__d__ts.txt +++ b/lib/node_modules/@stdlib/_tools/scaffold/math-strided-unary/data/docs/types/index__d__ts.txt @@ -42,7 +42,7 @@ interface Routine { * @returns `y` * * @example - * var {{TYPED_ARRAY_CTOR}} = require( `@stdlib/array/{{TYPED_ARRAY_DTYPE}}` ); + * var {{TYPED_ARRAY_CTOR}} = require( '@stdlib/array/{{TYPED_ARRAY_DTYPE}}' ); * * var x = new {{TYPED_ARRAY_CTOR}}( [ {{X_VALUES_LEN_5}} ] ); * var y = new {{TYPED_ARRAY_CTOR}}( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); @@ -70,7 +70,7 @@ interface Routine { * @returns `y` * * @example - * var {{TYPED_ARRAY_CTOR}} = require( `@stdlib/array/{{TYPED_ARRAY_DTYPE}}` ); + * var {{TYPED_ARRAY_CTOR}} = require( '@stdlib/array/{{TYPED_ARRAY_DTYPE}}' ); * * var x = new {{TYPED_ARRAY_CTOR}}( [ {{X_VALUES_LEN_5}}] ); * var y = new {{TYPED_ARRAY_CTOR}}( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); @@ -97,7 +97,7 @@ interface Routine { * @returns `y` * * @example -* var {{TYPED_ARRAY_CTOR}} = require( `@stdlib/array/{{TYPED_ARRAY_DTYPE}}` ); +* var {{TYPED_ARRAY_CTOR}} = require( '@stdlib/array/{{TYPED_ARRAY_DTYPE}}' ); * * var x = new {{TYPED_ARRAY_CTOR}}( [ {{X_VALUES_LEN_5}}] ); * var y = new {{TYPED_ARRAY_CTOR}}( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); @@ -106,7 +106,7 @@ interface Routine { * // y => <{{TYPED_ARRAY_CTOR}}>[ {{EXPECTED_LEN_5}} ] * * @example -* var {{TYPED_ARRAY_CTOR}} = require( `@stdlib/array/{{TYPED_ARRAY_DTYPE}}` ); +* var {{TYPED_ARRAY_CTOR}} = require( '@stdlib/array/{{TYPED_ARRAY_DTYPE}}' ); * * var x = new {{TYPED_ARRAY_CTOR}}( [ {{X_VALUES_LEN_5}}] ); * var y = new {{TYPED_ARRAY_CTOR}}( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); diff --git a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/benchmark/benchmark.accessors.length.js b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/benchmark/benchmark.accessors.length.js index 7ac5504885b3..d7117ede8bc5 100644 --- a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/benchmark/benchmark.accessors.length.js +++ b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/benchmark/benchmark.accessors.length.js @@ -91,7 +91,7 @@ function main() { len = pow( 10, i ); f = createBenchmark( len ); - bench( format( '%s::accessors:len=%s', pkg, len ), f ); + bench( format( '%s::accessors:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/benchmark/benchmark.length.js index 083f916c8a22..cc63b070042e 100644 --- a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/benchmark/benchmark.length.js @@ -90,7 +90,7 @@ function main() { len = pow( 10, i ); f = createBenchmark( len ); - bench( format( '%s:len=%s', pkg, len ), f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/join/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/join/benchmark/benchmark.length.js index 4b759371223d..77973c2fdd6d 100644 --- a/lib/node_modules/@stdlib/array/base/join/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/base/join/benchmark/benchmark.length.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var ones = require( '@stdlib/array/base/ones' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var join = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/last-index-of-same-value/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/last-index-of-same-value/benchmark/benchmark.length.js index 731272fc3738..a2d7428b62fd 100644 --- a/lib/node_modules/@stdlib/array/base/last-index-of-same-value/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/base/last-index-of-same-value/benchmark/benchmark.length.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var zeroTo = require( '@stdlib/array/base/zero-to' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var lastIndexOfSameValue = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/last-index-of/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/last-index-of/benchmark/benchmark.length.js index 91a1e314f8ea..fa6ceb26745d 100644 --- a/lib/node_modules/@stdlib/array/base/last-index-of/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/base/last-index-of/benchmark/benchmark.length.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var zeroTo = require( '@stdlib/array/base/zero-to' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var lastIndexOf = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/last/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/last/benchmark/benchmark.js index 3d18c8efd26d..127dc23bcd4a 100644 --- a/lib/node_modules/@stdlib/array/base/last/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/last/benchmark/benchmark.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var pow = require( '@stdlib/math/base/special/pow' ); var filledBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var last = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/linspace/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/linspace/benchmark/benchmark.length.js index f9120de2205b..62a766287b7d 100644 --- a/lib/node_modules/@stdlib/array/base/linspace/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/base/linspace/benchmark/benchmark.length.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArray = require( '@stdlib/assert/is-array' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -86,7 +87,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/linspace2d/benchmark/benchmark.size.js b/lib/node_modules/@stdlib/array/base/linspace2d/benchmark/benchmark.size.js index 997c4ac02238..c2c3b07828f9 100644 --- a/lib/node_modules/@stdlib/array/base/linspace2d/benchmark/benchmark.size.js +++ b/lib/node_modules/@stdlib/array/base/linspace2d/benchmark/benchmark.size.js @@ -25,6 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isArrayArray = require( '@stdlib/assert/is-array-array' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace2d = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = floor( sqrt( pow( 10, i ) ) ); f = createBenchmark( N ); - bench( pkg+'::square_matrix:size='+(N*N), f ); + bench( format( '%s::square_matrix:size=%d', pkg, N*N ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/logspace/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/logspace/benchmark/benchmark.length.js index b157c093b9d7..7e2f47cc5439 100644 --- a/lib/node_modules/@stdlib/array/base/logspace/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/base/logspace/benchmark/benchmark.length.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArray = require( '@stdlib/assert/is-array' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var logspace = require( './../lib' ); @@ -86,7 +87,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/map/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/array/base/map/benchmark/benchmark.assign.js index ad4b356656fa..84ce624f1c2f 100644 --- a/lib/node_modules/@stdlib/array/base/map/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/array/base/map/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var identity = require( '@stdlib/number/float64/base/identity' ); var zeros = require( '@stdlib/array/base/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var map = require( './../lib' ).assign; @@ -99,7 +100,7 @@ function main() { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/map/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/map/benchmark/benchmark.js index c57bee8baba3..146c34de14a7 100644 --- a/lib/node_modules/@stdlib/array/base/map/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/map/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var identity = require( '@stdlib/number/float64/base/identity' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var map = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/map2d/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/array/base/map2d/benchmark/benchmark.assign.js index c2064dc5847c..42bdf76b76c8 100644 --- a/lib/node_modules/@stdlib/array/base/map2d/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/array/base/map2d/benchmark/benchmark.assign.js @@ -29,6 +29,7 @@ var identity = require( '@stdlib/number/float64/base/identity' ); var filled2dBy = require( '@stdlib/array/base/filled2d-by' ); var zeros2d = require( '@stdlib/array/base/zeros2d' ); var numel = require( '@stdlib/ndarray/base/numel' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var map2d = require( './../lib' ).assign; @@ -107,7 +108,7 @@ function main() { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); sh = [ N, N ]; f = createBenchmark( sh ); - bench( pkg+'::square_matrix:assign:size='+numel( sh ), f ); + bench( format( '%s::square_matrix:assign:size=%d', pkg, numel( sh ) ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/map2d/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/map2d/benchmark/benchmark.js index 45307f0ae0a9..51b51b9c551e 100644 --- a/lib/node_modules/@stdlib/array/base/map2d/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/map2d/benchmark/benchmark.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var identity = require( '@stdlib/number/float64/base/identity' ); var filled2dBy = require( '@stdlib/array/base/filled2d-by' ); var numel = require( '@stdlib/ndarray/base/numel' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var map2d = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); sh = [ N, N ]; f = createBenchmark( sh ); - bench( pkg+'::square_matrix:size='+numel( sh ), f ); + bench( format( '%s::square_matrix:size=%d', pkg, numel( sh ) ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/map3d/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/array/base/map3d/benchmark/benchmark.assign.js index 93227fde0bc7..c087291143a1 100644 --- a/lib/node_modules/@stdlib/array/base/map3d/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/array/base/map3d/benchmark/benchmark.assign.js @@ -29,6 +29,7 @@ var identity = require( '@stdlib/number/float64/base/identity' ); var filled3dBy = require( '@stdlib/array/base/filled3d-by' ); var zeros3d = require( '@stdlib/array/base/zeros3d' ); var numel = require( '@stdlib/ndarray/base/numel' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var map3d = require( './../lib' ).assign; @@ -110,7 +111,7 @@ function main() { N = floor( pow( pow( 10, i ), 1.0/3.0 ) ); sh = [ N, N, N ]; f = createBenchmark( sh ); - bench( pkg+'::equidimensional:assign:size='+numel( sh ), f ); + bench( format( '%s::equidimensional:assign:size=%d', pkg, numel( sh ) ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/map3d/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/map3d/benchmark/benchmark.js index 7bc687669dbd..f44c277c646b 100644 --- a/lib/node_modules/@stdlib/array/base/map3d/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/map3d/benchmark/benchmark.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var identity = require( '@stdlib/number/float64/base/identity' ); var filled3dBy = require( '@stdlib/array/base/filled3d-by' ); var numel = require( '@stdlib/ndarray/base/numel' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var map3d = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { N = floor( pow( pow( 10, i ), 1.0/3.0 ) ); sh = [ N, N, N ]; f = createBenchmark( sh ); - bench( pkg+'::equidimensional:size='+numel( sh ), f ); + bench( format( '%s::equidimensional:size=%d', pkg, numel( sh ) ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/map4d/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/array/base/map4d/benchmark/benchmark.assign.js index a6d5c570cb2d..af2996603f1e 100644 --- a/lib/node_modules/@stdlib/array/base/map4d/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/array/base/map4d/benchmark/benchmark.assign.js @@ -29,6 +29,7 @@ var identity = require( '@stdlib/number/float64/base/identity' ); var filled4dBy = require( '@stdlib/array/base/filled4d-by' ); var zeros4d = require( '@stdlib/array/base/zeros4d' ); var numel = require( '@stdlib/ndarray/base/numel' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var map4d = require( './../lib' ).assign; @@ -113,7 +114,7 @@ function main() { N = floor( pow( pow( 10, i ), 1.0/4.0 ) ); sh = [ N, N, N, N ]; f = createBenchmark( sh ); - bench( pkg+'::equidimensional:assign:size='+numel( sh ), f ); + bench( format( '%s::equidimensional:assign:size=%d', pkg, numel( sh ) ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/map4d/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/map4d/benchmark/benchmark.js index 16aa08344732..d75b86ecb204 100644 --- a/lib/node_modules/@stdlib/array/base/map4d/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/map4d/benchmark/benchmark.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var identity = require( '@stdlib/number/float64/base/identity' ); var filled4dBy = require( '@stdlib/array/base/filled4d-by' ); var numel = require( '@stdlib/ndarray/base/numel' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var map4d = require( './../lib' ); @@ -107,7 +108,7 @@ function main() { N = floor( pow( pow( 10, i ), 1.0/4.0 ) ); sh = [ N, N, N, N ]; f = createBenchmark( sh ); - bench( pkg+'::equidimensional:size='+numel( sh ), f ); + bench( format( '%s::equidimensional:size=%d', pkg, numel( sh ) ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/map5d/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/array/base/map5d/benchmark/benchmark.assign.js index 915590ae9657..a9393d7d0ac4 100644 --- a/lib/node_modules/@stdlib/array/base/map5d/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/array/base/map5d/benchmark/benchmark.assign.js @@ -29,6 +29,7 @@ var identity = require( '@stdlib/number/float64/base/identity' ); var filled5dBy = require( '@stdlib/array/base/filled5d-by' ); var zeros5d = require( '@stdlib/array/base/zeros5d' ); var numel = require( '@stdlib/ndarray/base/numel' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var map5d = require( './../lib' ).assign; @@ -116,7 +117,7 @@ function main() { N = floor( pow( pow( 10, i ), 1.0/5.0 ) ); sh = [ N, N, N, N, N ]; f = createBenchmark( sh ); - bench( pkg+'::equidimensional:assign:size='+numel( sh ), f ); + bench( format( '%s::equidimensional:assign:size=%d', pkg, numel( sh ) ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/map5d/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/map5d/benchmark/benchmark.js index 64c86d57176a..39c4d29b2620 100644 --- a/lib/node_modules/@stdlib/array/base/map5d/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/map5d/benchmark/benchmark.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var identity = require( '@stdlib/number/float64/base/identity' ); var filled5dBy = require( '@stdlib/array/base/filled5d-by' ); var numel = require( '@stdlib/ndarray/base/numel' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var map5d = require( './../lib' ); @@ -110,7 +111,7 @@ function main() { N = floor( pow( pow( 10, i ), 1.0/5.0 ) ); sh = [ N, N, N, N, N ]; f = createBenchmark( sh ); - bench( pkg+'::equidimensional:size='+numel( sh ), f ); + bench( format( '%s::equidimensional:size=%d', pkg, numel( sh ) ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskbinary2d/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskbinary2d/benchmark/benchmark.js index fa8fa7ad9051..e13f7a85b6a0 100644 --- a/lib/node_modules/@stdlib/array/base/mskbinary2d/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/mskbinary2d/benchmark/benchmark.js @@ -30,6 +30,7 @@ var add = require( '@stdlib/number/float64/base/add' ); var filled2dBy = require( '@stdlib/array/base/filled2d-by' ); var zeros2d = require( '@stdlib/array/base/zeros2d' ); var numel = require( '@stdlib/ndarray/base/numel' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskbinary2d = require( './../lib' ); @@ -114,7 +115,7 @@ function main() { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); sh = [ N, N ]; f = createBenchmark( sh ); - bench( pkg+'::square_matrix:size='+numel( sh ), f ); + bench( format( '%s::square_matrix:size=%d', pkg, numel( sh ) ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskbinary3d/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskbinary3d/benchmark/benchmark.js index 6557280b10cb..3fbe224a09ec 100644 --- a/lib/node_modules/@stdlib/array/base/mskbinary3d/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/mskbinary3d/benchmark/benchmark.js @@ -30,6 +30,7 @@ var add = require( '@stdlib/number/float64/base/add' ); var filled3dBy = require( '@stdlib/array/base/filled3d-by' ); var zeros3d = require( '@stdlib/array/base/zeros3d' ); var numel = require( '@stdlib/ndarray/base/numel' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskbinary3d = require( './../lib' ); @@ -117,7 +118,7 @@ function main() { N = floor( pow( pow( 10, i ), 1.0/3.0 ) ); sh = [ N, N, N ]; f = createBenchmark( sh ); - bench( pkg+'::equidimensional:size='+numel( sh ), f ); + bench( format( '%s::equidimensional:size=%d', pkg, numel( sh ) ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskbinary4d/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskbinary4d/benchmark/benchmark.js index 3cd35efb3df7..5c4498f96ade 100644 --- a/lib/node_modules/@stdlib/array/base/mskbinary4d/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/mskbinary4d/benchmark/benchmark.js @@ -30,6 +30,7 @@ var add = require( '@stdlib/number/float64/base/add' ); var filled4dBy = require( '@stdlib/array/base/filled4d-by' ); var zeros4d = require( '@stdlib/array/base/zeros4d' ); var numel = require( '@stdlib/ndarray/base/numel' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskbinary4d = require( './../lib' ); @@ -120,7 +121,7 @@ function main() { N = floor( pow( pow( 10, i ), 1.0/4.0 ) ); sh = [ N, N, N, N ]; f = createBenchmark( sh ); - bench( pkg+'::equidimensional:size='+numel( sh ), f ); + bench( format( '%s::equidimensional:size=%d', pkg, numel( sh ) ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskbinary5d/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskbinary5d/benchmark/benchmark.js index b38ba45985a7..42b8336a20f3 100644 --- a/lib/node_modules/@stdlib/array/base/mskbinary5d/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/mskbinary5d/benchmark/benchmark.js @@ -30,6 +30,7 @@ var add = require( '@stdlib/number/float64/base/add' ); var filled5dBy = require( '@stdlib/array/base/filled5d-by' ); var zeros5d = require( '@stdlib/array/base/zeros5d' ); var numel = require( '@stdlib/ndarray/base/numel' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskbinary5d = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { N = floor( pow( pow( 10, i ), 1.0/5.0 ) ); sh = [ N, N, N, N, N ]; f = createBenchmark( sh ); - bench( pkg+'::equidimensional:size='+numel( sh ), f ); + bench( format( '%s::equidimensional:size=%d', pkg, numel( sh ) ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.assign.length.js b/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.assign.length.js index 1ce5e32f264c..075000ff01b7 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.assign.length.js +++ b/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.assign.length.js @@ -28,6 +28,7 @@ var ones = require( '@stdlib/array/ones' ); var isArray = require( '@stdlib/assert/is-array' ); var isnan = require( '@stdlib/assert/is-nan' ).isPrimitive; var identity = require( '@stdlib/utils/identity-function' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskfilterMap = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:len='+len, f ); + bench( format( '%s:assign:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.js index 86c146b031db..2067a6d086f7 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.js @@ -25,13 +25,14 @@ var isArray = require( '@stdlib/assert/is-array' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var ones = require( '@stdlib/array/base/ones' ); var identity = require( '@stdlib/utils/identity-function' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskfilterMap = require( './../lib' ); // MAIN // -bench( pkg+'::copy:len=100', function benchmark( b ) { +bench( format( '%s::copy:len=100', pkg ), function benchmark( b ) { var x; var y; var i; diff --git a/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.length.js index e095ad90d077..30314e501478 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.length.js @@ -26,6 +26,7 @@ var zeroTo = require( '@stdlib/array/base/zero-to' ); var ones = require( '@stdlib/array/base/ones' ); var isArray = require( '@stdlib/assert/is-array' ); var identity = require( '@stdlib/utils/identity-function' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskfilterMap = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskfilter/benchmark/benchmark.assign.length.js b/lib/node_modules/@stdlib/array/base/mskfilter/benchmark/benchmark.assign.length.js index 3f2fb20db1bd..9b53922339b7 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter/benchmark/benchmark.assign.length.js +++ b/lib/node_modules/@stdlib/array/base/mskfilter/benchmark/benchmark.assign.length.js @@ -27,6 +27,7 @@ var zeros = require( '@stdlib/array/zeros' ); var ones = require( '@stdlib/array/ones' ); var isArray = require( '@stdlib/assert/is-array' ); var isnan = require( '@stdlib/assert/is-nan' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskfilter = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:len='+len, f ); + bench( format( '%s:assign:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskfilter/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskfilter/benchmark/benchmark.js index 66641ff16d9e..58ac776e8eb6 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/mskfilter/benchmark/benchmark.js @@ -24,13 +24,14 @@ var bench = require( '@stdlib/bench' ); var isArray = require( '@stdlib/assert/is-array' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var ones = require( '@stdlib/array/base/ones' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskfilter = require( './../lib' ); // MAIN // -bench( pkg+'::copy:len=100', function benchmark( b ) { +bench( format( '%s::copy:len=100', pkg ), function benchmark( b ) { var x; var y; var i; diff --git a/lib/node_modules/@stdlib/array/base/mskfilter/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/mskfilter/benchmark/benchmark.length.js index f9f890632a17..9f2c5c2f1048 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/base/mskfilter/benchmark/benchmark.length.js @@ -25,6 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var ones = require( '@stdlib/array/base/ones' ); var isArray = require( '@stdlib/assert/is-array' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskfilter = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskfilter2/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskfilter2/benchmark/benchmark.js index 62a2b7786d5f..039a88592e50 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/mskfilter2/benchmark/benchmark.js @@ -24,13 +24,14 @@ var bench = require( '@stdlib/bench' ); var isArrayArray = require( '@stdlib/assert/is-array-array' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var ones = require( '@stdlib/array/base/ones' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskfilter2 = require( './../lib' ); // MAIN // -bench( pkg+'::copy:len=100', function benchmark( b ) { +bench( format( '%s::copy:len=100', pkg ), function benchmark( b ) { var x; var y; var i; diff --git a/lib/node_modules/@stdlib/array/base/mskfilter2/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/mskfilter2/benchmark/benchmark.length.js index 90a7c730cfe6..9655095b581f 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter2/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/base/mskfilter2/benchmark/benchmark.length.js @@ -25,6 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var ones = require( '@stdlib/array/base/ones' ); var isArrayArray = require( '@stdlib/assert/is-array-array' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskfilter2 = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskfiltern/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskfiltern/benchmark/benchmark.js index a2f993868ec0..b445eac6e733 100644 --- a/lib/node_modules/@stdlib/array/base/mskfiltern/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/mskfiltern/benchmark/benchmark.js @@ -24,13 +24,14 @@ var bench = require( '@stdlib/bench' ); var isArrayArray = require( '@stdlib/assert/is-array-array' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var ones = require( '@stdlib/array/base/ones' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskfiltern = require( './../lib' ); // MAIN // -bench( pkg+'::copy:num_arrays=2,len=100', function benchmark( b ) { +bench( format( '%s::copy:num_arrays=2,len=100', pkg ), function benchmark( b ) { var x; var y; var i; diff --git a/lib/node_modules/@stdlib/array/base/mskfiltern/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/mskfiltern/benchmark/benchmark.length.js index b0c53e10b5ee..f538c25e64ef 100644 --- a/lib/node_modules/@stdlib/array/base/mskfiltern/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/base/mskfiltern/benchmark/benchmark.length.js @@ -25,6 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var ones = require( '@stdlib/array/base/ones' ); var isArrayArray = require( '@stdlib/assert/is-array-array' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskfiltern = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':num_arrays=2,len='+len, f ); + bench( format( '%s:num_arrays=2,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskput/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskput/benchmark/benchmark.js index 652b5447aa2d..924f4fe91ec0 100644 --- a/lib/node_modules/@stdlib/array/base/mskput/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/mskput/benchmark/benchmark.js @@ -24,13 +24,14 @@ var bench = require( '@stdlib/bench' ); var isArray = require( '@stdlib/assert/is-array' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var zeros = require( '@stdlib/array/base/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskput = require( './../lib' ); // MAIN // -bench( pkg+'::no_broadcasting:len=100', function benchmark( b ) { +bench( format( '%s::no_broadcasting:len=100', pkg ), function benchmark( b ) { var mask; var x; var i; @@ -54,7 +55,7 @@ bench( pkg+'::no_broadcasting:len=100', function benchmark( b ) { b.end(); }); -bench( pkg+'::broadcasting:len=100', function benchmark( b ) { +bench( format( '%s::broadcasting:len=100', pkg ), function benchmark( b ) { var mask; var x; var i; diff --git a/lib/node_modules/@stdlib/array/base/mskput/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/mskput/benchmark/benchmark.length.js index ce6bba354872..a40491fd9c84 100644 --- a/lib/node_modules/@stdlib/array/base/mskput/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/base/mskput/benchmark/benchmark.length.js @@ -25,6 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var zeros = require( '@stdlib/array/base/zeros' ); var isArray = require( '@stdlib/assert/is-array' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskput = require( './../lib' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskreject-map/benchmark/benchmark.assign.length.js b/lib/node_modules/@stdlib/array/base/mskreject-map/benchmark/benchmark.assign.length.js index 70d168ed480d..fabc87b13799 100644 --- a/lib/node_modules/@stdlib/array/base/mskreject-map/benchmark/benchmark.assign.length.js +++ b/lib/node_modules/@stdlib/array/base/mskreject-map/benchmark/benchmark.assign.length.js @@ -26,6 +26,7 @@ var zeroTo = require( '@stdlib/array/base/zero-to' ); var zeros = require( '@stdlib/array/zeros' ); var isArray = require( '@stdlib/assert/is-array' ); var isnan = require( '@stdlib/assert/is-nan' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskrejectMap = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:len='+len, f ); + bench( format( '%s:assign:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskreject-map/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskreject-map/benchmark/benchmark.js index fe825af1b4db..c346fe331357 100644 --- a/lib/node_modules/@stdlib/array/base/mskreject-map/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/mskreject-map/benchmark/benchmark.js @@ -24,13 +24,14 @@ var bench = require( '@stdlib/bench' ); var isArray = require( '@stdlib/assert/is-array' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var zeros = require( '@stdlib/array/base/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskrejectMap = require( './../lib' ); // MAIN // -bench( pkg+'::copy:len=100', function benchmark( b ) { +bench( format( '%s::copy:len=100', pkg ), function benchmark( b ) { var x; var y; var i; diff --git a/lib/node_modules/@stdlib/array/base/mskreject-map/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/mskreject-map/benchmark/benchmark.length.js index b7ae1eb1e116..c42fa9e1476d 100644 --- a/lib/node_modules/@stdlib/array/base/mskreject-map/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/base/mskreject-map/benchmark/benchmark.length.js @@ -25,6 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var zeros = require( '@stdlib/array/base/zeros' ); var isArray = require( '@stdlib/assert/is-array' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskrejectMap = require( './../lib' ); @@ -92,7 +93,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskreject/benchmark/benchmark.assign.length.js b/lib/node_modules/@stdlib/array/base/mskreject/benchmark/benchmark.assign.length.js index 0d4aa67626e4..a2d118616019 100644 --- a/lib/node_modules/@stdlib/array/base/mskreject/benchmark/benchmark.assign.length.js +++ b/lib/node_modules/@stdlib/array/base/mskreject/benchmark/benchmark.assign.length.js @@ -26,6 +26,7 @@ var zeroTo = require( '@stdlib/array/base/zero-to' ); var zeros = require( '@stdlib/array/zeros' ); var isArray = require( '@stdlib/assert/is-array' ); var isnan = require( '@stdlib/assert/is-nan' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskreject = require( './../lib' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:len='+len, f ); + bench( format( '%s:assign:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskreject/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskreject/benchmark/benchmark.js index ba6fbf639468..57f9374186f9 100644 --- a/lib/node_modules/@stdlib/array/base/mskreject/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/mskreject/benchmark/benchmark.js @@ -24,13 +24,14 @@ var bench = require( '@stdlib/bench' ); var isArray = require( '@stdlib/assert/is-array' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var zeros = require( '@stdlib/array/base/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskreject = require( './../lib' ); // MAIN // -bench( pkg+'::copy:len=100', function benchmark( b ) { +bench( format( '%s::copy:len=100', pkg ), function benchmark( b ) { var x; var y; var i; diff --git a/lib/node_modules/@stdlib/array/base/mskreject/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/mskreject/benchmark/benchmark.length.js index df920c3830ac..6995228dbd2d 100644 --- a/lib/node_modules/@stdlib/array/base/mskreject/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/base/mskreject/benchmark/benchmark.length.js @@ -25,6 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var zeros = require( '@stdlib/array/base/zeros' ); var isArray = require( '@stdlib/assert/is-array' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskreject = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskunary2d/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskunary2d/benchmark/benchmark.js index a1cb6e2f292b..8dd2c26b2e81 100644 --- a/lib/node_modules/@stdlib/array/base/mskunary2d/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/mskunary2d/benchmark/benchmark.js @@ -30,6 +30,7 @@ var identity = require( '@stdlib/number/float64/base/identity' ); var filled2dBy = require( '@stdlib/array/base/filled2d-by' ); var zeros2d = require( '@stdlib/array/base/zeros2d' ); var numel = require( '@stdlib/ndarray/base/numel' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskunary2d = require( './../lib' ); @@ -112,7 +113,7 @@ function main() { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); sh = [ N, N ]; f = createBenchmark( sh ); - bench( pkg+'::square_matrix:size='+numel( sh ), f ); + bench( format( '%s::square_matrix:size=%d', pkg, numel( sh ) ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskunary3d/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskunary3d/benchmark/benchmark.js index 7cd954b4c01e..e7374aa85399 100644 --- a/lib/node_modules/@stdlib/array/base/mskunary3d/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/mskunary3d/benchmark/benchmark.js @@ -30,6 +30,7 @@ var identity = require( '@stdlib/number/float64/base/identity' ); var filled3dBy = require( '@stdlib/array/base/filled3d-by' ); var zeros3d = require( '@stdlib/array/base/zeros3d' ); var numel = require( '@stdlib/ndarray/base/numel' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskunary3d = require( './../lib' ); @@ -115,7 +116,7 @@ function main() { N = floor( pow( pow( 10, i ), 1.0/3.0 ) ); sh = [ N, N, N ]; f = createBenchmark( sh ); - bench( pkg+'::equidimensional:size='+numel( sh ), f ); + bench( format( '%s::equidimensional:size=%d', pkg, numel( sh ) ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskunary4d/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskunary4d/benchmark/benchmark.js index 92006f49974f..cef401c7ef41 100644 --- a/lib/node_modules/@stdlib/array/base/mskunary4d/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/mskunary4d/benchmark/benchmark.js @@ -30,6 +30,7 @@ var identity = require( '@stdlib/number/float64/base/identity' ); var filled4dBy = require( '@stdlib/array/base/filled4d-by' ); var zeros4d = require( '@stdlib/array/base/zeros4d' ); var numel = require( '@stdlib/ndarray/base/numel' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskunary4d = require( './../lib' ); @@ -118,7 +119,7 @@ function main() { N = floor( pow( pow( 10, i ), 1.0/4.0 ) ); sh = [ N, N, N, N ]; f = createBenchmark( sh ); - bench( pkg+'::equidimensional:size='+numel( sh ), f ); + bench( format( '%s::equidimensional:size=%d', pkg, numel( sh ) ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/mskunary5d/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskunary5d/benchmark/benchmark.js index 003f89f0286e..ec9a2b1d0aef 100644 --- a/lib/node_modules/@stdlib/array/base/mskunary5d/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/mskunary5d/benchmark/benchmark.js @@ -30,6 +30,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var filled5dBy = require( '@stdlib/array/base/filled5d-by' ); var zeros5d = require( '@stdlib/array/base/zeros5d' ); var numel = require( '@stdlib/ndarray/base/numel' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskunary5d = require( './../lib' ); @@ -121,7 +122,7 @@ function main() { N = floor( pow( pow( 10, i ), 1.0/5.0 ) ); sh = [ N, N, N, N, N ]; f = createBenchmark( sh ); - bench( pkg+'::equidimensional:size='+numel( sh ), f ); + bench( format( '%s::equidimensional:size=%d', pkg, numel( sh ) ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/n-cartesian-product/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/n-cartesian-product/benchmark/benchmark.js index c1ed87f27c18..87b22be8b24f 100644 --- a/lib/node_modules/@stdlib/array/base/n-cartesian-product/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/n-cartesian-product/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var isArrayArray = require( '@stdlib/assert/is-array-array' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nCartesianProduct = require( './../lib' ); // MAIN // -bench( pkg+':narrays=2,len=100', function benchmark( b ) { +bench( format( '%s:narrays=2,len=100', pkg ), function benchmark( b ) { var x; var i; var v; @@ -51,7 +52,7 @@ bench( pkg+':narrays=2,len=100', function benchmark( b ) { b.end(); }); -bench( pkg+':narrays=3,len=100', function benchmark( b ) { +bench( format( '%s:narrays=3,len=100', pkg ), function benchmark( b ) { var x; var y; var i; @@ -75,7 +76,7 @@ bench( pkg+':narrays=3,len=100', function benchmark( b ) { b.end(); }); -bench( pkg+':narrays=4,len=100', function benchmark( b ) { +bench( format( '%s:narrays=4,len=100', pkg ), function benchmark( b ) { var x; var y; var i; @@ -99,7 +100,7 @@ bench( pkg+':narrays=4,len=100', function benchmark( b ) { b.end(); }); -bench( pkg+':narrays=5,len=100', function benchmark( b ) { +bench( format( '%s:narrays=5,len=100', pkg ), function benchmark( b ) { var x; var y; var i; @@ -123,7 +124,7 @@ bench( pkg+':narrays=5,len=100', function benchmark( b ) { b.end(); }); -bench( pkg+':narrays=6,len=100', function benchmark( b ) { +bench( format( '%s:narrays=6,len=100', pkg ), function benchmark( b ) { var x; var y; var i; @@ -147,7 +148,7 @@ bench( pkg+':narrays=6,len=100', function benchmark( b ) { b.end(); }); -bench( pkg+':narrays=7,len=100', function benchmark( b ) { +bench( format( '%s:narrays=7,len=100', pkg ), function benchmark( b ) { var x; var y; var i; @@ -171,7 +172,7 @@ bench( pkg+':narrays=7,len=100', function benchmark( b ) { b.end(); }); -bench( pkg+':narrays=8,len=100', function benchmark( b ) { +bench( format( '%s:narrays=8,len=100', pkg ), function benchmark( b ) { var x; var y; var i; @@ -195,7 +196,7 @@ bench( pkg+':narrays=8,len=100', function benchmark( b ) { b.end(); }); -bench( pkg+':narrays=9,len=100', function benchmark( b ) { +bench( format( '%s:narrays=9,len=100', pkg ), function benchmark( b ) { var x; var y; var i; @@ -219,7 +220,7 @@ bench( pkg+':narrays=9,len=100', function benchmark( b ) { b.end(); }); -bench( pkg+':narrays=10,len=100', function benchmark( b ) { +bench( format( '%s:narrays=10,len=100', pkg ), function benchmark( b ) { var x; var y; var i; diff --git a/lib/node_modules/@stdlib/array/base/n-cartesian-product/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/n-cartesian-product/benchmark/benchmark.length.js index d41f981bc10a..3a4beeb2de36 100644 --- a/lib/node_modules/@stdlib/array/base/n-cartesian-product/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/base/n-cartesian-product/benchmark/benchmark.length.js @@ -25,6 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledBy = require( '@stdlib/array/base/filled-by' ); var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isArrayArray = require( '@stdlib/assert/is-array-array' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nCartesianProduct = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':narrays=3,len='+len, f ); + bench( format( '%s:narrays=3,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/base/nested2objects/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/nested2objects/benchmark/benchmark.js index be401a1f16a1..29821e2999a9 100644 --- a/lib/node_modules/@stdlib/array/base/nested2objects/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/nested2objects/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var isArray = require( '@stdlib/assert/is-array' ); var filled2d = require( '@stdlib/array/base/filled2d' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nested2objects = require( './../lib' ); // MAIN // -bench( pkg+':size=100', function benchmark( b ) { +bench( format( '%s:size=100', pkg ), function benchmark( b ) { var fields; var x; var i; diff --git a/lib/node_modules/@stdlib/array/base/nested2views/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/nested2views/benchmark/benchmark.js index 8fbd66c176c2..92a4f60e9259 100644 --- a/lib/node_modules/@stdlib/array/base/nested2views/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/nested2views/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var isArray = require( '@stdlib/assert/is-array' ); var filled2d = require( '@stdlib/array/base/filled2d' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nested2views = require( './../lib' ); // MAIN // -bench( pkg+':size=100', function benchmark( b ) { +bench( format( '%s:size=100', pkg ), function benchmark( b ) { var fields; var x; var i; diff --git a/lib/node_modules/@stdlib/array/complex128/README.md b/lib/node_modules/@stdlib/array/complex128/README.md index 2f1c930424d0..f700318485c0 100644 --- a/lib/node_modules/@stdlib/array/complex128/README.md +++ b/lib/node_modules/@stdlib/array/complex128/README.md @@ -282,8 +282,6 @@ The iterator returned by an iterable must return either a complex number or an a ```javascript var ITERATOR_SYMBOL = require( '@stdlib/symbol/iterator' ); var Float64Array = require( '@stdlib/array/float64' ); -var real = require( '@stdlib/complex/float64/real' ); -var imag = require( '@stdlib/complex/float64/imag' ); var iter; var arr; @@ -331,13 +329,7 @@ if ( ITERATOR_SYMBOL === null ) { // returns 2 z = arr.get( 0 ); - // returns - - re = real( z ); - // returns 1.0 - - im = imag( z ); - // returns -1.0 + // returns [ 1.0, -1.0 ] } ``` @@ -363,13 +355,7 @@ var len = arr.length; // returns 1 var z = arr.get( 0 ); -// returns - -var re = real( z ); -// returns 2.0 - -var im = imag( z ); -// returns -2.0 +// returns [ 2.0, -2.0 ] ``` or an array-like object containing real and imaginary components @@ -403,22 +389,10 @@ var len = arr.length; // returns 2 var z = arr.get( 0 ); -// returns - -var re = real( z ); -// returns 2.0 - -var im = imag( z ); -// returns -2.0 +// returns [ 2.0, -2.0 ] z = arr.get( 1 ); -// returns - -re = real( z ); -// returns 4.0 - -im = imag( z ); -// returns -4.0 +// returns [ 4.0, -4.0 ] ``` If `src` is an array-like object containing interleaved real and imaginary components, the callback is invoked for each component and should return the transformed component value. @@ -426,8 +400,6 @@ If `src` is an array-like object containing interleaved real and imaginary compo ```javascript var Float64Array = require( '@stdlib/array/float64' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); -var real = require( '@stdlib/complex/float64/real' ); -var imag = require( '@stdlib/complex/float64/imag' ); function map( v ) { return v * 2.0; @@ -444,13 +416,7 @@ var len = arr.length; // returns 1 var z = arr.get( 0 ); -// returns - -var re = real( z ); -// returns 2.0 - -var im = imag( z ); -// returns -2.0 +// returns [ 2.0, -2.0 ] ``` A callback function is provided two arguments: @@ -521,9 +487,6 @@ len = arr.length; Returns an array element located at integer position (index) `i`, with support for both nonnegative and negative integer positions. ```javascript -var real = require( '@stdlib/complex/float64/real' ); -var imag = require( '@stdlib/complex/float64/imag' ); - var arr = new Complex128Array( 10 ); // Set the first, second, and last elements: @@ -533,23 +496,11 @@ arr.set( [ 9.0, -9.0 ], 9 ); // Get the first element: var z = arr.at( 0 ); -// returns - -var re = real( z ); -// returns 1.0 - -var im = imag( z ); -// returns -1.0 +// returns [ 1.0, -1.0 ] // Get the last element: z = arr.at( -1 ); -// returns - -re = real( z ); -// returns 9.0 - -im = imag( z ); -// returns -9.0 +// returns [ 9.0, -9.0 ] ``` If provided an out-of-bounds index, the method returns `undefined`. @@ -572,8 +523,6 @@ Copies a sequence of elements within the array starting at `start` and ending at ```javascript var Complex128 = require( '@stdlib/complex/float64/ctor' ); -var real = require( '@stdlib/complex/float64/real' ); -var imag = require( '@stdlib/complex/float64/imag' ); var arr = new Complex128Array( 4 ); @@ -585,54 +534,28 @@ arr.set( new Complex128( 4.0, -4.0 ), 3 ); // Get the first array element: var z = arr.get( 0 ); -// returns - -var re = real( z ); -// returns 1.0 - -var im = imag( z ); -// returns -1.0 +// returns [ 1.0, -1.0 ] // Get the second array element: z = arr.get( 1 ); -// returns - -re = real( z ); -// returns 2.0 - -im = imag( z ); -// returns -2.0 +// returns [ 2.0, -2.0 ] // Copy the last two elements to the first two elements: arr.copyWithin( 0, 2 ); // Get the first array element: z = arr.get( 0 ); -// returns - -re = real( z ); -// returns 3.0 - -im = imag( z ); -// returns -3.0 +// returns [ 3.0, -3.0 ] // Get the second array element: z = arr.get( 1 ); -// returns - -re = real( z ); -// returns 4.0 - -im = imag( z ); -// returns -4.0 +// returns [ 4.0, -4.0 ] ``` By default, `end` equals the number of array elements (i.e., one more than the last array index). To limit the sequence length, provide an `end` argument. ```javascript var Complex128 = require( '@stdlib/complex/float64/ctor' ); -var real = require( '@stdlib/complex/float64/real' ); -var imag = require( '@stdlib/complex/float64/imag' ); var arr = new Complex128Array( 4 ); @@ -644,54 +567,28 @@ arr.set( new Complex128( 4.0, -4.0 ), 3 ); // Get the third array element: var z = arr.get( 2 ); -// returns - -var re = real( z ); -// returns 3.0 - -var im = imag( z ); -// returns -3.0 +// returns [ 3.0, -3.0 ] // Get the last array element: z = arr.get( 3 ); -// returns - -re = real( z ); -// returns 4.0 - -im = imag( z ); -// returns -4.0 +// returns [ 4.0, -4.0 ] // Copy the first two elements to the last two elements: arr.copyWithin( 2, 0, 2 ); // Get the third array element: z = arr.get( 2 ); -// returns - -re = real( z ); -// returns 1.0 - -im = imag( z ); -// returns -1.0 +// returns [ 1.0, -1.0 ] // Get the last array element: z = arr.get( 3 ); -// returns - -re = real( z ); -// returns 2.0 - -im = imag( z ); -// returns -2.0 +// returns [ 2.0, -2.0 ] ``` When a `target`, `start`, and/or `end` index is negative, the respective index is determined relative to the last array element. The following example achieves the same behavior as the previous example: ```javascript var Complex128 = require( '@stdlib/complex/float64/ctor' ); -var real = require( '@stdlib/complex/float64/real' ); -var imag = require( '@stdlib/complex/float64/imag' ); var arr = new Complex128Array( 4 ); @@ -703,46 +600,22 @@ arr.set( new Complex128( 4.0, -4.0 ), 3 ); // Get the third array element: var z = arr.get( 2 ); -// returns - -var re = real( z ); -// returns 3.0 - -var im = imag( z ); -// returns -3.0 +// returns [ 3.0, -3.0 ] // Get the last array element: z = arr.get( 3 ); -// returns - -re = real( z ); -// returns 4.0 - -im = imag( z ); -// returns -4.0 +// returns [ 4.0, -4.0 ] // Copy the first two elements to the last two elements using negative indices: arr.copyWithin( -2, -4, -2 ); // Get the third array element: z = arr.get( 2 ); -// returns - -re = real( z ); -// returns 1.0 - -im = imag( z ); -// returns -1.0 +// returns [ 1.0, -1.0 ] // Get the last array element: z = arr.get( 3 ); -// returns - -re = real( z ); -// returns 2.0 - -im = imag( z ); -// returns -2.0 +// returns [ 2.0, -2.0 ] ``` @@ -753,8 +626,6 @@ Returns an iterator for iterating over array key-value pairs. ```javascript var Complex128 = require( '@stdlib/complex/float64/ctor' ); -var real = require( '@stdlib/complex/float64/real' ); -var imag = require( '@stdlib/complex/float64/imag' ); var arr = [ new Complex128( 1.0, -1.0 ), @@ -768,31 +639,13 @@ var it = arr.entries(); // Iterate over the key-value pairs... var v = it.next().value; -// returns [ 0, ] - -var re = real( v[ 1 ] ); -// returns 1.0 - -var im = imag( v[ 1 ] ); -// returns -1.0 +// returns [ 0, [ 1.0, -1.0 ] ] v = it.next().value; -// returns [ 1, ] - -re = real( v[ 1 ] ); -// returns 2.0 - -im = imag( v[ 1 ] ); -// returns -2.0 +// returns [ 1, [ 2.0, -2.0 ] ] v = it.next().value; -// returns [ 2, ] - -re = real( v[ 1 ] ); -// returns 3.0 - -im = imag( v[ 1 ] ); -// returns -3.0 +// returns [ 2, [ 3.0, -3.0 ] ] var bool = it.next().done; // returns true @@ -864,8 +717,6 @@ Returns a modified typed array filled with a fill value. ```javascript var Complex128 = require( '@stdlib/complex/float64/ctor' ); -var real = require( '@stdlib/complex/float64/real' ); -var imag = require( '@stdlib/complex/float64/imag' ); var arr = new Complex128Array( 3 ); @@ -873,72 +724,34 @@ var arr = new Complex128Array( 3 ); arr.fill( new Complex128( 1.0, 1.0 ) ); var z = arr.get( 0 ); -// returns - -var re = real( z ); -// returns 1.0 - -var im = imag( z ); -// returns 1.0 +// returns [ 1.0, 1.0 ] z = arr.get( 2 ); -// returns - -re = real( z ); -// returns 1.0 - -im = imag( z ); -// returns 1.0 +// returns [ 1.0, 1.0 ] // Fill all elements starting from the second element: arr.fill( new Complex128( 2.0, 2.0 ), 1 ); z = arr.get( 1 ); -// returns - -re = real( z ); -// returns 2.0 - -im = imag( z ); -// returns 2.0 +// returns [ 2.0, 2.0 ] z = arr.get( 2 ); -// returns - -re = real( z ); -// returns 2.0 - -im = imag( z ); -// returns 2.0 +// returns [ 2.0, 2.0 ] // Fill all elements from first element until the second-to-last element: arr.fill( new Complex128( 3.0, 3.0 ), 0, 2 ); z = arr.get( 0 ); -// returns - -re = real( z ); -// returns 3.0 - -im = imag( z ); -// returns 3.0 +// returns [ 3.0, 3.0 ] z = arr.get( 1 ); -// returns - -re = real( z ); -// returns 3.0 - -im = imag( z ); -// returns 3.0 +// returns [ 3.0, 3.0 ] ``` When a `start` and/or `end` index is negative, the respective index is determined relative to the last array element. ```javascript var Complex128 = require( '@stdlib/complex/float64/ctor' ); -var real = require( '@stdlib/complex/float64/real' ); -var imag = require( '@stdlib/complex/float64/imag' ); var arr = new Complex128Array( 3 ); @@ -946,22 +759,10 @@ var arr = new Complex128Array( 3 ); arr.fill( new Complex128( 1.0, 1.0 ), 0, -1 ); var z = arr.get( 0 ); -// returns - -var re = real( z ); -// returns 1.0 - -var im = imag( z ); -// returns 1.0 +// returns [ 1.0, 1.0 ] z = arr.get( arr.length - 1 ); -// returns - -re = real( z ); -// returns 0.0 - -im = imag( z ); -// returns 0.0 +// returns [ 0.0, 0.0 ] ``` @@ -992,13 +793,7 @@ var len = out.length; // returns 1 var z = out.get( 0 ); -// returns - -var re = real( z ); -// returns 2.0 - -var im = imag( z ); -// returns 2.0 +// returns [ 2.0, 2.0 ] ``` The `predicate` function is provided three arguments: @@ -1061,13 +856,7 @@ arr.set( [ 2.0, 2.0 ], 1 ); arr.set( [ 3.0, 3.0 ], 2 ); var z = arr.find( predicate ); -// returns - -var re = real( z ); -// returns 1.0 - -var im = imag( z ); -// returns 1.0 +// returns [ 1.0, 1.0 ] ``` The `predicate` function is provided three arguments: @@ -1099,13 +888,7 @@ arr.set( [ 2.0, 2.0 ], 1 ); arr.set( [ 3.0, 3.0 ], 2 ); var z = arr.find( predicate, context ); -// returns - -var re = real( z ); -// returns 2.0 - -var im = imag( z ); -// returns 2.0 +// returns [ 2.0, 2.0 ] var count = context.count; // returns 2 @@ -1193,13 +976,7 @@ arr.set( [ 2.0, 2.0 ], 1 ); arr.set( [ 3.0, 3.0 ], 2 ); var z = arr.findLast( predicate ); -// returns - -var re = real( z ); -// returns 3.0 - -var im = imag( z ); -// returns 3.0 +// returns [ 3.0, 3.0 ] ``` The `predicate` function is provided three arguments: @@ -1231,13 +1008,7 @@ arr.set( [ 2.0, 2.0 ], 1 ); arr.set( [ 3.0, -3.0 ], 2 ); var z = arr.findLast( predicate, context ); -// returns - -var re = real( z ); -// returns 2.0 - -var im = imag( z ); -// returns 2.0 +// returns [ 2.0, 2.0 ] var count = context.count; // returns 2 diff --git a/lib/node_modules/@stdlib/array/complex128/docs/repl.txt b/lib/node_modules/@stdlib/array/complex128/docs/repl.txt index 0d99f99501cc..ef7ad30e5ce7 100644 --- a/lib/node_modules/@stdlib/array/complex128/docs/repl.txt +++ b/lib/node_modules/@stdlib/array/complex128/docs/repl.txt @@ -82,7 +82,7 @@ {{alias}}( obj ) - Creates a 128-bit complex number array from an array-like object or + Creates a 128-bit complex number array from an array-like object or iterable. Parameters @@ -165,12 +165,11 @@ thisArg: Any (optional) Callback execution context. - Returns ------- out: Complex128Array A typed array. - + Examples -------- > function clbkFcn( v ) { return v * 2.0 }; @@ -179,11 +178,7 @@ > var len = arr.length 2 > var z = arr.get( 0 ) - - > var re = {{alias:@stdlib/complex/float64/real}}( z ) - 2.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( z ) - -2.0 + [ 2.0, -2.0 ] {{alias}}.of( element0[, element1[, ...elementN]] ) @@ -219,11 +214,7 @@ > len = arr.length 2 > var z = arr.get( 0 ) - - > var re = {{alias:@stdlib/complex/float64/real}}( z ) - 1.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( z ) - -1.0 + [ 1.0, -1.0 ] {{alias}}.BYTES_PER_ELEMENT @@ -327,11 +318,7 @@ > var arr = new {{alias}}( [ 1.0, -1.0, 2.0, -2.0 ] ) > var z = arr.at( 1 ) - - > var re = {{alias:@stdlib/complex/float64/real}}( z ) - 2.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( z ) - -2.0 + [ 2.0, -2.0 ] {{alias}}.prototype.copyWithin( target, start[, end] ) @@ -342,10 +329,10 @@ ---------- target: integer Target start index position. - + start: integer Source start index position. - + end: integer (optional) Source end index position. Default: out.length. @@ -353,7 +340,7 @@ ------- out: Complex128Array Modified array. - + Examples -------- > var arr = new {{alias}}( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] ) @@ -361,11 +348,7 @@ > arr.copyWithin( 0, 2 ) > var z = arr.get( 0 ) - - > var re = {{alias:@stdlib/complex/float64/real}}( z ) - 3.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( z ) - -3.0 + [ 3.0, -3.0 ] {{alias}}.prototype.entries() @@ -382,23 +365,11 @@ > var it = arr.entries(); > var v = it.next().value - [ 0, ] - > var re = {{alias:@stdlib/complex/float64/real}}( v[ 1 ] ) - 1.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( v[ 1 ] ) - -1.0 + [ 0, [ 1.0, -1.0 ] ] > v = it.next().value - [ 1, ] - > re = {{alias:@stdlib/complex/float64/real}}( v[ 1 ] ) - 2.0 - > im = {{alias:@stdlib/complex/float64/imag}}( v[ 1 ] ) - -2.0 + [ 1, [ 2.0, -2.0 ] ] > v = it.next().value - [ 2, ] - > re = {{alias:@stdlib/complex/float64/real}}( v[ 1 ] ) - 3.0 - > im = {{alias:@stdlib/complex/float64/imag}}( v[ 1 ] ) - -3.0 + [ 2, [ 3.0, -3.0 ] ] > var bool = it.next().done true @@ -456,30 +427,18 @@ ------- out: Complex128Array Modified array. - + Examples -------- > var arr = new {{alias}}( 3 ) > arr.fill( new {{alias:@stdlib/complex/float64/ctor}}( 1.0, 1.0 ) ); > var z = arr.get( 0 ) - - > var re = {{alias:@stdlib/complex/float64/real}}( z ) - 1.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( z ) - 1.0 + [ 1.0, 1.0 ] > z = arr.get( 1 ) - - > re = {{alias:@stdlib/complex/float64/real}}( z ) - 1.0 - > im = {{alias:@stdlib/complex/float64/imag}}( z ) - 1.0 + [ 1.0, 1.0 ] > z = arr.get( 2 ) - - > re = {{alias:@stdlib/complex/float64/real}}( z ) - 1.0 - > im = {{alias:@stdlib/complex/float64/imag}}( z ) - 1.0 + [ 1.0, 1.0 ] {{alias}}.prototype.filter( predicate[, thisArg] ) @@ -508,7 +467,7 @@ ------- out: Complex128Array A new typed array. - + Examples -------- > function predicate( v ) { return ( {{alias:@stdlib/complex/float64/real}}( v ) === {{alias:@stdlib/complex/float64/imag}}( v ) ); }; @@ -519,11 +478,7 @@ > var len = out.length 1 > var z = out.get( 0 ) - - > var re = {{alias:@stdlib/complex/float64/real}}( z ) - 2.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( z ) - 2.0 + [ 2.0, 2.0 ] {{alias}}.prototype.find( predicate[, thisArg] ) @@ -546,23 +501,19 @@ thisArg: Any (optional) Execution context. - + Returns ------- out: Complex128|void Array element or `undefined`. - + Examples -------- > function predicate( v ) { return ( {{alias:@stdlib/complex/float64/real}}( v ) === {{alias:@stdlib/complex/float64/imag}}( v ) ); }; > var arr = new {{alias}}( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] ) > var z = arr.find( predicate ) - - > var re = {{alias:@stdlib/complex/float64/real}}( z ) - 1.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( z ) - 1.0 + [ 1.0, 1.0 ] {{alias}}.prototype.findIndex( predicate[, thisArg] ) @@ -585,12 +536,12 @@ thisArg: Any (optional) Execution context. - + Returns ------- out: integer Array index or `-1`. - + Examples -------- > function predicate( v ) { return ( {{alias:@stdlib/complex/float64/real}}( v ) === {{alias:@stdlib/complex/float64/imag}}( v ) ); }; @@ -619,24 +570,20 @@ Predicate function which tests array elements. thisArg: Any (optional) - Execution context. - + Execution context. + Returns ------- out: Complex128|void Array element or `undefined`. - + Examples -------- > function predicate( v ) { return ( {{alias:@stdlib/complex/float64/real}}( v ) === {{alias:@stdlib/complex/float64/imag}}( v ) ); }; > var arr = new {{alias}}( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] ) > var z = arr.findLast( predicate ) - - > var re = {{alias:@stdlib/complex/float64/real}}( z ) - 2.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( z ) - 2.0 + [ 2.0, 2.0 ] {{alias}}.prototype.findLastIndex( predicate[, thisArg] ) @@ -664,7 +611,7 @@ ------- out: integer Array index or `-1`. - + Examples -------- > function predicate( v ) { return ( {{alias:@stdlib/complex/float64/real}}( v ) === {{alias:@stdlib/complex/float64/imag}}( v ) ); }; @@ -690,7 +637,7 @@ thisArg: Any (optional) Execution context. - + Examples -------- > var str = '%'; @@ -712,22 +659,18 @@ ---------- i: integer Element index. - + Returns ------- out: Complex128|void Array element or `undefined`. - + Examples -------- > var arr = new {{alias}}( [ 1.0, -1.0, 2.0, -2.0 ] ) > var z = arr.get( 1 ) - - > var re = {{alias:@stdlib/complex/float64/real}}( z ) - 2.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( z ) - -2.0 + [ 2.0, -2.0 ] {{alias}}.prototype.includes( searchElement[, fromIndex] ) @@ -742,12 +685,12 @@ Array index at which to start the search. If provided a negative value, the method resolves the start index relative to the last array element. Default: 0. - + Returns ------- bool: boolean Boolean indicating whether an array includes a search element. - + Examples -------- > var arr = new {{alias}}( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] ) @@ -777,7 +720,7 @@ ------- out: integer Array index or `-1`. - + Examples -------- > var arr = new {{alias}}( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] ) @@ -796,12 +739,12 @@ ---------- separator: string (optional) Separator string. Default: ','. - + Returns ------- out: string Array serialized as a string. - + Examples -------- > var arr = new {{alias}}( [ 1.0, -1.0, 2.0, -2.0 ] ) @@ -819,7 +762,7 @@ ------- iterator: Iterator Iterator for iterating over array index keys. - + Examples -------- > var arr = new {{alias}}( [ 1.0, -1.0, 2.0, -2.0 ] ) @@ -847,12 +790,12 @@ Array index at which to start the search. If provided a negative value, the method resolves the start index relative to the last array element. Default: out.length-1. - + Returns ------- out: integer Array index or `-1`. - + Examples -------- > var arr = new {{alias}}( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] ) @@ -887,7 +830,7 @@ ------- out: Complex128Array A new typed array. - + Examples -------- > function clbk( v ) { return v; }; @@ -896,17 +839,9 @@ > var out = arr.map( clbk ) > var z = out.get( 0 ) - - > var re = {{alias:@stdlib/complex/float64/real}}( z ) - 1.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( z ) - -1.0 + [ 1.0, -1.0 ] > z = out.get( 1 ) - - > re = {{alias:@stdlib/complex/float64/real}}( z ) - 2.0 - > im = {{alias:@stdlib/complex/float64/imag}}( z ) - -2.0 + [ 2.0, -2.0 ] {{alias}}.prototype.reduce( reducerFn[, initialValue] ) @@ -932,26 +867,22 @@ Parameters ---------- reducerFn: Function - Function to apply to each array element. + Function to apply to each array element. initialValue: any (optional) Initial accumulation value. - + Returns ------- out: any Accumulated result. - + Examples -------- > var arr = new {{alias}}( [ 1.0, -1.0, 2.0, -2.0 ] ) > var z = arr.reduce( {{alias:@stdlib/complex/float64/base/add}} ) - - > var re = {{alias:@stdlib/complex/float64/real}}( z ) - 3.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( z ) - -3.0 + [ 3.0, -3.0 ] {{alias}}.prototype.reduceRight( reducerFn[, initialValue] ) @@ -981,22 +912,18 @@ initialValue: any (optional) Initial accumulation value. - + Returns ------- out: any Accumulated result. - + Examples -------- > var arr = new {{alias}}( [ 1.0, -1.0, 2.0, -2.0 ] ) > var z = arr.reduceRight( {{alias:@stdlib/complex/float64/base/add}} ) - - > var re = {{alias:@stdlib/complex/float64/real}}( z ) - 3.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( z ) - -3.0 + [ 3.0, -3.0 ] {{alias}}.prototype.reverse() @@ -1015,23 +942,11 @@ > arr.reverse(); > var z = arr.get( 0 ) - - > var re = {{alias:@stdlib/complex/float64/real}}( z ) - 3.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( z ) - -3.0 + [ 3.0, -3.0 ] > z = arr.get( 1 ) - - > re = {{alias:@stdlib/complex/float64/real}}( z ) - 2.0 - > im = {{alias:@stdlib/complex/float64/imag}}( z ) - -2.0 + [ 2.0, -2.0 ] > z = arr.get( 2 ) - - > re = {{alias:@stdlib/complex/float64/real}}( z ) - 1.0 - > im = {{alias:@stdlib/complex/float64/imag}}( z ) - -1.0 + [ 1.0, -1.0 ] {{alias}}.prototype.set( z[, i] ) @@ -1058,18 +973,10 @@ > arr.set( new {{alias:@stdlib/complex/float64/ctor}}( 1.0, -1.0 ) ); > var z = arr.get( 0 ) - - > var re = {{alias:@stdlib/complex/float64/real}}( z ) - 1.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( z ) - -1.0 + [ 1.0, -1.0 ] > arr.set( new {{alias:@stdlib/complex/float64/ctor}}( 2.0, -2.0 ), 1 ); > z = arr.get( 1 ) - - > re = {{alias:@stdlib/complex/float64/real}}( z ) - 2.0 - > im = {{alias:@stdlib/complex/float64/imag}}( z ) - -2.0 + [ 2.0, -2.0 ] {{alias}}.prototype.slice( [start[, end]] ) @@ -1084,12 +991,12 @@ end: integer (optional) End index (non-inclusive). If less than zero, the end index is resolved relative to the last array element. Default: out.length. - + Returns ------- out: Complex128Array New typed array. - + Examples -------- > var arr = new {{alias}}( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] ) @@ -1099,17 +1006,9 @@ > var len = out.length 2 > var z = out.get( 0 ) - - > var re = {{alias:@stdlib/complex/float64/real}}( z ) - 2.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( z ) - -2.0 + [ 2.0, -2.0 ] > z = out.get( 1 ) - - > re = {{alias:@stdlib/complex/float64/real}}( z ) - 3.0 - > im = {{alias:@stdlib/complex/float64/imag}}( z ) - -3.0 + [ 3.0, -3.0 ] {{alias}}.prototype.some( predicate[, thisArg] ) @@ -1127,15 +1026,15 @@ Predicate function which tests array elements. If a predicate function returns a truthy value, an array element passes; otherwise, an array element fails. - + thisArg: Any (optional) Execution context. - + Returns ------- bool: boolean Boolean indicating whether at least one element passes the test. - + Examples -------- > function predicate( v ) { return ( {{alias:@stdlib/complex/float64/real}}( v ) === {{alias:@stdlib/complex/float64/imag}}( v ) ); }; @@ -1162,12 +1061,12 @@ ---------- compareFunction: Function Comparison function. - + Returns ------- out: Complex128Array Modified array. - + Examples -------- > function compare( a, b ) { return ( {{alias:@stdlib/complex/float64/real}}( a ) - {{alias:@stdlib/complex/float64/real}}( b ) ); }; @@ -1175,23 +1074,11 @@ > arr.sort( compare ); > var z = arr.get( 0 ) - - > var re = {{alias:@stdlib/complex/float64/real}}( z ) - 1.0 - > var im = {{alias:@stdlib/complex/float64/imag}}( z ) - -1.0 + [ 1.0, -1.0 ] > z = arr.get( 1 ) - - > re = {{alias:@stdlib/complex/float64/real}}( z ) - 2.0 - > im = {{alias:@stdlib/complex/float64/imag}}( z ) - -2.0 + [ 2.0, -2.0 ] > z = arr.get( 2 ) - - > re = {{alias:@stdlib/complex/float64/real}}( z ) - 3.0 - > im = {{alias:@stdlib/complex/float64/imag}}( z ) - -3.0 + [ 3.0, -3.0 ] {{alias}}.prototype.subarray( [begin[, end]] ) @@ -1242,10 +1129,10 @@ ---------- locales: string|Array (optional) Locale identifier(s). - + options: Object (optional) An object containing serialization options. - + Returns ------- str: string @@ -1266,7 +1153,7 @@ ------- out: Complex128Array New typed array. - + Examples -------- > var arr = new {{alias}}( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ) @@ -1310,12 +1197,12 @@ ---------- compareFcn: Function Comparison function. - + Returns ------- out: Complex128Array New typed array. - + Examples -------- > function compare( a, b ) { return ( {{alias:@stdlib/complex/float64/real}}( a ) - {{alias:@stdlib/complex/float64/real}}( b ) ); }; @@ -1349,7 +1236,7 @@ ------- str: string String serialization of the array. - + Examples -------- > var arr = new {{alias}}( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] ) @@ -1365,7 +1252,7 @@ ------- iterator: Iterator Iterator for iterating over array values. - + Examples -------- > var arr = new {{alias}}( [ 1.0, -1.0, 2.0, -2.0 ] ) @@ -1395,15 +1282,15 @@ ---------- index: integer Element index. - + value: Complex128 - Element value. + Element value. Returns ------- out: Complex128Array New typed array. - + Examples -------- > var arr = new {{alias}}( [ 1.0, -1.0, 2.0, -2.0 ] ) diff --git a/lib/node_modules/@stdlib/array/complex128/lib/main.js b/lib/node_modules/@stdlib/array/complex128/lib/main.js index d46359f10ec5..49bd1f0ac59c 100644 --- a/lib/node_modules/@stdlib/array/complex128/lib/main.js +++ b/lib/node_modules/@stdlib/array/complex128/lib/main.js @@ -550,41 +550,20 @@ setReadOnly( Complex128Array, 'of', function of() { * @returns {(Complex128|void)} array element * * @example -* var real = require( '@stdlib/complex/float64/real' ); -* var imag = require( '@stdlib/complex/float64/imag' ); -* * var arr = new Complex128Array( 10 ); * * var z = arr.at( 0 ); -* // returns -* -* var re = real( z ); -* // returns 0.0 -* -* var im = imag( z ); -* // returns 0.0 +* // returns [ 0.0, 0.0 ] * * arr.set( [ 1.0, -1.0 ], 0 ); * arr.set( [ 2.0, -2.0 ], 1 ); * arr.set( [ 9.0, -9.0 ], 9 ); * * z = arr.at( 0 ); -* // returns -* -* re = real( z ); -* // returns 1.0 -* -* im = imag( z ); -* // returns -1.0 +* // returns [ 1.0, -1.0 ] * * z = arr.at( -1 ); -* // returns -* -* re = real( z ); -* // returns 9.0 -* -* im = imag( z ); -* // returns -9.0 +* // returns [ 9.0, -9.0 ] * * z = arr.at( 100 ); * // returns undefined @@ -693,8 +672,6 @@ setReadOnly( Complex128Array.prototype, 'BYTES_PER_ELEMENT', Complex128Array.BYT * * @example * var Complex128 = require( '@stdlib/complex/float64/ctor' ); -* var real = require( '@stdlib/complex/float64/real' ); -* var imag = require( '@stdlib/complex/float64/imag' ); * * var arr = new Complex128Array( 4 ); * @@ -709,12 +686,7 @@ setReadOnly( Complex128Array.prototype, 'BYTES_PER_ELEMENT', Complex128Array.BYT * * // Get the last array element: * var z = arr.get( 3 ); -* -* var re = real( z ); -* // returns 2.0 -* -* var im = imag( z ); -* // returns 2.0 +* // returns [ 2.0, 2.0 ] */ setReadOnly( Complex128Array.prototype, 'copyWithin', function copyWithin( target, start ) { if ( !isComplexArray( this ) ) { @@ -909,30 +881,15 @@ setReadOnly( Complex128Array.prototype, 'every', function every( predicate, this * @returns {Complex128Array} modified array * * @example -* var real = require( '@stdlib/complex/float64/real' ); -* var imag = require( '@stdlib/complex/float64/imag' ); -* * var arr = new Complex128Array( 3 ); * * arr.fill( new Complex128( 1.0, 1.0 ), 1 ); * * var z = arr.get( 1 ); -* // returns -* -* var re = real( z ); -* // returns 1.0 -* -* var im = imag( z ); -* // returns 1.0 +* // returns [ 1.0, 1.0 ] * * z = arr.get( 2 ); -* // returns -* -* re = real( z ); -* // returns 1.0 -* -* im = imag( z ); -* // returns 1.0 +* // returns [ 1.0, 1.0 ] */ setReadOnly( Complex128Array.prototype, 'fill', function fill( value, start, end ) { var buf; @@ -1002,9 +959,6 @@ setReadOnly( Complex128Array.prototype, 'fill', function fill( value, start, end * @returns {Complex128Array} complex number array * * @example -* var real = require( '@stdlib/complex/float64/real' ); -* var imag = require( '@stdlib/complex/float64/imag' ); -* * function predicate( v ) { * return ( real( v ) === imag( v ) ); * } @@ -1022,13 +976,7 @@ setReadOnly( Complex128Array.prototype, 'fill', function fill( value, start, end * // returns 1 * * var z = out.get( 0 ); -* // returns -* -* var re = real( z ); -* // returns 2.0 -* -* var im = imag( z ); -* // returns 2.0 +* // returns [ 2.0, 2.0 ] */ setReadOnly( Complex128Array.prototype, 'filter', function filter( predicate, thisArg ) { var buf; @@ -1065,9 +1013,6 @@ setReadOnly( Complex128Array.prototype, 'filter', function filter( predicate, th * @returns {(Complex128|void)} array element or undefined * * @example -* var real = require( '@stdlib/complex/float64/real' ); -* var imag = require( '@stdlib/complex/float64/imag' ); -* * function predicate( v ) { * return ( real( v ) === imag( v ) ); * } @@ -1079,13 +1024,7 @@ setReadOnly( Complex128Array.prototype, 'filter', function filter( predicate, th * arr.set( [ 3.0, 3.0 ], 2 ); * * var z = arr.find( predicate ); -* // returns -* -* var re = real( z ); -* // returns 1.0 -* -* var im = imag( z ); -* // returns 1.0 +* // returns [ 1.0, 1.0 ] */ setReadOnly( Complex128Array.prototype, 'find', function find( predicate, thisArg ) { var buf; diff --git a/lib/node_modules/@stdlib/array/empty/lib/polyfill.js b/lib/node_modules/@stdlib/array/empty/lib/polyfill.js index 1d66e8cc4a7d..dc55fa3b62ef 100644 --- a/lib/node_modules/@stdlib/array/empty/lib/polyfill.js +++ b/lib/node_modules/@stdlib/array/empty/lib/polyfill.js @@ -20,6 +20,7 @@ // MODULES // +var BooleanArray = require( '@stdlib/array/bool' ); var zeros = require( '@stdlib/array/zeros' ); @@ -44,8 +45,14 @@ var zeros = require( '@stdlib/array/zeros' ); * // returns */ function empty( length ) { + var dt; if ( arguments.length > 1 ) { - return zeros( length, arguments[ 1 ] ); + dt = arguments[ 1 ]; + if ( dt === 'bool' ) { + // Special handle boolean arrays as `zeros` only supports numeric data types: + return new BooleanArray( length ); + } + return zeros( length, dt ); } return zeros( length ); } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.complex128_complex.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.complex128_complex.length.js index b5b2976a5718..b3a0d58b9774 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.complex128_complex.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.complex128_complex.length.js @@ -25,6 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); var Complex128Array = require( '@stdlib/array/complex128' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -94,7 +95,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::complex:assign:dtype=complex128,len='+len, f ); + bench( format( '%s::complex:assign:dtype=complex128,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.complex128_real.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.complex128_real.length.js index 2dd12338150f..124986165b25 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.complex128_real.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.complex128_real.length.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::real:assign:dtype=complex128,len='+len, f ); + bench( format( '%s::real:assign:dtype=complex128,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.complex64_complex.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.complex64_complex.length.js index a66c2b2050b5..1a88eab89b63 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.complex64_complex.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.complex64_complex.length.js @@ -25,6 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); var Complex64Array = require( '@stdlib/array/complex64' ); var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -94,7 +95,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::complex:assign:dtype=complex64,len='+len, f ); + bench( format( '%s::complex:assign:dtype=complex64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.complex64_real.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.complex64_real.length.js index 2f4626042293..b765372fcda9 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.complex64_real.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.complex64_real.length.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); var Complex64Array = require( '@stdlib/array/complex64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::real:assign:dtype=complex64,len='+len, f ); + bench( format( '%s::real:assign:dtype=complex64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.float32_real.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.float32_real.length.js index 1fd54f13c88e..a63ded7b4365 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.float32_real.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.float32_real.length.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::real:assign:dtype=float32,len='+len, f ); + bench( format( '%s::real:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.float64_real.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.float64_real.length.js index 870eb17e3602..38d9c6ecf003 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.float64_real.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.float64_real.length.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::real:assign:dtype=float64,len='+len, f ); + bench( format( '%s::real:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.generic_complex.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.generic_complex.length.js index e3fb500ffe03..b400003605b6 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.generic_complex.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.generic_complex.length.js @@ -25,6 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); var zeros = require( '@stdlib/array/base/zeros' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -94,7 +95,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::complex:assign:dtype=generic,len='+len, f ); + bench( format( '%s::complex:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.generic_real.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.generic_real.length.js index a6982b39ed4f..1bcb72749720 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.generic_real.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.generic_real.length.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); var zeros = require( '@stdlib/array/base/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::real:assign:dtype=generic,len='+len, f ); + bench( format( '%s::real:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.js index a5b169cd4db4..3d5eeb2c0e02 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.assign.js @@ -29,13 +29,14 @@ var Complex64Array = require( '@stdlib/array/complex64' ); var Float64Array = require( '@stdlib/array/float64' ); var Float32Array = require( '@stdlib/array/float32' ); var zeros = require( '@stdlib/array/base/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); // MAIN // -bench( pkg+'::real:assign:dtype=float64', function benchmark( b ) { +bench( format( '%s::real:assign:dtype=float64', pkg ), function benchmark( b ) { var out; var v; var i; @@ -57,7 +58,7 @@ bench( pkg+'::real:assign:dtype=float64', function benchmark( b ) { b.end(); }); -bench( pkg+'::real:assign:dtype=float32', function benchmark( b ) { +bench( format( '%s::real:assign:dtype=float32', pkg ), function benchmark( b ) { var out; var v; var i; @@ -79,7 +80,7 @@ bench( pkg+'::real:assign:dtype=float32', function benchmark( b ) { b.end(); }); -bench( pkg+'::real:assign:dtype=generic', function benchmark( b ) { +bench( format( '%s::real:assign:dtype=generic', pkg ), function benchmark( b ) { var out; var v; var i; @@ -101,7 +102,7 @@ bench( pkg+'::real:assign:dtype=generic', function benchmark( b ) { b.end(); }); -bench( pkg+'::complex:assign:dtype=generic', function benchmark( b ) { +bench( format( '%s::complex:assign:dtype=generic', pkg ), function benchmark( b ) { var out; var x1; var x2; @@ -128,7 +129,7 @@ bench( pkg+'::complex:assign:dtype=generic', function benchmark( b ) { b.end(); }); -bench( pkg+'::real:assign:dtype=complex128', function benchmark( b ) { +bench( format( '%s::real:assign:dtype=complex128', pkg ), function benchmark( b ) { var out; var v; var i; @@ -150,7 +151,7 @@ bench( pkg+'::real:assign:dtype=complex128', function benchmark( b ) { b.end(); }); -bench( pkg+'::complex:assign:dtype=complex128', function benchmark( b ) { +bench( format( '%s::complex:assign:dtype=complex128', pkg ), function benchmark( b ) { var out; var x1; var x2; @@ -177,7 +178,7 @@ bench( pkg+'::complex:assign:dtype=complex128', function benchmark( b ) { b.end(); }); -bench( pkg+'::real:assign:dtype=complex64', function benchmark( b ) { +bench( format( '%s::real:assign:dtype=complex64', pkg ), function benchmark( b ) { var out; var v; var i; @@ -199,7 +200,7 @@ bench( pkg+'::real:assign:dtype=complex64', function benchmark( b ) { b.end(); }); -bench( pkg+'::complex:assign:dtype=complex64', function benchmark( b ) { +bench( format( '%s::complex:assign:dtype=complex64', pkg ), function benchmark( b ) { var out; var x1; var x2; diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.complex128_complex.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.complex128_complex.length.js index 0f7355ef80f9..56c5a41cbe78 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.complex128_complex.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.complex128_complex.length.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::complex:dtype=complex128,len='+len, f ); + bench( format( '%s::complex:dtype=complex128,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.complex128_real.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.complex128_real.length.js index dd99221a9f6b..1b90e9f1a172 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.complex128_real.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.complex128_real.length.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::real:dtype=complex128,len='+len, f ); + bench( format( '%s::real:dtype=complex128,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.complex64_complex.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.complex64_complex.length.js index 7645306a41b8..1f382e6ee398 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.complex64_complex.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.complex64_complex.length.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::complex:dtype=complex64,len='+len, f ); + bench( format( '%s::complex:dtype=complex64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.complex64_real.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.complex64_real.length.js index 555079cbe08c..64b61e463688 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.complex64_real.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.complex64_real.length.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::real:dtype=complex64,len='+len, f ); + bench( format( '%s::real:dtype=complex64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.default_complex.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.default_complex.length.js index c62d1ea6df4f..9933d704a16e 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.default_complex.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.default_complex.length.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -92,7 +93,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::default,complex:len='+len, f ); + bench( format( '%s::default,complex:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.default_real.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.default_real.length.js index 3f6c47f1e534..d157a4e090da 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.default_real.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.default_real.length.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -86,7 +87,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::default,real:len='+len, f ); + bench( format( '%s::default,real:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.float32_real.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.float32_real.length.js index 6060169cca00..2d0b79f170b9 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.float32_real.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.float32_real.length.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::real:dtype=float32,len='+len, f ); + bench( format( '%s::real:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.float64_real.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.float64_real.length.js index c872cad4e070..8e29232b7b15 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.float64_real.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.float64_real.length.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::real:dtype=float64,len='+len, f ); + bench( format( '%s::real:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.generic_complex.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.generic_complex.length.js index fb184b7fa9d4..dba4d937c6dd 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.generic_complex.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.generic_complex.length.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::complex:dtype=generic,len='+len, f ); + bench( format( '%s::complex:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.generic_real.length.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.generic_real.length.js index edfc25d1d2b0..957281a2e713 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.generic_real.length.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.generic_real.length.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::real:dtype=generic,len='+len, f ); + bench( format( '%s::real:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.js index 79dd2a47dd29..e9bde16f0701 100644 --- a/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/linspace/benchmark/benchmark.js @@ -24,13 +24,14 @@ var bench = require( '@stdlib/bench' ); var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var linspace = require( './../lib' ); // MAIN // -bench( pkg+'::default,real', function benchmark( b ) { +bench( format( '%s::default,real', pkg ), function benchmark( b ) { var v; var i; @@ -49,7 +50,7 @@ bench( pkg+'::default,real', function benchmark( b ) { b.end(); }); -bench( pkg+'::default,complex', function benchmark( b ) { +bench( format( '%s::default,complex', pkg ), function benchmark( b ) { var x1; var x2; var v; @@ -73,7 +74,7 @@ bench( pkg+'::default,complex', function benchmark( b ) { b.end(); }); -bench( pkg+'::real:dtype=float64', function benchmark( b ) { +bench( format( '%s::real:dtype=float64', pkg ), function benchmark( b ) { var opts; var v; var i; @@ -97,7 +98,7 @@ bench( pkg+'::real:dtype=float64', function benchmark( b ) { b.end(); }); -bench( pkg+'::real:dtype=float32', function benchmark( b ) { +bench( format( '%s::real:dtype=float32', pkg ), function benchmark( b ) { var opts; var v; var i; @@ -121,7 +122,7 @@ bench( pkg+'::real:dtype=float32', function benchmark( b ) { b.end(); }); -bench( pkg+'::real:dtype=generic', function benchmark( b ) { +bench( format( '%s::real:dtype=generic', pkg ), function benchmark( b ) { var opts; var v; var i; @@ -145,7 +146,7 @@ bench( pkg+'::real:dtype=generic', function benchmark( b ) { b.end(); }); -bench( pkg+'::complex:dtype=generic', function benchmark( b ) { +bench( format( '%s::complex:dtype=generic', pkg ), function benchmark( b ) { var opts; var x1; var x2; @@ -174,7 +175,7 @@ bench( pkg+'::complex:dtype=generic', function benchmark( b ) { b.end(); }); -bench( pkg+'::real:dtype=complex128', function benchmark( b ) { +bench( format( '%s::real:dtype=complex128', pkg ), function benchmark( b ) { var opts; var v; var i; @@ -198,7 +199,7 @@ bench( pkg+'::real:dtype=complex128', function benchmark( b ) { b.end(); }); -bench( pkg+'::complex:dtype=complex128', function benchmark( b ) { +bench( format( '%s::complex:dtype=complex128', pkg ), function benchmark( b ) { var opts; var x1; var x2; @@ -227,7 +228,7 @@ bench( pkg+'::complex:dtype=complex128', function benchmark( b ) { b.end(); }); -bench( pkg+'::real:dtype=complex64', function benchmark( b ) { +bench( format( '%s::real:dtype=complex64', pkg ), function benchmark( b ) { var opts; var v; var i; @@ -251,7 +252,7 @@ bench( pkg+'::real:dtype=complex64', function benchmark( b ) { b.end(); }); -bench( pkg+'::complex:dtype=complex64', function benchmark( b ) { +bench( format( '%s::complex:dtype=complex64', pkg ), function benchmark( b ) { var opts; var x1; var x2; diff --git a/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.from.js b/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.from.js index 7045afda885c..7a04aabe851a 100644 --- a/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.from.js +++ b/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.from.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var Float32Array = require( '@stdlib/array/float32' ); var ITERATOR_SYMBOL = require( '@stdlib/symbol/iterator' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float32ArrayLE = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+'::typed_array:from', function benchmark( b ) { +bench( format( '%s::typed_array:from', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -58,7 +59,7 @@ bench( pkg+'::typed_array:from', function benchmark( b ) { b.end(); }); -bench( pkg+'::typed_array:from:len=5', function benchmark( b ) { +bench( format( '%s::typed_array:from:len=5', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -80,7 +81,7 @@ bench( pkg+'::typed_array:from:len=5', function benchmark( b ) { b.end(); }); -bench( pkg+'::typed_array,clbk:from:len=5', function benchmark( b ) { +bench( format( '%s::typed_array,clbk:from:len=5', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -106,7 +107,7 @@ bench( pkg+'::typed_array,clbk:from:len=5', function benchmark( b ) { } }); -bench( pkg+'::array:from', function benchmark( b ) { +bench( format( '%s::array:from', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -128,7 +129,7 @@ bench( pkg+'::array:from', function benchmark( b ) { b.end(); }); -bench( pkg+'::array:from:len=5', function benchmark( b ) { +bench( format( '%s::array:from:len=5', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -150,7 +151,7 @@ bench( pkg+'::array:from:len=5', function benchmark( b ) { b.end(); }); -bench( pkg+'::array,clbk:from:len=5', function benchmark( b ) { +bench( format( '%s::array,clbk:from:len=5', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -176,7 +177,7 @@ bench( pkg+'::array,clbk:from:len=5', function benchmark( b ) { } }); -bench( pkg+'::iterable:from', opts, function benchmark( b ) { +bench( format( '%s::iterable:from', pkg ), opts, function benchmark( b ) { var arr; var i; @@ -213,7 +214,7 @@ bench( pkg+'::iterable:from', opts, function benchmark( b ) { } }); -bench( pkg+'::iterable:from:len=5', opts, function benchmark( b ) { +bench( format( '%s::iterable:from:len=5', pkg ), opts, function benchmark( b ) { var arr; var i; @@ -259,7 +260,7 @@ bench( pkg+'::iterable:from:len=5', opts, function benchmark( b ) { } }); -bench( pkg+'::iterable,clbk:from:len=5', opts, function benchmark( b ) { +bench( format( '%s::iterable,clbk:from:len=5', pkg ), opts, function benchmark( b ) { var arr; var i; diff --git a/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.get.js b/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.get.js index 753a76288fa0..9871358a0d28 100644 --- a/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.get.js +++ b/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.get.js @@ -22,13 +22,14 @@ var bench = require( '@stdlib/bench' ); var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float32ArrayLE = require( './../lib' ); // MAIN // -bench( pkg+':get', function benchmark( b ) { +bench( format( '%s:get', pkg ), function benchmark( b ) { var arr; var N; var v; diff --git a/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.js index da6a622ffbd7..a54ea76b8393 100644 --- a/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.js @@ -26,6 +26,7 @@ var Float32Array = require( '@stdlib/array/float32' ); var isArrayBuffer = require( '@stdlib/assert/is-arraybuffer' ); var isNonNegativeInteger = require( '@stdlib/assert/is-nonnegative-integer' ).isPrimitive; var ITERATOR_SYMBOL = require( '@stdlib/symbol/iterator' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float32ArrayLE = require( './../lib' ); @@ -66,7 +67,7 @@ function createIterable() { // MAIN // -bench( pkg+'::instantiation,new', function benchmark( b ) { +bench( format( '%s::instantiation,new', pkg ), function benchmark( b ) { var arr; var i; b.tic(); @@ -84,7 +85,7 @@ bench( pkg+'::instantiation,new', function benchmark( b ) { b.end(); }); -bench( pkg+'::instantiation,no_new', function benchmark( b ) { +bench( format( '%s::instantiation,no_new', pkg ), function benchmark( b ) { var ctor; var arr; var i; @@ -106,7 +107,7 @@ bench( pkg+'::instantiation,no_new', function benchmark( b ) { b.end(); }); -bench( pkg+'::instantiation,length', function benchmark( b ) { +bench( format( '%s::instantiation,length', pkg ), function benchmark( b ) { var arr; var i; b.tic(); @@ -124,7 +125,7 @@ bench( pkg+'::instantiation,length', function benchmark( b ) { b.end(); }); -bench( pkg+'::instantiation,typed_array', function benchmark( b ) { +bench( format( '%s::instantiation,typed_array', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -146,7 +147,7 @@ bench( pkg+'::instantiation,typed_array', function benchmark( b ) { b.end(); }); -bench( pkg+'::instantiation,array', function benchmark( b ) { +bench( format( '%s::instantiation,array', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -168,7 +169,7 @@ bench( pkg+'::instantiation,array', function benchmark( b ) { b.end(); }); -bench( pkg+'::instantiation,iterable', opts, function benchmark( b ) { +bench( format( '%s::instantiation,iterable', pkg ), opts, function benchmark( b ) { var arr; var i; @@ -187,7 +188,7 @@ bench( pkg+'::instantiation,iterable', opts, function benchmark( b ) { b.end(); }); -bench( pkg+'::instantiation,arraybuffer', function benchmark( b ) { +bench( format( '%s::instantiation,arraybuffer', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -209,7 +210,7 @@ bench( pkg+'::instantiation,arraybuffer', function benchmark( b ) { b.end(); }); -bench( pkg+'::instantiation,arraybuffer,byte_offset', function benchmark( b ) { +bench( format( '%s::instantiation,arraybuffer,byte_offset', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -231,7 +232,7 @@ bench( pkg+'::instantiation,arraybuffer,byte_offset', function benchmark( b ) { b.end(); }); -bench( pkg+'::instantiation,arraybuffer,byte_offset,length', function benchmark( b ) { +bench( format( '%s::instantiation,arraybuffer,byte_offset,length', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -253,7 +254,7 @@ bench( pkg+'::instantiation,arraybuffer,byte_offset,length', function benchmark( b.end(); }); -bench( pkg+'::get:buffer', function benchmark( b ) { +bench( format( '%s::get:buffer', pkg ), function benchmark( b ) { var arr; var v; var i; @@ -276,7 +277,7 @@ bench( pkg+'::get:buffer', function benchmark( b ) { b.end(); }); -bench( pkg+'::get:byteLength', function benchmark( b ) { +bench( format( '%s::get:byteLength', pkg ), function benchmark( b ) { var arr; var v; var i; @@ -299,7 +300,7 @@ bench( pkg+'::get:byteLength', function benchmark( b ) { b.end(); }); -bench( pkg+'::get:byteOffset', function benchmark( b ) { +bench( format( '%s::get:byteOffset', pkg ), function benchmark( b ) { var arr; var v; var i; @@ -322,7 +323,7 @@ bench( pkg+'::get:byteOffset', function benchmark( b ) { b.end(); }); -bench( pkg+'::get:length', function benchmark( b ) { +bench( format( '%s::get:length', pkg ), function benchmark( b ) { var arr; var v; var i; diff --git a/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.of.js b/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.of.js index d0d1b40a9902..e1d1db90d339 100644 --- a/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.of.js +++ b/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.of.js @@ -21,13 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float32ArrayLE = require( './../lib' ); // MAIN // -bench( pkg+':of', function benchmark( b ) { +bench( format( '%s:of', pkg ), function benchmark( b ) { var arr; var i; @@ -46,7 +47,7 @@ bench( pkg+':of', function benchmark( b ) { b.end(); }); -bench( pkg+':len=5', function benchmark( b ) { +bench( format( '%s:of:len=5', pkg ), function benchmark( b ) { var buf; var arr; var i; diff --git a/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.set.js b/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.set.js index 611c7413b289..3c8d7061b140 100644 --- a/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.set.js +++ b/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.set.js @@ -22,13 +22,14 @@ var bench = require( '@stdlib/bench' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float32ArrayLE = require( './../lib' ); // MAIN // -bench( pkg+'::number:set', function benchmark( b ) { +bench( format( '%s::number:set', pkg ), function benchmark( b ) { var values; var arr; var N; @@ -57,7 +58,7 @@ bench( pkg+'::number:set', function benchmark( b ) { b.end(); }); -bench( pkg+'::array:set', function benchmark( b ) { +bench( format( '%s::array:set', pkg ), function benchmark( b ) { var values; var arr; var N; @@ -86,7 +87,7 @@ bench( pkg+'::array:set', function benchmark( b ) { b.end(); }); -bench( pkg+'::typed_array:set', function benchmark( b ) { +bench( format( '%s::typed_array:set', pkg ), function benchmark( b ) { var values; var arr; var buf; diff --git a/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.set.length.js b/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.set.length.js index 052841da0741..de41916d60d0 100644 --- a/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.set.length.js +++ b/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.set.length.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var randu = require( '@stdlib/random/array/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float32ArrayLE = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':set:len='+len, f ); + bench( format( '%s:set:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.to_string.js b/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.to_string.js index 198b9663cee1..cc9ff4a40f82 100644 --- a/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.to_string.js +++ b/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.to_string.js @@ -21,13 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float32ArrayLE = require( './../lib' ); // MAIN // -bench( pkg+':toString', function benchmark( b ) { +bench( format( '%s:toString', pkg ), function benchmark( b ) { var out; var arr; var i; diff --git a/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.to_string.length.js b/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.to_string.length.js index c63c245058bc..2a1b7d931d04 100644 --- a/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.to_string.length.js +++ b/lib/node_modules/@stdlib/array/little-endian-float32/benchmark/benchmark.to_string.length.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeroTo = require( '@stdlib/array/zero-to' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float32ArrayLE = require( './../lib' ); @@ -87,7 +88,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':toString:len='+len, f ); + bench( format( '%s:toString:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.from.js b/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.from.js index 2cd64477a5b3..aa16a2559693 100644 --- a/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.from.js +++ b/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.from.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); var ITERATOR_SYMBOL = require( '@stdlib/symbol/iterator' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float64ArrayLE = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+'::typed_array:from', function benchmark( b ) { +bench( format( '%s::typed_array:from', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -58,7 +59,7 @@ bench( pkg+'::typed_array:from', function benchmark( b ) { b.end(); }); -bench( pkg+'::typed_array:from:len=5', function benchmark( b ) { +bench( format( '%s::typed_array:from:len=5', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -80,7 +81,7 @@ bench( pkg+'::typed_array:from:len=5', function benchmark( b ) { b.end(); }); -bench( pkg+'::typed_array,clbk:from:len=5', function benchmark( b ) { +bench( format( '%s::typed_array,clbk:from:len=5', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -106,7 +107,7 @@ bench( pkg+'::typed_array,clbk:from:len=5', function benchmark( b ) { } }); -bench( pkg+'::array:from', function benchmark( b ) { +bench( format( '%s::array:from', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -128,7 +129,7 @@ bench( pkg+'::array:from', function benchmark( b ) { b.end(); }); -bench( pkg+'::array:from:len=5', function benchmark( b ) { +bench( format( '%s::array:from:len=5', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -150,7 +151,7 @@ bench( pkg+'::array:from:len=5', function benchmark( b ) { b.end(); }); -bench( pkg+'::array,clbk:from:len=5', function benchmark( b ) { +bench( format( '%s::array,clbk:from:len=5', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -176,7 +177,7 @@ bench( pkg+'::array,clbk:from:len=5', function benchmark( b ) { } }); -bench( pkg+'::iterable:from', opts, function benchmark( b ) { +bench( format( '%s::iterable:from', pkg ), opts, function benchmark( b ) { var arr; var i; @@ -213,7 +214,7 @@ bench( pkg+'::iterable:from', opts, function benchmark( b ) { } }); -bench( pkg+'::iterable:from:len=5', opts, function benchmark( b ) { +bench( format( '%s::iterable:from:len=5', pkg ), opts, function benchmark( b ) { var arr; var i; @@ -259,7 +260,7 @@ bench( pkg+'::iterable:from:len=5', opts, function benchmark( b ) { } }); -bench( pkg+'::iterable,clbk:from:len=5', opts, function benchmark( b ) { +bench( format( '%s::iterable,clbk:from:len=5', pkg ), opts, function benchmark( b ) { var arr; var i; diff --git a/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.get.js b/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.get.js index 127c09523b32..809e0f3fdeb4 100644 --- a/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.get.js +++ b/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.get.js @@ -22,13 +22,14 @@ var bench = require( '@stdlib/bench' ); var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float64ArrayLE = require( './../lib' ); // MAIN // -bench( pkg+':get', function benchmark( b ) { +bench( format( '%s:get', pkg ), function benchmark( b ) { var arr; var N; var v; diff --git a/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.js index 51dababfb749..b8b50410bab0 100644 --- a/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.js @@ -26,6 +26,7 @@ var Float64Array = require( '@stdlib/array/float64' ); var isArrayBuffer = require( '@stdlib/assert/is-arraybuffer' ); var isNonNegativeInteger = require( '@stdlib/assert/is-nonnegative-integer' ).isPrimitive; var ITERATOR_SYMBOL = require( '@stdlib/symbol/iterator' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float64ArrayLE = require( './../lib' ); @@ -66,7 +67,7 @@ function createIterable() { // MAIN // -bench( pkg+'::instantiation,new', function benchmark( b ) { +bench( format( '%s::instantiation,new', pkg ), function benchmark( b ) { var arr; var i; b.tic(); @@ -84,7 +85,7 @@ bench( pkg+'::instantiation,new', function benchmark( b ) { b.end(); }); -bench( pkg+'::instantiation,no_new', function benchmark( b ) { +bench( format( '%s::instantiation,no_new', pkg ), function benchmark( b ) { var ctor; var arr; var i; @@ -106,7 +107,7 @@ bench( pkg+'::instantiation,no_new', function benchmark( b ) { b.end(); }); -bench( pkg+'::instantiation,length', function benchmark( b ) { +bench( format( '%s::instantiation,length', pkg ), function benchmark( b ) { var arr; var i; b.tic(); @@ -124,7 +125,7 @@ bench( pkg+'::instantiation,length', function benchmark( b ) { b.end(); }); -bench( pkg+'::instantiation,typed_array', function benchmark( b ) { +bench( format( '%s::instantiation,typed_array', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -146,7 +147,7 @@ bench( pkg+'::instantiation,typed_array', function benchmark( b ) { b.end(); }); -bench( pkg+'::instantiation,array', function benchmark( b ) { +bench( format( '%s::instantiation,array', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -168,7 +169,7 @@ bench( pkg+'::instantiation,array', function benchmark( b ) { b.end(); }); -bench( pkg+'::instantiation,iterable', opts, function benchmark( b ) { +bench( format( '%s::instantiation,iterable', pkg ), opts, function benchmark( b ) { var arr; var i; @@ -187,7 +188,7 @@ bench( pkg+'::instantiation,iterable', opts, function benchmark( b ) { b.end(); }); -bench( pkg+'::instantiation,arraybuffer', function benchmark( b ) { +bench( format( '%s::instantiation,arraybuffer', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -209,7 +210,7 @@ bench( pkg+'::instantiation,arraybuffer', function benchmark( b ) { b.end(); }); -bench( pkg+'::instantiation,arraybuffer,byte_offset', function benchmark( b ) { +bench( format( '%s::instantiation,arraybuffer,byte_offset', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -231,7 +232,7 @@ bench( pkg+'::instantiation,arraybuffer,byte_offset', function benchmark( b ) { b.end(); }); -bench( pkg+'::instantiation,arraybuffer,byte_offset,length', function benchmark( b ) { +bench( format( '%s::instantiation,arraybuffer,byte_offset,length', pkg ), function benchmark( b ) { var buf; var arr; var i; @@ -253,7 +254,7 @@ bench( pkg+'::instantiation,arraybuffer,byte_offset,length', function benchmark( b.end(); }); -bench( pkg+'::get:buffer', function benchmark( b ) { +bench( format( '%s::get:buffer', pkg ), function benchmark( b ) { var arr; var v; var i; @@ -276,7 +277,7 @@ bench( pkg+'::get:buffer', function benchmark( b ) { b.end(); }); -bench( pkg+'::get:byteLength', function benchmark( b ) { +bench( format( '%s::get:byteLength', pkg ), function benchmark( b ) { var arr; var v; var i; @@ -299,7 +300,7 @@ bench( pkg+'::get:byteLength', function benchmark( b ) { b.end(); }); -bench( pkg+'::get:byteOffset', function benchmark( b ) { +bench( format( '%s::get:byteOffset', pkg ), function benchmark( b ) { var arr; var v; var i; @@ -322,7 +323,7 @@ bench( pkg+'::get:byteOffset', function benchmark( b ) { b.end(); }); -bench( pkg+'::get:length', function benchmark( b ) { +bench( format( '%s::get:length', pkg ), function benchmark( b ) { var arr; var v; var i; diff --git a/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.of.js b/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.of.js index ca9ef910707c..9678886d4f9e 100644 --- a/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.of.js +++ b/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.of.js @@ -21,13 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float64ArrayLE = require( './../lib' ); // MAIN // -bench( pkg+':of', function benchmark( b ) { +bench( format( '%s:of', pkg ), function benchmark( b ) { var arr; var i; @@ -46,7 +47,7 @@ bench( pkg+':of', function benchmark( b ) { b.end(); }); -bench( pkg+':len=5', function benchmark( b ) { +bench( format( '%s:of:len=5', pkg ), function benchmark( b ) { var buf; var arr; var i; diff --git a/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.set.js b/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.set.js index d2f705325547..3c545a995f6a 100644 --- a/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.set.js +++ b/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.set.js @@ -22,13 +22,14 @@ var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float64ArrayLE = require( './../lib' ); // MAIN // -bench( pkg+'::number:set', function benchmark( b ) { +bench( format( '%s::number:set', pkg ), function benchmark( b ) { var values; var arr; var N; @@ -57,7 +58,7 @@ bench( pkg+'::number:set', function benchmark( b ) { b.end(); }); -bench( pkg+'::array:set', function benchmark( b ) { +bench( format( '%s::array:set', pkg ), function benchmark( b ) { var values; var arr; var N; @@ -86,7 +87,7 @@ bench( pkg+'::array:set', function benchmark( b ) { b.end(); }); -bench( pkg+'::typed_array:set', function benchmark( b ) { +bench( format( '%s::typed_array:set', pkg ), function benchmark( b ) { var values; var arr; var buf; diff --git a/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.set.length.js b/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.set.length.js index 885f756b4b89..1b5fc83f9eeb 100644 --- a/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.set.length.js +++ b/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.set.length.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var randu = require( '@stdlib/random/array/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float64ArrayLE = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':set:len='+len, f ); + bench( format( '%s:set:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.to_string.js b/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.to_string.js index c3ebf9c28393..3fe5a57320a8 100644 --- a/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.to_string.js +++ b/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.to_string.js @@ -21,13 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float64ArrayLE = require( './../lib' ); // MAIN // -bench( pkg+':toString', function benchmark( b ) { +bench( format( '%s:toString', pkg ), function benchmark( b ) { var out; var arr; var i; diff --git a/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.to_string.length.js b/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.to_string.length.js index 10a65c566271..e2b013f83738 100644 --- a/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.to_string.length.js +++ b/lib/node_modules/@stdlib/array/little-endian-float64/benchmark/benchmark.to_string.length.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeroTo = require( '@stdlib/array/zero-to' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float64ArrayLE = require( './../lib' ); @@ -87,7 +88,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':toString:len='+len, f ); + bench( format( '%s:toString:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/logspace/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/logspace/benchmark/benchmark.length.js index caff56d56232..53fa6a237388 100644 --- a/lib/node_modules/@stdlib/array/logspace/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/logspace/benchmark/benchmark.length.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var randu = require( '@stdlib/random/base/randu' ); var isArray = require( '@stdlib/assert/is-array' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var logspace = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/mostly-safe-casts/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/mostly-safe-casts/benchmark/benchmark.js index c33d252cdfb1..420d4877de16 100644 --- a/lib/node_modules/@stdlib/array/mostly-safe-casts/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/mostly-safe-casts/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isStringArray = require( '@stdlib/assert/is-string-array' ).primitives; var dtypes = require( '@stdlib/array/dtypes' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mostlySafeCasts = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::dtype', function benchmark( b ) { +bench( format( '%s::dtype', pkg ), function benchmark( b ) { var out; var dt; var i; diff --git a/lib/node_modules/@stdlib/array/mskfilter/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/mskfilter/benchmark/benchmark.js index 66641ff16d9e..58ac776e8eb6 100644 --- a/lib/node_modules/@stdlib/array/mskfilter/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/mskfilter/benchmark/benchmark.js @@ -24,13 +24,14 @@ var bench = require( '@stdlib/bench' ); var isArray = require( '@stdlib/assert/is-array' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var ones = require( '@stdlib/array/base/ones' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskfilter = require( './../lib' ); // MAIN // -bench( pkg+'::copy:len=100', function benchmark( b ) { +bench( format( '%s::copy:len=100', pkg ), function benchmark( b ) { var x; var y; var i; diff --git a/lib/node_modules/@stdlib/array/mskfilter/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/mskfilter/benchmark/benchmark.length.js index f9f890632a17..9f2c5c2f1048 100644 --- a/lib/node_modules/@stdlib/array/mskfilter/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/mskfilter/benchmark/benchmark.length.js @@ -25,6 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var ones = require( '@stdlib/array/base/ones' ); var isArray = require( '@stdlib/assert/is-array' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskfilter = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/mskput/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/mskput/benchmark/benchmark.js index 31a8a03c4af1..0052fba4d726 100644 --- a/lib/node_modules/@stdlib/array/mskput/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/mskput/benchmark/benchmark.js @@ -24,13 +24,14 @@ var bench = require( '@stdlib/bench' ); var isArray = require( '@stdlib/assert/is-array' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var zeros = require( '@stdlib/array/base/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskput = require( './../lib' ); // MAIN // -bench( pkg+'::no_broadcasting:len=100', function benchmark( b ) { +bench( format( '%s::no_broadcasting:len=100', pkg ), function benchmark( b ) { var mask; var x; var i; @@ -54,7 +55,7 @@ bench( pkg+'::no_broadcasting:len=100', function benchmark( b ) { b.end(); }); -bench( pkg+'::broadcasting:len=100', function benchmark( b ) { +bench( format( '%s::broadcasting:len=100', pkg ), function benchmark( b ) { var mask; var x; var i; diff --git a/lib/node_modules/@stdlib/array/mskput/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/mskput/benchmark/benchmark.length.js index 30b1a4785953..2251769273d0 100644 --- a/lib/node_modules/@stdlib/array/mskput/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/mskput/benchmark/benchmark.length.js @@ -25,6 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var zeros = require( '@stdlib/array/base/zeros' ); var isArray = require( '@stdlib/assert/is-array' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskput = require( './../lib' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/mskreject/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/mskreject/benchmark/benchmark.js index ba6fbf639468..57f9374186f9 100644 --- a/lib/node_modules/@stdlib/array/mskreject/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/mskreject/benchmark/benchmark.js @@ -24,13 +24,14 @@ var bench = require( '@stdlib/bench' ); var isArray = require( '@stdlib/assert/is-array' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var zeros = require( '@stdlib/array/base/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskreject = require( './../lib' ); // MAIN // -bench( pkg+'::copy:len=100', function benchmark( b ) { +bench( format( '%s::copy:len=100', pkg ), function benchmark( b ) { var x; var y; var i; diff --git a/lib/node_modules/@stdlib/array/mskreject/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/mskreject/benchmark/benchmark.length.js index df920c3830ac..6995228dbd2d 100644 --- a/lib/node_modules/@stdlib/array/mskreject/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/mskreject/benchmark/benchmark.length.js @@ -25,6 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var zeros = require( '@stdlib/array/base/zeros' ); var isArray = require( '@stdlib/assert/is-array' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskreject = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/array/next-dtype/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/next-dtype/benchmark/benchmark.js index 87a8c4b8bcdf..4fe76fc5fee1 100644 --- a/lib/node_modules/@stdlib/array/next-dtype/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/next-dtype/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var dtypes = require( '@stdlib/array/dtypes' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nextDataType = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::dtype', function benchmark( b ) { +bench( format( '%s::dtype', pkg ), function benchmark( b ) { var out; var dt; var i; diff --git a/lib/node_modules/@stdlib/assert/is-readable-property-in/benchmark/benchmark.js b/lib/node_modules/@stdlib/assert/is-readable-property-in/benchmark/benchmark.js index 63a39eb62326..c337b6b08758 100644 --- a/lib/node_modules/@stdlib/assert/is-readable-property-in/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/assert/is-readable-property-in/benchmark/benchmark.js @@ -18,6 +18,8 @@ 'use strict'; +'use strict'; + // MODULES // var bench = require( '@stdlib/bench' ); @@ -33,7 +35,8 @@ bench( pkg, function benchmark( b ) { var arr; var i; - arr = new Array( 100 ); + arr = []; + arr.length = 100; b.tic(); for ( i = 0; i < b.iterations; i++ ) { diff --git a/lib/node_modules/@stdlib/blas/base/dcabs1/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/base/dcabs1/benchmark/benchmark.native.js index 9aa8bd307d43..87aa54e4ca3b 100644 --- a/lib/node_modules/@stdlib/blas/base/dcabs1/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/base/dcabs1/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -40,7 +41,7 @@ var rand = discreteUniform( -500.0, 500.0 ); // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var values; var y; var i; diff --git a/lib/node_modules/@stdlib/blas/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/docs/types/index.d.ts index 855c6d22d5aa..55cce5dc9f4a 100644 --- a/lib/node_modules/@stdlib/blas/base/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/base/docs/types/index.d.ts @@ -466,12 +466,12 @@ interface Namespace { * @param K - number of columns in the matrix `op(A)` and number of rows in the matrix `op(B)` * @param alpha - scalar constant * @param A - first matrix - * @param LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) + * @param LDA - stride between successive contiguous vectors of the matrix `A` (a.k.a., leading dimension of the matrix `A`) * @param B - second matrix - * @param LDB - stride of the first dimension of `B` (a.k.a., leading dimension of the matrix `B`) + * @param LDB - stride between successive contiguous vectors of the matrix `B` (a.k.a., leading dimension of the matrix `B`) * @param beta - scalar constant * @param C - third matrix - * @param LDC - stride of the first dimension of `C` (a.k.a., leading dimension of the matrix `C`) + * @param LDC - stride between successive contiguous vectors of the matrix `C` (a.k.a., leading dimension of the matrix `C`) * @returns `C` * * @example diff --git a/lib/node_modules/@stdlib/blas/base/drotg/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/drotg/benchmark/benchmark.js index c4193eda5229..e96f650ecdcc 100644 --- a/lib/node_modules/@stdlib/blas/base/drotg/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/drotg/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var drotg = require( './../lib' ); @@ -61,7 +62,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+':assign', function benchmark( b ) { +bench( format( '%s:assign', pkg ), function benchmark( b ) { var out; var x; var y; diff --git a/lib/node_modules/@stdlib/blas/base/drotm/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/drotm/benchmark/benchmark.js index 58bc64efa902..2a59369a9516 100644 --- a/lib/node_modules/@stdlib/blas/base/drotm/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/drotm/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var drotm = require( './../lib/drotm.js' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/drotm/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/base/drotm/benchmark/benchmark.native.js index c5d4f7b3e91a..05eef1f50171 100644 --- a/lib/node_modules/@stdlib/blas/base/drotm/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/base/drotm/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/drotm/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/drotm/benchmark/benchmark.ndarray.js index dcffeb06bbe0..2f4467f86fd5 100644 --- a/lib/node_modules/@stdlib/blas/base/drotm/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/drotm/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var drotm = require( './../lib/ndarray.js' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/drotm/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/base/drotm/benchmark/benchmark.ndarray.native.js index c9f7bbddb295..280a0137005a 100644 --- a/lib/node_modules/@stdlib/blas/base/drotm/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/base/drotm/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/dsyr/README.md b/lib/node_modules/@stdlib/blas/base/dsyr/README.md index 2c37c5482c79..e20d2152f1d1 100644 --- a/lib/node_modules/@stdlib/blas/base/dsyr/README.md +++ b/lib/node_modules/@stdlib/blas/base/dsyr/README.md @@ -307,7 +307,7 @@ int main( void ) { // Print the result: for ( int i = 0; i < N*N; i++ ) { - printf( "A2[ %i ] = %lf\n", i, A[ i ] ); + printf( "A2[ %i ] = %lf\n", i, A2[ i ] ); } } ``` diff --git a/lib/node_modules/@stdlib/blas/base/dsyr/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/dsyr/benchmark/benchmark.js index d8b526ca4682..c6536498a4e5 100644 --- a/lib/node_modules/@stdlib/blas/base/dsyr/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/dsyr/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var ones = require( '@stdlib/array/ones' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsyr = require( './../lib/dsyr.js' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); f = createBenchmark( N ); - bench( pkg+':size='+(N*N), f ); + bench( format( '%s:size=%d', pkg, N*N ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/dsyr/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/base/dsyr/benchmark/benchmark.native.js index ec7bf95c8b72..4ccb1102cb1c 100644 --- a/lib/node_modules/@stdlib/blas/base/dsyr/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/base/dsyr/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var ones = require( '@stdlib/array/ones' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); f = createBenchmark( N ); - bench( pkg+'::native:size='+(N*N), opts, f ); + bench( format( '%s::native:size=%d', pkg, N*N ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/dsyr/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/dsyr/benchmark/benchmark.ndarray.js index 7d1a7e3c9ad1..cfdbb8e27b87 100644 --- a/lib/node_modules/@stdlib/blas/base/dsyr/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/dsyr/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var ones = require( '@stdlib/array/ones' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsyr = require( './../lib/ndarray.js' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); f = createBenchmark( N ); - bench( pkg+':ndarray:size='+(N*N), f ); + bench( format( '%s:ndarray:size=%d', pkg, N*N ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/dsyr/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/base/dsyr/benchmark/benchmark.ndarray.native.js index d9c133e73870..d5a035b146b0 100644 --- a/lib/node_modules/@stdlib/blas/base/dsyr/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/base/dsyr/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var ones = require( '@stdlib/array/ones' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); f = createBenchmark( N ); - bench( pkg+'::native:ndarray:size='+(N*N), opts, f ); + bench( format( '%s::native:ndarray:size=%d', pkg, N*N ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/dsyr2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/dsyr2/benchmark/benchmark.js index 1ed4902b29e4..32ae734a5efe 100644 --- a/lib/node_modules/@stdlib/blas/base/dsyr2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/dsyr2/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var ones = require( '@stdlib/array/ones' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsyr2 = require( './../lib/dsyr2.js' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); f = createBenchmark( N ); - bench( pkg+':size='+(N*N), f ); + bench( format( '%s:size=%d', pkg, N*N ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/dsyr2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/base/dsyr2/benchmark/benchmark.native.js index 0ce3799353f6..610ad0779f2f 100644 --- a/lib/node_modules/@stdlib/blas/base/dsyr2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/base/dsyr2/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var ones = require( '@stdlib/array/ones' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); f = createBenchmark( N ); - bench( pkg+'::native:size='+(N*N), opts, f ); + bench( format( '%s::native:size=%d', pkg, N*N ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/dsyr2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/dsyr2/benchmark/benchmark.ndarray.js index 3685431ce0d1..0f1683704d33 100644 --- a/lib/node_modules/@stdlib/blas/base/dsyr2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/dsyr2/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var ones = require( '@stdlib/array/ones' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsyr2 = require( './../lib/ndarray.js' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); f = createBenchmark( N ); - bench( pkg+':ndarray:size='+(N*N), f ); + bench( format( '%s:ndarray:size=%d', pkg, N*N ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/dsyr2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/base/dsyr2/benchmark/benchmark.ndarray.native.js index 534af4370389..522b0d96d7c7 100644 --- a/lib/node_modules/@stdlib/blas/base/dsyr2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/base/dsyr2/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var ones = require( '@stdlib/array/ones' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); f = createBenchmark( N ); - bench( pkg+'::native:ndarray:size='+(N*N), opts, f ); + bench( format( '%s::native:ndarray:size=%d', pkg, N*N ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/dtrsv/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/base/dtrsv/test/test.ndarray.js index 6738f6b22dca..3c5f0cec0d3c 100644 --- a/lib/node_modules/@stdlib/blas/base/dtrsv/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/dtrsv/test/test.ndarray.js @@ -46,7 +46,6 @@ var rsa1nsa2 = require( './fixtures/row_major_sa1n_sa2.json' ); var rsa1sa2n = require( './fixtures/row_major_sa1_sa2n.json' ); var rsa1nsa2n = require( './fixtures/row_major_sa1n_sa2n.json' ); var rcap = require( './fixtures/row_major_complex_access_pattern.json' ); - var clntnu = require( './fixtures/column_major_l_nt_nu.json' ); var cltnu = require( './fixtures/column_major_l_t_nu.json' ); var clntu = require( './fixtures/column_major_l_nt_u.json' ); @@ -62,7 +61,7 @@ var cox = require( './fixtures/column_major_ox.json' ); var csa1sa2 = require( './fixtures/column_major_sa1_sa2.json' ); var csa1nsa2 = require( './fixtures/column_major_sa1n_sa2.json' ); var csa1sa2n = require( './fixtures/column_major_sa1_sa2n.json' ); -var csa1nsa2n = require( './fixtures/column_major_sa1_sa2n.json' ); +var csa1nsa2n = require( './fixtures/column_major_sa1n_sa2n.json' ); var ccap = require( './fixtures/column_major_complex_access_pattern.json' ); diff --git a/lib/node_modules/@stdlib/blas/base/gaxpy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/gaxpy/benchmark/benchmark.js index 8abc989b8969..1ef50cf10fd0 100644 --- a/lib/node_modules/@stdlib/blas/base/gaxpy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/gaxpy/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gaxpy = require( './../lib' ); @@ -96,7 +97,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/gaxpy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/gaxpy/benchmark/benchmark.ndarray.js index 2eaab7a2e02e..f469d255f9b7 100644 --- a/lib/node_modules/@stdlib/blas/base/gaxpy/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/gaxpy/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gaxpy = require( './../lib' ).ndarray; @@ -96,7 +97,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/gcopy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/gcopy/benchmark/benchmark.js index c5ccae93c66a..27a71bed9066 100644 --- a/lib/node_modules/@stdlib/blas/base/gcopy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/gcopy/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gcopy = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/gcopy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/gcopy/benchmark/benchmark.ndarray.js index 913c2d5cb445..b382d5b09ac9 100644 --- a/lib/node_modules/@stdlib/blas/base/gcopy/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/gcopy/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gcopy = require( './../lib' ).ndarray; @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/gsyr/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/base/gsyr/test/test.ndarray.js index 38f2b3c5a394..51312eaa0853 100644 --- a/lib/node_modules/@stdlib/blas/base/gsyr/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/gsyr/test/test.ndarray.js @@ -41,7 +41,6 @@ var rsa1nsa2 = require( './fixtures/row_major_sa1n_sa2.json' ); var rsa1sa2n = require( './fixtures/row_major_sa1_sa2n.json' ); var rsa1nsa2n = require( './fixtures/row_major_sa1n_sa2n.json' ); var rcap = require( './fixtures/row_major_complex_access_pattern.json' ); - var cu = require( './fixtures/column_major_u.json' ); var cl = require( './fixtures/column_major_l.json' ); var cxp = require( './fixtures/column_major_xp.json' ); diff --git a/lib/node_modules/@stdlib/blas/base/matrix-orientation-resolve-enum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/matrix-orientation-resolve-enum/benchmark/benchmark.js index 39d5f6915895..8318a6ea5478 100644 --- a/lib/node_modules/@stdlib/blas/base/matrix-orientation-resolve-enum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/matrix-orientation-resolve-enum/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var str2enum = require( '@stdlib/blas/base/matrix-orientation-str2enum' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var resolve = require( './../lib' ); // MAIN // -bench( pkg+'::string', function benchmark( b ) { +bench( format( '%s::string', pkg ), function benchmark( b ) { var values; var out; var i; @@ -54,7 +55,7 @@ bench( pkg+'::string', function benchmark( b ) { b.end(); }); -bench( pkg+'::integer', function benchmark( b ) { +bench( format( '%s::integer', pkg ), function benchmark( b ) { var values; var out; var i; diff --git a/lib/node_modules/@stdlib/blas/base/matrix-triangle-resolve-enum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/matrix-triangle-resolve-enum/benchmark/benchmark.js index f7c84bd1d15b..be906655d271 100644 --- a/lib/node_modules/@stdlib/blas/base/matrix-triangle-resolve-enum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/matrix-triangle-resolve-enum/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var str2enum = require( '@stdlib/blas/base/matrix-triangle-str2enum' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var resolve = require( './../lib' ); // MAIN // -bench( pkg+'::string', function benchmark( b ) { +bench( format( '%s::string', pkg ), function benchmark( b ) { var values; var out; var i; @@ -54,7 +55,7 @@ bench( pkg+'::string', function benchmark( b ) { b.end(); }); -bench( pkg+'::integer', function benchmark( b ) { +bench( format( '%s::integer', pkg ), function benchmark( b ) { var values; var out; var i; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/README.md index f29b88ecb016..80aa93d66b8b 100644 --- a/lib/node_modules/@stdlib/blas/base/ndarray/README.md +++ b/lib/node_modules/@stdlib/blas/base/ndarray/README.md @@ -46,10 +46,13 @@ The namespace exposes the following APIs:
- [`dasum( arrays )`][@stdlib/blas/base/ndarray/dasum]: calculate the sum of absolute values for all elements in a one-dimensional double-precision floating-point ndarray. +- [`daxpy( arrays )`][@stdlib/blas/base/ndarray/daxpy]: multiply a one-dimensional double-precision floating-point ndarray `x` by a constant `alpha` and add the result to a one-dimensional double-precision floating-point ndarray `y`. - [`ddot( arrays )`][@stdlib/blas/base/ndarray/ddot]: calculate the dot product of two one-dimensional double-precision floating-point ndarrays. - [`gasum( arrays )`][@stdlib/blas/base/ndarray/gasum]: calculate the sum of absolute values for all elements in a one-dimensional ndarray. +- [`gaxpy( arrays )`][@stdlib/blas/base/ndarray/gaxpy]: multiply a one-dimensional ndarray `x` by a constant `alpha` and add the result to a one-dimensional ndarray `y`. - [`gdot( arrays )`][@stdlib/blas/base/ndarray/gdot]: calculate the dot product of two one-dimensional ndarrays. - [`sasum( arrays )`][@stdlib/blas/base/ndarray/sasum]: calculate the sum of absolute values for all elements in a one-dimensional single-precision floating-point ndarray. +- [`saxpy( arrays )`][@stdlib/blas/base/ndarray/saxpy]: multiply a one-dimensional single-precision floating-point ndarray `x` by a constant `alpha` and add the result to a one-dimensional single-precision floating-point ndarray `y`. - [`sdot( arrays )`][@stdlib/blas/base/ndarray/sdot]: calculate the dot product of two one-dimensional single-precision floating-point ndarrays.
@@ -95,14 +98,20 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/base/ndarray/dasum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/dasum +[@stdlib/blas/base/ndarray/daxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/daxpy + [@stdlib/blas/base/ndarray/ddot]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/ddot [@stdlib/blas/base/ndarray/gasum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/gasum +[@stdlib/blas/base/ndarray/gaxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/gaxpy + [@stdlib/blas/base/ndarray/gdot]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/gdot [@stdlib/blas/base/ndarray/sasum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/sasum +[@stdlib/blas/base/ndarray/saxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/saxpy + [@stdlib/blas/base/ndarray/sdot]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/sdot diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/README.md new file mode 100644 index 000000000000..17f3ba791032 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/README.md @@ -0,0 +1,124 @@ + + +# daxpy + +> Multiply a one-dimensional double-precision floating-point ndarray `x` by a constant `alpha` and add the result to a one-dimensional double-precision floating-point ndarray `y`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var daxpy = require( '@stdlib/blas/base/ndarray/daxpy' ); +``` + +#### daxpy( arrays ) + +Multiplies a one-dimensional double-precision floating-point ndarray `x` by a constant `alpha` and adds the result to a one-dimensional double-precision floating-point ndarray `y`. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); + +var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +var x = new ndarray( 'float64', xbuf, [ 5 ], [ 1 ], 0, 'row-major' ); + +var ybuf = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] ); +var y = new ndarray( 'float64', ybuf, [ 5 ], [ 1 ], 0, 'row-major' ); + +var alpha = scalar2ndarray( 5.0, 'float64', 'row-major' ); +var z = daxpy( [ x, y, alpha ] ); +// returns [ 6.0, 11.0, 16.0, 21.0, 26.0 ] + +var bool = ( y === z ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var daxpy = require( '@stdlib/blas/base/ndarray/daxpy' ); + +var opts = { + 'dtype': 'float64' +}; + +var xbuf = discreteUniform( 10, 0, 100, opts ); +var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var ybuf = discreteUniform( xbuf.length, 0, 10, opts ); +var y = new ndarray( opts.dtype, ybuf, [ ybuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( y ) ); + +var alpha = scalar2ndarray( 5.0, opts ); +var out = daxpy( [ x, y, alpha ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/benchmark/benchmark.js new file mode 100644 index 000000000000..c8e1e3533e21 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/benchmark/benchmark.js @@ -0,0 +1,118 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var daxpy = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len, -100.0, 100.0, options ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + + ybuf = uniform( len, -100.0, 100.0, options ); + y = new ndarray( options.dtype, ybuf, [ len ], [ 1 ], 0, 'row-major' ); + + alpha = scalar2ndarray( 5.0, options.dtype, 'row-major' ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = daxpy( [ x, y, alpha ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( z.get( i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/docs/repl.txt new file mode 100644 index 000000000000..025ad5db6efe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/docs/repl.txt @@ -0,0 +1,40 @@ + +{{alias}}( arrays ) + Multiplies a one-dimensional double-precision floating-point ndarray `x` + by a constant `alpha` and adds the result to a one-dimensional double- + precision floating-point ndarray `y`. + + If provided an empty input ndarray, the function returns the output ndarray + unchanged. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing an input ndarray, an output ndarray, and + a zero-dimensional ndarray containing a scalar constant `alpha`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = new {{alias:@stdlib/array/float64}}( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ); + > var ybuf = new {{alias:@stdlib/array/float64}}( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ); + > var dt = 'float64'; + > var sh = [ xbuf.length ]; + > var st = [ 1 ]; + > var oo = 0; + > var ord = 'row-major'; + > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, st, oo, ord ); + > var y = new {{alias:@stdlib/ndarray/ctor}}( dt, ybuf, sh, st, oo, ord ); + > var alpha = {{alias:@stdlib/ndarray/base/from-scalar}}( 5.0, dt, ord ); + + > {{alias}}( [ x, y, alpha ] ); + > y + [ 22.0, 16.0, -16.0, 21.0, 3.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/docs/types/index.d.ts new file mode 100644 index 000000000000..faf2d1ff5d89 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/docs/types/index.d.ts @@ -0,0 +1,55 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float64ndarray } from '@stdlib/types/ndarray'; + +/** +* Multiplies a one-dimensional double-precision floating-point ndarray `x` by a constant `alpha` and adds the result to a one-dimensional double-precision floating-point ndarray `y`. +* +* @param arrays - array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant +* @returns output ndarray +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var x = new ndarray( 'float64', xbuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var ybuf = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] ); +* var y = new ndarray( 'float64', ybuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var alpha = scalar2ndarray( 5.0, 'float64', 'row-major' ); +* +* var z = daxpy( [ x, y, alpha ] ); +* // returns [ 6.0, 11.0, 16.0, 21.0, 26.0 ] +* +* var bool = ( z === y ); +* // returns true +*/ +declare function daxpy( arrays: [ float64ndarray, float64ndarray, float64ndarray ] ): float64ndarray; + + +// EXPORTS // + +export = daxpy; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/docs/types/test.ts new file mode 100644 index 000000000000..d81e6e3f8a30 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/docs/types/test.ts @@ -0,0 +1,69 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import daxpy = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const y = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const alpha = zeros( [], { + 'dtype': 'float64' + }); + + daxpy( [ x, y, alpha ] ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + daxpy( '10' ); // $ExpectError + daxpy( 10 ); // $ExpectError + daxpy( true ); // $ExpectError + daxpy( false ); // $ExpectError + daxpy( null ); // $ExpectError + daxpy( undefined ); // $ExpectError + daxpy( [] ); // $ExpectError + daxpy( {} ); // $ExpectError + daxpy( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const y = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const alpha = zeros( [], { + 'dtype': 'float64' + }); + + daxpy(); // $ExpectError + daxpy( [ x, y, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/examples/index.js new file mode 100644 index 000000000000..4f094f632d67 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var daxpy = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var xbuf = discreteUniform( 10, 0, 100, opts ); +var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var ybuf = discreteUniform( xbuf.length, 0, 10, opts ); +var y = new ndarray( opts.dtype, ybuf, [ ybuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( y ) ); + +var alpha = scalar2ndarray( 5.0, opts ); +var out = daxpy( [ x, y, alpha ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/lib/index.js new file mode 100644 index 000000000000..8d71d0e054e4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 1 routine to multiply a one-dimensional double-precision floating-point ndarray `x` by a constant `alpha` and add the result to a one-dimensional double-precision floating-point ndarray `y`. +* +* @module @stdlib/blas/base/ndarray/daxpy +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* var daxpy = require( '@stdlib/blas/base/ndarray/daxpy' ); +* +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var x = new ndarray( 'float64', xbuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var ybuf = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] ); +* var y = new ndarray( 'float64', ybuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var alpha = scalar2ndarray( 5.0, 'float64', 'row-major' ); +* +* var z = daxpy( [ x, y, alpha ] ); +* // returns [ 6.0, 11.0, 16.0, 21.0, 26.0 ] +* +* var bool = ( z === y ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/lib/main.js new file mode 100644 index 000000000000..a849e320e624 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/lib/main.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/daxpy' ).ndarray; + + +// MAIN // + +/** +* Multiplies a one-dimensional double-precision floating-point ndarray `x` by a constant `alpha` and adds the result to a one-dimensional double-precision floating-point ndarray `y`. +* +* @param {ArrayLikeObject} arrays - array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant +* @returns {Object} output ndarray +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var x = new ndarray( 'float64', xbuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var ybuf = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] ); +* var y = new ndarray( 'float64', ybuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var alpha = scalar2ndarray( 5.0, 'float64', 'row-major' ); +* +* var z = daxpy( [ x, y, alpha ] ); +* // returns [ 6.0, 11.0, 16.0, 21.0, 26.0 ] +* +* var bool = ( z === y ); +* // returns true +*/ +function daxpy( arrays ) { + var alpha = ndarraylike2scalar( arrays[ 2 ] ); + var x = arrays[ 0 ]; + var y = arrays[ 1 ]; + strided( numelDimension( x, 0 ), alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) ); // eslint-disable-line max-len + return y; +} + + +// EXPORTS // + +module.exports = daxpy; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/package.json new file mode 100644 index 000000000000..063e2a0aa167 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/blas/base/ndarray/daxpy", + "version": "0.0.0", + "description": "Multiply a one-dimensional double-precision floating-point ndarray `x` by a constant `alpha` and add the result to a one-dimensional double-precision floating-point ndarray `y`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 1", + "daxpy", + "linear", + "algebra", + "subroutines", + "saxpy", + "gaxpy", + "add", + "alpha", + "vector", + "array", + "ndarray", + "float64", + "double", + "float64array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/test/test.js new file mode 100644 index 000000000000..7537ba315a48 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/daxpy/test/test.js @@ -0,0 +1,234 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var daxpy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof daxpy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( daxpy.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies one-dimensional ndarray `x` by a constant `alpha` and adds the result to one-dimensional ndarray `y`', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var x; + var y; + var v; + + xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + ybuf = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] ); + x = vector( xbuf, 5, 1, 0 ); + y = vector( ybuf, 5, 1, 0 ); + alpha = scalar2ndarray( 2.0, 'float64', 'row-major' ); + + v = daxpy( [ x, y, alpha ] ); + + expected = new Float64Array( [ 3.0, 5.0, 7.0, 9.0, 11.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = new Float64Array( [ 1.0, 2.0 ] ); + ybuf = new Float64Array( [ 1.0, 1.0 ] ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + alpha = scalar2ndarray( 2.0, 'float64', 'row-major' ); + + v = daxpy( [ x, y, alpha ] ); + + expected = new Float64Array( [ 3.0, 5.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided empty ndarrays, the function returns the output ndarray unchanged', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var x; + var y; + var v; + + xbuf = new Float64Array( [] ); + ybuf = new Float64Array( [] ); + x = vector( xbuf, 0, 1, 0 ); + y = vector( ybuf, 0, 1, 0 ); + alpha = scalar2ndarray( 5.0, 'float64', 'row-major' ); + + v = daxpy( [ x, y, alpha ] ); + + expected = new Float64Array( [] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var x; + var y; + var v; + + xbuf = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + x = vector( xbuf, 3, 2, 0 ); + + ybuf = new Float64Array([ + 1.0, // 0 + 1.0, // 1 + 1.0, // 2 + 1.0, + 1.0 + ]); + y = vector( ybuf, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, 'float64', 'row-major' ); + + v = daxpy( [ x, y, alpha ] ); + + expected = new Float64Array( [ 3.0, 7.0, 11.0, 1.0, 1.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var x; + var y; + var v; + + xbuf = new Float64Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + x = vector( xbuf, 3, -2, 4 ); + + ybuf = new Float64Array([ + 6.0, // 2 + 7.0, // 1 + 8.0, // 0 + 9.0, + 10.0 + ]); + y = vector( ybuf, 3, -1, 2 ); + alpha = scalar2ndarray( 3.0, 'float64', 'row-major' ); + + v = daxpy( [ x, y, alpha ] ); + + expected = new Float64Array( [ 9.0, 16.0, 23.0, 9.0, 10.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var x; + var y; + var v; + + xbuf = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + x = vector( xbuf, 4, 2, 1 ); + + ybuf = new Float64Array([ + 1.0, + 2.0, + 3.0, // 0 + 4.0, // 1 + 5.0, // 2 + 6.0, // 3 + 7.0, + 8.0 + ]); + y = vector( ybuf, 4, 1, 2 ); + alpha = scalar2ndarray( 3.0, 'float64', 'row-major' ); + + v = daxpy( [ x, y, alpha ] ); + + expected = new Float64Array( [ 1.0, 2.0, 6.0, -2.0, 11.0, 18.0, 7.0, 8.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ddot/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/ddot/benchmark/benchmark.js index e30d9c133f22..b0f622b5c064 100644 --- a/lib/node_modules/@stdlib/blas/base/ndarray/ddot/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ddot/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ddot = require( './../lib' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/docs/types/index.d.ts index db43a8ae4b05..4f192341f0f9 100644 --- a/lib/node_modules/@stdlib/blas/base/ndarray/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/base/ndarray/docs/types/index.d.ts @@ -21,10 +21,13 @@ /* eslint-disable max-lines */ import dasum = require( '@stdlib/blas/base/ndarray/dasum' ); +import daxpy = require( '@stdlib/blas/base/ndarray/daxpy' ); import ddot = require( '@stdlib/blas/base/ndarray/ddot' ); import gasum = require( '@stdlib/blas/base/ndarray/gasum' ); +import gaxpy = require( '@stdlib/blas/base/ndarray/gaxpy' ); import gdot = require( '@stdlib/blas/base/ndarray/gdot' ); import sasum = require( '@stdlib/blas/base/ndarray/sasum' ); +import saxpy = require( '@stdlib/blas/base/ndarray/saxpy' ); import sdot = require( '@stdlib/blas/base/ndarray/sdot' ); /** @@ -49,6 +52,33 @@ interface Namespace { */ dasum: typeof dasum; + /** + * Multiplies a one-dimensional double-precision floating-point ndarray `x` by a constant `alpha` and adds the result to a one-dimensional double-precision floating-point ndarray `y`. + * + * @param arrays - array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant + * @returns output ndarray + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); + * var ndarray = require( '@stdlib/ndarray/base/ctor' ); + * + * var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + * var x = new ndarray( 'float64', xbuf, [ 5 ], [ 1 ], 0, 'row-major' ); + * + * var ybuf = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] ); + * var y = new ndarray( 'float64', ybuf, [ 5 ], [ 1 ], 0, 'row-major' ); + * + * var alpha = scalar2ndarray( 5.0, 'float64', 'row-major' ); + * + * var z = ns.daxpy( [ x, y, alpha ] ); + * // returns [ 6.0, 11.0, 16.0, 21.0, 26.0 ] + * + * var bool = ( z === y ); + * // returns true + */ + daxpy: typeof daxpy; + /** * Computes the dot product of two one-dimensional double-precision floating-point ndarrays. * @@ -87,6 +117,32 @@ interface Namespace { */ gasum: typeof gasum; + /** + * Multiplies a one-dimensional ndarray `x` by a constant `alpha` and adds the result to a one-dimensional ndarray `y`. + * + * @param arrays - array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant + * @returns output ndarray + * + * @example + * var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); + * var ndarray = require( '@stdlib/ndarray/base/ctor' ); + * + * var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0 ]; + * var x = new ndarray( 'generic', xbuf, [ 5 ], [ 1 ], 0, 'row-major' ); + * + * var ybuf = [ 1.0, 1.0, 1.0, 1.0, 1.0 ]; + * var y = new ndarray( 'generic', ybuf, [ 5 ], [ 1 ], 0, 'row-major' ); + * + * var alpha = scalar2ndarray( 5.0, 'generic', 'row-major' ); + * + * var z = ns.gaxpy( [ x, y, alpha ] ); + * // returns [ 6.0, 11.0, 16.0, 21.0, 26.0 ] + * + * var bool = ( z === y ); + * // returns true + */ + gaxpy: typeof gaxpy; + /** * Computes the dot product of two one-dimensional ndarrays. * @@ -125,6 +181,33 @@ interface Namespace { */ sasum: typeof sasum; + /** + * Multiplies a one-dimensional single-precision floating-point ndarray `x` by a constant `alpha` and adds the result to a one-dimensional single-precision floating-point ndarray `y`. + * + * @param arrays - array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant + * @returns output ndarray + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); + * var ndarray = require( '@stdlib/ndarray/base/ctor' ); + * + * var xbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + * var x = new ndarray( 'float32', xbuf, [ 5 ], [ 1 ], 0, 'row-major' ); + * + * var ybuf = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] ); + * var y = new ndarray( 'float32', ybuf, [ 5 ], [ 1 ], 0, 'row-major' ); + * + * var alpha = scalar2ndarray( 5.0, 'float32', 'row-major' ); + * + * var z = ns.saxpy( [ x, y, alpha ] ); + * // returns [ 6.0, 11.0, 16.0, 21.0, 26.0 ] + * + * var bool = ( z === y ); + * // returns true + */ + saxpy: typeof saxpy; + /** * Computes the dot product of two one-dimensional single-precision floating-point ndarrays. * diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/README.md new file mode 100644 index 000000000000..c55989bde0a6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/README.md @@ -0,0 +1,123 @@ + + +# gaxpy + +> Multiply a one-dimensional ndarray `x` by a constant `alpha` and add the result to a one-dimensional ndarray `y`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var gaxpy = require( '@stdlib/blas/base/ndarray/gaxpy' ); +``` + +#### gaxpy( arrays ) + +Multiplies a one-dimensional ndarray `x` by a constant `alpha` and adds the result to a one-dimensional ndarray `y`. + +```javascript +var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); + +var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0 ]; +var x = new ndarray( 'generic', xbuf, [ 5 ], [ 1 ], 0, 'row-major' ); + +var ybuf = [ 1.0, 1.0, 1.0, 1.0, 1.0 ]; +var y = new ndarray( 'generic', ybuf, [ 5 ], [ 1 ], 0, 'row-major' ); + +var alpha = scalar2ndarray( 5.0, 'generic', 'row-major' ); +var z = gaxpy( [ x, y, alpha ] ); +// returns [ 6.0, 11.0, 16.0, 21.0, 26.0 ] + +var bool = ( y === z ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var gaxpy = require( '@stdlib/blas/base/ndarray/gaxpy' ); + +var opts = { + 'dtype': 'generic' +}; + +var xbuf = discreteUniform( 10, 0, 100, opts ); +var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var ybuf = discreteUniform( xbuf.length, 0, 10, opts ); +var y = new ndarray( opts.dtype, ybuf, [ ybuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( y ) ); + +var alpha = scalar2ndarray( 5.0, opts ); +var out = gaxpy( [ x, y, alpha ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/benchmark/benchmark.js new file mode 100644 index 000000000000..76c66e65493f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/benchmark/benchmark.js @@ -0,0 +1,118 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gaxpy = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len, -100.0, 100.0, options ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + + ybuf = uniform( len, -100.0, 100.0, options ); + y = new ndarray( options.dtype, ybuf, [ len ], [ 1 ], 0, 'row-major' ); + + alpha = scalar2ndarray( 5.0, options.dtype, 'row-major' ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = gaxpy( [ x, y, alpha ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( z.get( i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/docs/repl.txt new file mode 100644 index 000000000000..14005cb77fb5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/docs/repl.txt @@ -0,0 +1,39 @@ + +{{alias}}( arrays ) + Multiplies a one-dimensional ndarray `x` by a constant `alpha` and adds the + result to a one-dimensional ndarray `y`. + + If provided an empty input ndarray, the function returns the output ndarray + unchanged. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing an input ndarray, an output ndarray, and + a zero-dimensional ndarray containing a scalar constant `alpha`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 4.0, 2.0, -3.0, 5.0, -1.0 ]; + > var ybuf = [ 2.0, 6.0, -1.0, -4.0, 8.0 ]; + > var dt = 'generic'; + > var sh = [ xbuf.length ]; + > var st = [ 1 ]; + > var oo = 0; + > var ord = 'row-major'; + > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, st, oo, ord ); + > var y = new {{alias:@stdlib/ndarray/ctor}}( dt, ybuf, sh, st, oo, ord ); + > var alpha = {{alias:@stdlib/ndarray/base/from-scalar}}( 5.0, dt, ord ); + + > {{alias}}( [ x, y, alpha ] ); + > y + [ 22.0, 16.0, -16.0, 21.0, 3.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/docs/types/index.d.ts new file mode 100644 index 000000000000..21ea94ac4241 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/docs/types/index.d.ts @@ -0,0 +1,54 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray } from '@stdlib/types/ndarray'; + +/** +* Multiplies a one-dimensional ndarray `x` by a constant `alpha` and adds the result to a one-dimensional ndarray `y`. +* +* @param arrays - array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant +* @returns output ndarray +* +* @example +* var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0 ]; +* var x = new ndarray( 'generic', xbuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var ybuf = [ 1.0, 1.0, 1.0, 1.0, 1.0 ]; +* var y = new ndarray( 'generic', ybuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var alpha = scalar2ndarray( 5.0, 'generic', 'row-major' ); +* +* var z = gaxpy( [ x, y, alpha ] ); +* // returns [ 6.0, 11.0, 16.0, 21.0, 26.0 ] +* +* var bool = ( z === y ); +* // returns true +*/ +declare function gaxpy = typedndarray, U extends typedndarray = typedndarray>( arrays: [ T, U, T ] ): U; + + +// EXPORTS // + +export = gaxpy; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/docs/types/test.ts new file mode 100644 index 000000000000..dd6d2e1c0849 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/docs/types/test.ts @@ -0,0 +1,69 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import gaxpy = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'generic' + }); + const y = zeros( [ 10 ], { + 'dtype': 'generic' + }); + const alpha = zeros( [], { + 'dtype': 'generic' + }); + + gaxpy( [ x, y, alpha ] ); // $ExpectType genericndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + gaxpy( '10' ); // $ExpectError + gaxpy( 10 ); // $ExpectError + gaxpy( true ); // $ExpectError + gaxpy( false ); // $ExpectError + gaxpy( null ); // $ExpectError + gaxpy( undefined ); // $ExpectError + gaxpy( [] ); // $ExpectError + gaxpy( {} ); // $ExpectError + gaxpy( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'generic' + }); + const y = zeros( [ 10 ], { + 'dtype': 'generic' + }); + const alpha = zeros( [], { + 'dtype': 'generic' + }); + + gaxpy(); // $ExpectError + gaxpy( [ x, y, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/examples/index.js new file mode 100644 index 000000000000..52af3298d776 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var gaxpy = require( './../lib' ); + +var opts = { + 'dtype': 'generic' +}; + +var xbuf = discreteUniform( 10, 0, 100, opts ); +var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var ybuf = discreteUniform( xbuf.length, 0, 10, opts ); +var y = new ndarray( opts.dtype, ybuf, [ ybuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( y ) ); + +var alpha = scalar2ndarray( 5.0, opts ); +var out = gaxpy( [ x, y, alpha ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/lib/index.js new file mode 100644 index 000000000000..18dc54f5da68 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/lib/index.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 1 routine to multiply a one-dimensional ndarray `x` by a constant `alpha` and add the result to a one-dimensional ndarray `y`. +* +* @module @stdlib/blas/base/ndarray/gaxpy +* +* @example +* var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* var gaxpy = require( '@stdlib/blas/base/ndarray/gaxpy' ); +* +* var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0 ]; +* var x = new ndarray( 'generic', xbuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var ybuf = [ 1.0, 1.0, 1.0, 1.0, 1.0 ]; +* var y = new ndarray( 'generic', ybuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var alpha = scalar2ndarray( 5.0, 'generic', 'row-major' ); +* +* var z = gaxpy( [ x, y, alpha ] ); +* // returns [ 6.0, 11.0, 16.0, 21.0, 26.0 ] +* +* var bool = ( z === y ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/lib/main.js new file mode 100644 index 000000000000..2057ba423f54 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/lib/main.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/gaxpy' ).ndarray; + + +// MAIN // + +/** +* Multiplies a one-dimensional ndarray `x` by a constant `alpha` and adds the result to a one-dimensional ndarray `y`. +* +* @param {ArrayLikeObject} arrays - array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant +* @returns {Object} output ndarray +* +* @example +* var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0 ]; +* var x = new ndarray( 'generic', xbuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var ybuf = [ 1.0, 1.0, 1.0, 1.0, 1.0 ]; +* var y = new ndarray( 'generic', ybuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var alpha = scalar2ndarray( 5.0, 'generic', 'row-major' ); +* +* var z = gaxpy( [ x, y, alpha ] ); +* // returns [ 6.0, 11.0, 16.0, 21.0, 26.0 ] +* +* var bool = ( z === y ); +* // returns true +*/ +function gaxpy( arrays ) { + var alpha = ndarraylike2scalar( arrays[ 2 ] ); + var x = arrays[ 0 ]; + var y = arrays[ 1 ]; + strided( numelDimension( x, 0 ), alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) ); // eslint-disable-line max-len + return y; +} + + +// EXPORTS // + +module.exports = gaxpy; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/package.json new file mode 100644 index 000000000000..43b738d43677 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/package.json @@ -0,0 +1,72 @@ +{ + "name": "@stdlib/blas/base/ndarray/gaxpy", + "version": "0.0.0", + "description": "Multiply a one-dimensional ndarray `x` by a constant `alpha` and add the result to a one-dimensional ndarray `y`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 1", + "gaxpy", + "linear", + "algebra", + "subroutines", + "daxpy", + "add", + "alpha", + "vector", + "array", + "ndarray", + "generic", + "double", + "typedarray" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/test/test.js new file mode 100644 index 000000000000..61ba09572b6f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gaxpy/test/test.js @@ -0,0 +1,233 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameArray = require( '@stdlib/assert/is-same-array' ); +var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var gaxpy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'generic', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gaxpy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( gaxpy.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies one-dimensional ndarray `x` by a constant `alpha` and adds the result to one-dimensional ndarray `y`', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var x; + var y; + var v; + + xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0 ]; + ybuf = [ 1.0, 1.0, 1.0, 1.0, 1.0 ]; + x = vector( xbuf, 5, 1, 0 ); + y = vector( ybuf, 5, 1, 0 ); + alpha = scalar2ndarray( 2.0, 'generic', 'row-major' ); + + v = gaxpy( [ x, y, alpha ] ); + + expected = [ 3.0, 5.0, 7.0, 9.0, 11.0 ]; + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = [ 1.0, 2.0 ]; + ybuf = [ 1.0, 1.0 ]; + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + alpha = scalar2ndarray( 2.0, 'generic', 'row-major' ); + + v = gaxpy( [ x, y, alpha ] ); + + expected = [ 3.0, 5.0 ]; + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided empty ndarrays, the function returns the output ndarray unchanged', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var x; + var y; + var v; + + xbuf = []; + ybuf = []; + x = vector( xbuf, 0, 1, 0 ); + y = vector( ybuf, 0, 1, 0 ); + alpha = scalar2ndarray( 5.0, 'generic', 'row-major' ); + + v = gaxpy( [ x, y, alpha ] ); + + expected = []; + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var x; + var y; + var v; + + xbuf = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + x = vector( xbuf, 3, 2, 0 ); + + ybuf = [ + 1.0, // 0 + 1.0, // 1 + 1.0, // 2 + 1.0, + 1.0 + ]; + y = vector( ybuf, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, 'generic', 'row-major' ); + + v = gaxpy( [ x, y, alpha ] ); + + expected = [ 3.0, 7.0, 11.0, 1.0, 1.0 ]; + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var x; + var y; + var v; + + xbuf = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + x = vector( xbuf, 3, -2, 4 ); + + ybuf = [ + 6.0, // 2 + 7.0, // 1 + 8.0, // 0 + 9.0, + 10.0 + ]; + y = vector( ybuf, 3, -1, 2 ); + alpha = scalar2ndarray( 3.0, 'generic', 'row-major' ); + + v = gaxpy( [ x, y, alpha ] ); + + expected = [ 9.0, 16.0, 23.0, 9.0, 10.0 ]; + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var x; + var y; + var v; + + xbuf = [ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]; + x = vector( xbuf, 4, 2, 1 ); + + ybuf = [ + 1.0, + 2.0, + 3.0, // 0 + 4.0, // 1 + 5.0, // 2 + 6.0, // 3 + 7.0, + 8.0 + ]; + y = vector( ybuf, 4, 1, 2 ); + alpha = scalar2ndarray( 3.0, 'generic', 'row-major' ); + + v = gaxpy( [ x, y, alpha ] ); + + expected = [ 1.0, 2.0, 6.0, -2.0, 11.0, 18.0, 7.0, 8.0 ]; + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gdot/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/gdot/benchmark/benchmark.js index 2e88dc9cad05..fae741f48077 100644 --- a/lib/node_modules/@stdlib/blas/base/ndarray/gdot/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gdot/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gdot = require( './../lib' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/lib/index.js index 7a951b8152d3..5de30456a6e0 100644 --- a/lib/node_modules/@stdlib/blas/base/ndarray/lib/index.js +++ b/lib/node_modules/@stdlib/blas/base/ndarray/lib/index.js @@ -45,6 +45,15 @@ var ns = {}; */ setReadOnly( ns, 'dasum', require( '@stdlib/blas/base/ndarray/dasum' ) ); +/** +* @name daxpy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/daxpy} +*/ +setReadOnly( ns, 'daxpy', require( '@stdlib/blas/base/ndarray/daxpy' ) ); + /** * @name ddot * @memberof ns @@ -63,6 +72,15 @@ setReadOnly( ns, 'ddot', require( '@stdlib/blas/base/ndarray/ddot' ) ); */ setReadOnly( ns, 'gasum', require( '@stdlib/blas/base/ndarray/gasum' ) ); +/** +* @name gaxpy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/gaxpy} +*/ +setReadOnly( ns, 'gaxpy', require( '@stdlib/blas/base/ndarray/gaxpy' ) ); + /** * @name gdot * @memberof ns @@ -81,6 +99,15 @@ setReadOnly( ns, 'gdot', require( '@stdlib/blas/base/ndarray/gdot' ) ); */ setReadOnly( ns, 'sasum', require( '@stdlib/blas/base/ndarray/sasum' ) ); +/** +* @name saxpy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/saxpy} +*/ +setReadOnly( ns, 'saxpy', require( '@stdlib/blas/base/ndarray/saxpy' ) ); + /** * @name sdot * @memberof ns diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/README.md new file mode 100644 index 000000000000..9ef182459b66 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/README.md @@ -0,0 +1,124 @@ + + +# saxpy + +> Multiply a one-dimensional single-precision floating-point ndarray `x` by a constant `alpha` and add the result to a one-dimensional single-precision floating-point ndarray `y`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var saxpy = require( '@stdlib/blas/base/ndarray/saxpy' ); +``` + +#### saxpy( arrays ) + +Multiplies a one-dimensional single-precision floating-point ndarray `x` by a constant `alpha` and adds the result to a one-dimensional single-precision floating-point ndarray `y`. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); + +var xbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +var x = new ndarray( 'float32', xbuf, [ 5 ], [ 1 ], 0, 'row-major' ); + +var ybuf = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] ); +var y = new ndarray( 'float32', ybuf, [ 5 ], [ 1 ], 0, 'row-major' ); + +var alpha = scalar2ndarray( 5.0, 'float32', 'row-major' ); +var z = saxpy( [ x, y, alpha ] ); +// returns [ 6.0, 11.0, 16.0, 21.0, 26.0 ] + +var bool = ( y === z ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var saxpy = require( '@stdlib/blas/base/ndarray/saxpy' ); + +var opts = { + 'dtype': 'float32' +}; + +var xbuf = discreteUniform( 10, 0, 100, opts ); +var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var ybuf = discreteUniform( xbuf.length, 0, 10, opts ); +var y = new ndarray( opts.dtype, ybuf, [ ybuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( y ) ); + +var alpha = scalar2ndarray( 5.0, opts ); +var out = saxpy( [ x, y, alpha ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/benchmark/benchmark.js new file mode 100644 index 000000000000..f9c12ff22473 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/benchmark/benchmark.js @@ -0,0 +1,118 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var saxpy = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len, -100.0, 100.0, options ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + + ybuf = uniform( len, -100.0, 100.0, options ); + y = new ndarray( options.dtype, ybuf, [ len ], [ 1 ], 0, 'row-major' ); + + alpha = scalar2ndarray( 5.0, options.dtype, 'row-major' ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = saxpy( [ x, y, alpha ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( z.get( i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/docs/repl.txt new file mode 100644 index 000000000000..99683baffa8e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/docs/repl.txt @@ -0,0 +1,40 @@ + +{{alias}}( arrays ) + Multiplies a one-dimensional single-precision floating-point ndarray `x` + by a constant `alpha` and adds the result to a one-dimensional single- + precision floating-point ndarray `y`. + + If provided an empty input ndarray, the function returns the output ndarray + unchanged. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing an input ndarray, an output ndarray, and + a zero-dimensional ndarray containing a scalar constant `alpha`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = new {{alias:@stdlib/array/float32}}( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ); + > var ybuf = new {{alias:@stdlib/array/float32}}( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ); + > var dt = 'float32'; + > var sh = [ xbuf.length ]; + > var st = [ 1 ]; + > var oo = 0; + > var ord = 'row-major'; + > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, st, oo, ord ); + > var y = new {{alias:@stdlib/ndarray/ctor}}( dt, ybuf, sh, st, oo, ord ); + > var alpha = {{alias:@stdlib/ndarray/base/from-scalar}}( 5.0, dt, ord ); + + > {{alias}}( [ x, y, alpha ] ); + > y + [ 22.0, 16.0, -16.0, 21.0, 3.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/docs/types/index.d.ts new file mode 100644 index 000000000000..f34cf3064197 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/docs/types/index.d.ts @@ -0,0 +1,55 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float32ndarray } from '@stdlib/types/ndarray'; + +/** +* Multiplies a one-dimensional single-precision floating-point ndarray `x` by a constant `alpha` and adds the result to a one-dimensional single-precision floating-point ndarray `y`. +* +* @param arrays - array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant +* @returns output ndarray +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var x = new ndarray( 'float32', xbuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var ybuf = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] ); +* var y = new ndarray( 'float32', ybuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var alpha = scalar2ndarray( 5.0, 'float32', 'row-major' ); +* +* var z = saxpy( [ x, y, alpha ] ); +* // returns [ 6.0, 11.0, 16.0, 21.0, 26.0 ] +* +* var bool = ( z === y ); +* // returns true +*/ +declare function saxpy( arrays: [ float32ndarray, float32ndarray, float32ndarray ] ): float32ndarray; + + +// EXPORTS // + +export = saxpy; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/docs/types/test.ts new file mode 100644 index 000000000000..297729326ec7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/docs/types/test.ts @@ -0,0 +1,69 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import saxpy = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float32' + }); + const y = zeros( [ 10 ], { + 'dtype': 'float32' + }); + const alpha = zeros( [], { + 'dtype': 'float32' + }); + + saxpy( [ x, y, alpha ] ); // $ExpectType float32ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + saxpy( '10' ); // $ExpectError + saxpy( 10 ); // $ExpectError + saxpy( true ); // $ExpectError + saxpy( false ); // $ExpectError + saxpy( null ); // $ExpectError + saxpy( undefined ); // $ExpectError + saxpy( [] ); // $ExpectError + saxpy( {} ); // $ExpectError + saxpy( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float32' + }); + const y = zeros( [ 10 ], { + 'dtype': 'float32' + }); + const alpha = zeros( [], { + 'dtype': 'float32' + }); + + saxpy(); // $ExpectError + saxpy( [ x, y, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/examples/index.js new file mode 100644 index 000000000000..f19bcf77c010 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var saxpy = require( './../lib' ); + +var opts = { + 'dtype': 'float32' +}; + +var xbuf = discreteUniform( 10, 0, 100, opts ); +var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var ybuf = discreteUniform( xbuf.length, 0, 10, opts ); +var y = new ndarray( opts.dtype, ybuf, [ ybuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( y ) ); + +var alpha = scalar2ndarray( 5.0, opts ); +var out = saxpy( [ x, y, alpha ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/lib/index.js new file mode 100644 index 000000000000..d688c6438419 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 1 routine to multiply a one-dimensional single-precision floating-point ndarray `x` by a constant `alpha` and add the result to a one-dimensional single-precision floating-point ndarray `y`. +* +* @module @stdlib/blas/base/ndarray/saxpy +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* var saxpy = require( '@stdlib/blas/base/ndarray/saxpy' ); +* +* var xbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var x = new ndarray( 'float32', xbuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var ybuf = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] ); +* var y = new ndarray( 'float32', ybuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var alpha = scalar2ndarray( 5.0, 'float32', 'row-major' ); +* +* var z = saxpy( [ x, y, alpha ] ); +* // returns [ 6.0, 11.0, 16.0, 21.0, 26.0 ] +* +* var bool = ( z === y ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/lib/main.js new file mode 100644 index 000000000000..ee18791b0aa1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/lib/main.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/saxpy' ).ndarray; + + +// MAIN // + +/** +* Multiplies a one-dimensional single-precision floating-point ndarray `x` by a constant `alpha` and adds the result to a one-dimensional single-precision floating-point ndarray `y`. +* +* @param {ArrayLikeObject} arrays - array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant +* @returns {Object} output ndarray +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var x = new ndarray( 'float32', xbuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var ybuf = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] ); +* var y = new ndarray( 'float32', ybuf, [ 5 ], [ 1 ], 0, 'row-major' ); +* +* var alpha = scalar2ndarray( 5.0, 'float32', 'row-major' ); +* +* var z = saxpy( [ x, y, alpha ] ); +* // returns [ 6.0, 11.0, 16.0, 21.0, 26.0 ] +* +* var bool = ( z === y ); +* // returns true +*/ +function saxpy( arrays ) { + var alpha = ndarraylike2scalar( arrays[ 2 ] ); + var x = arrays[ 0 ]; + var y = arrays[ 1 ]; + strided( numelDimension( x, 0 ), alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) ); // eslint-disable-line max-len + return y; +} + + +// EXPORTS // + +module.exports = saxpy; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/package.json new file mode 100644 index 000000000000..2537bfa75fbf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/blas/base/ndarray/saxpy", + "version": "0.0.0", + "description": "Multiply a one-dimensional single-precision floating-point ndarray `x` by a constant `alpha` and add the result to a one-dimensional single-precision floating-point ndarray `y`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 1", + "saxpy", + "linear", + "algebra", + "subroutines", + "daxpy", + "gaxpy", + "add", + "alpha", + "vector", + "array", + "ndarray", + "float32", + "single", + "float32array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/test/test.js new file mode 100644 index 000000000000..8657d44ed577 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/saxpy/test/test.js @@ -0,0 +1,234 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var saxpy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof saxpy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( saxpy.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies one-dimensional ndarray `x` by a constant `alpha` and adds the result to one-dimensional ndarray `y`', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var x; + var y; + var v; + + xbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + ybuf = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] ); + x = vector( xbuf, 5, 1, 0 ); + y = vector( ybuf, 5, 1, 0 ); + alpha = scalar2ndarray( 2.0, 'float32', 'row-major' ); + + v = saxpy( [ x, y, alpha ] ); + + expected = new Float32Array( [ 3.0, 5.0, 7.0, 9.0, 11.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = new Float32Array( [ 1.0, 2.0 ] ); + ybuf = new Float32Array( [ 1.0, 1.0 ] ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + alpha = scalar2ndarray( 2.0, 'float32', 'row-major' ); + + v = saxpy( [ x, y, alpha ] ); + + expected = new Float32Array( [ 3.0, 5.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided empty ndarrays, the function returns the output ndarray unchanged', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var x; + var y; + var v; + + xbuf = new Float32Array( [] ); + ybuf = new Float32Array( [] ); + x = vector( xbuf, 0, 1, 0 ); + y = vector( ybuf, 0, 1, 0 ); + alpha = scalar2ndarray( 5.0, 'float32', 'row-major' ); + + v = saxpy( [ x, y, alpha ] ); + + expected = new Float32Array( [] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var x; + var y; + var v; + + xbuf = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + x = vector( xbuf, 3, 2, 0 ); + + ybuf = new Float32Array([ + 1.0, // 0 + 1.0, // 1 + 1.0, // 2 + 1.0, + 1.0 + ]); + y = vector( ybuf, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, 'float32', 'row-major' ); + + v = saxpy( [ x, y, alpha ] ); + + expected = new Float32Array( [ 3.0, 7.0, 11.0, 1.0, 1.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var x; + var y; + var v; + + xbuf = new Float32Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + x = vector( xbuf, 3, -2, 4 ); + + ybuf = new Float32Array([ + 6.0, // 2 + 7.0, // 1 + 8.0, // 0 + 9.0, + 10.0 + ]); + y = vector( ybuf, 3, -1, 2 ); + alpha = scalar2ndarray( 3.0, 'float32', 'row-major' ); + + v = saxpy( [ x, y, alpha ] ); + + expected = new Float32Array( [ 9.0, 16.0, 23.0, 9.0, 10.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var x; + var y; + var v; + + xbuf = new Float32Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + x = vector( xbuf, 4, 2, 1 ); + + ybuf = new Float32Array([ + 1.0, + 2.0, + 3.0, // 0 + 4.0, // 1 + 5.0, // 2 + 6.0, // 3 + 7.0, + 8.0 + ]); + y = vector( ybuf, 4, 1, 2 ); + alpha = scalar2ndarray( 3.0, 'float32', 'row-major' ); + + v = saxpy( [ x, y, alpha ] ); + + expected = new Float32Array( [ 1.0, 2.0, 6.0, -2.0, 11.0, 18.0, 7.0, 8.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sdot/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/sdot/benchmark/benchmark.js index 154d502c67dc..52f549719e82 100644 --- a/lib/node_modules/@stdlib/blas/base/ndarray/sdot/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sdot/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdot = require( './../lib' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/operation-side-resolve-enum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/operation-side-resolve-enum/benchmark/benchmark.js index ed9ce0b67047..5c0ff2788635 100644 --- a/lib/node_modules/@stdlib/blas/base/operation-side-resolve-enum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/operation-side-resolve-enum/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var str2enum = require( '@stdlib/blas/base/operation-side-str2enum' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var resolve = require( './../lib' ); // MAIN // -bench( pkg+'::string', function benchmark( b ) { +bench( format( '%s::string', pkg ), function benchmark( b ) { var values; var out; var i; @@ -54,7 +55,7 @@ bench( pkg+'::string', function benchmark( b ) { b.end(); }); -bench( pkg+'::integer', function benchmark( b ) { +bench( format( '%s::integer', pkg ), function benchmark( b ) { var values; var out; var i; diff --git a/lib/node_modules/@stdlib/blas/base/operation-side-resolve-str/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/operation-side-resolve-str/benchmark/benchmark.js index 9ecb5bf480b4..f021e32c733a 100644 --- a/lib/node_modules/@stdlib/blas/base/operation-side-resolve-str/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/operation-side-resolve-str/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var str2enum = require( '@stdlib/blas/base/operation-side-str2enum' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var resolve = require( './../lib' ); // MAIN // -bench( pkg+'::string', function benchmark( b ) { +bench( format( '%s::string', pkg ), function benchmark( b ) { var values; var out; var i; @@ -54,7 +55,7 @@ bench( pkg+'::string', function benchmark( b ) { b.end(); }); -bench( pkg+'::integer', function benchmark( b ) { +bench( format( '%s::integer', pkg ), function benchmark( b ) { var values; var out; var i; diff --git a/lib/node_modules/@stdlib/blas/base/scabs1/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/base/scabs1/benchmark/benchmark.native.js index 2d605f327e02..a158f4dc2c06 100644 --- a/lib/node_modules/@stdlib/blas/base/scabs1/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/base/scabs1/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Complex64 = require( '@stdlib/complex/float32/ctor' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -39,7 +40,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var values; var y; var i; diff --git a/lib/node_modules/@stdlib/blas/base/sdsdot/README.md b/lib/node_modules/@stdlib/blas/base/sdsdot/README.md index d6b8f9131d58..c1eb8301d180 100644 --- a/lib/node_modules/@stdlib/blas/base/sdsdot/README.md +++ b/lib/node_modules/@stdlib/blas/base/sdsdot/README.md @@ -213,7 +213,7 @@ const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; const float y[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; float v = c_sdsdot( 5, 0.0f, x, 1, y, -1 ); -// returns -120.0f +// returns 35.0f ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/blas/base/sger/README.md b/lib/node_modules/@stdlib/blas/base/sger/README.md index 3220d4a0614c..737fe0646aee 100644 --- a/lib/node_modules/@stdlib/blas/base/sger/README.md +++ b/lib/node_modules/@stdlib/blas/base/sger/README.md @@ -335,7 +335,7 @@ int main( void ) { } // Perform operation using alternative indexing semantics: - c_sger( CblasRowMajor, M, N, 1.0f, x, strideX, 0, y, 0, strideY, A, N, 1, 0 ); + c_sger_ndarray( M, N, 1.0f, x, strideX, 0, y, strideY, 0, A, N, 1, 0 ); // Print the result: for ( int i = 0; i < M; i++ ) { diff --git a/lib/node_modules/@stdlib/blas/base/srotm/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/base/srotm/benchmark/c/benchmark.length.c index 424c0dec1688..d0c5b5c642e2 100644 --- a/lib/node_modules/@stdlib/blas/base/srotm/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/base/srotm/benchmark/c/benchmark.length.c @@ -96,11 +96,13 @@ static float rand_float( void ) { */ static double benchmark1( int iterations, int len ) { double elapsed; - float x[ len ]; - float y[ len ]; + float *x; + float *y; double t; int i; + x = (float *) malloc( len * sizeof( float ) ); + y = (float *) malloc( len * sizeof( float ) ); const float param[5] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; for ( i = 0; i < len; i++ ) { x[ i ] = ( rand_float()*200.0f ) - 100.0f; @@ -119,6 +121,8 @@ static double benchmark1( int iterations, int len ) { if ( y[ 0 ] != y[ 0 ] ) { printf( "should not return NaN\n" ); } + free( x ); + free( y ); return elapsed; } @@ -131,11 +135,13 @@ static double benchmark1( int iterations, int len ) { */ static double benchmark2( int iterations, int len ) { double elapsed; - float x[ len ]; - float y[ len ]; + float *x; + float *y; double t; int i; + x = (float *) malloc( len * sizeof( float ) ); + y = (float *) malloc( len * sizeof( float ) ); const float param[5] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; for ( i = 0; i < len; i++ ) { x[ i ] = ( rand_float()*200.0f ) - 100.0f; @@ -154,6 +160,8 @@ static double benchmark2( int iterations, int len ) { if ( y[ 0 ] != y[ 0 ] ) { printf( "should not return NaN\n" ); } + free( x ); + free( y ); return elapsed; } diff --git a/lib/node_modules/@stdlib/blas/base/sspr/README.md b/lib/node_modules/@stdlib/blas/base/sspr/README.md index 0e5f73306609..85bd2f57a9e7 100644 --- a/lib/node_modules/@stdlib/blas/base/sspr/README.md +++ b/lib/node_modules/@stdlib/blas/base/sspr/README.md @@ -225,7 +225,7 @@ Performs the symmetric rank 1 operation `A = α*x*x^T + A` where `α` is a scala float AP[] = { 1.0f, 2.0f, 3.0f, 1.0f, 2.0f, 1.0f }; const float x[] = { 1.0f, 2.0f, 3.0f }; -c_sspr_ndarray( CblasColMajor, CblasUpper, 3, 1.0f, x, 1, AP, 1, 0 ); +c_sspr_ndarray( CblasColMajor, CblasUpper, 3, 1.0f, x, 1, 0, AP, 1, 0 ); ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/blas/base/ssyr/README.md b/lib/node_modules/@stdlib/blas/base/ssyr/README.md index 0526eef6cb2a..1ed5fad234b1 100644 --- a/lib/node_modules/@stdlib/blas/base/ssyr/README.md +++ b/lib/node_modules/@stdlib/blas/base/ssyr/README.md @@ -307,7 +307,7 @@ int main( void ) { // Print the result: for ( int i = 0; i < N*N; i++ ) { - printf( "A2[ %i ] = %f\n", i, A[ i ] ); + printf( "A2[ %i ] = %f\n", i, A2[ i ] ); } } ``` diff --git a/lib/node_modules/@stdlib/blas/base/ssyr2/test/test.ssyr2.native.js b/lib/node_modules/@stdlib/blas/base/ssyr2/test/test.ssyr2.native.js index e740454aaf0d..8ced0286d918 100644 --- a/lib/node_modules/@stdlib/blas/base/ssyr2/test/test.ssyr2.native.js +++ b/lib/node_modules/@stdlib/blas/base/ssyr2/test/test.ssyr2.native.js @@ -37,7 +37,6 @@ var rxpyp = require( './fixtures/row_major_xpyp.json' ); var rxnyp = require( './fixtures/row_major_xnyp.json' ); var rxpyn = require( './fixtures/row_major_xpyn.json' ); var rxnyn = require( './fixtures/row_major_xnyn.json' ); - var cu = require( './fixtures/column_major_u.json' ); var cl = require( './fixtures/column_major_l.json' ); var cx0 = require( './fixtures/column_major_x0.json' ); diff --git a/lib/node_modules/@stdlib/blas/base/strsv/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/strsv/docs/types/index.d.ts index 3514179cb4c6..fde9864f4d52 100644 --- a/lib/node_modules/@stdlib/blas/base/strsv/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/base/strsv/docs/types/index.d.ts @@ -60,7 +60,7 @@ interface Routine { * @param N - number of elements along each dimension in the matrix `A` * @param A - input matrix * @param strideA1 - stride of the first dimension of `A` - * @param strideA2 - stride of the first dimension of `A` + * @param strideA2 - stride of the second dimension of `A` * @param offsetA - starting index for `A` * @param x - input vector * @param strideX - `x` stride length @@ -73,7 +73,7 @@ interface Routine { * var A = new Float32Array( [ 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 ] ); // => [ [ 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0 ], [ 0.0, 0.0, 1.0 ] ] * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); * - * strsv.ndarray( 'lower', 'no-transpose', 'unit', 3, A, 3, 1, 0, x, 1, 0 ); + * strsv.ndarray( 'upper', 'no-transpose', 'unit', 3, A, 3, 1, 0, x, 1, 0 ); * // x => [ 0.0, -4.0, 3.0 ] */ ndarray( uplo: MatrixTriangle, trans: TransposeOperation, diag: DiagonalType, N: number, A: Float32Array, strideA1: number, strideA2: number, offsetA: number, x: Float32Array, strideX: number, offsetX: number ): Float32Array; diff --git a/lib/node_modules/@stdlib/blas/base/strsv/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/base/strsv/test/test.ndarray.js index 8d3dd06e365e..12e46c524e58 100644 --- a/lib/node_modules/@stdlib/blas/base/strsv/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/strsv/test/test.ndarray.js @@ -46,7 +46,6 @@ var rsa1nsa2 = require( './fixtures/row_major_sa1n_sa2.json' ); var rsa1sa2n = require( './fixtures/row_major_sa1_sa2n.json' ); var rsa1nsa2n = require( './fixtures/row_major_sa1n_sa2n.json' ); var rcap = require( './fixtures/row_major_complex_access_pattern.json' ); - var clntnu = require( './fixtures/column_major_l_nt_nu.json' ); var cltnu = require( './fixtures/column_major_l_t_nu.json' ); var clntu = require( './fixtures/column_major_l_nt_u.json' ); @@ -62,7 +61,7 @@ var cox = require( './fixtures/column_major_ox.json' ); var csa1sa2 = require( './fixtures/column_major_sa1_sa2.json' ); var csa1nsa2 = require( './fixtures/column_major_sa1n_sa2.json' ); var csa1sa2n = require( './fixtures/column_major_sa1_sa2n.json' ); -var csa1nsa2n = require( './fixtures/column_major_sa1_sa2n.json' ); +var csa1nsa2n = require( './fixtures/column_major_sa1n_sa2n.json' ); var ccap = require( './fixtures/column_major_complex_access_pattern.json' ); diff --git a/lib/node_modules/@stdlib/blas/base/transpose-operation-resolve-enum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/transpose-operation-resolve-enum/benchmark/benchmark.js index 629ee35ed9a2..d015e1badff1 100644 --- a/lib/node_modules/@stdlib/blas/base/transpose-operation-resolve-enum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/transpose-operation-resolve-enum/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var str2enum = require( '@stdlib/blas/base/transpose-operation-str2enum' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var resolve = require( './../lib' ); // MAIN // -bench( pkg+'::string', function benchmark( b ) { +bench( format( '%s::string', pkg ), function benchmark( b ) { var values; var out; var i; @@ -55,7 +56,7 @@ bench( pkg+'::string', function benchmark( b ) { b.end(); }); -bench( pkg+'::integer', function benchmark( b ) { +bench( format( '%s::integer', pkg ), function benchmark( b ) { var values; var out; var i; diff --git a/lib/node_modules/@stdlib/blas/base/transpose-operation-resolve-str/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/transpose-operation-resolve-str/benchmark/benchmark.js index 9183e09e24d7..662c11d44e96 100644 --- a/lib/node_modules/@stdlib/blas/base/transpose-operation-resolve-str/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/transpose-operation-resolve-str/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var str2enum = require( '@stdlib/blas/base/transpose-operation-str2enum' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var resolve = require( './../lib' ); // MAIN // -bench( pkg+'::string', function benchmark( b ) { +bench( format( '%s::string', pkg ), function benchmark( b ) { var values; var out; var i; @@ -55,7 +56,7 @@ bench( pkg+'::string', function benchmark( b ) { b.end(); }); -bench( pkg+'::integer', function benchmark( b ) { +bench( format( '%s::integer', pkg ), function benchmark( b ) { var values; var out; var i; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.js index e68d06c80345..30f4e9695257 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cswap = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.module.js index fa5ed59f62eb..87b4fdc5f7b5 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cswap = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.module.main.js index 694903cbd106..3232e0dadb8f 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cswap = require( './../lib' ); @@ -134,7 +135,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.module.ndarray.js index 13d8c23c7f58..7998237de377 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cswap = require( './../lib' ); @@ -134,7 +135,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.ndarray.js index d147fab5fb72..d5d3fb9887a7 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/cswap/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cswap = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.js index afc46d660bea..feeec636900b 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var idamax = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.module.js index f2b3bd4880a7..eadaf5f79601 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var idamax = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.module.main.js index 090d6319d3f9..a802d9315822 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var idamax = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.module.ndarray.js index eed0fdccae13..1c7245c662e7 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var idamax = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.ndarray.js index 6704dc34298f..64bed682fc16 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/idamax/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var idamax = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.js index 369c60e6fe28..d9183d786166 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var isamax = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.module.js index 82b4db3d09e3..648204d7685f 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var isamax = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.module.main.js index acdf26980367..40e0c6b43ebf 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var isamax = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.module.ndarray.js index 7cc34bd632f2..cc1bfb4ea007 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var isamax = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.ndarray.js index 874f4d070708..955651ae068a 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/isamax/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var isamax = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.js index 597ab5a3efbf..e3921b197513 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sasum = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.module.js index 90826f1239c8..c234d1794163 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sasum = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.module.main.js index a78f50ead285..660bbd3b29f2 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sasum = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.module.ndarray.js index 18ef66e7ffc1..74a5f0298c06 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sasum = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.ndarray.js index e04b16eb085b..244467e34808 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sasum/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sasum = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.js index 1912ec86edfb..f615df158cab 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var saxpy = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.module.js index 698b93789b02..f2a30ad08452 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var saxpy = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.module.main.js index 1772179a7cd8..d7d53cb5acf3 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var saxpy = require( './../lib' ); @@ -131,7 +132,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.module.ndarray.js index 26ceb38d823f..31d61b1b2219 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var saxpy = require( './../lib' ); @@ -131,7 +132,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.ndarray.js index e0a489d9be5b..580d485ada07 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var saxpy = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.js index 35801f5e00f1..e019702476bc 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scasum = require( './../lib' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.module.js index 897c82ecc971..98852f38abfa 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scasum = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.module.main.js index 9c23527c9b7c..0da0effa20ff 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.module.main.js @@ -28,6 +28,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Complex64Array = require( '@stdlib/array/complex64' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scasum = require( './../lib' ); @@ -131,7 +132,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.module.ndarray.js index 96ef18866120..d1dd3b8b1f56 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.module.ndarray.js @@ -28,6 +28,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scasum = require( './../lib' ); @@ -131,7 +132,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.ndarray.js index cd77c51dd6ce..0d4393698057 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/scasum/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scasum = require( './../lib' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.js index fb43167155c4..f3a124115585 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scnrm2 = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.module.js index 3489681a3e8f..a9760e76c5dc 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scnrm2 = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.module.main.js index 9c2317f0e8ca..280d91eb10df 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scnrm2 = require( './../lib' ); @@ -131,7 +132,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.module.ndarray.js index 0e761b12e210..339e3ce0546f 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scnrm2 = require( './../lib' ); @@ -131,7 +132,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.ndarray.js index bf14cffee928..6a57833bb1db 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scnrm2 = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.js index 2537749208ff..07226a09dfd7 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scopy = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.module.js index 8e67a6330251..6558979b8985 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scopy = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.module.main.js index e9e73c28f515..1e8ca36350fe 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scopy = require( './../lib' ); @@ -131,7 +132,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.module.ndarray.js index 7a4d8e79658d..9f00d24b83c4 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scopy = require( './../lib' ); @@ -131,7 +132,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.ndarray.js index 5dd09dc4e0e8..6b3537d2c219 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/scopy/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scopy = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.js index 6393bb53fb96..5f01be86e229 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdot = require( './../lib' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.module.js index ec6bd310f6e9..6b845ce8dc0f 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdot = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.module.main.js index d5f39886e4a1..798ca112eb43 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdot = require( './../lib' ); @@ -126,7 +127,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.module.ndarray.js index 2655c3892de2..b8798d0f2166 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdot = require( './../lib' ); @@ -126,7 +127,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.ndarray.js index 71e647f8e103..22eac22121c9 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sdot/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdot = require( './../lib' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.js index 631ebbeb93c3..de8bf8c6d0f7 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsdot = require( './../lib' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.module.js index a9410d0e5929..0c01e0cb1d95 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsdot = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.module.main.js index 934cec779fb0..3a045e13dccd 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsdot = require( './../lib' ); @@ -126,7 +127,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.module.ndarray.js index 4f0665d632f1..b33f6f1b7d62 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsdot = require( './../lib' ); @@ -126,7 +127,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.ndarray.js index 208ab4f353fa..77de5eb5d895 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsdot = require( './../lib' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.js index efb0831f1d98..bb5421ccc62e 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snrm2 = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.module.js index e10b4eed778d..89a7e9c0906f 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snrm2 = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.module.main.js index 329f226a55e9..65aff51b5983 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snrm2 = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.module.ndarray.js index c7da01bf160b..92672d3d8d38 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snrm2 = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.ndarray.js index 34f926872ba9..954ec9971c6a 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snrm2 = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.js index bb82f0474f80..c37dbc180fb3 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var srot = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.module.js index 11f40cf3375d..a9fae747530c 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var srot = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.module.main.js index 0d646ad6ab48..68dfdf1828cd 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var srot = require( './../lib' ); @@ -131,7 +132,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.module.ndarray.js index 686b15082162..c1acc6820ac2 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var srot = require( './../lib' ); @@ -131,7 +132,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.ndarray.js index fc70b417f42d..e7e6573e78b4 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/srot/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var srot = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.js index 6d4012ba1677..caea286a69cc 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.js @@ -26,6 +26,7 @@ var zeros = require( '@stdlib/array/zeros' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var srotm = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.module.js index 653e04645bb3..9eb081bd6b70 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var srotm = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.module.main.js index 9481da96f86d..e275ffba80ce 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.module.main.js @@ -28,6 +28,7 @@ var zeros = require( '@stdlib/array/zeros' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var srotm = require( './../lib' ); @@ -135,7 +136,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.module.ndarray.js index 7f60477eb369..5e1eb0abcb0d 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.module.ndarray.js @@ -28,6 +28,7 @@ var zeros = require( '@stdlib/array/zeros' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var srotm = require( './../lib' ); @@ -135,7 +136,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.ndarray.js index e8ec6f42c650..0ead684134cf 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/srotm/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var zeros = require( '@stdlib/array/zeros' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var srotm = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.js index 098d14aa5c21..89ea2d49d8a1 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sscal = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.module.js index 0b70c4b291c5..cb155f9a5eae 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sscal = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.module.main.js index a3271329f31b..18947ca4c39b 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sscal = require( './../lib' ); @@ -128,7 +129,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.module.ndarray.js index 4e919fb41dd0..692c30b8ae11 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sscal = require( './../lib' ); @@ -128,7 +129,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.ndarray.js index 790527a5b120..648ba0d13dd8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sscal/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sscal = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.js index 0e987e7d1bdf..1f6abd703953 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sswap = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.module.js index 38ab98136b36..9e0c1a56a311 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sswap = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.module.main.js index 8b6b60f73089..5520f151dfa7 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sswap = require( './../lib' ); @@ -131,7 +132,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.module.ndarray.js index 8c6994495887..b5165bfa7677 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sswap = require( './../lib' ); @@ -131,7 +132,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.ndarray.js index 6f896a37285a..36005306ecf0 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/sswap/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sswap = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.js index 79aa13d27e3d..562d532a0b30 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zcopy = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.module.js index 72ef2497f7f9..065fefc4a297 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zcopy = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.module.main.js index 64fa79dea758..585ba1aea5a7 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zcopy = require( './../lib' ); @@ -134,7 +135,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.module.ndarray.js index d80f1ff7d371..9f80aca64923 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zcopy = require( './../lib' ); @@ -134,7 +135,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.ndarray.js index f2f6ca8432ff..ffce1d058c8b 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zcopy = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.js index cacd41fc69a0..7f9c1c324bd1 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zdrot = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.module.js index bab25ca845e1..4d757d82db1f 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zdrot = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.module.main.js index 5938740d4d27..08f41a51d120 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zdrot = require( './../lib' ); @@ -134,7 +135,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.module.ndarray.js index 1f93fff97923..a9a2da4ec765 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zdrot = require( './../lib' ); @@ -134,7 +135,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.ndarray.js index c8c321362ee2..3c661477d764 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zdrot = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.js index b7334e72a186..1639cf22129e 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex128Array = require( '@stdlib/array/complex128' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zscal = require( './../lib' ); @@ -108,7 +109,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = pow( 10, i ); f = createBenchmark( N ); - bench( pkg+':size='+N, opts, f ); + bench( format( '%s:size=%d', pkg, N ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.module.js index 02c1140b1b06..859f6768f5cb 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zscal = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.module.main.js index 2f3c189c065a..3abcd9811828 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.module.main.js @@ -28,6 +28,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zscal = require( './../lib' ); @@ -134,7 +135,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = pow( 10, i ); f = createBenchmark( N ); - bench( pkg+'::module,pointers:size='+N, opts, f ); + bench( format( '%s::module,pointers:size=%d', pkg, N ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.module.ndarray.js index 3a141d36cfc2..cfcfdba913e9 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.module.ndarray.js @@ -28,6 +28,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zscal = require( './../lib' ); @@ -134,7 +135,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = pow( 10, i ); f = createBenchmark( N ); - bench( pkg+'::module,pointers:ndarray:N='+N, opts, f ); + bench( format( '%s::module,pointers:ndarray:N=%d', pkg, N ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.ndarray.js index e13a86cd0b91..1023fde63506 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zscal/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex128Array = require( '@stdlib/array/complex128' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zscal = require( './../lib' ); @@ -108,7 +109,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = pow( 10, i ); f = createBenchmark( N ); - bench( pkg+':ndarray:N='+N, opts, f ); + bench( format( '%s:ndarray:N=%d', pkg, N ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.js index e3e18a5d38a3..fd8c18f96997 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zswap = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.module.js index 9c0171339dae..eca0cf3d6d3b 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zswap = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.module.main.js index a555f520c575..8994f81be3c7 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zswap = require( './../lib' ); @@ -134,7 +135,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.module.ndarray.js index f09b8ae1cc0a..722354d2de95 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zswap = require( './../lib' ); @@ -134,7 +135,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.ndarray.js index 051fb7577a45..28fea3ff10aa 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zswap/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zswap = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/zaxpy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/zaxpy/benchmark/benchmark.js index 92835d7157fc..1655d1694a19 100644 --- a/lib/node_modules/@stdlib/blas/base/zaxpy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/zaxpy/benchmark/benchmark.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Complex128Array = require( '@stdlib/array/complex128' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zaxpy = require( './../lib/zaxpy.js' ); @@ -108,7 +109,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = pow( 10, i ); f = createBenchmark( N ); - bench( pkg+':len='+N, f ); + bench( format( '%s:len=%d', pkg, N ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/zaxpy/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/base/zaxpy/benchmark/benchmark.native.js index 9d7bb7e3b152..7943251baa48 100644 --- a/lib/node_modules/@stdlib/blas/base/zaxpy/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/base/zaxpy/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var Complex128Array = require( '@stdlib/array/complex128' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = pow( 10, i ); f = createBenchmark( N ); - bench( pkg+'::native:len='+N, opts, f ); + bench( format( '%s::native:len=%d', pkg, N ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/zaxpy/benchmark/benchmark.native.ndarray.js b/lib/node_modules/@stdlib/blas/base/zaxpy/benchmark/benchmark.native.ndarray.js index bfcb67af1f0f..cfdb059cd505 100644 --- a/lib/node_modules/@stdlib/blas/base/zaxpy/benchmark/benchmark.native.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/zaxpy/benchmark/benchmark.native.ndarray.js @@ -29,6 +29,7 @@ var Complex128Array = require( '@stdlib/array/complex128' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = pow( 10, i ); f = createBenchmark( N ); - bench( pkg+'::native:ndarray:len='+N, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, N ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/zaxpy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/zaxpy/benchmark/benchmark.ndarray.js index d945209274c5..661829e1498e 100644 --- a/lib/node_modules/@stdlib/blas/base/zaxpy/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/zaxpy/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Complex128Array = require( '@stdlib/array/complex128' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zaxpy = require( './../lib/ndarray.js' ); @@ -108,7 +109,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = pow( 10, i ); f = createBenchmark( N ); - bench( pkg+':ndarray:len='+N, f ); + bench( format( '%s:ndarray:len=%d', pkg, N ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/zcopy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/zcopy/benchmark/benchmark.js index 8eda5d591600..ac363b571bc1 100644 --- a/lib/node_modules/@stdlib/blas/base/zcopy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/zcopy/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex128Array = require( '@stdlib/array/complex128' ); var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zcopy = require( './../lib/zcopy.js' ); @@ -108,7 +109,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/zcopy/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/base/zcopy/benchmark/benchmark.native.js index 16a39807954d..384032414372 100644 --- a/lib/node_modules/@stdlib/blas/base/zcopy/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/base/zcopy/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Complex128Array = require( '@stdlib/array/complex128' ); var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/zcopy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/zcopy/benchmark/benchmark.ndarray.js index 7e7123add884..237cf07cc062 100644 --- a/lib/node_modules/@stdlib/blas/base/zcopy/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/zcopy/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex128Array = require( '@stdlib/array/complex128' ); var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zcopy = require( './../lib/ndarray.js' ); @@ -108,7 +109,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/base/zcopy/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/base/zcopy/benchmark/benchmark.ndarray.native.js index b06a0888fa55..ae87477eb035 100644 --- a/lib/node_modules/@stdlib/blas/base/zcopy/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/base/zcopy/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Complex128Array = require( '@stdlib/array/complex128' ); var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/README.md b/lib/node_modules/@stdlib/blas/ext/README.md index 8ec5536f200f..34cb41ec4359 100644 --- a/lib/node_modules/@stdlib/blas/ext/README.md +++ b/lib/node_modules/@stdlib/blas/ext/README.md @@ -57,6 +57,7 @@ The namespace contains the following: - [`sorthp( x[, sortOrder][, options] )`][@stdlib/blas/ext/sorthp]: sort an input ndarray along one or more ndarray dimensions using heapsort. - [`sum( x[, options] )`][@stdlib/blas/ext/sum]: compute the sum along one or more ndarray dimensions. - [`toSortedhp( x[, sortOrder][, options] )`][@stdlib/blas/ext/to-sortedhp]: return a new ndarray containing the elements of an input ndarray sorted along one or more ndarray dimensions using heapsort. +- [`zeroTo( shape[, options] )`][@stdlib/blas/ext/zero-to]: return a new ndarray filled with linearly spaced numeric elements which increment by `1` starting from zero along one or more ndarray dimensions. @@ -123,6 +124,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/to-sortedhp]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/to-sortedhp +[@stdlib/blas/ext/zero-to]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/zero-to + diff --git a/lib/node_modules/@stdlib/blas/ext/base/README.md b/lib/node_modules/@stdlib/blas/ext/base/README.md index 3b61e4068e73..74e4363f726c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/README.md @@ -141,6 +141,7 @@ var o = ns; - [`gnansumors( N, x, strideX )`][@stdlib/blas/ext/base/gnansumors]: calculate the sum of strided array elements, ignoring `NaN` values and using ordinary recursive summation. - [`gnansumpw( N, x, strideX )`][@stdlib/blas/ext/base/gnansumpw]: calculate the sum of strided array elements, ignoring `NaN` values and using pairwise summation. - [`goneTo( N, x, strideX )`][@stdlib/blas/ext/base/gone-to]: fill a strided array with linearly spaced numeric elements which increment by `1` starting from one. +- [`greplicate( N, k, x, strideX, out, strideOut )`][@stdlib/blas/ext/base/greplicate]: replicate each strided array element a specified number of times. - [`grev( N, x, strideX )`][@stdlib/blas/ext/base/grev]: reverse a strided array in-place. - [`gsort( N, order, x, strideX )`][@stdlib/blas/ext/base/gsort]: sort a strided array. - [`gsort2hp( N, order, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gsort2hp]: simultaneously sort two strided arrays based on the sort order of the first array using heapsort. @@ -154,6 +155,7 @@ var o = ns; - [`gsumkbn2( N, x, strideX )`][@stdlib/blas/ext/base/gsumkbn2]: calculate the sum of strided array elements using a second-order iterative Kahan–Babuška algorithm. - [`gsumors( N, x, strideX )`][@stdlib/blas/ext/base/gsumors]: calculate the sum of strided array elements using ordinary recursive summation. - [`gsumpw( N, x, strideX )`][@stdlib/blas/ext/base/gsumpw]: calculate the sum of strided array elements using pairwise summation. +- [`gvander( order, mode, M, N, x, strideX, out, ldo )`][@stdlib/blas/ext/base/gvander]: generate a Vandermonde matrix. - [`gzeroTo( N, x, strideX )`][@stdlib/blas/ext/base/gzero-to]: fill a strided array with linearly spaced numeric elements which increment by `1` starting from zero. - [`ndarray`][@stdlib/blas/ext/base/ndarray]: base ndarray extended BLAS functions. - [`sapx( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sapx]: add a scalar constant to each element in a single-precision floating-point strided array. @@ -187,10 +189,11 @@ var o = ns; - [`snansumpw( N, x, strideX )`][@stdlib/blas/ext/base/snansumpw]: calculate the sum of single-precision floating-point strided array elements, ignoring `NaN` values and using pairwise summation. - [`soneTo( N, x, strideX )`][@stdlib/blas/ext/base/sone-to]: fill a single-precision floating-point strided array with linearly spaced numeric elements which increment by `1` starting from one. - [`srev( N, x, strideX )`][@stdlib/blas/ext/base/srev]: reverse a single-precision floating-point strided array in-place. +- [`ssort( N, order, x, strideX )`][@stdlib/blas/ext/base/ssort]: sort a single-precision floating-point strided array. - [`ssort2hp( N, order, x, strideX, y, strideY )`][@stdlib/blas/ext/base/ssort2hp]: simultaneously sort two single-precision floating-point strided arrays based on the sort order of the first array using heapsort. - [`ssort2ins( N, order, x, strideX, y, strideY )`][@stdlib/blas/ext/base/ssort2ins]: simultaneously sort two single-precision floating-point strided arrays based on the sort order of the first array using insertion sort. - [`ssort2sh( N, order, x, strideX, y, strideY )`][@stdlib/blas/ext/base/ssort2sh]: simultaneously sort two single-precision floating-point strided arrays based on the sort order of the first array using Shellsort. -- [`ssorthp( N, order, x, stride )`][@stdlib/blas/ext/base/ssorthp]: sort a single-precision floating-point strided array using heapsort. +- [`ssorthp( N, order, x, strideX )`][@stdlib/blas/ext/base/ssorthp]: sort a single-precision floating-point strided array using heapsort. - [`ssortins( N, order, x, stride )`][@stdlib/blas/ext/base/ssortins]: sort a single-precision floating-point strided array using insertion sort. - [`ssortsh( N, order, x, stride )`][@stdlib/blas/ext/base/ssortsh]: sort a single-precision floating-point strided array using Shellsort. - [`ssum( N, x, strideX )`][@stdlib/blas/ext/base/ssum]: calculate the sum of single-precision floating-point strided array elements. @@ -452,6 +455,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/gone-to]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gone-to +[@stdlib/blas/ext/base/greplicate]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/greplicate + [@stdlib/blas/ext/base/grev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/grev [@stdlib/blas/ext/base/gsort]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gsort @@ -478,6 +483,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/gsumpw]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gsumpw +[@stdlib/blas/ext/base/gvander]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gvander + [@stdlib/blas/ext/base/gzero-to]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gzero-to [@stdlib/blas/ext/base/ndarray]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray @@ -544,6 +551,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/srev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/srev +[@stdlib/blas/ext/base/ssort]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ssort + [@stdlib/blas/ext/base/ssort2hp]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ssort2hp [@stdlib/blas/ext/base/ssort2ins]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ssort2ins diff --git a/lib/node_modules/@stdlib/blas/ext/base/cfill/README.md b/lib/node_modules/@stdlib/blas/ext/base/cfill/README.md index 3b560d4c1002..d56850103ad5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/cfill/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/cfill/README.md @@ -221,7 +221,7 @@ Fills a single-precision complex floating-point strided array `X` with a specifi float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; const stdlib_complex64_t alpha = stdlib_complex64( 2.0f, 2.0f ); -stdlib_strided_cfill_ndarray( 4, alpha, (stdlib_complex64_t *x), 1, 0 ); +stdlib_strided_cfill_ndarray( 4, alpha, (stdlib_complex64_t *)x, 1, 0 ); ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/blas/ext/base/cfill/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/cfill/benchmark/benchmark.js index ccb907c35257..e75eb34e933d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/cfill/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/cfill/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cfill = require( './../lib/cfill.js' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/cfill/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/cfill/benchmark/benchmark.native.js index f6e4486141e7..711be2c119cd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/cfill/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/cfill/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); var Complex64 = require( '@stdlib/complex/float32/ctor' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/cfill/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/cfill/benchmark/benchmark.ndarray.js index fdeb25d39f96..fa09fd96ab36 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/cfill/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/cfill/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cfill = require( './../lib/ndarray.js' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/cfill/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/cfill/benchmark/benchmark.ndarray.native.js index acab1b9a636b..53bc41b58250 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/cfill/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/cfill/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); var Complex64 = require( '@stdlib/complex/float32/ctor' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/cindex-of-row/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/cindex-of-row/docs/types/index.d.ts index 77446642714b..ba0797856f6b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/cindex-of-row/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/cindex-of-row/docs/types/index.d.ts @@ -47,8 +47,8 @@ interface Routine { * @returns row index * * @example - * var Complex64Array = require( `@stdlib/array/complex64` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var Complex64Array = require( '@stdlib/array/complex64' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Complex64Array( [ 1.0, 0.0, 2.0, 0.0, 0.0, 0.0, 3.0, 0.0, 4.0, 0.0, 0.0, 0.0 ] ); * var x = new Complex64Array( [ 2.0, 0.0, 4.0, 0.0 ] ); @@ -82,8 +82,8 @@ interface Routine { * @returns row index * * @example - * var Complex64Array = require( `@stdlib/array/complex64` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var Complex64Array = require( '@stdlib/array/complex64' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Complex64Array( [ 1.0, 0.0, 2.0, 0.0, 0.0, 0.0, 3.0, 0.0, 4.0, 0.0, 0.0, 0.0 ] ); * var x = new Complex64Array( [ 2.0, 0.0, 4.0, 0.0 ] ); @@ -115,8 +115,8 @@ interface Routine { * @returns row index * * @example -* var Complex64Array = require( `@stdlib/array/complex64` ); -* var Uint8Array = require( `@stdlib/array/uint8` ); +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Complex64Array( [ 1.0, 0.0, 2.0, 0.0, 0.0, 0.0, 3.0, 0.0, 4.0, 0.0, 0.0, 0.0 ] ); * var x = new Complex64Array( [ 2.0, 0.0, 4.0, 0.0 ] ); @@ -126,8 +126,8 @@ interface Routine { * // returns 1 * * @example -* var Complex64Array = require( `@stdlib/array/complex64` ); -* var Uint8Array = require( `@stdlib/array/uint8` ); +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Complex64Array( [ 1.0, 0.0, 2.0, 0.0, 0.0, 0.0, 3.0, 0.0, 4.0, 0.0, 0.0, 0.0 ] ); * var x = new Complex64Array( [ 2.0, 0.0, 4.0, 0.0 ] ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/csum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/csum/benchmark/benchmark.js index ce4df691643e..2368265fb9d0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/csum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/csum/benchmark/benchmark.js @@ -27,6 +27,7 @@ var realf = require( '@stdlib/complex/float32/real' ); var imagf = require( '@stdlib/complex/float32/imag' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var csum = require( './../lib/csum.js' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/csum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/csum/benchmark/benchmark.native.js index e77ad6a09c8a..18fa3d06d358 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/csum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/csum/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var imagf = require( '@stdlib/complex/float32/imag' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/csum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/csum/benchmark/benchmark.ndarray.js index b6fcf9ba8495..1a6c9da012ef 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/csum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/csum/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var realf = require( '@stdlib/complex/float32/real' ); var imagf = require( '@stdlib/complex/float32/imag' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var csum = require( './../lib/ndarray.js' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/csum/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/csum/benchmark/benchmark.ndarray.native.js index 1699bf20f419..8cc4712a98b1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/csum/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/csum/benchmark/benchmark.ndarray.native.js @@ -29,6 +29,7 @@ var imagf = require( '@stdlib/complex/float32/imag' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/csumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/csumkbn/benchmark/benchmark.js index 2c01743d3119..8316c88680ca 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/csumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/csumkbn/benchmark/benchmark.js @@ -27,6 +27,7 @@ var realf = require( '@stdlib/complex/float32/real' ); var imagf = require( '@stdlib/complex/float32/imag' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var csumkbn = require( './../lib/csumkbn.js' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/csumkbn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/csumkbn/benchmark/benchmark.native.js index df0327afb778..6e2b5dbac792 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/csumkbn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/csumkbn/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var imagf = require( '@stdlib/complex/float32/imag' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/csumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/csumkbn/benchmark/benchmark.ndarray.js index f16f3fc445ab..a43a180ed5dc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/csumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/csumkbn/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var realf = require( '@stdlib/complex/float32/real' ); var imagf = require( '@stdlib/complex/float32/imag' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var csumkbn = require( './../lib/ndarray.js' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/csumkbn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/csumkbn/benchmark/benchmark.ndarray.native.js index 6c286e7a6c90..17cb0f7ab6b8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/csumkbn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/csumkbn/benchmark/benchmark.ndarray.native.js @@ -29,6 +29,7 @@ var imagf = require( '@stdlib/complex/float32/imag' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dasumpw/README.md b/lib/node_modules/@stdlib/blas/ext/base/dasumpw/README.md index e901a320238e..d9ce0e8a4442 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dasumpw/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dasumpw/README.md @@ -192,7 +192,7 @@ console.log( v ); Computes the sum of absolute values ([_L1_ norm][l1norm]) of double-precision floating-point strided array elements using pairwise summation. ```c -const double x[] = { 1.0, 2.0, 3.0, 4.0 } +const double x[] = { 1.0, 2.0, 3.0, 4.0 }; double v = stdlib_strided_dasumpw( 4, x, 1 ); // returns 10.0 @@ -213,7 +213,7 @@ double stdlib_strided_dasumpw( const CBLAS_INT N, const double *X, const CBLAS_I Computes the sum of absolute values ([_L1_ norm][l1norm]) of double-precision floating-point strided array elements using pairwise summation and alternative indexing semantics. ```c -const double x[] = { 1.0, 2.0, 3.0, 4.0 } +const double x[] = { 1.0, 2.0, 3.0, 4.0 }; double v = stdlib_strided_dasumpw_ndarray( 4, x, 1, 0 ); // returns 10.0 diff --git a/lib/node_modules/@stdlib/blas/ext/base/dcusumkbn2/README.md b/lib/node_modules/@stdlib/blas/ext/base/dcusumkbn2/README.md index 2c80cfad2104..131a16f081b3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dcusumkbn2/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dcusumkbn2/README.md @@ -199,8 +199,8 @@ console.log( y ); Computes the cumulative sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. ```c -const double x[] = { 1.0, 2.0, 3.0, 4.0 } -double y[] = { 0.0, 0.0, 0.0, 0.0 } +const double x[] = { 1.0, 2.0, 3.0, 4.0 }; +double y[] = { 0.0, 0.0, 0.0, 0.0 }; stdlib_strided_dcusumkbn2( 4, 0.0, x, 1, y, 1 ); ``` @@ -227,8 +227,8 @@ void stdlib_strided_dcusumkbn2( const CBLAS_INT N, const double sum, const doubl Computes the cumulative sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. ```c -const double x[] = { 1.0, 2.0, 3.0, 4.0 } -double y[] = { 0.0, 0.0, 0.0, 0.0 } +const double x[] = { 1.0, 2.0, 3.0, 4.0 }; +double y[] = { 0.0, 0.0, 0.0, 0.0 }; stdlib_strided_dcusumkbn2_ndarray( 4, 0.0, x, 1, 0, y, 1, 0 ); ``` diff --git a/lib/node_modules/@stdlib/blas/ext/base/dcusumors/README.md b/lib/node_modules/@stdlib/blas/ext/base/dcusumors/README.md index 74ae9a85ad86..61b7fc5618a1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dcusumors/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dcusumors/README.md @@ -228,8 +228,8 @@ void stdlib_strided_dcusumors( const CBLAS_INT N, double sum, const double *X, c Computes the cumulative sum of double-precision floating-point strided array elements using ordinary recursive summation and alternative indexing semantics. ```c -const double x[] = { 1.0, 2.0, 3.0, 4.0 } -double y[] = { 0.0, 0.0, 0.0, 0.0 } +const double x[] = { 1.0, 2.0, 3.0, 4.0 }; +double y[] = { 0.0, 0.0, 0.0, 0.0 }; stdlib_strided_dcusumors_ndarray( 4, 0.0, x, 1, 0, y, 1, 0 ); ``` diff --git a/lib/node_modules/@stdlib/blas/ext/base/dcusumpw/README.md b/lib/node_modules/@stdlib/blas/ext/base/dcusumpw/README.md index a2fddff55051..1b0c9e3cef22 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dcusumpw/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dcusumpw/README.md @@ -228,8 +228,8 @@ void stdlib_strided_dcusumpw( const CBLAS_INT N, const double sum, const double Computes the cumulative sum of double-precision floating-point strided array elements using pairwise summation and alternative indexing semantics. ```c -const double x[] = { 1.0, 2.0, 3.0, 4.0 } -double y[] = { 0.0, 0.0, 0.0, 0.0 } +const double x[] = { 1.0, 2.0, 3.0, 4.0 }; +double y[] = { 0.0, 0.0, 0.0, 0.0 }; stdlib_strided_dcusumpw_ndarray( 4, 0.0, x, 1, 0, y, 1, 0 ); ``` diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-row/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-row/docs/types/index.d.ts index 71e924d21e5f..cd89559988f5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-row/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-row/docs/types/index.d.ts @@ -46,8 +46,8 @@ interface Routine { * @returns row index * * @example - * var Float64Array = require( `@stdlib/array/float64` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var Float64Array = require( '@stdlib/array/float64' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Float64Array( [ 1.0, 2.0, 0.0, 3.0, 4.0, 0.0 ] ); * var x = new Float64Array( [ 2.0, 4.0 ] ); @@ -81,8 +81,8 @@ interface Routine { * @returns row index * * @example - * var Float64Array = require( `@stdlib/array/float64` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var Float64Array = require( '@stdlib/array/float64' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Float64Array( [ 1.0, 2.0, 0.0, 3.0, 4.0, 0.0 ] ); * var x = new Float64Array( [ 2.0, 4.0 ] ); @@ -114,8 +114,8 @@ interface Routine { * @returns row index * * @example -* var Float64Array = require( `@stdlib/array/float64` ); -* var Uint8Array = require( `@stdlib/array/uint8` ); +* var Float64Array = require( '@stdlib/array/float64' ); +* var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Float64Array( [ 1.0, 2.0, 0.0, 3.0, 4.0, 0.0 ] ); * var x = new Float64Array( [ 2.0, 4.0 ] ); @@ -125,8 +125,8 @@ interface Routine { * // returns 1 * * @example -* var Float64Array = require( `@stdlib/array/float64` ); -* var Uint8Array = require( `@stdlib/array/uint8` ); +* var Float64Array = require( '@stdlib/array/float64' ); +* var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Float64Array( [ 1.0, 2.0, 0.0, 3.0, 4.0, 0.0 ] ); * var x = new Float64Array( [ 2.0, 4.0 ] ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of/README.md b/lib/node_modules/@stdlib/blas/ext/base/dindex-of/README.md index 31712a75019b..6538aced11c0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dindex-of/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of/README.md @@ -222,7 +222,7 @@ Returns the first index of a specified search element in a double-precision floa ```c double x[] = { 1.0, 2.0, 3.0, 4.0 }; -int idx = stdlib_strided_dindex_of( 4, 3.0, x, 1, 0 ); +int idx = stdlib_strided_dindex_of_ndarray( 4, 3.0, x, 1, 0 ); // returns 2 ``` diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnanasum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dnanasum/benchmark/benchmark.js index f7f1ae28cfd5..90498540a6fd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnanasum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnanasum/benchmark/benchmark.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanasum = require( './../lib/dnanasum.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnanasum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dnanasum/benchmark/benchmark.native.js index a9a8a158b7c8..0d39ff03324b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnanasum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnanasum/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnanasum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dnanasum/benchmark/benchmark.ndarray.js index bd8ee7480afe..b1d00444825f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnanasum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnanasum/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanasum = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnanasum/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dnanasum/benchmark/benchmark.ndarray.native.js index dfe214744fad..16042a6749ef 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnanasum/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnanasum/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnancusumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dnancusumkbn/benchmark/benchmark.js index 9953f9bc2652..a56090ec3ce8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnancusumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnancusumkbn/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var zeros = require( '@stdlib/array/zeros' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnancusumkbn = require( './../lib/dnancusumkbn.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnancusumkbn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dnancusumkbn/benchmark/benchmark.native.js index 1330baa7bf52..aa9a1ed13941 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnancusumkbn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnancusumkbn/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var zeros = require( '@stdlib/array/zeros' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnancusumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dnancusumkbn/benchmark/benchmark.ndarray.js index 3e475aa8f6b8..9fc7a4026a2f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnancusumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnancusumkbn/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var zeros = require( '@stdlib/array/zeros' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnancusumkbn = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnancusumkbn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dnancusumkbn/benchmark/benchmark.ndarray.native.js index b315b422dbfc..968a3d21f2f7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnancusumkbn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnancusumkbn/benchmark/benchmark.ndarray.native.js @@ -29,6 +29,7 @@ var zeros = require( '@stdlib/array/zeros' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnannsumors/README.md b/lib/node_modules/@stdlib/blas/ext/base/dnannsumors/README.md index 65de33ac5618..e1952e1bd894 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnannsumors/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dnannsumors/README.md @@ -259,7 +259,7 @@ double stdlib_strided_dnannsumors_ndarray( const CBLAS_INT N, const double *X, c ```c #include "stdlib/blas/ext/base/dnannsumors.h" -#include "stdlib/blase/base/shared.h" +#include "stdlib/blas/base/shared.h" #include int main( void ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnannsumpw/README.md b/lib/node_modules/@stdlib/blas/ext/base/dnannsumpw/README.md index 9046d473826b..01d48459a332 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnannsumpw/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dnannsumpw/README.md @@ -262,7 +262,7 @@ double stdlib_strided_dnannsumpw_ndarray( const CBLAS_INT N, const double *X, co ```c #include "stdlib/blas/ext/base/dnannsumpw.h" -#include "stdlib/blase/base/shared.h" +#include "stdlib/blas/base/shared.h" #include int main( void ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/benchmark/benchmark.js index a0a2ba343a46..c579b39ad6e8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumkbn2 = require( './../lib/dnansumkbn2.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/benchmark/benchmark.native.js index be14526ea51e..f98a34ebb6c2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/benchmark/benchmark.ndarray.js index 7e53528b86e9..620b18ad7bc8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumkbn2 = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/benchmark/benchmark.ndarray.native.js index accf0bc442da..fba379053024 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnansumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dnansumors/benchmark/benchmark.js index 42a1518cf3eb..ac873ebbc3b3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnansumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnansumors/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumors = require( './../lib/dnansumors.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnansumors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dnansumors/benchmark/benchmark.native.js index 320c156f8afa..6a075665b70a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnansumors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnansumors/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnansumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dnansumors/benchmark/benchmark.ndarray.js index 592faa21207e..e368b6a85982 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnansumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnansumors/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumors = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnansumors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dnansumors/benchmark/benchmark.ndarray.native.js index 1f3b2db083b0..c4c8b36f8ddd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnansumors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnansumors/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnansumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dnansumpw/benchmark/benchmark.js index 79c6668caa2e..924a6436edf7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnansumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnansumpw/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumpw = require( './../lib/dnansumpw.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnansumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dnansumpw/benchmark/benchmark.native.js index 5456e3789527..7f5d6b064570 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnansumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnansumpw/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnansumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dnansumpw/benchmark/benchmark.ndarray.js index a2ad04e88585..aeaf0d210eb6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnansumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnansumpw/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumpw = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dnansumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dnansumpw/benchmark/benchmark.ndarray.native.js index 41960428c125..60e1f23c136f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dnansumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dnansumpw/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts index 713574213006..b20dd96b7f74 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts @@ -118,6 +118,7 @@ import gnansumkbn2 = require( '@stdlib/blas/ext/base/gnansumkbn2' ); import gnansumors = require( '@stdlib/blas/ext/base/gnansumors' ); import gnansumpw = require( '@stdlib/blas/ext/base/gnansumpw' ); import goneTo = require( '@stdlib/blas/ext/base/gone-to' ); +import greplicate = require( '@stdlib/blas/ext/base/greplicate' ); import grev = require( '@stdlib/blas/ext/base/grev' ); import gsort = require( '@stdlib/blas/ext/base/gsort' ); import gsort2hp = require( '@stdlib/blas/ext/base/gsort2hp' ); @@ -131,6 +132,7 @@ import gsumkbn = require( '@stdlib/blas/ext/base/gsumkbn' ); import gsumkbn2 = require( '@stdlib/blas/ext/base/gsumkbn2' ); import gsumors = require( '@stdlib/blas/ext/base/gsumors' ); import gsumpw = require( '@stdlib/blas/ext/base/gsumpw' ); +import gvander = require( '@stdlib/blas/ext/base/gvander' ); import gzeroTo = require( '@stdlib/blas/ext/base/gzero-to' ); import ndarray = require( '@stdlib/blas/ext/base/ndarray' ); import sapx = require( '@stdlib/blas/ext/base/sapx' ); @@ -241,8 +243,8 @@ interface Namespace { * @returns row index * * @example - * var Complex64Array = require( `@stdlib/array/complex64` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var Complex64Array = require( '@stdlib/array/complex64' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Complex64Array( [ 1.0, 0.0, 2.0, 0.0, 0.0, 0.0, 3.0, 0.0, 4.0, 0.0, 0.0, 0.0 ] ); * var x = new Complex64Array( [ 2.0, 0.0, 4.0, 0.0 ] ); @@ -252,8 +254,8 @@ interface Namespace { * // returns 1 * * @example - * var Complex64Array = require( `@stdlib/array/complex64` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var Complex64Array = require( '@stdlib/array/complex64' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Complex64Array( [ 1.0, 0.0, 2.0, 0.0, 0.0, 0.0, 3.0, 0.0, 4.0, 0.0, 0.0, 0.0 ] ); * var x = new Complex64Array( [ 2.0, 0.0, 4.0, 0.0 ] ); @@ -816,8 +818,8 @@ interface Namespace { * @returns row index * * @example - * var Float64Array = require( `@stdlib/array/float64` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var Float64Array = require( '@stdlib/array/float64' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Float64Array( [ 1.0, 2.0, 0.0, 3.0, 4.0, 0.0 ] ); * var x = new Float64Array( [ 2.0, 4.0 ] ); @@ -827,8 +829,8 @@ interface Namespace { * // returns 1 * * @example - * var Float64Array = require( `@stdlib/array/float64` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var Float64Array = require( '@stdlib/array/float64' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Float64Array( [ 1.0, 2.0, 0.0, 3.0, 4.0, 0.0 ] ); * var x = new Float64Array( [ 2.0, 4.0 ] ); @@ -2965,6 +2967,33 @@ interface Namespace { */ goneTo: typeof goneTo; + /** + * Replicates each strided array element a specified number of times. + * + * @param N - number of indexed elements + * @param k - number of times to replicate each element + * @param x - input array + * @param strideX - stride length for `x` + * @param out - output array + * @param strideOut - stride length for `out` + * @returns output array + * + * @example + * var x = [ 1.0, 2.0, 3.0 ]; + * var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + * + * ns.greplicate( x.length, 2, x, 1, out, 1 ); + * // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + * + * @example + * var x = [ 1.0, 2.0, 3.0 ]; + * var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + * + * ns.greplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); + * // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + */ + greplicate: typeof greplicate; + /** * Reverses a strided array in-place. * @@ -3300,6 +3329,35 @@ interface Namespace { */ gsumpw: typeof gsumpw; + /** + * Generates a Vandermonde matrix. + * + * @param order - storage layout + * @param mode - mode indicating whether to generate increasing or decreasing powers + * @param M - number of rows in `out` + * @param N - number of columns in `out` + * @param x - input array + * @param strideX - stride length for `x` + * @param out - output matrix + * @param ldo - stride between successive contiguous vectors of the matrix `out` (a.k.a., leading dimension of the matrix `out`) + * @returns output matrix + * + * @example + * var x = [ 1.0, 2.0, 3.0 ]; + * var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + * + * ns.gvander( 'row-major', 1, 3, 3, x, 1, out, 3 ); + * // out => [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] + * + * @example + * var x = [ 1.0, 2.0, 3.0 ]; + * var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + * + * ns.gvander.ndarray( 1, 3, 3, x, 1, 0, out, 3, 1, 0 ); + * // out => [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] + */ + gvander: typeof gvander; + /** * Fills a strided array with linearly spaced numeric elements which increment by `1` starting from zero. * @@ -3933,8 +3991,8 @@ interface Namespace { * @returns row index * * @example - * var Float32Array = require( `@stdlib/array/float32` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var Float32Array = require( '@stdlib/array/float32' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Float32Array( [ 1.0, 2.0, 0.0, 3.0, 4.0, 0.0 ] ); * var x = new Float32Array( [ 2.0, 4.0 ] ); @@ -3944,8 +4002,8 @@ interface Namespace { * // returns 1 * * @example - * var Float32Array = require( `@stdlib/array/float32` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var Float32Array = require( '@stdlib/array/float32' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Float32Array( [ 1.0, 2.0, 0.0, 3.0, 4.0, 0.0 ] ); * var x = new Float32Array( [ 2.0, 4.0 ] ); @@ -4343,7 +4401,7 @@ interface Namespace { * @param N - number of indexed elements * @param order - sort order * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns input array * * @example @@ -4625,8 +4683,8 @@ interface Namespace { * @returns row index * * @example - * var Complex128Array = require( `@stdlib/array/complex128` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Complex128Array( [ 1.0, 0.0, 2.0, 0.0, 0.0, 0.0, 3.0, 0.0, 4.0, 0.0, 0.0, 0.0 ] ); * var x = new Complex128Array( [ 2.0, 0.0, 4.0, 0.0 ] ); @@ -4636,8 +4694,8 @@ interface Namespace { * // returns 1 * * @example - * var Complex128Array = require( `@stdlib/array/complex128` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Complex128Array( [ 1.0, 0.0, 2.0, 0.0, 0.0, 0.0, 3.0, 0.0, 4.0, 0.0, 0.0, 0.0 ] ); * var x = new Complex128Array( [ 2.0, 0.0, 4.0, 0.0 ] ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/README.md b/lib/node_modules/@stdlib/blas/ext/base/drrss/README.md index 1382897c81c8..660d891429a2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/drrss/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/README.md @@ -238,7 +238,7 @@ Computes the square root of the [residual sum of squares][wikipedia-residual-sum const double x[] = { 1.0, -2.0, 2.0 }; const double y[] = { 1.0, 1.0, -4.0 }; -double v = stdlib_strided_drrss_ndarray( 3, x, 1, 0, 1, 0 ); +double v = stdlib_strided_drrss_ndarray( 3, x, 1, 0, y, 1, 0 ); // returns ~6.7 ``` diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.js index 774dc9a22061..bb12e802bd9a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsapxsum = require( './../lib/dsapxsum.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.native.js index 8eaa95fc27c3..7db6979875c5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.ndarray.js index 0b51074c0a99..b3beebf4b972 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsapxsum = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.ndarray.native.js index 16cde4144a2c..1be9b68d92df 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsumpw/benchmark/benchmark.js index 7a4585cc919c..c1f649b0f521 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsumpw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsapxsumpw = require( './../lib/dsapxsumpw.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsumpw/benchmark/benchmark.native.js index 92f9f0c34a30..566db2c50ee5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsumpw/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsumpw/benchmark/benchmark.ndarray.js index 124810d16923..1a304dc55d88 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsumpw/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsapxsumpw = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsumpw/benchmark/benchmark.ndarray.native.js index ad76e1b444b3..d892a487983c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsumpw/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsnannsumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dsnannsumors/benchmark/benchmark.js index 4992efc83f25..cb520b2aa10b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsnannsumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsnannsumors/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsnannsumors = require( './../lib/dsnannsumors.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsnannsumors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsnannsumors/benchmark/benchmark.native.js index 0d1b2f45b07b..4d6ad15cac64 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsnannsumors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsnannsumors/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsnannsumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsnannsumors/benchmark/benchmark.ndarray.js index a7af4f3776d0..ad90a5252e8d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsnannsumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsnannsumors/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsnannsumors = require( './../lib/ndarray.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsnannsumors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsnannsumors/benchmark/benchmark.ndarray.native.js index 6c16d92d1f1a..7b45f475807a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsnannsumors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsnannsumors/benchmark/benchmark.ndarray.native.js @@ -29,6 +29,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsnansum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dsnansum/benchmark/benchmark.js index b4291bbc6302..62384b439298 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsnansum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsnansum/benchmark/benchmark.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsnansum = require( './../lib/dsnansum.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsnansum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsnansum/benchmark/benchmark.native.js index 28ac972c22b1..fe09e0d2c2e9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsnansum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsnansum/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsnansum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsnansum/benchmark/benchmark.ndarray.js index 9f8c8bcf505f..26e51afb4f13 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsnansum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsnansum/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsnansum = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsnansum/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsnansum/benchmark/benchmark.ndarray.native.js index 04c63425789c..e02fb4cefb7b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsnansum/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsnansum/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsnansumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dsnansumors/benchmark/benchmark.js index a2a4ea573d9a..0691c873c7e9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsnansumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsnansumors/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsnansumors = require( './../lib/dsnansumors.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsnansumors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsnansumors/benchmark/benchmark.native.js index 489c9c2634d2..ffa3721c76b3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsnansumors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsnansumors/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsnansumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsnansumors/benchmark/benchmark.ndarray.js index d5abb355d528..ecb6ddf50e90 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsnansumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsnansumors/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsnansumors = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsnansumors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsnansumors/benchmark/benchmark.ndarray.native.js index 2f677e99f9f0..9aa453e58593 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsnansumors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsnansumors/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.js index 60470a812d38..c73027c4edf4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsnansumpw = require( './../lib/dsnansumpw.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.native.js index db27d262778d..10723fceff20 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.ndarray.js index e73251a0fc11..80133f182ec2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsnansumpw = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.ndarray.native.js index f0c1de0d8687..62f58298cdb7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort/benchmark/c/unsorted-random/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/dsort/benchmark/c/unsorted-random/benchmark.length.c index 8ed684ee3af7..bf503e18e04a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort/benchmark/c/unsorted-random/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort/benchmark/c/unsorted-random/benchmark.length.c @@ -174,7 +174,7 @@ int main( void ) { iter = ITERATIONS / pow( 10, i-1 ); for ( j = 0; j < REPEATS; j++ ) { count += 1; - printf( "# c::%s:unsorted,random:len=%d\n", NAME, len ); + printf( "# c::%s::unsorted,random:len=%d\n", NAME, len ); elapsed = benchmark1( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); @@ -185,7 +185,7 @@ int main( void ) { iter = ITERATIONS / pow( 10, i-1 ); for ( j = 0; j < REPEATS; j++ ) { count += 1; - printf( "# c::%s:ndarray:unsorted,random:len=%d\n", NAME, len ); + printf( "# c::%s::unsorted,random:ndarray:len=%d\n", NAME, len ); elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.js index 316b2d72a237..116b56cd638f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/dsort2hp.js' ); @@ -127,7 +128,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.native.js index a70021a35bf1..f798ed2be617 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -137,7 +138,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js index c8b2dcfb84e7..dca62b93650d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/ndarray.js' ); @@ -127,7 +128,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js index 27e0d0d2fb02..75de68a1e941 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -137,7 +138,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_random.js index 804bdb73d929..6837120cf274 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_random.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/dsort2hp.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_random.native.js index c255c6649b45..2e47485b83ea 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_random.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_random.ndarray.js index 5a078225dea3..b2d1ac20efaa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_random.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/ndarray.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_random.ndarray.native.js index 197892274980..351e443d2f2f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.mostly_sorted_random.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.js index 5183db65bdeb..03027ae1a81f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/dsort2hp.js' ); @@ -127,7 +128,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js index 7d93fc9f5940..6068a4844e8b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -137,7 +138,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js index b7ef597af536..d2b3dee89dcf 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/ndarray.js' ); @@ -127,7 +128,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js index b810ce21031c..a02ab3e80533 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -137,7 +138,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_random.js index 5521b309e59d..286515882467 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_random.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/dsort2hp.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_random.native.js index 7f8cbeb139e8..7b5e122f672f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_random.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js index 7219d8693f52..3b713bf7e43a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/ndarray.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js index b8be75683c40..fa9b0c2f0101 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_few_uniques.js index 4ebeccdd0c66..a7c01e8f372e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/dsort2hp.js' ); @@ -128,7 +129,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_few_uniques.native.js index 157fbd787df0..25ebfaa55935 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -138,7 +139,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js index 5405c8b7799d..671f48da4543 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/ndarray.js' ); @@ -128,7 +129,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js index 54285c283b0b..c61341e47cd7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -138,7 +139,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_random.js index 156ea5cb93ad..5d4359ebfd07 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_random.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/dsort2hp.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_random.native.js index 5e853d42c31f..a6ae3ea04610 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_random.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_random.ndarray.js index 81f417fb781a..5ff18cb62f45 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_random.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/ndarray.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_random.ndarray.native.js index 2b8c96d7368c..5ca2a0eee766 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.rev_sorted_random.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_few_uniques.js index 124f2bafe1a0..3e721e95a4b3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/dsort2hp.js' ); @@ -126,7 +127,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_few_uniques.native.js index 2192298bab93..84a09b3e0491 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -136,7 +137,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,sorted,few_uniques:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_few_uniques.ndarray.js index 78fedefb1196..69fa9dbfa018 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/ndarray.js' ); @@ -126,7 +127,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_few_uniques.ndarray.native.js index f7ae227d327a..5c7c9868aa7d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -136,7 +137,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_random.js index 233234a8b7e7..0040e53332c5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_random.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/dsort2hp.js' ); @@ -115,7 +116,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:len='+len, opts, f ); + bench( format( '%s::sorted,random:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_random.native.js index 6345cd62b9be..c158c77e7f49 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_random.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,sorted,random:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_random.ndarray.js index d21e5a86a057..e2ead1735eb7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_random.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/ndarray.js' ); @@ -115,7 +116,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,random:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_random.ndarray.native.js index d65ec80031bd..1077e655af74 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.sorted_random.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_few_uniques.js index 9c0d965c51ed..5fdacf78f870 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/dsort2hp.js' ); @@ -121,7 +122,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_few_uniques.native.js index 9dc141b55aaf..9a7e3b8d1aa0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -131,7 +132,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_few_uniques.ndarray.js index ed2d80d3a7d9..dba4e79e186e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/ndarray.js' ); @@ -121,7 +122,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js index 0380b2c31ddf..edbe9e81e343 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -131,7 +132,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_random.js index d0b40ed2fd62..90c22d84f27a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_random.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/dsort2hp.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:len='+len, opts, f ); + bench( format( '%s::unsorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_random.native.js index ffd705eab921..7ec8103cbcb3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_random.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,random:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_random.ndarray.js index ee65d6c5be67..111603941b2c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_random.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2hp = require( './../lib/ndarray.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_random.ndarray.native.js index aeab8df17668..d0d851023938 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2hp/benchmark/benchmark.unsorted_random.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_few_uniques.js index 9c2c09962550..f2a2f5d8e991 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_few_uniques.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/dsort2ins.js' ); @@ -129,7 +130,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_few_uniques.native.js index 3fcf53281a76..adb3c25ba902 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -138,7 +139,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 2.0/3.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js index 9d2004d6b329..148503c70f73 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/ndarray.js' ); @@ -129,7 +130,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js index 3148164271d5..e6a64a4dd88b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -138,7 +139,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 2.0/3.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_random.js index a669ddec46dc..a93485c866ca 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_random.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/dsort2ins.js' ); @@ -120,7 +121,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_random.native.js index 6c5f75617e75..9591204f67ed 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_random.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -130,7 +131,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_random.ndarray.js index c7c9180a3a03..4bb9afa70e5d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_random.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/ndarray.js' ); @@ -120,7 +121,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_random.ndarray.native.js index e21b617aed00..c317e0b38d7f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.mostly_sorted_random.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -130,7 +131,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_few_uniques.js index e3ccc420ba19..477c9ae24ecf 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_few_uniques.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/dsort2ins.js' ); @@ -129,7 +130,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js index 0493b665d43b..3cae800b475f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -139,7 +140,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js index a5df8dbba485..72ef7fa17269 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/ndarray.js' ); @@ -129,7 +130,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js index 45c4ff0fbf05..b12a7e60ddb1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -139,7 +140,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_random.js index 4cf52826f84a..817d0d678fb9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_random.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/dsort2ins.js' ); @@ -120,7 +121,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_random.native.js index 1397286155bc..cbceb0fc1ae1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_random.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -130,7 +131,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js index 13a2a2082349..9d9b301fc366 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/ndarray.js' ); @@ -120,7 +121,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js index 39edf11e094c..b30a8d1c5e57 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -130,7 +131,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_few_uniques.js index 332676a5495d..7a851ebc17c4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_few_uniques.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/dsort2ins.js' ); @@ -130,7 +131,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_few_uniques.native.js index 89efe513cc87..030407cebe11 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_few_uniques.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -140,7 +141,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js index 74a32829d612..551283d36580 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/ndarray.js' ); @@ -130,7 +131,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js index dd766c6aa33e..32b5e1f3d5aa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -140,7 +141,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_random.js index dc8b777770e3..fedb023397d8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_random.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/dsort2ins.js' ); @@ -120,7 +121,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_random.native.js index ac4f5facd3a4..4bef4977fe2d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_random.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -130,7 +131,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_random.ndarray.js index faf57498f3bd..62d72d1cfde9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_random.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/ndarray.js' ); @@ -120,7 +121,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_random.ndarray.native.js index 51a097ebd950..800009c56580 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.rev_sorted_random.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -130,7 +131,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_few_uniques.js index 0c4fb14d3e9e..b82405dc0d39 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/dsort2ins.js' ); @@ -126,7 +127,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_few_uniques.native.js index 1194480f3dc6..ea7b94765903 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -136,7 +137,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,sorted,few_uniques:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_few_uniques.ndarray.js index ca5ccb3ff30f..a7265b651843 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/ndarray.js' ); @@ -126,7 +127,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_few_uniques.ndarray.native.js index 55f373953574..13a2cc66093e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -136,7 +137,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_random.js index b6ba54021136..68afc0b61f66 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_random.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/dsort2ins.js' ); @@ -115,7 +116,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:len='+len, opts, f ); + bench( format( '%s::sorted,random:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_random.native.js index 9ac32ac5b51f..523115c9894c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_random.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,sorted,random:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_random.ndarray.js index 1892bcdeec70..8b6f0748a9e1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_random.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/ndarray.js' ); @@ -115,7 +116,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,random:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_random.ndarray.native.js index 2624ea079c7c..d1eba70270af 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.sorted_random.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_few_uniques.js index 5fe8f5c68995..e32bda8b1dc1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_few_uniques.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/dsort2ins.js' ); @@ -123,7 +124,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_few_uniques.native.js index 30af8bd3c453..6e0dd4098b5d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_few_uniques.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -133,7 +134,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_few_uniques.ndarray.js index 76118e44d215..577919c1e54c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_few_uniques.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/ndarray.js' ); @@ -123,7 +124,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js index 1bdc55fba87f..7c6ed1ec6a89 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -133,7 +134,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_random.js index 6f3af8c7ef4b..b4b0d87a4192 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_random.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/dsort2ins.js' ); @@ -120,7 +121,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:len='+len, opts, f ); + bench( format( '%s::unsorted,random:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_random.native.js index b89dd01c7683..0c56130697bb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_random.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -130,7 +131,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,random:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_random.ndarray.js index 5c8d703fe20d..d6d1b7b93e53 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_random.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2ins = require( './../lib/ndarray.js' ); @@ -120,7 +121,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_random.ndarray.native.js index 48fdc755b014..b4298706869e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2ins/benchmark/benchmark.unsorted_random.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -130,7 +131,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.js index 4df2e8dc228a..5e93c4996192 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/dsort2sh.js' ); @@ -127,7 +128,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.native.js index 63b4f37f6ce6..173efdadd2a3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -137,7 +138,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js index ee21506656af..0514ba89e15d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/ndarray.js' ); @@ -127,7 +128,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js index b9041295c7bb..506e90e58f50 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -137,7 +138,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_random.js index cf4b58547cca..a28e28d0ed67 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_random.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/dsort2sh.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_random.native.js index 0f2177f31fea..335f5becde66 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_random.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_random.ndarray.js index 5b9266e7331b..4da157f26ed8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_random.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/ndarray.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_random.ndarray.native.js index 3be7032b136f..b15acf499530 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.mostly_sorted_random.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.js index 5c001491cb8e..cea64a8e623b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/dsort2sh.js' ); @@ -127,7 +128,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js index 927a5d5dd4ef..5cdb0731bb73 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -137,7 +138,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js index 2b642b250abc..590f013c16c0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/ndarray.js' ); @@ -127,7 +128,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js index 82f5c68e9fcb..cf83dc4c74a3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -137,7 +138,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_random.js index a1b01b8db7a8..15a68136daf5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_random.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/dsort2sh.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_random.native.js index b79d2e3fc020..f36eb490693a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_random.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js index 5fa627bc7e06..51a79978fb0e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/ndarray.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js index 8e928a72ef66..e80f7f7e3c27 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_few_uniques.js index 187fce1e911f..d0afebd642ba 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/dsort2sh.js' ); @@ -128,7 +129,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_few_uniques.native.js index a44c6982d913..34beb203809d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -138,7 +139,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js index 37071e165010..a1e3a465c82f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/ndarray.js' ); @@ -128,7 +129,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js index 4ad3ce5b45f2..bb0fb0a8aff9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -138,7 +139,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_random.js index 6e9c43794c10..5a662207cc09 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_random.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/dsort2sh.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_random.native.js index c9c2c21f7ef5..00af43e258e3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_random.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_random.ndarray.js index 8f8ac35d5930..dc2098b39daa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_random.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/ndarray.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_random.ndarray.native.js index a4cbec90c6a9..9cb5b0b71394 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.rev_sorted_random.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_few_uniques.js index 47f6663087c5..66f095a866fa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/dsort2sh.js' ); @@ -126,7 +127,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_few_uniques.native.js index 81f9f2026c16..4986bee281e6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -136,7 +137,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,sorted,few_uniques:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_few_uniques.ndarray.js index c9b88a97080e..f811570f2101 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/ndarray.js' ); @@ -126,7 +127,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_few_uniques.ndarray.native.js index 6172415a860b..f0f89789f3e4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -136,7 +137,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_random.js index 7278f683dc6a..6dabc6494684 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_random.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/dsort2sh.js' ); @@ -115,7 +116,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:len='+len, opts, f ); + bench( format( '%s::sorted,random:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_random.native.js index fd767ff69d4c..93e49997e9ba 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_random.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,sorted,random:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_random.ndarray.js index 16138b29ec2c..62aa4f09ebf9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_random.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/ndarray.js' ); @@ -115,7 +116,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,random:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_random.ndarray.native.js index e5ab23b7b577..c2ec6ae13d1f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.sorted_random.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_few_uniques.js index 43dd967c601b..59a5187fa687 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/dsort2sh.js' ); @@ -121,7 +122,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_few_uniques.native.js index efe3d61e65f7..e91038b24f25 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -131,7 +132,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_few_uniques.ndarray.js index 19ab154e257e..0d7089d69b0f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/ndarray.js' ); @@ -121,7 +122,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js index d47937b93d76..5e7350f4930d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -131,7 +132,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_random.js index 3cefa1f81115..98f731f5f65c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_random.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/dsort2sh.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:len='+len, opts, f ); + bench( format( '%s::unsorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_random.native.js index 6962010e5790..d6c1ad61ef68 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_random.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,random:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_random.ndarray.js index 9d9c2eb9c49a..b22a074f9158 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_random.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsort2sh = require( './../lib/ndarray.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_random.ndarray.native.js index 7f18ada2acda..bbaa2b9c0910 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsort2sh/benchmark/benchmark.unsorted_random.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_few_uniques.js index 92a981b1290f..1cb77cc01267 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/dsorthp.js' ); @@ -124,7 +125,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_few_uniques.native.js index a28975260a2c..93450f6b9ad8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -134,7 +135,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js index 759e361b0813..546ed2099d68 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/ndarray.js' ); @@ -124,7 +125,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js index 32b583fef1a8..6256851af24a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -134,7 +135,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_random.js index 565a7a35f5eb..fcfe2b70b10a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_random.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/dsorthp.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_random.native.js index b4afb6673531..690c30737080 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_random.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_random.ndarray.js index 8b4b8278fff8..a06065bcdc07 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_random.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/ndarray.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_random.ndarray.native.js index 1b46214f3755..f1ae9b04641d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.mostly_sorted_random.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.js index cdac83429632..14b739e8d1c2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/dsorthp.js' ); @@ -124,7 +125,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js index 1d6a79e4d9d5..a95af408c77e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -134,7 +135,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js index 3d85df25dad7..9f3296d5c2ae 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/ndarray.js' ); @@ -124,7 +125,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js index 459effd63c74..aae06e7466ce 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -134,7 +135,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_random.js index 2305fa4cbb2f..bdde98835fd9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_random.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/dsorthp.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_random.native.js index c158cbd2a3a9..dfcba611f8b2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_random.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js index eac3de517b32..e66114f59512 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/ndarray.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js index 8c6ccc8ddd0e..bc4abc429847 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_few_uniques.js index 4490c45bfba0..66abf9c44ddc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/dsorthp.js' ); @@ -125,7 +126,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_few_uniques.native.js index 9cd4fae01864..6a089f636a92 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -135,7 +136,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js index b732319cb662..d508841eda26 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/ndarray.js' ); @@ -125,7 +126,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js index 4554f5308825..18c2c4421725 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -135,7 +136,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_random.js index bd7486b97fb2..569477080c8d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_random.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/dsorthp.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_random.native.js index 8606f1e81276..b7acc0f5e5f0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_random.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_random.ndarray.js index b97edb800168..b3a1fa490915 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_random.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/ndarray.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_random.ndarray.native.js index 7766d1e6c800..7af3bc1e48c2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.rev_sorted_random.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_few_uniques.js index 84c225320bc5..cca41a3eec65 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/dsorthp.js' ); @@ -123,7 +124,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_few_uniques.native.js index 740fc73b0e18..b094d6a9846e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -133,7 +134,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,sorted,few_uniques:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_few_uniques.ndarray.js index d86a0c1e91df..f17d7c42d16b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/ndarray.js' ); @@ -123,7 +124,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_few_uniques.ndarray.native.js index 60c5ef73e58d..f2fe57f930ba 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -133,7 +134,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_random.js index d00a5c605bcc..1ec6e54c8ed6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_random.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/dsorthp.js' ); @@ -112,7 +113,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:len='+len, opts, f ); + bench( format( '%s::sorted,random:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_random.native.js index 301eca9a535d..19b467862545 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_random.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -122,7 +123,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,sorted,random:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_random.ndarray.js index b05b1addbed5..ddfee9b0d1e1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_random.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/ndarray.js' ); @@ -112,7 +113,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,random:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_random.ndarray.native.js index eb0b5fd3146a..f1f0b926b12c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.sorted_random.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -122,7 +123,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_few_uniques.js index d67441d10270..5fbc8b41a48e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/dsorthp.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_few_uniques.native.js index 4dccf4d6b6a2..eec126100afc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_few_uniques.ndarray.js index b532c4895afd..210a697e00d6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/ndarray.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js index b31c09a70354..de38d6fd9434 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_random.js index 7de79ceae505..91ecfab922c4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_random.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/dsorthp.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:len='+len, opts, f ); + bench( format( '%s::unsorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_random.native.js index a606a5f9b573..e2a6c66196ac 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_random.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,random:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_random.ndarray.js index 086bc120162b..9c1c2984e50a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_random.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib/ndarray.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_random.ndarray.native.js index 319922f5cdf2..52dca67408dc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/benchmark.unsorted_random.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/c/unsorted-random/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/c/unsorted-random/benchmark.length.c index 8c63e53c99a1..73cac97a1aa1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/c/unsorted-random/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dsorthp/benchmark/c/unsorted-random/benchmark.length.c @@ -174,7 +174,7 @@ int main( void ) { iter = ITERATIONS / pow( 10, i-1 ); for ( j = 0; j < REPEATS; j++ ) { count += 1; - printf( "# c::%s:unsorted,random:len=%d\n", NAME, len ); + printf( "# c::%s::unsorted,random:len=%d\n", NAME, len ); elapsed = benchmark1( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); @@ -185,7 +185,7 @@ int main( void ) { iter = ITERATIONS / pow( 10, i-1 ); for ( j = 0; j < REPEATS; j++ ) { count += 1; - printf( "# c::%s:ndarray:unsorted,random:len=%d\n", NAME, len ); + printf( "# c::%s::unsorted,random:ndarray:len=%d\n", NAME, len ); elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_few_uniques.js index 9dbfe26d9ee3..2fcc8a5a0d05 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_few_uniques.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/dsortins.js' ); @@ -126,7 +127,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_few_uniques.native.js index 828dfc4e9919..d62c77d5d1ac 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -135,7 +136,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 2.0/3.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js index 3e26e6792aad..cddf96465a0f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/ndarray.js' ); @@ -126,7 +127,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js index 37496bcfd089..1cc9a5af5d55 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -135,7 +136,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 2.0/3.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_random.js index 7a52c5e58151..13743b059730 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_random.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/dsortins.js' ); @@ -117,7 +118,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_random.native.js index 690fd277ec7c..49bb2f775467 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_random.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -127,7 +128,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_random.ndarray.js index 2241d3504228..e63f874ebace 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_random.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/ndarray.js' ); @@ -117,7 +118,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_random.ndarray.native.js index 1f9987ca8528..ca10907b7d65 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.mostly_sorted_random.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -127,7 +128,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.js index 1847b0616451..77607c82b71d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/dsortins.js' ); @@ -126,7 +127,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js index f5d71578ffee..e2180238de2e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -136,7 +137,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js index 4907349b36c2..21bd6266a7e2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/ndarray.js' ); @@ -126,7 +127,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js index 725743751177..b540be8e26c4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -136,7 +137,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_random.js index 95b8d3857b40..df094a15b783 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_random.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/dsortins.js' ); @@ -117,7 +118,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_random.native.js index 99bd49f5c82e..e9a2ca3680e8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_random.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -127,7 +128,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js index d2fba19c4a7e..29b0524fdccb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/ndarray.js' ); @@ -117,7 +118,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js index fd13506167bc..f35f391f631c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -127,7 +128,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_few_uniques.js index 9dfff6f05267..c38dfc765bbc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_few_uniques.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/dsortins.js' ); @@ -127,7 +128,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_few_uniques.native.js index b33f1abd21de..e34115fd53d8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_few_uniques.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -137,7 +138,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js index 1cfa1d8c2ce1..825d3bf7ea02 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/ndarray.js' ); @@ -127,7 +128,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js index ccb8e2c9e0d8..9e0bf67c4a5b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -137,7 +138,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_random.js index ee83a4b8cedc..f43b197f1511 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_random.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/dsortins.js' ); @@ -117,7 +118,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_random.native.js index f87d49ea1731..18d389d04921 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_random.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -127,7 +128,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_random.ndarray.js index 9611b97089d3..3246fa3c86b1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_random.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/ndarray.js' ); @@ -117,7 +118,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_random.ndarray.native.js index 1d4800e5fe07..3bbf33009b5e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.rev_sorted_random.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -127,7 +128,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_few_uniques.js index 0528baa48fa8..691765c9fb3a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/dsortins.js' ); @@ -123,7 +124,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_few_uniques.native.js index e8f1257e3a00..7d2e9ad2dc8f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -133,7 +134,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,sorted,few_uniques:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_few_uniques.ndarray.js index c8011f2f26ca..40df0b741f2c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/ndarray.js' ); @@ -123,7 +124,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_few_uniques.ndarray.native.js index e29fdb61d86d..43ddea7b26e5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -133,7 +134,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_random.js index cfd5819b860c..eca9c5da7430 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_random.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/dsortins.js' ); @@ -112,7 +113,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:len='+len, opts, f ); + bench( format( '%s::sorted,random:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_random.native.js index 1011fc2836ee..8e51f3b55019 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_random.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -122,7 +123,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,sorted,random:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_random.ndarray.js index f48bc588f146..e115f4e2ff5d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_random.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/ndarray.js' ); @@ -112,7 +113,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,random:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_random.ndarray.native.js index 7ad451085d96..d823dfbb281c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.sorted_random.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -122,7 +123,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_few_uniques.js index 4a15d39f6575..2119001a8af1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_few_uniques.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/dsortins.js' ); @@ -120,7 +121,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_few_uniques.native.js index a1c4c81a91e4..f37d8ebe8919 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_few_uniques.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -130,7 +131,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_few_uniques.ndarray.js index c0b44b70b042..25053acccc1d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_few_uniques.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/ndarray.js' ); @@ -120,7 +121,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js index 068d988b6434..a3cc036d9ee0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -130,7 +131,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_random.js index 8f1663d41f58..25ab467e6651 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_random.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/dsortins.js' ); @@ -117,7 +118,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:len='+len, opts, f ); + bench( format( '%s::unsorted,random:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_random.native.js index 9b478e16db08..c65c928f8e31 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_random.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -127,7 +128,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,random:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_random.ndarray.js index 4f12d9db278d..43b6d2110771 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_random.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib/ndarray.js' ); @@ -117,7 +118,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_random.ndarray.native.js index abd29ea91d09..2c38ee4d67dd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/benchmark.unsorted_random.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -127,7 +128,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/c/unsorted-random/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/c/unsorted-random/benchmark.length.c index e745bc0db139..61bf4742d915 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/c/unsorted-random/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortins/benchmark/c/unsorted-random/benchmark.length.c @@ -174,7 +174,7 @@ int main( void ) { iter = ITERATIONS / pow( 10, i-1 ); for ( j = 0; j < REPEATS; j++ ) { count += 1; - printf( "# c::%s:unsorted,random:len=%d\n", NAME, len ); + printf( "# c::%s::unsorted,random:len=%d\n", NAME, len ); elapsed = benchmark1( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); @@ -185,7 +185,7 @@ int main( void ) { iter = ITERATIONS / pow( 10, i-1 ); for ( j = 0; j < REPEATS; j++ ) { count += 1; - printf( "# c::%s:ndarray:unsorted,random:len=%d\n", NAME, len ); + printf( "# c::%s::unsorted,random:ndarray:len=%d\n", NAME, len ); elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_few_uniques.js index 45ee1ba98421..231d1aab48ac 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/dsortsh.js' ); @@ -124,7 +125,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_few_uniques.native.js index c37246d15b8c..f47851dca9b2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -134,7 +135,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js index d5bd71bef7d3..e105a1a88f7d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/ndarray.js' ); @@ -124,7 +125,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js index 8d1a98059a85..b14dcc7f6e28 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -134,7 +135,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_random.js index c6e7b3c8fd61..25156fa88443 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_random.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/dsortsh.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_random.native.js index c013a9c28ee7..8aeb02463f2d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_random.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_random.ndarray.js index 80bdd1af64df..c9854fdf1982 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_random.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/ndarray.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_random.ndarray.native.js index ba9cca96c986..fd33a7f7a66a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.mostly_sorted_random.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,mostly_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,mostly_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.js index 3158d068f315..d3a2ffb63329 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/dsortsh.js' ); @@ -124,7 +125,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js index e9c318f6d909..d2c33460c8d7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -134,7 +135,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js index 52ffe2c0e595..4fe7408cb73e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/ndarray.js' ); @@ -124,7 +125,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js index c473c1be422c..d3123c7bc86d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -134,7 +135,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_random.js index 1871a64bbd6b..3b08581e10ce 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_random.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/dsortsh.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_random.native.js index 3f975c060789..f4a86f985b44 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_random.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js index 98186f6475b1..3c70b12a429c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/ndarray.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js index e3785d5f25f6..39758b6861d6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_mostly_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_few_uniques.js index 48ed04129b2b..4312b0c3174c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/dsortsh.js' ); @@ -125,7 +126,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_few_uniques.native.js index 26a83cfacbdf..8899fcff284c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -135,7 +136,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js index 58e1517b414c..94bad37abf6e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/ndarray.js' ); @@ -125,7 +126,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js index 62435b05cc34..530b3ad24e82 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -135,7 +136,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_random.js index 944ac6485c2d..815a48bb9003 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_random.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/dsortsh.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_random.native.js index 349caa490e84..008d6b8bbf17 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_random.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_random.ndarray.js index 6f2888812df1..863db34d9556 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_random.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/ndarray.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_random.ndarray.native.js index 3d7c7836f4c7..f6ec159cce08 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.rev_sorted_random.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_few_uniques.js index 1728ea561858..2df34edc91ee 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/dsortsh.js' ); @@ -123,7 +124,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_few_uniques.native.js index 2d130bfe69ed..11d9b97c5f23 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -133,7 +134,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,sorted,few_uniques:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_few_uniques.ndarray.js index 69403d592ccd..76fe55b15a64 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/ndarray.js' ); @@ -123,7 +124,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_few_uniques.ndarray.native.js index 56becff57fea..22505317e98e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -133,7 +134,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,sorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_random.js index 0acd7fa5f651..d27fcd3e3484 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_random.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/dsortsh.js' ); @@ -112,7 +113,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:len='+len, opts, f ); + bench( format( '%s::sorted,random:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_random.native.js index 35d8b117fcab..a290acedc0d6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_random.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -122,7 +123,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,random:len='+len, bopts, f ); + bench( format( '%s::native,sorted,random:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_random.ndarray.js index b1035fc69a50..30669ed0c1b0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_random.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/ndarray.js' ); @@ -112,7 +113,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,random:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_random.ndarray.native.js index b2b4837cc823..05b468cabdf7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.sorted_random.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -122,7 +123,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( bopts.iterations, len ); - bench( pkg+'::native,sorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,sorted,random:ndarray:len=%d', pkg, len ), bopts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_few_uniques.js index 77d667e3ce2a..dfdc1b7616c4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_few_uniques.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/dsortsh.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_few_uniques.native.js index e54ab9093436..822ae1c72e21 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_few_uniques.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_few_uniques.ndarray.js index 84dc0bb143e4..f032441d1586 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_few_uniques.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/ndarray.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js index bdc1138730bd..e8382a318545 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -128,7 +129,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_random.js index d316c8e86953..2c0f611bd4aa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_random.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/dsortsh.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:len='+len, opts, f ); + bench( format( '%s::unsorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_random.native.js index 7820416f87db..b48881051fdf 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_random.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,random:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_random.ndarray.js index 91b1467983a5..c84eb409007b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_random.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib/ndarray.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_random.ndarray.native.js index 698b45582a4c..019c7184a12c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsortsh/benchmark/benchmark.unsorted_random.ndarray.native.js @@ -29,6 +29,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var dcopy = require( '@stdlib/blas/base/dcopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -125,7 +126,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dssumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dssumors/benchmark/benchmark.js index 9857ddd0397c..d4fa566b047c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dssumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dssumors/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dssumors = require( './../lib/dssumors.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dssumors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dssumors/benchmark/benchmark.native.js index 2e4370d42604..7ff1ae020b96 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dssumors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dssumors/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dssumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dssumors/benchmark/benchmark.ndarray.js index f3e101cd0d15..6818c11d2107 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dssumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dssumors/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dssumors = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dssumors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dssumors/benchmark/benchmark.ndarray.native.js index a35cc3bd4a17..4d836d8931de 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dssumors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dssumors/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dssumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dssumpw/benchmark/benchmark.js index 4d9d24494ace..7df4d40f7a35 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dssumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dssumpw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dssumpw = require( './../lib/dssumpw.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dssumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dssumpw/benchmark/benchmark.native.js index 059aac745a76..3761fc10c66a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dssumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dssumpw/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dssumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dssumpw/benchmark/benchmark.ndarray.js index c1f81526137f..62c990199375 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dssumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dssumpw/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dssumpw = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dssumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dssumpw/benchmark/benchmark.ndarray.native.js index c32b3e4cda6f..3a30c764701c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dssumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dssumpw/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.js index 7ae3b72feaf2..1ebfa7c0a45d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsum = require( './../lib/dsum.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.native.js index c1c30acca359..a7d003b06ef4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.ndarray.js index aa5fe53a2bbf..62d0e76b843f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsum = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.ndarray.native.js index 2036f71a89a3..5e03be2d7cb3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.js index 3aa2915b4e29..37203cfd6c7c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsumpw = require( './../lib/dsumpw.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.native.js index 3ea84bb7b1d1..f4100dcdf2fb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.ndarray.js index 2484acfefda3..8c4b84334730 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsumpw = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.ndarray.native.js index c8bcb9107e11..a3a721b96d04 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapx/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gapx/benchmark/benchmark.js index 90ded8d7f0b6..d57e2d3ea6b4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapx/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapx/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gapx = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapx/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapx/benchmark/benchmark.ndarray.js index 7eea0dcaccb6..f1fa74a734da 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapx/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapx/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gapx = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/benchmark/benchmark.js index 77e237871d95..a22b89bc2020 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gapxsum = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/benchmark/benchmark.ndarray.js index 7e2c380beaff..6f92f94dda3f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gapxsum = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/benchmark/benchmark.js index d6af26904f7e..da7c63531072 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gapxsumors = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/benchmark/benchmark.ndarray.js index 12105bc1aa6e..28448c1f88ae 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gapxsumors = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/benchmark/benchmark.js index fb862c120d69..249de2a0529e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gapxsumpw = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/benchmark/benchmark.ndarray.js index 4cc9fa6c3aa5..a739d41e8984 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gapxsumpw = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/benchmark/benchmark.js index 9752bfbe8e73..3bfe7d846f5f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gasumpw = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/benchmark/benchmark.ndarray.js index c92dedbe0cb0..cd08fb0b98e6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gasumpw = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/benchmark/benchmark.js index f0d1c272ccf8..252a84fcfcf2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gcusumkbn = require( './../lib/main.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/benchmark/benchmark.ndarray.js index 6b520881e3e6..a293915745ec 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gcusumkbn = require( './../lib/ndarray.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/benchmark/benchmark.js index 9802d8e8dab9..f0bddc062bb4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gcusumkbn2 = require( './../lib/main.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/benchmark/benchmark.ndarray.js index 0328da479507..e6ab3a72a389 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gcusumkbn2 = require( './../lib/ndarray.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/benchmark/benchmark.js index c29a04ccd114..474d6e28160c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gcusumors = require( './../lib/main.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/benchmark/benchmark.ndarray.js index 39505744c752..a3190e57e793 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gcusumors = require( './../lib/ndarray.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/benchmark/benchmark.js index a7f6be8bea67..ac83360ec88a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gcusumpw = require( './../lib/main.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/benchmark/benchmark.ndarray.js index 0c00786a7408..4e2d3975b368 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gcusumpw = require( './../lib/ndarray.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/benchmark/benchmark.js index c2df62c4fd8c..b170902a9b51 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledBy = require( '@stdlib/array/base/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gfillBy = require( './../lib' ); @@ -92,7 +93,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/benchmark/benchmark.ndarray.js index 5f2bb44e4063..2fdf27ed6b60 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledBy = require( '@stdlib/array/base/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gfillBy = require( './../lib' ).ndarray; @@ -92,7 +93,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfind-index/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gfind-index/benchmark/benchmark.js index 9286ca981624..9c9dfeb709b1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfind-index/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfind-index/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var isInteger = require( '@stdlib/math/base/assert/is-integer' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gfindIndex = require( './../lib' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfind-index/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfind-index/benchmark/benchmark.ndarray.js index 810a4e431ada..7f862d36d5e3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfind-index/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfind-index/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var isInteger = require( '@stdlib/math/base/assert/is-integer' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gfindIndex = require( './../lib' ).ndarray; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfind-last-index/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gfind-last-index/benchmark/benchmark.js index d991a3bfe451..5ef90bede6e8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfind-last-index/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfind-last-index/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var isInteger = require( '@stdlib/math/base/assert/is-integer' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gfindLastIndex = require( './../lib' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfind-last-index/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfind-last-index/benchmark/benchmark.ndarray.js index 5c93d0eb214a..9efc9fca29cc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfind-last-index/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfind-last-index/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var isInteger = require( '@stdlib/math/base/assert/is-integer' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gfindLastIndex = require( './../lib' ).ndarray; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-row/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-row/benchmark/benchmark.js index 6c59a8ecebb3..a537ceb8f851 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-row/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-row/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var zeros = require( '@stdlib/array/zeros' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gindexOfRow = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); f = createBenchmark( ord, N ); - bench( pkg+'::square_matrix:order='+ord+',size='+(N*N), f ); + bench( format( '%s::square_matrix:order=%s,size=%d', pkg, ord, N*N ), f ); } } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-row/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-row/benchmark/benchmark.ndarray.js index a2a68bc9242e..d58ed05dbfeb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-row/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-row/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gindexOfRow = require( './../lib/ndarray.js' ); @@ -115,7 +116,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); f = createBenchmark( ord, N ); - bench( pkg+'::square_matrix:ndarray:order='+ord+',size='+(N*N), f ); + bench( format( '%s::square_matrix:ndarray:order=%s,size=%d', pkg, ord, N*N ), f ); } } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of/benchmark/benchmark.js index d28575b0258c..c6a9f00c0b1b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gindex-of/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var oneTo = require( '@stdlib/array/one-to' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gindexOf = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of/benchmark/benchmark.ndarray.js index cc23229fb23d..95e0925ba4a3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gindex-of/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var oneTo = require( '@stdlib/array/one-to' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gindexOf = require( './../lib/ndarray.js' ); @@ -89,7 +90,7 @@ function main() { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gjoin/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gjoin/benchmark/benchmark.js index d55a91d819ae..c1d6f85a9af4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gjoin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gjoin/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var oneTo = require( '@stdlib/array/one-to' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gjoin = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gjoin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gjoin/benchmark/benchmark.ndarray.js index 3f5d62ea1b1b..db7310ff485e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gjoin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gjoin/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var oneTo = require( '@stdlib/array/one-to' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gjoin = require( './../lib/ndarray.js' ); @@ -89,7 +90,7 @@ function main() { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/glinspace/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/glinspace/benchmark/benchmark.js index 6eb7f00f1aad..3bdabc51cab3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/glinspace/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/glinspace/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var glinspace = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/glinspace/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/glinspace/benchmark/benchmark.ndarray.js index 6dec7d9441bc..e09a5a76cf65 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/glinspace/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/glinspace/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var glinspace = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnannsumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gnannsumpw/benchmark/benchmark.js index 296c90990960..a5a507e0ad04 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnannsumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnannsumpw/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnannsumpw = require( './../lib' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnannsumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnannsumpw/benchmark/benchmark.ndarray.js index 4cabd340ec14..a016c75e9a2f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnannsumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnannsumpw/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnannsumpw = require( './../lib/ndarray.js' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gnansum/benchmark/benchmark.js index 030114dd91e4..64acef817b17 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansum/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnansum = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansum/benchmark/benchmark.ndarray.js index 4b9bfc006f4b..39bfc1c2e431 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansum/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnansum = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/benchmark/benchmark.js index ee14c29d362b..26c2d1c5fb47 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnansumkbn = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/benchmark/benchmark.ndarray.js index 55d01555b7e4..ac916e6f5133 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnansumkbn = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/benchmark/benchmark.js index 794304ea86ce..4ebf0bce16a8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/benchmark/benchmark.js @@ -26,6 +26,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnansumkbn2 = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/benchmark/benchmark.ndarray.js index 08b2156611c7..4a8178eaab49 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnansumkbn2 = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/benchmark/benchmark.js index ed66dfddf6f7..5dab6c05f53b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnansumors = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/benchmark/benchmark.ndarray.js index 863486b6c401..099d1e076835 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnansumors = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/benchmark/benchmark.js index cd23fbc7e996..0b0a6d406849 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnansumpw = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/benchmark/benchmark.ndarray.js index 060c10556f92..2fcc3649840b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnansumpw = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/greplicate/README.md b/lib/node_modules/@stdlib/blas/ext/base/greplicate/README.md new file mode 100644 index 000000000000..3d591c60badf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/greplicate/README.md @@ -0,0 +1,177 @@ + + +# greplicate + +> Replicate each strided array element a specified number of times. + +
+ +
+ + + +
+ +## Usage + +```javascript +var greplicate = require( '@stdlib/blas/ext/base/greplicate' ); +``` + +#### greplicate( N, k, x, strideX, out, strideOut ) + +Replicates each strided array element a specified number of times. + +```javascript +var x = [ 1.0, 2.0, 3.0 ]; +var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + +greplicate( x.length, 2, x, 1, out, 1 ); +// out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **k**: number of times to replicate each element. +- **x**: input array. +- **strideX**: stride length for `x`. +- **out**: output array. +- **strideOut**: stride length for `out`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to replicate every other element: + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; +var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + +greplicate( 3, 2, x, 2, out, 1 ); +// out => [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial arrays... +var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var out0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +// Create offset views... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*2 ); // start at 3rd element + +greplicate( 3, 2, x1, 2, out1, 1 ); +// out0 => [ 0.0, 0.0, 2.0, 2.0, 4.0, 4.0, 6.0, 6.0 ] +``` + +#### greplicate.ndarray( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) + +Replicates each strided array element a specified number of times using alternative indexing semantics. + +```javascript +var x = [ 1.0, 2.0, 3.0 ]; +var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + +greplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); +// out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetOut**: starting index for `out`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to replicate every other element in the strided input array starting from the second element and to store in the last `N*k` elements of the strided output array starting from the last element: + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; +var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + +greplicate.ndarray( 3, 2, x, 2, 1, out, -1, out.length-1 ); +// out => [ 0.0, 0.0, 6.0, 6.0, 4.0, 4.0, 2.0, 2.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0` or `k <= 0`, both functions return `out` unchanged. +- Both functions assume that the output array supports `N*k` indexed elements. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Float64Array = require( '@stdlib/array/float64' ); +var greplicate = require( '@stdlib/blas/ext/base/greplicate' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +console.log( x ); + +var out = new Float64Array( x.length * 3 ); +console.log( out ); + +greplicate( x.length, 3, x, 1, out, 1 ); +console.log( out ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/greplicate/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/greplicate/benchmark/benchmark.js new file mode 100644 index 000000000000..fa40e657c74b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/greplicate/benchmark/benchmark.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var greplicate = require( './../lib/main.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var out = zeros( len * 2, options.dtype ); + var x = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x[ 0 ] += 1.0; + v = greplicate( x.length, 2, x, 1, out, 1 ); + if ( isnan( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/greplicate/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/greplicate/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..aa6ec6ad0d2b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/greplicate/benchmark/benchmark.ndarray.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var greplicate = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var out = zeros( len * 2, options.dtype ); + var x = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x[ 0 ] += 1.0; + v = greplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + if ( isnan( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/greplicate/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/greplicate/docs/repl.txt new file mode 100644 index 000000000000..b17f53ae12cf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/greplicate/docs/repl.txt @@ -0,0 +1,118 @@ + +{{alias}}( N, k, x, strideX, out, strideOut ) + Replicates each strided array element a specified number of times. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0` or `k <= 0`, the function returns `out` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + k: integer + Number of times to replicate each element. + + x: ArrayLikeObject + Input array. + + strideX: integer + Stride length for `x`. + + out: ArrayLikeObject + Output array. + + strideOut: integer + Stride length for `out`. + + Returns + ------- + out: ArrayLikeObject + Output array. + + Examples + -------- + // Standard Usage: + > var x = [ 1.0, 2.0, 3.0 ]; + > var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > {{alias}}( x.length, 2, x, 1, out, 1 ) + [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + + // Using `N` and stride parameters: + > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > {{alias}}( 3, 2, x, 2, out, 1 ) + [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > var out0 = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var out1 = new {{alias:@stdlib/array/float64}}( out0.buffer, out0.BYTES_PER_ELEMENT*2 ); + > {{alias}}( 3, 2, x1, 2, out1, 1 ) + [ 2.0, 2.0, 4.0, 4.0, 6.0, 6.0 ] + > out0 + [ 0.0, 0.0, 2.0, 2.0, 4.0, 4.0, 6.0, 6.0 ] + + +{{alias}}.ndarray( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) + Replicates each strided array element a specified number of times using + alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + k: integer + Number of times to replicate each element. + + x: ArrayLikeObject + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + out: ArrayLikeObject + Output array. + + strideOut: integer + Stride length for `out`. + + offsetOut: integer + Starting index for `out`. + + Returns + ------- + out: ArrayLikeObject + Output array. + + Examples + -------- + // Standard Usage: + > var x = [ 1.0, 2.0, 3.0 ]; + > var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > {{alias}}.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ) + [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + + // Advanced indexing: + > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > {{alias}}.ndarray( 3, 2, x, 2, 1, out, -1, out.length-1 ) + [ 6.0, 6.0, 4.0, 4.0, 2.0, 2.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/greplicate/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/greplicate/docs/types/index.d.ts new file mode 100644 index 000000000000..70f490125920 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/greplicate/docs/types/index.d.ts @@ -0,0 +1,112 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = Collection | AccessorArrayLike; + +/** +* Output array. +*/ +type OutputArray = Collection | AccessorArrayLike; + +/** +* Interface describing `greplicate`. +*/ +interface Routine { + /** + * Replicates each strided array element a specified number of times. + * + * @param N - number of indexed elements + * @param k - number of times to replicate each element + * @param x - input array + * @param strideX - stride length for `x` + * @param out - output array + * @param strideOut - stride length for `out` + * @returns output array + * + * @example + * var x = [ 1.0, 2.0, 3.0 ]; + * var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + * + * greplicate( x.length, 2, x, 1, out, 1 ); + * // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + */ + = InputArray, V extends OutputArray = OutputArray>( N: number, k: number, x: U, strideX: number, out: V, strideOut: number ): V; + + /** + * Replicates each strided array element a specified number of times using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param k - number of times to replicate each element + * @param x - input array + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` + * @param out - output array + * @param strideOut - stride length for `out` + * @param offsetOut - starting index for `out` + * @returns output array + * + * @example + * var x = [ 1.0, 2.0, 3.0 ]; + * var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + * + * greplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); + * // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + */ + ndarray = InputArray, V extends OutputArray = OutputArray>( N: number, k: number, x: U, strideX: number, offsetX: number, out: V, strideOut: number, offsetOut: number ): V; +} + +/** +* Replicates each strided array element a specified number of times. +* +* @param N - number of indexed elements +* @param k - number of times to replicate each element +* @param x - input array +* @param strideX - stride length for `x` +* @param out - output array +* @param strideOut - stride length for `out` +* @returns output array +* +* @example +* var x = [ 1.0, 2.0, 3.0 ]; +* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; +* +* greplicate( x.length, 2, x, 1, out, 1 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +* +* @example +* var x = [ 1.0, 2.0, 3.0 ]; +* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; +* +* greplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +*/ +declare var greplicate: Routine; + + +// EXPORTS // + +export = greplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/greplicate/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/greplicate/docs/types/test.ts new file mode 100644 index 000000000000..8cbf784be867 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/greplicate/docs/types/test.ts @@ -0,0 +1,283 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import greplicate = require( './index' ); + + +// TESTS // + +// The function returns a collection... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + greplicate( x.length, 2, x, 1, out, 1 ); // $ExpectType Float64Array + greplicate( x.length, 2, new AccessorArray( x ), 1, new AccessorArray( out ), 1 ); // $ExpectType AccessorArray +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + greplicate( '10', 2, x, 1, out, 1 ); // $ExpectError + greplicate( true, 2, x, 1, out, 1 ); // $ExpectError + greplicate( false, 2, x, 1, out, 1 ); // $ExpectError + greplicate( null, 2, x, 1, out, 1 ); // $ExpectError + greplicate( undefined, 2, x, 1, out, 1 ); // $ExpectError + greplicate( [], 2, x, 1, out, 1 ); // $ExpectError + greplicate( {}, 2, x, 1, out, 1 ); // $ExpectError + greplicate( ( x: number ): number => x, 2, x, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + greplicate( x.length, '10', x, 1, out, 1 ); // $ExpectError + greplicate( x.length, true, x, 1, out, 1 ); // $ExpectError + greplicate( x.length, false, x, 1, out, 1 ); // $ExpectError + greplicate( x.length, null, x, 1, out, 1 ); // $ExpectError + greplicate( x.length, undefined, x, 1, out, 1 ); // $ExpectError + greplicate( x.length, [], x, 1, out, 1 ); // $ExpectError + greplicate( x.length, {}, x, 1, out, 1 ); // $ExpectError + greplicate( x.length, ( x: number ): number => x, x, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a collection... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + greplicate( x.length, 2, 10, 1, out, 1 ); // $ExpectError + greplicate( x.length, 2, '10', 1, out, 1 ); // $ExpectError + greplicate( x.length, 2, true, 1, out, 1 ); // $ExpectError + greplicate( x.length, 2, false, 1, out, 1 ); // $ExpectError + greplicate( x.length, 2, null, 1, out, 1 ); // $ExpectError + greplicate( x.length, 2, undefined, 1, out, 1 ); // $ExpectError + greplicate( x.length, 2, [ '1' ], 1, out, 1 ); // $ExpectError + greplicate( x.length, 2, {}, 1, out, 1 ); // $ExpectError + greplicate( x.length, 2, ( x: number ): number => x, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + greplicate( x.length, 2, x, '10', out, 1 ); // $ExpectError + greplicate( x.length, 2, x, true, out, 1 ); // $ExpectError + greplicate( x.length, 2, x, false, out, 1 ); // $ExpectError + greplicate( x.length, 2, x, null, out, 1 ); // $ExpectError + greplicate( x.length, 2, x, undefined, out, 1 ); // $ExpectError + greplicate( x.length, 2, x, [], out, 1 ); // $ExpectError + greplicate( x.length, 2, x, {}, out, 1 ); // $ExpectError + greplicate( x.length, 2, x, ( x: number ): number => x, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a collection... +{ + const x = new Float64Array( 10 ); + + greplicate( x.length, 2, x, 1, 10, 1 ); // $ExpectError + greplicate( x.length, 2, x, 1, '10', 1 ); // $ExpectError + greplicate( x.length, 2, x, 1, true, 1 ); // $ExpectError + greplicate( x.length, 2, x, 1, false, 1 ); // $ExpectError + greplicate( x.length, 2, x, 1, null, 1 ); // $ExpectError + greplicate( x.length, 2, x, 1, undefined, 1 ); // $ExpectError + greplicate( x.length, 2, x, 1, [ '1' ], 1 ); // $ExpectError + greplicate( x.length, 2, x, 1, {}, 1 ); // $ExpectError + greplicate( x.length, 2, x, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + greplicate( x.length, 2, x, 1, out, '10' ); // $ExpectError + greplicate( x.length, 2, x, 1, out, true ); // $ExpectError + greplicate( x.length, 2, x, 1, out, false ); // $ExpectError + greplicate( x.length, 2, x, 1, out, null ); // $ExpectError + greplicate( x.length, 2, x, 1, out, undefined ); // $ExpectError + greplicate( x.length, 2, x, 1, out, [] ); // $ExpectError + greplicate( x.length, 2, x, 1, out, {} ); // $ExpectError + greplicate( x.length, 2, x, 1, out, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + greplicate(); // $ExpectError + greplicate( x.length ); // $ExpectError + greplicate( x.length, 2 ); // $ExpectError + greplicate( x.length, 2, x ); // $ExpectError + greplicate( x.length, 2, x, 1 ); // $ExpectError + greplicate( x.length, 2, x, 1, out ); // $ExpectError + greplicate( x.length, 2, x, 1, out, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a collection... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + greplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); // $ExpectType Float64Array + greplicate.ndarray( x.length, 2, new AccessorArray( x ), 1, 0, new AccessorArray( out ), 1, 0 ); // $ExpectType AccessorArray +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + greplicate.ndarray( '10', 2, x, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( true, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( false, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( null, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( undefined, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( [], 2, x, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( {}, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( ( x: number ): number => x, 2, x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + greplicate.ndarray( x.length, '10', x, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, true, x, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, false, x, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, null, x, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, undefined, x, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, [], x, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, {}, x, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, ( x: number ): number => x, x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a collection... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + greplicate.ndarray( x.length, 2, 10, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, '10', 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, true, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, false, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, null, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, undefined, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, [ '1' ], 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, {}, 1, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, ( x: number ): number => x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + greplicate.ndarray( x.length, 2, x, '10', 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, true, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, false, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, null, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, undefined, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, [], 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, {}, 0, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, ( x: number ): number => x, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + greplicate.ndarray( x.length, 2, x, 1, '10', out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, true, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, false, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, null, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, undefined, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, [], out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, {}, out, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, ( x: number ): number => x, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a collection... +{ + const x = new Float64Array( 10 ); + + greplicate.ndarray( x.length, 2, x, 1, 0, 10, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, '10', 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, true, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, false, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, null, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, undefined, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, [ '1' ], 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, {}, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + greplicate.ndarray( x.length, 2, x, 1, 0, out, '10', 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out, true, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out, false, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out, null, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out, undefined, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out, [], 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out, {}, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + greplicate.ndarray( x.length, 2, x, 1, 0, out, 1, '10' ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out, 1, true ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out, 1, false ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out, 1, null ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out, 1, undefined ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out, 1, [] ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out, 1, {} ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + greplicate.ndarray(); // $ExpectError + greplicate.ndarray( x.length ); // $ExpectError + greplicate.ndarray( x.length, 2 ); // $ExpectError + greplicate.ndarray( x.length, 2, x ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out, 1 ); // $ExpectError + greplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/greplicate/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/greplicate/examples/index.js new file mode 100644 index 000000000000..8b0db9a9d84e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/greplicate/examples/index.js @@ -0,0 +1,34 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Float64Array = require( '@stdlib/array/float64' ); +var greplicate = require( './../lib' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +console.log( x ); + +var out = new Float64Array( x.length * 3 ); +console.log( out ); + +greplicate( x.length, 3, x, 1, out, 1 ); +console.log( out ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/greplicate/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/greplicate/lib/accessors.js new file mode 100644 index 000000000000..d359e3d84d43 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/greplicate/lib/accessors.js @@ -0,0 +1,88 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Replicates each strided array element a specified number of times. +* +* @private +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Object} x - input array object +* @param {Collection} x.data - input array data +* @param {Array} x.accessors - array element accessors +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Object} out - output array object +* @param {Collection} out.data - output array data +* @param {Array} out.accessors - array element accessors +* @param {integer} strideOut - stride length for `out` +* @param {NonNegativeInteger} offsetOut - starting index for `out` +* @returns {Object} output array object +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = toAccessorArray( [ 1.0, 2.0, 3.0 ] ); +* var out = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* greplicate( 3, 2, arraylike2object( x ), 1, 0, arraylike2object( out ), 1, 0 ); +* +* var v = out.get( 0 ); +* // returns 1.0 +*/ +function greplicate( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) { + var xbuf; + var obuf; + var get; + var set; + var io; + var ix; + var v; + var i; + var j; + + // Cache references to array data: + xbuf = x.data; + obuf = out.data; + + // Cache references to element accessors: + get = x.accessors[ 0 ]; + set = out.accessors[ 1 ]; + + ix = offsetX; + io = offsetOut; + for ( i = 0; i < N; i++ ) { + v = get( xbuf, ix ); + for ( j = 0; j < k; j++ ) { + set( obuf, io, v ); + io += strideOut; + } + ix += strideX; + } + return out; +} + + +// EXPORTS // + +module.exports = greplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/greplicate/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/greplicate/lib/index.js new file mode 100644 index 000000000000..903938b4079a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/greplicate/lib/index.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Replicate each strided array element a specified number of times. +* +* @module @stdlib/blas/ext/base/greplicate +* +* @example +* var greplicate = require( '@stdlib/blas/ext/base/greplicate' ); +* +* var x = [ 1.0, 2.0, 3.0 ]; +* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; +* +* greplicate( x.length, 2, x, 1, out, 1 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +* +* @example +* var greplicate = require( '@stdlib/blas/ext/base/greplicate' ); +* +* var x = [ 1.0, 2.0, 3.0 ]; +* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; +* +* greplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/greplicate/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/greplicate/lib/main.js new file mode 100644 index 000000000000..241452418a92 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/greplicate/lib/main.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Replicates each strided array element a specified number of times. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Collection} x - input array +* @param {integer} strideX - stride length for `x` +* @param {Collection} out - output array +* @param {integer} strideOut - stride length for `out` +* @returns {Collection} output array +* +* @example +* var x = [ 1.0, 2.0, 3.0 ]; +* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; +* +* greplicate( x.length, 2, x, 1, out, 1 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +*/ +function greplicate( N, k, x, strideX, out, strideOut ) { + var ox = stride2offset( N, strideX ); + var oo = stride2offset( N * k, strideOut ); + return ndarray( N, k, x, strideX, ox, out, strideOut, oo ); +} + + +// EXPORTS // + +module.exports = greplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/greplicate/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/greplicate/lib/ndarray.js new file mode 100644 index 000000000000..f957ea8388b3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/greplicate/lib/ndarray.js @@ -0,0 +1,83 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var accessors = require( './accessors.js' ); + + +// MAIN // + +/** +* Replicates each strided array element a specified number of times. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Collection} x - input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Collection} out - output array +* @param {integer} strideOut - stride length for `out` +* @param {NonNegativeInteger} offsetOut - starting index for `out` +* @returns {Collection} output array +* +* @example +* var x = [ 1.0, 2.0, 3.0 ]; +* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; +* +* greplicate( 3, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +*/ +function greplicate( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) { + var io; + var ix; + var ox; + var oy; + var v; + var i; + var j; + + if ( N <= 0 || k <= 0 ) { + return out; + } + ox = arraylike2object( x ); + oy = arraylike2object( out ); + if ( ox.accessorProtocol || oy.accessorProtocol ) { + accessors( N, k, ox, strideX, offsetX, oy, strideOut, offsetOut ); + return out; + } + ix = offsetX; + io = offsetOut; + for ( i = 0; i < N; i++ ) { + v = x[ ix ]; + for ( j = 0; j < k; j++ ) { + out[ io ] = v; + io += strideOut; + } + ix += strideX; + } + return out; +} + + +// EXPORTS // + +module.exports = greplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/greplicate/package.json b/lib/node_modules/@stdlib/blas/ext/base/greplicate/package.json new file mode 100644 index 000000000000..d3f54d4bca0b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/greplicate/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/blas/ext/base/greplicate", + "version": "0.0.0", + "description": "Replicate each strided array element a specified number of times.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "replicate", + "repeat", + "copy", + "strided", + "strided array", + "typed", + "array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/greplicate/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/greplicate/test/test.js new file mode 100644 index 000000000000..f39caae9e253 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/greplicate/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var greplicate = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof greplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof greplicate.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/greplicate/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/greplicate/test/test.main.js new file mode 100644 index 000000000000..5a4c57480349 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/greplicate/test/test.main.js @@ -0,0 +1,430 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var greplicate = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof greplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( greplicate.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + greplicate( x.length, 2, x, 1, out, 1 ); + expected = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + x = [ 1.0, 2.0, 3.0, 4.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + greplicate( x.length, 3, x, 1, out, 1 ); + expected = [ 1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0, 4.0, 4.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0 ]; + + greplicate( x.length, 1, x, 1, out, 1 ); + expected = [ 1.0, 2.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', function test( t ) { + var expected; + var out; + var x; + + x = [ 5.0 ]; + out = [ 0.0, 0.0, 0.0 ]; + + greplicate( 1, 3, x, 1, out, 1 ); + expected = [ 5.0, 5.0, 5.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + greplicate( x.length, 2, toAccessorArray( x ), 1, toAccessorArray( out ), 1 ); + expected = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + x = [ 1.0, 2.0, 3.0, 4.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + greplicate( x.length, 3, toAccessorArray( x ), 1, toAccessorArray( out ), 1 ); + expected = [ 1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0, 4.0, 4.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var v; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + v = greplicate( x.length, 2, x, 1, out, 1 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'the function returns a reference to the output array (accessors)', function test( t ) { + var out; + var x; + var v; + + x = toAccessorArray( [ 1.0, 2.0, 3.0 ] ); + out = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + v = greplicate( x.length, 2, x, 1, out, 1 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ]; + + expected = [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ]; + + greplicate( -1, 2, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + greplicate( 0, 2, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ]; + + expected = [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ]; + + greplicate( x.length, -1, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + greplicate( x.length, 0, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + out = [ + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]; + + greplicate( 3, 2, x, 2, out, 1 ); + + expected = [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + out = [ + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]; + + greplicate( 3, 2, toAccessorArray( x ), 2, toAccessorArray( out ), 1 ); + + expected = [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]; + out = [ + 0.0, // 0 + 0.0, + 0.0, // 0 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 2 + 0.0, + 0.0, // 2 + 0.0 + ]; + + greplicate( 3, 2, x, 1, out, 2 ); + + expected = [ 1.0, 0.0, 1.0, 0.0, 2.0, 0.0, 2.0, 0.0, 3.0, 0.0, 3.0, 0.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride (accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]; + out = [ + 0.0, // 0 + 0.0, + 0.0, // 0 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 2 + 0.0, + 0.0, // 2 + 0.0 + ]; + + greplicate( 3, 2, toAccessorArray( x ), 1, toAccessorArray( out ), 2 ); + + expected = [ 1.0, 0.0, 1.0, 0.0, 2.0, 0.0, 2.0, 0.0, 3.0, 0.0, 3.0, 0.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + out = [ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]; + + greplicate( 3, 2, x, -2, out, -1 ); + + expected = [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + out = [ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]; + + greplicate( 3, 2, toAccessorArray( x ), -2, toAccessorArray( out ), -1 ); + + expected = [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + out = [ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]; + + greplicate( 3, 2, x, 2, out, -1 ); + + expected = [ 5.0, 5.0, 3.0, 3.0, 1.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var out0; + var out1; + var x0; + var x1; + + // Initial arrays... + x0 = new Float64Array([ + 1.0, + 2.0, // 0 + 3.0, + 4.0, // 1 + 5.0, + 6.0 // 2 + ]); + out0 = new Float64Array([ + 0.0, + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + // Create offset views... + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element + + greplicate( 3, 2, x1, 2, out1, 1 ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 2.0, 2.0, 4.0, 4.0, 6.0, 6.0 ] ); + + t.deepEqual( out0, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/greplicate/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/greplicate/test/test.ndarray.js new file mode 100644 index 000000000000..1d7b621c0491 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/greplicate/test/test.ndarray.js @@ -0,0 +1,543 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var greplicate = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof greplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', function test( t ) { + t.strictEqual( greplicate.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + greplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + expected = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + x = [ 1.0, 2.0, 3.0, 4.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + greplicate( x.length, 3, x, 1, 0, out, 1, 0 ); + expected = [ 1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0, 4.0, 4.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0 ]; + + greplicate( x.length, 1, x, 1, 0, out, 1, 0 ); + expected = [ 1.0, 2.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', function test( t ) { + var expected; + var out; + var x; + + x = [ 5.0 ]; + out = [ 0.0, 0.0, 0.0 ]; + + greplicate( 1, 3, x, 1, 0, out, 1, 0 ); + expected = [ 5.0, 5.0, 5.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + greplicate( x.length, 2, toAccessorArray( x ), 1, 0, toAccessorArray( out ), 1, 0 ); + expected = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + x = [ 1.0, 2.0, 3.0, 4.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + greplicate( x.length, 3, toAccessorArray( x ), 1, 0, toAccessorArray( out ), 1, 0 ); + expected = [ 1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0, 4.0, 4.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var v; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + v = greplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'the function returns a reference to the output array (accessors)', function test( t ) { + var out; + var x; + var v; + + x = toAccessorArray( [ 1.0, 2.0, 3.0 ] ); + out = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + v = greplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ]; + + expected = [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ]; + + greplicate( -1, 2, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + greplicate( 0, 2, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ]; + + expected = [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ]; + + greplicate( x.length, -1, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + greplicate( x.length, 0, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + out = [ + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]; + + greplicate( 3, 2, x, 2, 0, out, 1, 0 ); + + expected = [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + out = [ + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]; + + greplicate( 3, 2, toAccessorArray( x ), 2, 0, toAccessorArray( out ), 1, 0 ); + + expected = [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]; + out = [ + 0.0, // 0 + 0.0, + 0.0, // 0 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 2 + 0.0, + 0.0, // 2 + 0.0 + ]; + + greplicate( 3, 2, x, 1, 0, out, 2, 0 ); + + expected = [ 1.0, 0.0, 1.0, 0.0, 2.0, 0.0, 2.0, 0.0, 3.0, 0.0, 3.0, 0.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride (accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]; + out = [ + 0.0, // 0 + 0.0, + 0.0, // 0 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 2 + 0.0, + 0.0, // 2 + 0.0 + ]; + + greplicate( 3, 2, toAccessorArray( x ), 1, 0, toAccessorArray( out ), 2, 0 ); + + expected = [ 1.0, 0.0, 1.0, 0.0, 2.0, 0.0, 2.0, 0.0, 3.0, 0.0, 3.0, 0.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + out = [ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]; + + greplicate( 3, 2, x, -2, 4, out, -1, 5 ); + + expected = [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + out = [ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]; + + greplicate( 3, 2, toAccessorArray( x ), -2, 4, toAccessorArray( out ), -1, 5 ); + + expected = [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var expected; + var out; + var x; + + x = [ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]; + out = [ + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, // 3 + 0.0 // 3 + ]; + + greplicate( 4, 2, x, 2, 1, out, 1, 0 ); + + expected = [ 1.0, 1.0, -2.0, -2.0, 2.0, 2.0, 4.0, 4.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset (accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]; + out = [ + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, // 3 + 0.0 // 3 + ]; + + greplicate( 4, 2, toAccessorArray( x ), 2, 1, toAccessorArray( out ), 1, 0 ); + + expected = [ 1.0, 1.0, -2.0, -2.0, 2.0, 2.0, 4.0, 4.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output offset', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]; + out = [ + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]; + + greplicate( 3, 2, x, 1, 0, out, 1, 2 ); + + expected = [ 0.0, 0.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output offset (accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]; + out = [ + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]; + + greplicate( 3, 2, toAccessorArray( x ), 1, 0, toAccessorArray( out ), 1, 2 ); + + expected = [ 0.0, 0.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a zero `x` stride', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, + 2.0, // 0, 1, 2 + 3.0 + ]; + out = [ + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]; + + greplicate( 3, 2, x, 0, 1, out, 1, 0 ); + + expected = [ 2.0, 2.0, 2.0, 2.0, 2.0, 2.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var out; + var x; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + out = [ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]; + + greplicate( 3, 2, x, 2, 0, out, -1, 5 ); + + expected = [ 5.0, 5.0, 3.0, 3.0, 1.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/grev/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/grev/benchmark/benchmark.js index 9e985df98d1a..025a22740e85 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/grev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/grev/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var grev = require( './../lib/main.js' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/grev/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/grev/benchmark/benchmark.ndarray.js index 3ee5a5913d6b..2e34a0892577 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/grev/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/grev/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var grev = require( './../lib/ndarray.js' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.js index 3f8e6466183a..4b2c7bf6e179 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/main.js' ); @@ -128,7 +129,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js index ce9237412309..0352ff991b33 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/ndarray.js' ); @@ -128,7 +129,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.mostly_sorted_random.js index 505384216a77..6a9d56a84cfd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.mostly_sorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/main.js' ); @@ -119,7 +120,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.mostly_sorted_random.ndarray.js index 972527f9d644..b043d8631bbb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.mostly_sorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/ndarray.js' ); @@ -119,7 +120,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.js index 19bd89f03a70..456335e7bd8f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/main.js' ); @@ -128,7 +129,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js index d3dec4231e97..5c4b0f447300 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/ndarray.js' ); @@ -128,7 +129,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_mostly_sorted_random.js index 366668f020d2..c526af103d5d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_mostly_sorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/main.js' ); @@ -119,7 +120,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js index 50c7eebbd75d..74075f8c547e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/ndarray.js' ); @@ -119,7 +120,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_sorted_few_uniques.js index 56827d4af87e..957991c90503 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_sorted_few_uniques.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/main.js' ); @@ -129,7 +130,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js index d3c2cd5edb10..1491b63de336 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/ndarray.js' ); @@ -129,7 +130,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_sorted_random.js index a7491848e7e8..1499ee90ac99 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_sorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/main.js' ); @@ -119,7 +120,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_sorted_random.ndarray.js index 1bfac4b66c64..07e683d69632 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.rev_sorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/ndarray.js' ); @@ -119,7 +120,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.sorted_few_uniques.js index 7fd4520965e0..dcdcdf59104c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.sorted_few_uniques.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/main.js' ); @@ -127,7 +128,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.sorted_few_uniques.ndarray.js index 38ae3e1b511d..ec26d5aabfe8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/ndarray.js' ); @@ -127,7 +128,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.sorted_random.js index c14857489b50..91f091b78a23 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.sorted_random.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/main.js' ); @@ -116,7 +117,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:len='+len, opts, f ); + bench( format( '%s::sorted,random:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.sorted_random.ndarray.js index e2bb2bf69f1e..a2c206d63633 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.sorted_random.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/ndarray.js' ); @@ -116,7 +117,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,random:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.unsorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.unsorted_few_uniques.js index 91523ff79b4b..a7d923e7d8a6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.unsorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.unsorted_few_uniques.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/main.js' ); @@ -122,7 +123,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.unsorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.unsorted_few_uniques.ndarray.js index f74df89f955a..392ede2e3454 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.unsorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.unsorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/ndarray.js' ); @@ -122,7 +123,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.unsorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.unsorted_random.js index b1afca6eee5b..4b7b9bfc8812 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.unsorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.unsorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/main.js' ); @@ -119,7 +120,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:len='+len, opts, f ); + bench( format( '%s::unsorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.unsorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.unsorted_random.ndarray.js index 21e489d3ff6c..d434c058af08 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.unsorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2hp/benchmark/benchmark.unsorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2hp = require( './../lib/ndarray.js' ); @@ -119,7 +120,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.js index 9ff29929bdd1..b6db64cf32da 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/main.js' ); @@ -128,7 +129,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js index 432f9ff83860..4d081494f367 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/ndarray.js' ); @@ -128,7 +129,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.mostly_sorted_random.js index b0edd5515271..0c9cbd2dae0b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.mostly_sorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/main.js' ); @@ -119,7 +120,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.mostly_sorted_random.ndarray.js index d819eac1088a..7a44c7dc9b75 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.mostly_sorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/ndarray.js' ); @@ -119,7 +120,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.js index 8dbd08bcb078..f2649d2b21b8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/main.js' ); @@ -128,7 +129,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js index 073d50d5d6ce..559b12fbbb45 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/ndarray.js' ); @@ -128,7 +129,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_mostly_sorted_random.js index 4cd6a3bebbae..ed9544c384d1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_mostly_sorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/main.js' ); @@ -119,7 +120,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js index 4a14f7639cf0..ec44aa1d3274 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/ndarray.js' ); @@ -119,7 +120,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_sorted_few_uniques.js index d5ea4068ec4a..99bb58790cfb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_sorted_few_uniques.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/main.js' ); @@ -129,7 +130,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js index fad5305b418c..043cd7d6d0fd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/ndarray.js' ); @@ -129,7 +130,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_sorted_random.js index 7920eff0a55c..379cdd0a5c35 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_sorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/main.js' ); @@ -119,7 +120,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_sorted_random.ndarray.js index e9d6462814bc..b35e1b0ed232 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.rev_sorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/ndarray.js' ); @@ -119,7 +120,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.sorted_few_uniques.js index 8b139e28a921..16ce0054b688 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.sorted_few_uniques.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/main.js' ); @@ -127,7 +128,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.sorted_few_uniques.ndarray.js index b4e023207e54..48e8675e75d8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/ndarray.js' ); @@ -127,7 +128,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.sorted_random.js index 7c41c086e606..90864354f69c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.sorted_random.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/main.js' ); @@ -116,7 +117,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:len='+len, opts, f ); + bench( format( '%s::sorted,random:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.sorted_random.ndarray.js index 1a7a7df96b43..81b596260b0b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.sorted_random.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/ndarray.js' ); @@ -116,7 +117,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,random:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.unsorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.unsorted_few_uniques.js index ea0416921360..315336492837 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.unsorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.unsorted_few_uniques.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/main.js' ); @@ -122,7 +123,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.unsorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.unsorted_few_uniques.ndarray.js index 8e99013340f7..49bacb971543 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.unsorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.unsorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/ndarray.js' ); @@ -122,7 +123,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.unsorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.unsorted_random.js index 2bc45e3b07f8..8db768595e55 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.unsorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.unsorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/main.js' ); @@ -119,7 +120,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:len='+len, opts, f ); + bench( format( '%s::unsorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.unsorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.unsorted_random.ndarray.js index fc21c3fc6995..78c867548780 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.unsorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsort2sh/benchmark/benchmark.unsorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsort2sh = require( './../lib/ndarray.js' ); @@ -119,7 +120,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.mostly_sorted_few_uniques.js index ce16eb18c13f..0c04120b8605 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.mostly_sorted_few_uniques.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/main.js' ); @@ -122,7 +123,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js index f0a62808bca4..aa517af6d18e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/ndarray.js' ); @@ -122,7 +123,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.mostly_sorted_random.js index 027c7801c017..c57051bb19c8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.mostly_sorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.mostly_sorted_random.ndarray.js index e3ac6749fee8..b5049b714002 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.mostly_sorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.js index 0676f0f194a0..56aba9d86801 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/main.js' ); @@ -122,7 +123,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js index d93aceb5184b..0825f6b83047 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/ndarray.js' ); @@ -122,7 +123,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_mostly_sorted_random.js index c9824e19dafc..9675b5000b17 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_mostly_sorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js index 828f9a9889c5..8da44aec7d68 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_sorted_few_uniques.js index ac9a2bc68963..381ddfe04b8f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_sorted_few_uniques.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/main.js' ); @@ -123,7 +124,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js index c023baad57a2..7ce24172647c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/ndarray.js' ); @@ -123,7 +124,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_sorted_random.js index 1dc73496ce11..41463f30c155 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_sorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_sorted_random.ndarray.js index 90b9fad6e99f..b0bf12fa633c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.rev_sorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.sorted_few_uniques.js index 1f7adcdb5385..6c800b6521b2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.sorted_few_uniques.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/main.js' ); @@ -123,7 +124,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.sorted_few_uniques.ndarray.js index deae64360064..2b3225e71399 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/ndarray.js' ); @@ -123,7 +124,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.sorted_random.js index 7355671c0c33..960f1c01a20e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.sorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::sorted,random:len='+len, opts, f ); + bench( format( '%s::sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.sorted_random.ndarray.js index 5b0d943f0e9b..fbdbb88f9e3d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.sorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.unsorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.unsorted_few_uniques.js index 788dedcd9cb9..8a9cf15be3fb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.unsorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.unsorted_few_uniques.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/main.js' ); @@ -116,7 +117,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.unsorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.unsorted_few_uniques.ndarray.js index da0fd8858244..9abe1a92d70a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.unsorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.unsorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/ndarray.js' ); @@ -116,7 +117,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.unsorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.unsorted_random.js index be36ea88d6bb..e1643d128ddf 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.unsorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.unsorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:len='+len, opts, f ); + bench( format( '%s::unsorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.unsorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.unsorted_random.ndarray.js index 8ef64b9ce8f0..331ffdddff32 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.unsorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsorthp/benchmark/benchmark.unsorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.mostly_sorted_few_uniques.js index 3c240ed0f04b..a57e2d62a83b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.mostly_sorted_few_uniques.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/main.js' ); @@ -124,7 +125,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js index 350680823350..86872dddfdea 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/ndarray.js' ); @@ -124,7 +125,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.mostly_sorted_random.js index 81096a4c8c63..40d431922a5b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.mostly_sorted_random.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/main.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.mostly_sorted_random.ndarray.js index fa0d868f3285..b6903f06e6be 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.mostly_sorted_random.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/ndarray.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.js index 2ef582e058ef..4dfd29662eda 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/main.js' ); @@ -124,7 +125,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js index ff7c822b3d7e..f4b4eb392048 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/ndarray.js' ); @@ -124,7 +125,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_mostly_sorted_random.js index 48ec26bea1f2..ef7e8d4a4fd2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_mostly_sorted_random.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/main.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js index 6049480d8238..2a0c8b4bb44d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/ndarray.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_sorted_few_uniques.js index 45cf9ef162fe..e4c10b471225 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_sorted_few_uniques.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/main.js' ); @@ -125,7 +126,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js index aea1bb4aaef0..5c422daab8f4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/ndarray.js' ); @@ -125,7 +126,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_sorted_random.js index 5bcf36489efe..bb351e6f2e39 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_sorted_random.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/main.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_sorted_random.ndarray.js index 01e05ee535fc..0c2f2b27d6c4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.rev_sorted_random.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/ndarray.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.sorted_few_uniques.js index fe2acc9e1743..4de3397572eb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.sorted_few_uniques.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/main.js' ); @@ -121,7 +122,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.sorted_few_uniques.ndarray.js index 52f993bbc6ba..5fb34ccfb511 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/ndarray.js' ); @@ -121,7 +122,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.sorted_random.js index c01f21359630..711e3a84e7b8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.sorted_random.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/main.js' ); @@ -110,7 +111,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:len='+len, opts, f ); + bench( format( '%s::sorted,random:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.sorted_random.ndarray.js index 000ea4743db5..6424dd24ff9c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.sorted_random.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/ndarray.js' ); @@ -110,7 +111,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,random:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.unsorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.unsorted_few_uniques.js index 81d8b13a8d3e..d039103e6458 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.unsorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.unsorted_few_uniques.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/main.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.unsorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.unsorted_few_uniques.ndarray.js index 3a9790700793..13c83eb19db0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.unsorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.unsorted_few_uniques.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/ndarray.js' ); @@ -118,7 +119,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.unsorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.unsorted_random.js index 28b6e064e721..087296d22216 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.unsorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.unsorted_random.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/main.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:len='+len, opts, f ); + bench( format( '%s::unsorted,random:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.unsorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.unsorted_random.ndarray.js index 829ecb9025d3..850f11e8760f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.unsorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortins/benchmark/benchmark.unsorted_random.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortins = require( './../lib/ndarray.js' ); @@ -115,7 +116,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.mostly_sorted_few_uniques.js index 60510fe09c6e..09ec6b563578 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.mostly_sorted_few_uniques.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/main.js' ); @@ -122,7 +123,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js index c6cdf41695c7..7c247f234c9a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.mostly_sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/ndarray.js' ); @@ -122,7 +123,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.mostly_sorted_random.js index b244962f8b92..d86276643c45 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.mostly_sorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.mostly_sorted_random.ndarray.js index d817773200f9..69d8dd1baf45 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.mostly_sorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.js index 56d09ea6888f..afada2e1b566 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/main.js' ); @@ -122,7 +123,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js index cd6a0550d84b..1337f68670cc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_mostly_sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/ndarray.js' ); @@ -122,7 +123,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_mostly_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_mostly_sorted_random.js index 28a61d11ef12..4616d4e585b0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_mostly_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_mostly_sorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js index 5f36a5a05950..34c064b8705d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_mostly_sorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_mostly_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_mostly_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_sorted_few_uniques.js index 2c0f193ba57e..350881cedabe 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_sorted_few_uniques.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/main.js' ); @@ -123,7 +124,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js index 5e6ba16467c3..d0690f45598f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/ndarray.js' ); @@ -123,7 +124,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_sorted_random.js index 6e8547e5a271..1582f3b950dc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_sorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_sorted_random.ndarray.js index 5089d95e1abe..7e49c4a3f8ac 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.rev_sorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::reverse_sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::reverse_sorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.sorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.sorted_few_uniques.js index 405e657713f7..cf623f47d8d6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.sorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.sorted_few_uniques.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/main.js' ); @@ -121,7 +122,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.sorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.sorted_few_uniques.ndarray.js index 445418fd2b0f..10ecad2493aa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.sorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.sorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/ndarray.js' ); @@ -121,7 +122,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.sorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.sorted_random.js index 787820e7c6dc..652cbc71dfa3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.sorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.sorted_random.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/main.js' ); @@ -110,7 +111,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:len='+len, opts, f ); + bench( format( '%s::sorted,random:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.sorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.sorted_random.ndarray.js index 9f44199cf76a..babe003aca30 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.sorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.sorted_random.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/ndarray.js' ); @@ -110,7 +111,7 @@ function main() { 'iterations': 1e7 / len }; f = createBenchmark( opts.iterations, len ); - bench( pkg+'::sorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::sorted,random:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.unsorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.unsorted_few_uniques.js index 0b66934ee184..0d9784e461a3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.unsorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.unsorted_few_uniques.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/main.js' ); @@ -116,7 +117,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.unsorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.unsorted_few_uniques.ndarray.js index 8320bfff9204..60f067cf9855 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.unsorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.unsorted_few_uniques.ndarray.js @@ -25,6 +25,7 @@ var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/ndarray.js' ); @@ -116,7 +117,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.unsorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.unsorted_random.js index bf3220b8ad2f..0b33abe86013 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.unsorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.unsorted_random.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:len='+len, opts, f ); + bench( format( '%s::unsorted,random:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.unsorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.unsorted_random.ndarray.js index d813c1eeb28e..826d9a12aa26 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.unsorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsortsh/benchmark/benchmark.unsorted_random.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsortsh = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( pow( iter, 3.0/4.0 ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gsum/benchmark/benchmark.js index 4efcd7c0b80d..364d27e8046b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsum/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsum = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsum/benchmark/benchmark.ndarray.js index fa5041e95e57..8bc9acb8dc02 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsum/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsum = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/benchmark/benchmark.js index 95b739669930..60e21d955562 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsumkbn = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/benchmark/benchmark.ndarray.js index 639eeb9eb6b3..9273a6196741 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsumkbn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/benchmark/benchmark.js index 42ce6533ed44..37b46cc6bed9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsumkbn2 = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/benchmark/benchmark.ndarray.js index 5097cda3209b..ab3326d5cb07 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsumkbn2 = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gsumors/benchmark/benchmark.js index 9bf5cfb3bf47..5c94e3f73177 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumors/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsumors = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsumors/benchmark/benchmark.ndarray.js index 2c68b43ac7b2..4897a6b329b0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumors/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsumors = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gvander/README.md b/lib/node_modules/@stdlib/blas/ext/base/gvander/README.md new file mode 100644 index 000000000000..7ba7734aebd9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gvander/README.md @@ -0,0 +1,216 @@ + + +# gvander + +> Generate a Vandermonde matrix. + +
+ +
+ + + +
+ +## Usage + +```javascript +var gvander = require( '@stdlib/blas/ext/base/gvander' ); +``` + +#### gvander( order, mode, M, N, x, strideX, out, ldo ) + +Generates a Vandermonde matrix. + +```javascript +var x = [ 1.0, 2.0, 3.0 ]; +var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + +gvander( 'row-major', 1, 3, 3, x, 1, out, 3 ); +// out => [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] +``` + +The function has the following parameters: + +- **order**: row-major (C-style) or column-major (Fortran-style) order. +- **mode**: mode. If `mode < 0`, the function generates decreasing powers. If `mode > 0`, the function generates increasing powers. +- **M**: number of rows in `out` and number of indexed elements in `x`. +- **N**: number of columns in `out`. +- **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. +- **strideX**: stride length for `x`. +- **out**: output matrix. +- **ldo**: stride between successive contiguous vectors of the matrix `out` (a.k.a., leading dimension of the matrix `out`). + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial arrays: +var x0 = new Float64Array( [ 999.0, 1.0, 2.0, 3.0 ] ); +var out0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +// Create offset views: +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +gvander( 'row-major', 1, 3, 3, x1, 1, out1, 3 ); +// out0 => [ 0.0, 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] +``` + +When the mode is positive, the matrix is generated such that + +```text +[ + 1 x_0^1 x_0^2 ... x_0^(N-1) + 1 x_1^1 x_1^2 ... x_1^(N-1) + ... +] +``` + +with increasing powers along the rows. + +When the mode is negative, the matrix is generated such that + +```text +[ + x_0^(N-1) ... x_0^2 x_0^1 1 + x_1^(N-1) ... x_1^2 x_1^1 1 + ... +] +``` + +with decreasing powers along the rows. + + + +#### gvander.ndarray( mode, M, N, x, strideX, offsetX, out, strideOut1, strideOut2, offsetOut ) + + + +Generates a Vandermonde matrix using alternative indexing semantics. + +```javascript +var x = [ 1.0, 2.0, 3.0 ]; +var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + +gvander.ndarray( 1, 3, 3, x, 1, 0, out, 3, 1, 0 ); +// out => [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **strideOut1**: stride length for the first dimension of `out`. +- **strideOut2**: stride length for the second dimension of `out`. +- **offsetOut**: starting index for `out`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to use every other element from the input array starting from the second element: + +```javascript +var x = [ 0.0, 1.0, 0.0, 2.0, 0.0, 3.0 ]; +var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + +gvander.ndarray( 1, 3, 3, x, 2, 1, out, 3, 1, 0 ); +// out => [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] +``` + +
+ + + +
+ +## Notes + +- If `M <= 0` or `N <= 0`, both functions return `out` unchanged. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). +- Depending on the environment, the typed versions ([`dvander`][@stdlib/blas/ext/base/dvander], [`svander`][@stdlib/blas/ext/base/svander], etc.) are likely to be significantly more performant. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var zeros = require( '@stdlib/array/zeros' ); +var gvander = require( '@stdlib/blas/ext/base/gvander' ); + +var M = 3; +var N = 4; + +var x = discreteUniform( M, 0, 10, { + 'dtype': 'generic' +}); +var out = zeros( M*N, 'generic' ); +console.log( x ); + +gvander( 'row-major', -1, M, N, x, 1, out, N ); +console.log( out ); +``` + +
+ + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + +[@stdlib/blas/ext/base/dvander]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dvander + +[@stdlib/blas/ext/base/svander]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/svander + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gvander/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gvander/benchmark/benchmark.js new file mode 100644 index 000000000000..8d9965229356 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gvander/benchmark/benchmark.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gvander = require( './../lib/main.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var out = zeros( len * len, options.dtype ); + var x = uniform( len, -10, 10, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x[ 0 ] += 0.1; + v = gvander( 'row-major', 1, len, len, x, 1, out, len ); + if ( isnan( v[ i%v.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v[ i%v.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gvander/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gvander/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..0f83aae16e71 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gvander/benchmark/benchmark.ndarray.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gvander = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var out = zeros( len * len, options.dtype ); + var x = uniform( len, -10, 10, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x[ 0 ] += 0.1; + v = gvander( 1, len, len, x, 1, 0, out, len, 1, 0 ); + if ( isnan( v[ i%v.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v[ i%v.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gvander/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gvander/docs/repl.txt new file mode 100644 index 000000000000..9b065eec2a0e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gvander/docs/repl.txt @@ -0,0 +1,136 @@ + +{{alias}}( order, mode, M, N, x, strideX, out, ldo ) + Generates a Vandermonde matrix. + + When the mode is positive, the matrix is generated such that + + [ + 1 x_0^1 x_0^2 ... x_0^(N-1) + 1 x_1^1 x_1^2 ... x_1^(N-1) + ... + ] + + with increasing powers along the rows. + + When the mode is negative, the matrix is generated such that + + [ + x_0^(N-1) ... x_0^2 x_0^1 1 + x_1^(N-1) ... x_1^2 x_1^1 1 + ... + ] + + with decreasing powers along the rows. + + If `M <= 0` or `N <= 0`, the function returns the output matrix unchanged. + + Parameters + ---------- + order: string + Row-major (C-style) or column-major (Fortran-style) order. + + mode: integer + Mode. If `mode < 0`, the function generates decreasing powers. If + `mode > 0`, the function generates increasing powers. + + M: integer + Number of rows in `out` and number of indexed elements in `x`. + + N: integer + Number of columns in `out`. + + x: Array|TypedArray + Input array. + + strideX: integer + Stride length for `x`. + + out: Array|TypedArray + Output matrix. + + ldo: integer + Stride between successive contiguous vectors of the matrix `out` + (a.k.a., leading dimension of the matrix `out`). + + Returns + ------- + out: Array|TypedArray + Output matrix. + + Examples + -------- + // Standard Usage: + > var x = [ 1.0, 2.0, 3.0 ]; + > var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > {{alias}}( 'row-major', 1, 3, 3, x, 1, out, 3 ) + [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] + + // Decreasing mode: + > x = [ 1.0, 2.0, 3.0 ]; + > out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > {{alias}}( 'row-major', -1, 3, 3, x, 1, out, 3 ) + [ 1.0, 1.0, 1.0, 4.0, 2.0, 1.0, 9.0, 3.0, 1.0 ] + + +{{alias}}.ndarray( mode, M, N, x, strideX, offsetX, out, so1, so2, oo ) + Generates a Vandermonde matrix using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on + starting indices. + + Parameters + ---------- + mode: integer + Mode. If `mode < 0`, the function generates decreasing powers. If + `mode > 0`, the function generates increasing powers. + + M: integer + Number of rows in `out` and number of indexed elements in `x`. + + N: integer + Number of columns in `out`. + + x: Array|TypedArray + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + out: Array|TypedArray + Output matrix. + + so1: integer + Stride length for the first dimension of `out`. + + so2: integer + Stride length for the second dimension of `out`. + + oo: integer + Starting index for `out`. + + Returns + ------- + out: Array|TypedArray + Output matrix. + + Examples + -------- + // Standard Usage: + > var x = [ 1.0, 2.0, 3.0 ]; + > var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > {{alias}}.ndarray( 1, 3, 3, x, 1, 0, out, 3, 1, 0 ) + [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] + + // Advanced indexing: + > x = [ 0.0, 1.0, 0.0, 2.0, 0.0, 3.0 ]; + > out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > {{alias}}.ndarray( 1, 3, 3, x, 2, 1, out, 3, 1, 0 ) + [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gvander/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gvander/docs/types/index.d.ts new file mode 100644 index 000000000000..ae5ca2b39871 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gvander/docs/types/index.d.ts @@ -0,0 +1,119 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Layout } from '@stdlib/types/blas'; +import { NumericArray, Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = NumericArray | Collection | AccessorArrayLike; + +/** +* Output matrix. +*/ +type OutputArray = NumericArray | Collection | AccessorArrayLike; + +/** +* Interface describing `gvander`. +*/ +interface Routine { + /** + * Generates a Vandermonde matrix. + * + * @param order - storage layout + * @param mode - mode indicating whether to generate increasing or decreasing powers + * @param M - number of rows in `out` + * @param N - number of columns in `out` + * @param x - input array + * @param strideX - stride length for `x` + * @param out - output matrix + * @param ldo - stride between successive contiguous vectors of the matrix `out` (a.k.a., leading dimension of the matrix `out`) + * @returns output matrix + * + * @example + * var x = [ 1.0, 2.0, 3.0 ]; + * var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + * + * gvander( 'row-major', 1, 3, 3, x, 1, out, 3 ); + * // out => [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] + */ + ( order: Layout, mode: number, M: number, N: number, x: InputArray, strideX: number, out: T, ldo: number ): T; + + /** + * Generates a Vandermonde matrix using alternative indexing semantics. + * + * @param mode - mode indicating whether to generate increasing or decreasing powers + * @param M - number of rows in `out` + * @param N - number of columns in `out` + * @param x - input array + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` + * @param out - output matrix + * @param strideOut1 - stride length for the first dimension of `out` + * @param strideOut2 - stride length for the second dimension of `out` + * @param offsetOut - starting index for `out` + * @returns output matrix + * + * @example + * var x = [ 1.0, 2.0, 3.0 ]; + * var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + * + * gvander.ndarray( 1, 3, 3, x, 1, 0, out, 3, 1, 0 ); + * // out => [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] + */ + ndarray( mode: number, M: number, N: number, x: InputArray, strideX: number, offsetX: number, out: T, strideOut1: number, strideOut2: number, offsetOut: number ): T; +} + +/** +* Generates a Vandermonde matrix. +* +* @param order - storage layout +* @param mode - mode indicating whether to generate increasing or decreasing powers +* @param M - number of rows in `out` +* @param N - number of columns in `out` +* @param x - input array +* @param strideX - stride length for `x` +* @param out - output matrix +* @param ldo - stride between successive contiguous vectors of the matrix `out` (a.k.a., leading dimension of the matrix `out`) +* @returns output matrix +* +* @example +* var x = [ 1.0, 2.0, 3.0 ]; +* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; +* +* gvander( 'row-major', 1, 3, 3, x, 1, out, 3 ); +* // out => [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] +* +* @example +* var x = [ 1.0, 2.0, 3.0 ]; +* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; +* +* gvander.ndarray( 1, 3, 3, x, 1, 0, out, 3, 1, 0 ); +* // out => [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] +*/ +declare var gvander: Routine; + + +// EXPORTS // + +export = gvander; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gvander/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/gvander/docs/types/test.ts new file mode 100644 index 000000000000..70e940864733 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gvander/docs/types/test.ts @@ -0,0 +1,341 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import gvander = require( './index' ); + + +// TESTS // + +// The function returns a numeric array... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander( 'row-major', 1, 10, 3, x, 1, out, 3 ); // $ExpectType Float64Array + gvander( 'row-major', 1, 10, 3, new AccessorArray( x ), 1, new AccessorArray( out ), 3 ); // $ExpectType AccessorArray +} + +// The compiler throws an error if the function is provided a first argument which is not a valid order... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander( '10', 1, 10, 3, x, 1, out, 3 ); // $ExpectError + gvander( true, 1, 10, 3, x, 1, out, 3 ); // $ExpectError + gvander( false, 1, 10, 3, x, 1, out, 3 ); // $ExpectError + gvander( null, 1, 10, 3, x, 1, out, 3 ); // $ExpectError + gvander( undefined, 1, 10, 3, x, 1, out, 3 ); // $ExpectError + gvander( [], 1, 10, 3, x, 1, out, 3 ); // $ExpectError + gvander( {}, 1, 10, 3, x, 1, out, 3 ); // $ExpectError + gvander( ( x: number ): number => x, 1, 10, 3, x, 1, out, 3 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander( 'row-major', '10', 10, 3, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', true, 10, 3, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', false, 10, 3, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', null, 10, 3, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', undefined, 10, 3, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', [], 10, 3, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', {}, 10, 3, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', ( x: number ): number => x, 10, 3, x, 1, out, 3 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander( 'row-major', 1, '10', 3, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, true, 3, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, false, 3, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, null, 3, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, undefined, 3, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, [], 3, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, {}, 3, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, ( x: number ): number => x, 3, x, 1, out, 3 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander( 'row-major', 1, 10, '10', x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, true, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, false, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, null, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, undefined, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, [], x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, {}, x, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, ( x: number ): number => x, x, 1, out, 3 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a numeric array... +{ + const out = new Float64Array( 30 ); + + gvander( 'row-major', 1, 10, 3, '10', 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, true, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, false, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, null, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, undefined, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, [ '1' ], 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, {}, 1, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, ( x: number ): number => x, 1, out, 3 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander( 'row-major', 1, 10, 3, x, '10', out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, true, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, false, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, null, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, undefined, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, [], out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, {}, out, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, ( x: number ): number => x, out, 3 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a seventh argument which is not a numeric array... +{ + const x = new Float64Array( 10 ); + + gvander( 'row-major', 1, 10, 3, x, 1, '10', 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1, true, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1, false, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1, null, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1, undefined, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1, [ '1' ], 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1, {}, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1, ( x: number ): number => x, 3 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an eighth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander( 'row-major', 1, 10, 3, x, 1, out, '10' ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1, out, true ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1, out, false ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1, out, null ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1, out, undefined ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1, out, [] ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1, out, {} ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1, out, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander(); // $ExpectError + gvander( 'row-major' ); // $ExpectError + gvander( 'row-major', 1 ); // $ExpectError + gvander( 'row-major', 1, 10 ); // $ExpectError + gvander( 'row-major', 1, 10, 3 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1 ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1, out ); // $ExpectError + gvander( 'row-major', 1, 10, 3, x, 1, out, 3, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a numeric array... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectType Float64Array + gvander.ndarray( 1, 10, 3, new AccessorArray( x ), 1, 0, new AccessorArray( out ), 3, 1, 0 ); // $ExpectType AccessorArray +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander.ndarray( '10', 10, 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( true, 10, 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( false, 10, 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( null, 10, 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( undefined, 10, 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( [], 10, 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( {}, 10, 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( ( x: number ): number => x, 10, 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander.ndarray( 1, '10', 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, true, 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, false, 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, null, 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, undefined, 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, [], 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, {}, 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, ( x: number ): number => x, 3, x, 1, 0, out, 3, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander.ndarray( 1, 10, '10', x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, true, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, false, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, null, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, undefined, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, [], x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, {}, x, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, ( x: number ): number => x, x, 1, 0, out, 3, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a numeric array... +{ + const out = new Float64Array( 30 ); + + gvander.ndarray( 1, 10, 3, '10', 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, true, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, false, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, null, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, undefined, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, [ '1' ], 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, {}, 1, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, ( x: number ): number => x, 1, 0, out, 3, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander.ndarray( 1, 10, 3, x, '10', 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, true, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, false, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, null, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, undefined, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, [], 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, {}, 0, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, ( x: number ): number => x, 0, out, 3, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander.ndarray( 1, 10, 3, x, 1, '10', out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, true, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, false, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, null, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, undefined, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, [], out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, {}, out, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, ( x: number ): number => x, out, 3, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a numeric array... +{ + const x = new Float64Array( 10 ); + + gvander.ndarray( 1, 10, 3, x, 1, 0, '10', 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, true, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, false, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, null, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, undefined, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, [ '1' ], 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, {}, 3, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, ( x: number ): number => x, 3, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander.ndarray( 1, 10, 3, x, 1, 0, out, '10', 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, true, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, false, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, null, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, undefined, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, [], 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, {}, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a ninth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, '10', 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, true, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, false, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, null, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, undefined, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, [], 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, {}, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a tenth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, 1, '10' ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, 1, true ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, 1, false ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, 1, null ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, 1, undefined ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, 1, [] ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, 1, {} ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 30 ); + + gvander.ndarray(); // $ExpectError + gvander.ndarray( 1 ); // $ExpectError + gvander.ndarray( 1, 10 ); // $ExpectError + gvander.ndarray( 1, 10, 3 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, 1 ); // $ExpectError + gvander.ndarray( 1, 10, 3, x, 1, 0, out, 3, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gvander/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gvander/examples/index.js new file mode 100644 index 000000000000..e7115e5918d3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gvander/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var zeros = require( '@stdlib/array/zeros' ); +var gvander = require( './../lib' ); + +var M = 3; +var N = 4; + +var x = discreteUniform( M, 0, 10, { + 'dtype': 'generic' +}); +var out = zeros( M*N, 'generic' ); +console.log( x ); + +gvander( 'row-major', -1, M, N, x, 1, out, N ); +console.log( out ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gvander/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/gvander/lib/accessors.js new file mode 100644 index 000000000000..9fe455991033 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gvander/lib/accessors.js @@ -0,0 +1,168 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' ); +var gfill = require( '@stdlib/blas/ext/base/gfill' ).ndarray; + + +// MAIN // + +/** +* Generates a Vandermonde matrix using accessor arrays. +* +* ## Notes +* +* - The implementation uses recursive multiplication to generate successive powers, which carries risk of additional accumulated floating-point error; however, for most use cases, such additional error should be negligible and not problematic. +* +* @private +* @param {integer} mode - mode indicating whether to generate increasing or decreasing powers +* @param {NonNegativeInteger} M - number of rows in `out` +* @param {NonNegativeInteger} N - number of columns in `out` +* @param {Object} x - input array object +* @param {integer} sx - stride length for `x` +* @param {NonNegativeInteger} ox - starting index for `x` +* @param {Object} out - output matrix object +* @param {integer} so1 - stride length for the first dimension of `out` +* @param {integer} so2 - stride length for the second dimension of `out` +* @param {NonNegativeInteger} oo - starting index for `out` +* @returns {Collection} output matrix +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = [ 1.0, 2.0, 3.0 ]; +* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; +* +* gvander( 1, 3, 3, arraylike2object( toAccessorArray( x ) ), 1, 0, arraylike2object( toAccessorArray( out ) ), 3, 1, 0 ); +* +* console.log( out ); +* // => [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] +*/ +function gvander( mode, M, N, x, sx, ox, out, so1, so2, oo ) { + var xbuf; + var obuf; + var xget; + var oget; + var oset; + var tmp; + var do0; + var do1; + var S0; + var S1; + var io; + var ix; + var i0; + var i1; + var v; + + xbuf = x.data; + obuf = out.data; + xget = x.accessors[ 0 ]; + oget = out.accessors[ 0 ]; + oset = out.accessors[ 1 ]; + + // Note on variable naming convention: S#, do#, io, i# where # corresponds to the loop number, with `0` being the innermost loop... + if ( isRowMajor( [ so1, so2 ] ) ) { + S0 = N; + S1 = M; + do0 = so2; + do1 = so1 - ( S0*so2 ); + + // Increasing: x^0, x^1, ..., x^(N-1) + if ( mode > 0 ) { + io = oo; + ix = ox; + for ( i1 = 0; i1 < S1; i1++ ) { + v = xget( xbuf, ix ); + oset( obuf, io, 1.0 ); + tmp = 1.0; + io += do0; + for ( i0 = 1; i0 < S0; i0++ ) { + tmp *= v; + oset( obuf, io, tmp ); + io += do0; + } + ix += sx; + io += do1; + } + return obuf; + } + // Decreasing: x^(N-1), x^(N-2), ..., x^0 + io = oo + ( ( S1-1 ) * so1 ) + ( ( S0-1 ) * so2 ); + ix = ox + ( ( S1-1 ) * sx ); + for ( i1 = S1-1; i1 >= 0; i1-- ) { + v = xget( xbuf, ix ); + oset( obuf, io, 1.0 ); + tmp = 1.0; + io -= do0; + for ( i0 = 1; i0 < S0; i0++ ) { + tmp *= v; + oset( obuf, io, tmp ); + io -= do0; + } + ix -= sx; + io -= do1; + } + return obuf; + } + // Column-major... + S0 = M; + S1 = N; + do0 = so1; + do1 = so2 - ( S0*so1 ); + + // Increasing: column j contains x^j + if ( mode > 0 ) { + io = oo; + gfill( S0, 1.0, obuf, do0, io ); + io += so2; + for ( i1 = 1; i1 < S1; i1++ ) { + ix = ox; + for ( i0 = 0; i0 < S0; i0++ ) { + oset( obuf, io, oget( obuf, io - so2 ) * xget( xbuf, ix ) ); + ix += sx; + io += do0; + } + io += do1; + } + return obuf; + } + // Decreasing: column 0 contains x^(N-1), last column all ones + gfill( S0, 1.0, obuf, so1, oo + ( ( S1-1 ) * so2 ) ); + io = oo + ( ( S1-2 ) * so2 ) + ( ( S0-1 ) * so1 ); + for ( i1 = S1-2; i1 >= 0; i1-- ) { + ix = ox + ( ( S0-1 ) * sx ); + for ( i0 = S0-1; i0 >= 0; i0-- ) { + oset( obuf, io, oget( obuf, io + so2 ) * xget( xbuf, ix ) ); + ix -= sx; + io -= do0; + } + io -= do1; + } + return obuf; +} + + +// EXPORTS // + +module.exports = gvander; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gvander/lib/base.js b/lib/node_modules/@stdlib/blas/ext/base/gvander/lib/base.js new file mode 100644 index 000000000000..69503c01175a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gvander/lib/base.js @@ -0,0 +1,155 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-len */ + +'use strict'; + +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' ); +var gfill = require( '@stdlib/blas/ext/base/gfill' ).ndarray; +var accessors = require( './accessors.js' ); + + +// MAIN // + +/** +* Generates a Vandermonde matrix using alternative indexing semantics. +* +* ## Notes +* +* - The implementation uses recursive multiplication to generate successive powers, which carries risk of additional accumulated floating-point error; however, for most use cases, such additional error should be negligible and not problematic. +* +* @private +* @param {integer} mode - mode indicating whether to generate increasing or decreasing powers +* @param {NonNegativeInteger} M - number of rows in `out` +* @param {NonNegativeInteger} N - number of columns in `out` +* @param {NumericArray} x - input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {NumericArray} out - output matrix +* @param {integer} strideOut1 - stride length for the first dimension of `out` +* @param {integer} strideOut2 - stride length for the second dimension of `out` +* @param {NonNegativeInteger} offsetOut - starting index for `out` +* @returns {NumericArray} output matrix +* +* @example +* var x = [ 1.0, 2.0, 3.0 ]; +* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; +* +* gvander( 1, 3, 3, x, 1, 0, out, 3, 1, 0 ); +* // out => [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] +*/ +function gvander( mode, M, N, x, strideX, offsetX, out, strideOut1, strideOut2, offsetOut ) { + var xobj; + var oobj; + var do0; + var do1; + var S0; + var S1; + var io; + var ix; + var i0; + var i1; + + xobj = arraylike2object( x ); + oobj = arraylike2object( out ); + if ( xobj.accessorProtocol || oobj.accessorProtocol ) { + return accessors( mode, M, N, xobj, strideX, offsetX, oobj, strideOut1, strideOut2, offsetOut ); + } + + // Note on variable naming convention: S#, do#, io, i# where # corresponds to the loop number, with `0` being the innermost loop... + if ( isRowMajor( [ strideOut1, strideOut2 ] ) ) { + S0 = N; + S1 = M; + do0 = strideOut2; + do1 = strideOut1 - ( S0*strideOut2 ); + + // Increasing: x^0, x^1, ..., x^(N-1) + if ( mode > 0 ) { + io = offsetOut; + ix = offsetX; + for ( i1 = 0; i1 < S1; i1++ ) { + out[ io ] = 1.0; + io += do0; + for ( i0 = 1; i0 < S0; i0++ ) { + out[ io ] = out[ io-do0 ] * x[ ix ]; + io += do0; + } + ix += strideX; + io += do1; + } + return out; + } + // Decreasing: x^(N-1), x^(N-2), ..., x^0 + io = offsetOut + ( ( S1-1 ) * strideOut1 ) + ( ( S0-1 ) * strideOut2 ); + ix = offsetX + ( ( S1-1 ) * strideX ); + for ( i1 = S1-1; i1 >= 0; i1-- ) { + out[ io ] = 1.0; + io -= do0; + for ( i0 = 1; i0 < S0; i0++ ) { + out[ io ] = out[ io+do0 ] * x[ ix ]; + io -= do0; + } + ix -= strideX; + io -= do1; + } + return out; + } + // Column-major... + S0 = M; + S1 = N; + do0 = strideOut1; + do1 = strideOut2 - ( S0*strideOut1 ); + + // Increasing: column j contains x^j + if ( mode > 0 ) { + gfill( S0, 1.0, out, strideOut1, offsetOut ); + io = offsetOut + strideOut2; + for ( i1 = 1; i1 < S1; i1++ ) { + ix = offsetX; + for ( i0 = 0; i0 < S0; i0++ ) { + out[ io ] = out[ io-strideOut2 ] * x[ ix ]; + ix += strideX; + io += do0; + } + io += do1; + } + return out; + } + // Decreasing: column 0 contains x^(N-1), last column all ones + gfill( S0, 1.0, out, strideOut1, offsetOut + ( ( S1-1 ) * strideOut2 ) ); + io = offsetOut + ( ( S1-2 ) * strideOut2 ) + ( ( S0-1 ) * strideOut1 ); + for ( i1 = S1-2; i1 >= 0; i1-- ) { + ix = offsetX + ( ( S0-1 ) * strideX ); + for ( i0 = S0-1; i0 >= 0; i0-- ) { + out[ io ] = out[ io+strideOut2 ] * x[ ix ]; + ix -= strideX; + io -= do0; + } + io -= do1; + } + return out; +} + + +// EXPORTS // + +module.exports = gvander; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gvander/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gvander/lib/index.js new file mode 100644 index 000000000000..d1690184dc46 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gvander/lib/index.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Generate a Vandermonde matrix. +* +* @module @stdlib/blas/ext/base/gvander +* +* @example +* var gvander = require( '@stdlib/blas/ext/base/gvander' ); +* +* var x = [ 1.0, 2.0, 3.0 ]; +* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; +* +* gvander( 'row-major', 1, 3, 3, x, 1, out, 3 ); +* // out => [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] +* +* @example +* var gvander = require( '@stdlib/blas/ext/base/gvander' ); +* +* var x = [ 1.0, 2.0, 3.0 ]; +* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; +* +* gvander.ndarray( 1, 3, 3, x, 1, 0, out, 3, 1, 0 ); +* // out => [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gvander/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gvander/lib/main.js new file mode 100644 index 000000000000..4c6a70233bc3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gvander/lib/main.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); +var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var max = require( '@stdlib/math/base/special/fast/max' ); +var format = require( '@stdlib/string/format' ); +var base = require( './base.js' ); + + +// MAIN // + +/** +* Generates a Vandermonde matrix. +* +* @param {string} order - storage layout +* @param {integer} mode - mode indicating whether to generate increasing or decreasing powers +* @param {NonNegativeInteger} M - number of rows in `out` +* @param {NonNegativeInteger} N - number of columns in `out` +* @param {NumericArray} x - input array +* @param {integer} strideX - stride length for `x` +* @param {NumericArray} out - output matrix +* @param {PositiveInteger} ldo - stride between successive contiguous vectors of the matrix `out` (a.k.a., leading dimension of the matrix `out`) +* @throws {TypeError} first argument must be a valid order +* @throws {RangeError} third argument must be a nonnegative integer +* @throws {RangeError} fourth argument must be a nonnegative integer +* @throws {RangeError} eighth argument must be a valid stride +* @returns {NumericArray} output matrix +* +* @example +* var x = [ 1.0, 2.0, 3.0 ]; +* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; +* +* gvander( 'row-major', 1, 3, 3, x, 1, out, 3 ); +* // out => [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] +*/ +function gvander( order, mode, M, N, x, strideX, out, ldo ) { + var iscm; + var sa1; + var sa2; + var ox; + var k; + + if ( !isLayout( order ) ) { + throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); + } + if ( M < 0 ) { + throw new RangeError( format( 'invalid argument. Third argument must be a nonnegative integer. Value: `%d`.', M ) ); + } + if ( N < 0 ) { + throw new RangeError( format( 'invalid argument. Fourth argument must be a nonnegative integer. Value: `%d`.', N ) ); + } + iscm = isColumnMajor( order ); + if ( iscm ) { + k = M; + } else { + k = N; + } + if ( ldo < max( 1, k ) ) { + throw new RangeError( format( 'invalid argument. Eighth argument must be greater than or equal to max(1,%d). Value: `%d`.', k, ldo ) ); + } + if ( M === 0 || N === 0 ) { + return out; + } + ox = stride2offset( M, strideX ); + if ( iscm ) { + sa1 = 1; + sa2 = ldo; + } else { // order === 'row-major' + sa1 = ldo; + sa2 = 1; + } + return base( mode, M, N, x, strideX, ox, out, sa1, sa2, 0 ); +} + + +// EXPORTS // + +module.exports = gvander; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gvander/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gvander/lib/ndarray.js new file mode 100644 index 000000000000..6d6f42be8196 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gvander/lib/ndarray.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-len */ + +'use strict'; + +// MODULES // + +var format = require( '@stdlib/string/format' ); +var base = require( './base.js' ); + + +// MAIN // + +/** +* Generates a Vandermonde matrix using alternative indexing semantics. +* +* @param {integer} mode - mode indicating whether to generate increasing or decreasing powers +* @param {NonNegativeInteger} M - number of rows in `out` +* @param {NonNegativeInteger} N - number of columns in `out` +* @param {NumericArray} x - input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {NumericArray} out - output matrix +* @param {integer} strideOut1 - stride length for the first dimension of `out` +* @param {integer} strideOut2 - stride length for the second dimension of `out` +* @param {NonNegativeInteger} offsetOut - starting index for `out` +* @throws {RangeError} second argument must be a nonnegative integer +* @throws {RangeError} third argument must be a nonnegative integer +* @returns {NumericArray} output matrix +* +* @example +* var x = [ 1.0, 2.0, 3.0 ]; +* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; +* +* gvander( 1, 3, 3, x, 1, 0, out, 3, 1, 0 ); +* // out => [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ] +*/ +function gvander( mode, M, N, x, strideX, offsetX, out, strideOut1, strideOut2, offsetOut ) { + if ( M < 0 ) { + throw new RangeError( format( 'invalid argument. Second argument must be a nonnegative integer. Value: `%d`.', M ) ); + } + if ( N < 0 ) { + throw new RangeError( format( 'invalid argument. Third argument must be a nonnegative integer. Value: `%d`.', N ) ); + } + if ( M === 0 || N === 0 ) { + return out; + } + return base( mode, M, N, x, strideX, offsetX, out, strideOut1, strideOut2, offsetOut ); +} + + +// EXPORTS // + +module.exports = gvander; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gvander/package.json b/lib/node_modules/@stdlib/blas/ext/base/gvander/package.json new file mode 100644 index 000000000000..3ce0d0088cad --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gvander/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/blas/ext/base/gvander", + "version": "0.0.0", + "description": "Generate a Vandermonde matrix.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "vandermonde", + "matrix", + "generate", + "strided", + "strided array", + "typed", + "array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gvander/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/gvander/test/test.js new file mode 100644 index 000000000000..e601d310a933 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gvander/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var gvander = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gvander, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof gvander.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gvander/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gvander/test/test.main.js new file mode 100644 index 000000000000..89f16cc304c3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gvander/test/test.main.js @@ -0,0 +1,710 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var gvander = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gvander, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', function test( t ) { + t.strictEqual( gvander.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function throws an error if provided an invalid first argument', function test( t ) { + var values; + var i; + + values = [ + 'foo', + 'bar', + 'beep', + 'boop' + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + gvander( value, -1, 3, 3, [ 1.0, 2.0, 3.0 ], 1, [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], 3 ); // eslint-disable-line max-len + }; + } +}); + +tape( 'the function throws an error if provided an invalid first argument (accessors)', function test( t ) { + var values; + var i; + + values = [ + 'foo', + 'bar', + 'beep', + 'boop' + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + gvander( value, -1, 3, 3, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ), 3 ); // eslint-disable-line max-len + }; + } +}); + +tape( 'the function throws an error if provided an invalid third argument', function test( t ) { + var values; + var i; + + values = [ + -1, + -2, + -3 + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + gvander( 'row-major', -1, value, 3, [ 1.0, 2.0, 3.0 ], 1, [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], 3 ); + }; + } +}); + +tape( 'the function throws an error if provided an invalid third argument (accessors)', function test( t ) { + var values; + var i; + + values = [ + -1, + -2, + -3 + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + gvander( 'row-major', -1, value, 3, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ), 3 ); + }; + } +}); + +tape( 'the function throws an error if provided an invalid fourth argument', function test( t ) { + var values; + var i; + + values = [ + -1, + -2, + -3 + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + gvander( 'row-major', -1, 3, value, [ 1.0, 2.0, 3.0 ], 1, [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], 3 ); + }; + } +}); + +tape( 'the function throws an error if provided an invalid fourth argument (accessors)', function test( t ) { + var values; + var i; + + values = [ + -1, + -2, + -3 + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + gvander( 'row-major', -1, 3, value, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ), 3 ); + }; + } +}); + +tape( 'the function throws an error if provided an invalid eighth argument', function test( t ) { + var values; + var i; + + values = [ + -3, + -2, + -1, + 0, + 1 + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + gvander( 'row-major', -1, 3, 3, [ 1.0, 2.0, 3.0 ], 1, [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], value ); + }; + } +}); + +tape( 'the function throws an error if provided an invalid eighth argument (accessors)', function test( t ) { + var values; + var i; + + values = [ + -3, + -2, + -1, + 0, + 1 + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + gvander( 'row-major', -1, 3, 3, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ), value ); + }; + } +}); + +tape( 'the function generates a Vandermonde matrix (row-major, decreasing)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'row-major', -1, 3, 3, x, 1, out, 3 ); + + expected = [ 1.0, 1.0, 1.0, 4.0, 2.0, 1.0, 9.0, 3.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function generates a Vandermonde matrix (row-major, decreasing, accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'row-major', -1, 3, 3, toAccessorArray( x ), 1, toAccessorArray( out ), 3 ); + + expected = [ 1.0, 1.0, 1.0, 4.0, 2.0, 1.0, 9.0, 3.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function generates a Vandermonde matrix (row-major, increasing)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'row-major', 1, 3, 3, x, 1, out, 3 ); + + expected = [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function generates a Vandermonde matrix (row-major, increasing, accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'row-major', 1, 3, 3, toAccessorArray( x ), 1, toAccessorArray( out ), 3 ); + + expected = [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function generates a Vandermonde matrix (column-major, decreasing)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'column-major', -1, 3, 3, x, 1, out, 3 ); + + expected = [ 1.0, 4.0, 9.0, 1.0, 2.0, 3.0, 1.0, 1.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function generates a Vandermonde matrix (column-major, decreasing, accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'column-major', -1, 3, 3, toAccessorArray( x ), 1, toAccessorArray( out ), 3 ); + + expected = [ 1.0, 4.0, 9.0, 1.0, 2.0, 3.0, 1.0, 1.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function generates a Vandermonde matrix (column-major, increasing)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'column-major', 1, 3, 3, x, 1, out, 3 ); + + expected = [ 1.0, 1.0, 1.0, 1.0, 2.0, 3.0, 1.0, 4.0, 9.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function generates a Vandermonde matrix (column-major, increasing, accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'column-major', 1, 3, 3, toAccessorArray( x ), 1, toAccessorArray( out ), 3 ); + + expected = [ 1.0, 1.0, 1.0, 1.0, 2.0, 3.0, 1.0, 4.0, 9.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns the output matrix', function test( t ) { + var out; + var x; + var v; + + x = [ 1.0, 2.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0 ]; + + v = gvander( 'row-major', -1, 2, 2, x, 1, out, 2 ); + + t.strictEqual( v, out, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns the output matrix (accessors)', function test( t ) { + var out; + var x; + var v; + + x = toAccessorArray( [ 1.0, 2.0 ] ); + out = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0 ] ); + + v = gvander( 'row-major', -1, 2, 2, x, 1, out, 2 ); + + t.strictEqual( v, out, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride for `x` (row-major)', function test( t ) { + var expected; + var out; + var x; + + // Pick every other element: x[0]=1.0, x[2]=3.0 + x = [ 1.0, 0.0, 3.0, 0.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'row-major', -1, 2, 3, x, 2, out, 3 ); + + expected = [ 1.0, 1.0, 1.0, 9.0, 3.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride for `x` (row-major, accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 0.0, 3.0, 0.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'row-major', -1, 2, 3, toAccessorArray( x ), 2, toAccessorArray( out ), 3 ); + + expected = [ 1.0, 1.0, 1.0, 9.0, 3.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride for `x` (row-major)', function test( t ) { + var expected; + var out; + var x; + + // Negative stride: starts from last and goes backward + x = [ 3.0, 0.0, 1.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'row-major', -1, 2, 3, x, -2, out, 3 ); + + // x[2]=1.0 (first), x[0]=3.0 (second) + expected = [ 1.0, 1.0, 1.0, 9.0, 3.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride for `x` (column-major)', function test( t ) { + var expected; + var out; + var x; + + // Pick every other element: x[0]=1.0, x[2]=3.0 + x = [ 1.0, 0.0, 3.0, 0.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'column-major', -1, 2, 3, x, 2, out, 2 ); + + expected = [ 1.0, 9.0, 1.0, 3.0, 1.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride for `x` (column-major, accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 0.0, 3.0, 0.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'column-major', -1, 2, 3, toAccessorArray( x ), 2, toAccessorArray( out ), 2 ); + + expected = [ 1.0, 9.0, 1.0, 3.0, 1.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride for `x` (column-major)', function test( t ) { + var expected; + var out; + var x; + + // Negative stride: starts from last and goes backward + x = [ 3.0, 0.0, 1.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'column-major', -1, 2, 3, x, -2, out, 2 ); + + // x[2]=1.0 (first), x[0]=3.0 (second) + expected = [ 1.0, 9.0, 1.0, 3.0, 1.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `ldo` larger than the matrix dimension (row-major)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + // 2x3 row-major with ldo=5 (padding of 2 per row) + gvander( 'row-major', -1, 2, 3, x, 1, out, 5 ); + + expected = [ + 1.0, + 1.0, + 1.0, + 0.0, + 0.0, + 4.0, + 2.0, + 1.0, + 0.0, + 0.0 + ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `ldo` larger than the matrix dimension (row-major, accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'row-major', -1, 2, 3, toAccessorArray( x ), 1, toAccessorArray( out ), 5 ); + + expected = [ + 1.0, + 1.0, + 1.0, + 0.0, + 0.0, + 4.0, + 2.0, + 1.0, + 0.0, + 0.0 + ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `ldo` larger than the matrix dimension (column-major)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + // 2x3 column-major with ldo=4 (padding of 2 per column) + gvander( 'column-major', -1, 2, 3, x, 1, out, 4 ); + + expected = [ + 1.0, + 4.0, + 0.0, + 0.0, + 1.0, + 2.0, + 0.0, + 0.0, + 1.0, + 1.0, + 0.0, + 0.0 + ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `ldo` larger than the matrix dimension (column-major, accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'column-major', -1, 2, 3, toAccessorArray( x ), 1, toAccessorArray( out ), 4 ); + + expected = [ + 1.0, + 4.0, + 0.0, + 0.0, + 1.0, + 2.0, + 0.0, + 0.0, + 1.0, + 1.0, + 0.0, + 0.0 + ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports non-square matrices (M > N, row-major, decreasing)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'row-major', -1, 3, 2, x, 1, out, 2 ); + + // 3x2 matrix, decreasing: + expected = [ 1.0, 1.0, 2.0, 1.0, 3.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports non-square matrices (M < N, row-major, increasing)', function test( t ) { + var expected; + var out; + var x; + + x = [ 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'row-major', 1, 2, 4, x, 1, out, 4 ); + + // 2x4 matrix, increasing: + expected = [ 1.0, 2.0, 4.0, 8.0, 1.0, 3.0, 9.0, 27.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var out; + var x0; + var x1; + + // Initial array: + x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] ); + + // Create an offset view: + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + + out = new Float64Array( 9 ); + + gvander( 'row-major', 1, 3, 3, x1, 1, out, 3 ); + + expected = new Float64Array([ + 1.0, + 1.0, + 1.0, + 1.0, + 2.0, + 4.0, + 1.0, + 3.0, + 9.0 + ]); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function handles zero values in the input array (row-major, increasing)', function test( t ) { + var expected; + var out; + var x; + + x = [ 0.0, 2.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'row-major', 1, 2, 3, x, 1, out, 3 ); + + expected = [ 1.0, 0.0, 0.0, 1.0, 2.0, 4.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function handles a single column (N=1)', function test( t ) { + var expected; + var out; + var x; + + x = [ 5.0, 10.0, 15.0 ]; + out = [ 0.0, 0.0, 0.0 ]; + + gvander( 'row-major', 1, 3, 1, x, 1, out, 1 ); + + // Single column: all x^0 = 1 + expected = [ 1.0, 1.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function handles a single row (M=1)', function test( t ) { + var expected; + var out; + var x; + + x = [ 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 'row-major', 1, 1, 4, x, 1, out, 4 ); + + // Single row: [ 3^0, 3^1, 3^2, 3^3 ] = [ 1, 3, 9, 27 ] + expected = [ 1.0, 3.0, 9.0, 27.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gvander/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gvander/test/test.ndarray.js new file mode 100644 index 000000000000..ca83ce3e0871 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gvander/test/test.ndarray.js @@ -0,0 +1,721 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gvander = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gvander, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 10', function test( t ) { + t.strictEqual( gvander.length, 10, 'has expected arity' ); + t.end(); +}); + +tape( 'the function throws an error if provided an invalid second argument', function test( t ) { + var values; + var i; + + values = [ + -1, + -2, + -3 + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + gvander( -1, value, 3, [ 1.0, 2.0, 3.0 ], 1, 0, [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], 3, 1, 0 ); // eslint-disable-line max-len + }; + } +}); + +tape( 'the function throws an error if provided an invalid second argument (accessors)', function test( t ) { + var values; + var i; + + values = [ + -1, + -2, + -3 + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + gvander( -1, value, 3, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0, toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ), 3, 1, 0 ); // eslint-disable-line max-len + }; + } +}); + +tape( 'the function throws an error if provided an invalid third argument', function test( t ) { + var values; + var i; + + values = [ + -1, + -2, + -3 + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + gvander( -1, 3, value, [ 1.0, 2.0, 3.0 ], 1, 0, [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], 3, 1, 0 ); // eslint-disable-line max-len + }; + } +}); + +tape( 'the function throws an error if provided an invalid third argument (accessors)', function test( t ) { + var values; + var i; + + values = [ + -1, + -2, + -3 + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + gvander( -1, 3, value, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0, toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ), 3, 1, 0 ); // eslint-disable-line max-len + }; + } +}); + +tape( 'the function generates a Vandermonde matrix (row-major, decreasing)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( -1, 3, 3, x, 1, 0, out, 3, 1, 0 ); + + expected = [ 1.0, 1.0, 1.0, 4.0, 2.0, 1.0, 9.0, 3.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function generates a Vandermonde matrix (row-major, decreasing, accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( -1, 3, 3, toAccessorArray( x ), 1, 0, toAccessorArray( out ), 3, 1, 0 ); // eslint-disable-line max-len + + expected = [ 1.0, 1.0, 1.0, 4.0, 2.0, 1.0, 9.0, 3.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function generates a Vandermonde matrix (row-major, increasing)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 1, 3, 3, x, 1, 0, out, 3, 1, 0 ); + + expected = [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function generates a Vandermonde matrix (row-major, increasing, accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 1, 3, 3, toAccessorArray( x ), 1, 0, toAccessorArray( out ), 3, 1, 0 ); // eslint-disable-line max-len + + expected = [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function generates a Vandermonde matrix (column-major, decreasing)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( -1, 3, 3, x, 1, 0, out, 1, 3, 0 ); + + expected = [ 1.0, 4.0, 9.0, 1.0, 2.0, 3.0, 1.0, 1.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function generates a Vandermonde matrix (column-major, decreasing, accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( -1, 3, 3, toAccessorArray( x ), 1, 0, toAccessorArray( out ), 1, 3, 0 ); // eslint-disable-line max-len + + expected = [ 1.0, 4.0, 9.0, 1.0, 2.0, 3.0, 1.0, 1.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function generates a Vandermonde matrix (column-major, increasing)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 1, 3, 3, x, 1, 0, out, 1, 3, 0 ); + + expected = [ 1.0, 1.0, 1.0, 1.0, 2.0, 3.0, 1.0, 4.0, 9.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function generates a Vandermonde matrix (column-major, increasing, accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 1, 3, 3, toAccessorArray( x ), 1, 0, toAccessorArray( out ), 1, 3, 0 ); // eslint-disable-line max-len + + expected = [ 1.0, 1.0, 1.0, 1.0, 2.0, 3.0, 1.0, 4.0, 9.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns the output matrix', function test( t ) { + var out; + var x; + var v; + + x = [ 1.0, 2.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0 ]; + + v = gvander( -1, 2, 2, x, 1, 0, out, 2, 1, 0 ); + + t.strictEqual( v, out, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns the output matrix (accessors)', function test( t ) { + var out; + var x; + var v; + + x = toAccessorArray( [ 1.0, 2.0 ] ); + out = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0 ] ); + + v = gvander( -1, 2, 2, x, 1, 0, out, 2, 1, 0 ); + + t.strictEqual( v, out, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `M` equal to `0`, the function returns the output matrix unchanged', function test( t ) { + var out; + var x; + + x = []; + out = []; + + gvander( -1, 0, 3, x, 1, 0, out, 3, 1, 0 ); + + t.deepEqual( out, [], 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` equal to `0`, the function returns the output matrix unchanged', function test( t ) { + var out; + var x; + + x = [ 1.0, 2.0 ]; + out = []; + + gvander( -1, 2, 0, x, 1, 0, out, 0, 1, 0 ); + + t.deepEqual( out, [], 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride for `x` (row-major)', function test( t ) { + var expected; + var out; + var x; + + // Pick every other element: x[0]=1.0, x[2]=3.0 + x = [ 1.0, 0.0, 3.0, 0.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( -1, 2, 3, x, 2, 0, out, 3, 1, 0 ); + + expected = [ 1.0, 1.0, 1.0, 9.0, 3.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride for `x` (row-major, accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 0.0, 3.0, 0.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( -1, 2, 3, toAccessorArray( x ), 2, 0, toAccessorArray( out ), 3, 1, 0 ); // eslint-disable-line max-len + + expected = [ 1.0, 1.0, 1.0, 9.0, 3.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride for `x` (row-major)', function test( t ) { + var expected; + var out; + var x; + + // Negative stride: starts from last and goes backward + x = [ 3.0, 0.0, 1.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( -1, 2, 3, x, -2, 2, out, 3, 1, 0 ); + + // x[2]=1.0 (first), x[0]=3.0 (second) + expected = [ 1.0, 1.0, 1.0, 9.0, 3.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride for `x` (column-major)', function test( t ) { + var expected; + var out; + var x; + + // Pick every other element: x[0]=1.0, x[2]=3.0 + x = [ 1.0, 0.0, 3.0, 0.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( -1, 2, 3, x, 2, 0, out, 1, 2, 0 ); + + expected = [ 1.0, 9.0, 1.0, 3.0, 1.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride for `x` (column-major, accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 0.0, 3.0, 0.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( -1, 2, 3, toAccessorArray( x ), 2, 0, toAccessorArray( out ), 1, 2, 0 ); // eslint-disable-line max-len + + expected = [ 1.0, 9.0, 1.0, 3.0, 1.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride for `x` (column-major)', function test( t ) { + var expected; + var out; + var x; + + // Negative stride: starts from last and goes backward + x = [ 3.0, 0.0, 1.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( -1, 2, 3, x, -2, 2, out, 1, 2, 0 ); + + // x[2]=1.0 (first), x[0]=3.0 (second) + expected = [ 1.0, 9.0, 1.0, 3.0, 1.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var expected; + var out; + var x; + + x = [ + 0.0, + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 1, 3, 3, x, 1, 1, out, 3, 1, 0 ); + + expected = [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset (accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ + 0.0, + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 1, 3, 3, toAccessorArray( x ), 1, 1, toAccessorArray( out ), 3, 1, 0 ); // eslint-disable-line max-len + + expected = [ 1.0, 1.0, 1.0, 1.0, 2.0, 4.0, 1.0, 3.0, 9.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output offset', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 1, 2, 2, x, 1, 0, out, 2, 1, 2 ); + + expected = [ 0.0, 0.0, 1.0, 1.0, 1.0, 2.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output offset (accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 1, 2, 2, toAccessorArray( x ), 1, 0, toAccessorArray( out ), 2, 1, 2 ); // eslint-disable-line max-len + + expected = [ 0.0, 0.0, 1.0, 1.0, 1.0, 2.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports output stride with padding (row-major)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + // 2x3 row-major with strideOut1=5 (padding of 2 per row) + gvander( -1, 2, 3, x, 1, 0, out, 5, 1, 0 ); + + expected = [ + 1.0, + 1.0, + 1.0, + 0.0, + 0.0, + 4.0, + 2.0, + 1.0, + 0.0, + 0.0 + ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports output stride with padding (row-major, accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( -1, 2, 3, toAccessorArray( x ), 1, 0, toAccessorArray( out ), 5, 1, 0 ); // eslint-disable-line max-len + + expected = [ + 1.0, + 1.0, + 1.0, + 0.0, + 0.0, + 4.0, + 2.0, + 1.0, + 0.0, + 0.0 + ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports output stride with padding (column-major)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + // 2x3 column-major with strideOut2=4 (padding of 2 per column) + gvander( -1, 2, 3, x, 1, 0, out, 1, 4, 0 ); + + expected = [ + 1.0, + 4.0, + 0.0, + 0.0, + 1.0, + 2.0, + 0.0, + 0.0, + 1.0, + 1.0, + 0.0, + 0.0 + ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports output stride with padding (column-major, accessors)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( -1, 2, 3, toAccessorArray( x ), 1, 0, toAccessorArray( out ), 1, 4, 0 ); // eslint-disable-line max-len + + expected = [ + 1.0, + 4.0, + 0.0, + 0.0, + 1.0, + 2.0, + 0.0, + 0.0, + 1.0, + 1.0, + 0.0, + 0.0 + ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports non-square matrices (M > N, row-major, decreasing)', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( -1, 3, 2, x, 1, 0, out, 2, 1, 0 ); + + // 3x2 matrix, decreasing: + expected = [ 1.0, 1.0, 2.0, 1.0, 3.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports non-square matrices (M < N, row-major, increasing)', function test( t ) { + var expected; + var out; + var x; + + x = [ 2.0, 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 1, 2, 4, x, 1, 0, out, 4, 1, 0 ); + + // 2x4 matrix, increasing: + expected = [ 1.0, 2.0, 4.0, 8.0, 1.0, 3.0, 9.0, 27.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var out; + var x; + + x = [ + 0.0, + 2.0, // 0 + 0.0, + 3.0 // 1 + ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 1, 2, 3, x, 2, 1, out, 3, -1, 2 ); + + expected = [ 4.0, 2.0, 1.0, 9.0, 3.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function handles zero values in the input array (row-major, increasing)', function test( t ) { + var expected; + var out; + var x; + + x = [ 0.0, 2.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 1, 2, 3, x, 1, 0, out, 3, 1, 0 ); + + expected = [ 1.0, 0.0, 0.0, 1.0, 2.0, 4.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function handles a single column (N=1)', function test( t ) { + var expected; + var out; + var x; + + x = [ 5.0, 10.0, 15.0 ]; + out = [ 0.0, 0.0, 0.0 ]; + + gvander( 1, 3, 1, x, 1, 0, out, 1, 1, 0 ); + + // Single column: all x^0 = 1 + expected = [ 1.0, 1.0, 1.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function handles a single row (M=1)', function test( t ) { + var expected; + var out; + var x; + + x = [ 3.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0 ]; + + gvander( 1, 1, 4, x, 1, 0, out, 4, 1, 0 ); + + // Single row: [ 3^0, 3^1, 3^2, 3^3 ] = [ 1, 3, 9, 27 ] + expected = [ 1.0, 3.0, 9.0, 27.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports column-major with output offset and stride', function test( t ) { + var expected; + var out; + var x; + + x = [ 1.0, 2.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + // Column-major 2x2 starting at offset 2, with strideOut2=3 (padding of 1) + gvander( 1, 2, 2, x, 1, 0, out, 1, 3, 2 ); + + expected = [ 0.0, 0.0, 1.0, 1.0, 0.0, 1.0, 2.0, 0.0 ]; + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gwhere/README.md b/lib/node_modules/@stdlib/blas/ext/base/gwhere/README.md new file mode 100644 index 000000000000..f21c221a7254 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gwhere/README.md @@ -0,0 +1,213 @@ + + +# gwhere + +> Take elements from one of two strided arrays depending on a condition. + +
+ +
+ + + +
+ +## Usage + +```javascript +var gwhere = require( '@stdlib/blas/ext/base/gwhere' ); +``` + +#### gwhere( N, condition, strideC, x, strideX, y, strideY, out, strideOut ) + +Takes elements from one of two strided arrays depending on a condition. + +```javascript +var condition = [ 1, 0, 1 ]; +var x = [ 1.0, 2.0, 3.0 ]; +var y = [ 4.0, 5.0, 6.0 ]; +var out = [ 0.0, 0.0, 0.0 ]; + +gwhere( 3, condition, 1, x, 1, y, 1, out, 1 ); +// out => [ 1.0, 5.0, 3.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **condition**: condition [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. +- **strideC**: stride length for `condition`. +- **x**: first input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. +- **strideX**: stride length for `x`. +- **y**: second input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. +- **strideY**: stride length for `y`. +- **out**: output [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. +- **strideOut**: stride length for `out`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to select from every other element: + +```javascript +var condition = [ 1, 0, 0, 1, 1, 0 ]; +var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; +var y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ]; +var out = [ 0.0, 0.0, 0.0 ]; + +gwhere( 3, condition, 2, x, 2, y, 2, out, 1 ); +// out => [ 1.0, 9.0, 5.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial arrays... +var condition0 = new Float64Array( [ 0.0, 1.0, 0.0, 1.0, 0.0, 1.0 ] ); +var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +var out0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +// Create offset views... +var condition1 = new Float64Array( condition0.buffer, condition0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +gwhere( 3, condition1, 2, x1, 2, y1, 2, out1, 1 ); +// out0 => [ 0.0, 2.0, 4.0, 6.0, 0.0, 0.0 ] +``` + + + +#### gwhere.ndarray( N, condition, strideC, offsetC, x, strideX, offsetX, y, strideY, offsetY, out, strideOut, offsetOut ) + + + +Takes elements from one of two strided arrays depending on a condition using alternative indexing semantics. + +```javascript +var condition = [ 1, 0, 1 ]; +var x = [ 1.0, 2.0, 3.0 ]; +var y = [ 4.0, 5.0, 6.0 ]; +var out = [ 0.0, 0.0, 0.0 ]; + +gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); +// out => [ 1.0, 5.0, 3.0 ] +``` + +The function has the following additional parameters: + +- **offsetC**: starting index for `condition`. +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. +- **offsetOut**: starting index for `out`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to select from every other element starting from the second element: + +```javascript +var condition = [ 0, 1, 0, 0, 0, 1 ]; +var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; +var y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ]; +var out = [ 0.0, 0.0, 0.0 ]; + +gwhere.ndarray( 3, condition, 2, 1, x, 2, 1, y, 2, 1, out, 1, 0 ); +// out => [ 2.0, 10.0, 6.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `out` unchanged. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). +- Depending on the environment, the typed versions ([`dwhere`][@stdlib/blas/ext/base/dwhere], [`swhere`][@stdlib/blas/ext/base/swhere], etc.) are likely to be significantly more performant. + +
+ + + +
+ +## Examples + + + +```javascript +var bernoulli = require( '@stdlib/random/array/bernoulli' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var zeros = require( '@stdlib/array/base/zeros' ); +var gwhere = require( '@stdlib/blas/ext/base/gwhere' ); + +var condition = bernoulli( 20, 0.5, { + 'dtype': 'generic' +}); +console.log( condition ); +var x = discreteUniform( 20, 0, 100, { + 'dtype': 'generic' +}); +console.log( x ); +var y = discreteUniform( 20, -100, 0, { + 'dtype': 'generic' +}); +console.log( y ); + +var out = zeros( condition.length ); +console.log( out ); + +gwhere( condition.length, condition, 1, x, 1, y, 1, out, 1 ); +console.log( out ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + +[@stdlib/blas/ext/base/dwhere]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dwhere + +[@stdlib/blas/ext/base/swhere]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/swhere + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gwhere/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gwhere/benchmark/benchmark.js new file mode 100644 index 000000000000..663888e00111 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gwhere/benchmark/benchmark.js @@ -0,0 +1,108 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var zeros = require( '@stdlib/array/zeros' ); +var isArray = require( '@stdlib/assert/is-array' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gwhere = require( './../lib/main.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var condition = bernoulli( len, 0.5, options ); + var out = zeros( len, options.dtype ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = gwhere( len, condition, 1, x, 1, y, 1, out, 1 ); + if ( !isArray( v ) ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isArray( v ) ) { + b.fail( 'should return an array' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gwhere/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gwhere/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..db0a6bc5873a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gwhere/benchmark/benchmark.ndarray.js @@ -0,0 +1,108 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var zeros = require( '@stdlib/array/zeros' ); +var isArray = require( '@stdlib/assert/is-array' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gwhere = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var condition = bernoulli( len, 0.5, options ); + var out = zeros( len, options.dtype ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = gwhere( len, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); + if ( !isArray( v ) ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isArray( v ) ) { + b.fail( 'should return an array' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gwhere/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gwhere/docs/repl.txt new file mode 100644 index 000000000000..dfac394a1ad4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gwhere/docs/repl.txt @@ -0,0 +1,152 @@ + +{{alias}}( N, condition, strideC, x, strideX, y, strideY, out, strideOut ) + Takes elements from one of two strided arrays depending on a condition. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `out` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + condition: ArrayLikeObject + Condition array. + + strideC: integer + Stride length for `condition`. + + x: ArrayLikeObject + First input array. + + strideX: integer + Stride length for `x`. + + y: ArrayLikeObject + Second input array. + + strideY: integer + Stride length for `y`. + + out: ArrayLikeObject + Output array. + + strideOut: integer + Stride length for `out`. + + Returns + ------- + out: ArrayLikeObject + Output array. + + Examples + -------- + // Standard Usage: + > var condition = [ 1, 0, 1 ]; + > var x = [ 1.0, 2.0, 3.0 ]; + > var y = [ 4.0, 5.0, 6.0 ]; + > var out = [ 0.0, 0.0, 0.0 ]; + > {{alias}}( 3, condition, 1, x, 1, y, 1, out, 1 ) + [ 1.0, 5.0, 3.0 ] + + // Using `N` and stride parameters: + > condition = [ 1, 0, 0, 1, 1, 0 ]; + > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ]; + > out = [ 0.0, 0.0, 0.0 ]; + > {{alias}}( 3, condition, 2, x, 2, y, 2, out, 1 ) + [ 1.0, 9.0, 5.0 ] + + // Using view offsets: + > var c0 = new {{alias:@stdlib/array/float64}}( [ 0.0, 1.0, 0.0, 1.0 ] ); + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var y0 = new {{alias:@stdlib/array/float64}}( [ 5.0, 6.0, 7.0, 8.0 ] ); + > var o0 = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0 ] ); + > var c1 = new {{alias:@stdlib/array/float64}}( c0.buffer, c0.BYTES_PER_ELEMENT*1 ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); + > var o1 = new {{alias:@stdlib/array/float64}}( o0.buffer, o0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 2, c1, 1, x1, 1, y1, 1, o1, 1 ) + [ 2.0, 7.0, 0.0 ] + + +{{alias}}.ndarray( N, c, sc, oc, x, sx, ox, y, sy, oy, o, so, oo ) + Takes elements from one of two strided arrays depending on a condition + using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + c: ArrayLikeObject + Condition array. + + sc: integer + Stride length for `c`. + + oc: integer + Starting index for `c`. + + x: ArrayLikeObject + First input array. + + sx: integer + Stride length for `x`. + + ox: integer + Starting index for `x`. + + y: ArrayLikeObject + Second input array. + + sy: integer + Stride length for `y`. + + oy: integer + Starting index for `y`. + + o: ArrayLikeObject + Output array. + + so: integer + Stride length for `o`. + + oo: integer + Starting index for `o`. + + Returns + ------- + o: ArrayLikeObject + Output array. + + Examples + -------- + // Standard Usage: + > var c = [ 1, 0, 1 ]; + > var x = [ 1.0, 2.0, 3.0 ]; + > var y = [ 4.0, 5.0, 6.0 ]; + > var o = [ 0.0, 0.0, 0.0 ]; + > {{alias}}.ndarray( 3, c, 1, 0, x, 1, 0, y, 1, 0, o, 1, 0 ) + [ 1.0, 5.0, 3.0 ] + + // Advanced indexing: + > c = [ 0, 1, 0, 0, 0, 1 ]; + > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ]; + > o = [ 0.0, 0.0, 0.0 ]; + > {{alias}}.ndarray( 3, c, 2, 1, x, 2, 1, y, 2, 1, o, -1, o.length-1 ) + [ 6.0, 10.0, 2.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gwhere/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gwhere/docs/types/index.d.ts new file mode 100644 index 000000000000..c3f069130450 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gwhere/docs/types/index.d.ts @@ -0,0 +1,131 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = Collection | AccessorArrayLike; + +/** +* Output array. +*/ +type OutputArray = Collection | AccessorArrayLike; + +/** +* Interface describing `gwhere`. +*/ +interface Routine { + /** + * Takes elements from one of two strided arrays depending on a condition. + * + * @param N - number of indexed elements + * @param condition - condition array + * @param strideC - stride length for `condition` + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @param out - output array + * @param strideOut - stride length for `out` + * @returns output array + * + * @example + * var condition = [ 1, 0, 1 ]; + * var x = [ 1.0, 2.0, 3.0 ]; + * var y = [ 4.0, 5.0, 6.0 ]; + * var out = [ 0.0, 0.0, 0.0 ]; + * + * gwhere( 3, condition, 1, x, 1, y, 1, out, 1 ); + * // out => [ 1.0, 5.0, 3.0 ] + */ + = OutputArray>( N: number, condition: InputArray, strideC: number, x: InputArray, strideX: number, y: InputArray, strideY: number, out: W, strideOut: number ): W; + + /** + * Takes elements from one of two strided arrays depending on a condition using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param condition - condition array + * @param strideC - stride length for `condition` + * @param offsetC - starting index for `condition` + * @param x - first input array + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @param offsetY - starting index for `y` + * @param out - output array + * @param strideOut - stride length for `out` + * @param offsetOut - starting index for `out` + * @returns output array + * + * @example + * var condition = [ 1, 0, 1 ]; + * var x = [ 1.0, 2.0, 3.0 ]; + * var y = [ 4.0, 5.0, 6.0 ]; + * var out = [ 0.0, 0.0, 0.0 ]; + * + * gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); + * // out => [ 1.0, 5.0, 3.0 ] + */ + ndarray = OutputArray>( N: number, condition: InputArray, strideC: number, offsetC: number, x: InputArray, strideX: number, offsetX: number, y: InputArray, strideY: number, offsetY: number, out: W, strideOut: number, offsetOut: number ): W; +} + +/** +* Takes elements from one of two strided arrays depending on a condition. +* +* @param N - number of indexed elements +* @param condition - condition array +* @param strideC - stride length for `condition` +* @param x - first input array +* @param strideX - stride length for `x` +* @param y - second input array +* @param strideY - stride length for `y` +* @param out - output array +* @param strideOut - stride length for `out` +* @returns output array +* +* @example +* var condition = [ 1, 0, 1 ]; +* var x = [ 1.0, 2.0, 3.0 ]; +* var y = [ 4.0, 5.0, 6.0 ]; +* var out = [ 0.0, 0.0, 0.0 ]; +* +* gwhere( 3, condition, 1, x, 1, y, 1, out, 1 ); +* // out => [ 1.0, 5.0, 3.0 ] +* +* @example +* var condition = [ 1, 0, 1 ]; +* var x = [ 1.0, 2.0, 3.0 ]; +* var y = [ 4.0, 5.0, 6.0 ]; +* var out = [ 0.0, 0.0, 0.0 ]; +* +* gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 5.0, 3.0 ] +*/ +declare var gwhere: Routine; + + +// EXPORTS // + +export = gwhere; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gwhere/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/gwhere/docs/types/test.ts new file mode 100644 index 000000000000..4f87f64edf56 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gwhere/docs/types/test.ts @@ -0,0 +1,445 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import gwhere = require( './index' ); + + +// TESTS // + +// The function returns a collection... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere( 3, condition, 1, x, 1, y, 1, out, 1 ); // $ExpectType Float64Array + gwhere( 3, new AccessorArray( condition ), 1, new AccessorArray( x ), 1, new AccessorArray( y ), 1, new AccessorArray( out ), 1 ); // $ExpectType AccessorArray +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere( '10', condition, 1, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( true, condition, 1, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( false, condition, 1, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( null, condition, 1, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( undefined, condition, 1, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( [], condition, 1, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( {}, condition, 1, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( ( x: number ): number => x, condition, 1, x, 1, y, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a collection... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere( 3, 10, 1, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, true, 1, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, false, 1, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, null, 1, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, undefined, 1, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, {}, 1, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, ( x: number ): number => x, 1, x, 1, y, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere( 3, condition, '10', x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, true, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, false, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, null, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, undefined, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, [], x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, {}, x, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, ( x: number ): number => x, x, 1, y, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a collection... +{ + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere( 3, condition, 1, 10, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, true, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, false, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, null, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, undefined, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, {}, 1, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, ( x: number ): number => x, 1, y, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere( 3, condition, 1, x, '10', y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, true, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, false, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, null, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, undefined, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, [], y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, {}, y, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, ( x: number ): number => x, y, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a collection... +{ + const x = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere( 3, condition, 1, x, 1, 10, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, true, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, false, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, null, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, undefined, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, {}, 1, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, ( x: number ): number => x, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a seventh argument which is not a number... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere( 3, condition, 1, x, 1, y, '10', out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, true, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, false, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, null, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, undefined, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, [], out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, {}, out, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, ( x: number ): number => x, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an eighth argument which is not a collection... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + + gwhere( 3, condition, 1, x, 1, y, 1, 10, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, 1, true, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, 1, false, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, 1, null, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, 1, undefined, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, 1, {}, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a ninth argument which is not a number... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere( 3, condition, 1, x, 1, y, 1, out, '10' ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, 1, out, true ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, 1, out, false ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, 1, out, null ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, 1, out, undefined ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, 1, out, [] ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, 1, out, {} ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, 1, out, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere(); // $ExpectError + gwhere( 3 ); // $ExpectError + gwhere( 3, condition ); // $ExpectError + gwhere( 3, condition, 1 ); // $ExpectError + gwhere( 3, condition, 1, x ); // $ExpectError + gwhere( 3, condition, 1, x, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, 1 ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, 1, out ); // $ExpectError + gwhere( 3, condition, 1, x, 1, y, 1, out, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a collection... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectType Float64Array + gwhere.ndarray( 3, new AccessorArray( condition ), 1, 0, new AccessorArray( x ), 1, 0, new AccessorArray( y ), 1, 0, new AccessorArray( out ), 1, 0 ); // $ExpectType AccessorArray +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere.ndarray( '10', condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( true, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( false, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( null, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( undefined, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( [], condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( {}, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( ( x: number ): number => x, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a collection... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere.ndarray( 3, 10, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, true, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, false, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, null, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, undefined, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, {}, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, ( x: number ): number => x, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere.ndarray( 3, condition, '10', 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, true, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, false, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, null, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, undefined, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, [], 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, {}, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, ( x: number ): number => x, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere.ndarray( 3, condition, 1, '10', x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, true, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, false, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, null, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, undefined, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, [], x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, {}, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, ( x: number ): number => x, x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a collection... +{ + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere.ndarray( 3, condition, 1, 0, 10, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, true, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, false, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, null, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, undefined, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, {}, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, ( x: number ): number => x, 1, 0, y, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere.ndarray( 3, condition, 1, 0, x, '10', 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, true, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, false, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, null, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, undefined, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, [], 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, {}, 0, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, ( x: number ): number => x, 0, y, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere.ndarray( 3, condition, 1, 0, x, 1, '10', y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, true, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, false, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, null, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, undefined, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, [], y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, {}, y, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, ( x: number ): number => x, y, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a collection... +{ + const x = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, 10, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, true, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, false, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, null, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, undefined, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, {}, 1, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, ( x: number ): number => x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a ninth argument which is not a number... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, '10', 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, true, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, false, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, null, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, undefined, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, [], 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, {}, 0, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, ( x: number ): number => x, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a tenth argument which is not a number... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, '10', out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, true, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, false, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, null, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, undefined, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, [], out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, {}, out, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, ( x: number ): number => x, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an eleventh argument which is not a collection... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, 10, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, true, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, false, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, null, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, undefined, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, {}, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a twelfth argument which is not a number... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, '10', 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, true, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, false, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, null, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, undefined, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, [], 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, {}, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a thirteenth argument which is not a number... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, '10' ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, true ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, false ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, null ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, undefined ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, [] ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, {} ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 3 ); + const y = new Float64Array( 3 ); + const condition = new Float64Array( 3 ); + const out = new Float64Array( 3 ); + + gwhere.ndarray(); // $ExpectError + gwhere.ndarray( 3 ); // $ExpectError + gwhere.ndarray( 3, condition ); // $ExpectError + gwhere.ndarray( 3, condition, 1 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1 ); // $ExpectError + gwhere.ndarray( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gwhere/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gwhere/examples/index.js new file mode 100644 index 000000000000..4aab88e0214a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gwhere/examples/index.js @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var bernoulli = require( '@stdlib/random/array/bernoulli' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var zeros = require( '@stdlib/array/base/zeros' ); +var gwhere = require( './../lib' ); + +var condition = bernoulli( 20, 0.5, { + 'dtype': 'generic' +}); +console.log( condition ); + +var x = discreteUniform( 20, 0, 100, { + 'dtype': 'generic' +}); +console.log( x ); + +var y = discreteUniform( 20, -100, 0, { + 'dtype': 'generic' +}); +console.log( y ); + +var out = zeros( condition.length ); +console.log( out ); + +gwhere( condition.length, condition, 1, x, 1, y, 1, out, 1 ); +console.log( out ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gwhere/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/gwhere/lib/accessors.js new file mode 100644 index 000000000000..169f48b722ef --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gwhere/lib/accessors.js @@ -0,0 +1,112 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Takes elements from one of two strided arrays depending on a condition. +* +* @private +* @param {PositiveInteger} N - number of indexed elements +* @param {Object} condition - condition array object +* @param {Collection} condition.data - condition array data +* @param {Array} condition.accessors - array element accessors +* @param {integer} strideC - stride length for `condition` +* @param {NonNegativeInteger} offsetC - starting index for `condition` +* @param {Object} x - first input array object +* @param {Collection} x.data - first input array data +* @param {Array} x.accessors - array element accessors +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Object} y - second input array object +* @param {Collection} y.data - second input array data +* @param {Array} y.accessors - array element accessors +* @param {integer} strideY - stride length for `y` +* @param {NonNegativeInteger} offsetY - starting index for `y` +* @param {Object} out - output array object +* @param {Collection} out.data - output array data +* @param {Array} out.accessors - array element accessors +* @param {integer} strideOut - stride length for `out` +* @param {NonNegativeInteger} offsetOut - starting index for `out` +* @returns {Object} output array object +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var condition = arraylike2object( toAccessorArray( [ 1, 0, 1 ] ) ); +* var x = arraylike2object( toAccessorArray( [ 1.0, 2.0, 3.0 ] ) ); +* var y = arraylike2object( toAccessorArray( [ 4.0, 5.0, 6.0 ] ) ); +* var out = arraylike2object( toAccessorArray( [ 0.0, 0.0, 0.0 ] ) ); +* +* gwhere( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); +* +* var v = out.data.get( 0 ); +* // returns 1.0 +*/ +function gwhere( N, condition, strideC, offsetC, x, strideX, offsetX, y, strideY, offsetY, out, strideOut, offsetOut ) { // eslint-disable-line max-len, max-params + var cbuf; + var xbuf; + var ybuf; + var obuf; + var cget; + var xget; + var yget; + var oset; + var ic; + var ix; + var iy; + var io; + var i; + + // Cache references to array data: + cbuf = condition.data; + xbuf = x.data; + ybuf = y.data; + obuf = out.data; + + // Cache references to element accessors: + cget = condition.accessors[ 0 ]; + xget = x.accessors[ 0 ]; + yget = y.accessors[ 0 ]; + oset = out.accessors[ 1 ]; + + ic = offsetC; + ix = offsetX; + iy = offsetY; + io = offsetOut; + for ( i = 0; i < N; i++ ) { + if ( cget( cbuf, ic ) ) { + oset( obuf, io, xget( xbuf, ix ) ); + } else { + oset( obuf, io, yget( ybuf, iy ) ); + } + ic += strideC; + ix += strideX; + iy += strideY; + io += strideOut; + } + return out; +} + + +// EXPORTS // + +module.exports = gwhere; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gwhere/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gwhere/lib/index.js new file mode 100644 index 000000000000..adb2a9789ca6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gwhere/lib/index.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Take elements from one of two strided arrays depending on a condition. +* +* @module @stdlib/blas/ext/base/gwhere +* +* @example +* var gwhere = require( '@stdlib/blas/ext/base/gwhere' ); +* +* var condition = [ 1, 0, 1 ]; +* var x = [ 1.0, 2.0, 3.0 ]; +* var y = [ 4.0, 5.0, 6.0 ]; +* var out = [ 0.0, 0.0, 0.0 ]; +* +* gwhere( 3, condition, 1, x, 1, y, 1, out, 1 ); +* // out => [ 1.0, 5.0, 3.0 ] +* +* @example +* var gwhere = require( '@stdlib/blas/ext/base/gwhere' ); +* +* var condition = [ 1, 0, 1, 0 ]; +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 5.0, 6.0, 7.0, 8.0 ]; +* var out = [ 0.0, 0.0, 0.0, 0.0 ]; +* +* gwhere.ndarray( 4, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 6.0, 3.0, 8.0 ] +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gwhere/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gwhere/lib/main.js new file mode 100644 index 000000000000..b8564edaab5e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gwhere/lib/main.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Takes elements from one of two strided arrays depending on a condition. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Collection} condition - condition array +* @param {integer} strideC - stride length for `condition` +* @param {Collection} x - first input array +* @param {integer} strideX - stride length for `x` +* @param {Collection} y - second input array +* @param {integer} strideY - stride length for `y` +* @param {Collection} out - output array +* @param {integer} strideOut - stride length for `out` +* @returns {Collection} output array +* +* @example +* var x = [ 1.0, 2.0, 3.0 ]; +* var y = [ 4.0, 5.0, 6.0 ]; +* var condition = [ 1, 0, 1 ]; +* var out = [ 0.0, 0.0, 0.0 ]; +* +* gwhere( 3, condition, 1, x, 1, y, 1, out, 1 ); +* // out => [ 1.0, 5.0, 3.0 ] +*/ +function gwhere( N, condition, strideC, x, strideX, y, strideY, out, strideOut ) { // eslint-disable-line max-len + var oc = stride2offset( N, strideC ); + var ox = stride2offset( N, strideX ); + var oy = stride2offset( N, strideY ); + var oo = stride2offset( N, strideOut ); + return ndarray( N, condition, strideC, oc, x, strideX, ox, y, strideY, oy, out, strideOut, oo ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = gwhere; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gwhere/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gwhere/lib/ndarray.js new file mode 100644 index 000000000000..11bfc8e25fbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gwhere/lib/ndarray.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var accessors = require( './accessors.js' ); + + +// MAIN // + +/** +* Takes elements from one of two strided arrays depending on a condition. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Collection} condition - condition array +* @param {integer} strideC - stride length for `condition` +* @param {NonNegativeInteger} offsetC - starting index for `condition` +* @param {Collection} x - first input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Collection} y - second input array +* @param {integer} strideY - stride length for `y` +* @param {NonNegativeInteger} offsetY - starting index for `y` +* @param {Collection} out - output array +* @param {integer} strideOut - stride length for `out` +* @param {NonNegativeInteger} offsetOut - starting index for `out` +* @returns {Collection} output array +* +* @example +* var x = [ 1.0, 2.0, 3.0 ]; +* var y = [ 4.0, 5.0, 6.0 ]; +* var condition = [ 1, 0, 1 ]; +* var out = [ 0.0, 0.0, 0.0 ]; +* +* gwhere( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 5.0, 3.0 ] +*/ +function gwhere( N, condition, strideC, offsetC, x, strideX, offsetX, y, strideY, offsetY, out, strideOut, offsetOut ) { // eslint-disable-line max-len, max-params + var oc; + var ox; + var oy; + var oo; + var ic; + var ix; + var iy; + var io; + var i; + + if ( N <= 0 ) { + return out; + } + oc = arraylike2object( condition ); + ox = arraylike2object( x ); + oy = arraylike2object( y ); + oo = arraylike2object( out ); + if ( oc.accessorProtocol || ox.accessorProtocol || oy.accessorProtocol || oo.accessorProtocol ) { // eslint-disable-line max-len + accessors( N, oc, strideC, offsetC, ox, strideX, offsetX, oy, strideY, offsetY, oo, strideOut, offsetOut ); // eslint-disable-line max-len + return out; + } + ic = offsetC; + ix = offsetX; + iy = offsetY; + io = offsetOut; + for ( i = 0; i < N; i++ ) { + if ( condition[ ic ] ) { + out[ io ] = x[ ix ]; + } else { + out[ io ] = y[ iy ]; + } + ic += strideC; + ix += strideX; + iy += strideY; + io += strideOut; + } + return out; +} + + +// EXPORTS // + +module.exports = gwhere; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gwhere/package.json b/lib/node_modules/@stdlib/blas/ext/base/gwhere/package.json new file mode 100644 index 000000000000..a1cfbf2011ee --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gwhere/package.json @@ -0,0 +1,69 @@ +{ + "name": "@stdlib/blas/ext/base/gwhere", + "version": "0.0.0", + "description": "Take elements from one of two strided arrays depending on a condition.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "where", + "condition", + "conditional", + "select", + "ternary", + "strided", + "strided array", + "typed", + "array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gwhere/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/gwhere/test/test.js new file mode 100644 index 000000000000..0419572eec7d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gwhere/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var gwhere = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gwhere, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof gwhere.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gwhere/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gwhere/test/test.main.js new file mode 100644 index 000000000000..17d3beb6f67b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gwhere/test/test.main.js @@ -0,0 +1,580 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var gwhere = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gwhere, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 9', function test( t ) { + t.strictEqual( gwhere.length, 9, 'has expected arity' ); + t.end(); +}); + +tape( 'the function selects elements from `x` or `y` based on a condition', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ 1, 0, 1, 0, 1 ]; + x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ]; + y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gwhere( 5, condition, 1, x, 1, y, 1, out, 1 ); + expected = [ 1.0, 7.0, 3.0, 9.0, 5.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function selects elements from `x` or `y` based on a condition (all true)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ 1, 1, 1 ]; + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 1, x, 1, y, 1, out, 1 ); + expected = [ 1.0, 2.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function selects elements from `x` or `y` based on a condition (all false)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ 0, 0, 0 ]; + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 1, x, 1, y, 1, out, 1 ); + expected = [ 4.0, 5.0, 6.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function selects elements from `x` or `y` based on a condition (truthy/falsy)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ true, false, 'a', '', 5, 0, null ]; + x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]; + y = [ 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gwhere( 7, condition, 1, x, 1, y, 1, out, 1 ); + expected = [ 1.0, 9.0, 3.0, 11.0, 5.0, 13.0, 14.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function selects elements from `x` or `y` based on a condition (accessors)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ 1, 0, 1, 0, 1 ]; + x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ]; + y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gwhere( 5, toAccessorArray( condition ), 1, toAccessorArray( x ), 1, toAccessorArray( y ), 1, toAccessorArray( out ), 1 ); // eslint-disable-line max-len + expected = [ 1.0, 7.0, 3.0, 9.0, 5.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var condition; + var actual; + var out; + var x; + var y; + + condition = [ 1, 0, 1 ]; + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + out = [ 0.0, 0.0, 0.0 ]; + + actual = gwhere( 3, condition, 1, x, 1, y, 1, out, 1 ); + + t.strictEqual( actual, out, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ 1, 0, 1 ]; + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + expected = [ 0.0, 0.0, 0.0 ]; + + out = [ 0.0, 0.0, 0.0 ]; + gwhere( -1, condition, 1, x, 1, y, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + out = [ 0.0, 0.0, 0.0 ]; + gwhere( 0, condition, 1, x, 1, y, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `condition` stride', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 1, // 0 + 0, + 0, // 1 + 1, + 1 // 2 + ]; + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 6.0, // 0 + 7.0, // 1 + 8.0, // 2 + 9.0, + 10.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 2, x, 1, y, 1, out, 1 ); + expected = [ 1.0, 7.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `condition` stride (accessors)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 1, // 0 + 0, + 0, // 1 + 1, + 1 // 2 + ]; + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 6.0, // 0 + 7.0, // 1 + 8.0, // 2 + 9.0, + 10.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, toAccessorArray( condition ), 2, toAccessorArray( x ), 1, toAccessorArray( y ), 1, toAccessorArray( out ), 1 ); // eslint-disable-line max-len + expected = [ 1.0, 7.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 1, // 0 + 0, // 1 + 1, // 2 + 0, + 0 + ]; + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 6.0, // 0 + 7.0, // 1 + 8.0, // 2 + 9.0, + 10.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 1, x, 2, y, 1, out, 1 ); + expected = [ 1.0, 7.0, 5.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 1, // 0 + 0, // 1 + 1, // 2 + 0, + 0 + ]; + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 6.0, // 0 + 7.0, // 1 + 8.0, // 2 + 9.0, + 10.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, toAccessorArray( condition ), 1, toAccessorArray( x ), 2, toAccessorArray( y ), 1, toAccessorArray( out ), 1 ); // eslint-disable-line max-len + expected = [ 1.0, 7.0, 5.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 0, // 0 + 1, // 1 + 0, // 2 + 1, + 0 + ]; + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 6.0, // 0 + 7.0, + 8.0, // 1 + 9.0, + 10.0 // 2 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 1, x, 1, y, 2, out, 1 ); + expected = [ 6.0, 2.0, 10.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` stride (accessors)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 0, // 0 + 1, // 1 + 0, // 2 + 1, + 0 + ]; + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 6.0, // 0 + 7.0, + 8.0, // 1 + 9.0, + 10.0 // 2 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, toAccessorArray( condition ), 1, toAccessorArray( x ), 1, toAccessorArray( y ), 2, toAccessorArray( out ), 1 ); // eslint-disable-line max-len + expected = [ 6.0, 2.0, 10.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `out` stride', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ 1, 0, 1 ]; + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 1, x, 1, y, 1, out, 2 ); + expected = [ 1.0, 0.0, 5.0, 0.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `out` stride (accessors)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ 1, 0, 1 ]; + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gwhere( 3, toAccessorArray( condition ), 1, toAccessorArray( x ), 1, toAccessorArray( y ), 1, toAccessorArray( out ), 2 ); // eslint-disable-line max-len + expected = [ 1.0, 0.0, 5.0, 0.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 1, // 2 + 0, + 0, // 1 + 1, + 1 // 0 + ]; + x = [ + 1.0, // 2 + 2.0, // 1 + 3.0, // 0 + 4.0, + 5.0 + ]; + y = [ + 6.0, // 2 + 7.0, // 1 + 8.0, // 0 + 9.0, + 10.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, -2, x, -1, y, -1, out, -1 ); + expected = [ 1.0, 7.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 1, // 2 + 0, + 0, // 1 + 1, + 1 // 0 + ]; + x = [ + 1.0, // 2 + 2.0, // 1 + 3.0, // 0 + 4.0, + 5.0 + ]; + y = [ + 6.0, // 2 + 7.0, // 1 + 8.0, // 0 + 9.0, + 10.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, toAccessorArray( condition ), -2, toAccessorArray( x ), -1, toAccessorArray( y ), -1, toAccessorArray( out ), -1 ); // eslint-disable-line max-len + expected = [ 1.0, 7.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 1, // 0 + 0, + 0, // 1 + 1, + 1, // 2 + 0 + ]; + x = [ + 1.0, // 2 + 2.0, // 1 + 3.0, // 0 + 4.0, + 5.0, + 6.0 + ]; + y = [ + 7.0, // 0 + 8.0, + 9.0, // 1 + 10.0, + 11.0, // 2 + 12.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 2, x, -1, y, 2, out, 1 ); + expected = [ 3.0, 9.0, 1.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var condition0; + var condition1; + var expected; + var out0; + var out1; + var x0; + var y0; + var x1; + var y1; + + // Initial arrays... + condition0 = new Float64Array( [ 0.0, 1.0, 0.0, 1.0, 0.0, 1.0 ] ); + x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); + out0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + // Create offset views... + condition1 = new Float64Array( condition0.buffer, condition0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element // eslint-disable-line max-len + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + + gwhere( 3, condition1, 2, x1, 2, y1, 2, out1, 1 ); + expected = new Float64Array( [ 0.0, 2.0, 4.0, 6.0, 0.0, 0.0 ] ); + + t.deepEqual( out0, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gwhere/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gwhere/test/test.ndarray.js new file mode 100644 index 000000000000..0aef137a04a5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gwhere/test/test.ndarray.js @@ -0,0 +1,831 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gwhere = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gwhere, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 13', function test( t ) { + t.strictEqual( gwhere.length, 13, 'has expected arity' ); + t.end(); +}); + +tape( 'the function selects elements from `x` or `y` based on a condition', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ 1, 0, 1, 0, 1 ]; + x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ]; + y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gwhere( 5, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); + expected = [ 1.0, 7.0, 3.0, 9.0, 5.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function selects elements from `x` or `y` based on a condition (all true)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ 1, 1, 1 ]; + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); + expected = [ 1.0, 2.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function selects elements from `x` or `y` based on a condition (all false)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ 0, 0, 0 ]; + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); + expected = [ 4.0, 5.0, 6.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function selects elements from `x` or `y` based on a condition (truthy/falsy)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ true, false, 'a', '', 5, 0, null ]; + x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]; + y = [ 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gwhere( 7, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); + expected = [ 1.0, 9.0, 3.0, 11.0, 5.0, 13.0, 14.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function selects elements from `x` or `y` based on a condition (accessors)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ 1, 0, 1, 0, 1 ]; + x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ]; + y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gwhere( 5, toAccessorArray( condition ), 1, 0, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 1, 0, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len + expected = [ 1.0, 7.0, 3.0, 9.0, 5.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var condition; + var actual; + var out; + var x; + var y; + + condition = [ 1, 0, 1 ]; + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + out = [ 0.0, 0.0, 0.0 ]; + + actual = gwhere( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); + + t.strictEqual( actual, out, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ 1, 0, 1 ]; + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + expected = [ 0.0, 0.0, 0.0 ]; + + out = [ 0.0, 0.0, 0.0 ]; + gwhere( -1, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + out = [ 0.0, 0.0, 0.0 ]; + gwhere( 0, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `condition` stride', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 1, // 0 + 0, + 0, // 1 + 1, + 1 // 2 + ]; + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 6.0, // 0 + 7.0, // 1 + 8.0, // 2 + 9.0, + 10.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 2, 0, x, 1, 0, y, 1, 0, out, 1, 0 ); + expected = [ 1.0, 7.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `condition` stride (accessors)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 1, // 0 + 0, + 0, // 1 + 1, + 1 // 2 + ]; + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 6.0, // 0 + 7.0, // 1 + 8.0, // 2 + 9.0, + 10.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, toAccessorArray( condition ), 2, 0, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 1, 0, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len + expected = [ 1.0, 7.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 1, // 0 + 0, // 1 + 1, // 2 + 0, + 0 + ]; + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 6.0, // 0 + 7.0, // 1 + 8.0, // 2 + 9.0, + 10.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 1, 0, x, 2, 0, y, 1, 0, out, 1, 0 ); + expected = [ 1.0, 7.0, 5.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 1, // 0 + 0, // 1 + 1, // 2 + 0, + 0 + ]; + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 6.0, // 0 + 7.0, // 1 + 8.0, // 2 + 9.0, + 10.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, toAccessorArray( condition ), 1, 0, toAccessorArray( x ), 2, 0, toAccessorArray( y ), 1, 0, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len + expected = [ 1.0, 7.0, 5.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 0, // 0 + 1, // 1 + 0, // 2 + 1, + 0 + ]; + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 6.0, // 0 + 7.0, + 8.0, // 1 + 9.0, + 10.0 // 2 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 1, 0, x, 1, 0, y, 2, 0, out, 1, 0 ); + expected = [ 6.0, 2.0, 10.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` stride (accessors)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 0, // 0 + 1, // 1 + 0, // 2 + 1, + 0 + ]; + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 6.0, // 0 + 7.0, + 8.0, // 1 + 9.0, + 10.0 // 2 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, toAccessorArray( condition ), 1, 0, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 2, 0, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len + expected = [ 6.0, 2.0, 10.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `out` stride', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ 1, 0, 1 ]; + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 2, 0 ); + expected = [ 1.0, 0.0, 5.0, 0.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `out` stride (accessors)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ 1, 0, 1 ]; + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + gwhere( 3, toAccessorArray( condition ), 1, 0, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 1, 0, toAccessorArray( out ), 2, 0 ); // eslint-disable-line max-len + expected = [ 1.0, 0.0, 5.0, 0.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 1, // 2 + 0, + 0, // 1 + 1, + 1 // 0 + ]; + x = [ + 1.0, // 2 + 2.0, // 1 + 3.0, // 0 + 4.0, + 5.0 + ]; + y = [ + 6.0, // 2 + 7.0, // 1 + 8.0, // 0 + 9.0, + 10.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, -2, 4, x, -1, 2, y, -1, 2, out, -1, 2 ); + expected = [ 1.0, 7.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 1, // 2 + 0, + 0, // 1 + 1, + 1 // 0 + ]; + x = [ + 1.0, // 2 + 2.0, // 1 + 3.0, // 0 + 4.0, + 5.0 + ]; + y = [ + 6.0, // 2 + 7.0, // 1 + 8.0, // 0 + 9.0, + 10.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, toAccessorArray( condition ), -2, 4, toAccessorArray( x ), -1, 2, toAccessorArray( y ), -1, 2, toAccessorArray( out ), -1, 2 ); // eslint-disable-line max-len + expected = [ 1.0, 7.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `condition` offset', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 0, + 1, // 0 + 0, + 0, // 1 + 0, + 1 // 2 + ]; + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0, + 6.0 + ]; + y = [ + 7.0, // 0 + 8.0, // 1 + 9.0, // 2 + 10.0, + 11.0, + 12.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 2, 1, x, 1, 0, y, 1, 0, out, 1, 0 ); + expected = [ 1.0, 8.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `condition` offset (accessors)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 0, + 1, // 0 + 0, + 0, // 1 + 0, + 1 // 2 + ]; + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0, + 6.0 + ]; + y = [ + 7.0, // 0 + 8.0, // 1 + 9.0, // 2 + 10.0, + 11.0, + 12.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, toAccessorArray( condition ), 2, 1, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 1, 0, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len + expected = [ 1.0, 8.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 1, // 0 + 0, // 1 + 1, // 2 + 0 + ]; + x = [ + 0.0, + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0, // 2 + 0.0, + 4.0 + ]; + y = [ + 5.0, // 0 + 6.0, // 1 + 7.0, // 2 + 8.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 1, 0, x, 2, 1, y, 1, 0, out, 1, 0 ); + expected = [ 1.0, 6.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` offset (accessors)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 1, // 0 + 0, // 1 + 1, // 2 + 0 + ]; + x = [ + 0.0, + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0, // 2 + 0.0, + 4.0 + ]; + y = [ + 5.0, // 0 + 6.0, // 1 + 7.0, // 2 + 8.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, toAccessorArray( condition ), 1, 0, toAccessorArray( x ), 2, 1, toAccessorArray( y ), 1, 0, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len + expected = [ 1.0, 6.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` offset', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 0, // 0 + 1, // 1 + 0, // 2 + 1 + ]; + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0 + ]; + y = [ + 0.0, + 5.0, // 0 + 0.0, + 6.0, // 1 + 0.0, + 7.0, // 2 + 0.0, + 8.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 1, 0, x, 1, 0, y, 2, 1, out, 1, 0 ); + expected = [ 5.0, 2.0, 7.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` offset (accessors)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 0, // 0 + 1, // 1 + 0, // 2 + 1 + ]; + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0 + ]; + y = [ + 0.0, + 5.0, // 0 + 0.0, + 6.0, // 1 + 0.0, + 7.0, // 2 + 0.0, + 8.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, toAccessorArray( condition ), 1, 0, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 2, 1, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len + expected = [ 5.0, 2.0, 7.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `out` offset', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ 1, 0, 1 ]; + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + out = [ + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 1 + 0.0 // 2 + ]; + + gwhere( 3, condition, 1, 0, x, 1, 0, y, 1, 0, out, 1, 2 ); + expected = [ 0.0, 0.0, 1.0, 5.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `out` offset (accessors)', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ 1, 0, 1 ]; + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + out = [ + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 1 + 0.0 // 2 + ]; + + gwhere( 3, toAccessorArray( condition ), 1, 0, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 1, 0, toAccessorArray( out ), 1, 2 ); // eslint-disable-line max-len + expected = [ 0.0, 0.0, 1.0, 5.0, 3.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var condition; + var expected; + var out; + var x; + var y; + + condition = [ + 1, // 0 + 0, + 0, // 1 + 1, + 1, // 2 + 0 + ]; + x = [ + 1.0, // 2 + 2.0, // 1 + 3.0, // 0 + 4.0, + 5.0, + 6.0 + ]; + y = [ + 7.0, // 0 + 8.0, + 9.0, // 1 + 10.0, + 11.0, // 2 + 12.0 + ]; + out = [ 0.0, 0.0, 0.0 ]; + + gwhere( 3, condition, 2, 0, x, -1, 2, y, 2, 0, out, 1, 0 ); + expected = [ 3.0, 9.0, 1.0 ]; + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/lib/index.js index 3bc9d46a28ba..72b9e149e538 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/lib/index.js @@ -918,6 +918,15 @@ setReadOnly( ns, 'gnansumpw', require( '@stdlib/blas/ext/base/gnansumpw' ) ); */ setReadOnly( ns, 'goneTo', require( '@stdlib/blas/ext/base/gone-to' ) ); +/** +* @name greplicate +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/greplicate} +*/ +setReadOnly( ns, 'greplicate', require( '@stdlib/blas/ext/base/greplicate' ) ); + /** * @name grev * @memberof ns @@ -1035,6 +1044,15 @@ setReadOnly( ns, 'gsumors', require( '@stdlib/blas/ext/base/gsumors' ) ); */ setReadOnly( ns, 'gsumpw', require( '@stdlib/blas/ext/base/gsumpw' ) ); +/** +* @name gvander +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/gvander} +*/ +setReadOnly( ns, 'gvander', require( '@stdlib/blas/ext/base/gvander' ) ); + /** * @name gzeroTo * @memberof ns @@ -1332,6 +1350,15 @@ setReadOnly( ns, 'soneTo', require( '@stdlib/blas/ext/base/sone-to' ) ); */ setReadOnly( ns, 'srev', require( '@stdlib/blas/ext/base/srev' ) ); +/** +* @name ssort +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ssort} +*/ +setReadOnly( ns, 'ssort', require( '@stdlib/blas/ext/base/ssort' ) ); + /** * @name ssort2hp * @memberof ns diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/README.md index dc8e2cbd9881..9421c5ef11e5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/README.md @@ -45,6 +45,7 @@ The namespace exposes the following APIs:
+- [`coneTo( arrays )`][@stdlib/blas/ext/base/ndarray/cone-to]: fill a one-dimensional single-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from one. - [`csum( arrays )`][@stdlib/blas/ext/base/ndarray/csum]: compute the sum of all elements in a one-dimensional single-precision complex floating-point ndarray. - [`csumkbn( arrays )`][@stdlib/blas/ext/base/ndarray/csumkbn]: compute the sum of all elements in a one-dimensional single-precision complex floating-point ndarray using an improved Kahan–Babuška algorithm. - [`czeroTo( arrays )`][@stdlib/blas/ext/base/ndarray/czero-to]: fill a one-dimensional single-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from zero. @@ -63,6 +64,7 @@ The namespace exposes the following APIs: - [`dnansumors( arrays )`][@stdlib/blas/ext/base/ndarray/dnansumors]: compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values and using ordinary recursive summation. - [`dnansumpw( arrays )`][@stdlib/blas/ext/base/ndarray/dnansumpw]: compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values and using pairwise summation. - [`doneTo( arrays )`][@stdlib/blas/ext/base/ndarray/done-to]: fill a one-dimensional double-precision floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from one. +- [`dsort( arrays )`][@stdlib/blas/ext/base/ndarray/dsort]: sort a one-dimensional double-precision floating-point ndarray. - [`dsorthp( arrays )`][@stdlib/blas/ext/base/ndarray/dsorthp]: sort a one-dimensional double-precision floating-point ndarray using heapsort. - [`dsortins( arrays )`][@stdlib/blas/ext/base/ndarray/dsortins]: sort a one-dimensional double-precision floating-point ndarray using insertion sort. - [`dsortsh( arrays )`][@stdlib/blas/ext/base/ndarray/dsortsh]: sort a one-dimensional double-precision floating-point ndarray using Shellsort. @@ -113,6 +115,7 @@ The namespace exposes the following APIs: - [`snansumors( arrays )`][@stdlib/blas/ext/base/ndarray/snansumors]: compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values and using ordinary recursive summation. - [`snansumpw( arrays )`][@stdlib/blas/ext/base/ndarray/snansumpw]: compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values and using pairwise summation. - [`soneTo( arrays )`][@stdlib/blas/ext/base/ndarray/sone-to]: fill a one-dimensional single-precision floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from one. +- [`ssort( arrays )`][@stdlib/blas/ext/base/ndarray/ssort]: sort a one-dimensional single-precision floating-point ndarray. - [`ssorthp( arrays )`][@stdlib/blas/ext/base/ndarray/ssorthp]: sort a one-dimensional single-precision floating-point ndarray using heapsort. - [`ssum( arrays )`][@stdlib/blas/ext/base/ndarray/ssum]: compute the sum of all elements in a one-dimensional single-precision floating-point ndarray. - [`ssumkbn( arrays )`][@stdlib/blas/ext/base/ndarray/ssumkbn]: compute the sum of all elements in a one-dimensional single-precision floating-point ndarray using an improved Kahan–Babuška algorithm. @@ -120,6 +123,7 @@ The namespace exposes the following APIs: - [`ssumors( arrays )`][@stdlib/blas/ext/base/ndarray/ssumors]: compute the sum of a one-dimensional single-precision floating-point ndarray using ordinary recursive summation. - [`ssumpw( arrays )`][@stdlib/blas/ext/base/ndarray/ssumpw]: compute the sum of all elements in a one-dimensional single-precision floating-point ndarray using pairwise summation. - [`szeroTo( arrays )`][@stdlib/blas/ext/base/ndarray/szero-to]: fill a one-dimensional single-precision floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from zero. +- [`zoneTo( arrays )`][@stdlib/blas/ext/base/ndarray/zone-to]: fill a one-dimensional double-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from one. - [`zsum( arrays )`][@stdlib/blas/ext/base/ndarray/zsum]: compute the sum of all elements in a one-dimensional double-precision complex floating-point ndarray. - [`zsumkbn( arrays )`][@stdlib/blas/ext/base/ndarray/zsumkbn]: compute the sum of all elements in a one-dimensional double-precision complex floating-point ndarray using an improved Kahan–Babuška algorithm. - [`zzeroTo( arrays )`][@stdlib/blas/ext/base/ndarray/zzero-to]: fill a one-dimensional double-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from zero. @@ -165,6 +169,8 @@ console.log( objectKeys( ns ) ); +[@stdlib/blas/ext/base/ndarray/cone-to]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/cone-to + [@stdlib/blas/ext/base/ndarray/csum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/csum [@stdlib/blas/ext/base/ndarray/csumkbn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/csumkbn @@ -201,6 +207,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/ndarray/done-to]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/done-to +[@stdlib/blas/ext/base/ndarray/dsort]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dsort + [@stdlib/blas/ext/base/ndarray/dsorthp]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dsorthp [@stdlib/blas/ext/base/ndarray/dsortins]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dsortins @@ -301,6 +309,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/ndarray/sone-to]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/sone-to +[@stdlib/blas/ext/base/ndarray/ssort]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/ssort + [@stdlib/blas/ext/base/ndarray/ssorthp]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/ssorthp [@stdlib/blas/ext/base/ndarray/ssum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/ssum @@ -315,6 +325,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/ndarray/szero-to]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/szero-to +[@stdlib/blas/ext/base/ndarray/zone-to]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/zone-to + [@stdlib/blas/ext/base/ndarray/zsum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/zsum [@stdlib/blas/ext/base/ndarray/zsumkbn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/zsumkbn diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/README.md new file mode 100644 index 000000000000..f4eca5937a8b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/README.md @@ -0,0 +1,110 @@ + + +# coneTo + +> Fill a one-dimensional single-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from one. + +
+ +
+ + + +
+ +## Usage + +```javascript +var coneTo = require( '@stdlib/blas/ext/base/ndarray/cone-to' ); +``` + +#### coneTo( arrays ) + +Fills a one-dimensional single-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from one. + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); + +var xbuf = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +var x = new ndarray( 'complex64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); + +var out = coneTo( [ x ] ); +// returns [ [ 1.0, 0.0 ], [ 2.0, 0.0 ], [ 3.0, 0.0 ], [ 4.0, 0.0 ] ] +``` + +The function has the following parameters: + +- **arrays**: array-like object containing a one-dimensional input ndarray. + +
+ + + +
+ +## Notes + +- The input ndarray is modified **in-place** (i.e., the input ndarray is **mutated**). + +
+ + + +
+ +## Examples + + + +```javascript +var zeros = require( '@stdlib/array/zeros' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var coneTo = require( '@stdlib/blas/ext/base/ndarray/cone-to' ); + +var xbuf = zeros( 10, 'complex64' ); +var x = new ndarray( 'complex64', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +coneTo( [ x ] ); +console.log( ndarray2array( x ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/benchmark/benchmark.js new file mode 100644 index 000000000000..673e390818ea --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/benchmark/benchmark.js @@ -0,0 +1,108 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var zeros = require( '@stdlib/array/zeros' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var pkg = require( './../package.json' ).name; +var coneTo = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'complex64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var x; + + xbuf = zeros( len, options.dtype ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = coneTo( [ x ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/docs/repl.txt new file mode 100644 index 000000000000..c6a976c28d44 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/docs/repl.txt @@ -0,0 +1,32 @@ + +{{alias}}( arrays ) + Fills a one-dimensional single-precision complex floating-point ndarray with + linearly spaced numeric elements which increment by `1` starting from one. + + The input ndarray is modified *in-place* (i.e., the input ndarray is + *mutated*). + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing a one-dimensional input ndarray. + + Returns + ------- + out: ndarray + Input ndarray. + + Examples + -------- + > var xbuf = new {{alias:@stdlib/array/complex64}}( [ 0.0, 0.0, 0.0, 0.0 ] ); + > var dt = 'complex64'; + > var sh = [ 2 ]; + > var sx = [ 1 ]; + > var ox = 0; + > var ord = 'row-major'; + > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord ); + > {{alias}}( [ x ] ) + [ [ 1.0, 0.0 ], [ 2.0, 0.0 ] ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/docs/types/index.d.ts new file mode 100644 index 000000000000..f4b37e6b4393 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/docs/types/index.d.ts @@ -0,0 +1,46 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { complex64ndarray } from '@stdlib/types/ndarray'; + +/** +* Fills a one-dimensional single-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from one. +* +* @param arrays - array-like object containing a one-dimensional input ndarray +* @returns input ndarray +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var x = new ndarray( 'complex64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var out = coneTo( [ x ] ); +* // returns [ [ 1.0, 0.0 ], [ 2.0, 0.0 ], [ 3.0, 0.0 ], [ 4.0, 0.0 ] ] +*/ +declare function coneTo( arrays: [ complex64ndarray ] ): complex64ndarray; + + +// EXPORTS // + +export = coneTo; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/docs/types/test.ts new file mode 100644 index 000000000000..0694d73a36d9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/docs/types/test.ts @@ -0,0 +1,57 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import coneTo = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'complex64' + }); + + coneTo( [ x ] ); // $ExpectType complex64ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + coneTo( '10' ); // $ExpectError + coneTo( 10 ); // $ExpectError + coneTo( true ); // $ExpectError + coneTo( false ); // $ExpectError + coneTo( null ); // $ExpectError + coneTo( undefined ); // $ExpectError + coneTo( [] ); // $ExpectError + coneTo( {} ); // $ExpectError + coneTo( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'complex64' + }); + + coneTo(); // $ExpectError + coneTo( [ x ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/examples/index.js new file mode 100644 index 000000000000..825bd3d14112 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var zeros = require( '@stdlib/array/zeros' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var coneTo = require( './../lib' ); + +var xbuf = zeros( 10, 'complex64' ); +var x = new ndarray( 'complex64', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +coneTo( [ x ] ); +console.log( ndarray2array( x ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/lib/index.js new file mode 100644 index 000000000000..bfeba8135238 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/lib/index.js @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Fill a one-dimensional single-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from one. +* +* @module @stdlib/blas/ext/base/ndarray/cone-to +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* var coneTo = require( '@stdlib/blas/ext/base/ndarray/cone-to' ); +* +* var xbuf = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var x = new ndarray( 'complex64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var out = coneTo( [ x ] ); +* // returns [ [ 1.0, 0.0 ], [ 2.0, 0.0 ], [ 3.0, 0.0 ], [ 4.0, 0.0 ] ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/lib/main.js new file mode 100644 index 000000000000..e053e2cea257 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/lib/main.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/cone-to' ).ndarray; + + +// MAIN // + +/** +* Fills a one-dimensional single-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from one. +* +* @param {ArrayLikeObject} arrays - array-like object containing a one-dimensional input ndarray +* @returns {ndarray} input ndarray +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var x = new ndarray( 'complex64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var out = coneTo( [ x ] ); +* // returns [ [ 1.0, 0.0 ], [ 2.0, 0.0 ], [ 3.0, 0.0 ], [ 4.0, 0.0 ] ] +*/ +function coneTo( arrays ) { + var x = arrays[ 0 ]; + strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len + return x; +} + + +// EXPORTS // + +module.exports = coneTo; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/package.json new file mode 100644 index 000000000000..755055e0857c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/package.json @@ -0,0 +1,74 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/cone-to", + "version": "0.0.0", + "description": "Fill a one-dimensional single-precision complex floating-point ndarray with linearly spaced numeric elements which increment by 1 starting from one.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "fill", + "one", + "oneto", + "one-to", + "linearly", + "spaced", + "increment", + "strided", + "array", + "ndarray", + "complex64", + "complex", + "single-precision", + "float32" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/test/test.js new file mode 100644 index 000000000000..061b571a5d33 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cone-to/test/test.js @@ -0,0 +1,290 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var coneTo = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Complex64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'complex64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof coneTo, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( coneTo.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function fills a one-dimensional ndarray with linearly spaced numeric elements which increment by 1 starting from one', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + x = vector( xbuf, 4, 1, 0 ); + + actual = coneTo( [ x ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Complex64Array( [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0, 4.0, 0.0 ] ); + t.strictEqual( isSameComplex64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the input ndarray unchanged when the input ndarray is empty', function test( t ) { + var actual; + var xbuf; + var x; + + xbuf = new Complex64Array( [] ); + x = vector( xbuf, 0, 1, 0 ); + + actual = coneTo( [ x ] ); + t.strictEqual( actual, x, 'returns expected value' ); + t.strictEqual( getData( actual ).length, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function fills a one-dimensional ndarray containing a single element', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Complex64Array( [ 5.0, 5.0 ] ); + x = vector( xbuf, 1, 1, 0 ); + + actual = coneTo( [ x ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Complex64Array( [ 1.0, 0.0 ] ); + t.strictEqual( isSameComplex64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a non-unit stride', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Complex64Array([ + 0.0, // 0 + 0.0, // 0 + 9.0, + 9.0, + 0.0, // 1 + 0.0, // 1 + 9.0, + 9.0, + 0.0, // 2 + 0.0, // 2 + 9.0, + 9.0, + 0.0, // 3 + 0.0, // 3 + 9.0, + 9.0 + ]); + x = vector( xbuf, 4, 2, 0 ); + + actual = coneTo( [ x ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Complex64Array([ + 1.0, // 0 + 0.0, // 0 + 9.0, + 9.0, + 2.0, // 1 + 0.0, // 1 + 9.0, + 9.0, + 3.0, // 2 + 0.0, // 2 + 9.0, + 9.0, + 4.0, // 3 + 0.0, // 3 + 9.0, + 9.0 + ]); + t.strictEqual( isSameComplex64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a negative stride', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Complex64Array([ + 0.0, // 4 + 0.0, // 4 + 0.0, // 3 + 0.0, // 3 + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]); + x = vector( xbuf, 5, -1, 4 ); + + actual = coneTo( [ x ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Complex64Array([ + 5.0, // 4 + 0.0, // 4 + 4.0, // 3 + 0.0, // 3 + 3.0, // 2 + 0.0, // 2 + 2.0, // 1 + 0.0, // 1 + 1.0, // 0 + 0.0 // 0 + ]); + t.strictEqual( isSameComplex64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a non-zero offset', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Complex64Array([ + 9.0, + 9.0, + 9.0, + 9.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, // 3 + 0.0 // 3 + ]); + x = vector( xbuf, 4, 1, 2 ); + + actual = coneTo( [ x ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Complex64Array([ + 9.0, + 9.0, + 9.0, + 9.0, + 1.0, // 0 + 0.0, // 0 + 2.0, // 1 + 0.0, // 1 + 3.0, // 2 + 0.0, // 2 + 4.0, // 3 + 0.0 // 3 + ]); + t.strictEqual( isSameComplex64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a negative stride and non-zero offset', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Complex64Array([ + 9.0, + 9.0, + 0.0, // 2 + 0.0, // 2 + 9.0, + 9.0, + 0.0, // 1 + 0.0, // 1 + 9.0, + 9.0, + 0.0, // 0 + 0.0 // 0 + ]); + x = vector( xbuf, 3, -2, 5 ); + + actual = coneTo( [ x ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Complex64Array([ + 9.0, + 9.0, + 3.0, // 2 + 0.0, // 2 + 9.0, + 9.0, + 2.0, // 1 + 0.0, // 1 + 9.0, + 9.0, + 1.0, // 0 + 0.0 // 0 + ]); + t.strictEqual( isSameComplex64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/README.md index f13b7d704485..56e449229166 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/README.md @@ -98,6 +98,164 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/ndarray/csum.h" +``` + +#### stdlib_blas_ext_csum( arrays ) + +Computes the sum of all elements in a one-dimensional single-precision complex floating-point ndarray. + +```c +#include "stdlib/complex/float32/ctor.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include "stdlib/complex/float32/real.h" +#include "stdlib/complex/float32/imag.h" +#include + +// Create an ndarray: +const float data[] = { 1.0f, 2.0f, 3.0f, 4.0f }; +int64_t shape[] = { 2 }; +int64_t strides[] = { STDLIB_NDARRAY_COMPLEX64_BYTES_PER_ELEMENT }; +int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + +struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_COMPLEX64, (uint8_t *)data, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes ); + +// Compute the sum: +const struct ndarray *arrays[] = { x }; +stdlib_complex64_t v = stdlib_blas_ext_csum( arrays ); + +float re = stdlib_complex64_real( v ); +// returns 4.0f + +float im = stdlib_complex64_imag( v ); +// returns 6.0f + +// Free allocated memory: +stdlib_ndarray_free( x ); +``` + +The function accepts the following arguments: + +- **arrays**: `[in] struct ndarray**` list containing a one-dimensional input ndarray. + +```c +stdlib_complex64_t stdlib_blas_ext_csum( const struct ndarray *arrays[] ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/ndarray/csum.h" +#include "stdlib/complex/float32/ctor.h" +#include "stdlib/complex/float32/real.h" +#include "stdlib/complex/float32/imag.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include + +int main( void ) { + // Create a data buffer: + const float data[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; + + // Specify the number of array dimensions: + const int64_t ndims = 1; + + // Specify the array shape: + int64_t shape[] = { 4 }; + + // Specify the array strides: + int64_t strides[] = { STDLIB_NDARRAY_COMPLEX64_BYTES_PER_ELEMENT }; + + // Specify the byte offset: + const int64_t offset = 0; + + // Specify the array order: + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const int64_t nsubmodes = 1; + + // Create an ndarray: + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_COMPLEX64, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x }; + + // Compute the sum: + stdlib_complex64_t v = stdlib_blas_ext_csum( arrays ); + + // Print the result: + printf( "sum: %f + %fi\n", stdlib_complex64_real( v ), stdlib_complex64_imag( v ) ); + + // Free allocated memory: + stdlib_ndarray_free( x ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/benchmark/benchmark.js index b0326f31275c..cfc3cd6c7b38 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/benchmark/benchmark.js @@ -28,8 +28,9 @@ var imagf = require( '@stdlib/complex/float32/imag' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var Complex64Array = require( '@stdlib/array/complex64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; -var csum = require( './../lib' ); +var csum = require( './../lib/main.js' ); // VARIABLES // @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/benchmark/benchmark.native.js new file mode 100644 index 000000000000..2fb243925a97 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/benchmark/benchmark.native.js @@ -0,0 +1,119 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var csum = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( csum instanceof Error ) +}; +var options = { + 'dtype': 'complex64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var x; + + xbuf = uniform( len*2, -10.0, 10.0, { + 'dtype': 'float32' + }); + x = new ndarray( options.dtype, new Complex64Array( xbuf ), [ len ], [ 1 ], 0, 'row-major' ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = csum( [ x ] ); + if ( isnanf( realf( v ) ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( imagf( v ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..4441ef2d9f28 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/benchmark/c/benchmark.length.c @@ -0,0 +1,193 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ndarray/csum.h" +#include "stdlib/complex/float32/ctor.h" +#include "stdlib/complex/float32/real.h" +#include "stdlib/complex/float32/imag.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include +#include +#include +#include + +#define NAME "csum" +#define ITERATIONS 1000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static float rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark( int iterations, int len ) { + enum STDLIB_NDARRAY_INDEX_MODE imode; + const struct ndarray *arrays[ 1 ]; + enum STDLIB_NDARRAY_ORDER order; + int8_t submodes[ 1 ]; + int64_t strides[ 1 ]; + int64_t shape[ 1 ]; + int64_t nsubmodes; + struct ndarray *x; + stdlib_complex64_t v; + int64_t offset; + double elapsed; + int64_t ndims; + float *data; + double t; + float r; + int i; + + ndims = 1; + shape[ 0 ] = len; + strides[ 0 ] = STDLIB_NDARRAY_COMPLEX64_BYTES_PER_ELEMENT; + offset = 0; + order = STDLIB_NDARRAY_ROW_MAJOR; + imode = STDLIB_NDARRAY_INDEX_ERROR; + submodes[ 0 ] = imode; + nsubmodes = 1; + + data = (float *) malloc( len * 2 * sizeof( float ) ); + for ( i = 0; i < len*2; i += 2 ) { + r = ( rand_float() * 20000.0f ) - 10000.0f; + data[ i ] = r; + data[ i+1 ] = r; + } + // cppcheck-suppress invalidPointerCast + x = stdlib_ndarray_allocate( STDLIB_NDARRAY_COMPLEX64, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + arrays[ 0 ] = x; + + v = stdlib_complex64( 0.0f, 0.0f ); + t = tic(); + for ( i = 0; i < iterations; i++ ) { + v = stdlib_blas_ext_csum( arrays ); + r = stdlib_complex64_real( v ); + if ( r != r ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + r = stdlib_complex64_imag( v ); + if ( r != r ) { + printf( "should not return NaN\n" ); + } + stdlib_ndarray_free( x ); + free( data ); + arrays[ 0 ] = NULL; + + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/examples/c/example.c new file mode 100644 index 000000000000..70656a4b36c7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/examples/c/example.c @@ -0,0 +1,77 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ndarray/csum.h" +#include "stdlib/complex/float32/ctor.h" +#include "stdlib/complex/float32/real.h" +#include "stdlib/complex/float32/imag.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include + +int main( void ) { + // Create a data buffer: + const float data[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; + + // Specify the number of array dimensions: + const int64_t ndims = 1; + + // Specify the array shape: + int64_t shape[] = { 4 }; + + // Specify the array strides: + int64_t strides[] = { STDLIB_NDARRAY_COMPLEX64_BYTES_PER_ELEMENT }; + + // Specify the byte offset: + const int64_t offset = 0; + + // Specify the array order: + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const int64_t nsubmodes = 1; + + // Create an ndarray: + // cppcheck-suppress invalidPointerCast + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_COMPLEX64, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x }; + + // Compute the sum: + stdlib_complex64_t v = stdlib_blas_ext_csum( arrays ); + + // Print the result: + printf( "sum: %f + %fi\n", stdlib_complex64_real( v ), stdlib_complex64_imag( v ) ); + + // Free allocated memory: + stdlib_ndarray_free( x ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '} arrays - array-like object containing an input ndarray +* @returns {Complex64} sum +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Complex64Array( [ 1.0, 3.0, 4.0, 2.0 ] ); +* var x = new ndarray( 'complex64', xbuf, [ 2 ], [ 1 ], 0, 'row-major' ); +* +* var v = csum( [ x ] ); +* // returns [ 5.0, 5.0 ] +*/ +function csum( arrays ) { + var x = arrays[ 0 ]; + var o = addon( reinterpret( getData( x ), 0 ), serialize( x ) ); + return new Complex64( o.re, o.im ); +} + + +// EXPORTS // + +module.exports = csum; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/manifest.json new file mode 100644 index 000000000000..0fe3db50998b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/manifest.json @@ -0,0 +1,120 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/csum", + "@stdlib/complex/float32/ctor", + "@stdlib/complex/float32/real", + "@stdlib/complex/float32/imag", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/base/napi/addon-arguments", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/create-complex-like" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/csum", + "@stdlib/complex/float32/ctor", + "@stdlib/complex/float32/real", + "@stdlib/complex/float32/imag", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/dtypes", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders", + "@stdlib/ndarray/base/bytes-per-element" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/csum", + "@stdlib/complex/float32/ctor", + "@stdlib/complex/float32/real", + "@stdlib/complex/float32/imag", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/dtypes", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders", + "@stdlib/ndarray/base/bytes-per-element" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/csum", + "@stdlib/complex/float32/ctor", + "@stdlib/ndarray/ctor" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/package.json index 7cce5b1c156b..601b45605811 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/package.json @@ -14,11 +14,15 @@ } ], "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/src/addon.c new file mode 100644 index 000000000000..fdda8c4ae150 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/src/addon.c @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ndarray/csum.h" +#include "stdlib/complex/float32/ctor.h" +#include "stdlib/complex/float32/real.h" +#include "stdlib/complex/float32/imag.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/base/napi/addon_arguments.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/create_complex_like.h" +#include +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 2 ); + + // Process provided arguments: + struct ndarray *arrays[ 1 ]; + napi_value err; + napi_status status = stdlib_ndarray_napi_addon_arguments( env, argv, 2, 1, arrays, &err ); + assert( status == napi_ok ); + if ( err != NULL ) { + status = napi_throw( env, err ); + assert( status == napi_ok ); + return NULL; + } + // Perform computation: + stdlib_complex64_t z = stdlib_blas_ext_csum( (const struct ndarray **)arrays ); + STDLIB_NAPI_CREATE_COMPLEX_LIKE( env, (double)stdlib_complex64_real( z ), (double)stdlib_complex64_imag( z ), v ); + + // Free allocated memory: + stdlib_ndarray_free( arrays[ 0 ] ); + arrays[ 0 ] = NULL; + + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/src/main.c new file mode 100644 index 000000000000..f6f47b7f15f6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/src/main.c @@ -0,0 +1,34 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ndarray/csum.h" +#include "stdlib/blas/ext/base/csum.h" +#include "stdlib/complex/float32/ctor.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/blas/base/shared.h" + +/** +* Computes the sum of all elements in a one-dimensional single-precision complex floating-point ndarray. +* +* @param arrays list containing an input ndarray +* @return sum +*/ +stdlib_complex64_t stdlib_blas_ext_csum( const struct ndarray *arrays[] ) { + const struct ndarray *x = arrays[ 0 ]; + return API_SUFFIX(stdlib_strided_csum_ndarray)( stdlib_ndarray_dimension( x, 0 ), (const stdlib_complex64_t *)stdlib_ndarray_data( x ), stdlib_ndarray_stride_elements( x, 0 ), stdlib_ndarray_offset_elements( x ) ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/test/test.js index 5ab5e1da0f66..08b8f60f9b49 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/test/test.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/test/test.js @@ -21,28 +21,16 @@ // MODULES // var tape = require( 'tape' ); -var isSameComplex64 = require( '@stdlib/assert/is-same-complex64' ); -var Complex64Array = require( '@stdlib/array/complex64' ); -var Complex64 = require( '@stdlib/complex/float32/ctor' ); -var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); var csum = require( './../lib' ); -// FUNCTIONS // +// VARIABLES // -/** -* Returns a one-dimensional ndarray. -* -* @private -* @param {Complex64Array} buffer - underlying data buffer -* @param {NonNegativeInteger} length - number of indexed elements -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - index offset -* @returns {ndarray} one-dimensional ndarray -*/ -function vector( buffer, length, stride, offset ) { - return new ndarray( 'complex64', buffer, [ length ], [ stride ], offset, 'row-major' ); -} +var opts = { + 'skip': IS_BROWSER +}; // TESTS // @@ -53,147 +41,37 @@ tape( 'main export is a function', function test( t ) { t.end(); }); -tape( 'the function has an arity of 1', function test( t ) { - t.strictEqual( csum.length, 1, 'has expected arity' ); - t.end(); -}); - -tape( 'the function computes the sum of all elements in a one-dimensional ndarray', function test( t ) { - var x; - var v; - - x = new Complex64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); - v = csum( [ vector( x, 3, 1, 0 ) ] ); - t.strictEqual( isSameComplex64( v, new Complex64( -3.0, 6.0 ) ), true, 'returns expected value' ); - - x = new Complex64Array( [ -4.0, -5.0, -4.0, -5.0 ] ); - v = csum( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( isSameComplex64( v, new Complex64( -8.0, -10.0 ) ), true, 'returns expected value' ); - - x = new Complex64Array( [ -0.0, 0.0, -0.0, -0.0 ] ); - v = csum( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( isSameComplex64( v, new Complex64( -0.0, 0.0 ) ), true, 'returns expected value' ); - - x = new Complex64Array( [ NaN, NaN ] ); - v = csum( [ vector( x, 1, 1, 0 ) ] ); - t.strictEqual( isSameComplex64( v, new Complex64( NaN, NaN ) ), true, 'returns expected value' ); - - x = new Complex64Array( [ NaN, NaN, NaN, NaN ] ); - v = csum( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( isSameComplex64( v, new Complex64( NaN, NaN ) ), true, 'returns expected value' ); +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var csum = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + t.strictEqual( csum, mock, 'returns expected value' ); t.end(); -}); -tape( 'if provided an empty vector, the function returns `0.0`', function test( t ) { - var x; - var v; + function tryRequire() { + return mock; + } - x = new Complex64Array( [] ); - - v = csum( [ vector( x, 0, 1, 0 ) ] ); - t.strictEqual( isSameComplex64( v, new Complex64( 0.0, 0.0 ) ), true, 'returns expected value' ); - - t.end(); + function mock() { + // Mock... + } }); -tape( 'if provided a vector containing a single element, the function returns that element', function test( t ) { - var x; - var v; +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var csum; + var main; - x = new Complex64Array( [ 1.0, 2.0 ] ); - - v = csum( [ vector( x, 1, 1, 0 ) ] ); - t.strictEqual( isSameComplex64( v, new Complex64( 1.0, 2.0 ) ), true, 'returns expected value' ); - - t.end(); -}); + main = require( './../lib/main.js' ); -tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { - var x; - var v; - - x = new Complex64Array([ - 1.0, // 0 - 1.0, // 0 - 2.0, - 2.0, - 2.0, // 1 - 2.0, // 1 - -7.0, - -7.0, - -2.0, // 2 - -2.0, // 2 - 3.0, - 3.0, - 4.0, // 3 - 4.0, // 3 - 2.0, - 2.0 - ]); - - v = csum( [ vector( x, 4, 2, 0 ) ] ); - - t.strictEqual( isSameComplex64( v, new Complex64( 5.0, 5.0 ) ), true, 'returns expected value' ); - t.end(); -}); + csum = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); -tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { - var x; - var v; - - x = new Complex64Array([ - 1.0, // 3 - 1.0, // 3 - 2.0, - 2.0, - 2.0, // 2 - 2.0, // 2 - -7.0, - -7.0, - -2.0, // 1 - -2.0, // 1 - 3.0, - 3.0, - 4.0, // 0 - 4.0, // 0 - 2.0, - 2.0 - ]); - - v = csum( [ vector( x, 4, -2, 6 ) ] ); - - t.strictEqual( isSameComplex64( v, new Complex64( 5.0, 5.0 ) ), true, 'returns expected value' ); + t.strictEqual( csum, main, 'returns expected value' ); t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { - var x; - var v; - - x = new Complex64Array([ - -9.0, - -9.0, - 1.0, // 3 - 1.0, // 3 - 2.0, - 2.0, - 2.0, // 2 - 2.0, // 2 - -7.0, - -7.0, - -2.0, // 1 - -2.0, // 1 - 3.0, - 3.0, - 4.0, // 0 - 4.0, // 0 - 2.0, - 2.0 - ]); - - v = csum( [ vector( x, 4, 2, 1 ) ] ); - t.strictEqual( isSameComplex64( v, new Complex64( 5.0, 5.0 ) ), true, 'returns expected value' ); - t.end(); + function tryRequire() { + return new Error( 'Cannot find module' ); + } }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/test/test.main.js new file mode 100644 index 000000000000..4b0476555844 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/test/test.main.js @@ -0,0 +1,199 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex64 = require( '@stdlib/assert/is-same-complex64' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var csum = require( './../lib/main.js' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Complex64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'complex64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof csum, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( csum.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the sum of all elements in a one-dimensional ndarray', function test( t ) { + var x; + var v; + + x = new Complex64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + v = csum( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( isSameComplex64( v, new Complex64( -3.0, 6.0 ) ), true, 'returns expected value' ); + + x = new Complex64Array( [ -4.0, -5.0, -4.0, -5.0 ] ); + v = csum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isSameComplex64( v, new Complex64( -8.0, -10.0 ) ), true, 'returns expected value' ); + + x = new Complex64Array( [ -0.0, 0.0, -0.0, -0.0 ] ); + v = csum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isSameComplex64( v, new Complex64( -0.0, 0.0 ) ), true, 'returns expected value' ); + + x = new Complex64Array( [ NaN, NaN ] ); + v = csum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( isSameComplex64( v, new Complex64( NaN, NaN ) ), true, 'returns expected value' ); + + x = new Complex64Array( [ NaN, NaN, NaN, NaN ] ); + v = csum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isSameComplex64( v, new Complex64( NaN, NaN ) ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `0.0`', function test( t ) { + var x; + var v; + + x = new Complex64Array( [] ); + + v = csum( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( isSameComplex64( v, new Complex64( 0.0, 0.0 ) ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a vector containing a single element, the function returns that element', function test( t ) { + var x; + var v; + + x = new Complex64Array( [ 1.0, 2.0 ] ); + + v = csum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( isSameComplex64( v, new Complex64( 1.0, 2.0 ) ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var x; + var v; + + x = new Complex64Array([ + 1.0, // 0 + 1.0, // 0 + 2.0, + 2.0, + 2.0, // 1 + 2.0, // 1 + -7.0, + -7.0, + -2.0, // 2 + -2.0, // 2 + 3.0, + 3.0, + 4.0, // 3 + 4.0, // 3 + 2.0, + 2.0 + ]); + + v = csum( [ vector( x, 4, 2, 0 ) ] ); + + t.strictEqual( isSameComplex64( v, new Complex64( 5.0, 5.0 ) ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var x; + var v; + + x = new Complex64Array([ + 1.0, // 3 + 1.0, // 3 + 2.0, + 2.0, + 2.0, // 2 + 2.0, // 2 + -7.0, + -7.0, + -2.0, // 1 + -2.0, // 1 + 3.0, + 3.0, + 4.0, // 0 + 4.0, // 0 + 2.0, + 2.0 + ]); + + v = csum( [ vector( x, 4, -2, 6 ) ] ); + + t.strictEqual( isSameComplex64( v, new Complex64( 5.0, 5.0 ) ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var x; + var v; + + x = new Complex64Array([ + -9.0, + -9.0, + 1.0, // 3 + 1.0, // 3 + 2.0, + 2.0, + 2.0, // 2 + 2.0, // 2 + -7.0, + -7.0, + -2.0, // 1 + -2.0, // 1 + 3.0, + 3.0, + 4.0, // 0 + 4.0, // 0 + 2.0, + 2.0 + ]); + + v = csum( [ vector( x, 4, 2, 1 ) ] ); + t.strictEqual( isSameComplex64( v, new Complex64( 5.0, 5.0 ) ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/test/test.native.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/test/test.native.js new file mode 100644 index 000000000000..ddcf884d0b02 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csum/test/test.native.js @@ -0,0 +1,208 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isSameComplex64 = require( '@stdlib/assert/is-same-complex64' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var csum = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( csum instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Complex64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'complex64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof csum, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', opts, function test( t ) { + t.strictEqual( csum.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function computes the sum of all elements in a one-dimensional ndarray', opts, function test( t ) { + var x; + var v; + + x = new Complex64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + v = csum( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( isSameComplex64( v, new Complex64( -3.0, 6.0 ) ), true, 'returns expected value' ); + + x = new Complex64Array( [ -4.0, -5.0, -4.0, -5.0 ] ); + v = csum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isSameComplex64( v, new Complex64( -8.0, -10.0 ) ), true, 'returns expected value' ); + + x = new Complex64Array( [ -0.0, 0.0, -0.0, -0.0 ] ); + v = csum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isSameComplex64( v, new Complex64( -0.0, 0.0 ) ), true, 'returns expected value' ); + + x = new Complex64Array( [ NaN, NaN ] ); + v = csum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( isSameComplex64( v, new Complex64( NaN, NaN ) ), true, 'returns expected value' ); + + x = new Complex64Array( [ NaN, NaN, NaN, NaN ] ); + v = csum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isSameComplex64( v, new Complex64( NaN, NaN ) ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `0.0`', opts, function test( t ) { + var x; + var v; + + x = new Complex64Array( [] ); + + v = csum( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( isSameComplex64( v, new Complex64( 0.0, 0.0 ) ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an ndarray containing a single element, the function returns that element', opts, function test( t ) { + var x; + var v; + + x = new Complex64Array( [ 1.0, 2.0 ] ); + + v = csum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( isSameComplex64( v, new Complex64( 1.0, 2.0 ) ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', opts, function test( t ) { + var x; + var v; + + x = new Complex64Array([ + 1.0, // 0 + 1.0, // 0 + 2.0, + 2.0, + 2.0, // 1 + 2.0, // 1 + -7.0, + -7.0, + -2.0, // 2 + -2.0, // 2 + 3.0, + 3.0, + 4.0, // 3 + 4.0, // 3 + 2.0, + 2.0 + ]); + + v = csum( [ vector( x, 4, 2, 0 ) ] ); + + t.strictEqual( isSameComplex64( v, new Complex64( 5.0, 5.0 ) ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', opts, function test( t ) { + var x; + var v; + + x = new Complex64Array([ + 1.0, // 3 + 1.0, // 3 + 2.0, + 2.0, + 2.0, // 2 + 2.0, // 2 + -7.0, + -7.0, + -2.0, // 1 + -2.0, // 1 + 3.0, + 3.0, + 4.0, // 0 + 4.0, // 0 + 2.0, + 2.0 + ]); + + v = csum( [ vector( x, 4, -2, 6 ) ] ); + + t.strictEqual( isSameComplex64( v, new Complex64( 5.0, 5.0 ) ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', opts, function test( t ) { + var x; + var v; + + x = new Complex64Array([ + -9.0, + -9.0, + 1.0, // 3 + 1.0, // 3 + 2.0, + 2.0, + 2.0, // 2 + 2.0, // 2 + -7.0, + -7.0, + -2.0, // 1 + -2.0, // 1 + 3.0, + 3.0, + 4.0, // 0 + 4.0, // 0 + 2.0, + 2.0 + ]); + + v = csum( [ vector( x, 4, 2, 1 ) ] ); + t.strictEqual( isSameComplex64( v, new Complex64( 5.0, 5.0 ) ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csumkbn/benchmark/benchmark.js index ad258968d868..f478b296905b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/csumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/csumkbn/benchmark/benchmark.js @@ -28,6 +28,7 @@ var imagf = require( '@stdlib/complex/float32/imag' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var Complex64Array = require( '@stdlib/array/complex64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var csumkbn = require( './../lib' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusum/benchmark/benchmark.js index ff7bc06ed0ef..4ed2d79a2a44 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusum/benchmark/benchmark.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcusum = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/README.md index 3789090b9237..b02701f66388 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/README.md @@ -42,7 +42,6 @@ Computes the cumulative sum of a one-dimensional double-precision floating-point ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); @@ -55,13 +54,10 @@ var y = new ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' ); var initial = scalar2ndarray( 0.0, 'float64', 'row-major' ); var v = dcusumkbn( [ x, y, initial ] ); -// returns +// returns [ 1.0, 4.0, 8.0, 10.0 ] var bool = ( v === y ); // returns true - -var arr = ndarray2array( v ); -// returns [ 1.0, 4.0, 8.0, 10.0 ] ``` The function has the following parameters: diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/docs/types/index.d.ts index 692b9b9b729b..fc4e31c78101 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/docs/types/index.d.ts @@ -30,7 +30,6 @@ import { float64ndarray } from '@stdlib/types/ndarray'; * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); * var ndarray = require( '@stdlib/ndarray/base/ctor' ); * @@ -43,13 +42,10 @@ import { float64ndarray } from '@stdlib/types/ndarray'; * var initial = scalar2ndarray( 0.0, 'float64', 'row-major' ); * * var v = dcusumkbn( [ x, y, initial ] ); -* // returns +* // returns [ 1.0, 4.0, 8.0, 10.0 ] * * var bool = ( v === y ); * // returns true -* -* var arr = ndarray2array( v ); -* // returns [ 1.0, 4.0, 8.0, 10.0 ] */ declare function dcusumkbn( arrays: [ float64ndarray, float64ndarray, float64ndarray ] ): float64ndarray; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/lib/index.js index fedfcf64e6a9..bbc4fc3f4078 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/lib/index.js @@ -25,7 +25,6 @@ * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var ndarray = require( '@stdlib/ndarray/base/ctor' ); * var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); * var dcusumkbn = require( '@stdlib/blas/ext/base/ndarray/dcusumkbn' ); @@ -39,13 +38,10 @@ * var initial = scalar2ndarray( 0.0, 'float64', 'row-major' ); * * var v = dcusumkbn( [ x, y, initial ] ); -* // returns +* // returns [ 1.0, 4.0, 8.0, 10.0 ] * * var bool = ( v === y ); * // returns true -* -* var arr = ndarray2array( v ); -* // returns [ 1.0, 4.0, 8.0, 10.0 ] */ // MODULES // diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn2/benchmark/benchmark.js index 5038e9224f3e..c2e25a5454de 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn2/benchmark/benchmark.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcusumkbn2 = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg + ':len=' + len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumors/benchmark/benchmark.js index 01169305f589..58b4c35de1e4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumors/benchmark/benchmark.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcusumors = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of/benchmark/benchmark.js index d13c358b0740..112b42815147 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dindexOf = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dlast-index-of/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dlast-index-of/benchmark/benchmark.js index 185d2af1ebff..402e61811cbe 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dlast-index-of/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dlast-index-of/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dlastIndexOf = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dlinspace/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dlinspace/benchmark/benchmark.js index b76cbd6ccdb3..a3c795b41f11 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dlinspace/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dlinspace/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dlinspace = require( './../lib' ); @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/README.md index e07729cba97c..cc52e77cea00 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/README.md @@ -102,6 +102,153 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/ndarray/dnansum.h" +``` + +#### stdlib_blas_ext_dnansum( arrays ) + +Computes the sum of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values. + +```c +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include + +// Create an ndarray: +const double data[] = { 1.0, 0.0/0.0, 3.0, 4.0 }; +int64_t shape[] = { 4 }; +int64_t strides[] = { STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT }; +int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + +struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)data, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes ); + +// Compute the sum: +const struct ndarray *arrays[] = { x }; +double v = stdlib_blas_ext_dnansum( arrays ); +// returns 8.0 + +// Free allocated memory: +stdlib_ndarray_free( x ); +``` + +The function accepts the following arguments: + +- **arrays**: `[in] struct ndarray**` list containing a one-dimensional input ndarray. + +```c +double stdlib_blas_ext_dnansum( const struct ndarray *arrays[] ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/ndarray/dnansum.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include + +int main( void ) { + // Create a data buffer: + const double data[] = { 1.0, -2.0, 0.0/0.0, -4.0, 5.0, -6.0, 0.0/0.0, -8.0 }; + + // Specify the number of array dimensions: + const int64_t ndims = 1; + + // Specify the array shape: + int64_t shape[] = { 4 }; + + // Specify the array strides: + int64_t strides[] = { 2*STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT }; + + // Specify the byte offset: + const int64_t offset = 0; + + // Specify the array order: + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const int64_t nsubmodes = 1; + + // Create an ndarray: + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x }; + + // Compute the sum: + double v = stdlib_blas_ext_dnansum( arrays ); + + // Print the result: + printf( "sum: %lf\n", v ); + + // Free allocated memory: + stdlib_ndarray_free( x ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/benchmark/benchmark.js index f9f31bc7b7ee..96b54b7dd733 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/benchmark/benchmark.js @@ -27,8 +27,9 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; -var dnansum = require( './../lib' ); +var dnansum = require( './../lib/main.js' ); // VARIABLES // @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/benchmark/benchmark.native.js new file mode 100644 index 000000000000..79a8c0a74674 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/benchmark/benchmark.native.js @@ -0,0 +1,129 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dnansum = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( dnansum instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.7 ) > 0 ) { + return discreteUniform( -10.0, 10.0 ); + } + return NaN; +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var x; + + xbuf = filledarrayBy( len, options.dtype, rand ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = dnansum( [ x ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..1e1a8ca86b0a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/benchmark/c/benchmark.length.c @@ -0,0 +1,189 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ndarray/dnansum.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include +#include +#include +#include + +#define NAME "dnansum" +#define ITERATIONS 1000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark( int iterations, int len ) { + enum STDLIB_NDARRAY_INDEX_MODE imode; + const struct ndarray *arrays[ 1 ]; + enum STDLIB_NDARRAY_ORDER order; + int8_t submodes[ 1 ]; + int64_t strides[ 1 ]; + int64_t shape[ 1 ]; + int64_t nsubmodes; + struct ndarray *x; + int64_t offset; + double elapsed; + int64_t ndims; + double *data; + double v; + double t; + int i; + + ndims = 1; + shape[ 0 ] = len; + strides[ 0 ] = STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT; + offset = 0; + order = STDLIB_NDARRAY_ROW_MAJOR; + imode = STDLIB_NDARRAY_INDEX_ERROR; + submodes[ 0 ] = imode; + nsubmodes = 1; + + data = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + if ( rand_double() < 0.2 ) { + data[ i ] = 0.0 / 0.0; // NaN + } else { + data[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + } + // cppcheck-suppress invalidPointerCast + x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + arrays[ 0 ] = x; + + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + v = stdlib_blas_ext_dnansum( arrays ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + stdlib_ndarray_free( x ); + free( data ); + arrays[ 0 ] = NULL; + + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/examples/c/example.c new file mode 100644 index 000000000000..10f83c567951 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/examples/c/example.c @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ndarray/dnansum.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include + +int main( void ) { + // Create a data buffer: + const double data[] = { 1.0, -2.0, 0.0/0.0, -4.0, 5.0, -6.0, 0.0/0.0, -8.0 }; + + // Specify the number of array dimensions: + const int64_t ndims = 1; + + // Specify the array shape: + int64_t shape[] = { 4 }; + + // Specify the array strides: + int64_t strides[] = { 2*STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT }; + + // Specify the byte offset: + const int64_t offset = 0; + + // Specify the array order: + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const int64_t nsubmodes = 1; + + // Create an ndarray: + // cppcheck-suppress invalidPointerCast + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x }; + + // Compute the sum: + double v = stdlib_blas_ext_dnansum( arrays ); + + // Print the result: + printf( "sum: %lf\n", v ); + + // Free allocated memory: + stdlib_ndarray_free( x ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '} arrays - array-like object containing an input ndarray +* @returns {number} sum +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); +* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var v = dnansum( [ x ] ); +* // returns 1.0 +*/ +function dnansum( arrays ) { + var x = arrays[ 0 ]; + return addon( getData( x ), serialize( x ) ); +} + + +// EXPORTS // + +module.exports = dnansum; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/manifest.json new file mode 100644 index 000000000000..268743e8021a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/manifest.json @@ -0,0 +1,110 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/dnansum", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/base/napi/addon-arguments", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/dnansum", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/dtypes", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders", + "@stdlib/ndarray/base/bytes-per-element" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/dnansum", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/dtypes", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders", + "@stdlib/ndarray/base/bytes-per-element" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/dnansum", + "@stdlib/ndarray/ctor" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/package.json index 4ff912d88e05..0a439cfa7053 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/package.json @@ -14,11 +14,15 @@ } ], "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/src/addon.c new file mode 100644 index 000000000000..d01905481d67 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/src/addon.c @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ndarray/dnansum.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/base/napi/addon_arguments.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/create_double.h" +#include +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 2 ); + + // Process provided arguments: + struct ndarray *arrays[ 1 ]; + napi_value err; + napi_status status = stdlib_ndarray_napi_addon_arguments( env, argv, 2, 1, arrays, &err ); + assert( status == napi_ok ); + if ( err != NULL ) { + status = napi_throw( env, err ); + assert( status == napi_ok ); + return NULL; + } + // Perform computation: + STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_blas_ext_dnansum( arrays ), v ); + + // Free allocated memory: + stdlib_ndarray_free( arrays[ 0 ] ); + arrays[ 0 ] = NULL; + + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/src/main.c new file mode 100644 index 000000000000..ba8e5a61f96a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/src/main.c @@ -0,0 +1,33 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ndarray/dnansum.h" +#include "stdlib/blas/ext/base/dnansum.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/blas/base/shared.h" + +/** +* Computes the sum of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values. +* +* @param arrays list containing an input ndarray +* @return sum +*/ +double stdlib_blas_ext_dnansum( const struct ndarray *arrays[] ) { + const struct ndarray *x = arrays[ 0 ]; + return API_SUFFIX(stdlib_strided_dnansum_ndarray)( stdlib_ndarray_dimension( x, 0 ), (const double *)stdlib_ndarray_data( x ), stdlib_ndarray_stride_elements( x, 0 ), stdlib_ndarray_offset_elements( x ) ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/test/test.js index f4dd232f781e..c6702af100a1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/test/test.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/test/test.js @@ -21,27 +21,16 @@ // MODULES // var tape = require( 'tape' ); -var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); -var Float64Array = require( '@stdlib/array/float64' ); -var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); var dnansum = require( './../lib' ); -// FUNCTIONS // +// VARIABLES // -/** -* Returns a one-dimensional ndarray. -* -* @private -* @param {Float64Array} buffer - underlying data buffer -* @param {NonNegativeInteger} length - number of indexed elements -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - index offset -* @returns {ndarray} one-dimensional ndarray -*/ -function vector( buffer, length, stride, offset ) { - return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); -} +var opts = { + 'skip': IS_BROWSER +}; // TESTS // @@ -52,129 +41,37 @@ tape( 'main export is a function', function test( t ) { t.end(); }); -tape( 'the function has an arity of 1', function test( t ) { - t.strictEqual( dnansum.length, 1, 'has expected arity' ); - t.end(); -}); - -tape( 'the function computes the sum of a one-dimensional ndarray, ignoring NaN values', function test( t ) { - var x; - var v; - - x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ] ); - v = dnansum( [ vector( x, 7, 1, 0 ) ] ); - t.strictEqual( v, 3.0, 'returns expected value' ); - - x = new Float64Array( [ -4.0, NaN, -5.0 ] ); - v = dnansum( [ vector( x, 3, 1, 0 ) ] ); - t.strictEqual( v, -9.0, 'returns expected value' ); - - x = new Float64Array( [ NaN, 4.0 ] ); - v = dnansum( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( v, 4.0, 'returns expected value' ); - - x = new Float64Array( [ NaN, NaN ] ); - v = dnansum( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( v, 0.0, 'returns expected value' ); - - x = new Float64Array( [ NaN ] ); - v = dnansum( [ vector( x, 1, 1, 0 ) ] ); - t.strictEqual( v, 0.0, 'returns expected value' ); - - x = new Float64Array( [ 1.0, 1.0e100, 1.0, -1.0e100 ] ); - v = dnansum( [ vector( x, 4, 1, 0 ) ] ); - t.strictEqual( v, 2.0, 'returns expected value' ); +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var dnansum = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + t.strictEqual( dnansum, mock, 'returns expected value' ); t.end(); -}); - -tape( 'if provided an empty ndarray, the function returns `0.0`', function test( t ) { - var x; - var v; - x = new Float64Array( [] ); + function tryRequire() { + return mock; + } - v = dnansum( [ vector( x, 0, 1, 0 ) ] ); - t.strictEqual( isPositiveZero( v ), true, 'returns expected value' ); - - t.end(); + function mock() { + // Mock... + } }); -tape( 'if provided a ndarray containing a single element, the function returns that element', function test( t ) { - var x; - var v; +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var dnansum; + var main; - x = new Float64Array( [ 1.0 ] ); + main = require( './../lib/main.js' ); - v = dnansum( [ vector( x, 1, 1, 0 ) ] ); - t.strictEqual( v, 1.0, 'returns expected value' ); + dnansum = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + t.strictEqual( dnansum, main, 'returns expected value' ); t.end(); -}); -tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { - var x; - var v; - - x = new Float64Array([ - 1.0, // 0 - 2.0, - 2.0, // 1 - -7.0, - -2.0, // 2 - 3.0, - 4.0, // 3 - 2.0, - NaN, // 4 - NaN - ]); - - v = dnansum( [ vector( x, 5, 2, 0 ) ] ); - - t.strictEqual( v, 5.0, 'returns expected value' ); - t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { - var x; - var v; - - x = new Float64Array([ - NaN, // 4 - NaN, - 1.0, // 3 - 2.0, - 2.0, // 2 - -7.0, - -2.0, // 1 - 3.0, - 4.0, // 0 - 2.0 - ]); - - v = dnansum( [ vector( x, 5, -2, 8 ) ] ); - - t.strictEqual( v, 5.0, 'returns expected value' ); - t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { - var x; - var v; - - x = new Float64Array([ - 2.0, - 1.0, // 0 - 2.0, - -2.0, // 1 - -2.0, - 2.0, // 2 - 3.0, - 4.0 // 3 - ]); - - v = dnansum( [ vector( x, 4, 2, 1 ) ] ); - t.strictEqual( v, 5.0, 'returns expected value' ); - - t.end(); + function tryRequire() { + return new Error( 'Cannot find module' ); + } }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/test/test.main.js new file mode 100644 index 000000000000..e4200138d1af --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/test/test.main.js @@ -0,0 +1,180 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var dnansum = require( './../lib/main.js' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dnansum, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( dnansum.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the sum of a one-dimensional ndarray, ignoring NaN values', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ] ); + v = dnansum( [ vector( x, 7, 1, 0 ) ] ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + x = new Float64Array( [ -4.0, NaN, -5.0 ] ); + v = dnansum( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, -9.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, 4.0 ] ); + v = dnansum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, 4.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + v = dnansum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float64Array( [ NaN ] ); + v = dnansum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0e100, 1.0, -1.0e100 ] ); + v = dnansum( [ vector( x, 4, 1, 0 ) ] ); + t.strictEqual( v, 2.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `0.0`', function test( t ) { + var x; + var v; + + x = new Float64Array( [] ); + + v = dnansum( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( isPositiveZero( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an ndarray containing a single element, the function returns that element', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0 ] ); + + v = dnansum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]); + + v = dnansum( [ vector( x, 5, 2, 0 ) ] ); + + t.strictEqual( v, 5.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var x; + var v; + + x = new Float64Array([ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = dnansum( [ vector( x, 5, -2, 8 ) ] ); + + t.strictEqual( v, 5.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + + v = dnansum( [ vector( x, 4, 2, 1 ) ] ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/test/test.native.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/test/test.native.js new file mode 100644 index 000000000000..f062e3cfbddc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/test/test.native.js @@ -0,0 +1,189 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dnansum = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( dnansum instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dnansum, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', opts, function test( t ) { + t.strictEqual( dnansum.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the sum of a one-dimensional ndarray, ignoring NaN values', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ] ); + v = dnansum( [ vector( x, 7, 1, 0 ) ] ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + x = new Float64Array( [ -4.0, NaN, -5.0 ] ); + v = dnansum( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, -9.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, 4.0 ] ); + v = dnansum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, 4.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + v = dnansum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float64Array( [ NaN ] ); + v = dnansum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0e100, 1.0, -1.0e100 ] ); + v = dnansum( [ vector( x, 4, 1, 0 ) ] ); + t.strictEqual( v, 2.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `0.0`', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [] ); + + v = dnansum( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( isPositiveZero( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an ndarray containing a single element, the function returns that element', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0 ] ); + + v = dnansum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]); + + v = dnansum( [ vector( x, 5, 2, 0 ) ] ); + + t.strictEqual( v, 5.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = dnansum( [ vector( x, 5, -2, 8 ) ] ); + + t.strictEqual( v, 5.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + + v = dnansum( [ vector( x, 4, 2, 1 ) ] ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumkbn/benchmark/benchmark.js index 50d37c928b56..5d61ee09adac 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumkbn/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumkbn = require( './../lib' ); @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumkbn2/benchmark/benchmark.js index c0935b69deb2..5effb2b85d2a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumkbn2/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumkbn2 = require( './../lib' ); @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumors/benchmark/benchmark.js index cc1ce13a842f..6199326d3a7d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumors/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumors = require( './../lib' ); @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumpw/benchmark/benchmark.js index 733842cacf75..f05d7da7f5fb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumpw/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumpw = require( './../lib' ); @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/docs/types/index.d.ts index e50f11ad392f..158a32e4d5a3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/docs/types/index.d.ts @@ -20,6 +20,7 @@ /* eslint-disable max-lines */ +import coneTo = require( '@stdlib/blas/ext/base/ndarray/cone-to' ); import csum = require( '@stdlib/blas/ext/base/ndarray/csum' ); import csumkbn = require( '@stdlib/blas/ext/base/ndarray/csumkbn' ); import czeroTo = require( '@stdlib/blas/ext/base/ndarray/czero-to' ); @@ -38,6 +39,7 @@ import dnansumkbn2 = require( '@stdlib/blas/ext/base/ndarray/dnansumkbn2' ); import dnansumors = require( '@stdlib/blas/ext/base/ndarray/dnansumors' ); import dnansumpw = require( '@stdlib/blas/ext/base/ndarray/dnansumpw' ); import doneTo = require( '@stdlib/blas/ext/base/ndarray/done-to' ); +import dsort = require( '@stdlib/blas/ext/base/ndarray/dsort' ); import dsorthp = require( '@stdlib/blas/ext/base/ndarray/dsorthp' ); import dsortins = require( '@stdlib/blas/ext/base/ndarray/dsortins' ); import dsortsh = require( '@stdlib/blas/ext/base/ndarray/dsortsh' ); @@ -88,6 +90,7 @@ import snansumkbn2 = require( '@stdlib/blas/ext/base/ndarray/snansumkbn2' ); import snansumors = require( '@stdlib/blas/ext/base/ndarray/snansumors' ); import snansumpw = require( '@stdlib/blas/ext/base/ndarray/snansumpw' ); import soneTo = require( '@stdlib/blas/ext/base/ndarray/sone-to' ); +import ssort = require( '@stdlib/blas/ext/base/ndarray/ssort' ); import ssorthp = require( '@stdlib/blas/ext/base/ndarray/ssorthp' ); import ssum = require( '@stdlib/blas/ext/base/ndarray/ssum' ); import ssumkbn = require( '@stdlib/blas/ext/base/ndarray/ssumkbn' ); @@ -95,6 +98,7 @@ import ssumkbn2 = require( '@stdlib/blas/ext/base/ndarray/ssumkbn2' ); import ssumors = require( '@stdlib/blas/ext/base/ndarray/ssumors' ); import ssumpw = require( '@stdlib/blas/ext/base/ndarray/ssumpw' ); import szeroTo = require( '@stdlib/blas/ext/base/ndarray/szero-to' ); +import zoneTo = require( '@stdlib/blas/ext/base/ndarray/zone-to' ); import zsum = require( '@stdlib/blas/ext/base/ndarray/zsum' ); import zsumkbn = require( '@stdlib/blas/ext/base/ndarray/zsumkbn' ); import zzeroTo = require( '@stdlib/blas/ext/base/ndarray/zzero-to' ); @@ -103,6 +107,24 @@ import zzeroTo = require( '@stdlib/blas/ext/base/ndarray/zzero-to' ); * Interface describing the `ndarray` namespace. */ interface Namespace { + /** + * Fills a one-dimensional single-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from one. + * + * @param arrays - array-like object containing a one-dimensional input ndarray + * @returns input ndarray + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * var ndarray = require( '@stdlib/ndarray/base/ctor' ); + * + * var xbuf = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * var x = new ndarray( 'complex64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); + * + * var out = ns.coneTo( [ x ] ); + * // returns [ [ 1.0, 0.0 ], [ 2.0, 0.0 ], [ 3.0, 0.0 ], [ 4.0, 0.0 ] ] + */ + coneTo: typeof coneTo; + /** * Computes the sum of all elements in a one-dimensional single-precision complex floating-point ndarray. * @@ -215,7 +237,6 @@ interface Namespace { * * @example * var Float64Array = require( '@stdlib/array/float64' ); - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); * var ndarray = require( '@stdlib/ndarray/base/ctor' ); * @@ -228,13 +249,10 @@ interface Namespace { * var initial = scalar2ndarray( 0.0, 'float64', 'row-major' ); * * var v = ns.dcusumkbn( [ x, y, initial ] ); - * // returns + * // returns [ 1.0, 4.0, 8.0, 10.0 ] * * var bool = ( v === y ); * // returns true - * - * var arr = ndarray2array( v ); - * // returns [ 1.0, 4.0, 8.0, 10.0 ] */ dcusumkbn: typeof dcusumkbn; @@ -522,6 +540,36 @@ interface Namespace { */ doneTo: typeof doneTo; + /** + * Sorts a one-dimensional double-precision floating-point ndarray. + * + * ## Notes + * + * - When the sort order is less than zero, the input ndarray is sorted in **decreasing** order. When the sort order is greater than zero, the input ndarray is sorted in **increasing** order. When the sort order is equal to zero, the input ndarray is left unchanged. + * + * @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying the sort order + * @returns input ndarray + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * var ndarray = require( '@stdlib/ndarray/base/ctor' ); + * + * var xbuf = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] ); + * var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); + * + * var ord = scalar2ndarray( 1.0, { + * 'dtype': 'generic' + * }); + * + * var out = ns.dsort( [ x, ord ] ); + * // returns [ -4.0, -2.0, 1.0, 3.0 ] + * + * var bool = ( out === x ); + * // returns true + */ + dsort: typeof dsort; + /** * Sorts a one-dimensional double-precision floating-point ndarray using heapsort. * @@ -1707,6 +1755,36 @@ interface Namespace { */ soneTo: typeof soneTo; + /** + * Sorts a one-dimensional single-precision floating-point ndarray. + * + * ## Notes + * + * - When the sort order is less than zero, the input ndarray is sorted in **decreasing** order. When the sort order is greater than zero, the input ndarray is sorted in **increasing** order. When the sort order is equal to zero, the input ndarray is left unchanged. + * + * @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying the sort order + * @returns input ndarray + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * var ndarray = require( '@stdlib/ndarray/base/ctor' ); + * + * var xbuf = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); + * var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); + * + * var ord = scalar2ndarray( 1.0, { + * 'dtype': 'generic' + * }); + * + * var out = ns.ssort( [ x, ord ] ); + * // returns [ -4.0, -2.0, 1.0, 3.0 ] + * + * var bool = ( out === x ); + * // returns true + */ + ssort: typeof ssort; + /** * Sorts a one-dimensional single-precision floating-point ndarray using heapsort. * @@ -1847,6 +1925,24 @@ interface Namespace { */ szeroTo: typeof szeroTo; + /** + * Fills a one-dimensional double-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from one. + * + * @param arrays - array-like object containing a one-dimensional input ndarray + * @returns input ndarray + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var ndarray = require( '@stdlib/ndarray/base/ctor' ); + * + * var xbuf = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * var x = new ndarray( 'complex128', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); + * + * var out = ns.zoneTo( [ x ] ); + * // returns [ [ 1.0, 0.0 ], [ 2.0, 0.0 ], [ 3.0, 0.0 ], [ 4.0, 0.0 ] ] + */ + zoneTo: typeof zoneTo; + /** * Computes the sum of all elements in a one-dimensional double-precision complex floating-point ndarray. * diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/README.md new file mode 100644 index 000000000000..666ebe5cd5f5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/README.md @@ -0,0 +1,129 @@ + + +# dsort + +> Sort a one-dimensional double-precision floating-point ndarray. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dsort = require( '@stdlib/blas/ext/base/ndarray/dsort' ); +``` + +#### dsort( arrays ) + +Sorts a one-dimensional double-precision floating-point ndarray. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); + +var xbuf = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] ); +var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); + +var order = scalar2ndarray( 1.0, { + 'dtype': 'generic' +}); + +var out = dsort( [ x, order ] ); +// returns [ -4.0, -2.0, 1.0, 3.0 ] + +var bool = ( out === x ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying the sort order. + +
+ + + +
+ +## Notes + +- The input ndarray is sorted **in-place** (i.e., the input ndarray is **mutated**). +- When the sort order is less than zero, the input ndarray is sorted in **decreasing** order. When the sort order is greater than zero, the input ndarray is sorted in **increasing** order. When the sort order is equal to zero, the input ndarray is left unchanged. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dsort = require( '@stdlib/blas/ext/base/ndarray/dsort' ); + +var x = uniform( [ 10 ], -100, 100 ); +console.log( ndarray2array( x ) ); + +var order = scalar2ndarray( 1.0, { + 'dtype': 'generic' +}); + +dsort( [ x, order ] ); +console.log( ndarray2array( x ) ); + +order = scalar2ndarray( -1.0, { + 'dtype': 'generic' +}); + +dsort( [ x, order ] ); +console.log( ndarray2array( x ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/benchmark/benchmark.js new file mode 100644 index 000000000000..f063d20eca13 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/benchmark/benchmark.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var pkg = require( './../package.json' ).name; +var dsort = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var order; + var xbuf; + var x; + + xbuf = uniform( len, 0.0, 100.0, options ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + order = scalar2ndarray( -1.0, options ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dsort( [ x, order ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( xbuf[ i%len ] !== xbuf[ i%len ] ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/docs/repl.txt new file mode 100644 index 000000000000..0d75b137eb07 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/docs/repl.txt @@ -0,0 +1,38 @@ + +{{alias}}( arrays ) + Sorts a one-dimensional double-precision floating-point ndarray. + + When the sort order is less than zero, the input ndarray is sorted in + decreasing order. When the sort order is greater than zero, the input + ndarray is sorted in increasing order. When the sort order is equal to zero, + the input ndarray is left unchanged. + + The input ndarray is sorted *in-place* (i.e., the input ndarray is + *mutated*). + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing a one-dimensional input ndarray and a + zero-dimensional ndarray specifying the sort order. + + Returns + ------- + out: ndarray + Input ndarray. + + Examples + -------- + > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0 ] ); + > var dt = 'float64'; + > var sh = [ xbuf.length ]; + > var sx = [ 1 ]; + > var ox = 0; + > var ord = 'row-major'; + > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord ); + > var o = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, { 'dtype': dt } ); + > {{alias}}( [ x, o ] ) + [ -4.0, -2.0, 1.0, 3.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/docs/types/index.d.ts new file mode 100644 index 000000000000..5bb0431baba9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/docs/types/index.d.ts @@ -0,0 +1,58 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray, float64ndarray } from '@stdlib/types/ndarray'; + +/** +* Sorts a one-dimensional double-precision floating-point ndarray. +* +* ## Notes +* +* - When the sort order is less than zero, the input ndarray is sorted in **decreasing** order. When the sort order is greater than zero, the input ndarray is sorted in **increasing** order. When the sort order is equal to zero, the input ndarray is left unchanged. +* +* @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying the sort order +* @returns input ndarray +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] ); +* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var ord = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var out = dsort( [ x, ord ] ); +* // returns [ -4.0, -2.0, 1.0, 3.0 ] +* +* var bool = ( out === x ); +* // returns true +*/ +declare function dsort( arrays: [ float64ndarray, typedndarray ] ): float64ndarray; + + +// EXPORTS // + +export = dsort; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/docs/types/test.ts new file mode 100644 index 000000000000..bd8703b93445 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/docs/types/test.ts @@ -0,0 +1,64 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +import dsort = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const order = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + + dsort( [ x, order ] ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dsort( '10' ); // $ExpectError + dsort( 10 ); // $ExpectError + dsort( true ); // $ExpectError + dsort( false ); // $ExpectError + dsort( null ); // $ExpectError + dsort( undefined ); // $ExpectError + dsort( [] ); // $ExpectError + dsort( {} ); // $ExpectError + dsort( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const order = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + + dsort(); // $ExpectError + dsort( [ x, order ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/examples/index.js new file mode 100644 index 000000000000..77c560f4f41d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/examples/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var dsort = require( './../lib' ); + +var x = uniform( [ 10 ], -100, 100 ); +console.log( ndarray2array( x ) ); + +var order = scalar2ndarray( 1.0, { + 'dtype': 'generic' +}); +console.log( 'Order:', ndarraylike2scalar( order ) ); + +dsort( [ x, order ] ); +console.log( ndarray2array( x ) ); + +order = scalar2ndarray( -1.0, { + 'dtype': 'generic' +}); +console.log( 'Order:', ndarraylike2scalar( order ) ); + +dsort( [ x, order ] ); +console.log( ndarray2array( x ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/lib/index.js new file mode 100644 index 000000000000..2c58717157f8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/lib/index.js @@ -0,0 +1,50 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Sort a one-dimensional double-precision floating-point ndarray. +* +* @module @stdlib/blas/ext/base/ndarray/dsort +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var dsort = require( '@stdlib/blas/ext/base/ndarray/dsort' ); +* +* var xbuf = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] ); +* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var order = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var out = dsort( [ x, order ] ); +* // returns [ -4.0, -2.0, 1.0, 3.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/lib/main.js new file mode 100644 index 000000000000..4ccdce95ec0e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/lib/main.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/dsort' ).ndarray; + + +// MAIN // + +/** +* Sorts a one-dimensional double-precision floating-point ndarray. +* +* ## Notes +* +* - When the sort order is less than zero, the input ndarray is sorted in **decreasing** order. When the sort order is greater than zero, the input ndarray is sorted in **increasing** order. When the sort order is equal to zero, the input ndarray is left unchanged. +* +* @param {ArrayLikeObject} arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying the sort order +* @returns {ndarray} input ndarray +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] ); +* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var order = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var out = dsort( [ x, order ] ); +* // returns [ -4.0, -2.0, 1.0, 3.0 ] +*/ +function dsort( arrays ) { + var order; + var x; + + x = arrays[ 0 ]; + order = arrays[ 1 ]; + strided( numelDimension( x, 0 ), ndarraylike2scalar( order ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len + return x; +} + + +// EXPORTS // + +module.exports = dsort; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/package.json new file mode 100644 index 000000000000..fc221520a8d8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/package.json @@ -0,0 +1,66 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/dsort", + "version": "0.0.0", + "description": "Sort a one-dimensional double-precision floating-point ndarray.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "sort", + "order", + "arrange", + "strided", + "array", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/test/test.js new file mode 100644 index 000000000000..bc9122edd1d5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsort/test/test.js @@ -0,0 +1,83 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var getDType = require( '@stdlib/ndarray/dtype' ); +var getStrides = require( '@stdlib/ndarray/strides' ); +var getOffset = require( '@stdlib/ndarray/offset' ); +var getShape = require( '@stdlib/ndarray/shape' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var dsort = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dsort, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function sorts a one-dimensional ndarray (increasing order)', function test( t ) { + var actual; + var order; + var x; + + x = ndarray( 'float64', new Float64Array( [ 3.0, 1.0, 2.0, 5.0, 4.0 ] ), [ 5 ], [ 1 ], 0, 'row-major' ); + order = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + + actual = dsort( [ x, order ] ); + t.strictEqual( actual, x, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getData( actual ), new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ), 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 5 ], 'returns expected value' ); + t.deepEqual( getStrides( actual ), [ 1 ], 'returns expected value' ); + t.strictEqual( getOffset( actual ), 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function sorts a one-dimensional ndarray (decreasing order)', function test( t ) { + var actual; + var order; + var x; + + x = ndarray( 'float64', new Float64Array( [ 3.0, 1.0, 2.0, 5.0, 4.0 ] ), [ 5 ], [ 1 ], 0, 'row-major' ); + order = scalar2ndarray( -1.0, { + 'dtype': 'generic' + }); + + actual = dsort( [ x, order ] ); + t.strictEqual( actual, x, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getData( actual ), new Float64Array( [ 5.0, 4.0, 3.0, 2.0, 1.0 ] ), 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 5 ], 'returns expected value' ); + t.deepEqual( getStrides( actual ), [ 1 ], 'returns expected value' ); + t.strictEqual( getOffset( actual ), 0, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsorthp/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsorthp/benchmark/benchmark.js index 4fc94f6b353d..24c261a40d44 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsorthp/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsorthp/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsorthp = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsorthp/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsorthp/docs/repl.txt index 29befd5ea51d..92df0d63f567 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsorthp/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsorthp/docs/repl.txt @@ -8,7 +8,7 @@ ndarray is sorted in increasing order. When the sort order is equal to zero, the input ndarray is left unchanged. - The input ndarray is sorted *in-place* (i.e., the input strided array is + The input ndarray is sorted *in-place* (i.e., the input ndarray is *mutated*). Parameters diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsorthp/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsorthp/test/test.js index 6622e4d90fb0..60c965a9c013 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsorthp/test/test.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsorthp/test/test.js @@ -24,7 +24,7 @@ var tape = require( 'tape' ); var Float64Array = require( '@stdlib/array/float64' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); var getData = require( '@stdlib/ndarray/data-buffer' ); -var getDtype = require( '@stdlib/ndarray/dtype' ); +var getDType = require( '@stdlib/ndarray/dtype' ); var getStrides = require( '@stdlib/ndarray/strides' ); var getOffset = require( '@stdlib/ndarray/offset' ); var getShape = require( '@stdlib/ndarray/shape' ); @@ -52,7 +52,7 @@ tape( 'the function sorts a one-dimensional ndarray (increasing order)', functio actual = dsorthp( [ x, order ] ); t.strictEqual( actual, x, 'returns expected value' ); - t.strictEqual( getDtype( actual ), 'float64', 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); t.deepEqual( getData( actual ), new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ), 'returns expected value' ); t.deepEqual( getShape( actual ), [ 5 ], 'returns expected value' ); t.deepEqual( getStrides( actual ), [ 1 ], 'returns expected value' ); @@ -73,7 +73,7 @@ tape( 'the function sorts a one-dimensional ndarray (decreasing order)', functio actual = dsorthp( [ x, order ] ); t.strictEqual( actual, x, 'returns expected value' ); - t.strictEqual( getDtype( actual ), 'float64', 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); t.deepEqual( getData( actual ), new Float64Array( [ 5.0, 4.0, 3.0, 2.0, 1.0 ] ), 'returns expected value' ); t.deepEqual( getShape( actual ), [ 5 ], 'returns expected value' ); t.deepEqual( getStrides( actual ), [ 1 ], 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsortins/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsortins/benchmark/benchmark.js index 88fb58926a2b..f9253b1b472a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsortins/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsortins/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortins = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsortins/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsortins/test/test.js index fd8c5ad41b05..186f658bc70a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsortins/test/test.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsortins/test/test.js @@ -24,7 +24,7 @@ var tape = require( 'tape' ); var Float64Array = require( '@stdlib/array/float64' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); var getData = require( '@stdlib/ndarray/data-buffer' ); -var getDtype = require( '@stdlib/ndarray/dtype' ); +var getDType = require( '@stdlib/ndarray/dtype' ); var getStrides = require( '@stdlib/ndarray/strides' ); var getOffset = require( '@stdlib/ndarray/offset' ); var getShape = require( '@stdlib/ndarray/shape' ); @@ -52,7 +52,7 @@ tape( 'the function sorts a one-dimensional ndarray (increasing order)', functio actual = dsortins( [ x, order ] ); t.strictEqual( actual, x, 'returns expected value' ); - t.strictEqual( getDtype( actual ), 'float64', 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); t.deepEqual( getData( actual ), new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ), 'returns expected value' ); t.deepEqual( getShape( actual ), [ 5 ], 'returns expected value' ); t.deepEqual( getStrides( actual ), [ 1 ], 'returns expected value' ); @@ -73,7 +73,7 @@ tape( 'the function sorts a one-dimensional ndarray (decreasing order)', functio actual = dsortins( [ x, order ] ); t.strictEqual( actual, x, 'returns expected value' ); - t.strictEqual( getDtype( actual ), 'float64', 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); t.deepEqual( getData( actual ), new Float64Array( [ 5.0, 4.0, 3.0, 2.0, 1.0 ] ), 'returns expected value' ); t.deepEqual( getShape( actual ), [ 5 ], 'returns expected value' ); t.deepEqual( getStrides( actual ), [ 1 ], 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsortsh/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsortsh/benchmark/benchmark.js index 957646a242af..12b72ce9e1b4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsortsh/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsortsh/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsortsh = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsortsh/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsortsh/test/test.js index 0e28458893d9..b81410dcda9c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsortsh/test/test.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsortsh/test/test.js @@ -24,7 +24,7 @@ var tape = require( 'tape' ); var Float64Array = require( '@stdlib/array/float64' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); var getData = require( '@stdlib/ndarray/data-buffer' ); -var getDtype = require( '@stdlib/ndarray/dtype' ); +var getDType = require( '@stdlib/ndarray/dtype' ); var getStrides = require( '@stdlib/ndarray/strides' ); var getOffset = require( '@stdlib/ndarray/offset' ); var getShape = require( '@stdlib/ndarray/shape' ); @@ -52,7 +52,7 @@ tape( 'the function sorts a one-dimensional ndarray (increasing order)', functio actual = dsortsh( [ x, order ] ); t.strictEqual( actual, x, 'returns expected value' ); - t.strictEqual( getDtype( actual ), 'float64', 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); t.deepEqual( getData( actual ), new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ), 'returns expected value' ); t.deepEqual( getShape( actual ), [ 5 ], 'returns expected value' ); t.deepEqual( getStrides( actual ), [ 1 ], 'returns expected value' ); @@ -73,7 +73,7 @@ tape( 'the function sorts a one-dimensional ndarray (decreasing order)', functio actual = dsortsh( [ x, order ] ); t.strictEqual( actual, x, 'returns expected value' ); - t.strictEqual( getDtype( actual ), 'float64', 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); t.deepEqual( getData( actual ), new Float64Array( [ 5.0, 4.0, 3.0, 2.0, 1.0 ] ), 'returns expected value' ); t.deepEqual( getShape( actual ), [ 5 ], 'returns expected value' ); t.deepEqual( getStrides( actual ), [ 1 ], 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsumkbn/benchmark/benchmark.js index 5447ea66da16..1147183a553f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsumkbn/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsumkbn = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsumkbn2/benchmark/benchmark.js index 4b0c4ac2648e..371fb31fbe4f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsumkbn2/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsumkbn2 = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg + ':len=' + len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsumors/benchmark/benchmark.js index 094f27971a3a..f149e3d918fa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsumors/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsumors = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsumpw/benchmark/benchmark.js index e133aa5ecbce..dced63b76dc1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dsumpw/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsumpw = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusum/benchmark/benchmark.js index 557e7ddd43f2..81e96bdf16db 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusum/benchmark/benchmark.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gcusum = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusumkbn/benchmark/benchmark.js index b549dddce728..9d27f1074c75 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusumkbn/benchmark/benchmark.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gcusumkbn = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusumkbn2/benchmark/benchmark.js index aecaba08466f..dc4b9e1171ac 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusumkbn2/benchmark/benchmark.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gcusumkbn2 = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusumors/benchmark/benchmark.js index 4c84fe330186..86cc7b894d5e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusumors/benchmark/benchmark.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gcusumors = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusumpw/benchmark/benchmark.js index 8b9b3c3e5ca2..12ae49d85914 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gcusumpw/benchmark/benchmark.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gcusumpw = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfind-index/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfind-index/benchmark/benchmark.js index a4b4a5126c1f..82751b7e89ae 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfind-index/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfind-index/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gfindIndex = require( './../lib' ); @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfind-last-index/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfind-last-index/benchmark/benchmark.js index 587ff2c8aa2c..d3c0354f998e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfind-last-index/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfind-last-index/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gfindLastIndex = require( './../lib' ); @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of/benchmark/benchmark.js index 3796f6d42609..3e5f290b5901 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gindexOf = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gjoin/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gjoin/benchmark/benchmark.js index 23cec6526a07..4a7704741b3a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gjoin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gjoin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gjoin = require( './../lib' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/glast-index-of/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/glast-index-of/benchmark/benchmark.js index 2e9b183c5038..a89d7ae43570 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/glast-index-of/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/glast-index-of/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var glastIndexOf = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/glinspace/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/glinspace/benchmark/benchmark.js index 3aecfb5e1725..92907c732222 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/glinspace/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/glinspace/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var glinspace = require( './../lib' ); @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansum/benchmark/benchmark.js index bdb1e81c9706..fc21300992cc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansum/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnansum = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumkbn/benchmark/benchmark.js index 3dbd4d8189e8..414f80950992 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumkbn/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnansumkbn = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumkbn2/benchmark/benchmark.js index f85e50932530..1d5035054074 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumkbn2/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnansumkbn2 = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumors/benchmark/benchmark.js index a3bc9e251473..6db11a44d63d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumors/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnansumors = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumpw/benchmark/benchmark.js index d8cbd4ab7460..1166ade12eca 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumpw/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gnansumpw = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsort/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsort/docs/repl.txt index 7a7d99fb77d6..20251329b4ee 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsort/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsort/docs/repl.txt @@ -7,7 +7,8 @@ ndarray is sorted in increasing order. When the sort order is equal to zero, the input ndarray is left unchanged. - The input ndarray is sorted in-place (i.e., the input ndarray is mutated). + The input ndarray is sorted *in-place* (i.e., the input ndarray is + *mutated*). Parameters ---------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsorthp/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsorthp/benchmark/benchmark.js index baa044a177cf..a40aeb043d67 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsorthp/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsorthp/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsorthp = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsorthp/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsorthp/docs/repl.txt index bde7c87f4334..59dddd938673 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsorthp/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsorthp/docs/repl.txt @@ -7,7 +7,8 @@ ndarray is sorted in increasing order. When the sort order is equal to zero, the input ndarray is left unchanged. - The input ndarray is sorted in-place (i.e., the input ndarray is mutated). + The input ndarray is sorted *in-place* (i.e., the input ndarray is + *mutated*). Parameters ---------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsum/benchmark/benchmark.js index 9b4bc798b8d8..c30aecead9bd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsum/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsum = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsumkbn2/benchmark/benchmark.js index a12c1b83e611..316be17a8822 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsumkbn2/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsumkbn2 = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg + ':len=' + len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsumors/benchmark/benchmark.js index 657af17d0692..3d51008574e6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsumors/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsumors = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsumpw/benchmark/benchmark.js index f5681f91471d..7963f0902528 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gsumpw/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gsumpw = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/lib/index.js index 0b2bd6c980fc..b927f28f8d15 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/lib/index.js @@ -36,6 +36,15 @@ var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); */ var ns = {}; +/** +* @name coneTo +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/cone-to} +*/ +setReadOnly( ns, 'coneTo', require( '@stdlib/blas/ext/base/ndarray/cone-to' ) ); + /** * @name csum * @memberof ns @@ -198,6 +207,15 @@ setReadOnly( ns, 'dnansumpw', require( '@stdlib/blas/ext/base/ndarray/dnansumpw' */ setReadOnly( ns, 'doneTo', require( '@stdlib/blas/ext/base/ndarray/done-to' ) ); +/** +* @name dsort +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/dsort} +*/ +setReadOnly( ns, 'dsort', require( '@stdlib/blas/ext/base/ndarray/dsort' ) ); + /** * @name dsorthp * @memberof ns @@ -648,6 +666,15 @@ setReadOnly( ns, 'snansumpw', require( '@stdlib/blas/ext/base/ndarray/snansumpw' */ setReadOnly( ns, 'soneTo', require( '@stdlib/blas/ext/base/ndarray/sone-to' ) ); +/** +* @name ssort +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/ssort} +*/ +setReadOnly( ns, 'ssort', require( '@stdlib/blas/ext/base/ndarray/ssort' ) ); + /** * @name ssorthp * @memberof ns @@ -711,6 +738,15 @@ setReadOnly( ns, 'ssumpw', require( '@stdlib/blas/ext/base/ndarray/ssumpw' ) ); */ setReadOnly( ns, 'szeroTo', require( '@stdlib/blas/ext/base/ndarray/szero-to' ) ); +/** +* @name zoneTo +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/zone-to} +*/ +setReadOnly( ns, 'zoneTo', require( '@stdlib/blas/ext/base/ndarray/zone-to' ) ); + /** * @name zsum * @memberof ns diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/scusum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/scusum/benchmark/benchmark.js index cf980516f746..1ad7c8b74119 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/scusum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/scusum/benchmark/benchmark.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scusum = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/scusumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/scusumkbn/benchmark/benchmark.js index 745dd870dbd3..6473f2e136c5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/scusumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/scusumkbn/benchmark/benchmark.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scusumkbn = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg + ':len=' + len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/scusumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/scusumkbn2/benchmark/benchmark.js index 98e4c3d20461..838f77c1b360 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/scusumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/scusumkbn2/benchmark/benchmark.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scusumkbn2 = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg + ':len=' + len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/scusumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/scusumors/benchmark/benchmark.js index 2ea848cdcee2..694039ebe692 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/scusumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/scusumors/benchmark/benchmark.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scusumors = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sindex-of/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sindex-of/benchmark/benchmark.js index c35a6acd9b79..62955efd844e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sindex-of/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sindex-of/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sindexOf = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/slast-index-of/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/slast-index-of/benchmark/benchmark.js index e26a2ff5cacc..c1662021dc18 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/slast-index-of/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/slast-index-of/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var slastIndexOf = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/slinspace/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/slinspace/benchmark/benchmark.js index 32963dd283a6..621eda243e04 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/slinspace/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/slinspace/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var slinspace = require( './../lib' ); @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/README.md index 4d4f6301b5b1..30feedfe4be4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/README.md @@ -102,6 +102,153 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/ndarray/snansum.h" +``` + +#### stdlib_blas_ext_snansum( arrays ) + +Computes the sum of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values. + +```c +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include + +// Create an ndarray: +const float data[] = { 1.0f, 0.0f/0.0f, 3.0f, 4.0f }; +int64_t shape[] = { 4 }; +int64_t strides[] = { STDLIB_NDARRAY_FLOAT32_BYTES_PER_ELEMENT }; +int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + +struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)data, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes ); + +// Compute the sum: +const struct ndarray *arrays[] = { x }; +float v = stdlib_blas_ext_snansum( arrays ); +// returns 8.0f + +// Free allocated memory: +stdlib_ndarray_free( x ); +``` + +The function accepts the following arguments: + +- **arrays**: `[in] struct ndarray**` list containing a one-dimensional input ndarray. + +```c +float stdlib_blas_ext_snansum( const struct ndarray *arrays[] ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/ndarray/snansum.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include + +int main( void ) { + // Create a data buffer: + const float data[] = { 1.0f, -2.0f, 0.0f/0.0f, -4.0f, 5.0f, -6.0f, 0.0f/0.0f, -8.0f }; + + // Specify the number of array dimensions: + const int64_t ndims = 1; + + // Specify the array shape: + int64_t shape[] = { 4 }; + + // Specify the array strides: + int64_t strides[] = { 2*STDLIB_NDARRAY_FLOAT32_BYTES_PER_ELEMENT }; + + // Specify the byte offset: + const int64_t offset = 0; + + // Specify the array order: + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const int64_t nsubmodes = 1; + + // Create an ndarray: + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x }; + + // Compute the sum: + float v = stdlib_blas_ext_snansum( arrays ); + + // Print the result: + printf( "sum: %f\n", v ); + + // Free allocated memory: + stdlib_ndarray_free( x ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/benchmark/benchmark.js index e1e4a299e07d..93c5bc202132 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/benchmark/benchmark.js @@ -27,8 +27,9 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; -var snansum = require( './../lib' ); +var snansum = require( './../lib/main.js' ); // VARIABLES // @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/benchmark/benchmark.native.js new file mode 100644 index 000000000000..30a4ea473db1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/benchmark/benchmark.native.js @@ -0,0 +1,129 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var snansum = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( snansum instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.7 ) > 0 ) { + return discreteUniform( -10.0, 10.0 ); + } + return NaN; +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var x; + + xbuf = filledarrayBy( len, options.dtype, rand ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = snansum( [ x ] ); + if ( isnanf( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..45dc4957c206 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/benchmark/c/benchmark.length.c @@ -0,0 +1,189 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ndarray/snansum.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include +#include +#include +#include + +#define NAME "snansum" +#define ITERATIONS 1000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static float rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark( int iterations, int len ) { + enum STDLIB_NDARRAY_INDEX_MODE imode; + const struct ndarray *arrays[ 1 ]; + enum STDLIB_NDARRAY_ORDER order; + int8_t submodes[ 1 ]; + int64_t strides[ 1 ]; + int64_t shape[ 1 ]; + int64_t nsubmodes; + struct ndarray *x; + int64_t offset; + double elapsed; + int64_t ndims; + float *data; + float v; + double t; + int i; + + ndims = 1; + shape[ 0 ] = len; + strides[ 0 ] = STDLIB_NDARRAY_FLOAT32_BYTES_PER_ELEMENT; + offset = 0; + order = STDLIB_NDARRAY_ROW_MAJOR; + imode = STDLIB_NDARRAY_INDEX_ERROR; + submodes[ 0 ] = imode; + nsubmodes = 1; + + data = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + if ( rand_float() < 0.2f ) { + data[ i ] = 0.0f / 0.0f; // NaN + } else { + data[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + } + // cppcheck-suppress invalidPointerCast + x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + arrays[ 0 ] = x; + + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + v = stdlib_blas_ext_snansum( arrays ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + stdlib_ndarray_free( x ); + free( data ); + arrays[ 0 ] = NULL; + + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/examples/c/example.c new file mode 100644 index 000000000000..7a1dc23ace21 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/examples/c/example.c @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ndarray/snansum.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include + +int main( void ) { + // Create a data buffer: + const float data[] = { 1.0f, -2.0f, 0.0f/0.0f, -4.0f, 5.0f, -6.0f, 0.0f/0.0f, -8.0f }; + + // Specify the number of array dimensions: + const int64_t ndims = 1; + + // Specify the array shape: + int64_t shape[] = { 4 }; + + // Specify the array strides: + int64_t strides[] = { 2*STDLIB_NDARRAY_FLOAT32_BYTES_PER_ELEMENT }; + + // Specify the byte offset: + const int64_t offset = 0; + + // Specify the array order: + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const int64_t nsubmodes = 1; + + // Create an ndarray: + // cppcheck-suppress invalidPointerCast + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x }; + + // Compute the sum: + float v = stdlib_blas_ext_snansum( arrays ); + + // Print the result: + printf( "sum: %f\n", v ); + + // Free allocated memory: + stdlib_ndarray_free( x ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '} arrays - array-like object containing an input ndarray +* @returns {number} sum +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] ); +* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var v = snansum( [ x ] ); +* // returns 1.0 +*/ +function snansum( arrays ) { + var x = arrays[ 0 ]; + return addon( getData( x ), serialize( x ) ); +} + + +// EXPORTS // + +module.exports = snansum; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/manifest.json new file mode 100644 index 000000000000..f27f2ebca6bd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/manifest.json @@ -0,0 +1,110 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/snansum", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/base/napi/addon-arguments", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/snansum", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/dtypes", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders", + "@stdlib/ndarray/base/bytes-per-element" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/snansum", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/dtypes", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders", + "@stdlib/ndarray/base/bytes-per-element" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/snansum", + "@stdlib/ndarray/ctor" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/package.json index 2d939a2b6131..a008530fd94d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/package.json @@ -14,11 +14,15 @@ } ], "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/src/addon.c new file mode 100644 index 000000000000..575e47dd18bf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/src/addon.c @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ndarray/snansum.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/base/napi/addon_arguments.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/create_double.h" +#include +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 2 ); + + // Process provided arguments: + struct ndarray *arrays[ 1 ]; + napi_value err; + napi_status status = stdlib_ndarray_napi_addon_arguments( env, argv, 2, 1, arrays, &err ); + assert( status == napi_ok ); + if ( err != NULL ) { + status = napi_throw( env, err ); + assert( status == napi_ok ); + return NULL; + } + // Perform computation: + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_blas_ext_snansum( arrays ), v ); + + // Free allocated memory: + stdlib_ndarray_free( arrays[ 0 ] ); + arrays[ 0 ] = NULL; + + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/src/main.c new file mode 100644 index 000000000000..bfb4604d8380 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/src/main.c @@ -0,0 +1,33 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ndarray/snansum.h" +#include "stdlib/blas/ext/base/snansum.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/blas/base/shared.h" + +/** +* Computes the sum of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values. +* +* @param arrays list containing an input ndarray +* @return sum +*/ +float stdlib_blas_ext_snansum( const struct ndarray *arrays[] ) { + const struct ndarray *x = arrays[ 0 ]; + return API_SUFFIX(stdlib_strided_snansum_ndarray)( stdlib_ndarray_dimension( x, 0 ), (const float *)stdlib_ndarray_data( x ), stdlib_ndarray_stride_elements( x, 0 ), stdlib_ndarray_offset_elements( x ) ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/test/test.js index e208b2f23c12..28281153e98c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/test/test.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/test/test.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2025 The Stdlib Authors. +* Copyright (c) 2026 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -21,27 +21,16 @@ // MODULES // var tape = require( 'tape' ); -var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); -var Float32Array = require( '@stdlib/array/float32' ); -var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); var snansum = require( './../lib' ); -// FUNCTIONS // +// VARIABLES // -/** -* Returns a one-dimensional ndarray. -* -* @private -* @param {Float32Array} buffer - underlying data buffer -* @param {NonNegativeInteger} length - number of indexed elements -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - index offset -* @returns {ndarray} one-dimensional ndarray -*/ -function vector( buffer, length, stride, offset ) { - return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); -} +var opts = { + 'skip': IS_BROWSER +}; // TESTS // @@ -52,144 +41,37 @@ tape( 'main export is a function', function test( t ) { t.end(); }); -tape( 'the function has an arity of 1', function test( t ) { - t.strictEqual( snansum.length, 1, 'has expected arity' ); - t.end(); -}); - -tape( 'the function computes the sum of a one-dimensional ndarray, ignoring `NaN` values', function test( t ) { - var x; - var v; - - x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0, 0.0, -3.0, 3.0 ] ); - v = snansum( [ vector( x, 10, 1, 0 ) ] ); - t.strictEqual( v, 3.0, 'returns expected value' ); - - x = new Float32Array( [ 1.0, -2.0, -4.0, NaN, 5.0, 0.0, 3.0 ] ); - v = snansum( [ vector( x, 7, 1, 0 ) ] ); - t.strictEqual( v, 3.0, 'returns expected value' ); - - x = new Float32Array( [ -4.0, -5.0 ] ); - v = snansum( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( v, -9.0, 'returns expected value' ); - - x = new Float32Array( [ NaN, 4.0 ] ); - v = snansum( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( v, 4.0, 'returns expected value' ); - - x = new Float32Array( [ NaN, NaN ] ); - v = snansum( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( v, 0.0, 'returns expected value' ); - - x = new Float32Array( [ NaN ] ); - v = snansum( [ vector( x, 1, 1, 0 ) ] ); - t.strictEqual( v, 0.0, 'returns expected value' ); - - x = new Float32Array( [ 4.0 ] ); - v = snansum( [ vector( x, 1, 1, 0 ) ] ); - t.strictEqual( v, 4.0, 'returns expected value' ); - - x = new Float32Array( [ 1.0, 1.0e38, 1.0, -1.0e38 ] ); - v = snansum( [ vector( x, 4, 1, 0 ) ] ); - t.strictEqual( v, 2.0, 'returns expected value' ); +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var snansum = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + t.strictEqual( snansum, mock, 'returns expected value' ); t.end(); -}); -tape( 'if provided an empty ndarray, the function returns `0.0`', function test( t ) { - var x; - var v; + function tryRequire() { + return mock; + } - x = new Float32Array( [] ); - - v = snansum( [ vector( x, 0, 1, 0 ) ] ); - t.strictEqual( isPositiveZerof( v ), true, 'returns expected value' ); - - t.end(); + function mock() { + // Mock... + } }); -tape( 'if provided a vector containing a single element, the function returns that element', function test( t ) { - var x; - var v; - - x = new Float32Array( [ 1.0 ] ); - - v = snansum( [ vector( x, 1, 1, 0 ) ] ); - t.strictEqual( v, 1.0, 'returns expected value' ); - - x = new Float32Array( [ NaN ] ); - - v = snansum( [ vector( x, 1, 1, 0 ) ] ); - t.strictEqual( v, 0.0, 'returns expected value' ); +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var snansum; + var main; - t.end(); -}); + main = require( './../lib/main.js' ); -tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { - var x; - var v; - - x = new Float32Array([ - 1.0, // 0 - 2.0, - 2.0, // 1 - -7.0, - -2.0, // 2 - 3.0, - 4.0, // 3 - 2.0, - NaN, // 4 - NaN - ]); - - v = snansum( [ vector( x, 5, 2, 0 ) ] ); - - t.strictEqual( v, 5.0, 'returns expected value' ); - t.end(); -}); + snansum = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); -tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { - var x; - var v; - - x = new Float32Array([ - NaN, // 4 - NaN, - 1.0, // 3 - 2.0, - 2.0, // 2 - -7.0, - -2.0, // 1 - 3.0, - 4.0, // 0 - 2.0 - ]); - - v = snansum( [ vector( x, 5, -2, 8 ) ] ); - - t.strictEqual( v, 5.0, 'returns expected value' ); + t.strictEqual( snansum, main, 'returns expected value' ); t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { - var x; - var v; - - x = new Float32Array([ - 2.0, - 1.0, // 0 - 2.0, - -2.0, // 1 - -2.0, - 2.0, // 2 - 3.0, - 4.0, // 3 - NaN, - NaN // 4 - ]); - - v = snansum( [ vector( x, 5, 2, 1 ) ] ); - t.strictEqual( v, 5.0, 'returns expected value' ); - t.end(); + function tryRequire() { + return new Error( 'Cannot find module' ); + } }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/test/test.main.js new file mode 100644 index 000000000000..d692dace3400 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/test/test.main.js @@ -0,0 +1,195 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); +var Float32Array = require( '@stdlib/array/float32' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var snansum = require( './../lib/main.js' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float32Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof snansum, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( snansum.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function computes the sum of a one-dimensional ndarray, ignoring `NaN` values', function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0, 0.0, -3.0, 3.0 ] ); + v = snansum( [ vector( x, 10, 1, 0 ) ] ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + x = new Float32Array( [ 1.0, -2.0, -4.0, NaN, 5.0, 0.0, 3.0 ] ); + v = snansum( [ vector( x, 7, 1, 0 ) ] ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + x = new Float32Array( [ -4.0, -5.0 ] ); + v = snansum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, -9.0, 'returns expected value' ); + + x = new Float32Array( [ NaN, 4.0 ] ); + v = snansum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, 4.0, 'returns expected value' ); + + x = new Float32Array( [ NaN, NaN ] ); + v = snansum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float32Array( [ NaN ] ); + v = snansum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float32Array( [ 4.0 ] ); + v = snansum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 4.0, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0e38, 1.0, -1.0e38 ] ); + v = snansum( [ vector( x, 4, 1, 0 ) ] ); + t.strictEqual( v, 2.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `0.0`', function test( t ) { + var x; + var v; + + x = new Float32Array( [] ); + + v = snansum( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( isPositiveZerof( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a vector containing a single element, the function returns that element', function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0 ] ); + + v = snansum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + x = new Float32Array( [ NaN ] ); + + v = snansum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var x; + var v; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]); + + v = snansum( [ vector( x, 5, 2, 0 ) ] ); + + t.strictEqual( v, 5.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var x; + var v; + + x = new Float32Array([ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = snansum( [ vector( x, 5, -2, 8 ) ] ); + + t.strictEqual( v, 5.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var x; + var v; + + x = new Float32Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + NaN, + NaN // 4 + ]); + + v = snansum( [ vector( x, 5, 2, 1 ) ] ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/test/test.native.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/test/test.native.js new file mode 100644 index 000000000000..a8213ecca3fc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/test/test.native.js @@ -0,0 +1,204 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); +var Float32Array = require( '@stdlib/array/float32' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var snansum = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( snansum instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float32Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof snansum, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', opts, function test( t ) { + t.strictEqual( snansum.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function computes the sum of a one-dimensional ndarray, ignoring `NaN` values', opts, function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0, 0.0, -3.0, 3.0 ] ); + v = snansum( [ vector( x, 10, 1, 0 ) ] ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + x = new Float32Array( [ 1.0, -2.0, -4.0, NaN, 5.0, 0.0, 3.0 ] ); + v = snansum( [ vector( x, 7, 1, 0 ) ] ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + x = new Float32Array( [ -4.0, -5.0 ] ); + v = snansum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, -9.0, 'returns expected value' ); + + x = new Float32Array( [ NaN, 4.0 ] ); + v = snansum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, 4.0, 'returns expected value' ); + + x = new Float32Array( [ NaN, NaN ] ); + v = snansum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float32Array( [ NaN ] ); + v = snansum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float32Array( [ 4.0 ] ); + v = snansum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 4.0, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0e38, 1.0, -1.0e38 ] ); + v = snansum( [ vector( x, 4, 1, 0 ) ] ); + t.strictEqual( v, 2.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `0.0`', opts, function test( t ) { + var x; + var v; + + x = new Float32Array( [] ); + + v = snansum( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( isPositiveZerof( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an ndarray containing a single element, the function returns that element', opts, function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0 ] ); + + v = snansum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + x = new Float32Array( [ NaN ] ); + + v = snansum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', opts, function test( t ) { + var x; + var v; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]); + + v = snansum( [ vector( x, 5, 2, 0 ) ] ); + + t.strictEqual( v, 5.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', opts, function test( t ) { + var x; + var v; + + x = new Float32Array([ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = snansum( [ vector( x, 5, -2, 8 ) ] ); + + t.strictEqual( v, 5.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', opts, function test( t ) { + var x; + var v; + + x = new Float32Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + NaN, + NaN // 4 + ]); + + v = snansum( [ vector( x, 5, 2, 1 ) ] ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumkbn/benchmark/benchmark.js index 876bb103cf4c..95c5dcd635c0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumkbn/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snansumkbn = require( './../lib' ); @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumkbn2/benchmark/benchmark.js index 8022216e9963..70a50f8cac5f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumkbn2/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snansumkbn2 = require( './../lib' ); @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumors/benchmark/benchmark.js index 018c00792301..b5572850ce7c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumors/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snansumors = require( './../lib' ); @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumpw/benchmark/benchmark.js index 5f92eea02589..95c06430c4f2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumpw/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snansumpw = require( './../lib' ); @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/README.md new file mode 100644 index 000000000000..a9ad09ff1cca --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/README.md @@ -0,0 +1,131 @@ + + +# ssort + +> Sort a one-dimensional single-precision floating-point ndarray. + +
+ +
+ + + +
+ +## Usage + +```javascript +var ssort = require( '@stdlib/blas/ext/base/ndarray/ssort' ); +``` + +#### ssort( arrays ) + +Sorts a one-dimensional single-precision floating-point ndarray. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); + +var xbuf = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); +var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); + +var order = scalar2ndarray( 1.0, { + 'dtype': 'generic' +}); + +var out = ssort( [ x, order ] ); +// returns [ -4.0, -2.0, 1.0, 3.0 ] + +var bool = ( out === x ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying the sort order. + +
+ + + +
+ +## Notes + +- The input ndarray is sorted **in-place** (i.e., the input ndarray is **mutated**). +- When the sort order is less than zero, the input ndarray is sorted in **decreasing** order. When the sort order is greater than zero, the input ndarray is sorted in **increasing** order. When the sort order is equal to zero, the input ndarray is left unchanged. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ssort = require( '@stdlib/blas/ext/base/ndarray/ssort' ); + +var x = uniform( [ 10 ], -100, 100, { + 'dtype': 'float32' +}); +console.log( ndarray2array( x ) ); + +var order = scalar2ndarray( 1.0, { + 'dtype': 'generic' +}); + +ssort( [ x, order ] ); +console.log( ndarray2array( x ) ); + +order = scalar2ndarray( -1.0, { + 'dtype': 'generic' +}); + +ssort( [ x, order ] ); +console.log( ndarray2array( x ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/benchmark/benchmark.js new file mode 100644 index 000000000000..0c99b95fc52f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/benchmark/benchmark.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var pkg = require( './../package.json' ).name; +var ssort = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var order; + var xbuf; + var x; + + xbuf = uniform( len, 0.0, 100.0, options ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + order = scalar2ndarray( -1.0, options ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = ssort( [ x, order ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( xbuf[ i%len ] !== xbuf[ i%len ] ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/docs/repl.txt new file mode 100644 index 000000000000..15e1d23bcb7c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/docs/repl.txt @@ -0,0 +1,38 @@ + +{{alias}}( arrays ) + Sorts a one-dimensional single-precision floating-point ndarray. + + When the sort order is less than zero, the input ndarray is sorted in + decreasing order. When the sort order is greater than zero, the input + ndarray is sorted in increasing order. When the sort order is equal to zero, + the input ndarray is left unchanged. + + The input ndarray is sorted *in-place* (i.e., the input ndarray is + *mutated*). + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing a one-dimensional input ndarray and a + zero-dimensional ndarray specifying the sort order. + + Returns + ------- + out: ndarray + Input ndarray. + + Examples + -------- + > var xbuf = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, -4.0 ] ); + > var dt = 'float32'; + > var sh = [ xbuf.length ]; + > var sx = [ 1 ]; + > var ox = 0; + > var ord = 'row-major'; + > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord ); + > var o = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, { 'dtype': dt } ); + > {{alias}}( [ x, o ] ) + [ -4.0, -2.0, 1.0, 3.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/docs/types/index.d.ts new file mode 100644 index 000000000000..0f853d8d017d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/docs/types/index.d.ts @@ -0,0 +1,58 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray, float32ndarray } from '@stdlib/types/ndarray'; + +/** +* Sorts a one-dimensional single-precision floating-point ndarray. +* +* ## Notes +* +* - When the sort order is less than zero, the input ndarray is sorted in **decreasing** order. When the sort order is greater than zero, the input ndarray is sorted in **increasing** order. When the sort order is equal to zero, the input ndarray is left unchanged. +* +* @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying the sort order +* @returns input ndarray +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); +* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var ord = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var out = ssort( [ x, ord ] ); +* // returns [ -4.0, -2.0, 1.0, 3.0 ] +* +* var bool = ( out === x ); +* // returns true +*/ +declare function ssort( arrays: [ float32ndarray, typedndarray ] ): float32ndarray; + + +// EXPORTS // + +export = ssort; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/docs/types/test.ts new file mode 100644 index 000000000000..4997bbe6aae0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/docs/types/test.ts @@ -0,0 +1,64 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +import ssort = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float32' + }); + const order = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + + ssort( [ x, order ] ); // $ExpectType float32ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + ssort( '10' ); // $ExpectError + ssort( 10 ); // $ExpectError + ssort( true ); // $ExpectError + ssort( false ); // $ExpectError + ssort( null ); // $ExpectError + ssort( undefined ); // $ExpectError + ssort( [] ); // $ExpectError + ssort( {} ); // $ExpectError + ssort( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float32' + }); + const order = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + + ssort(); // $ExpectError + ssort( [ x, order ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/examples/index.js new file mode 100644 index 000000000000..a21c508e8ae7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/examples/index.js @@ -0,0 +1,46 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var ssort = require( './../lib' ); + +var x = uniform( [ 10 ], -100, 100, { + 'dtype': 'float32' +}); +console.log( ndarray2array( x ) ); + +var order = scalar2ndarray( 1.0, { + 'dtype': 'generic' +}); +console.log( 'Order:', ndarraylike2scalar( order ) ); + +ssort( [ x, order ] ); +console.log( ndarray2array( x ) ); + +order = scalar2ndarray( -1.0, { + 'dtype': 'generic' +}); +console.log( 'Order:', ndarraylike2scalar( order ) ); + +ssort( [ x, order ] ); +console.log( ndarray2array( x ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/lib/index.js new file mode 100644 index 000000000000..1f00102a4530 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/lib/index.js @@ -0,0 +1,50 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Sort a one-dimensional single-precision floating-point ndarray. +* +* @module @stdlib/blas/ext/base/ndarray/ssort +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ssort = require( '@stdlib/blas/ext/base/ndarray/ssort' ); +* +* var xbuf = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); +* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var order = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var out = ssort( [ x, order ] ); +* // returns [ -4.0, -2.0, 1.0, 3.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/lib/main.js new file mode 100644 index 000000000000..b50e5250dc70 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/lib/main.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/ssort' ).ndarray; + + +// MAIN // + +/** +* Sorts a one-dimensional single-precision floating-point ndarray. +* +* ## Notes +* +* - When the sort order is less than zero, the input ndarray is sorted in **decreasing** order. When the sort order is greater than zero, the input ndarray is sorted in **increasing** order. When the sort order is equal to zero, the input ndarray is left unchanged. +* +* @param {ArrayLikeObject} arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying the sort order +* @returns {ndarray} input ndarray +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); +* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var order = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var out = ssort( [ x, order ] ); +* // returns [ -4.0, -2.0, 1.0, 3.0 ] +*/ +function ssort( arrays ) { + var order; + var x; + + x = arrays[ 0 ]; + order = arrays[ 1 ]; + strided( numelDimension( x, 0 ), ndarraylike2scalar( order ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len + return x; +} + + +// EXPORTS // + +module.exports = ssort; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/package.json new file mode 100644 index 000000000000..4e0c3d12ea0e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/package.json @@ -0,0 +1,66 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/ssort", + "version": "0.0.0", + "description": "Sort a one-dimensional single-precision floating-point ndarray.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "sort", + "order", + "arrange", + "strided", + "array", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/test/test.js new file mode 100644 index 000000000000..f8815e6ea34e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssort/test/test.js @@ -0,0 +1,83 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var getDType = require( '@stdlib/ndarray/dtype' ); +var getStrides = require( '@stdlib/ndarray/strides' ); +var getOffset = require( '@stdlib/ndarray/offset' ); +var getShape = require( '@stdlib/ndarray/shape' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ssort = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof ssort, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function sorts a one-dimensional ndarray (increasing order)', function test( t ) { + var actual; + var order; + var x; + + x = ndarray( 'float32', new Float32Array( [ 3.0, 1.0, 2.0, 5.0, 4.0 ] ), [ 5 ], [ 1 ], 0, 'row-major' ); + order = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + + actual = ssort( [ x, order ] ); + t.strictEqual( actual, x, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float32', 'returns expected value' ); + t.deepEqual( getData( actual ), new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ), 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 5 ], 'returns expected value' ); + t.deepEqual( getStrides( actual ), [ 1 ], 'returns expected value' ); + t.strictEqual( getOffset( actual ), 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function sorts a one-dimensional ndarray (decreasing order)', function test( t ) { + var actual; + var order; + var x; + + x = ndarray( 'float32', new Float32Array( [ 3.0, 1.0, 2.0, 5.0, 4.0 ] ), [ 5 ], [ 1 ], 0, 'row-major' ); + order = scalar2ndarray( -1.0, { + 'dtype': 'generic' + }); + + actual = ssort( [ x, order ] ); + t.strictEqual( actual, x, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float32', 'returns expected value' ); + t.deepEqual( getData( actual ), new Float32Array( [ 5.0, 4.0, 3.0, 2.0, 1.0 ] ), 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 5 ], 'returns expected value' ); + t.deepEqual( getStrides( actual ), [ 1 ], 'returns expected value' ); + t.strictEqual( getOffset( actual ), 0, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssorthp/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssorthp/benchmark/benchmark.js index 06fb6ac13e78..9ca6b686bf12 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssorthp/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssorthp/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ssorthp = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssorthp/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssorthp/docs/repl.txt index 428f3aec1048..99143859a549 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssorthp/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssorthp/docs/repl.txt @@ -8,7 +8,7 @@ ndarray is sorted in increasing order. When the sort order is equal to zero, the input ndarray is left unchanged. - The input ndarray is sorted *in-place* (i.e., the input strided array is + The input ndarray is sorted *in-place* (i.e., the input ndarray is *mutated*). Parameters diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssorthp/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssorthp/test/test.js index 70e43a16b261..e066197d8f6c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssorthp/test/test.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssorthp/test/test.js @@ -24,7 +24,7 @@ var tape = require( 'tape' ); var Float32Array = require( '@stdlib/array/float32' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); var getData = require( '@stdlib/ndarray/data-buffer' ); -var getDtype = require( '@stdlib/ndarray/dtype' ); +var getDType = require( '@stdlib/ndarray/dtype' ); var getStrides = require( '@stdlib/ndarray/strides' ); var getOffset = require( '@stdlib/ndarray/offset' ); var getShape = require( '@stdlib/ndarray/shape' ); @@ -52,7 +52,7 @@ tape( 'the function sorts a one-dimensional ndarray (increasing order)', functio actual = ssorthp( [ x, order ] ); t.strictEqual( actual, x, 'returns expected value' ); - t.strictEqual( getDtype( actual ), 'float32', 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float32', 'returns expected value' ); t.deepEqual( getData( actual ), new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ), 'returns expected value' ); t.deepEqual( getShape( actual ), [ 5 ], 'returns expected value' ); t.deepEqual( getStrides( actual ), [ 1 ], 'returns expected value' ); @@ -73,7 +73,7 @@ tape( 'the function sorts a one-dimensional ndarray (decreasing order)', functio actual = ssorthp( [ x, order ] ); t.strictEqual( actual, x, 'returns expected value' ); - t.strictEqual( getDtype( actual ), 'float32', 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float32', 'returns expected value' ); t.deepEqual( getData( actual ), new Float32Array( [ 5.0, 4.0, 3.0, 2.0, 1.0 ] ), 'returns expected value' ); t.deepEqual( getShape( actual ), [ 5 ], 'returns expected value' ); t.deepEqual( getStrides( actual ), [ 1 ], 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssumkbn/benchmark/benchmark.js index f43d12f447ce..df4c6b9c03fa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssumkbn/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ssumkbn = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssumkbn2/benchmark/benchmark.js index 056fd4ca970f..54ff3064795e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssumkbn2/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ssumkbn2 = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssumors/benchmark/benchmark.js index 8416496d5b75..6a67999c1b13 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssumors/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ssumors = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssumpw/benchmark/benchmark.js index ee8b5af0d702..0d676bd7bd50 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/ssumpw/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ssumpw = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/README.md new file mode 100644 index 000000000000..63b09150c062 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/README.md @@ -0,0 +1,110 @@ + + +# zoneTo + +> Fill a one-dimensional double-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from one. + +
+ +
+ + + +
+ +## Usage + +```javascript +var zoneTo = require( '@stdlib/blas/ext/base/ndarray/zone-to' ); +``` + +#### zoneTo( arrays ) + +Fills a one-dimensional double-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from one. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); + +var xbuf = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +var x = new ndarray( 'complex128', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); + +var out = zoneTo( [ x ] ); +// returns [ [ 1.0, 0.0 ], [ 2.0, 0.0 ], [ 3.0, 0.0 ], [ 4.0, 0.0 ] ] +``` + +The function has the following parameters: + +- **arrays**: array-like object containing a one-dimensional input ndarray. + +
+ + + +
+ +## Notes + +- The input ndarray is modified **in-place** (i.e., the input ndarray is **mutated**). + +
+ + + +
+ +## Examples + + + +```javascript +var zeros = require( '@stdlib/array/zeros' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var zoneTo = require( '@stdlib/blas/ext/base/ndarray/zone-to' ); + +var xbuf = zeros( 10, 'complex128' ); +var x = new ndarray( 'complex128', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +zoneTo( [ x ] ); +console.log( ndarray2array( x ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/benchmark/benchmark.js new file mode 100644 index 000000000000..43c1101f8c73 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/benchmark/benchmark.js @@ -0,0 +1,108 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var zeros = require( '@stdlib/array/zeros' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var pkg = require( './../package.json' ).name; +var zoneTo = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'complex128' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var x; + + xbuf = zeros( len, options.dtype ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = zoneTo( [ x ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/docs/repl.txt new file mode 100644 index 000000000000..5203d7d3b07a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/docs/repl.txt @@ -0,0 +1,32 @@ + +{{alias}}( arrays ) + Fills a one-dimensional double-precision complex floating-point ndarray with + linearly spaced numeric elements which increment by `1` starting from one. + + The input ndarray is modified *in-place* (i.e., the input ndarray is + *mutated*). + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing a one-dimensional input ndarray. + + Returns + ------- + out: ndarray + Input ndarray. + + Examples + -------- + > var xbuf = new {{alias:@stdlib/array/complex128}}( [ 0.0, 0.0, 0.0, 0.0 ] ); + > var dt = 'complex128'; + > var sh = [ 2 ]; + > var sx = [ 1 ]; + > var ox = 0; + > var ord = 'row-major'; + > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord ); + > {{alias}}( [ x ] ) + [ [ 1.0, 0.0 ], [ 2.0, 0.0 ] ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/docs/types/index.d.ts new file mode 100644 index 000000000000..c581f30d2719 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/docs/types/index.d.ts @@ -0,0 +1,46 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { complex128ndarray } from '@stdlib/types/ndarray'; + +/** +* Fills a one-dimensional double-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from one. +* +* @param arrays - array-like object containing a one-dimensional input ndarray +* @returns input ndarray +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var x = new ndarray( 'complex128', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var out = zoneTo( [ x ] ); +* // returns [ [ 1.0, 0.0 ], [ 2.0, 0.0 ], [ 3.0, 0.0 ], [ 4.0, 0.0 ] ] +*/ +declare function zoneTo( arrays: [ complex128ndarray ] ): complex128ndarray; + + +// EXPORTS // + +export = zoneTo; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/docs/types/test.ts new file mode 100644 index 000000000000..f5a990e9bd58 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/docs/types/test.ts @@ -0,0 +1,57 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import zoneTo = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'complex128' + }); + + zoneTo( [ x ] ); // $ExpectType complex128ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + zoneTo( '10' ); // $ExpectError + zoneTo( 10 ); // $ExpectError + zoneTo( true ); // $ExpectError + zoneTo( false ); // $ExpectError + zoneTo( null ); // $ExpectError + zoneTo( undefined ); // $ExpectError + zoneTo( [] ); // $ExpectError + zoneTo( {} ); // $ExpectError + zoneTo( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'complex128' + }); + + zoneTo(); // $ExpectError + zoneTo( [ x ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/examples/index.js new file mode 100644 index 000000000000..65324005cc00 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var zeros = require( '@stdlib/array/zeros' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var zoneTo = require( './../lib' ); + +var xbuf = zeros( 10, 'complex128' ); +var x = new ndarray( 'complex128', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +zoneTo( [ x ] ); +console.log( ndarray2array( x ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/lib/index.js new file mode 100644 index 000000000000..8680cdd88550 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/lib/index.js @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Fill a one-dimensional double-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from one. +* +* @module @stdlib/blas/ext/base/ndarray/zone-to +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* var zoneTo = require( '@stdlib/blas/ext/base/ndarray/zone-to' ); +* +* var xbuf = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var x = new ndarray( 'complex128', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var out = zoneTo( [ x ] ); +* // returns [ [ 1.0, 0.0 ], [ 2.0, 0.0 ], [ 3.0, 0.0 ], [ 4.0, 0.0 ] ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/lib/main.js new file mode 100644 index 000000000000..a534cdbb24e2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/lib/main.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/zone-to' ).ndarray; + + +// MAIN // + +/** +* Fills a one-dimensional double-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from one. +* +* @param {ArrayLikeObject} arrays - array-like object containing a one-dimensional input ndarray +* @returns {ndarray} input ndarray +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var x = new ndarray( 'complex128', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var out = zoneTo( [ x ] ); +* // returns [ [ 1.0, 0.0 ], [ 2.0, 0.0 ], [ 3.0, 0.0 ], [ 4.0, 0.0 ] ] +*/ +function zoneTo( arrays ) { + var x = arrays[ 0 ]; + strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len + return x; +} + + +// EXPORTS // + +module.exports = zoneTo; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/package.json new file mode 100644 index 000000000000..385f227b4705 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/package.json @@ -0,0 +1,74 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/zone-to", + "version": "0.0.0", + "description": "Fill a one-dimensional double-precision complex floating-point ndarray with linearly spaced numeric elements which increment by 1 starting from one.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "fill", + "one", + "oneto", + "one-to", + "linearly", + "spaced", + "increment", + "strided", + "array", + "ndarray", + "complex128", + "complex", + "double-precision", + "float64" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/test/test.js new file mode 100644 index 000000000000..3270de939b0d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zone-to/test/test.js @@ -0,0 +1,290 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var zoneTo = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Complex128Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'complex128', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zoneTo, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( zoneTo.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function fills a one-dimensional ndarray with linearly spaced numeric elements which increment by 1 starting from one', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + x = vector( xbuf, 4, 1, 0 ); + + actual = zoneTo( [ x ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Complex128Array( [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0, 4.0, 0.0 ] ); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the input ndarray unchanged when the input ndarray is empty', function test( t ) { + var actual; + var xbuf; + var x; + + xbuf = new Complex128Array( [] ); + x = vector( xbuf, 0, 1, 0 ); + + actual = zoneTo( [ x ] ); + t.strictEqual( actual, x, 'returns expected value' ); + t.strictEqual( getData( actual ).length, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function fills a one-dimensional ndarray containing a single element', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Complex128Array( [ 5.0, 5.0 ] ); + x = vector( xbuf, 1, 1, 0 ); + + actual = zoneTo( [ x ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Complex128Array( [ 1.0, 0.0 ] ); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a non-unit stride', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Complex128Array([ + 0.0, // 0 + 0.0, // 0 + 9.0, + 9.0, + 0.0, // 1 + 0.0, // 1 + 9.0, + 9.0, + 0.0, // 2 + 0.0, // 2 + 9.0, + 9.0, + 0.0, // 3 + 0.0, // 3 + 9.0, + 9.0 + ]); + x = vector( xbuf, 4, 2, 0 ); + + actual = zoneTo( [ x ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Complex128Array([ + 1.0, // 0 + 0.0, // 0 + 9.0, + 9.0, + 2.0, // 1 + 0.0, // 1 + 9.0, + 9.0, + 3.0, // 2 + 0.0, // 2 + 9.0, + 9.0, + 4.0, // 3 + 0.0, // 3 + 9.0, + 9.0 + ]); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a negative stride', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Complex128Array([ + 0.0, // 4 + 0.0, // 4 + 0.0, // 3 + 0.0, // 3 + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]); + x = vector( xbuf, 5, -1, 4 ); + + actual = zoneTo( [ x ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Complex128Array([ + 5.0, // 4 + 0.0, // 4 + 4.0, // 3 + 0.0, // 3 + 3.0, // 2 + 0.0, // 2 + 2.0, // 1 + 0.0, // 1 + 1.0, // 0 + 0.0 // 0 + ]); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a non-zero offset', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Complex128Array([ + 9.0, + 9.0, + 9.0, + 9.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, // 3 + 0.0 // 3 + ]); + x = vector( xbuf, 4, 1, 2 ); + + actual = zoneTo( [ x ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Complex128Array([ + 9.0, + 9.0, + 9.0, + 9.0, + 1.0, // 0 + 0.0, // 0 + 2.0, // 1 + 0.0, // 1 + 3.0, // 2 + 0.0, // 2 + 4.0, // 3 + 0.0 // 3 + ]); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a negative stride and non-zero offset', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Complex128Array([ + 9.0, + 9.0, + 0.0, // 2 + 0.0, // 2 + 9.0, + 9.0, + 0.0, // 1 + 0.0, // 1 + 9.0, + 9.0, + 0.0, // 0 + 0.0 // 0 + ]); + x = vector( xbuf, 3, -2, 5 ); + + actual = zoneTo( [ x ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Complex128Array([ + 9.0, + 9.0, + 3.0, // 2 + 0.0, // 2 + 9.0, + 9.0, + 2.0, // 1 + 0.0, // 1 + 9.0, + 9.0, + 1.0, // 0 + 0.0 // 0 + ]); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/README.md index cc09d158d740..b189a3b1cd43 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/README.md @@ -98,6 +98,164 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/ndarray/zsum.h" +``` + +#### stdlib_blas_ext_zsum( arrays ) + +Computes the sum of all elements in a one-dimensional double-precision complex floating-point ndarray. + +```c +#include "stdlib/complex/float64/ctor.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include "stdlib/complex/float64/real.h" +#include "stdlib/complex/float64/imag.h" +#include + +// Create an ndarray: +const double data[] = { 1.0, 2.0, 3.0, 4.0 }; +int64_t shape[] = { 2 }; +int64_t strides[] = { STDLIB_NDARRAY_COMPLEX128_BYTES_PER_ELEMENT }; +int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + +struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_COMPLEX128, (uint8_t *)data, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes ); + +// Compute the sum: +const struct ndarray *arrays[] = { x }; +stdlib_complex128_t v = stdlib_blas_ext_zsum( arrays ); + +double re = stdlib_complex128_real( v ); +// returns 4.0 + +double im = stdlib_complex128_imag( v ); +// returns 6.0 + +// Free allocated memory: +stdlib_ndarray_free( x ); +``` + +The function accepts the following arguments: + +- **arrays**: `[in] struct ndarray**` list containing a one-dimensional input ndarray. + +```c +stdlib_complex128_t stdlib_blas_ext_zsum( const struct ndarray *arrays[] ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/ndarray/zsum.h" +#include "stdlib/complex/float64/ctor.h" +#include "stdlib/complex/float64/real.h" +#include "stdlib/complex/float64/imag.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include + +int main( void ) { + // Create a data buffer: + const double data[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + + // Specify the number of array dimensions: + const int64_t ndims = 1; + + // Specify the array shape: + int64_t shape[] = { 4 }; + + // Specify the array strides: + int64_t strides[] = { STDLIB_NDARRAY_COMPLEX128_BYTES_PER_ELEMENT }; + + // Specify the byte offset: + const int64_t offset = 0; + + // Specify the array order: + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const int64_t nsubmodes = 1; + + // Create an ndarray: + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_COMPLEX128, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x }; + + // Compute the sum: + stdlib_complex128_t v = stdlib_blas_ext_zsum( arrays ); + + // Print the result: + printf( "sum: %lf + %lfi\n", stdlib_complex128_real( v ), stdlib_complex128_imag( v ) ); + + // Free allocated memory: + stdlib_ndarray_free( x ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/benchmark/benchmark.js index 28b42f2b8681..ff8ec90db306 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/benchmark/benchmark.js @@ -28,8 +28,9 @@ var imag = require( '@stdlib/complex/float64/imag' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; -var zsum = require( './../lib' ); +var zsum = require( './../lib/main.js' ); // VARIABLES // @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/benchmark/benchmark.native.js new file mode 100644 index 000000000000..a76369228e00 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/benchmark/benchmark.native.js @@ -0,0 +1,119 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var zsum = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( zsum instanceof Error ) +}; +var options = { + 'dtype': 'complex128' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var x; + + xbuf = uniform( len*2, -10.0, 10.0, { + 'dtype': 'float64' + }); + x = new ndarray( options.dtype, new Complex128Array( xbuf ), [ len ], [ 1 ], 0, 'row-major' ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = zsum( [ x ] ); + if ( isnan( real( v ) ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( imag( v ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..6aa340c92350 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/benchmark/c/benchmark.length.c @@ -0,0 +1,193 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ndarray/zsum.h" +#include "stdlib/complex/float64/ctor.h" +#include "stdlib/complex/float64/real.h" +#include "stdlib/complex/float64/imag.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include +#include +#include +#include + +#define NAME "zsum" +#define ITERATIONS 1000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark( int iterations, int len ) { + enum STDLIB_NDARRAY_INDEX_MODE imode; + const struct ndarray *arrays[ 1 ]; + enum STDLIB_NDARRAY_ORDER order; + int8_t submodes[ 1 ]; + int64_t strides[ 1 ]; + int64_t shape[ 1 ]; + int64_t nsubmodes; + struct ndarray *x; + stdlib_complex128_t v; + int64_t offset; + double r; + double elapsed; + int64_t ndims; + double *data; + double t; + int i; + + ndims = 1; + shape[ 0 ] = len; + strides[ 0 ] = STDLIB_NDARRAY_COMPLEX128_BYTES_PER_ELEMENT; + offset = 0; + order = STDLIB_NDARRAY_ROW_MAJOR; + imode = STDLIB_NDARRAY_INDEX_ERROR; + submodes[ 0 ] = imode; + nsubmodes = 1; + + data = (double *) malloc( len * 2 * sizeof( double ) ); + for ( i = 0; i < len*2; i += 2 ) { + r = ( rand_double() * 20000.0 ) - 10000.0; + data[ i ] = r; + data[ i+1 ] = r; + } + // cppcheck-suppress invalidPointerCast + x = stdlib_ndarray_allocate( STDLIB_NDARRAY_COMPLEX128, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + arrays[ 0 ] = x; + + v = stdlib_complex128( 0.0, 0.0 ); + t = tic(); + for ( i = 0; i < iterations; i++ ) { + v = stdlib_blas_ext_zsum( arrays ); + r = stdlib_complex128_real( v ); + if ( r != r ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + r = stdlib_complex128_imag( v ); + if ( r != r ) { + printf( "should not return NaN\n" ); + } + stdlib_ndarray_free( x ); + free( data ); + arrays[ 0 ] = NULL; + + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/examples/c/example.c new file mode 100644 index 000000000000..b353ae0b5cec --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/examples/c/example.c @@ -0,0 +1,77 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ndarray/zsum.h" +#include "stdlib/complex/float64/ctor.h" +#include "stdlib/complex/float64/real.h" +#include "stdlib/complex/float64/imag.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include + +int main( void ) { + // Create a data buffer: + const double data[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + + // Specify the number of array dimensions: + const int64_t ndims = 1; + + // Specify the array shape: + int64_t shape[] = { 4 }; + + // Specify the array strides: + int64_t strides[] = { STDLIB_NDARRAY_COMPLEX128_BYTES_PER_ELEMENT }; + + // Specify the byte offset: + const int64_t offset = 0; + + // Specify the array order: + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const int64_t nsubmodes = 1; + + // Create an ndarray: + // cppcheck-suppress invalidPointerCast + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_COMPLEX128, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x }; + + // Compute the sum: + stdlib_complex128_t v = stdlib_blas_ext_zsum( arrays ); + + // Print the result: + printf( "sum: %lf + %lfi\n", stdlib_complex128_real( v ), stdlib_complex128_imag( v ) ); + + // Free allocated memory: + stdlib_ndarray_free( x ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '} arrays - array-like object containing an input ndarray +* @returns {Complex128} sum +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Complex128Array( [ 1.0, 3.0, 4.0, 2.0 ] ); +* var x = new ndarray( 'complex128', xbuf, [ 2 ], [ 1 ], 0, 'row-major' ); +* +* var v = zsum( [ x ] ); +* // returns [ 5.0, 5.0 ] +*/ +function zsum( arrays ) { + var x = arrays[ 0 ]; + var o = addon( reinterpret( getData( x ), 0 ), serialize( x ) ); + return new Complex128( o.re, o.im ); +} + + +// EXPORTS // + +module.exports = zsum; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/manifest.json new file mode 100644 index 000000000000..5e9466a2a25b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/manifest.json @@ -0,0 +1,119 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/zsum", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/base/napi/addon-arguments", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/create-complex-like", + "@stdlib/complex/float64/ctor", + "@stdlib/complex/float64/real", + "@stdlib/complex/float64/imag" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/zsum", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/dtypes", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders", + "@stdlib/ndarray/base/bytes-per-element", + "@stdlib/complex/float64/ctor", + "@stdlib/complex/float64/real", + "@stdlib/complex/float64/imag" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/zsum", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/dtypes", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders", + "@stdlib/ndarray/base/bytes-per-element", + "@stdlib/complex/float64/ctor", + "@stdlib/complex/float64/real", + "@stdlib/complex/float64/imag" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/zsum", + "@stdlib/ndarray/ctor" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/package.json index 6c1a30ac01b4..cfc3a748e12e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/package.json @@ -14,11 +14,15 @@ } ], "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/src/addon.c new file mode 100644 index 000000000000..7e8165694be1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/src/addon.c @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ndarray/zsum.h" +#include "stdlib/complex/float64/ctor.h" +#include "stdlib/complex/float64/real.h" +#include "stdlib/complex/float64/imag.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/base/napi/addon_arguments.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/create_complex_like.h" +#include +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 2 ); + + // Process provided arguments: + struct ndarray *arrays[ 1 ]; + napi_value err; + napi_status status = stdlib_ndarray_napi_addon_arguments( env, argv, 2, 1, arrays, &err ); + assert( status == napi_ok ); + if ( err != NULL ) { + status = napi_throw( env, err ); + assert( status == napi_ok ); + return NULL; + } + // Perform computation: + stdlib_complex128_t z = stdlib_blas_ext_zsum( (const struct ndarray **)arrays ); + STDLIB_NAPI_CREATE_COMPLEX_LIKE( env, stdlib_complex128_real( z ), stdlib_complex128_imag( z ), v ); + + // Free allocated memory: + stdlib_ndarray_free( arrays[ 0 ] ); + arrays[ 0 ] = NULL; + + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/src/main.c new file mode 100644 index 000000000000..06624b96c379 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/src/main.c @@ -0,0 +1,34 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ndarray/zsum.h" +#include "stdlib/blas/ext/base/zsum.h" +#include "stdlib/complex/float64/ctor.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/blas/base/shared.h" + +/** +* Computes the sum of all elements in a one-dimensional double-precision complex floating-point ndarray. +* +* @param arrays list containing an input ndarray +* @return sum +*/ +stdlib_complex128_t stdlib_blas_ext_zsum( const struct ndarray *arrays[] ) { + const struct ndarray *x = arrays[ 0 ]; + return API_SUFFIX(stdlib_strided_zsum_ndarray)( stdlib_ndarray_dimension( x, 0 ), (const stdlib_complex128_t *)stdlib_ndarray_data( x ), stdlib_ndarray_stride_elements( x, 0 ), stdlib_ndarray_offset_elements( x ) ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/test/test.js index 8af09bc1ddbe..e728cc940c28 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/test/test.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/test/test.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2025 The Stdlib Authors. +* Copyright (c) 2026 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -21,28 +21,16 @@ // MODULES // var tape = require( 'tape' ); -var isSameComplex128 = require( '@stdlib/assert/is-same-complex128' ); -var Complex128Array = require( '@stdlib/array/complex128' ); -var Complex128 = require( '@stdlib/complex/float64/ctor' ); -var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); var zsum = require( './../lib' ); -// FUNCTIONS // +// VARIABLES // -/** -* Returns a one-dimensional ndarray. -* -* @private -* @param {Complex128Array} buffer - underlying data buffer -* @param {NonNegativeInteger} length - number of indexed elements -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - index offset -* @returns {ndarray} one-dimensional ndarray -*/ -function vector( buffer, length, stride, offset ) { - return new ndarray( 'complex128', buffer, [ length ], [ stride ], offset, 'row-major' ); -} +var opts = { + 'skip': IS_BROWSER +}; // TESTS // @@ -53,147 +41,37 @@ tape( 'main export is a function', function test( t ) { t.end(); }); -tape( 'the function has an arity of 1', function test( t ) { - t.strictEqual( zsum.length, 1, 'has expected arity' ); - t.end(); -}); - -tape( 'the function computes the sum of all elements in a one-dimensional ndarray', function test( t ) { - var x; - var v; - - x = new Complex128Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); - v = zsum( [ vector( x, 3, 1, 0 ) ] ); - t.strictEqual( isSameComplex128( v, new Complex128( -3.0, 6.0 ) ), true, 'returns expected value' ); - - x = new Complex128Array( [ -4.0, -5.0, -4.0, -5.0 ] ); - v = zsum( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( isSameComplex128( v, new Complex128( -8.0, -10.0 ) ), true, 'returns expected value' ); - - x = new Complex128Array( [ -0.0, 0.0, -0.0, -0.0 ] ); - v = zsum( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( isSameComplex128( v, new Complex128( -0.0, 0.0 ) ), true, 'returns expected value' ); - - x = new Complex128Array( [ NaN, NaN ] ); - v = zsum( [ vector( x, 1, 1, 0 ) ] ); - t.strictEqual( isSameComplex128( v, new Complex128( NaN, NaN ) ), true, 'returns expected value' ); - - x = new Complex128Array( [ NaN, NaN, NaN, NaN ] ); - v = zsum( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( isSameComplex128( v, new Complex128( NaN, NaN ) ), true, 'returns expected value' ); +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var zsum = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + t.strictEqual( zsum, mock, 'returns expected value' ); t.end(); -}); -tape( 'if provided an empty vector, the function returns `0.0`', function test( t ) { - var x; - var v; + function tryRequire() { + return mock; + } - x = new Complex128Array( [] ); - - v = zsum( [ vector( x, 0, 1, 0 ) ] ); - t.strictEqual( isSameComplex128( v, new Complex128( 0.0, 0.0 ) ), true, 'returns expected value' ); - - t.end(); + function mock() { + // Mock... + } }); -tape( 'if provided a vector containing a single element, the function returns that element', function test( t ) { - var x; - var v; +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var zsum; + var main; - x = new Complex128Array( [ 1.0, 2.0 ] ); - - v = zsum( [ vector( x, 1, 1, 0 ) ] ); - t.strictEqual( isSameComplex128( v, new Complex128( 1.0, 2.0 ) ), true, 'returns expected value' ); - - t.end(); -}); + main = require( './../lib/main.js' ); -tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { - var x; - var v; - - x = new Complex128Array([ - 1.0, // 0 - 1.0, // 0 - 2.0, - 2.0, - 2.0, // 1 - 2.0, // 1 - -7.0, - -7.0, - -2.0, // 2 - -2.0, // 2 - 3.0, - 3.0, - 4.0, // 3 - 4.0, // 3 - 2.0, - 2.0 - ]); - - v = zsum( [ vector( x, 4, 2, 0 ) ] ); - - t.strictEqual( isSameComplex128( v, new Complex128( 5.0, 5.0 ) ), true, 'returns expected value' ); - t.end(); -}); + zsum = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); -tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { - var x; - var v; - - x = new Complex128Array([ - 1.0, // 3 - 1.0, // 3 - 2.0, - 2.0, - 2.0, // 2 - 2.0, // 2 - -7.0, - -7.0, - -2.0, // 1 - -2.0, // 1 - 3.0, - 3.0, - 4.0, // 0 - 4.0, // 0 - 2.0, - 2.0 - ]); - - v = zsum( [ vector( x, 4, -2, 6 ) ] ); - - t.strictEqual( isSameComplex128( v, new Complex128( 5.0, 5.0 ) ), true, 'returns expected value' ); + t.strictEqual( zsum, main, 'returns expected value' ); t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { - var x; - var v; - - x = new Complex128Array([ - -9.0, - -9.0, - 1.0, // 3 - 1.0, // 3 - 2.0, - 2.0, - 2.0, // 2 - 2.0, // 2 - -7.0, - -7.0, - -2.0, // 1 - -2.0, // 1 - 3.0, - 3.0, - 4.0, // 0 - 4.0, // 0 - 2.0, - 2.0 - ]); - - v = zsum( [ vector( x, 4, 2, 1 ) ] ); - t.strictEqual( isSameComplex128( v, new Complex128( 5.0, 5.0 ) ), true, 'returns expected value' ); - t.end(); + function tryRequire() { + return new Error( 'Cannot find module' ); + } }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/test/test.main.js new file mode 100644 index 000000000000..0c9654081aa3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/test/test.main.js @@ -0,0 +1,199 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128 = require( '@stdlib/assert/is-same-complex128' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var zsum = require( './../lib/main.js' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Complex128Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'complex128', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zsum, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( zsum.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the sum of all elements in a one-dimensional ndarray', function test( t ) { + var x; + var v; + + x = new Complex128Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + v = zsum( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( isSameComplex128( v, new Complex128( -3.0, 6.0 ) ), true, 'returns expected value' ); + + x = new Complex128Array( [ -4.0, -5.0, -4.0, -5.0 ] ); + v = zsum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isSameComplex128( v, new Complex128( -8.0, -10.0 ) ), true, 'returns expected value' ); + + x = new Complex128Array( [ -0.0, 0.0, -0.0, -0.0 ] ); + v = zsum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isSameComplex128( v, new Complex128( -0.0, 0.0 ) ), true, 'returns expected value' ); + + x = new Complex128Array( [ NaN, NaN ] ); + v = zsum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( isSameComplex128( v, new Complex128( NaN, NaN ) ), true, 'returns expected value' ); + + x = new Complex128Array( [ NaN, NaN, NaN, NaN ] ); + v = zsum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isSameComplex128( v, new Complex128( NaN, NaN ) ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty vector, the function returns `0.0`', function test( t ) { + var x; + var v; + + x = new Complex128Array( [] ); + + v = zsum( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( isSameComplex128( v, new Complex128( 0.0, 0.0 ) ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a vector containing a single element, the function returns that element', function test( t ) { + var x; + var v; + + x = new Complex128Array( [ 1.0, 2.0 ] ); + + v = zsum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( isSameComplex128( v, new Complex128( 1.0, 2.0 ) ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var x; + var v; + + x = new Complex128Array([ + 1.0, // 0 + 1.0, // 0 + 2.0, + 2.0, + 2.0, // 1 + 2.0, // 1 + -7.0, + -7.0, + -2.0, // 2 + -2.0, // 2 + 3.0, + 3.0, + 4.0, // 3 + 4.0, // 3 + 2.0, + 2.0 + ]); + + v = zsum( [ vector( x, 4, 2, 0 ) ] ); + + t.strictEqual( isSameComplex128( v, new Complex128( 5.0, 5.0 ) ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var x; + var v; + + x = new Complex128Array([ + 1.0, // 3 + 1.0, // 3 + 2.0, + 2.0, + 2.0, // 2 + 2.0, // 2 + -7.0, + -7.0, + -2.0, // 1 + -2.0, // 1 + 3.0, + 3.0, + 4.0, // 0 + 4.0, // 0 + 2.0, + 2.0 + ]); + + v = zsum( [ vector( x, 4, -2, 6 ) ] ); + + t.strictEqual( isSameComplex128( v, new Complex128( 5.0, 5.0 ) ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var x; + var v; + + x = new Complex128Array([ + -9.0, + -9.0, + 1.0, // 3 + 1.0, // 3 + 2.0, + 2.0, + 2.0, // 2 + 2.0, // 2 + -7.0, + -7.0, + -2.0, // 1 + -2.0, // 1 + 3.0, + 3.0, + 4.0, // 0 + 4.0, // 0 + 2.0, + 2.0 + ]); + + v = zsum( [ vector( x, 4, 2, 1 ) ] ); + t.strictEqual( isSameComplex128( v, new Complex128( 5.0, 5.0 ) ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/test/test.native.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/test/test.native.js new file mode 100644 index 000000000000..89a2c11a2f70 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsum/test/test.native.js @@ -0,0 +1,208 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isSameComplex128 = require( '@stdlib/assert/is-same-complex128' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var zsum = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( zsum instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Complex128Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'complex128', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zsum, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', opts, function test( t ) { + t.strictEqual( zsum.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function computes the sum of all elements in a one-dimensional ndarray', opts, function test( t ) { + var x; + var v; + + x = new Complex128Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + v = zsum( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( isSameComplex128( v, new Complex128( -3.0, 6.0 ) ), true, 'returns expected value' ); + + x = new Complex128Array( [ -4.0, -5.0, -4.0, -5.0 ] ); + v = zsum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isSameComplex128( v, new Complex128( -8.0, -10.0 ) ), true, 'returns expected value' ); + + x = new Complex128Array( [ -0.0, 0.0, -0.0, -0.0 ] ); + v = zsum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isSameComplex128( v, new Complex128( -0.0, 0.0 ) ), true, 'returns expected value' ); + + x = new Complex128Array( [ NaN, NaN ] ); + v = zsum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( isSameComplex128( v, new Complex128( NaN, NaN ) ), true, 'returns expected value' ); + + x = new Complex128Array( [ NaN, NaN, NaN, NaN ] ); + v = zsum( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isSameComplex128( v, new Complex128( NaN, NaN ) ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `0.0`', opts, function test( t ) { + var x; + var v; + + x = new Complex128Array( [] ); + + v = zsum( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( isSameComplex128( v, new Complex128( 0.0, 0.0 ) ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an ndarray containing a single element, the function returns that element', opts, function test( t ) { + var x; + var v; + + x = new Complex128Array( [ 1.0, 2.0 ] ); + + v = zsum( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( isSameComplex128( v, new Complex128( 1.0, 2.0 ) ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', opts, function test( t ) { + var x; + var v; + + x = new Complex128Array([ + 1.0, // 0 + 1.0, // 0 + 2.0, + 2.0, + 2.0, // 1 + 2.0, // 1 + -7.0, + -7.0, + -2.0, // 2 + -2.0, // 2 + 3.0, + 3.0, + 4.0, // 3 + 4.0, // 3 + 2.0, + 2.0 + ]); + + v = zsum( [ vector( x, 4, 2, 0 ) ] ); + + t.strictEqual( isSameComplex128( v, new Complex128( 5.0, 5.0 ) ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', opts, function test( t ) { + var x; + var v; + + x = new Complex128Array([ + 1.0, // 3 + 1.0, // 3 + 2.0, + 2.0, + 2.0, // 2 + 2.0, // 2 + -7.0, + -7.0, + -2.0, // 1 + -2.0, // 1 + 3.0, + 3.0, + 4.0, // 0 + 4.0, // 0 + 2.0, + 2.0 + ]); + + v = zsum( [ vector( x, 4, -2, 6 ) ] ); + + t.strictEqual( isSameComplex128( v, new Complex128( 5.0, 5.0 ) ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', opts, function test( t ) { + var x; + var v; + + x = new Complex128Array([ + -9.0, + -9.0, + 1.0, // 3 + 1.0, // 3 + 2.0, + 2.0, + 2.0, // 2 + 2.0, // 2 + -7.0, + -7.0, + -2.0, // 1 + -2.0, // 1 + 3.0, + 3.0, + 4.0, // 0 + 4.0, // 0 + 2.0, + 2.0 + ]); + + v = zsum( [ vector( x, 4, 2, 1 ) ] ); + t.strictEqual( isSameComplex128( v, new Complex128( 5.0, 5.0 ) ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsumkbn/benchmark/benchmark.js index d1b8606b073c..ffe00965fbf7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zsumkbn/benchmark/benchmark.js @@ -28,6 +28,7 @@ var imag = require( '@stdlib/complex/float64/imag' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var zsumkbn = require( './../lib' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.js index 2bc087e22c15..fb8215b92448 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapx = require( './../lib/sapx.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.native.js index 8b58292ee808..aab78a32d905 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.js index fda21ed0cd12..ca2982ecdc8b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapx = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.native.js index 7e0738fd7722..bd8488971f86 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.js index 117302d66905..d55831e2a0ad 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapxsum = require( './../lib/sapxsum.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.native.js index db53fa31aec9..b64e57a98726 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.js index b6cd2780f864..860c17f41f2d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapxsum = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.native.js index 60f6e71357dd..a5a126f3c727 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.js index ac68c9f9fb54..ac7ba091b5d2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapxsumkbn = require( './../lib/sapxsumkbn.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.native.js index d5f5cdfb397f..c538c63f6bed 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.js index 81a68b7635e6..eac87ea7f2e8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapxsumkbn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.native.js index ae505b7568f2..b080b57379fa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.js index 156095c0d3db..f8b658871fbc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapxsumkbn2 = require( './../lib/sapxsumkbn2.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.native.js index 0aa73451ad9f..9951112aba67 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.ndarray.js index ec2ad6e49c24..e061a88d94f1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapxsumkbn2 = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.ndarray.native.js index 48c499f5f1f0..851ae578b5fa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.js index e02dacfee09a..2f1cf0afed81 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapxsumors = require( './../lib/sapxsumors.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.native.js index edece2cd97d0..ea35aaf4743f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.ndarray.js index 22e2383fce61..4f7647188e46 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapxsumors = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.ndarray.native.js index 9eb687abe578..0cf9f189aaf5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.js index ea799f1c0d54..f262f4672365 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapxsumpw = require( './../lib/sapxsumpw.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.native.js index b72178b5013b..60de6a9880c3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.js index f77f2905ecfb..36a3155e1321 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapxsumpw = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.native.js index 87d5407fdb71..55acfb2dadd7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.js index 5f06d86485fe..3fd4dd2b944d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sasumpw = require( './../lib/sasumpw.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.native.js index 0479c94d8f63..2b3aa4747bb0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.js index 9a5b44d5aaae..d1622757e4d8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sasumpw = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.native.js index 7bd16c754465..cb938fd722d2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.js index 9819a5687b00..03e909de8cf4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scusum = require( './../lib/scusum.js' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.native.js index 943a0c6bf2a6..bc2284331b68 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.js index 020f411ca947..f2519782a340 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scusum = require( './../lib/ndarray.js' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.native.js index 2ec819c2e52e..47f0fc1d7b34 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.js index 85a8e84e3949..b4b7bbbb99ea 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scusumkbn = require( './../lib/scusumkbn.js' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.native.js index e4f9dfe6debb..e910bac377ea 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.js index 53025b8ab1e1..c93f88ca1230 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scusumkbn = require( './../lib/ndarray.js' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.native.js index a7986df42bd8..c2fe71fd6ad3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.js index bc81e3fa9655..818aaf5e85ea 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scusumkbn2 = require( './../lib/scusumkbn2.js' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.native.js index 29ca294bd730..7ce93b846e06 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.js index 717503e8a8e1..f567d008d392 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scusumkbn2 = require( './../lib/ndarray.js' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.native.js index b0dd2c17075d..1cddd0ef73b9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.js index 120902caf035..45d357927701 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scusumors = require( './../lib/scusumors.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.native.js index 085e885193cf..4804a85038c1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.js index 84b911b7e4ee..7bc7da90494e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scusumors = require( './../lib/ndarray.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.native.js index 35079be87300..97e245ee292a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.js index a4d8f75c3403..1b20dd637c9d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scusumpw = require( './../lib/scusumpw.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.native.js index bad1e811f02b..4a3803f71e96 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.js index b53dc56dba7f..9d0e24b42979 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scusumpw = require( './../lib/ndarray.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.native.js index 81236bfcc81e..8b5bd5d87fe0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.js index 4adbff0152f7..d05a114b6573 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsapxsum = require( './../lib/sdsapxsum.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.native.js index f83d0d3f4f6f..9c71302a3327 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.ndarray.js index 987153804089..2f5c0ecccbd4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsapxsum = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.ndarray.native.js index 8329649d7882..bd48f4572a9e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.js index 9a9e51daee0a..b0176573b9b1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsapxsumpw = require( './../lib/sdsapxsumpw.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.native.js index a4ad9474aa63..222e8f356a01 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.ndarray.js index 35d88d1f7c35..03ca02ebb6e1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsapxsumpw = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.ndarray.native.js index d4aec1bca558..3591c872f624 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsnansumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sdsnansumpw/benchmark/benchmark.js index 42b058355bb7..275bcd9fa583 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsnansumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsnansumpw/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsnansumpw = require( './../lib/sdsnansumpw.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsnansumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdsnansumpw/benchmark/benchmark.native.js index 0fd0bde7a745..a1a7238bc03e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsnansumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsnansumpw/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsnansumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sdsnansumpw/benchmark/benchmark.ndarray.js index 724f3b62feef..7867e455d13d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsnansumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsnansumpw/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsnansumpw = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsnansumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdsnansumpw/benchmark/benchmark.ndarray.native.js index 866236fd48de..3a44d647d49e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsnansumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsnansumpw/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdssum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sdssum/benchmark/benchmark.js index 3b4736bf91d2..c8ec4174b591 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdssum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdssum/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdssum = require( './../lib/sdssum.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdssum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdssum/benchmark/benchmark.native.js index d29b3380ac31..0525b4fb4609 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdssum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdssum/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdssum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sdssum/benchmark/benchmark.ndarray.js index 0a0790e15367..26c87dbd1f08 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdssum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdssum/benchmark/benchmark.ndarray.js @@ -24,8 +24,9 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); -var sdssum = require( './../lib/ndarray.js' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; +var sdssum = require( './../lib/ndarray.js' ); // VARIABLES // @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdssum/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdssum/benchmark/benchmark.ndarray.native.js index 832804e00b8a..9e125d87adf3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdssum/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdssum/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdssumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sdssumpw/benchmark/benchmark.js index 919a7f7d2615..22cd1294d7cd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdssumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdssumpw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdssumpw = require( './../lib/sdssumpw.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdssumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdssumpw/benchmark/benchmark.native.js index 77b63289c510..27261e7a1845 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdssumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdssumpw/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdssumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sdssumpw/benchmark/benchmark.ndarray.js index 768c4eb7ddf2..0cec59dc6c6a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdssumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdssumpw/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdssumpw = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdssumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdssumpw/benchmark/benchmark.ndarray.native.js index b815881d2a88..f60f7e051d06 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdssumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdssumpw/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sfill/benchmark/benchmark.js index 57b4b730c988..d2950de566bb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sfill/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sfill = require( './../lib/sfill.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill/benchmark/benchmark.native.js index c2be19a10aec..849a87c298d3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sfill/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sfill/benchmark/benchmark.ndarray.js index e9b0ca2a060a..b203cb2501df 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sfill/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sfill = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill/benchmark/benchmark.ndarray.native.js index a50b1a3e5a2b..d7692054a82f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sfill/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sindex-of-row/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/sindex-of-row/docs/types/index.d.ts index ac3ccaac5830..f71a9348a2c7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sindex-of-row/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/sindex-of-row/docs/types/index.d.ts @@ -46,8 +46,8 @@ interface Routine { * @returns row index * * @example - * var Float32Array = require( `@stdlib/array/float32` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var Float32Array = require( '@stdlib/array/float32' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Float32Array( [ 1.0, 2.0, 0.0, 3.0, 4.0, 0.0 ] ); * var x = new Float32Array( [ 2.0, 4.0 ] ); @@ -81,8 +81,8 @@ interface Routine { * @returns row index * * @example - * var Float32Array = require( `@stdlib/array/float32` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var Float32Array = require( '@stdlib/array/float32' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Float32Array( [ 1.0, 2.0, 0.0, 3.0, 4.0, 0.0 ] ); * var x = new Float32Array( [ 2.0, 4.0 ] ); @@ -114,8 +114,8 @@ interface Routine { * @returns row index * * @example -* var Float32Array = require( `@stdlib/array/float32` ); -* var Uint8Array = require( `@stdlib/array/uint8` ); +* var Float32Array = require( '@stdlib/array/float32' ); +* var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Float32Array( [ 1.0, 2.0, 0.0, 3.0, 4.0, 0.0 ] ); * var x = new Float32Array( [ 2.0, 4.0 ] ); @@ -125,8 +125,8 @@ interface Routine { * // returns 1 * * @example -* var Float32Array = require( `@stdlib/array/float32` ); -* var Uint8Array = require( `@stdlib/array/uint8` ); +* var Float32Array = require( '@stdlib/array/float32' ); +* var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Float32Array( [ 1.0, 2.0, 0.0, 3.0, 4.0, 0.0 ] ); * var x = new Float32Array( [ 2.0, 4.0 ] ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/README.md b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/README.md index f2cb92b0e5c1..dc945842cf96 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/README.md @@ -222,7 +222,7 @@ Returns the first index of a specified search element in a single-precision floa ```c float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; -int idx = stdlib_strided_sindex_of( 4, 3.0f, x, 1, 0 ); +int idx = stdlib_strided_sindex_of_ndarray( 4, 3.0f, x, 1, 0 ); // returns 2 ``` diff --git a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/benchmark/benchmark.js index 7108395688c3..cadd35a4890f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var oneTo = require( '@stdlib/array/one-to' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sindexOf = require( './../lib/sindex_of.js' ); @@ -89,7 +90,7 @@ function main() { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/benchmark/benchmark.native.js index 2921ff9f7737..f6a2608e2fb6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var oneTo = require( '@stdlib/array/one-to' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -98,7 +99,7 @@ function main() { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/benchmark/benchmark.ndarray.js index a04c50fc4d3c..0af5980a587e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var oneTo = require( '@stdlib/array/one-to' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sindexOf = require( './../lib/ndarray.js' ); @@ -89,7 +90,7 @@ function main() { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/benchmark/benchmark.ndarray.native.js index af2978b15726..aebabb7e5a3c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var oneTo = require( '@stdlib/array/one-to' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -98,7 +99,7 @@ function main() { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/README.md b/lib/node_modules/@stdlib/blas/ext/base/ssort/README.md new file mode 100644 index 000000000000..c28332490a21 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/README.md @@ -0,0 +1,299 @@ + + +# ssort + +> Sort a single-precision floating-point strided array. + +
+ +## Usage + +```javascript +var ssort = require( '@stdlib/blas/ext/base/ssort' ); +``` + +#### ssort( N, order, x, strideX ) + +Sorts a single-precision floating-point strided array. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); + +ssort( x.length, 1.0, x, 1 ); +// x => [ -4.0, -2.0, 1.0, 3.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **order**: sort order. If `order < 0.0`, the input strided array is sorted in **decreasing** order. If `order > 0.0`, the input strided array is sorted in **increasing** order. If `order == 0.0`, the input strided array is left unchanged. +- **x**: input [`Float32Array`][@stdlib/array/float32]. +- **strideX**: stride length. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to sort every other element: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); + +ssort( 2, -1.0, x, 2 ); +// x => [ 3.0, -2.0, 1.0, -4.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +// Initial array... +var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + +// Create an offset view... +var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Sort every other element... +ssort( 2, -1.0, x1, 2 ); +// x0 => [ 1.0, 4.0, 3.0, 2.0 ] +``` + +#### ssort.ndarray( N, order, x, strideX, offsetX ) + +Sorts a single-precision floating-point strided array using alternative indexing semantics. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); + +ssort.ndarray( x.length, 1.0, x, 1, 0 ); +// x => [ -4.0, -2.0, 1.0, 3.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); + +ssort.ndarray( 3, 1.0, x, 1, 3 ); +// x => [ 1.0, -2.0, 3.0, -6.0, -4.0, 5.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0` or `order == 0.0`, both functions return `x` unchanged. +- The algorithm distinguishes between `-0` and `+0`. When sorted in increasing order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is sorted after `+0`. +- The algorithm sorts `NaN` values to the end. When sorted in increasing order, `NaN` values are sorted last. When sorted in decreasing order, `NaN` values are sorted first. +- The input strided array is sorted **in-place** (i.e., the input strided array is **mutated**). + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var ssort = require( '@stdlib/blas/ext/base/ssort' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); +console.log( x ); + +ssort( x.length, 1.0, x, 1 ); +console.log( x ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/ssort.h" +``` + +#### stdlib_strided_ssort( N, order, \*X, strideX ) + +Sorts a single-precision floating-point strided array. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; + +stdlib_strided_ssort( 4, 1.0f, x, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **order**: `[in] float` sort order. If `order < 0.0`, the input strided array is sorted in **decreasing** order. If `order > 0.0`, the input strided array is sorted in **increasing** order. If `order == 0.0`, the input strided array is left unchanged. +- **X**: `[inout] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +void stdlib_strided_ssort( const CBLAS_INT N, const float order, float *X, const CBLAS_INT strideX ); +``` + + + +#### stdlib_strided_ssort_ndarray( N, order, \*X, strideX, offsetX ) + + + +Sorts a single-precision floating-point strided array using alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; + +stdlib_strided_ssort_ndarray( 4, 1.0f, x, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **order**: `[in] float` sort order. If `order < 0.0`, the input strided array is sorted in **decreasing** order. If `order > 0.0`, the input strided array is sorted in **increasing** order. If `order == 0.0`, the input strided array is left unchanged. +- **X**: `[inout] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +void stdlib_strided_ssort_ndarray( const CBLAS_INT N, const float order, float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/ssort.h" +#include + +int main( void ) { + // Create a strided array: + float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; + + // Specify the number of elements: + const int N = 8; + + // Specify the stride length: + const int strideX = 1; + + // Sort the array: + stdlib_strided_ssort( N, 1.0f, x, strideX ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "x[ %i ] = %f\n", i, x[ i ] ); + } +} +``` + +
+ + + +
+ + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float32 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/benchmark.unsorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/benchmark.unsorted_random.js new file mode 100644 index 000000000000..242155c5c138 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/benchmark.unsorted_random.js @@ -0,0 +1,122 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scopy = require( '@stdlib/blas/base/scopy' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var ssort = require( './../lib/ssort.js' ); + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} iter - number of iterations +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( iter, len ) { + var tmp; + var x; + var i; + + x = []; + for ( i = 0; i < iter; i++ ) { + tmp = uniform( len, -100.0, 100.0, { + 'dtype': 'float32' + }); + x.push( tmp ); + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var xc; + var y; + var i; + + xc = x.slice(); + for ( i = 0; i < iter; i++ ) { + xc[ i ] = scopy( len, x[ i ], 1, new Float32Array( len ), 1 ); + } + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = ssort( len, 1, xc[ i ], 1 ); + if ( isnanf( y[ i%len ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y[ i%len ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var opts; + var iter; + var len; + var min; + var max; + var f; + var i; + + iter = 1e6; + min = 1; // 10^min + max = 4; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( iter, len ); + opts = { + 'iterations': iter + }; + bench( format( '%s::unsorted,random:len=%d', pkg, len ), opts, f ); + iter = floor( pow( iter, 3.0/4.0 ) ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/benchmark.unsorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/benchmark.unsorted_random.native.js new file mode 100644 index 000000000000..7d54a2ea26b2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/benchmark.unsorted_random.native.js @@ -0,0 +1,132 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scopy = require( '@stdlib/blas/base/scopy' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var ssort = tryRequire( resolve( __dirname, './../lib/ssort.native.js' ) ); +var opts = { + 'skip': ( ssort instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} iter - number of iterations +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( iter, len ) { + var tmp; + var x; + var i; + + x = []; + for ( i = 0; i < iter; i++ ) { + tmp = uniform( len, -100.0, 100.0, { + 'dtype': 'float32' + }); + x.push( tmp ); + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var xc; + var y; + var i; + + xc = x.slice(); + for ( i = 0; i < iter; i++ ) { + xc[ i ] = scopy( len, x[ i ], 1, new Float32Array( len ), 1 ); + } + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = ssort( len, 1, xc[ i ], 1 ); + if ( isnanf( y[ i%len ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y[ i%len ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var bopts; + var iter; + var len; + var min; + var max; + var f; + var i; + + iter = 1e6; + min = 1; // 10^min + max = 4; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( iter, len ); + bopts = { + 'skip': opts.skip, + 'iterations': iter + }; + bench( format( '%s::native,unsorted,random:len=%d', pkg, len ), bopts, f ); + iter = floor( pow( iter, 3.0/4.0 ) ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/benchmark.unsorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/benchmark.unsorted_random.ndarray.js new file mode 100644 index 000000000000..8964e1688064 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/benchmark.unsorted_random.ndarray.js @@ -0,0 +1,122 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scopy = require( '@stdlib/blas/base/scopy' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var ssort = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} iter - number of iterations +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( iter, len ) { + var tmp; + var x; + var i; + + x = []; + for ( i = 0; i < iter; i++ ) { + tmp = uniform( len, -100.0, 100.0, { + 'dtype': 'float32' + }); + x.push( tmp ); + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var xc; + var y; + var i; + + xc = x.slice(); + for ( i = 0; i < iter; i++ ) { + xc[ i ] = scopy( len, x[ i ], 1, new Float32Array( len ), 1 ); + } + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = ssort( len, 1, xc[ i ], 1, 0 ); + if ( isnanf( y[ i%len ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y[ i%len ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var opts; + var iter; + var len; + var min; + var max; + var f; + var i; + + iter = 1e6; + min = 1; // 10^min + max = 4; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( iter, len ); + opts = { + 'iterations': iter + }; + bench( format( '%s::unsorted,random:ndarray:len=%d', pkg, len ), opts, f ); + iter = floor( pow( iter, 3.0/4.0 ) ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/benchmark.unsorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/benchmark.unsorted_random.ndarray.native.js new file mode 100644 index 000000000000..07aa742b646d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/benchmark.unsorted_random.ndarray.native.js @@ -0,0 +1,132 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scopy = require( '@stdlib/blas/base/scopy' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var ssort = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( ssort instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} iter - number of iterations +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( iter, len ) { + var tmp; + var x; + var i; + + x = []; + for ( i = 0; i < iter; i++ ) { + tmp = uniform( len, -100.0, 100.0, { + 'dtype': 'float32' + }); + x.push( tmp ); + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var xc; + var y; + var i; + + xc = x.slice(); + for ( i = 0; i < iter; i++ ) { + xc[ i ] = scopy( len, x[ i ], 1, new Float32Array( len ), 1 ); + } + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = ssort( len, 1, xc[ i ], 1, 0 ); + if ( isnan( y[ i%len ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%len ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var bopts; + var iter; + var len; + var min; + var max; + var f; + var i; + + iter = 1e6; + min = 1; // 10^min + max = 4; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( iter, len ); + bopts = { + 'skip': opts.skip, + 'iterations': iter + }; + bench( format( '%s::native,unsorted,random:ndarray:len=%d', pkg, len ), bopts, f ); + iter = floor( pow( iter, 3.0/4.0 ) ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/c/unsorted-random/Makefile b/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/c/unsorted-random/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/c/unsorted-random/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/c/unsorted-random/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/c/unsorted-random/benchmark.length.c new file mode 100644 index 000000000000..a9b602b95b9c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/benchmark/c/unsorted-random/benchmark.length.c @@ -0,0 +1,195 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ssort.h" +#include +#include +#include +#include +#include + +#define NAME "ssort" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static float rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + float *x; + double t; + int i; + + x = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float()*20.0f ) - 10.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_strided_ssort( len, 1.0f, x, 1 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float *x; + double t; + int i; + + x = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float()*20.0f ) - 10.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_strided_ssort_ndarray( len, 1.0f, x, 1, 0 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s::unsorted,random:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s::unsorted,random:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/ssort/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ssort/docs/repl.txt new file mode 100644 index 000000000000..7434b5ef0109 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/docs/repl.txt @@ -0,0 +1,113 @@ + +{{alias}}( N, order, x, strideX ) + Sorts a single-precision floating-point strided array. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0` or `order == 0`, the function returns `x` unchanged. + + The algorithm distinguishes between `-0` and `+0`. When sorted in increasing + order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is + sorted after `+0`. + + The algorithm sorts `NaN` values to the end. When sorted in increasing + order, `NaN` values are sorted last. When sorted in decreasing order, `NaN` + values are sorted first. + + The input strided array is sorted *in-place* (i.e., the input strided array + is *mutated*). + + Parameters + ---------- + N: integer + Number of indexed elements. + + order: number + Sort order. If `order < 0`, the function sorts `x` in decreasing order. + If `order > 0`, the function sorts `x` in increasing order. + + x: Float32Array + Input array. + + strideX: integer + Stride length. + + Returns + ------- + x: Float32Array + Input array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, -4.0 ] ); + > {{alias}}( x.length, 1.0, x, 1 ); + > x + [ -4.0, -2.0, 1.0, 3.0 ] + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, -4.0 ] ); + > {{alias}}( 2, -1.0, x, 2 ); + > x + [ 3.0, -2.0, 1.0, -4.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, -4.0 ] ); + > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 2, 1.0, x1, 2 ); + > x0 + [ 1.0, -4.0, 3.0, -2.0 ] + + +{{alias}}.ndarray( N, order, x, strideX, offsetX ) + Sorts a double-precision floating-point strided array using alternative + indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + order: number + Sort order. If `order < 0`, the function sorts `x` in decreasing order. + If `order > 0`, the function sorts `x` in increasing order. + + x: Float32Array + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + x: Float32Array + Input array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, -4.0 ] ); + > {{alias}}.ndarray( x.length, 1.0, x, 1, 0 ); + > x + [ -4.0, -2.0, 1.0, 3.0 ] + + // Using an index offset: + > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); + > {{alias}}.ndarray( 3, 1.0, x, 1, 3 ); + > x + [ 1.0, -2.0, 3.0, -6.0, -4.0, 5.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ssort/docs/types/index.d.ts new file mode 100644 index 000000000000..17b1d891682b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/docs/types/index.d.ts @@ -0,0 +1,95 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `ssort`. +*/ +interface Routine { + /** + * Sorts a single-precision floating-point strided array. + * + * @param N - number of indexed elements + * @param order - sort order + * @param x - input array + * @param strideX - stride length + * @returns input array + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); + * + * ssort( x.length, 1.0, x, 1 ); + * // x => [ -4.0, -2.0, 1.0, 3.0 ] + */ + ( N: number, order: number, x: Float32Array, strideX: number ): Float32Array; + + /** + * Sorts a single-precision floating-point strided array using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param order - sort order + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns input array + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); + * + * ssort.ndarray( x.length, 1.0, x, 1, 0 ); + * // x => [ -4.0, -2.0, 1.0, 3.0 ] + */ + ndarray( N: number, order: number, x: Float32Array, strideX: number, offsetX: number ): Float32Array; +} + +/** +* Sorts a single-precision floating-point strided array. +* +* @param N - number of indexed elements +* @param order - sort order +* @param x - input array +* @param strideX - stride length +* @returns input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); +* +* ssort( x.length, 1.0, x, 1 ); +* // x => [ -4.0, -2.0, 1.0, 3.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); +* +* ssort.ndarray( x.length, 1.0, x, 1, 0 ); +* // x => [ -4.0, -2.0, 1.0, 3.0 ] +*/ +declare var ssort: Routine; + + +// EXPORTS // + +export = ssort; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ssort/docs/types/test.ts new file mode 100644 index 000000000000..cfcf9a821a42 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/docs/types/test.ts @@ -0,0 +1,187 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import ssort = require( './index' ); + + +// TESTS // + +// The function returns a Float32Array... +{ + const x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + + ssort( x.length, 1.0, x, 1 ); // $ExpectType Float32Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + + ssort( '10', 1.0, x, 1 ); // $ExpectError + ssort( true, 1.0, x, 1 ); // $ExpectError + ssort( false, 1.0, x, 1 ); // $ExpectError + ssort( null, 1.0, x, 1 ); // $ExpectError + ssort( undefined, 1.0, x, 1 ); // $ExpectError + ssort( [], 1.0, x, 1 ); // $ExpectError + ssort( {}, 1.0, x, 1 ); // $ExpectError + ssort( ( x: number ): number => x, 1.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + + ssort( x.length, '10', x, 1 ); // $ExpectError + ssort( x.length, true, x, 1 ); // $ExpectError + ssort( x.length, false, x, 1 ); // $ExpectError + ssort( x.length, null, x, 1 ); // $ExpectError + ssort( x.length, undefined, x, 1 ); // $ExpectError + ssort( x.length, [], x, 1 ); // $ExpectError + ssort( x.length, {}, x, 1 ); // $ExpectError + ssort( x.length, ( x: number ): number => x, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a Float32Array... +{ + const x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + + ssort( x.length, 1.0, '10', 1 ); // $ExpectError + ssort( x.length, 1.0, 10, 1 ); // $ExpectError + ssort( x.length, 1.0, true, 1 ); // $ExpectError + ssort( x.length, 1.0, false, 1 ); // $ExpectError + ssort( x.length, 1.0, null, 1 ); // $ExpectError + ssort( x.length, 1.0, undefined, 1 ); // $ExpectError + ssort( x.length, 1.0, [], 1 ); // $ExpectError + ssort( x.length, 1.0, {}, 1 ); // $ExpectError + ssort( x.length, 1.0, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + + ssort( x.length, 1.0, x, '10' ); // $ExpectError + ssort( x.length, 1.0, x, true ); // $ExpectError + ssort( x.length, 1.0, x, false ); // $ExpectError + ssort( x.length, 1.0, x, null ); // $ExpectError + ssort( x.length, 1.0, x, undefined ); // $ExpectError + ssort( x.length, 1.0, x, [] ); // $ExpectError + ssort( x.length, 1.0, x, {} ); // $ExpectError + ssort( x.length, 1.0, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + + ssort(); // $ExpectError + ssort( x.length ); // $ExpectError + ssort( x.length, 1.0 ); // $ExpectError + ssort( x.length, 1.0, x ); // $ExpectError + ssort( x.length, 1.0, x, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Float32Array... +{ + const x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + + ssort.ndarray( x.length, 1.0, x, 1, 0 ); // $ExpectType Float32Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + + ssort.ndarray( '10', 1.0, x, 1, 0 ); // $ExpectError + ssort.ndarray( true, 1.0, x, 1, 0 ); // $ExpectError + ssort.ndarray( false, 1.0, x, 1, 0 ); // $ExpectError + ssort.ndarray( null, 1.0, x, 1, 0 ); // $ExpectError + ssort.ndarray( undefined, 1.0, x, 1, 0 ); // $ExpectError + ssort.ndarray( [], 1.0, x, 1, 0 ); // $ExpectError + ssort.ndarray( {}, 1.0, x, 1, 0 ); // $ExpectError + ssort.ndarray( ( x: number ): number => x, 1.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + + ssort.ndarray( x.length, '10', x, 1, 0 ); // $ExpectError + ssort.ndarray( x.length, true, x, 1, 0 ); // $ExpectError + ssort.ndarray( x.length, false, x, 1, 0 ); // $ExpectError + ssort.ndarray( x.length, null, x, 1, 0 ); // $ExpectError + ssort.ndarray( x.length, undefined, x, 1, 0 ); // $ExpectError + ssort.ndarray( x.length, [], x, 1, 0 ); // $ExpectError + ssort.ndarray( x.length, {}, x, 1, 0 ); // $ExpectError + ssort.ndarray( x.length, ( x: number ): number => x, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a Float32Array... +{ + const x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + + ssort.ndarray( x.length, 1.0, '10', 1, 0 ); // $ExpectError + ssort.ndarray( x.length, 1.0, 10, 1, 0 ); // $ExpectError + ssort.ndarray( x.length, 1.0, true, 1, 0 ); // $ExpectError + ssort.ndarray( x.length, 1.0, false, 1, 0 ); // $ExpectError + ssort.ndarray( x.length, 1.0, null, 1, 0 ); // $ExpectError + ssort.ndarray( x.length, 1.0, undefined, 1, 0 ); // $ExpectError + ssort.ndarray( x.length, 1.0, [], 1, 0 ); // $ExpectError + ssort.ndarray( x.length, 1.0, {}, 1, 0 ); // $ExpectError + ssort.ndarray( x.length, 1.0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + + ssort.ndarray( x.length, 1.0, x, '10', 0 ); // $ExpectError + ssort.ndarray( x.length, 1.0, x, true, 0 ); // $ExpectError + ssort.ndarray( x.length, 1.0, x, false, 0 ); // $ExpectError + ssort.ndarray( x.length, 1.0, x, null, 0 ); // $ExpectError + ssort.ndarray( x.length, 1.0, x, undefined, 0 ); // $ExpectError + ssort.ndarray( x.length, 1.0, x, [], 0 ); // $ExpectError + ssort.ndarray( x.length, 1.0, x, {}, 0 ); // $ExpectError + ssort.ndarray( x.length, 1.0, x, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + + ssort.ndarray( x.length, 1.0, x, 1, '10' ); // $ExpectError + ssort.ndarray( x.length, 1.0, x, 1, true ); // $ExpectError + ssort.ndarray( x.length, 1.0, x, 1, false ); // $ExpectError + ssort.ndarray( x.length, 1.0, x, 1, null ); // $ExpectError + ssort.ndarray( x.length, 1.0, x, 1, undefined ); // $ExpectError + ssort.ndarray( x.length, 1.0, x, 1, [] ); // $ExpectError + ssort.ndarray( x.length, 1.0, x, 1, {} ); // $ExpectError + ssort.ndarray( x.length, 1.0, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + + ssort.ndarray(); // $ExpectError + ssort.ndarray( x.length ); // $ExpectError + ssort.ndarray( x.length, 1.0 ); // $ExpectError + ssort.ndarray( x.length, 1.0, x ); // $ExpectError + ssort.ndarray( x.length, 1.0, x, 1 ); // $ExpectError + ssort.ndarray( x.length, 1.0, x, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/ssort/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/ssort/examples/c/example.c new file mode 100644 index 000000000000..a5cf4dde4e7d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/examples/c/example.c @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ssort.h" +#include + +int main( void ) { + // Create a strided array: + float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; + + // Specify the number of elements: + int N = 8; + + // Specify a stride: + int strideX = 1; + + // Sort the array: + stdlib_strided_ssort( N, 1.0f, x, strideX ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "x[ %i ] = %f\n", i, x[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/examples/index.js new file mode 100644 index 000000000000..8930f5a86f8b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/examples/index.js @@ -0,0 +1,30 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var ssort = require( './../lib' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); +console.log( x ); + +ssort( x.length, 1.0, x, 1 ); +console.log( x ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/ssort/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ -4.0, -2.0, 1.0, 3.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* var ssort = require( '@stdlib/blas/ext/base/ssort' ); +* +* var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); +* +* ssort.ndarray( x.length, 1.0, x, 1, 0 ); +* // x => [ -4.0, -2.0, 1.0, 3.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var ssort; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + ssort = main; +} else { + ssort = tmp; +} + + +// EXPORTS // + +module.exports = ssort; + +// exports: { "ndarray": "ssort.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/main.js new file mode 100644 index 000000000000..34243a645db2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var ssort = require( './ssort.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( ssort, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = ssort; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/native.js new file mode 100644 index 000000000000..2db6e93302d2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var ssort = require( './ssort.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( ssort, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = ssort; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/ndarray.js new file mode 100644 index 000000000000..239ecde6ca33 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/ndarray.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var ssorthp = require( '@stdlib/blas/ext/base/ssorthp' ).ndarray; + + +// MAIN // + +/** +* Sorts a single-precision floating-point strided array. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} order - sort order +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Float32Array} input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); +* +* ssort( x.length, 1.0, x, 1, 0 ); +* // x => [ -4.0, -2.0, 1.0, 3.0 ] +*/ +function ssort( N, order, x, strideX, offsetX ) { + return ssorthp( N, order, x, strideX, offsetX ); +} + + +// EXPORTS // + +module.exports = ssort; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/ndarray.native.js new file mode 100644 index 000000000000..4dc85a66de6f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/ndarray.native.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Sorts a single-precision floating-point strided array. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} order - sort order +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Float32Array} input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); +* +* ssort( x.length, 1.0, x, 1, 0 ); +*/ +function ssort( N, order, x, strideX, offsetX ) { + addon.ndarray( N, order, x, strideX, offsetX ); + return x; +} + + +// EXPORTS // + +module.exports = ssort; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/ssort.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/ssort.js new file mode 100644 index 000000000000..9c9aaaacc730 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/ssort.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Sorts a single-precision floating-point strided array. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} order - sort order +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length +* @returns {Float32Array} input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); +* +* ssort( x.length, 1.0, x, 1 ); +* // x => [ -4.0, -2.0, 1.0, 3.0 ] +*/ +function ssort( N, order, x, strideX ) { + return ndarray( N, order, x, strideX, stride2offset( N, strideX ) ); +} + + +// EXPORTS // + +module.exports = ssort; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/ssort.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/ssort.native.js new file mode 100644 index 000000000000..37b6db60fd1f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/lib/ssort.native.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Sorts a single-precision floating-point strided array. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} order - sort order +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length +* @returns {Float32Array} input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] ); +* +* ssort( x.length, 1.0, x, 1 ); +* // x => [ -4.0, -2.0, 1.0, 3.0 ] +*/ +function ssort( N, order, x, strideX ) { + addon( N, order, x, strideX ); + return x; +} + + +// EXPORTS // + +module.exports = ssort; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/ssort/manifest.json new file mode 100644 index 000000000000..864f65d4a1f2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/manifest.json @@ -0,0 +1,82 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-float", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/ssorthp" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/ssorthp" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", + "@stdlib/blas/ext/base/ssorthp" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/package.json b/lib/node_modules/@stdlib/blas/ext/base/ssort/package.json new file mode 100644 index 000000000000..069f1226fab9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/package.json @@ -0,0 +1,74 @@ +{ + "name": "@stdlib/blas/ext/base/ssort", + "version": "0.0.0", + "description": "Sort a single-precision floating-point strided array.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "sort", + "order", + "arrange", + "permute", + "strided", + "array", + "ndarray", + "float32", + "single", + "float32array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/ssort/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/ssort/src/addon.c new file mode 100644 index 000000000000..61abafd41118 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/src/addon.c @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ssort.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_float.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, order, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + API_SUFFIX(stdlib_strided_ssort)( N, order, X, strideX ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_FLOAT( env, order, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + API_SUFFIX(stdlib_strided_ssort_ndarray)( N, order, X, strideX, offsetX ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/ssort/src/main.c new file mode 100644 index 000000000000..1e6f08a03fa3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/src/main.c @@ -0,0 +1,48 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ssort.h" +#include "stdlib/blas/ext/base/ssorthp.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Sorts a single-precision floating-point strided array. +* +* @param N number of indexed elements +* @param order sort order +* @param X input array +* @param strideX stride length +*/ +void API_SUFFIX(stdlib_strided_ssort)( const CBLAS_INT N, const float order, float *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + API_SUFFIX(stdlib_strided_ssort_ndarray)( N, order, X, strideX, ox ); +} + +/** +* Sorts a single-precision floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param order sort order +* @param X input array +* @param strideX stride length +* @param offsetX starting index +*/ +void API_SUFFIX(stdlib_strided_ssort_ndarray)( const CBLAS_INT N, const float order, float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + API_SUFFIX(stdlib_strided_ssorthp_ndarray)( N, order, X, strideX, offsetX ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/test/fixtures/ascending.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/test/fixtures/ascending.js new file mode 100644 index 000000000000..cc1d74a8f111 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/test/fixtures/ascending.js @@ -0,0 +1,75 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); + + +// MAIN // + +/** +* Determines sort order by comparing two values. +* +* ## Notes +* +* - Return values are as follows: +* +* - `-1`: sort `a` to a lower index than `b` (i.e., `a` comes first) +* - `1`: sort `b` to a lower index than `a` (i.e., `b` comes first) +* - `0`: leave the order of `a` and `b` unchanged with respect to one another +* +* @private +* @param {number} a - first value +* @param {number} b - second value +* @returns {integer} value indicating sort order +*/ +function ascending( a, b ) { + // Sort NaNs to the end... + if ( isnanf( a ) ) { + return 1; + } + if ( isnanf( b ) ) { + return -1; + } + // Sort negative 0s to the left... + if ( a === b && a === 0 ) { + if ( isNegativeZerof( a ) ) { + return -1; + } + if ( isNegativeZerof( b ) ) { + return 1; + } + return 0; + } + if ( a > b ) { + return 1; + } + if ( a < b ) { + return -1; + } + return 0; +} + + +// EXPORTS // + +module.exports = ascending; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/test/fixtures/num2str.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/test/fixtures/num2str.js new file mode 100644 index 000000000000..cb17904d655b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/test/fixtures/num2str.js @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); + + +// MAIN // + +/** +* Converts a number to a string. +* +* @private +* @param {number} value - input value +* @returns {string} string representation +*/ +function num2str( value ) { + if ( isNegativeZerof( value ) ) { + return '-0'; + } + return value.toString(); +} + + +// EXPORTS // + +module.exports = num2str; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/test/test.js new file mode 100644 index 000000000000..304bebb45900 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var ssort = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof ssort, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof ssort.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var ssort = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( ssort, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var ssort; + var main; + + main = require( './../lib/ssort.js' ); + + ssort = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( ssort, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/test/test.ndarray.js new file mode 100644 index 000000000000..5e342d1b8eb0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/test/test.ndarray.js @@ -0,0 +1,622 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); +var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); +var randu = require( '@stdlib/random/base/randu' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scopy = require( '@stdlib/blas/base/scopy' ); +var ascending = require( './fixtures/ascending.js' ); +var num2str = require( './fixtures/num2str.js' ); +var ssort = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof ssort, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( ssort.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function sorts a strided array (increasing order)', function test( t ) { + var expected; + var x; + var i; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = (randu()*20.0) - 10.0; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array (decreasing order)', function test( t ) { + var expected; + var x; + var i; + var j; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = (randu()*20.0) - 10.0; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array which includes NaNs (increasing order)', function test( t ) { + var expected; + var x; + var v; + var i; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = (randu()*20.0) - 10.0; + } + x[ i ] = v; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array which includes NaNs (decreasing order)', function test( t ) { + var expected; + var x; + var v; + var i; + var j; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = (randu()*20.0) - 10.0; + } + x[ i ] = v; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array which includes positive and negative zeros (increasing order)', function test( t ) { + var expected; + var x; + var v; + var i; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + if ( randu() < 0.5 ) { + v = -0.0; + } else { + v = 0.0; + } + x[ i ] = v; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array which includes positive and negative zeros (decreasing order)', function test( t ) { + var expected; + var x; + var v; + var i; + var j; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + if ( randu() < 0.5 ) { + v = -0.0; + } else { + v = 0.0; + } + x[ i ] = v; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array (increasing order; special cases)', function test( t ) { + var expected; + var x; + var i; + + x = new Float32Array( [ NaN, 1.0, -1.0, 2.0, 2.0 ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + + x = new Float32Array( [ 1.0, -1.0, 2.0, 2.0, NaN ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + + x = new Float32Array( [ NaN, 1.0, -1.0, 2.0, 2.0, NaN ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array (decreasing order; special cases)', function test( t ) { + var expected; + var x; + var i; + var j; + + x = new Float32Array( [ NaN, 1.0, -1.0, 2.0, 2.0 ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + + x = new Float32Array( [ 1.0, -1.0, 2.0, 2.0, NaN ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + + x = new Float32Array( [ NaN, 1.0, -1.0, 2.0, 2.0, NaN ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + out = ssort( x.length, 1.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = new Float32Array( [ 3.0, -4.0, 1.0 ] ); + expected = new Float32Array( [ 3.0, -4.0, 1.0 ] ); + + ssort( 0, 1.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + ssort( -4, 1.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `order` equals `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = new Float32Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + expected = new Float32Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + + ssort( x.length, 0.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride (increasing order)', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 2.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 2 + ]); + expected = new Float32Array([ + -5.0, // 0 + -3.0, + 2.0, // 1 + 7.0, + 6.0 // 2 + ]); + + ssort( 3, 1.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride (decreasing order)', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 2.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 2 + ]); + expected = new Float32Array([ + 6.0, // 0 + -3.0, + 2.0, // 1 + 7.0, + -5.0 // 2 + ]); + + ssort( 3, -1.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride (increasing order)', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 2.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 0 + ]); + expected = new Float32Array([ + 6.0, // 2 + -3.0, + 2.0, // 1 + 7.0, + -5.0 // 0 + ]); + + ssort( 3, 1.0, x, -2, x.length-1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride (decreasing order)', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 2.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 0 + ]); + expected = new Float32Array([ + -5.0, // 2 + -3.0, + 2.0, // 1 + 7.0, + 6.0 // 0 + ]); + + ssort( 3, -1.0, x, -2, x.length-1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying an offset (increasing order)', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, + -2.0, // 0 + 3.0, + -4.0, // 1 + 5.0, + -6.0 // 2 + ]); + expected = new Float32Array([ + 1.0, + -6.0, // 0 + 3.0, + -4.0, // 1 + 5.0, + -2.0 // 2 + ]); + + ssort( 3, 1.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying an offset (decreasing order)', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, + -6.0, // 0 + 3.0, + -4.0, // 1 + 5.0, + -2.0 // 2 + ]); + expected = new Float32Array([ + 1.0, + -2.0, // 0 + 3.0, + -4.0, // 1 + 5.0, + -6.0 // 2 + ]); + + ssort( 3, -1.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns (increasing order)', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, + -4.0, // 2 + 3.0, + -2.0, // 1 + 5.0, + -6.0 // 0 + ]); + expected = new Float32Array([ + 1.0, + -2.0, // 2 + 3.0, + -4.0, // 1 + 5.0, + -6.0 // 0 + ]); + + ssort( 3, 1.0, x, -2, x.length-1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns (decreasing order)', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, + -2.0, // 2 + 3.0, + -4.0, // 1 + 5.0, + -6.0 // 0 + ]); + expected = new Float32Array([ + 1.0, + -6.0, // 2 + 3.0, + -4.0, // 1 + 5.0, + -2.0 // 0 + ]); + + ssort( 3, -1.0, x, -2, x.length-1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/test/test.ndarray.native.js new file mode 100644 index 000000000000..d4330a1657d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/test/test.ndarray.native.js @@ -0,0 +1,631 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); +var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); +var randu = require( '@stdlib/random/base/randu' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scopy = require( '@stdlib/blas/base/scopy' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var ascending = require( './fixtures/ascending.js' ); +var num2str = require( './fixtures/num2str.js' ); + + +// VARIABLES // + +var ssort = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( ssort instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof ssort, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( ssort.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function sorts a strided array (increasing order)', opts, function test( t ) { + var expected; + var x; + var i; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = (randu()*20.0) - 10.0; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array (decreasing order)', opts, function test( t ) { + var expected; + var x; + var i; + var j; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = (randu()*20.0) - 10.0; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array which includes NaNs (increasing order)', opts, function test( t ) { + var expected; + var x; + var v; + var i; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = (randu()*20.0) - 10.0; + } + x[ i ] = v; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array which includes NaNs (decreasing order)', opts, function test( t ) { + var expected; + var x; + var v; + var i; + var j; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = (randu()*20.0) - 10.0; + } + x[ i ] = v; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array which includes positive and negative zeros (increasing order)', opts, function test( t ) { + var expected; + var x; + var v; + var i; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + if ( randu() < 0.5 ) { + v = -0.0; + } else { + v = 0.0; + } + x[ i ] = v; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array which includes positive and negative zeros (decreasing order)', opts, function test( t ) { + var expected; + var x; + var v; + var i; + var j; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + if ( randu() < 0.5 ) { + v = -0.0; + } else { + v = 0.0; + } + x[ i ] = v; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array (increasing order; special cases)', opts, function test( t ) { + var expected; + var x; + var i; + + x = new Float32Array( [ NaN, 1.0, -1.0, 2.0, 2.0 ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + + x = new Float32Array( [ 1.0, -1.0, 2.0, 2.0, NaN ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + + x = new Float32Array( [ NaN, 1.0, -1.0, 2.0, 2.0, NaN ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array (decreasing order; special cases)', opts, function test( t ) { + var expected; + var x; + var i; + var j; + + x = new Float32Array( [ NaN, 1.0, -1.0, 2.0, 2.0 ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + + x = new Float32Array( [ 1.0, -1.0, 2.0, 2.0, NaN ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + + x = new Float32Array( [ NaN, 1.0, -1.0, 2.0, 2.0, NaN ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1, 0 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + t.end(); +}); + +tape( 'the function returns a reference to the input array', opts, function test( t ) { + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + out = ssort( x.length, 1.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array( [ 3.0, -4.0, 1.0 ] ); + expected = new Float32Array( [ 3.0, -4.0, 1.0 ] ); + + ssort( 0, 1.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + ssort( -4, 1.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `order` equals `0`, the function returns `x` unchanged', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + expected = new Float32Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + + ssort( x.length, 0.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride (increasing order)', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 2.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 2 + ]); + expected = new Float32Array([ + -5.0, // 0 + -3.0, + 2.0, // 1 + 7.0, + 6.0 // 2 + ]); + + ssort( 3, 1.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride (decreasing order)', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 2.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 2 + ]); + expected = new Float32Array([ + 6.0, // 0 + -3.0, + 2.0, // 1 + 7.0, + -5.0 // 2 + ]); + + ssort( 3, -1.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride (increasing order)', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 2.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 0 + ]); + expected = new Float32Array([ + 6.0, // 2 + -3.0, + 2.0, // 1 + 7.0, + -5.0 // 0 + ]); + + ssort( 3, 1.0, x, -2, x.length-1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride (decreasing order)', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 2.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 0 + ]); + expected = new Float32Array([ + -5.0, // 2 + -3.0, + 2.0, // 1 + 7.0, + 6.0 // 0 + ]); + + ssort( 3, -1.0, x, -2, x.length-1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying an offset (increasing order)', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, + -2.0, // 0 + 3.0, + -4.0, // 1 + 5.0, + -6.0 // 2 + ]); + expected = new Float32Array([ + 1.0, + -6.0, // 0 + 3.0, + -4.0, // 1 + 5.0, + -2.0 // 2 + ]); + + ssort( 3, 1.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying an offset (decreasing order)', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, + -6.0, // 0 + 3.0, + -4.0, // 1 + 5.0, + -2.0 // 2 + ]); + expected = new Float32Array([ + 1.0, + -2.0, // 0 + 3.0, + -4.0, // 1 + 5.0, + -6.0 // 2 + ]); + + ssort( 3, -1.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns (increasing order)', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, + -4.0, // 2 + 3.0, + -2.0, // 1 + 5.0, + -6.0 // 0 + ]); + expected = new Float32Array([ + 1.0, + -2.0, // 2 + 3.0, + -4.0, // 1 + 5.0, + -6.0 // 0 + ]); + + ssort( 3, 1.0, x, -2, x.length-1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns (decreasing order)', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, + -2.0, // 2 + 3.0, + -4.0, // 1 + 5.0, + -6.0 // 0 + ]); + expected = new Float32Array([ + 1.0, + -6.0, // 2 + 3.0, + -4.0, // 1 + 5.0, + -2.0 // 0 + ]); + + ssort( 3, -1.0, x, -2, x.length-1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/test/test.ssort.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/test/test.ssort.js new file mode 100644 index 000000000000..ec2fa6c15a35 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/test/test.ssort.js @@ -0,0 +1,576 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); +var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); +var randu = require( '@stdlib/random/base/randu' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scopy = require( '@stdlib/blas/base/scopy' ); +var ascending = require( './fixtures/ascending.js' ); +var num2str = require( './fixtures/num2str.js' ); +var ssort = require( './../lib/ssort.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof ssort, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', function test( t ) { + t.strictEqual( ssort.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function sorts a strided array (increasing order)', function test( t ) { + var expected; + var x; + var i; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = (randu()*20.0) - 10.0; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array (decreasing order)', function test( t ) { + var expected; + var x; + var i; + var j; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = (randu()*20.0) - 10.0; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array which includes NaNs (increasing order)', function test( t ) { + var expected; + var x; + var v; + var i; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = (randu()*20.0) - 10.0; + } + x[ i ] = v; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array which includes NaNs (decreasing order)', function test( t ) { + var expected; + var x; + var v; + var i; + var j; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = (randu()*20.0) - 10.0; + } + x[ i ] = v; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array which includes positive and negative zeros (increasing order)', function test( t ) { + var expected; + var x; + var v; + var i; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + if ( randu() < 0.5 ) { + v = -0.0; + } else { + v = 0.0; + } + x[ i ] = v; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array which includes positive and negative zeros (decreasing order)', function test( t ) { + var expected; + var x; + var v; + var i; + var j; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + if ( randu() < 0.5 ) { + v = -0.0; + } else { + v = 0.0; + } + x[ i ] = v; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array (increasing order; special cases)', function test( t ) { + var expected; + var x; + var i; + + x = new Float32Array( [ NaN, 1.0, -1.0, 2.0, 2.0 ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + + x = new Float32Array( [ 1.0, -1.0, 2.0, 2.0, NaN ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + + x = new Float32Array( [ NaN, 1.0, -1.0, 2.0, 2.0, NaN ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array (decreasing order; special cases)', function test( t ) { + var expected; + var x; + var i; + var j; + + x = new Float32Array( [ NaN, 1.0, -1.0, 2.0, 2.0 ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + + x = new Float32Array( [ 1.0, -1.0, 2.0, 2.0, NaN ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + + x = new Float32Array( [ NaN, 1.0, -1.0, 2.0, 2.0, NaN ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + out = ssort( x.length, 1.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = new Float32Array( [ 3.0, -4.0, 1.0 ] ); + expected = new Float32Array( [ 3.0, -4.0, 1.0 ] ); + + ssort( 0, 1.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + ssort( -4, 1.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `order` equals `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = new Float32Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + expected = new Float32Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + + ssort( x.length, 0.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride (increasing order)', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 2.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 2 + ]); + expected = new Float32Array([ + -5.0, // 0 + -3.0, + 2.0, // 1 + 7.0, + 6.0 // 2 + ]); + + ssort( 3, 1.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride (decreasing order)', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 2.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 2 + ]); + expected = new Float32Array([ + 6.0, // 0 + -3.0, + 2.0, // 1 + 7.0, + -5.0 // 2 + ]); + + ssort( 3, -1.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride (increasing order)', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 2.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 0 + ]); + expected = new Float32Array([ + 6.0, // 2 + -3.0, + 2.0, // 1 + 7.0, + -5.0 // 0 + ]); + + ssort( 3, 1.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride (decreasing order)', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 2.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 0 + ]); + expected = new Float32Array([ + -5.0, // 2 + -3.0, + 2.0, // 1 + 7.0, + 6.0 // 0 + ]); + + ssort( 3, -1.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets (increasing order)', function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float32Array([ + 1.0, + -2.0, // 0 + 3.0, + -4.0, // 1 + 5.0, + -6.0 // 2 + ]); + expected = new Float32Array([ + 1.0, + -6.0, // 0 + 3.0, + -4.0, // 1 + 5.0, + -2.0 // 2 + ]); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + ssort( 3, 1.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets (decreasing order)', function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float32Array([ + 1.0, + -6.0, // 0 + 3.0, + -4.0, // 1 + 5.0, + -2.0 // 2 + ]); + expected = new Float32Array([ + 1.0, + -2.0, // 0 + 3.0, + -4.0, // 1 + 5.0, + -6.0 // 2 + ]); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + ssort( 3, -1.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort/test/test.ssort.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssort/test/test.ssort.native.js new file mode 100644 index 000000000000..f5c2758ec3ce --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort/test/test.ssort.native.js @@ -0,0 +1,585 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); +var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); +var randu = require( '@stdlib/random/base/randu' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scopy = require( '@stdlib/blas/base/scopy' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var ascending = require( './fixtures/ascending.js' ); +var num2str = require( './fixtures/num2str.js' ); + + +// VARIABLES // + +var ssort = tryRequire( resolve( __dirname, './../lib/ssort.native.js' ) ); +var opts = { + 'skip': ( ssort instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof ssort, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', opts, function test( t ) { + t.strictEqual( ssort.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function sorts a strided array (increasing order)', opts, function test( t ) { + var expected; + var x; + var i; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = (randu()*20.0) - 10.0; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array (decreasing order)', opts, function test( t ) { + var expected; + var x; + var i; + var j; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = (randu()*20.0) - 10.0; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array which includes NaNs (increasing order)', opts, function test( t ) { + var expected; + var x; + var v; + var i; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = (randu()*20.0) - 10.0; + } + x[ i ] = v; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array which includes NaNs (decreasing order)', opts, function test( t ) { + var expected; + var x; + var v; + var i; + var j; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = (randu()*20.0) - 10.0; + } + x[ i ] = v; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array which includes positive and negative zeros (increasing order)', opts, function test( t ) { + var expected; + var x; + var v; + var i; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + if ( randu() < 0.5 ) { + v = -0.0; + } else { + v = 0.0; + } + x[ i ] = v; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array which includes positive and negative zeros (decreasing order)', opts, function test( t ) { + var expected; + var x; + var v; + var i; + var j; + + x = new Float32Array( 1e2 ); + for ( i = 0; i < x.length; i++ ) { + if ( randu() < 0.5 ) { + v = -0.0; + } else { + v = 0.0; + } + x[ i ] = v; + } + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array (increasing order; special cases)', opts, function test( t ) { + var expected; + var x; + var i; + + x = new Float32Array( [ NaN, 1.0, -1.0, 2.0, 2.0 ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + + x = new Float32Array( [ 1.0, -1.0, 2.0, 2.0, NaN ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + + x = new Float32Array( [ NaN, 1.0, -1.0, 2.0, 2.0, NaN ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, 1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + if ( isnanf( expected[ i ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } else if ( isNegativeZerof( expected[ i ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[i] )+'.' ); + } else if ( isPositiveZerof( expected[ i ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[i]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ i ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[i]+'.' ); + } + } + t.end(); +}); + +tape( 'the function sorts a strided array (decreasing order; special cases)', opts, function test( t ) { + var expected; + var x; + var i; + var j; + + x = new Float32Array( [ NaN, 1.0, -1.0, 2.0, 2.0 ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + + x = new Float32Array( [ 1.0, -1.0, 2.0, 2.0, NaN ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + + x = new Float32Array( [ NaN, 1.0, -1.0, 2.0, 2.0, NaN ] ); + + // Note: we assume that the built-in sort returns a correctly sorted result + expected = scopy( x.length, x, 1, new Float32Array( x.length ), 1 ); + expected.sort( ascending ); + + ssort( x.length, -1.0, x, 1 ); + for ( i = 0; i < expected.length; i++ ) { + j = expected.length - i - 1; + if ( isnanf( expected[ j ] ) ) { + t.strictEqual( isnanf( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } else if ( isNegativeZerof( expected[ j ] ) ) { + t.strictEqual( isNegativeZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+num2str( expected[j] )+'.' ); + } else if ( isPositiveZerof( expected[ j ] ) ) { + t.strictEqual( isPositiveZerof( x[ i ] ), true, 'returns expected value. index: '+i+'. actual: '+num2str( x[i] )+'. expected: '+expected[j]+'.' ); + } else { + t.strictEqual( x[ i ], expected[ j ], 'returns expected value. index: '+i+' actual: '+x[i]+'. expected: '+expected[j]+'.' ); + } + } + t.end(); +}); + +tape( 'the function returns a reference to the input array', opts, function test( t ) { + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + out = ssort( x.length, 1.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array( [ 3.0, -4.0, 1.0 ] ); + expected = new Float32Array( [ 3.0, -4.0, 1.0 ] ); + + ssort( 0, 1.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + ssort( -4, 1.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `order` equals `0`, the function returns `x` unchanged', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + expected = new Float32Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + + ssort( x.length, 0.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride (increasing order)', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 2.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 2 + ]); + expected = new Float32Array([ + -5.0, // 0 + -3.0, + 2.0, // 1 + 7.0, + 6.0 // 2 + ]); + + ssort( 3, 1.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride (decreasing order)', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 2.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 2 + ]); + expected = new Float32Array([ + 6.0, // 0 + -3.0, + 2.0, // 1 + 7.0, + -5.0 // 2 + ]); + + ssort( 3, -1.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride (increasing order)', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 2.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 0 + ]); + expected = new Float32Array([ + 6.0, // 2 + -3.0, + 2.0, // 1 + 7.0, + -5.0 // 0 + ]); + + ssort( 3, 1.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride (decreasing order)', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 2.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 0 + ]); + expected = new Float32Array([ + -5.0, // 2 + -3.0, + 2.0, // 1 + 7.0, + 6.0 // 0 + ]); + + ssort( 3, -1.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets (increasing order)', opts, function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float32Array([ + 1.0, + -2.0, // 0 + 3.0, + -4.0, // 1 + 5.0, + -6.0 // 2 + ]); + expected = new Float32Array([ + 1.0, + -6.0, // 0 + 3.0, + -4.0, // 1 + 5.0, + -2.0 // 2 + ]); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + ssort( 3, 1.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets (decreasing order)', opts, function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float32Array([ + 1.0, + -6.0, // 0 + 3.0, + -4.0, // 1 + 5.0, + -2.0 // 2 + ]); + expected = new Float32Array([ + 1.0, + -2.0, // 0 + 3.0, + -4.0, // 1 + 5.0, + -6.0 // 2 + ]); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + ssort( 3, -1.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort2ins/benchmark/benchmark.rev_sorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssort2ins/benchmark/benchmark.rev_sorted_few_uniques.native.js index 5c687dc7c4d9..2193167a41a3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssort2ins/benchmark/benchmark.rev_sorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort2ins/benchmark/benchmark.rev_sorted_few_uniques.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float32Array = require( '@stdlib/array/float32' ); var scopy = require( '@stdlib/blas/base/scopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -140,7 +141,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,reverse_sorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,reverse_sorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort2ins/benchmark/benchmark.unsorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssort2ins/benchmark/benchmark.unsorted_random.native.js index ae825765a430..8d5e80ff85b8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssort2ins/benchmark/benchmark.unsorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort2ins/benchmark/benchmark.unsorted_random.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float32Array = require( '@stdlib/array/float32' ); var scopy = require( '@stdlib/blas/base/scopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -130,7 +131,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,random:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort2ins/benchmark/benchmark.unsorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/ssort2ins/benchmark/benchmark.unsorted_random.ndarray.js index 4880fcbeb9d7..9e467b753cbe 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssort2ins/benchmark/benchmark.unsorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort2ins/benchmark/benchmark.unsorted_random.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float32Array = require( '@stdlib/array/float32' ); var scopy = require( '@stdlib/blas/base/scopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ssort2ins = require( './../lib/ndarray.js' ); @@ -120,7 +121,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssort2ins/benchmark/benchmark.unsorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssort2ins/benchmark/benchmark.unsorted_random.ndarray.native.js index f382bb1c08e2..545d7e0206bd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssort2ins/benchmark/benchmark.unsorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssort2ins/benchmark/benchmark.unsorted_random.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float32Array = require( '@stdlib/array/float32' ); var scopy = require( '@stdlib/blas/base/scopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -130,7 +131,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/README.md b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/README.md index 5f0b462a8db9..e46545f83204 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/README.md @@ -30,7 +30,7 @@ limitations under the License. var ssorthp = require( '@stdlib/blas/ext/base/ssorthp' ); ``` -#### ssorthp( N, order, x, stride ) +#### ssorthp( N, order, x, strideX ) Sorts a single-precision floating-point strided array using heapsort. @@ -48,9 +48,9 @@ The function has the following parameters: - **N**: number of indexed elements. - **order**: sort order. If `order < 0.0`, the input strided array is sorted in **decreasing** order. If `order > 0.0`, the input strided array is sorted in **increasing** order. If `order == 0.0`, the input strided array is left unchanged. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment. +- **strideX**: stride length. -The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to sort every other element +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to sort every other element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -77,7 +77,7 @@ ssorthp( 2, -1.0, x1, 2 ); // x0 => [ 1.0, 4.0, 3.0, 2.0 ] ``` -#### ssorthp.ndarray( N, order, x, stride, offset ) +#### ssorthp.ndarray( N, order, x, strideX, offsetX ) Sorts a single-precision floating-point strided array using heapsort and alternative indexing semantics. @@ -92,9 +92,9 @@ ssorthp.ndarray( x.length, 1.0, x, 1, 0 ); The function has the following additional parameters: -- **offset**: starting index. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of the strided array +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -131,13 +131,12 @@ ssorthp.ndarray( 3, 1.0, x, 1, x.length-3 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var ssorthp = require( '@stdlib/blas/ext/base/ssorthp' ); -var rand = discreteUniform( -100, 100 ); -var x = filledarrayBy( 10, 'float32', rand ); - +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); ssorthp( x.length, -1.0, x, -1 ); @@ -150,6 +149,125 @@ console.log( x ); * * * +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/ssorthp.h" +``` + +#### stdlib_strided_ssorthp( N, order, \*X, strideX ) + +Sorts a single-precision floating-point strided array using heapsort. + +```c +float x[] = { 1.0f, -2.0f, 3.0f, -4.0f }; + +stdlib_strided_ssorthp( 2, -1.0f, x, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **order**: `[in] float` sort order. If `order < 0.0`, the input strided array is sorted in **decreasing** order. If `order > 0.0`, the input strided array is sorted in **increasing** order. If `order == 0.0`, the input strided array is left unchanged. +- **X**: `[inout] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +stdlib_strided_ssorthp( const CBLAS_INT N, const float order, float *X, const CBLAS_INT strideX ); +``` + + + +#### stdlib_strided_ssorthp_ndarray( N, order, \*X, strideX, offsetX ) + + + +Sorts a single-precision floating-point strided array using heapsort and alternative indexing semantics. + +```c +float x[] = { 1.0f, -2.0f, 3.0f, -4.0f }; + +stdlib_strided_ssorthp_ndarray( 4, 1.0f, x, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **order**: `[in] float` sort order. If `order < 0.0`, the input strided array is sorted in **decreasing** order. If `order > 0.0`, the input strided array is sorted in **increasing** order. If `order == 0.0`, the input strided array is left unchanged. +- **X**: `[inout] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +stdlib_strided_ssorthp_ndarray( const CBLAS_INT N, const float order, float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/ssorthp.h" +#include + +int main( void ) { + // Create a strided array: + float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; + + // Specify the number of elements: + int N = 8; + + // Specify a stride: + int strideX = 1; + + // Sort the array: + stdlib_strided_ssorthp( N, 1.0f, x, strideX ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "x[ %i ] = %f\n", i, x[ i ] ); + } +} +``` + +
+ + + +
+ + +
## References diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/benchmark/c/unsorted-random/Makefile b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/benchmark/c/unsorted-random/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/benchmark/c/unsorted-random/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/benchmark/c/unsorted-random/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/benchmark/c/unsorted-random/benchmark.length.c new file mode 100644 index 000000000000..f960175e2997 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/benchmark/c/unsorted-random/benchmark.length.c @@ -0,0 +1,195 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ssorthp.h" +#include +#include +#include +#include +#include + +#define NAME "ssorthp" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static float rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + float *x; + double t; + int i; + + x = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float()*20.0f ) - 10.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_strided_ssorthp( len, 1.0f, x, 1 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float *x; + double t; + int i; + + x = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float()*20.0f ) - 10.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_strided_ssorthp_ndarray( len, 1.0f, x, 1, 0 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s::unsorted,random:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s::unsorted,random:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/docs/repl.txt index 39173edee4ff..4e50626363fc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/docs/repl.txt @@ -1,16 +1,15 @@ -{{alias}}( N, order, x, stride ) +{{alias}}( N, order, x, strideX ) Sorts a single-precision floating-point strided array using heapsort. - The `N` and stride parameters determine which elements in the strided - array are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use typed array views. - If `N <= 0` or `order == 0`, the function returns the strided - array unchanged. + If `N <= 0` or `order == 0`, the function returns the strided array + unchanged. The algorithm distinguishes between `-0` and `+0`. When sorted in increasing order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is @@ -42,13 +41,13 @@ x: Float32Array Input array. - stride: integer - Index increment for the strided array. + strideX: integer + Stride length. Returns ------- x: Float32Array - Input array the strided array. + Input array. Examples -------- @@ -71,7 +70,7 @@ [ 1.0, -4.0, 3.0, -2.0 ] -{{alias}}.ndarray( N, order, x, stride, offset ) +{{alias}}.ndarray( N, order, x, strideX, offsetX ) Sorts a single-precision floating-point strided array using heapsort and alternative indexing semantics. @@ -92,11 +91,11 @@ x: Float32Array Input array. - stride: integer - Index increment for the strided array. + strideX: integer + Stride length. - offset: integer - Starting index of the strided array. + offsetX: integer + Starting index. Returns ------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/docs/types/index.d.ts index b18977d731c8..99cd4d4b56ad 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param order - sort order * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns input array * * @example @@ -39,7 +39,7 @@ interface Routine { * ssorthp( x.length, 1, x, 1 ); * // x => [ -4.0, -2.0, 1.0, 3.0 ] */ - ( N: number, order: number, x: Float32Array, stride: number ): Float32Array; + ( N: number, order: number, x: Float32Array, strideX: number ): Float32Array; /** * Sorts a single-precision floating-point strided array using heapsort and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param order - sort order * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns input array * * @example @@ -59,7 +59,7 @@ interface Routine { * ssorthp.ndarray( x.length, 1, x, 1, 0 ); * // x => [ -4.0, -2.0, 1.0, 3.0 ] */ - ndarray( N: number, order: number, x: Float32Array, stride: number, offset: number ): Float32Array; + ndarray( N: number, order: number, x: Float32Array, strideX: number, offsetX: number ): Float32Array; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param order - sort order * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns input array * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/examples/c/example.c index 110f89c05813..1a702e821bf5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/examples/c/example.c @@ -21,7 +21,7 @@ int main( void ) { // Create a strided array: - float x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; // Specify the number of elements: int N = 8; @@ -30,7 +30,7 @@ int main( void ) { int strideX = 1; // Sort the array: - c_ssorthp( N, 1.0f, x, strideX ); + stdlib_strided_ssorthp( N, 1.0f, x, strideX ); // Print the result: for ( int i = 0; i < 8; i++ ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/examples/index.js index d900b4e600ce..5f27e668138e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/examples/index.js @@ -18,13 +18,12 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var ssorthp = require( './../lib' ); -var rand = discreteUniform( -100, 100 ); - -var x = filledarrayBy( 10, 'float32', rand ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); ssorthp( x.length, -1.0, x, -1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/include/stdlib/blas/ext/base/ssorthp.h b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/include/stdlib/blas/ext/base/ssorthp.h index 03550b39a759..2e26b4349ed4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/include/stdlib/blas/ext/base/ssorthp.h +++ b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/include/stdlib/blas/ext/base/ssorthp.h @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -19,7 +19,7 @@ #ifndef STDLIB_BLAS_EXT_BASE_SSORTHP_H #define STDLIB_BLAS_EXT_BASE_SSORTHP_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Sorts a single-precision floating-point strided array using heapsort. */ -void c_ssorthp( const int64_t N, const float order, float *X, const int64_t stride ); +void API_SUFFIX(stdlib_strided_ssorthp)( const CBLAS_INT N, const float order, float *X, const CBLAS_INT strideX ); + +/** +* Sorts a single-precision floating-point strided array using heapsort and alternative indexing semantics. +*/ +void API_SUFFIX(stdlib_strided_ssorthp_ndarray)( const CBLAS_INT N, const float order, float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/lib/ndarray.js index 6bb464f6bf9f..6aee88a259fa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/lib/ndarray.js @@ -42,8 +42,8 @@ var floor = require( '@stdlib/math/base/special/floor' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} order - sort order * @param {Float32Array} x - input array -* @param {integer} stride - index increment -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {Float32Array} input array * * @example @@ -54,7 +54,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); * ssorthp( x.length, 1.0, x, 1, 0 ); * // x => [ -4.0, -2.0, 1.0, 3.0 ] */ -function ssorthp( N, order, x, stride, offset ) { +function ssorthp( N, order, x, strideX, offsetX ) { var parent; var child; var v1; @@ -70,8 +70,8 @@ function ssorthp( N, order, x, stride, offset ) { } // For a positive stride, sorting in decreasing order is equivalent to providing a negative stride and sorting in increasing order, and, for a negative stride, sorting in decreasing order is equivalent to providing a positive stride and sorting in increasing order... if ( order < 0.0 ) { - stride *= -1; - offset -= (N-1) * stride; + strideX *= -1; + offsetX -= (N-1) * strideX; } // Set the initial heap size: n = N; @@ -84,7 +84,7 @@ function ssorthp( N, order, x, stride, offset ) { if ( parent > 0 ) { // We need to build the heap... parent -= 1; - t = x[ offset+(parent*stride) ]; + t = x[ offsetX+(parent*strideX) ]; } else { // Reduce the heap size: n -= 1; @@ -94,11 +94,11 @@ function ssorthp( N, order, x, stride, offset ) { return x; } // Store the last heap value in a temporary variable in order to make room for the heap root being placed into its sorted position: - i = offset + (n*stride); + i = offsetX + (n*strideX); t = x[ i ]; // Move the heap root to its sorted position: - x[ i ] = x[ offset ]; + x[ i ] = x[ offsetX ]; } // We need to "sift down", pushing `t` down the heap to in order to replace the parent and satisfy the heap property... @@ -112,8 +112,8 @@ function ssorthp( N, order, x, stride, offset ) { // Find the largest child... k = child + 1; if ( k < n ) { - v1 = x[ offset+(k*stride) ]; - v2 = x[ offset+(child*stride) ]; + v1 = x[ offsetX+(k*strideX) ]; + v2 = x[ offsetX+(child*strideX) ]; // Check if a "right" child exists and is "bigger"... if ( v1 > v2 || isnanf( v1 ) || (v1 === v2 && isPositiveZerof( v1 ) ) ) { // eslint-disable-line max-len @@ -121,10 +121,10 @@ function ssorthp( N, order, x, stride, offset ) { } } // Check if the largest child is bigger than `t`... - v1 = x[ offset+(child*stride) ]; + v1 = x[ offsetX+(child*strideX) ]; if ( v1 > t || isnanf( v1 ) || ( v1 === t && isPositiveZerof( v1 ) ) ) { // eslint-disable-line max-len // Insert the larger child value: - x[ offset+(j*stride) ] = v1; + x[ offsetX+(j*strideX) ] = v1; // Update `j` to point to the child index: j = child; @@ -137,7 +137,7 @@ function ssorthp( N, order, x, stride, offset ) { } } // Insert `t` into the heap: - x[ offset+(j*stride) ] = t; + x[ offsetX+(j*strideX) ] = t; } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/lib/ndarray.native.js index 21a73e687cfa..c7e19218d27b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var offsetView = require( '@stdlib/strided/base/offset-view' ); -var addon = require( './ssorthp.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,8 +31,8 @@ var addon = require( './ssorthp.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} order - sort order * @param {Float32Array} x - input array -* @param {integer} stride - index increment -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {Float32Array} input array * * @example @@ -43,15 +42,8 @@ var addon = require( './ssorthp.native.js' ); * * ssorthp( x.length, 1.0, x, 1, 0 ); */ -function ssorthp( N, order, x, stride, offset ) { - var view; - if ( stride < 0 ) { - order *= -1.0; - stride *= -1; - offset -= (N-1) * stride; - } - view = offsetView( x, offset ); - addon( N, order, view, stride ); +function ssorthp( N, order, x, strideX, offsetX ) { + addon.ndarray( N, order, x, strideX, offsetX ); return x; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/lib/ssorthp.js b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/lib/ssorthp.js index 1ec750b5dec1..4aae02791973 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/lib/ssorthp.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/lib/ssorthp.js @@ -20,9 +20,8 @@ // MODULES // -var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); -var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); -var floor = require( '@stdlib/math/base/special/floor' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -42,7 +41,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} order - sort order * @param {Float32Array} x - input array -* @param {integer} stride - index increment +* @param {integer} strideX - stride length * @returns {Float32Array} input array * * @example @@ -53,96 +52,8 @@ var floor = require( '@stdlib/math/base/special/floor' ); * ssorthp( x.length, 1.0, x, 1 ); * // x => [ -4.0, -2.0, 1.0, 3.0 ] */ -function ssorthp( N, order, x, stride ) { - var offset; - var parent; - var child; - var v1; - var v2; - var n; - var t; - var i; - var j; - var k; - - if ( N <= 0 || order === 0.0 ) { - return x; - } - // For a positive stride, sorting in decreasing order is equivalent to providing a negative stride and sorting in increasing order, and, for a negative stride, sorting in decreasing order is equivalent to providing a positive stride and sorting in increasing order... - if ( order < 0.0 ) { - stride *= -1; - } - if ( stride < 0 ) { - offset = (1-N) * stride; - } else { - offset = 0; - } - // Set the initial heap size: - n = N; - - // Specify an initial "parent" index for building the heap: - parent = floor( N / 2 ); - - // Continue looping until the array is sorted... - while ( true ) { - if ( parent > 0 ) { - // We need to build the heap... - parent -= 1; - t = x[ offset+(parent*stride) ]; - } else { - // Reduce the heap size: - n -= 1; - - // Check if the heap is empty, and, if so, we are finished sorting... - if ( n === 0 ) { - return x; - } - // Store the last heap value in a temporary variable in order to make room for the heap root being placed into its sorted position: - i = offset + (n*stride); - t = x[ i ]; - - // Move the heap root to its sorted position: - x[ i ] = x[ offset ]; - } - // We need to "sift down", pushing `t` down the heap to in order to replace the parent and satisfy the heap property... - - // Start at the parent index: - j = parent; - - // Get the "left" child index: - child = (j*2) + 1; - - while ( child < n ) { - // Find the largest child... - k = child + 1; - if ( k < n ) { - v1 = x[ offset+(k*stride) ]; - v2 = x[ offset+(child*stride) ]; - - // Check if a "right" child exists and is "bigger"... - if ( v1 > v2 || isnanf( v1 ) || (v1 === v2 && isPositiveZerof( v1 ) ) ) { // eslint-disable-line max-len - child += 1; - } - } - // Check if the largest child is bigger than `t`... - v1 = x[ offset+(child*stride) ]; - if ( v1 > t || isnanf( v1 ) || ( v1 === t && isPositiveZerof( v1 ) ) ) { // eslint-disable-line max-len - // Insert the larger child value: - x[ offset+(j*stride) ] = v1; - - // Update `j` to point to the child index: - j = child; - - // Get the "left" child index and repeat... - child = (j*2) + 1; - } else { - // We've found `t`'s place in the heap... - break; - } - } - // Insert `t` into the heap: - x[ offset+(j*stride) ] = t; - } +function ssorthp( N, order, x, strideX ) { + return ndarray( N, order, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/lib/ssorthp.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/lib/ssorthp.native.js index e8e603fa785a..8319808d9079 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/lib/ssorthp.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/lib/ssorthp.native.js @@ -31,7 +31,7 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} order - sort order * @param {Float32Array} x - input array -* @param {integer} stride - index increment +* @param {integer} strideX - stride length * @returns {Float32Array} input array * * @example @@ -42,8 +42,8 @@ var addon = require( './../src/addon.node' ); * ssorthp( x.length, 1.0, x, 1 ); * // x => [ -4.0, -2.0, 1.0, 3.0 ] */ -function ssorthp( N, order, x, stride ) { - addon( N, order, x, stride ); +function ssorthp( N, order, x, strideX ) { + addon( N, order, x, strideX ); return x; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/manifest.json index 7452140b7fe3..4ca8ce4ed4f5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/manifest.json @@ -1,5 +1,7 @@ { - "options": {}, + "options": { + "task": "build" + }, "fields": [ { "field": "src", @@ -24,24 +26,59 @@ ], "confs": [ { + "task": "build", "src": [ - "./src/ssorthp.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nanf", - "@stdlib/math/base/assert/is-positive-zerof", "@stdlib/napi/export", "@stdlib/napi/argv", - "@stdlib/napi/argv-float", "@stdlib/napi/argv-int64", - "@stdlib/napi/argv-strided-float32array" + "@stdlib/napi/argv-float", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-positive-zerof", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-positive-zerof", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-positive-zerof", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" ] } ] diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/src/addon.c index b7dd6f4ce6ba..26f5ead8afea 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/src/addon.c @@ -35,10 +35,28 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_FLOAT( env, order, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); - c_ssorthp( N, order, X, stride ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + API_SUFFIX(stdlib_strided_ssorthp)( N, order, X, strideX ); return NULL; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_FLOAT( env, order, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + API_SUFFIX(stdlib_strided_ssorthp_ndarray)( N, order, X, strideX, offsetX ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/src/ssorthp.c b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/src/main.c similarity index 63% rename from lib/node_modules/@stdlib/blas/ext/base/ssorthp/src/ssorthp.c rename to lib/node_modules/@stdlib/blas/ext/base/ssorthp/src/main.c index f1fd6121ed73..9c1c58b683bb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssorthp/src/ssorthp.c +++ b/lib/node_modules/@stdlib/blas/ext/base/ssorthp/src/main.c @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -19,8 +19,8 @@ #include "stdlib/blas/ext/base/ssorthp.h" #include "stdlib/math/base/assert/is_positive_zerof.h" #include "stdlib/math/base/assert/is_nanf.h" -#include -#include +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" /** * Sorts a single-precision floating-point strided array using heapsort. @@ -34,20 +34,43 @@ * - Williams, John William Joseph. 1964. "Algorithm 232: Heapsort." _Communications of the ACM_ 7 (6). New York, NY, USA: Association for Computing Machinery: 347–49. doi:[10.1145/512274.512284](https://doi.org/10.1145/512274.512284). * - Floyd, Robert W. 1964. "Algorithm 245: Treesort." _Communications of the ACM_ 7 (12). New York, NY, USA: Association for Computing Machinery: 701. doi:[10.1145/355588.365103](https://doi.org/10.1145/355588.365103). * -* @param N number of indexed elements -* @param order sort order -* @param X input array -* @param stride index increment +* @param N number of indexed elements +* @param order sort order +* @param X input array +* @param strideX stride length */ -void c_ssorthp( const int64_t N, const float order, float *X, const int64_t stride ) { - int64_t offset; - int64_t parent; - int64_t child; - int64_t sx; - int64_t n; - int64_t i; - int64_t j; - int64_t k; +void API_SUFFIX(stdlib_strided_ssorthp)( const CBLAS_INT N, const float order, float *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + API_SUFFIX(stdlib_strided_ssorthp_ndarray)( N, order, X, strideX, ox ); +} + +/** +* Sorts a single-precision floating-point strided array using heapsort and alternative indexing semantics. +* +* ## Notes +* +* - This implementation uses an in-place algorithm derived from the work of Floyd (1964). +* +* ## References +* +* - Williams, John William Joseph. 1964. "Algorithm 232: Heapsort." _Communications of the ACM_ 7 (6). New York, NY, USA: Association for Computing Machinery: 347–49. doi:[10.1145/512274.512284](https://doi.org/10.1145/512274.512284). +* - Floyd, Robert W. 1964. "Algorithm 245: Treesort." _Communications of the ACM_ 7 (12). New York, NY, USA: Association for Computing Machinery: 701. doi:[10.1145/355588.365103](https://doi.org/10.1145/355588.365103). +* +* @param N number of indexed elements +* @param order sort order +* @param X input array +* @param strideX stride length +* @param offsetX starting index +*/ +void API_SUFFIX(stdlib_strided_ssorthp_ndarray)( const CBLAS_INT N, const float order, float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT parent; + CBLAS_INT child; + CBLAS_INT ox; + CBLAS_INT sx; + CBLAS_INT n; + CBLAS_INT i; + CBLAS_INT j; + CBLAS_INT k; float v1; float v2; float t; @@ -57,27 +80,24 @@ void c_ssorthp( const int64_t N, const float order, float *X, const int64_t stri } // For a positive stride, sorting in decreasing order is equivalent to providing a negative stride and sorting in increasing order, and, for a negative stride, sorting in decreasing order is equivalent to providing a positive stride and sorting in increasing order... if ( order < 0.0f ) { - sx = -stride; - } else { - sx = stride; - } - if ( sx < 0 ) { - offset = (1-N) * sx; + sx = -strideX; + ox = offsetX - ( (N-1)*sx ); } else { - offset = 0; + sx = strideX; + ox = offsetX; } // Set the initial heap size: n = N; // Specify an initial "parent" index for building the heap: - parent = floorf( N / 2 ); + parent = N / 2; // Continue looping until the array is sorted... while ( true ) { if ( parent > 0 ) { // We need to build the heap... parent -= 1; - t = X[ offset+(parent*sx) ]; + t = X[ ox+(parent*sx) ]; } else { // Reduce the heap size: n -= 1; @@ -87,11 +107,11 @@ void c_ssorthp( const int64_t N, const float order, float *X, const int64_t stri return; } // Store the last heap value in a temporary variable in order to make room for the heap root being placed into its sorted position: - i = offset + (n*sx); + i = ox + (n*sx); t = X[ i ]; // Move the heap root to its sorted position: - X[ i ] = X[ offset ]; + X[ i ] = X[ ox ]; } // We need to "sift down", pushing `t` down the heap to in order to replace the parent and satisfy the heap property... @@ -105,8 +125,8 @@ void c_ssorthp( const int64_t N, const float order, float *X, const int64_t stri // Find the largest child... k = child + 1; if ( k < n ) { - v1 = X[ offset+(k*sx) ]; - v2 = X[ offset+(child*sx) ]; + v1 = X[ ox+(k*sx) ]; + v2 = X[ ox+(child*sx) ]; // Check if a "right" child exists and is "bigger"... if ( v1 > v2 || stdlib_base_is_nanf( v1 ) || (v1 == v2 && stdlib_base_is_positive_zerof( v1 ) ) ) { @@ -114,10 +134,10 @@ void c_ssorthp( const int64_t N, const float order, float *X, const int64_t stri } } // Check if the largest child is bigger than `t`... - v1 = X[ offset+(child*sx) ]; + v1 = X[ ox+(child*sx) ]; if ( v1 > t || stdlib_base_is_nanf( v1 ) || ( v1 == t && stdlib_base_is_positive_zerof( v1 ) ) ) { // Insert the larger child value: - X[ offset+(j*sx) ] = v1; + X[ ox+(j*sx) ] = v1; // Update `j` to point to the child index: j = child; @@ -130,6 +150,6 @@ void c_ssorthp( const int64_t N, const float order, float *X, const int64_t stri } } // Insert `t` into the heap: - X[ offset+(j*sx) ] = t; + X[ ox+(j*sx) ] = t; } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_few_uniques.js b/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_few_uniques.js index db78e14da8a8..6125adea3505 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_few_uniques.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_few_uniques.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float32Array = require( '@stdlib/array/float32' ); var scopy = require( '@stdlib/blas/base/scopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ssortins = require( './../lib/ssortins.js' ); @@ -120,7 +121,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_few_uniques.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_few_uniques.native.js index b562e6d9c631..359b3532585f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_few_uniques.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_few_uniques.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float32Array = require( '@stdlib/array/float32' ); var scopy = require( '@stdlib/blas/base/scopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -130,7 +131,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,few_uniques:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,few_uniques:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_few_uniques.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_few_uniques.ndarray.js index bc0dab63fad1..98c6e1b9fcf6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_few_uniques.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_few_uniques.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float32Array = require( '@stdlib/array/float32' ); var scopy = require( '@stdlib/blas/base/scopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ssortins = require( './../lib/ndarray.js' ); @@ -120,7 +121,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,few_uniques:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,few_uniques:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js index e9cf1a3419a5..25206b7f93df 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_few_uniques.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float32Array = require( '@stdlib/array/float32' ); var scopy = require( '@stdlib/blas/base/scopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -130,7 +131,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,few_uniques:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,few_uniques:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_random.js b/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_random.js index 40aa24c5a2ed..3ce5211ce6cb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_random.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_random.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float32Array = require( '@stdlib/array/float32' ); var scopy = require( '@stdlib/blas/base/scopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ssortins = require( './../lib/ssortins.js' ); @@ -117,7 +118,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:len='+len, opts, f ); + bench( format( '%s::unsorted,random:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_random.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_random.native.js index 78481e510d98..feb34c748501 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_random.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_random.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float32Array = require( '@stdlib/array/float32' ); var scopy = require( '@stdlib/blas/base/scopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -127,7 +128,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,random:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,random:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_random.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_random.ndarray.js index 8c4d0cb34854..0f2911837d1d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_random.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_random.ndarray.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float32Array = require( '@stdlib/array/float32' ); var scopy = require( '@stdlib/blas/base/scopy' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ssortins = require( './../lib/ndarray.js' ); @@ -117,7 +118,7 @@ function main() { opts = { 'iterations': iter }; - bench( pkg+'::unsorted,random:ndarray:len='+len, opts, f ); + bench( format( '%s::unsorted,random:ndarray:len=%d', pkg, len ), opts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_random.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_random.ndarray.native.js index a17a9c9571ae..67698116ecd8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_random.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssortins/benchmark/benchmark.unsorted_random.ndarray.native.js @@ -30,6 +30,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var Float32Array = require( '@stdlib/array/float32' ); var scopy = require( '@stdlib/blas/base/scopy' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -127,7 +128,7 @@ function main() { 'skip': opts.skip, 'iterations': iter }; - bench( pkg+'::native,unsorted,random:ndarray:len='+len, bopts, f ); + bench( format( '%s::native,unsorted,random:ndarray:len=%d', pkg, len ), bopts, f ); iter = floor( sqrt( iter ) ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.js index d0ec73c2d599..903f209fa0d1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapx = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.module.js index aa55ff1b329e..cffc2feeabe9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapx = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.module.main.js index 766eb0d973ed..0f979c83a6d0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapx = require( './../lib' ); @@ -128,7 +129,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.module.ndarray.js index 7588c497f90d..9b0c28b38959 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapx = require( './../lib' ); @@ -128,7 +129,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.ndarray.js index 281e340778e5..e320b4e47f2e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapx = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.js index 4c8a0be908af..12b88710fb26 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsum = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.module.js index 37291ba60edd..7b1d4cb6a06b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsum = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.module.main.js index 1e12235dc0fb..4c52c9cc1549 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsum = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.module.ndarray.js index 1e68c773752f..dc1310f41b91 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsum = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.ndarray.js index 05394325ac47..ac2ee472f83e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsum = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.js index b10ac5d3b102..1a6614d60eb5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsumkbn = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.module.js index 1110f8893ccd..e30939da277a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsumkbn = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.module.main.js index 7463536cf3fa..dc861d34c8e7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsumkbn = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.module.ndarray.js index 1530dc8217fc..ceabc538bdd4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsumkbn = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.ndarray.js index 32ccd8d59bbf..e48c0821b099 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsumkbn = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.js index 91a73bdacf4f..35cb2176cf7f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsumors = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.module.js index 9f3364544db5..f0882a0040f1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsumors = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.module.main.js index fb945bbab747..95122777d4e6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsumors = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.module.ndarray.js index 7a59c43463fe..5909dfa29027 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsumors = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.ndarray.js index dc30f7cffe82..6063570ebbda 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsumors = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.js index f388fb79b85c..4eed8dde4a64 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsumpw = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.module.js index 053718bfccae..d147e2db1245 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsumpw = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.module.main.js index b3086b0e1066..42929105664e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsumpw = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.module.ndarray.js index e9d4b0d86bff..aa5eb50d9334 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsumpw = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.ndarray.js index a2f9795230e0..14e6f5f4cbac 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dapxsumpw = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.js index d1f88fe0f7bf..7062995903ac 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dasumpw = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.module.js index 19710a193bcc..d3feb5f1a9aa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dasumpw = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.module.main.js index cfc4c893097c..924fbf7feec8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dasumpw = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.module.ndarray.js index 417574c7d0c2..c36be3a6c4c1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dasumpw = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.ndarray.js index 9501f7a71edb..beffb2900dbd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dasumpw = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.js index fda2315b1fa5..150d653483b5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanasumors = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.module.js index ed26cfaccc42..3417796d6f04 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanasumors = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.module.main.js index 424314eb70c4..a5b9cd3a0bce 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanasumors = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.module.ndarray.js index 6827347bc9d2..ad544a3005e5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanasumors = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.ndarray.js index 6ae3b7d862c4..9e0abbbf2aa7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanasumors = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.js index ee021220341f..319cb245344b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.js @@ -27,6 +27,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumkbn2 = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.module.js index 4d342b073f3a..cee7a5e87948 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumkbn2 = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.module.main.js index 705d61aa7c93..815b5788de79 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.module.main.js @@ -29,6 +29,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumkbn2 = require( './../lib' ); @@ -138,7 +139,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.module.ndarray.js index ea2ded100cdf..74cad82aa086 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.module.ndarray.js @@ -29,6 +29,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumkbn2 = require( './../lib' ); @@ -138,7 +139,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.ndarray.js index ffd49ea6e7a0..476bd7df6d4f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumkbn2 = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.js index 88ce6e333bd5..371a3adcf330 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumpw = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.module.js index a4ceff2ffa3e..b1e8c3b83766 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumpw = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.module.main.js index 4aeb774d0da1..9e6dfff7c876 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumpw = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.module.ndarray.js index c6d9925dd076..2a5e85d6b612 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumpw = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.ndarray.js index 5b6573c105f7..e2d937ca92a8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnansumpw = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.js index d54d9c280193..c3d2297528d4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapxsumkbn = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.module.js index 6fe977de909a..09b4a1b4909c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapxsumkbn = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.module.main.js index 705e4f531068..74f5c46098ee 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapxsumkbn = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.module.ndarray.js index 29c36aee1353..1f0ee9d6cc6a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapxsumkbn = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.ndarray.js index c5a45d3ebd8a..717a8becd94f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sapxsumkbn = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-row/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-row/docs/types/index.d.ts index 9e382bc26964..fb5e15155a68 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-row/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-row/docs/types/index.d.ts @@ -47,8 +47,8 @@ interface Routine { * @returns row index * * @example - * var Complex128Array = require( `@stdlib/array/complex128` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Complex128Array( [ 1.0, 0.0, 2.0, 0.0, 0.0, 0.0, 3.0, 0.0, 4.0, 0.0, 0.0, 0.0 ] ); * var x = new Complex128Array( [ 2.0, 0.0, 4.0, 0.0 ] ); @@ -82,8 +82,8 @@ interface Routine { * @returns row index * * @example - * var Complex128Array = require( `@stdlib/array/complex128` ); - * var Uint8Array = require( `@stdlib/array/uint8` ); + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Complex128Array( [ 1.0, 0.0, 2.0, 0.0, 0.0, 0.0, 3.0, 0.0, 4.0, 0.0, 0.0, 0.0 ] ); * var x = new Complex128Array( [ 2.0, 0.0, 4.0, 0.0 ] ); @@ -115,8 +115,8 @@ interface Routine { * @returns row index * * @example -* var Complex128Array = require( `@stdlib/array/complex128` ); -* var Uint8Array = require( `@stdlib/array/uint8` ); +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Complex128Array( [ 1.0, 0.0, 2.0, 0.0, 0.0, 0.0, 3.0, 0.0, 4.0, 0.0, 0.0, 0.0 ] ); * var x = new Complex128Array( [ 2.0, 0.0, 4.0, 0.0 ] ); @@ -126,8 +126,8 @@ interface Routine { * // returns 1 * * @example -* var Complex128Array = require( `@stdlib/array/complex128` ); -* var Uint8Array = require( `@stdlib/array/uint8` ); +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Uint8Array = require( '@stdlib/array/uint8' ); * * var A = new Complex128Array( [ 1.0, 0.0, 2.0, 0.0, 0.0, 0.0, 3.0, 0.0, 4.0, 0.0, 0.0, 0.0 ] ); * var x = new Complex128Array( [ 2.0, 0.0, 4.0, 0.0 ] ); diff --git a/lib/node_modules/@stdlib/blas/ext/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/docs/types/index.d.ts index 508c9dd61683..8b96e61c9970 100644 --- a/lib/node_modules/@stdlib/blas/ext/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/docs/types/index.d.ts @@ -21,15 +21,18 @@ /* eslint-disable max-lines */ import base = require( '@stdlib/blas/ext/base' ); +import circshift = require( '@stdlib/blas/ext/circshift' ); import cusum = require( '@stdlib/blas/ext/cusum' ); import findIndex = require( '@stdlib/blas/ext/find-index' ); import findLastIndex = require( '@stdlib/blas/ext/find-last-index' ); import indexOf = require( '@stdlib/blas/ext/index-of' ); +import join = require( '@stdlib/blas/ext/join' ); import lastIndexOf = require( '@stdlib/blas/ext/last-index-of' ); import linspace = require( '@stdlib/blas/ext/linspace' ); import sorthp = require( '@stdlib/blas/ext/sorthp' ); import sum = require( '@stdlib/blas/ext/sum' ); import toSortedhp = require( '@stdlib/blas/ext/to-sortedhp' ); +import zeroTo = require( '@stdlib/blas/ext/zero-to' ); /** * Interface describing the `ext` namespace. @@ -40,6 +43,35 @@ interface Namespace { */ base: typeof base; + /** + * Circularly shifts the elements of an input ndarray by a specified number of positions along one or more ndarray dimensions. + * + * ## Notes + * + * - The input ndarray is shifted **in-place** (i.e., the input ndarray is **mutated**). + * - When shifting elements along a single dimension, a positive `k` shifts elements to the right (toward higher indices), and a negative `k` shifts elements to the left (toward lower indices). If `k` is zero, the input ndarray is left unchanged. + * + * @param x - input ndarray + * @param k - number of positions to shift + * @param options - function options + * @returns input ndarray + * + * @example + * var array = require( '@stdlib/ndarray/array' ); + * + * var x = array( [ 1.0, 2.0, 3.0, 4.0 ], { + * 'shape': [ 2, 2 ], + * 'order': 'row-major' + * }); + * // returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] + * + * var y = ns.circshift( x, 1, { + * 'dims': [ 0 ] + * }); + * // returns [ [ 3.0, 4.0 ], [ 1.0, 2.0 ] ] + */ + circshift: typeof circshift; + /** * Computes the cumulative sum along one or more ndarray dimensions. * @@ -215,6 +247,40 @@ interface Namespace { */ indexOf: typeof indexOf; + /** + * Returns an ndarray created by joining elements using a separator along one or more ndarray dimensions. + * + * @param x - input ndarray + * @param options - function options + * @returns output ndarray + * + * @example + * var array = require( '@stdlib/ndarray/array' ); + * + * var x = array( [ 1.0, 2.0, 3.0 ] ); + * + * var y = ns.join( x ); + * // returns [ '1,2,3' ] + * + * @example + * var empty = require( '@stdlib/ndarray/empty' ); + * var array = require( '@stdlib/ndarray/array' ); + * + * var x = array( [ 1.0, 2.0, 3.0 ], { + * 'dtype': 'generic' + * }); + * var y = empty( [], { + * 'dtype': 'generic' + * }); + * + * var out = ns.join.assign( x, y ); + * // returns [ '1,2,3' ] + * + * var bool = ( out === y ); + * // returns true + */ + join: typeof join; + /** * Returns the last index of a specified search element along an ndarray dimension. * @@ -270,29 +336,20 @@ interface Namespace { * @param options - function options * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); - * * var out = ns.linspace( [ 2, 4 ], 0.0, 3.0 ); - * // returns - * - * var arr = ndarray2array( out ); - * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] + * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] * * @example * var zeros = require( '@stdlib/ndarray/zeros' ); - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); * * var x = zeros( [ 2, 4 ] ); * // returns * * var out = ns.linspace.assign( x, 0.0, 3.0 ); - * // returns + * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] * * var bool = ( out === x ); * // returns true - * - * var arr = ndarray2array( out ); - * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] */ linspace: typeof linspace; @@ -422,6 +479,31 @@ interface Namespace { * // returns true */ toSortedhp: typeof toSortedhp; + + /** + * Returns a new ndarray filled with linearly spaced numeric elements which increment by 1 starting from zero along one or more ndarray dimensions. + * + * @param shape - array shape + * @param options - function options + * @returns output ndarray + * + * @example + * var out = ns.zeroTo( [ 2, 3 ] ); + * // returns [ [ 0.0, 1.0, 2.0 ], [ 0.0, 1.0, 2.0 ] ] + * + * @example + * var zeros = require( '@stdlib/ndarray/zeros' ); + * + * var x = zeros( [ 2, 3 ] ); + * // returns [ [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ] ] + * + * var out = ns.zeroTo.assign( x ); + * // returns [ [ 0.0, 1.0, 2.0 ], [ 0.0, 1.0, 2.0 ] ] + * + * var bool = ( out === x ); + * // returns true + */ + zeroTo: typeof zeroTo; } /** diff --git a/lib/node_modules/@stdlib/blas/ext/find-index/README.md b/lib/node_modules/@stdlib/blas/ext/find-index/README.md index 6611c05dade8..70ea5efca68a 100644 --- a/lib/node_modules/@stdlib/blas/ext/find-index/README.md +++ b/lib/node_modules/@stdlib/blas/ext/find-index/README.md @@ -47,10 +47,7 @@ var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); // Perform operation: var out = findIndex( x, isEven ); -// returns - -var idx = out.get(); -// returns 1 +// returns [ 1 ] ``` The function has the following parameters: @@ -84,10 +81,7 @@ var ctx = { 'count': 0 }; var out = findIndex( x, isEven, ctx ); -// returns - -var idx = out.get(); -// returns 1 +// returns [ 1 ] var count = ctx.count; // returns 2 @@ -114,16 +108,12 @@ var x = array( [ 1.0, 3.0, 5.0, 7.0 ] ); // Perform operation: var out = findIndex( x, isEven ); -// returns - -var idx = out.get(); -// returns -1 +// returns [ -1 ] ``` By default, the function performs the operation over elements in the last dimension. To perform the operation over a different dimension, provide a `dim` option. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); function isEven( v ) { @@ -137,17 +127,13 @@ var opts = { }; var out = findIndex( x, opts, isEven ); -// returns - -var idx = ndarray2array( out ); -// returns [ -1, 0 ] +// returns [ -1, 0 ] ``` By default, the function excludes reduced dimensions from the output [ndarray][@stdlib/ndarray/ctor]. To include the reduced dimensions as singleton dimensions, set the `keepdims` option to `true`. ```javascript var array = require( '@stdlib/ndarray/array' ); -var ndarray2array = require( '@stdlib/ndarray/to-array' ); function isEven( v ) { return v % 2.0 === 0.0; @@ -161,10 +147,7 @@ var opts = { }; var out = findIndex( x, opts, isEven ); -// returns - -var idx = ndarray2array( out ); -// returns [ [ -1, 0 ] ] +// returns [ [ -1, 0 ] ] ``` By default, the function returns an [ndarray][@stdlib/ndarray/ctor] having a [data type][@stdlib/ndarray/dtypes] determined by the function's output data type [policy][@stdlib/ndarray/output-dtype-policies]. To override the default behavior, set the `dtype` option. @@ -184,7 +167,7 @@ var opts = { }; var idx = findIndex( x, opts, isEven ); -// returns +// returns [ 1 ] var dt = dtype( idx ); // returns 'generic' @@ -208,10 +191,7 @@ var y = zeros( [], { }); var out = findIndex.assign( x, y, isEven ); -// returns - -var idx = out.get(); -// returns 1 +// returns [ 1 ] var bool = ( out === y ); // returns true diff --git a/lib/node_modules/@stdlib/blas/ext/find-index/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/find-index/docs/repl.txt index 2868eaadb233..56c183c4dd5a 100644 --- a/lib/node_modules/@stdlib/blas/ext/find-index/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/find-index/docs/repl.txt @@ -51,9 +51,8 @@ -------- > var x = {{alias:@stdlib/ndarray/array}}( [ -1.0, 2.0, -3.0, -4.0 ] ); > function clbk( v ) { return v % 2.0 === 0.0; }; - > var y = {{alias}}( x, clbk ); - > var v = y.get() - 1 + > var y = {{alias}}( x, clbk ) + [ 1 ] {{alias}}.assign( x, out[, options], clbk[, thisArg] ) @@ -107,11 +106,9 @@ > var out = {{alias:@stdlib/ndarray/zeros}}( [] ); > function clbk( v ) { return v % 2.0 === 0.0; }; > var y = {{alias}}.assign( x, out, clbk ) - + [ 1 ] > var bool = ( out === y ) true - > var v = out.get() - 1 See Also -------- diff --git a/lib/node_modules/@stdlib/blas/ext/find-index/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/find-index/docs/types/index.d.ts index f2253a6ed413..193aa35cad2a 100644 --- a/lib/node_modules/@stdlib/blas/ext/find-index/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/find-index/docs/types/index.d.ts @@ -131,10 +131,7 @@ interface FindIndex { * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = findIndex( x, clbk ); - * // returns - * - * var v = y.get(); - * // returns 1 + * // returns [ 1 ] */ = InputArray, ThisArg = unknown>( x: U, clbk: Predicate, thisArg?: ThisParameterType> ): OutputArray; @@ -161,10 +158,7 @@ interface FindIndex { * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = findIndex( x, {}, clbk ); - * // returns - * - * var v = y.get(); - * // returns 1 + * // returns [ 1 ] */ = InputArray, ThisArg = unknown>( x: U, options: Options, clbk: Predicate, thisArg?: ThisParameterType> ): OutputArray; @@ -193,10 +187,7 @@ interface FindIndex { * var y = zeros( [] ); * * var out = findIndex.assign( x, y, clbk ); - * // returns - * - * var v = out.get(); - * // returns 1 + * // returns [ 1 ] * * var bool = ( out === y ); * // returns true @@ -229,10 +220,7 @@ interface FindIndex { * var y = zeros( [] ); * * var out = findIndex.assign( x, y, {}, clbk ); - * // returns - * - * var v = out.get(); - * // returns 1 + * // returns [ 1 ] * * var bool = ( out === y ); * // returns true @@ -263,10 +251,7 @@ interface FindIndex { * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = findIndex( x, clbk ); -* // returns -* -* var v = y.get(); -* // returns 1 +* // returns [ 1 ] * * @example * var array = require( '@stdlib/ndarray/array' ); @@ -280,10 +265,7 @@ interface FindIndex { * var y = zeros( [] ); * * var out = findIndex.assign( x, y, clbk ); -* // returns -* -* var v = out.get(); -* // returns 1 +* // returns [ 1 ] * * var bool = ( out === y ); * // returns true diff --git a/lib/node_modules/@stdlib/blas/ext/find-index/lib/assign.js b/lib/node_modules/@stdlib/blas/ext/find-index/lib/assign.js index 94efbfb2571b..ebe52c62c871 100644 --- a/lib/node_modules/@stdlib/blas/ext/find-index/lib/assign.js +++ b/lib/node_modules/@stdlib/blas/ext/find-index/lib/assign.js @@ -52,7 +52,6 @@ var base = require( './base.js' ).assign; * * @example * var zeros = require( '@stdlib/ndarray/zeros' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * * function isEven( v ) { @@ -81,13 +80,10 @@ var base = require( './base.js' ).assign; * * // Perform operation: * var out = assign( x, y, isEven ); -* // returns +* // returns [ 1, 0 ] * * var bool = ( out === y ); * // returns true -* -* var arr = ndarray2array( out ); -* // returns [ 1, 0 ] */ function assign( x, out ) { var hasOptions; diff --git a/lib/node_modules/@stdlib/blas/ext/find-index/lib/base.js b/lib/node_modules/@stdlib/blas/ext/find-index/lib/base.js index 076a81f35a6f..7be8c1bf06a8 100644 --- a/lib/node_modules/@stdlib/blas/ext/find-index/lib/base.js +++ b/lib/node_modules/@stdlib/blas/ext/find-index/lib/base.js @@ -83,10 +83,7 @@ var table = { * * // Perform operation: * var out = findIndex( x, isEven ); -* // returns -* -* var idx = out.get(); -* // returns 1 +* // returns [ 1 ] */ var findIndex = factory( table, [ idtypes ], odtypes, policies ); diff --git a/lib/node_modules/@stdlib/blas/ext/find-index/lib/index.js b/lib/node_modules/@stdlib/blas/ext/find-index/lib/index.js index 9719d0188e1c..acc53b0175af 100644 --- a/lib/node_modules/@stdlib/blas/ext/find-index/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/find-index/lib/index.js @@ -24,7 +24,6 @@ * @module @stdlib/blas/ext/find-index * * @example -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * var findIndex = require( '@stdlib/blas/ext/find-index' ); * @@ -49,10 +48,7 @@ * * // Perform operation: * var out = findIndex( x, isEven ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ 1, 0 ] +* // returns [ 1, 0 ] */ // MODULES // diff --git a/lib/node_modules/@stdlib/blas/ext/find-index/lib/main.js b/lib/node_modules/@stdlib/blas/ext/find-index/lib/main.js index 7518455114ce..fc6005e60031 100644 --- a/lib/node_modules/@stdlib/blas/ext/find-index/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/find-index/lib/main.js @@ -50,7 +50,6 @@ var base = require( './base.js' ); * @returns {ndarray} output ndarray * * @example -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * * function isEven( v ) { @@ -74,10 +73,7 @@ var base = require( './base.js' ); * * // Perform operation: * var out = findIndex( x, isEven ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ 1, 0 ] +* // returns [ 1, 0 ] */ function findIndex( x ) { var hasOptions; diff --git a/lib/node_modules/@stdlib/blas/ext/index-of/README.md b/lib/node_modules/@stdlib/blas/ext/index-of/README.md index 3fa9337380f2..314fbe0a4d4a 100644 --- a/lib/node_modules/@stdlib/blas/ext/index-of/README.md +++ b/lib/node_modules/@stdlib/blas/ext/index-of/README.md @@ -43,10 +43,7 @@ var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); // Perform operation: var out = indexOf( x, 2.0 ); -// returns - -var idx = out.get(); -// returns 1 +// returns [ 1 ] ``` The function has the following parameters: @@ -73,10 +70,7 @@ var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); // Perform operation: var out = indexOf( x, 10.0 ); -// returns - -var idx = out.get(); -// returns -1 +// returns [ -1 ] ``` By default, the function begins searching from the first element along the reduction dimension. To begin searching from a different index, provide a `fromIndex` argument. @@ -90,16 +84,12 @@ var x = array( [ 1.0, 2.0, 3.0, 4.0, 2.0, 6.0 ] ); // Perform operation: var out = indexOf( x, 2.0, 2 ); -// returns - -var idx = out.get(); -// returns 4 +// returns [ 4 ] ``` By default, the function performs the operation over elements in the last dimension. To perform the operation over a different dimension, provide a `dim` option. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ] ); @@ -107,17 +97,13 @@ var x = array( [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ] ); var out = indexOf( x, -3.0, { 'dim': 0 }); -// returns - -var idx = ndarray2array( out ); -// returns [ 1, -1 ] +// returns [ 1, -1 ] ``` By default, the function excludes reduced dimensions from the output [ndarray][@stdlib/ndarray/ctor]. To include the reduced dimensions as singleton dimensions, set the `keepdims` option to `true`. ```javascript var array = require( '@stdlib/ndarray/array' ); -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var x = array( [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ] ); @@ -127,10 +113,7 @@ var opts = { }; var out = indexOf( x, -3.0, opts ); -// returns - -var idx = ndarray2array( out ); -// returns [ [ 1, -1 ] ] +// returns [ [ 1, -1 ] ] ``` By default, the function returns an [ndarray][@stdlib/ndarray/ctor] having a [data type][@stdlib/ndarray/dtypes] determined by the function's output data type [policy][@stdlib/ndarray/output-dtype-policies]. To override the default behavior, set the `dtype` option. @@ -164,10 +147,7 @@ var y = zeros( [], { }); var out = indexOf.assign( x, 3.0, y ); -// returns - -var idx = out.get(); -// returns 2 +// returns [ 2 ] var bool = ( out === y ); // returns true diff --git a/lib/node_modules/@stdlib/blas/ext/index-of/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/index-of/docs/repl.txt index ab96c7bcfdf5..496461b6f4b1 100644 --- a/lib/node_modules/@stdlib/blas/ext/index-of/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/index-of/docs/repl.txt @@ -59,9 +59,8 @@ Examples -------- > var x = {{alias:@stdlib/ndarray/array}}( [ -1.0, 2.0, -3.0, -4.0 ] ); - > var y = {{alias}}( x, 2.0 ); - > var v = y.get() - 1 + > var y = {{alias}}( x, 2.0 ) + [ 1 ] {{alias}}.assign( x, searchElement[, fromIndex], out[, options] ) @@ -122,11 +121,9 @@ > var x = {{alias:@stdlib/ndarray/array}}( [ -1.0, 2.0, -3.0, -4.0 ] ); > var out = {{alias:@stdlib/ndarray/zeros}}( [], { 'dtype': 'int32' } ); > var y = {{alias}}.assign( x, 2.0, out ) - + [ 1 ] > var bool = ( out === y ) true - > var v = out.get() - 1 See Also -------- diff --git a/lib/node_modules/@stdlib/blas/ext/index-of/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/index-of/docs/types/index.d.ts index a87ed9df9a34..e0f59a8ba709 100644 --- a/lib/node_modules/@stdlib/blas/ext/index-of/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/index-of/docs/types/index.d.ts @@ -95,10 +95,7 @@ interface IndexOf { * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = indexOf( x, 2.0 ); - * // returns - * - * var idx = y.get(); - * // returns 1 + * // returns [ 1 ] */ ( x: InputArray, searchElement: SearchElement, options?: Options ): OutputArray; @@ -122,10 +119,7 @@ interface IndexOf { * var x = array( [ -1.0, 2.0, -3.0, 2.0, -5.0, 6.0 ] ); * * var y = indexOf( x, 2.0, 2 ); - * // returns - * - * var idx = y.get(); - * // returns 3 + * // returns [ 3 ] */ ( x: InputArray, searchElement: SearchElement, fromIndex: FromIndex, options?: Options ): OutputArray; @@ -153,13 +147,10 @@ interface IndexOf { * } ); * * var out = indexOf.assign( x, 2.0, y ); - * // returns + * // returns [ 1 ] * * var bool = ( out === y ); * // returns true - * - * var idx = out.get(); - * // returns 1 */ assign( x: InputArray, searchElement: SearchElement, out: U, options?: BaseOptions ): U; @@ -188,13 +179,10 @@ interface IndexOf { * } ); * * var out = indexOf.assign( x, 2.0, 2, y ); - * // returns + * // returns [ 3 ] * * var bool = ( out === y ); * // returns true - * - * var idx = out.get(); - * // returns 3 */ assign( x: InputArray, searchElement: SearchElement, fromIndex: FromIndex, out: U, options?: BaseOptions ): U; } @@ -219,10 +207,7 @@ interface IndexOf { * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = indexOf( x, 2.0, 0 ); -* // returns -* -* var idx = y.get(); -* // returns 1 +* // returns [ 1 ] * * @example * var zeros = require( '@stdlib/ndarray/zeros' ); @@ -234,13 +219,10 @@ interface IndexOf { * } ); * * var out = indexOf.assign( x, 2.0, 2, y ); -* // returns +* // returns [ 3 ] * * var bool = ( out === y ); * // returns true -* -* var idx = out.get(); -* // returns 3 */ declare const indexOf: IndexOf; diff --git a/lib/node_modules/@stdlib/blas/ext/index-of/lib/assign.js b/lib/node_modules/@stdlib/blas/ext/index-of/lib/assign.js index b3e2e4e87a13..6c1626729a21 100644 --- a/lib/node_modules/@stdlib/blas/ext/index-of/lib/assign.js +++ b/lib/node_modules/@stdlib/blas/ext/index-of/lib/assign.js @@ -64,7 +64,6 @@ var DEFAULT_DTYPE = defaults.get( 'dtypes.integer_index' ); * @example * var Float64Array = require( '@stdlib/array/float64' ); * var zeros = require( '@stdlib/ndarray/zeros' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * * // Create data buffers: @@ -89,13 +88,10 @@ var DEFAULT_DTYPE = defaults.get( 'dtypes.integer_index' ); * * // Perform operation: * var out = assign( x, -5.0, y ); -* // returns +* // returns [ -1, 1 ] * * var bool = ( out === y ); * // returns true -* -* var arr = ndarray2array( out ); -* // returns [ -1, 1 ] */ function assign( x, searchElement, fromIndex, out ) { var hasOptions; diff --git a/lib/node_modules/@stdlib/blas/ext/index-of/lib/base.js b/lib/node_modules/@stdlib/blas/ext/index-of/lib/base.js index c5f9af5d5138..22bd2cc69728 100644 --- a/lib/node_modules/@stdlib/blas/ext/index-of/lib/base.js +++ b/lib/node_modules/@stdlib/blas/ext/index-of/lib/base.js @@ -107,10 +107,7 @@ var table = { * * // Perform operation: * var out = indexOf( x, searchElement, fromIndex ); -* // returns -* -* var idx = out.get(); -* // returns 3 +* // returns [ 4 ] */ var indexOf = factory( table, [ idtypes0, idtypes1, idtypes2 ], odtypes, policies ); // eslint-disable-line max-len diff --git a/lib/node_modules/@stdlib/blas/ext/index-of/lib/index.js b/lib/node_modules/@stdlib/blas/ext/index-of/lib/index.js index 6a29015f62f8..0189ba2191c8 100644 --- a/lib/node_modules/@stdlib/blas/ext/index-of/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/index-of/lib/index.js @@ -25,7 +25,6 @@ * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * var indexOf = require( '@stdlib/blas/ext/index-of' ); * @@ -46,10 +45,7 @@ * * // Perform operation: * var out = indexOf( x, -5.0 ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ -1, 1 ] +* // returns [ -1, 1 ] */ // MODULES // diff --git a/lib/node_modules/@stdlib/blas/ext/index-of/lib/main.js b/lib/node_modules/@stdlib/blas/ext/index-of/lib/main.js index 3f6da9fae8fa..d7ea6e9b3e4d 100644 --- a/lib/node_modules/@stdlib/blas/ext/index-of/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/index-of/lib/main.js @@ -63,7 +63,6 @@ var DEFAULT_DTYPE = defaults.get( 'dtypes.integer_index' ); * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * * // Create a data buffer: @@ -83,10 +82,7 @@ var DEFAULT_DTYPE = defaults.get( 'dtypes.integer_index' ); * * // Perform operation: * var out = indexOf( x, -5.0 ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ -1, 1 ] +* // returns [ -1, 1 ] */ function indexOf( x, searchElement, fromIndex ) { var hasOptions; diff --git a/lib/node_modules/@stdlib/blas/ext/last-index-of/README.md b/lib/node_modules/@stdlib/blas/ext/last-index-of/README.md index b06e610d8bd0..e9029ee6387b 100644 --- a/lib/node_modules/@stdlib/blas/ext/last-index-of/README.md +++ b/lib/node_modules/@stdlib/blas/ext/last-index-of/README.md @@ -43,10 +43,7 @@ var x = array( [ 1.0, 2.0, 3.0, 2.0, 5.0, 6.0 ] ); // Perform operation: var out = lastIndexOf( x, 2.0 ); -// returns - -var idx = out.get(); -// returns 3 +// returns [ 3 ] ``` The function has the following parameters: @@ -73,10 +70,7 @@ var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); // Perform operation: var out = lastIndexOf( x, 10.0 ); -// returns - -var idx = out.get(); -// returns -1 +// returns [ -1 ] ``` By default, the function begins searching from the last element along the reduction dimension. To begin searching from a different index, provide a `fromIndex` argument. @@ -90,16 +84,12 @@ var x = array( [ 1.0, 2.0, 3.0, 4.0, 2.0, 6.0 ] ); // Perform operation: var out = lastIndexOf( x, 2.0, 3 ); -// returns - -var idx = out.get(); -// returns 1 +// returns [ 1 ] ``` By default, the function performs the operation over elements in the last dimension. To perform the operation over a different dimension, provide a `dim` option. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ [ -3.0, 2.0 ], [ -3.0, 4.0 ] ] ); @@ -107,17 +97,13 @@ var x = array( [ [ -3.0, 2.0 ], [ -3.0, 4.0 ] ] ); var out = lastIndexOf( x, -3.0, { 'dim': 0 }); -// returns - -var idx = ndarray2array( out ); -// returns [ 1, -1 ] +// returns [ 1, -1 ] ``` By default, the function excludes reduced dimensions from the output [ndarray][@stdlib/ndarray/ctor]. To include the reduced dimensions as singleton dimensions, set the `keepdims` option to `true`. ```javascript var array = require( '@stdlib/ndarray/array' ); -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var x = array( [ [ -3.0, 2.0 ], [ -3.0, 4.0 ] ] ); @@ -127,10 +113,7 @@ var opts = { }; var out = lastIndexOf( x, -3.0, opts ); -// returns - -var idx = ndarray2array( out ); -// returns [ [ 1, -1 ] ] +// returns [ [ 1, -1 ] ] ``` By default, the function returns an [ndarray][@stdlib/ndarray/ctor] having a [data type][@stdlib/ndarray/dtypes] determined by the function's output data type [policy][@stdlib/ndarray/output-dtype-policies]. To override the default behavior, set the `dtype` option. @@ -164,10 +147,7 @@ var y = zeros( [], { }); var out = lastIndexOf.assign( x, 2.0, y ); -// returns - -var idx = out.get(); -// returns 3 +// returns [ 3 ] var bool = ( out === y ); // returns true diff --git a/lib/node_modules/@stdlib/blas/ext/last-index-of/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/last-index-of/docs/repl.txt index c09ef620e64e..5e1167292265 100644 --- a/lib/node_modules/@stdlib/blas/ext/last-index-of/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/last-index-of/docs/repl.txt @@ -59,9 +59,8 @@ Examples -------- > var x = {{alias:@stdlib/ndarray/array}}( [ -1.0, 2.0, -3.0, 2.0 ] ); - > var y = {{alias}}( x, 2.0, 3 ); - > var v = y.get() - 3 + > var y = {{alias}}( x, 2.0, 3 ) + [ 3 ] {{alias}}.assign( x, searchElement[, fromIndex], out[, options] ) @@ -122,11 +121,9 @@ > var x = {{alias:@stdlib/ndarray/array}}( [ -1.0, 2.0, -3.0, 2.0 ] ); > var out = {{alias:@stdlib/ndarray/zeros}}( [], { 'dtype': 'int32' } ); > var y = {{alias}}.assign( x, 2.0, 3, out ) - + [ 3 ] > var bool = ( out === y ) true - > var v = out.get() - 3 See Also -------- diff --git a/lib/node_modules/@stdlib/blas/ext/last-index-of/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/last-index-of/docs/types/index.d.ts index 8a2c5a7e1e6e..65db605a41bc 100644 --- a/lib/node_modules/@stdlib/blas/ext/last-index-of/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/last-index-of/docs/types/index.d.ts @@ -95,10 +95,7 @@ interface lastIndexOf { * var x = array( [ -1.0, 2.0, -3.0, 2.0 ] ); * * var y = lastIndexOf( x, 2.0 ); - * // returns - * - * var idx = y.get(); - * // returns 3 + * // returns [ 3 ] */ ( x: InputArray, searchElement: SearchElement, options?: Options ): OutputArray; @@ -122,10 +119,7 @@ interface lastIndexOf { * var x = array( [ 1.0, 2.0, -3.0, 2.0, -5.0, 6.0 ] ); * * var y = lastIndexOf( x, 2.0, 5 ); - * // returns - * - * var idx = y.get(); - * // returns 3 + * // returns [ 3 ] */ ( x: InputArray, searchElement: SearchElement, fromIndex: FromIndex, options?: Options ): OutputArray; @@ -153,13 +147,10 @@ interface lastIndexOf { * } ); * * var out = lastIndexOf.assign( x, 2.0, y ); - * // returns + * // returns [ 3 ] * * var bool = ( out === y ); * // returns true - * - * var idx = out.get(); - * // returns 3 */ assign( x: InputArray, searchElement: SearchElement, out: U, options?: BaseOptions ): U; @@ -188,13 +179,10 @@ interface lastIndexOf { * } ); * * var out = lastIndexOf.assign( x, 1.0, 5, y ); - * // returns + * // returns [ 0 ] * * var bool = ( out === y ); * // returns true - * - * var idx = out.get(); - * // returns 0 */ assign( x: InputArray, searchElement: SearchElement, fromIndex: FromIndex, out: U, options?: BaseOptions ): U; } @@ -219,10 +207,7 @@ interface lastIndexOf { * var x = array( [ -1.0, 2.0, -3.0, 2.0 ] ); * * var y = lastIndexOf( x, 2.0 ); -* // returns -* -* var idx = y.get(); -* // returns 3 +* // returns [ 3 ] * * @example * var zeros = require( '@stdlib/ndarray/zeros' ); @@ -234,13 +219,10 @@ interface lastIndexOf { * } ); * * var out = lastIndexOf.assign( x, 2.0, y ); -* // returns +* // returns [ 3 ] * * var bool = ( out === y ); * // returns true -* -* var idx = out.get(); -* // returns 3 */ declare const lastIndexOf: lastIndexOf; diff --git a/lib/node_modules/@stdlib/blas/ext/last-index-of/lib/assign.js b/lib/node_modules/@stdlib/blas/ext/last-index-of/lib/assign.js index f372d2aa00ef..12ef29a441a3 100644 --- a/lib/node_modules/@stdlib/blas/ext/last-index-of/lib/assign.js +++ b/lib/node_modules/@stdlib/blas/ext/last-index-of/lib/assign.js @@ -64,7 +64,6 @@ var DEFAULT_DTYPE = defaults.get( 'dtypes.integer_index' ); * @example * var Float64Array = require( '@stdlib/array/float64' ); * var zeros = require( '@stdlib/ndarray/zeros' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * * // Create data buffers: @@ -89,13 +88,10 @@ var DEFAULT_DTYPE = defaults.get( 'dtypes.integer_index' ); * * // Perform operation: * var out = assign( x, 2.0, y ); -* // returns +* // returns [ 1, 0 ] * * var bool = ( out === y ); * // returns true -* -* var arr = ndarray2array( out ); -* // returns [ 1, 0 ] */ function assign( x, searchElement, fromIndex, out ) { var hasOptions; diff --git a/lib/node_modules/@stdlib/blas/ext/last-index-of/lib/base.js b/lib/node_modules/@stdlib/blas/ext/last-index-of/lib/base.js index aadb2a6c0d32..0a6224c02f1a 100644 --- a/lib/node_modules/@stdlib/blas/ext/last-index-of/lib/base.js +++ b/lib/node_modules/@stdlib/blas/ext/last-index-of/lib/base.js @@ -107,10 +107,7 @@ var table = { * * // Perform operation: * var out = lastIndexOf( x, searchElement, fromIndex ); -* // returns -* -* var idx = out.get(); -* // returns 3 +* // returns [ 2 ] */ var lastIndexOf = factory( table, [ idtypes0, idtypes1, idtypes2 ], odtypes, policies ); // eslint-disable-line max-len diff --git a/lib/node_modules/@stdlib/blas/ext/last-index-of/lib/index.js b/lib/node_modules/@stdlib/blas/ext/last-index-of/lib/index.js index 094c1eaaa42a..069d103c9149 100644 --- a/lib/node_modules/@stdlib/blas/ext/last-index-of/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/last-index-of/lib/index.js @@ -25,7 +25,6 @@ * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * var lastIndexOf = require( '@stdlib/blas/ext/last-index-of' ); * @@ -46,10 +45,7 @@ * * // Perform operation: * var out = lastIndexOf( x, 2.0 ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ 1, 0 ] +* // returns [ 1, 0 ] */ // MODULES // diff --git a/lib/node_modules/@stdlib/blas/ext/last-index-of/lib/main.js b/lib/node_modules/@stdlib/blas/ext/last-index-of/lib/main.js index fbff5adaed0b..727d3fb54c0b 100644 --- a/lib/node_modules/@stdlib/blas/ext/last-index-of/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/last-index-of/lib/main.js @@ -63,7 +63,6 @@ var DEFAULT_DTYPE = defaults.get( 'dtypes.integer_index' ); * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * * // Create a data buffer: @@ -83,10 +82,7 @@ var DEFAULT_DTYPE = defaults.get( 'dtypes.integer_index' ); * * // Perform operation: * var out = lastIndexOf( x, 2.0 ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ 1, 0 ] +* // returns [ 1, 0 ] */ function lastIndexOf( x, searchElement, fromIndex ) { var hasOptions; diff --git a/lib/node_modules/@stdlib/blas/ext/lib/index.js b/lib/node_modules/@stdlib/blas/ext/lib/index.js index f31e5ebb85f4..2f5d26165bb7 100644 --- a/lib/node_modules/@stdlib/blas/ext/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/lib/index.js @@ -144,6 +144,15 @@ setReadOnly( ns, 'sum', require( '@stdlib/blas/ext/sum' ) ); */ setReadOnly( ns, 'toSortedhp', require( '@stdlib/blas/ext/to-sortedhp' ) ); +/** +* @name zeroTo +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/zero-to} +*/ +setReadOnly( ns, 'zeroTo', require( '@stdlib/blas/ext/zero-to' ) ); + // EXPORTS // diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/README.md b/lib/node_modules/@stdlib/blas/ext/linspace/README.md index 037849b7dc8d..36089b8ae4d8 100644 --- a/lib/node_modules/@stdlib/blas/ext/linspace/README.md +++ b/lib/node_modules/@stdlib/blas/ext/linspace/README.md @@ -35,13 +35,8 @@ var linspace = require( '@stdlib/blas/ext/linspace' ); Returns a new [ndarray][@stdlib/ndarray/ctor] filled with linearly spaced values over a specified interval along one or more [ndarray][@stdlib/ndarray/ctor] dimensions. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); - var x = linspace( [ 4 ], 1.0, 4.0 ); -// returns - -var arr = ndarray2array( x ); -// returns [ 1.0, 2.0, 3.0, 4.0 ] +// returns [ 1.0, 2.0, 3.0, 4.0 ] ``` The function has the following parameters: @@ -58,18 +53,13 @@ The function accepts the following options: - **dtype**: output [ndarray][@stdlib/ndarray/ctor] [data type][@stdlib/ndarray/dtypes]. If both `start` and `stop` are real-valued, the output array data type may be any floating-point data type or "generic". However, if either `start` or `stop` are complex-valued, the output array type must be a complex floating-point data type or "generic". If a data type is provided, `start` and `stop` are cast to the specified data type. If a data type is not provided and both `start` and `stop` are the same type (either `'float64'`, `'complex64'`, or `'complex128'`), the default output array data type is the same type as the input values (either `'float64'`, `'complex64'`, or `'complex128'`, respectively). Otherwise, if a data type is not provided and `start` and `stop` have different types, the default output array data type is determined according to type promotion rules. - **order**: specifies whether an [ndarray][@stdlib/ndarray/ctor] is `'row-major'` (C-style) or `'column-major'` (Fortran-style). If `start`, `stop`, and `endpoint` are scalar values, the default order is `'row-major'`. If `start`, `stop`, and/or `endpoint` arrays have the same memory layout, the default order is the same layout. Otherwise, the default order is `'row-major'`. - **mode**: specifies how to handle indices which exceed array dimensions (see [`ndarray`][@stdlib/ndarray/ctor]). Default: `'throw'`. -- **submode**: a mode array which specifies for each dimension how to handle subscripts which exceed array dimensions (see [`ndarray`][@stdlib/ndarray/ctor]). If provided fewer modes than dimensions, the constructor recycles modes using modulo arithmetic. Default: `[ options.mode ]`. +- **submode**: a mode array which specifies for each dimension how to handle subscripts which exceed array dimensions (see [`ndarray`][@stdlib/ndarray/ctor]). If provided fewer modes than dimensions, the function recycles modes using modulo arithmetic. Default: `[ options.mode ]`. By default, the function always includes the end of the interval in the list of values written to an output [ndarray][@stdlib/ndarray/ctor]. To exclude the end of the interval, provide an `endpoint` argument. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); - var x = linspace( [ 4 ], 1.0, 5.0, false ); -// returns - -var arr = ndarray2array( x ); -// returns [ 1.0, 2.0, 3.0, 4.0 ] +// returns [ 1.0, 2.0, 3.0, 4.0 ] ``` When provided scalar or zero-dimensional [ndarray][@stdlib/ndarray/ctor] `start`, `stop`, and `endpoint` arguments, the values are broadcast across all elements in the shape defined by the complement of those dimensions specified by `options.dims`. To specify separate sub-array configurations, provide non-zero-dimensional [ndarray][@stdlib/ndarray/ctor] arguments. @@ -77,45 +67,31 @@ When provided scalar or zero-dimensional [ndarray][@stdlib/ndarray/ctor] `start` ```javascript var array = require( '@stdlib/ndarray/array' ); var BooleanArray = require( '@stdlib/array/bool' ); -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var start = array( [ 1.0, 5.0 ] ); var end = array( [ 3.0, 8.0 ] ); var endpoint = array( new BooleanArray( [ true, false ] ) ); var x = linspace( [ 2, 3 ], start, end, endpoint ); -// returns - -var arr = ndarray2array( x ); -// returns [ [ 1.0, 2.0, 3.0 ], [ 5.0, 6.0, 7.0 ] ] +// returns [ [ 1.0, 2.0, 3.0 ], [ 5.0, 6.0, 7.0 ] ] ``` By default, the function generates linearly spaced values along the last dimension of an output [ndarray][@stdlib/ndarray/ctor]. To perform the operation over specific dimensions, provide a `dims` option. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); - var x = linspace( [ 2, 2 ], 1.0, 4.0, { 'dims': [ 0, 1 ] }); -// returns - -var arr = ndarray2array( x ); -// returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] +// returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ``` To specify the output [ndarray][@stdlib/ndarray/ctor] [data type][@stdlib/ndarray/dtypes], provide a `dtype` option. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); - var x = linspace( [ 4 ], 1.0, 4.0, { 'dtype': 'float32' }); -// returns - -var arr = ndarray2array( x ); -// returns [ 1.0, 2.0, 3.0, 4.0 ] +// returns [ 1.0, 2.0, 3.0, 4.0 ] ``` #### linspace.assign( out, start, stop\[, endpoint]\[, options] ) @@ -123,17 +99,13 @@ var arr = ndarray2array( x ); Fills an [ndarray][@stdlib/ndarray/ctor] with linearly spaced values over a specified interval along one or more [ndarray][@stdlib/ndarray/ctor] dimensions. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var zeros = require( '@stdlib/ndarray/zeros' ); var x = zeros( [ 4 ] ); // returns var out = linspace.assign( x, 1.0, 4.0 ); -// returns - -var arr = ndarray2array( out ); -// returns [ 1.0, 2.0, 3.0, 4.0 ] +// returns [ 1.0, 2.0, 3.0, 4.0 ] var bool = ( x === out ); // returns true diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/linspace/docs/repl.txt index 55bac43b2702..bb60e19453ad 100644 --- a/lib/node_modules/@stdlib/blas/ext/linspace/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/linspace/docs/repl.txt @@ -128,9 +128,8 @@ Examples -------- - > var out = {{alias}}( [ 4 ], 1.0, 4.0 ); - > {{alias:@stdlib/ndarray/to-array}}( out ) - [ 1.0, 2.0, 3.0, 4.0 ] + > var out = {{alias}}( [ 4 ], 1.0, 4.0 ) + [ 1.0, 2.0, 3.0, 4.0 ] {{alias}}.assign( out, start, stop[, endpoint][, options] ) @@ -220,9 +219,8 @@ Examples -------- > var x = {{alias:@stdlib/ndarray/zeros}}( [ 4 ] ); - > var out = {{alias}}.assign( x, 1.0, 4.0 ); - > {{alias:@stdlib/ndarray/to-array}}( out ) - [ 1.0, 2.0, 3.0, 4.0 ] + > var out = {{alias}}.assign( x, 1.0, 4.0 ) + [ 1.0, 2.0, 3.0, 4.0 ] > var bool = ( out === x ) true diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/linspace/docs/types/index.d.ts index b811d5c83641..05376b7448a8 100644 --- a/lib/node_modules/@stdlib/blas/ext/linspace/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/linspace/docs/types/index.d.ts @@ -128,15 +128,10 @@ interface Linspace { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); - * * var out = linspace( [ 2, 4 ], 0.0, 3.0, { * 'dtype': 'float64' * }); - * // returns - * - * var arr = ndarray2array( out ); - * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] + * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] */ ( shape: number | ArrayLike, start: T, stop: U, options: OptionsWithDataType ): OutputArray; // TODO: we lose some type specificity here. We could likely improve specificity here by using type maps @@ -150,13 +145,8 @@ interface Linspace { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); - * * var out = linspace( [ 2, 4 ], 0.0, 3.0, {} ); - * // returns - * - * var arr = ndarray2array( out ); - * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] + * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] */ ( shape: number | ArrayLike, start: T, stop: U, options: Options ): RealOutputArray; // NOTE: we lose some type specificity here, as the output ndarray data type is determined according to type promotion rules @@ -171,15 +161,10 @@ interface Linspace { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); - * * var out = linspace( [ 2, 4 ], 0.0, 3.0, true, { * 'dtype': 'float64' * }); - * // returns - * - * var arr = ndarray2array( out ); - * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] + * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] */ ( shape: number | ArrayLike, start: T, stop: U, endpoint: V, options: OptionsWithDataType ): OutputArray; // TODO: we lose some type specificity here. We could likely improve specificity here by using type maps @@ -194,13 +179,8 @@ interface Linspace { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); - * * var out = linspace( [ 2, 4 ], 0.0, 3.0 ); - * // returns - * - * var arr = ndarray2array( out ); - * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] + * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] */ ( shape: number | ArrayLike, start: T, stop: U, endpoint?: V, options?: Options ): RealOutputArray; // NOTE: we lose some type specificity here, as the output ndarray data type is determined according to type promotion rules @@ -214,15 +194,10 @@ interface Linspace { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); - * * var out = linspace( [ 2, 4 ], 0.0, 3.0, { * 'dtype': 'float64' * }); - * // returns - * - * var arr = ndarray2array( out ); - * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] + * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] */ ( shape: number | ArrayLike, start: T, stop: U, options: OptionsWithDataType ): ComplexOutputArray; // TODO: we lose some type specificity here. We could likely improve specificity here by using type maps @@ -236,13 +211,8 @@ interface Linspace { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); - * * var out = linspace( [ 2, 4 ], 0.0, 3.0, {} ); - * // returns - * - * var arr = ndarray2array( out ); - * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] + * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] */ ( shape: number | ArrayLike, start: T, stop: U, options: Options ): ComplexOutputArray; /* eslint-disable-line @typescript-eslint/unified-signatures */ // NOTE: we lose some type specificity here, as the output ndarray data type is determined according to type promotion rules @@ -257,15 +227,10 @@ interface Linspace { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); - * * var out = linspace( [ 2, 4 ], 0.0, 3.0, true, { * 'dtype': 'float64' * }); - * // returns - * - * var arr = ndarray2array( out ); - * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] + * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] */ ( shape: number | ArrayLike, start: T, stop: U, endpoint: V, options: OptionsWithDataType ): ComplexOutputArray; // TODO: we lose some type specificity here. We could likely improve specificity here by using type maps @@ -280,13 +245,8 @@ interface Linspace { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); - * * var out = linspace( [ 2, 4 ], 0.0, 3.0, true ); - * // returns - * - * var arr = ndarray2array( out ); - * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] + * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] */ ( shape: number | ArrayLike, start: T, stop: U, endpoint?: V, options?: Options ): ComplexOutputArray; // NOTE: we lose some type specificity here, as the output ndarray data type is determined according to type promotion rules @@ -301,19 +261,15 @@ interface Linspace { * * @example * var zeros = require( '@stdlib/ndarray/zeros' ); - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); * * var x = zeros( [ 2, 4 ] ); * // returns * * var out = linspace.assign( x, 0.0, 3.0 ); - * // returns + * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] * * var bool = ( out === x ); * // returns true - * - * var arr = ndarray2array( out ); - * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] */ assign( out: T, start: Start, stop: Stop, options: BaseOptions ): T; @@ -329,19 +285,15 @@ interface Linspace { * * @example * var zeros = require( '@stdlib/ndarray/zeros' ); - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); * * var x = zeros( [ 2, 4 ] ); * // returns * * var out = linspace.assign( x, 0.0, 3.0 ); - * // returns + * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] * * var bool = ( out === x ); * // returns true - * - * var arr = ndarray2array( out ); - * // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] */ assign( out: T, start: Start, stop: Stop, endpoint?: Endpoint, options?: BaseOptions ): T; } @@ -356,29 +308,20 @@ interface Linspace { * @param options - function options * * @example -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); -* * var out = linspace( [ 2, 4 ], 0.0, 3.0 ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] +* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] * * @example * var zeros = require( '@stdlib/ndarray/zeros' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * * var x = zeros( [ 2, 4 ] ); * // returns * * var out = linspace.assign( x, 0.0, 3.0 ); -* // returns +* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] * * var bool = ( out === x ); * // returns true -* -* var arr = ndarray2array( out ); -* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] */ declare const linspace: Linspace; diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/lib/assign.js b/lib/node_modules/@stdlib/blas/ext/linspace/lib/assign.js index 614913ce8acd..405b3f5695a1 100644 --- a/lib/node_modules/@stdlib/blas/ext/linspace/lib/assign.js +++ b/lib/node_modules/@stdlib/blas/ext/linspace/lib/assign.js @@ -63,23 +63,19 @@ var base = require( './base.js' ); * @throws {RangeError} dimension indices must not exceed input ndarray bounds * @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions * @throws {Error} must provide valid options -* @returns {ndarray} output ndarray +* @returns {ndarray} input ndarray * * @example * var zeros = require( '@stdlib/ndarray/zeros' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * * var x = zeros( [ 2, 4 ] ); * // returns * * var out = assign( x, 0.0, 3.0 ); -* // returns +* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] * * var bool = ( out === x ); * // returns true -* -* var arr = ndarray2array( out ); -* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] */ function assign( x, start, stop ) { var endpoint; diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/lib/base.js b/lib/node_modules/@stdlib/blas/ext/linspace/lib/base.js index 78846467f161..2dec8fe7bad4 100644 --- a/lib/node_modules/@stdlib/blas/ext/linspace/lib/base.js +++ b/lib/node_modules/@stdlib/blas/ext/linspace/lib/base.js @@ -67,13 +67,12 @@ var options = { * @throws {RangeError} dimension indices must not exceed input ndarray bounds * @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions * @throws {Error} must provide valid options -* @returns {ndarray} output ndarray +* @returns {ndarray} input ndarray * * @example * var Float64Array = require( '@stdlib/array/float64' ); * var BooleanArray = require( '@stdlib/array/bool' ); * var array = require( '@stdlib/ndarray/array' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * * // Create a data buffer: @@ -110,10 +109,7 @@ var options = { * var out = linspace( x, start, end, endpoint, { * 'dims': [ -1 ] * }); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ [ [ 1.0, 2.0, 3.0 ] ], [ [ 4.0, 5.0, 6.0 ] ] ] +* // returns [ [ [ 1.0, 2.0, 3.0 ] ], [ [ 4.0, 5.0, 6.0 ] ] ] */ var linspace = factory( table, [ DTYPES.idtypes0, DTYPES.idtypes1, DTYPES.idtypes2 ], DTYPES.odtypes, options ); // eslint-disable-line max-len diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/lib/index.js b/lib/node_modules/@stdlib/blas/ext/linspace/lib/index.js index ebe9dd7070cb..3078a189d8fa 100644 --- a/lib/node_modules/@stdlib/blas/ext/linspace/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/linspace/lib/index.js @@ -24,31 +24,23 @@ * @module @stdlib/blas/ext/linspace * * @example -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var linspace = require( '@stdlib/blas/ext/linspace' ); * * var out = linspace( [ 2, 4 ], 0.0, 3.0 ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] +* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] * * @example * var zeros = require( '@stdlib/ndarray/zeros' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var linspace = require( '@stdlib/blas/ext/linspace' ); * * var x = zeros( [ 2, 4 ] ); * // returns * * var out = linspace.assign( x, 0.0, 3.0 ); -* // returns +* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] * * var bool = ( out === x ); * // returns true -* -* var arr = ndarray2array( out ); -* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] */ // MODULES // diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/lib/main.js b/lib/node_modules/@stdlib/blas/ext/linspace/lib/main.js index 9c40f698a2d0..b3ec91f34242 100644 --- a/lib/node_modules/@stdlib/blas/ext/linspace/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/linspace/lib/main.js @@ -74,13 +74,8 @@ var base = require( './base.js' ); * @returns {ndarray} output ndarray * * @example -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); -* * var out = linspace( [ 2, 4 ], 0.0, 3.0 ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] +* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ] */ function linspace( shape, start, stop ) { var endpoint; diff --git a/lib/node_modules/@stdlib/blas/ext/sorthp/README.md b/lib/node_modules/@stdlib/blas/ext/sorthp/README.md index c56ceeb1a214..87d9ddf0d9b4 100644 --- a/lib/node_modules/@stdlib/blas/ext/sorthp/README.md +++ b/lib/node_modules/@stdlib/blas/ext/sorthp/README.md @@ -35,16 +35,12 @@ var sorthp = require( '@stdlib/blas/ext/sorthp' ); Sorts an input [ndarray][@stdlib/ndarray/ctor] along one or more [ndarray][@stdlib/ndarray/ctor] dimensions using heapsort. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ -1.0, 2.0, -3.0 ] ); var y = sorthp( x ); -// returns - -var arr = ndarray2array( y ); -// returns [ -3.0, -1.0, 2.0 ] +// returns [ -3.0, -1.0, 2.0 ] var bool = ( x === y ); // returns true @@ -63,62 +59,45 @@ The function accepts the following options: By default, the function sorts elements in increasing order. To sort in a different order, provide a `sortOrder` argument. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ -1.0, 2.0, -3.0 ] ); var y = sorthp( x, -1.0 ); -// returns - -var arr = ndarray2array( y ); -// returns [ 2.0, -1.0, -3.0 ] +// returns [ 2.0, -1.0, -3.0 ] ``` In addition to numeric values, one can specify the sort order via one of the following string literals: `'ascending'`, `'asc'`, `'descending'`, or `'desc'`. The first two literals indicate to sort in ascending (i.e., increasing) order. The last two literals indicate to sort in descending (i.e., decreasing) order. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ -1.0, 2.0, -3.0 ] ); // Sort in ascending order: var y = sorthp( x, 'asc' ); -// returns - -var arr = ndarray2array( y ); -// returns [ -3.0, -1.0, 2.0 ] +// returns [ -3.0, -1.0, 2.0 ] // Sort in descending order: y = sorthp( x, 'descending' ); -// returns - -arr = ndarray2array( y ); -// returns [ 2.0, -1.0, -3.0 ] +// returns [ 2.0, -1.0, -3.0 ] ``` By default, the function performs the operation over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. To perform the operation over specific dimensions, provide a `dims` option. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ -1.0, 2.0, -3.0, 4.0 ], { 'shape': [ 2, 2 ], 'order': 'row-major' }); - -var v = ndarray2array( x ); -// returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ] +// returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ] var y = sorthp( x, { 'dims': [ 0 ] }); -// returns - -v = ndarray2array( y ); -// returns [ [ -3.0, 2.0 ], [ -1.0, 4.0 ] ] +// returns [ [ -3.0, 2.0 ], [ -1.0, 4.0 ] ] ```
diff --git a/lib/node_modules/@stdlib/blas/ext/sorthp/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/sorthp/docs/repl.txt index 472c27605a4e..19437560e3e3 100644 --- a/lib/node_modules/@stdlib/blas/ext/sorthp/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/sorthp/docs/repl.txt @@ -58,9 +58,8 @@ Examples -------- > var x = {{alias:@stdlib/ndarray/array}}( [ -1.0, 2.0, -3.0, -4.0 ] ); - > var y = {{alias}}( x ); - > {{alias:@stdlib/ndarray/to-array}}( y ) - [ -4.0, -3.0, -1.0, 2.0 ] + > var y = {{alias}}( x ) + [ -4.0, -3.0, -1.0, 2.0 ] See Also -------- diff --git a/lib/node_modules/@stdlib/blas/ext/sorthp/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/sorthp/docs/types/index.d.ts index 0106cb13ac7f..bd3e2e5fc3d1 100644 --- a/lib/node_modules/@stdlib/blas/ext/sorthp/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/sorthp/docs/types/index.d.ts @@ -65,16 +65,12 @@ interface Sorthp { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var array = require( '@stdlib/ndarray/array' ); * * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = sorthp( x ); - * // returns - * - * var arr = ndarray2array( y ); - * // returns [ -3.0, -1.0, 2.0 ] + * // returns [ -3.0, -1.0, 2.0 ] */ ( x: T, options?: Options ): T; @@ -96,16 +92,12 @@ interface Sorthp { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var array = require( '@stdlib/ndarray/array' ); * * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = sorthp( x, 1.0 ); - * // returns - * - * var arr = ndarray2array( y ); - * // returns [ -3.0, -1.0, 2.0 ] + * // returns [ -3.0, -1.0, 2.0 ] */ ( x: T, sortOrder: SortOrder, options?: Options ): T; } @@ -128,28 +120,20 @@ interface Sorthp { * @returns output ndarray * * @example -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var array = require( '@stdlib/ndarray/array' ); * * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = sorthp( x, 1.0 ); -* // returns -* -* var arr = ndarray2array( y ); -* // returns [ -3.0, -1.0, 2.0 ] +* // returns [ -3.0, -1.0, 2.0 ] * * @example -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var array = require( '@stdlib/ndarray/array' ); * * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = sorthp( x, 1.0 ); -* // returns -* -* var arr = ndarray2array( y ); -* // returns [ -3.0, -1.0, 2.0 ] +* // returns [ -3.0, -1.0, 2.0 ] */ declare const sorthp: Sorthp; diff --git a/lib/node_modules/@stdlib/blas/ext/sorthp/lib/base.js b/lib/node_modules/@stdlib/blas/ext/sorthp/lib/base.js index 620270654deb..8e34cfb525f3 100644 --- a/lib/node_modules/@stdlib/blas/ext/sorthp/lib/base.js +++ b/lib/node_modules/@stdlib/blas/ext/sorthp/lib/base.js @@ -69,7 +69,6 @@ var options = { * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * @@ -95,10 +94,7 @@ var options = { * * // Perform operation: * var out = sorthp( x, sortOrder ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ [ [ -5.0, -3.0 ] ], [ [ 1.0, 2.0 ] ], [ [ 4.0, 6.0 ] ] ] +* // returns [ [ [ -5.0, -3.0 ] ], [ [ 1.0, 2.0 ] ], [ [ 4.0, 6.0 ] ] ] */ var sorthp = factory( table, [ idtypes0 ], odtypes, options ); diff --git a/lib/node_modules/@stdlib/blas/ext/sorthp/lib/index.js b/lib/node_modules/@stdlib/blas/ext/sorthp/lib/index.js index 09412ed7dd01..889047ccbd1e 100644 --- a/lib/node_modules/@stdlib/blas/ext/sorthp/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/sorthp/lib/index.js @@ -26,7 +26,6 @@ * @example * var Float64Array = require( '@stdlib/array/float64' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var sorthp = require( '@stdlib/blas/ext/sorthp' ); * * // Create a data buffer: @@ -46,10 +45,7 @@ * * // Perform operation: * var out = sorthp( x ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ [ [ -5.0, -3.0 ] ], [ [ 1.0, 2.0 ] ], [ [ 4.0, 6.0 ] ] ] +* // returns [ [ [ -5.0, -3.0 ] ], [ [ 1.0, 2.0 ] ], [ [ 4.0, 6.0 ] ] ] */ // MODULES // diff --git a/lib/node_modules/@stdlib/blas/ext/sorthp/lib/main.js b/lib/node_modules/@stdlib/blas/ext/sorthp/lib/main.js index 008a712f980c..fb9353958dc3 100644 --- a/lib/node_modules/@stdlib/blas/ext/sorthp/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/sorthp/lib/main.js @@ -121,7 +121,6 @@ function normalizeOrder( value ) { * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * * // Create a data buffer: @@ -141,10 +140,7 @@ function normalizeOrder( value ) { * * // Perform operation: * var out = sorthp( x ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ [ [ -5.0, -3.0 ] ], [ [ 1.0, 2.0 ] ], [ [ 4.0, 6.0 ] ] ] +* // returns [ [ [ -5.0, -3.0 ] ], [ [ 1.0, 2.0 ] ], [ [ 4.0, 6.0 ] ] ] */ function sorthp( x ) { var nargs; diff --git a/lib/node_modules/@stdlib/blas/ext/sum/README.md b/lib/node_modules/@stdlib/blas/ext/sum/README.md index 03ce257568a9..1fa6b2cedf73 100644 --- a/lib/node_modules/@stdlib/blas/ext/sum/README.md +++ b/lib/node_modules/@stdlib/blas/ext/sum/README.md @@ -40,10 +40,7 @@ var array = require( '@stdlib/ndarray/array' ); var x = array( [ -1.0, 2.0, -3.0 ] ); var y = sum( x ); -// returns - -var v = y.get(); -// returns -2.0 +// returns [ -2.0 ] ``` The function has the following parameters: @@ -60,7 +57,6 @@ The function accepts the following options: By default, the function performs a reduction over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. To perform a reduction over specific dimensions, provide a `dims` option. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ -1.0, 2.0, -3.0, 4.0 ], { @@ -68,38 +64,25 @@ var x = array( [ -1.0, 2.0, -3.0, 4.0 ], { 'order': 'row-major' }); -var v = ndarray2array( x ); -// returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ] - var y = sum( x, { 'dims': [ 0 ] }); -// returns - -v = ndarray2array( y ); -// returns [ -4.0, 6.0 ] +// returns [ -4.0, 6.0 ] y = sum( x, { 'dims': [ 1 ] }); -// returns - -v = ndarray2array( y ); -// returns [ 1.0, 1.0 ] +// returns [ 1.0, 1.0 ] y = sum( x, { 'dims': [ 0, 1 ] }); -// returns - -v = y.get(); -// returns 2.0 +// returns [ 2.0 ] ``` By default, the function excludes reduced dimensions from the output [ndarray][@stdlib/ndarray/ctor]. To include the reduced dimensions as singleton dimensions, set the `keepdims` option to `true`. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ -1.0, 2.0, -3.0, 4.0 ], { @@ -107,35 +90,23 @@ var x = array( [ -1.0, 2.0, -3.0, 4.0 ], { 'order': 'row-major' }); -var v = ndarray2array( x ); -// returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ] - var y = sum( x, { 'dims': [ 0 ], 'keepdims': true }); -// returns - -v = ndarray2array( y ); -// returns [ [ -4.0, 6.0 ] ] +// returns [ [ -4.0, 6.0 ] ] y = sum( x, { 'dims': [ 1 ], 'keepdims': true }); -// returns - -v = ndarray2array( y ); -// returns [ [ 1.0 ], [ 1.0 ] ] +// returns [ [ 1.0 ], [ 1.0 ] ] y = sum( x, { 'dims': [ 0, 1 ], 'keepdims': true }); -// returns - -v = ndarray2array( y ); -// returns [ [ 2.0 ] ] +// returns [ [ 2.0 ] ] ``` By default, the function returns an [ndarray][@stdlib/ndarray/ctor] having a [data type][@stdlib/ndarray/dtypes] determined by the function's output data type [policy][@stdlib/ndarray/output-dtype-policies]. To override the default behavior, set the `dtype` option. @@ -169,10 +140,7 @@ var x = array( [ -1.0, 2.0, -3.0 ] ); var y = zeros( [] ); var out = sum.assign( x, y ); -// returns - -var v = out.get(); -// returns -2.0 +// returns [ -2.0 ] var bool = ( out === y ); // returns true diff --git a/lib/node_modules/@stdlib/blas/ext/sum/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/sum/docs/repl.txt index 5812ac6074c0..4b90c457a10c 100644 --- a/lib/node_modules/@stdlib/blas/ext/sum/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/sum/docs/repl.txt @@ -30,9 +30,8 @@ Examples -------- > var x = {{alias:@stdlib/ndarray/array}}( [ -1.0, 2.0, -3.0, -4.0 ] ); - > var y = {{alias}}( x ); - > var v = y.get() - -6.0 + > var y = {{alias}}( x ) + [ -6.0 ] {{alias}}.assign( x, out[, options] ) @@ -65,11 +64,9 @@ > var x = {{alias:@stdlib/ndarray/array}}( [ -1.0, 2.0, -3.0, -4.0 ] ); > var out = {{alias:@stdlib/ndarray/zeros}}( [] ); > var y = {{alias}}.assign( x, out ) - + [ -6.0 ] > var bool = ( out === y ) true - > var v = out.get() - -6.0 See Also -------- diff --git a/lib/node_modules/@stdlib/blas/ext/sum/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/sum/docs/types/index.d.ts index 66f621c4b981..8a4512d8e523 100644 --- a/lib/node_modules/@stdlib/blas/ext/sum/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/sum/docs/types/index.d.ts @@ -75,10 +75,7 @@ interface Unary { * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = sum( x ); - * // returns - * - * var v = y.get(); - * // returns -2.0 + * // returns [ -2.0 ] */ ( x: InputArray, options?: Options ): OutputArray; // NOTE: we lose type specificity here, but retaining specificity would likely be difficult and/or tedious to completely enumerate, as the output ndarray data type is dependent on how `x` interacts with output data type policy and whether that policy has been overridden by `options.dtype`. @@ -98,10 +95,7 @@ interface Unary { * var y = zeros( [] ); * * var out = sum.assign( x, y ); - * // returns - * - * var v = out.get(); - * // returns -2.0 + * // returns [ -2.0 ] * * var bool = ( out === y ); * // returns true @@ -122,10 +116,7 @@ interface Unary { * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = sum( x ); -* // returns -* -* var v = y.get(); -* // returns -2.0 +* // returns [ -2.0 ] * * @example * var array = require( '@stdlib/ndarray/array' ); @@ -135,10 +126,7 @@ interface Unary { * var y = zeros( [] ); * * var out = sum.assign( x, y ); -* // returns -* -* var v = out.get(); -* // returns -2.0 +* // returns [ -2.0 ] * * var bool = ( out === y ); * // returns true diff --git a/lib/node_modules/@stdlib/blas/ext/sum/lib/index.js b/lib/node_modules/@stdlib/blas/ext/sum/lib/index.js index 7c6e630b2747..fcf131ae4506 100644 --- a/lib/node_modules/@stdlib/blas/ext/sum/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/sum/lib/index.js @@ -45,10 +45,7 @@ * * // Perform reduction: * var out = sum( x ); -* // returns -* -* var v = out.get(); -* // returns 39.0 +* // returns [ 39.0 ] */ // MODULES // diff --git a/lib/node_modules/@stdlib/blas/ext/sum/lib/main.js b/lib/node_modules/@stdlib/blas/ext/sum/lib/main.js index 2d2b5d0ba450..4fe08dec4a9b 100644 --- a/lib/node_modules/@stdlib/blas/ext/sum/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/sum/lib/main.js @@ -94,10 +94,7 @@ var table = { * * // Perform reduction: * var out = sum( x ); -* // returns -* -* var v = out.get(); -* // returns 39.0 +* // returns [ 39.0 ] */ var sum = factory( table, [ idtypes ], odtypes, policies ); diff --git a/lib/node_modules/@stdlib/blas/ext/to-sortedhp/README.md b/lib/node_modules/@stdlib/blas/ext/to-sortedhp/README.md index d34b9f3033af..89ecaff367ff 100644 --- a/lib/node_modules/@stdlib/blas/ext/to-sortedhp/README.md +++ b/lib/node_modules/@stdlib/blas/ext/to-sortedhp/README.md @@ -35,16 +35,12 @@ var toSortedhp = require( '@stdlib/blas/ext/to-sortedhp' ); Returns a new [ndarray][@stdlib/ndarray/ctor] containing the elements of an input [ndarray][@stdlib/ndarray/ctor] sorted along one or more [ndarray][@stdlib/ndarray/ctor] dimensions using heapsort. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ -1.0, 2.0, -3.0 ] ); var y = toSortedhp( x ); -// returns - -var arr = ndarray2array( y ); -// returns [ -3.0, -1.0, 2.0 ] +// returns [ -3.0, -1.0, 2.0 ] ``` The function has the following parameters: @@ -61,45 +57,33 @@ The function accepts the following options: By default, the function sorts elements in increasing order. To sort in a different order, provide a `sortOrder` argument. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ -1.0, 2.0, -3.0 ] ); var y = toSortedhp( x, -1.0 ); -// returns - -var arr = ndarray2array( y ); -// returns [ 2.0, -1.0, -3.0 ] +// returns [ 2.0, -1.0, -3.0 ] ``` In addition to numeric values, one can specify the sort order via one of the following string literals: `'ascending'`, `'asc'`, `'descending'`, or `'desc'`. The first two literals indicate to sort in ascending (i.e., increasing) order. The last two literals indicate to sort in descending (i.e., decreasing) order. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ -1.0, 2.0, -3.0 ] ); // Sort in ascending order: var y = toSortedhp( x, 'asc' ); -// returns - -var arr = ndarray2array( y ); -// returns [ -3.0, -1.0, 2.0 ] +// returns [ -3.0, -1.0, 2.0 ] // Sort in descending order: y = toSortedhp( x, 'descending' ); -// returns - -arr = ndarray2array( y ); -// returns [ 2.0, -1.0, -3.0 ] +// returns [ 2.0, -1.0, -3.0 ] ``` By default, the function performs the operation over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. To perform the operation over specific dimensions, provide a `dims` option. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ -1.0, 2.0, -3.0, 4.0 ], { @@ -107,22 +91,15 @@ var x = array( [ -1.0, 2.0, -3.0, 4.0 ], { 'order': 'row-major' }); -var v = ndarray2array( x ); -// returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ] - var y = toSortedhp( x, { 'dims': [ 0 ] }); -// returns - -v = ndarray2array( y ); -// returns [ [ -3.0, 2.0 ], [ -1.0, 4.0 ] ] +// returns [ [ -3.0, 2.0 ], [ -1.0, 4.0 ] ] ``` To specify the output [ndarray][@stdlib/ndarray/ctor] [data type][@stdlib/ndarray/dtypes], provide a `dtype` option. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ -1.0, 2.0, -3.0 ] ); @@ -130,10 +107,7 @@ var x = array( [ -1.0, 2.0, -3.0 ] ); var y = toSortedhp( x, { 'dtype': 'float32' }); -// returns - -var arr = ndarray2array( y ); -// returns [ -3.0, -1.0, 2.0 ] +// returns [ -3.0, -1.0, 2.0 ] ``` #### toSortedhp.assign( x, out\[, sortOrder]\[, options] ) @@ -141,7 +115,6 @@ var arr = ndarray2array( y ); Sorts the elements of an input [ndarray][@stdlib/ndarray/ctor] along one or more [ndarray][@stdlib/ndarray/ctor] dimensions using heapsort and assigns the results to an output [ndarray][@stdlib/ndarray/ctor]. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var zeros = require( '@stdlib/ndarray/zeros' ); var array = require( '@stdlib/ndarray/array' ); @@ -149,10 +122,7 @@ var x = array( [ -1.0, 2.0, -3.0 ] ); var y = zeros( [ 3 ] ); var out = toSortedhp.assign( x, y ); -// returns - -var arr = ndarray2array( out ); -// returns [ -3.0, -1.0, 2.0 ] +// returns [ -3.0, -1.0, 2.0 ] var bool = ( y === out ); // returns true diff --git a/lib/node_modules/@stdlib/blas/ext/to-sortedhp/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/to-sortedhp/docs/repl.txt index 005be213a8c4..9a43f125f592 100644 --- a/lib/node_modules/@stdlib/blas/ext/to-sortedhp/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/to-sortedhp/docs/repl.txt @@ -59,9 +59,8 @@ Examples -------- > var x = {{alias:@stdlib/ndarray/array}}( [ -1.0, 2.0, -3.0, -4.0 ] ); - > var out = {{alias}}( x ); - > {{alias:@stdlib/ndarray/to-array}}( out ) - [ -4.0, -3.0, -1.0, 2.0 ] + > var out = {{alias}}( x ) + [ -4.0, -3.0, -1.0, 2.0 ] {{alias}}.assign( x, out[, sortOrder][, options] ) @@ -112,9 +111,8 @@ -------- > var x = {{alias:@stdlib/ndarray/array}}( [ -1.0, 2.0, -3.0, -4.0 ] ); > var y = {{alias:@stdlib/ndarray/zeros}}( [ 4 ] ); - > var out = {{alias}}.assign( x, y ); - > {{alias:@stdlib/ndarray/to-array}}( out ) - [ -4.0, -3.0, -1.0, 2.0 ] + > var out = {{alias}}.assign( x, y ) + [ -4.0, -3.0, -1.0, 2.0 ] > var bool = ( out === y ) true diff --git a/lib/node_modules/@stdlib/blas/ext/to-sortedhp/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/to-sortedhp/docs/types/index.d.ts index fdef48296575..c06b2c52e63e 100644 --- a/lib/node_modules/@stdlib/blas/ext/to-sortedhp/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/to-sortedhp/docs/types/index.d.ts @@ -78,16 +78,12 @@ interface ToSortedhp { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var array = require( '@stdlib/ndarray/array' ); * * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = toSortedhp( x ); - * // returns - * - * var arr = ndarray2array( y ); - * // returns [ -3.0, -1.0, 2.0 ] + * // returns [ -3.0, -1.0, 2.0 ] */ ( x: T, options?: BaseOptions ): T; @@ -107,16 +103,12 @@ interface ToSortedhp { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var array = require( '@stdlib/ndarray/array' ); * * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = toSortedhp( x ); - * // returns - * - * var arr = ndarray2array( y ); - * // returns [ -3.0, -1.0, 2.0 ] + * // returns [ -3.0, -1.0, 2.0 ] */ ( x: T, options?: Options ): U; // NOTE: we lose type specificity here. We can likely address this with type maps @@ -137,16 +129,12 @@ interface ToSortedhp { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var array = require( '@stdlib/ndarray/array' ); * * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = toSortedhp( x, 1.0 ); - * // returns - * - * var arr = ndarray2array( y ); - * // returns [ -3.0, -1.0, 2.0 ] + * // returns [ -3.0, -1.0, 2.0 ] */ ( x: T, sortOrder: SortOrder, options?: BaseOptions ): T; @@ -167,16 +155,12 @@ interface ToSortedhp { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var array = require( '@stdlib/ndarray/array' ); * * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = toSortedhp( x, 1.0 ); - * // returns - * - * var arr = ndarray2array( y ); - * // returns [ -3.0, -1.0, 2.0 ] + * // returns [ -3.0, -1.0, 2.0 ] */ ( x: T, sortOrder: SortOrder, options?: Options ): U; // NOTE: we lose type specificity here. We can likely address this with type maps @@ -197,7 +181,6 @@ interface ToSortedhp { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var zeros = require( '@stdlib/ndarray/zeros' ); * var array = require( '@stdlib/ndarray/array' ); * @@ -206,10 +189,7 @@ interface ToSortedhp { * var y = zeros( [ 3 ] ); * * var out = toSortedhp.assign( x, y ); - * // returns - * - * var arr = ndarray2array( out ); - * // returns [ -3.0, -1.0, 2.0 ] + * // returns [ -3.0, -1.0, 2.0 ] * * var bool = ( out === y ); * // returns true @@ -234,7 +214,6 @@ interface ToSortedhp { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var zeros = require( '@stdlib/ndarray/zeros' ); * var array = require( '@stdlib/ndarray/array' ); * @@ -243,10 +222,7 @@ interface ToSortedhp { * var y = zeros( [ 3 ] ); * * var out = toSortedhp.assign( x, y, 1); - * // returns - * - * var arr = ndarray2array( out ); - * // returns [ -3.0, -1.0, 2.0 ] + * // returns [ -3.0, -1.0, 2.0 ] * * var bool = ( out === y ); * // returns true @@ -271,19 +247,14 @@ interface ToSortedhp { * @returns output ndarray * * @example -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var array = require( '@stdlib/ndarray/array' ); * * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = toSortedhp( x, 1.0 ); -* // returns -* -* var arr = ndarray2array( y ); -* // returns [ -3.0, -1.0, 2.0 ] +* // returns [ -3.0, -1.0, 2.0 ] * * @example -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var zeros = require( '@stdlib/ndarray/zeros' ); * var array = require( '@stdlib/ndarray/array' ); * @@ -292,10 +263,7 @@ interface ToSortedhp { * var y = zeros( [ 3 ] ); * * var out = toSortedhp.assign( x, y ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ -3.0, -1.0, 2.0 ] +* // returns [ -3.0, -1.0, 2.0 ] * * var bool = ( out === y ); * // returns true diff --git a/lib/node_modules/@stdlib/blas/ext/to-sortedhp/lib/assign.js b/lib/node_modules/@stdlib/blas/ext/to-sortedhp/lib/assign.js index 4c95fe280200..263562366c97 100644 --- a/lib/node_modules/@stdlib/blas/ext/to-sortedhp/lib/assign.js +++ b/lib/node_modules/@stdlib/blas/ext/to-sortedhp/lib/assign.js @@ -51,7 +51,6 @@ var format = require( '@stdlib/string/format' ); * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var zeros = require( '@stdlib/ndarray/zeros' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * @@ -75,10 +74,7 @@ var format = require( '@stdlib/string/format' ); * * // Perform operation: * var out = assign( x, y ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ [ [ -5.0, -3.0 ] ], [ [ 1.0, 2.0 ] ], [ [ 4.0, 6.0 ] ] ] +* // returns [ [ [ -5.0, -3.0 ] ], [ [ 1.0, 2.0 ] ], [ [ 4.0, 6.0 ] ] ] * * var bool = ( y === out ); * // returns true diff --git a/lib/node_modules/@stdlib/blas/ext/to-sortedhp/lib/index.js b/lib/node_modules/@stdlib/blas/ext/to-sortedhp/lib/index.js index 2662601a5a6d..cec3ffdd894b 100644 --- a/lib/node_modules/@stdlib/blas/ext/to-sortedhp/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/to-sortedhp/lib/index.js @@ -26,7 +26,6 @@ * @example * var Float64Array = require( '@stdlib/array/float64' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var toSortedhp = require( '@stdlib/blas/ext/to-sortedhp' ); * * // Create a data buffer: @@ -46,14 +45,10 @@ * * // Perform operation: * var out = toSortedhp( x ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ [ [ -5.0, -3.0 ] ], [ [ 1.0, 2.0 ] ], [ [ 4.0, 6.0 ] ] ] +* // returns [ [ [ -5.0, -3.0 ] ], [ [ 1.0, 2.0 ] ], [ [ 4.0, 6.0 ] ] ] * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var zeros = require( '@stdlib/ndarray/zeros' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * var toSortedhp = require( '@stdlib/blas/ext/to-sortedhp' ); @@ -78,10 +73,7 @@ * * // Perform operation: * var out = toSortedhp.assign( x, y ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ [ [ -5.0, -3.0 ] ], [ [ 1.0, 2.0 ] ], [ [ 4.0, 6.0 ] ] ] +* // returns [ [ [ -5.0, -3.0 ] ], [ [ 1.0, 2.0 ] ], [ [ 4.0, 6.0 ] ] ] * * var bool = ( y === out ); * // returns true diff --git a/lib/node_modules/@stdlib/blas/ext/to-sortedhp/lib/main.js b/lib/node_modules/@stdlib/blas/ext/to-sortedhp/lib/main.js index 71250be97342..107a85ecc8b6 100644 --- a/lib/node_modules/@stdlib/blas/ext/to-sortedhp/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/to-sortedhp/lib/main.js @@ -56,7 +56,6 @@ var format = require( '@stdlib/string/format' ); * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * * // Create a data buffer: @@ -76,10 +75,7 @@ var format = require( '@stdlib/string/format' ); * * // Perform operation: * var out = toSortedhp( x ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ [ [ -5.0, -3.0 ] ], [ [ 1.0, 2.0 ] ], [ [ 4.0, 6.0 ] ] ] +* // returns [ [ [ -5.0, -3.0 ] ], [ [ 1.0, 2.0 ] ], [ [ 4.0, 6.0 ] ] ] */ function toSortedhp( x ) { var sortOrder; diff --git a/lib/node_modules/@stdlib/blas/ext/to-sortedhp/test/test.assign.js b/lib/node_modules/@stdlib/blas/ext/to-sortedhp/test/test.assign.js index 3e8c5d23e391..e8725e500f99 100644 --- a/lib/node_modules/@stdlib/blas/ext/to-sortedhp/test/test.assign.js +++ b/lib/node_modules/@stdlib/blas/ext/to-sortedhp/test/test.assign.js @@ -23,6 +23,7 @@ var tape = require( 'tape' ); var ndarray = require( '@stdlib/ndarray/ctor' ); var zeros = require( '@stdlib/ndarray/zeros' ); +var empty = require( '@stdlib/ndarray/empty' ); var ndarray2array = require( '@stdlib/ndarray/to-array' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); var assign = require( './../lib/assign.js' ); @@ -209,7 +210,7 @@ tape( 'the function throws an error if provided a first argument which does not var i; values = [ - zeros( [ 2, 2 ], { + empty( [ 2, 2 ], { 'dtype': 'bool' }) ]; @@ -230,7 +231,7 @@ tape( 'the function throws an error if provided a first argument which does not var i; values = [ - zeros( [ 2, 2 ], { + empty( [ 2, 2 ], { 'dtype': 'bool' }) ]; @@ -251,7 +252,7 @@ tape( 'the function throws an error if provided a first argument which does not var i; values = [ - zeros( [ 2, 2 ], { + empty( [ 2, 2 ], { 'dtype': 'bool' }) ]; @@ -272,7 +273,7 @@ tape( 'the function throws an error if provided a first argument which does not var i; values = [ - zeros( [ 2, 2 ], { + empty( [ 2, 2 ], { 'dtype': 'bool' }) ]; @@ -293,7 +294,7 @@ tape( 'the function throws an error if provided a first argument which does not var i; values = [ - zeros( [ 2, 2 ], { + empty( [ 2, 2 ], { 'dtype': 'bool' }) ]; @@ -314,7 +315,7 @@ tape( 'the function throws an error if provided a first argument which does not var i; values = [ - zeros( [ 2, 2 ], { + empty( [ 2, 2 ], { 'dtype': 'bool' }) ]; @@ -503,7 +504,7 @@ tape( 'the function throws an error if provided a second argument which does not var i; values = [ - zeros( [ 2, 2 ], { + empty( [ 2, 2 ], { 'dtype': 'bool' }) ]; @@ -524,7 +525,7 @@ tape( 'the function throws an error if provided a second argument which does not var i; values = [ - zeros( [ 2, 2 ], { + empty( [ 2, 2 ], { 'dtype': 'bool' }) ]; @@ -545,7 +546,7 @@ tape( 'the function throws an error if provided a second argument which does not var i; values = [ - zeros( [ 2, 2 ], { + empty( [ 2, 2 ], { 'dtype': 'bool' }) ]; @@ -566,7 +567,7 @@ tape( 'the function throws an error if provided a second argument which does not var i; values = [ - zeros( [ 2, 2 ], { + empty( [ 2, 2 ], { 'dtype': 'bool' }) ]; @@ -587,7 +588,7 @@ tape( 'the function throws an error if provided a second argument which does not var i; values = [ - zeros( [ 2, 2 ], { + empty( [ 2, 2 ], { 'dtype': 'bool' }) ]; @@ -608,7 +609,7 @@ tape( 'the function throws an error if provided a second argument which does not var i; values = [ - zeros( [ 2, 2 ], { + empty( [ 2, 2 ], { 'dtype': 'bool' }) ]; diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/README.md b/lib/node_modules/@stdlib/blas/ext/zero-to/README.md new file mode 100644 index 000000000000..b2e2b2113656 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/README.md @@ -0,0 +1,166 @@ + + +# zeroTo + +> Return a new [ndarray][@stdlib/ndarray/ctor] filled with linearly spaced numeric elements which increment by `1` starting from zero along one or more [ndarray][@stdlib/ndarray/ctor] dimensions. + +
+ +## Usage + +```javascript +var zeroTo = require( '@stdlib/blas/ext/zero-to' ); +``` + +#### zeroTo( shape\[, options] ) + +Returns a new [ndarray][@stdlib/ndarray/ctor] filled with linearly spaced numeric elements which increment by `1` starting from zero along one or more [ndarray][@stdlib/ndarray/ctor] dimensions. + +```javascript +var x = zeroTo( [ 2, 3 ] ); +// returns [ [ 0.0, 1.0, 2.0 ], [ 0.0, 1.0, 2.0 ] ] +``` + +The function has the following parameters: + +- **shape**: array shape. +- **options**: function options (_optional_). + +The function accepts the following options: + +- **dims**: list of dimensions over which to perform operation. If not provided, the function generates values along the last dimension. Default: `[-1]`. +- **dtype**: output [ndarray][@stdlib/ndarray/ctor] [data type][@stdlib/ndarray/dtypes]. Must be a numeric or "generic" [data type][@stdlib/ndarray/dtypes]. Default: `'float64'`. +- **order**: specifies whether an [ndarray][@stdlib/ndarray/ctor] is `'row-major'` (C-style) or `'column-major'` (Fortran-style). Default: `'row-major'`. +- **mode**: specifies how to handle indices which exceed array dimensions (see [`ndarray`][@stdlib/ndarray/ctor]). Default: `'throw'`. +- **submode**: a mode array which specifies for each dimension how to handle subscripts which exceed array dimensions (see [`ndarray`][@stdlib/ndarray/ctor]). If provided fewer modes than dimensions, the function recycles modes using modulo arithmetic. Default: `[ options.mode ]`. + +By default, the function generates values along the last dimension of an output [ndarray][@stdlib/ndarray/ctor]. To perform the operation over specific dimensions, provide a `dims` option. + +```javascript +var x = zeroTo( [ 2, 2 ], { + 'dims': [ 0, 1 ] +}); +// returns [ [ 0.0, 1.0 ], [ 2.0, 3.0 ] ] +``` + +To specify the output [ndarray][@stdlib/ndarray/ctor] [data type][@stdlib/ndarray/dtypes], provide a `dtype` option. + +```javascript +var x = zeroTo( [ 3 ], { + 'dtype': 'float32' +}); +// returns [ 0.0, 1.0, 2.0 ] +``` + +#### zeroTo.assign( x\[, options] ) + +Fills an [ndarray][@stdlib/ndarray/ctor] with linearly spaced numeric elements which increment by `1` starting from zero along one or more [ndarray][@stdlib/ndarray/ctor] dimensions. + +```javascript +var zeros = require( '@stdlib/ndarray/zeros' ); + +var x = zeros( [ 2, 3 ] ); +// returns [ [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ] ] + +var out = zeroTo.assign( x ); +// returns [ [ 0.0, 1.0, 2.0 ], [ 0.0, 1.0, 2.0 ] ] + +var bool = ( x === out ); +// returns true +``` + +The function has the following parameters: + +- **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a numeric or "generic" [data type][@stdlib/ndarray/dtypes]. +- **options**: function options (_optional_). + +The function accepts the following options: + +- **dims**: list of dimensions over which to perform operation. If not provided, the function generates values along the last dimension. Default: `[-1]`. + +
+ + + +
+ +## Notes + +- The function iterates over [ndarray][@stdlib/ndarray/ctor] elements according to the memory layout of the input [ndarray][@stdlib/ndarray/ctor]. Accordingly, performance degradation is possible when operating over multiple dimensions of a large non-contiguous multi-dimensional input [ndarray][@stdlib/ndarray/ctor]. In such scenarios, one may want to copy an input [ndarray][@stdlib/ndarray/ctor] to contiguous memory before performing the operation. + +
+ + + +
+ +## Examples + + + +```javascript +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var zeroTo = require( '@stdlib/blas/ext/zero-to' ); + +// Create a new ndarray: +var x = zeroTo( [ 5, 5 ], { + 'dtype': 'generic' +}); +console.log( ndarray2array( x ) ); + +// Generate values over a specific dimension: +x = zeroTo( [ 5, 5 ], { + 'dtype': 'generic', + 'dims': [ 0 ] +}); +console.log( ndarray2array( x ) ); + +// Generate values over all dimensions: +x = zeroTo( [ 5, 5 ], { + 'dtype': 'generic', + 'dims': [ 0, 1 ] +}); +console.log( ndarray2array( x ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor + +[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/dtypes + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/blas/ext/zero-to/benchmark/benchmark.assign.js new file mode 100644 index 000000000000..0087b9a7c7da --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/benchmark/benchmark.assign.js @@ -0,0 +1,103 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var assign = require( './../lib/assign.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = zeros( [ len ], options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var o; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + o = assign( x ); + if ( typeof o !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnan( x.get( i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/zero-to/benchmark/benchmark.js new file mode 100644 index 000000000000..dfdc4bb36380 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/benchmark/benchmark.js @@ -0,0 +1,101 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var zeroTo = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var o; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + o = zeroTo( [ len ], options ); + if ( typeof o !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnan( o.get( i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/zero-to/docs/repl.txt new file mode 100644 index 000000000000..eec9301746d7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/docs/repl.txt @@ -0,0 +1,92 @@ + +{{alias}}( shape[, options] ) + Returns a new ndarray filled with linearly spaced numeric elements which + increment by 1 starting from zero along one or more ndarray dimensions. + + Parameters + ---------- + shape: Array|integer + Array shape. + + options: Object (optional) + Function options. + + options.dims: Array (optional) + List of dimensions over which to perform operation. If not provided, + the function generates values along the last dimension. Default: [-1]. + + options.dtype: string (optional) + Output ndarray data type. Must be a numeric or "generic" data type. + Default: 'float64'. + + options.order: string (optional) + Specifies whether an array is row-major (C-style) or column-major + (Fortran-style). Default: 'row-major'. + + options.mode: string (optional) + Specifies how to handle indices which exceed array dimensions. If equal + to 'throw', an ndarray instance throws an error when an index exceeds + array dimensions. If equal to 'normalize', an ndarray instance + normalizes negative indices and throws an error when an index exceeds + array dimensions. If equal to 'wrap', an ndarray instance wraps around + indices exceeding array dimensions using modulo arithmetic. If equal to + 'clamp', an ndarray instance sets an index exceeding array dimensions + to either `0` (minimum index) or the maximum index. Default: 'throw'. + + options.submode: Array (optional) + Specifies how to handle subscripts which exceed array dimensions. If a + mode for a corresponding dimension is equal to 'throw', an ndarray + instance throws an error when a subscript exceeds array dimensions. If + equal to 'normalize', an ndarray instance normalizes negative + subscripts and throws an error when a subscript exceeds array + dimensions. If equal to 'wrap', an ndarray instance wraps around + subscripts exceeding array dimensions using modulo arithmetic. If equal + to 'clamp', an ndarray instance sets a subscript exceeding array + dimensions to either `0` (minimum index) or the maximum index. If the + number of modes is fewer than the number of dimensions, the function + recycles modes using modulo arithmetic. Default: [ options.mode ]. + + Returns + ------- + out: ndarray + Output array. + + Examples + -------- + > var out = {{alias}}( [ 2, 3 ] ) + [ [ 0.0, 1.0, 2.0 ], [ 0.0, 1.0, 2.0 ] ] + + +{{alias}}.assign( x[, options] ) + Fills an ndarray with linearly spaced numeric elements which increment by + 1 starting from zero along one or more ndarray dimensions. + + The function fills an ndarray in-place and thus mutates the input ndarray. + + Parameters + ---------- + x: ndarray + Input array. Must have a numeric or "generic" data type. + + options: Object (optional) + Function options. + + options.dims: Array (optional) + List of dimensions over which to perform operation. If not provided, + the function generates values along the last dimension. Default: [-1]. + + Returns + ------- + out: ndarray + Input array. + + Examples + -------- + > var x = {{alias:@stdlib/ndarray/zeros}}( [ 2, 3 ] ); + > var out = {{alias}}.assign( x ) + [ [ 0.0, 1.0, 2.0 ], [ 0.0, 1.0, 2.0 ] ] + > var bool = ( out === x ) + true + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/zero-to/docs/types/index.d.ts new file mode 100644 index 000000000000..1f28a866994c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/docs/types/index.d.ts @@ -0,0 +1,137 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { ArrayLike } from '@stdlib/types/array'; +import { NumericAndGenericDataType as DataType, typedndarray, genericndarray, Mode, Order } from '@stdlib/types/ndarray'; + +/** +* Output array. +*/ +type OutputArray = typedndarray | genericndarray; + +/** +* Interface defining "base" options. +*/ +interface BaseOptions { + /** + * List of dimensions over which to perform operation. + */ + dims?: ArrayLike; +} + +/** +* Interface defining options. +*/ +interface Options extends BaseOptions { + /** + * Output ndarray data type. + */ + dtype?: DataType; + + /** + * Array order (either 'row-major' (C-style) or 'column-major' (Fortran-style)). + */ + order?: Order; + + /** + * Specifies how to handle a linear index which exceeds array dimensions (default: 'throw'). + */ + mode?: Mode; + + /** + * Specifies how to handle subscripts which exceed array dimensions on a per dimension basis (default: ['throw']). + */ + submode?: Array; +} + +/** +* Interface for performing an operation on an ndarray. +*/ +interface ZeroTo { + /** + * Returns a new ndarray filled with linearly spaced numeric elements which increment by 1 starting from zero along one or more ndarray dimensions. + * + * @param shape - array shape + * @param options - function options + * @returns output ndarray + * + * @example + * var out = zeroTo( [ 2, 3 ] ); + * // returns [ [ 0.0, 1.0, 2.0 ], [ 0.0, 1.0, 2.0 ] ] + */ + ( shape: number | ArrayLike, options?: Options ): OutputArray; + + /** + * Fills an ndarray with linearly spaced numeric elements which increment by 1 starting from zero along one or more ndarray dimensions. + * + * ## Notes + * + * - The input ndarray is filled **in-place** (i.e., the input ndarray is **mutated**). + * + * @param x - input ndarray + * @param options - function options + * @returns output ndarray + * + * @example + * var zeros = require( '@stdlib/ndarray/zeros' ); + * + * var x = zeros( [ 2, 3 ] ); + * // returns [ [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ] ] + * + * var out = zeroTo.assign( x ); + * // returns [ [ 0.0, 1.0, 2.0 ], [ 0.0, 1.0, 2.0 ] ] + * + * var bool = ( out === x ); + * // returns true + */ + assign( x: T, options?: BaseOptions ): T; +} + +/** +* Returns a new ndarray filled with linearly spaced numeric elements which increment by 1 starting from zero along one or more ndarray dimensions. +* +* @param shape - array shape +* @param options - function options +* @returns output ndarray +* +* @example +* var out = zeroTo( [ 2, 3 ] ); +* // returns [ [ 0.0, 1.0, 2.0 ], [ 0.0, 1.0, 2.0 ] ] +* +* @example +* var zeros = require( '@stdlib/ndarray/zeros' ); +* +* var x = zeros( [ 2, 3 ] ); +* // returns [ [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ] ] +* +* var out = zeroTo.assign( x ); +* // returns [ [ 0.0, 1.0, 2.0 ], [ 0.0, 1.0, 2.0 ] ] +* +* var bool = ( out === x ); +* // returns true +*/ +declare const zeroTo: ZeroTo; + + +// EXPORTS // + +export = zeroTo; diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/zero-to/docs/types/test.ts new file mode 100644 index 000000000000..35bf4e48930f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/docs/types/test.ts @@ -0,0 +1,166 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +/// + +import zeros = require( '@stdlib/ndarray/zeros' ); +import zeroTo = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + zeroTo( [ 3 ] ); // $ExpectType OutputArray + zeroTo( [ 2, 2 ] ); // $ExpectType OutputArray + zeroTo( 3 ); // $ExpectType OutputArray + zeroTo( [ 3 ], {} ); // $ExpectType OutputArray + zeroTo( [ 3 ], { 'dtype': 'float32' } ); // $ExpectType OutputArray +} + +// The compiler throws an error if the function is provided a first argument which is not a number or an array of numbers... +{ + zeroTo( '5' ); // $ExpectError + zeroTo( true ); // $ExpectError + zeroTo( false ); // $ExpectError + zeroTo( null ); // $ExpectError + zeroTo( void 0 ); // $ExpectError + zeroTo( {} ); // $ExpectError + zeroTo( ( x: number ): number => x ); // $ExpectError + + zeroTo( '5', {} ); // $ExpectError + zeroTo( true, {} ); // $ExpectError + zeroTo( false, {} ); // $ExpectError + zeroTo( null, {} ); // $ExpectError + zeroTo( void 0, {} ); // $ExpectError + zeroTo( {}, {} ); // $ExpectError + zeroTo( ( x: number ): number => x, {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided an options argument which is not an object... +{ + zeroTo( [ 3 ], '5' ); // $ExpectError + zeroTo( [ 3 ], 5 ); // $ExpectError + zeroTo( [ 3 ], true ); // $ExpectError + zeroTo( [ 3 ], false ); // $ExpectError + zeroTo( [ 3 ], null ); // $ExpectError + zeroTo( [ 3 ], [] ); // $ExpectError + zeroTo( [ 3 ], ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid `dtype` option... +{ + zeroTo( [ 3 ], { 'dtype': '5' } ); // $ExpectError + zeroTo( [ 3 ], { 'dtype': 5 } ); // $ExpectError + zeroTo( [ 3 ], { 'dtype': true } ); // $ExpectError + zeroTo( [ 3 ], { 'dtype': false } ); // $ExpectError + zeroTo( [ 3 ], { 'dtype': null } ); // $ExpectError + zeroTo( [ 3 ], { 'dtype': [] } ); // $ExpectError + zeroTo( [ 3 ], { 'dtype': {} } ); // $ExpectError + zeroTo( [ 3 ], { 'dtype': ( x: number ): number => x } ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid `dims` option... +{ + zeroTo( [ 3 ], { 'dims': '5' } ); // $ExpectError + zeroTo( [ 3 ], { 'dims': 5 } ); // $ExpectError + zeroTo( [ 3 ], { 'dims': true } ); // $ExpectError + zeroTo( [ 3 ], { 'dims': false } ); // $ExpectError + zeroTo( [ 3 ], { 'dims': null } ); // $ExpectError + zeroTo( [ 3 ], { 'dims': {} } ); // $ExpectError + zeroTo( [ 3 ], { 'dims': ( x: number ): number => x } ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + zeroTo(); // $ExpectError + zeroTo( [ 3 ], {}, {} ); // $ExpectError +} + +// Attached to the function is an `assign` method which returns an ndarray... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + zeroTo.assign( x ); // $ExpectType float64ndarray + zeroTo.assign( x, {} ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the `assign` method is provided a first argument which is not an ndarray... +{ + zeroTo.assign( '5' ); // $ExpectError + zeroTo.assign( 5 ); // $ExpectError + zeroTo.assign( true ); // $ExpectError + zeroTo.assign( false ); // $ExpectError + zeroTo.assign( null ); // $ExpectError + zeroTo.assign( void 0 ); // $ExpectError + zeroTo.assign( {} ); // $ExpectError + zeroTo.assign( ( x: number ): number => x ); // $ExpectError + + zeroTo.assign( '5', {} ); // $ExpectError + zeroTo.assign( 5, {} ); // $ExpectError + zeroTo.assign( true, {} ); // $ExpectError + zeroTo.assign( false, {} ); // $ExpectError + zeroTo.assign( null, {} ); // $ExpectError + zeroTo.assign( void 0, {} ); // $ExpectError + zeroTo.assign( {}, {} ); // $ExpectError + zeroTo.assign( ( x: number ): number => x, {} ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided an options argument which is not an object... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + zeroTo.assign( x, '5' ); // $ExpectError + zeroTo.assign( x, 5 ); // $ExpectError + zeroTo.assign( x, true ); // $ExpectError + zeroTo.assign( x, false ); // $ExpectError + zeroTo.assign( x, null ); // $ExpectError + zeroTo.assign( x, [] ); // $ExpectError + zeroTo.assign( x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided an invalid `dims` option... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + zeroTo.assign( x, { 'dims': '5' } ); // $ExpectError + zeroTo.assign( x, { 'dims': 5 } ); // $ExpectError + zeroTo.assign( x, { 'dims': true } ); // $ExpectError + zeroTo.assign( x, { 'dims': false } ); // $ExpectError + zeroTo.assign( x, { 'dims': null } ); // $ExpectError + zeroTo.assign( x, { 'dims': {} } ); // $ExpectError + zeroTo.assign( x, { 'dims': ( x: number ): number => x } ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided an unsupported number of arguments... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + zeroTo.assign(); // $ExpectError + zeroTo.assign( x, {}, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/examples/index.js b/lib/node_modules/@stdlib/blas/ext/zero-to/examples/index.js new file mode 100644 index 000000000000..a2f04c93ede8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/examples/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var zeroTo = require( './../lib' ); + +// Create a new ndarray: +var x = zeroTo( [ 5, 5 ], { + 'dtype': 'generic' +}); +console.log( ndarray2array( x ) ); + +// Generate values over a specific dimension: +x = zeroTo( [ 5, 5 ], { + 'dtype': 'generic', + 'dims': [ 0 ] +}); +console.log( ndarray2array( x ) ); + +// Generate values over all dimensions: +x = zeroTo( [ 5, 5 ], { + 'dtype': 'generic', + 'dims': [ 0, 1 ] +}); +console.log( ndarray2array( x ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/lib/assign.js b/lib/node_modules/@stdlib/blas/ext/zero-to/lib/assign.js new file mode 100644 index 000000000000..3e287f2b6ce7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/lib/assign.js @@ -0,0 +1,105 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var isPlainObject = require( '@stdlib/assert/is-plain-object' ); +var isEmptyCollection = require( '@stdlib/assert/is-empty-collection' ); +var isIntegerArray = require( '@stdlib/assert/is-integer-array' ).primitives; +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var resolveStr = require( '@stdlib/ndarray/base/dtype-resolve-str' ); +var getDType = require( '@stdlib/ndarray/dtype' ); +var getShape = require( '@stdlib/ndarray/shape' ); +var contains = require( '@stdlib/array/base/assert/contains' ); +var join = require( '@stdlib/array/base/join' ); +var format = require( '@stdlib/string/format' ); +var DTYPES = require( './dtypes.js' ); +var defaults = require( './defaults.js' ); +var base = require( './base.js' ); + + +// MAIN // + +/** +* Fills an ndarray with linearly spaced numeric elements which increment by 1 starting from zero along one or more ndarray dimensions. +* +* @param {ndarrayLike} x - input ndarray +* @param {Options} [options] - function options +* @param {IntegerArray} [options.dims=[-1]] - list of dimensions over which to perform operation +* @throws {TypeError} first argument must be an ndarray-like object having at least one dimension +* @throws {TypeError} first argument must have a supported data type +* @throws {TypeError} options argument must be an object +* @throws {TypeError} must provide valid options +* @throws {RangeError} dimension indices must not exceed input ndarray bounds +* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions +* @returns {ndarray} input ndarray +* +* @example +* var zeros = require( '@stdlib/ndarray/zeros' ); +* +* var x = zeros( [ 2, 3 ] ); +* // returns [ [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ] ] +* +* var out = assign( x ); +* // returns [ [ 0.0, 1.0, 2.0 ], [ 0.0, 1.0, 2.0 ] ] +* +* var bool = ( out === x ); +* // returns true +*/ +function assign( x ) { + var options; + var opts; + var sh; + var dt; + + if ( !isndarrayLike( x ) ) { + throw new TypeError( format( 'invalid argument. First argument must be an ndarray. Value: `%s`.', x ) ); + } + sh = getShape( x ); + if ( sh.length < 1 ) { + throw new TypeError( 'invalid argument. First argument must be an ndarray having at least one dimension.' ); + } + dt = resolveStr( getDType( x ) ); + if ( !contains( DTYPES.odtypes, dt ) ) { + throw new TypeError( format( 'invalid argument. First argument must have one of the following data types: "%s". Data type: `%s`.', join( DTYPES.odtypes, '", "' ), dt ) ); + } + options = defaults(); + + if ( arguments.length > 1 ) { + opts = arguments[ 1 ]; + if ( !isPlainObject( opts ) ) { + throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', opts ) ); + } + if ( hasOwnProp( opts, 'dims' ) ) { + if ( !isIntegerArray( opts.dims ) && !isEmptyCollection( opts.dims ) ) { // eslint-disable-line max-len + throw new TypeError( format( 'invalid option. `%s` option must be an array of integers. Option: `%s`.', 'dims', opts.dims ) ); + } + options.dims = opts.dims; + } + } + // Perform operation: + return base( x, options ); +} + + +// EXPORTS // + +module.exports = assign; diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/lib/base.js b/lib/node_modules/@stdlib/blas/ext/zero-to/lib/base.js new file mode 100644 index 000000000000..b3dfd12ca75a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/lib/base.js @@ -0,0 +1,87 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var gzeroTo = require( '@stdlib/blas/ext/base/ndarray/gzero-to' ); +var dzeroTo = require( '@stdlib/blas/ext/base/ndarray/dzero-to' ); +var szeroTo = require( '@stdlib/blas/ext/base/ndarray/szero-to' ); +var czeroTo = require( '@stdlib/blas/ext/base/ndarray/czero-to' ); +var zzeroTo = require( '@stdlib/blas/ext/base/ndarray/zzero-to' ); +var factory = require( '@stdlib/ndarray/base/nullary-strided1d-dispatch-factory' ); +var DTYPES = require( './dtypes.js' ); + + +// VARIABLES // + +var table = { + 'types': [ + 'float64', // output + 'float32', // output + 'complex128', // output + 'complex64' // output + ], + 'fcns': [ + dzeroTo, + szeroTo, + zzeroTo, + czeroTo + ], + 'default': gzeroTo +}; +var options = { + 'strictTraversalOrder': true +}; + + +// MAIN // + +/** +* Fills an ndarray with linearly spaced numeric elements which increment by 1 starting from zero. +* +* @private +* @name zeroTo +* @type {Function} +* @param {ndarray} x - input ndarray +* @param {Options} [options] - function options +* @param {IntegerArray} [options.dims] - list of dimensions over which to perform operation +* @throws {TypeError} first argument must be an ndarray-like object +* @throws {TypeError} first argument must have a supported data type +* @throws {TypeError} options argument must be an object +* @throws {RangeError} dimension indices must not exceed input ndarray bounds +* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions +* @throws {Error} must provide valid options +* @returns {ndarray} input ndarray +* +* @example +* var zeros = require( '@stdlib/ndarray/zeros' ); +* +* var x = zeros( [ 2, 3 ] ); +* // returns [ [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ] ] +* +* var y = zeroTo( x ); +* // returns [ [ 0.0, 1.0, 2.0 ], [ 3.0, 4.0, 5.0 ] ] +*/ +var zeroTo = factory( table, [], DTYPES.odtypes, options ); + + +// EXPORTS // + +module.exports = zeroTo; diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/lib/defaults.js b/lib/node_modules/@stdlib/blas/ext/zero-to/lib/defaults.js new file mode 100644 index 000000000000..a8ac5148b369 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/lib/defaults.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Returns default options. +* +* @private +* @returns {Object} default options +*/ +function defaults() { + return { + 'dims': [ -1 ] // by default, generate values along the last dimension + }; +} + + +// EXPORTS // + +module.exports = defaults; diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/lib/dtypes.js b/lib/node_modules/@stdlib/blas/ext/zero-to/lib/dtypes.js new file mode 100644 index 000000000000..1b5a26cdd918 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/lib/dtypes.js @@ -0,0 +1,36 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var dtypes2strings = require( '@stdlib/ndarray/base/dtypes2strings' ); +var dtypes = require( '@stdlib/ndarray/dtypes' ); + + +// MAIN // + +var dt = { + 'odtypes': dtypes2strings( dtypes( 'numeric_and_generic' ) ) +}; + + +// EXPORTS // + +module.exports = dt; diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/lib/index.js b/lib/node_modules/@stdlib/blas/ext/zero-to/lib/index.js new file mode 100644 index 000000000000..efcfccacb5f5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/lib/index.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return a new ndarray filled with linearly spaced numeric elements which increment by 1 starting from zero along one or more ndarray dimensions. +* +* @module @stdlib/blas/ext/zero-to +* +* @example +* var zeroTo = require( '@stdlib/blas/ext/zero-to' ); +* +* var out = zeroTo( [ 2, 3 ] ); +* // returns [ [ 0.0, 1.0, 2.0 ], [ 0.0, 1.0, 2.0 ] ] +* +* @example +* var zeros = require( '@stdlib/ndarray/zeros' ); +* var zeroTo = require( '@stdlib/blas/ext/zero-to' ); +* +* var x = zeros( [ 2, 3 ] ); +* // returns [ [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ] ] +* +* var out = zeroTo.assign( x ); +* // returns [ [ 0.0, 1.0, 2.0 ], [ 0.0, 1.0, 2.0 ] ] +* +* var bool = ( out === x ); +* // returns true +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var assign = require( './assign.js' ); + + +// MAIN // + +setReadOnly( main, 'assign', assign ); + + +// EXPORTS // + +module.exports = main; + +// exports: { "assign": "main.assign" } diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/lib/main.js b/lib/node_modules/@stdlib/blas/ext/zero-to/lib/main.js new file mode 100644 index 000000000000..9f30dfb834c0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/lib/main.js @@ -0,0 +1,126 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var isPlainObject = require( '@stdlib/assert/is-plain-object' ); +var isNonNegativeIntegerArray = require( '@stdlib/assert/is-nonnegative-integer-array' ).primitives; +var isEmptyCollection = require( '@stdlib/assert/is-empty-collection' ); +var isIntegerArray = require( '@stdlib/assert/is-integer-array' ).primitives; +var isNonNegativeInteger = require( '@stdlib/assert/is-nonnegative-integer' ).isPrimitive; +var isOrder = require( '@stdlib/ndarray/base/assert/is-order' ); +var isDataType = require( '@stdlib/ndarray/base/assert/is-data-type' ); +var resolveStr = require( '@stdlib/ndarray/base/dtype-resolve-str' ); +var contains = require( '@stdlib/array/base/assert/contains' ); +var empty = require( '@stdlib/ndarray/empty' ); +var join = require( '@stdlib/array/base/join' ); +var format = require( '@stdlib/string/format' ); +var DTYPES = require( './dtypes.js' ); +var defaults = require( './defaults.js' ); +var base = require( './base.js' ); + + +// MAIN // + +/** +* Returns a new ndarray filled with linearly spaced numeric elements which increment by 1 starting from zero along one or more ndarray dimensions. +* +* @param {(NonNegativeInteger|NonNegativeIntegerArray)} shape - array shape +* @param {Options} [options] - function options +* @param {IntegerArray} [options.dims=[-1]] - list of dimensions over which to perform operation +* @param {*} [options.dtype] - output ndarray data type +* @param {string} [options.order] - ndarray order +* @param {string} [options.mode="throw"] - specifies how to handle indices which exceed ndarray dimensions +* @param {ArrayLikeObject} [options.submode=["throw"]] - specifies how to handle subscripts which exceed ndarray dimensions on a per dimension basis +* @throws {TypeError} first argument must be either a nonnegative integer or an array of nonnegative integers +* @throws {TypeError} options argument must be an object +* @throws {TypeError} must provide valid options +* @throws {RangeError} dimension indices must not exceed input ndarray bounds +* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions +* @returns {ndarray} output ndarray +* +* @example +* var out = zeroTo( [ 2, 3 ] ); +* // returns [ [ 0.0, 1.0, 2.0 ], [ 0.0, 1.0, 2.0 ] ] +*/ +function zeroTo( shape ) { + var options; + var opts; + var out; + var sh; + var dt; + + if ( isNonNegativeInteger( shape ) ) { + sh = [ shape ]; + } else if ( isNonNegativeIntegerArray( shape ) ) { + sh = shape; // Note: empty shape (i.e., a shape for a zero-dimensional ndarray) is not allowed + } else { + throw new TypeError( format( 'invalid argument. First argument must be a nonnegative integer or an array of nonnegative integers. Value: `%s`.', shape ) ); + } + options = defaults(); + + if ( arguments.length > 1 ) { + opts = arguments[ 1 ]; + if ( !isPlainObject( opts ) ) { + throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', opts ) ); + } + if ( hasOwnProp( opts, 'dtype' ) ) { + dt = resolveStr( opts.dtype ); + if ( !isDataType( opts.dtype ) || !contains( DTYPES.odtypes, dt ) ) { // eslint-disable-line max-len + throw new TypeError( format( 'invalid option. `%s` option must be one of the following: "%s". Option: `%s`.', 'dtype', join( DTYPES.odtypes, '", "' ), opts.dtype ) ); + } + options.dtype = dt; + } + if ( hasOwnProp( opts, 'order' ) ) { + if ( !isOrder( opts.order ) ) { + throw new TypeError( format( 'invalid option. `%s` option must be a supported order. Option: `%s`.', 'order', opts.order ) ); + } + options.order = opts.order; + } + if ( hasOwnProp( opts, 'mode' ) ) { + // Defer to `empty` to validate below... + options.mode = opts.mode; + } + if ( hasOwnProp( opts, 'submode' ) ) { + // Defer to `empty` to validate below... + options.submode = opts.submode; + } + if ( hasOwnProp( opts, 'dims' ) ) { + if ( !isIntegerArray( opts.dims ) && !isEmptyCollection( opts.dims ) ) { // eslint-disable-line max-len + throw new TypeError( format( 'invalid option. `%s` option must be an array of integers. Option: `%s`.', 'dims', opts.dims ) ); + } + options.dims = opts.dims; + } + } + // Set the default data type if not provided: + options.dtype = options.dtype || 'float64'; + + // Create an output ndarray: + out = empty( sh, options ); + + // Perform operation: + return base( out, options ); +} + + +// EXPORTS // + +module.exports = zeroTo; diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/package.json b/lib/node_modules/@stdlib/blas/ext/zero-to/package.json new file mode 100644 index 000000000000..290fd10db05f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/blas/ext/zero-to", + "version": "0.0.0", + "description": "Return a new ndarray filled with linearly spaced numeric elements which increment by 1 starting from zero along one or more ndarray dimensions.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "zero", + "fill", + "iota", + "sequence", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/test/test.assign.js b/lib/node_modules/@stdlib/blas/ext/zero-to/test/test.assign.js new file mode 100644 index 000000000000..81017816b81e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/test/test.assign.js @@ -0,0 +1,478 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ndarray = require( '@stdlib/ndarray/ctor' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var empty = require( '@stdlib/ndarray/empty' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var assign = require( './../lib/assign.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof assign, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object', function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + assign( value ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (options)', function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + assign( value, {} ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object having a supported data type', function test( t ) { + var values; + var i; + + values = [ + empty( [ 2, 2 ], { + 'dtype': 'bool' + }) + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + assign( value ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object having a supported data type (options)', function test( t ) { + var values; + var i; + + values = [ + empty( [ 2, 2 ], { + 'dtype': 'bool' + }) + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + assign( value, {} ); + }; + } +}); + +tape( 'the function throws an error if provided a second argument which is not an object', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + assign( x, value ); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which is not an array-like object of integers', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + assign( x, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains out-of-bounds indices', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + [ 5 ], + [ -5 ], + [ 2 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + assign( x, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains too many indices', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + [ 0, 1, 0 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + assign( x, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains duplicate indices', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + [ 0, 0 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + assign( x, { + 'dims': value + }); + }; + } +}); + +tape( 'the function fills an ndarray with linearly spaced values incrementing by 1 from zero', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'float64', xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); + expected = [ 0.0, 1.0, 2.0 ]; + + actual = assign( x ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function fills an ndarray with linearly spaced values incrementing by 1 from zero (row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'float64', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + expected = [ [ 0.0, 1.0 ], [ 0.0, 1.0 ] ]; + + actual = assign( x ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function fills an ndarray with linearly spaced values incrementing by 1 from zero (column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'float64', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + expected = [ [ 0.0, 1.0 ], [ 0.0, 1.0 ] ]; + + actual = assign( x ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function fills an ndarray with linearly spaced values incrementing by 1 from zero (all dimensions, row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'float64', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + expected = [ [ 0.0, 1.0 ], [ 2.0, 3.0 ] ]; + + actual = assign( x, { + 'dims': [ 0, 1 ] + }); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function fills an ndarray with linearly spaced values incrementing by 1 from zero (all dimensions, column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'float64', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + expected = [ [ 0.0, 2.0 ], [ 1.0, 3.0 ] ]; + + actual = assign( x, { + 'dims': [ 0, 1 ] + }); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function fills an ndarray with linearly spaced values incrementing by 1 from zero (no dimensions, row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'float64', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + expected = [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]; + + actual = assign( x, { + 'dims': [] + }); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function fills an ndarray with linearly spaced values incrementing by 1 from zero (no dimensions, column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'float64', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + expected = [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]; + + actual = assign( x, { + 'dims': [] + }); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying operation dimensions (row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'float64', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + expected = [ [ 0.0, 0.0 ], [ 1.0, 1.0 ] ]; + + actual = assign( x, { + 'dims': [ 0 ] + }); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'float64', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + expected = [ [ 0.0, 1.0 ], [ 0.0, 1.0 ] ]; + + actual = assign( x, { + 'dims': [ 1 ] + }); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying operation dimensions (column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'float64', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + expected = [ [ 0.0, 0.0 ], [ 1.0, 1.0 ] ]; + + actual = assign( x, { + 'dims': [ 0 ] + }); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'float64', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + expected = [ [ 0.0, 1.0 ], [ 0.0, 1.0 ] ]; + + actual = assign( x, { + 'dims': [ 1 ] + }); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/test/test.js b/lib/node_modules/@stdlib/blas/ext/zero-to/test/test.js new file mode 100644 index 000000000000..f01239ae22f6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/test/test.js @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isMethod = require( '@stdlib/assert/is-method' ); +var zeroTo = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zeroTo, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is an `assign` method', function test( t ) { + t.strictEqual( isMethod( zeroTo, 'assign' ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/zero-to/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/zero-to/test/test.main.js new file mode 100644 index 000000000000..a0a957671fae --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/zero-to/test/test.main.js @@ -0,0 +1,432 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var getDType = require( '@stdlib/ndarray/dtype' ); +var getShape = require( '@stdlib/ndarray/shape' ); +var getOrder = require( '@stdlib/ndarray/order' ); +var zeroTo = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zeroTo, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a first argument which is not a nonnegative integer or an array of nonnegative integers', function test( t ) { + var values; + var i; + + values = [ + '5', + -1, + 3.14, + NaN, + true, + false, + null, + void 0, + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + zeroTo( value ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not a nonnegative integer or an array of nonnegative integers (options)', function test( t ) { + var values; + var i; + + values = [ + '5', + -1, + 3.14, + NaN, + true, + false, + null, + void 0, + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + zeroTo( value, {} ); + }; + } +}); + +tape( 'the function throws an error if provided a second argument which is not an object', function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + zeroTo( [ 2, 2 ], value ); + }; + } +}); + +tape( 'the function throws an error if provided an invalid `dtype` option', function test( t ) { + var values; + var i; + + values = [ + 'foo', + 'bool', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + zeroTo( [ 2, 2 ], { + 'dtype': value + }); + }; + } +}); + +tape( 'the function throws an error if provided an invalid `order` option', function test( t ) { + var values; + var i; + + values = [ + 'foo', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + zeroTo( [ 2, 2 ], { + 'order': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which is not an array-like object of integers', function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + zeroTo( [ 2, 2 ], { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains out-of-bounds indices', function test( t ) { + var values; + var i; + + values = [ + [ 5 ], + [ -5 ], + [ 2 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + zeroTo( [ 2, 2 ], { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains too many indices', function test( t ) { + var values; + var i; + + values = [ + [ 0, 1, 0 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + zeroTo( [ 2, 2 ], { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains duplicate indices', function test( t ) { + var values; + var i; + + values = [ + [ 0, 0 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + zeroTo( [ 2, 2 ], { + 'dims': value + }); + }; + } +}); + +tape( 'the function returns an ndarray containing linearly spaced values incrementing by 1 from zero', function test( t ) { + var expected; + var actual; + + expected = [ 0.0, 1.0, 2.0 ]; + actual = zeroTo( 3 ); + + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 3 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + expected = [ 0.0, 1.0, 2.0 ]; + actual = zeroTo( [ 3 ] ); + + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 3 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + expected = [ [ 0.0, 1.0 ], [ 0.0, 1.0 ] ]; + actual = zeroTo( [ 2, 2 ] ); + + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying an output data type', function test( t ) { + var expected; + var actual; + + expected = [ 0.0, 1.0, 2.0 ]; + actual = zeroTo( [ 3 ], { + 'dtype': 'float32' + }); + + t.strictEqual( String( getDType( actual ) ), 'float32', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 3 ], 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying an output array order', function test( t ) { + var expected; + var actual; + + expected = [ [ 0.0, 1.0 ], [ 0.0, 1.0 ] ]; + actual = zeroTo( [ 2, 2 ], { + 'order': 'row-major' + }); + + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + expected = [ [ 0.0, 1.0 ], [ 0.0, 1.0 ] ]; + actual = zeroTo( [ 2, 2 ], { + 'order': 'column-major' + }); + + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), 'column-major', 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying operation dimensions', function test( t ) { + var expected; + var actual; + + expected = [ [ 0.0, 1.0 ], [ 0.0, 1.0 ] ]; + actual = zeroTo( [ 2, 2 ], { + 'dims': [ -1 ] + }); + + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + expected = [ [ 0.0, 0.0 ], [ 1.0, 1.0 ] ]; + actual = zeroTo( [ 2, 2 ], { + 'dims': [ 0 ] + }); + + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + expected = [ [ 0.0, 1.0 ], [ 2.0, 3.0 ] ]; + actual = zeroTo( [ 2, 2 ], { + 'dims': [ 0, 1 ] + }); + + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + expected = [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]; + actual = zeroTo( [ 2, 2 ], { + 'dims': [] + }); + + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying array index modes and submodes', function test( t ) { + var expected; + var actual; + var opts; + + opts = { + 'mode': 'clamp', + 'submode': [ 'wrap' ] + }; + actual = zeroTo( [ 2, 2, 3 ], opts ); + expected = [ + [ + // 0 1 2 + [ 0.0, 1.0, 2.0 ], + + // 3 4 5 + [ 0.0, 1.0, 2.0 ] + ], + [ + // 6 7 8 + [ 0.0, 1.0, 2.0 ], + + // 9 10 11 + [ 0.0, 1.0, 2.0 ] + ] + ]; + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + // Clamped: + t.strictEqual( actual.iget( actual.length+10 ), 2.0, 'returns expected value' ); + actual.iset( actual.length+10, 10.0 ); + t.strictEqual( actual.iget( actual.length+10 ), 10.0, 'returns expected value' ); + + // Wrapped: + t.strictEqual( actual.get( 2, 2, 3 ), 0.0, 'returns expected value' ); + actual.set( 2, 2, 3, 30.0 ); + t.strictEqual( actual.get( 0, 0, 0 ), 30.0, 'returns expected value' ); + t.strictEqual( actual.get( 2, 2, 3 ), 30.0, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/sswap/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/sswap/benchmark/benchmark.js index ea80b8712700..dd907a420f34 100644 --- a/lib/node_modules/@stdlib/blas/sswap/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/sswap/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var array = require( '@stdlib/ndarray/array' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sswap = require( './../lib/main.js' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/blas/sswap/benchmark/benchmark.stacks.js b/lib/node_modules/@stdlib/blas/sswap/benchmark/benchmark.stacks.js index f027899c21db..458fa58b5291 100644 --- a/lib/node_modules/@stdlib/blas/sswap/benchmark/benchmark.stacks.js +++ b/lib/node_modules/@stdlib/blas/sswap/benchmark/benchmark.stacks.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var numel = require( '@stdlib/ndarray/base/numel' ); var array = require( '@stdlib/ndarray/array' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sswap = require( './../lib/main.js' ); @@ -111,11 +112,11 @@ function main() { shape = [ 2, N/2 ]; f = createBenchmark( shape ); - bench( pkg+'::stacks:size='+N+',ndims='+shape.length+',shape=('+shape.join( ',' )+')', f ); + bench( format( '%s::stacks:size=%d,ndims=%d,shape=(%s)', pkg, N, shape.length, shape.join( ',' ) ), f ); shape = [ N/2, 2 ]; f = createBenchmark( shape ); - bench( pkg+'::stacks:size='+N+',ndims='+shape.length+',shape=('+shape.join( ',' )+')', f ); + bench( format( '%s::stacks:size=%d,ndims=%d,shape=(%s)', pkg, N, shape.length, shape.join( ',' ) ), f ); } } diff --git a/lib/node_modules/@stdlib/complex/float32/base/mul-add/README.md b/lib/node_modules/@stdlib/complex/float32/base/mul-add/README.md index ac0da3f66d3c..274afb7653af 100644 --- a/lib/node_modules/@stdlib/complex/float32/base/mul-add/README.md +++ b/lib/node_modules/@stdlib/complex/float32/base/mul-add/README.md @@ -183,9 +183,9 @@ Performs a multiply-add operation involving three single-precision complex float #include "stdlib/complex/float32/real.h" #include "stdlib/complex/float32/imag.h" -stdlib_complex64_t z1 = sstdlib_complex64( 5.0f, 3.0f ); -stdlib_complex64_t z2 = sstdlib_complex64( -2.0f, 1.0f ); -stdlib_complex64_t z3 = sstdlib_complex64( 7.0f, -8.0f ); +stdlib_complex64_t z1 = stdlib_complex64( 5.0f, 3.0f ); +stdlib_complex64_t z2 = stdlib_complex64( -2.0f, 1.0f ); +stdlib_complex64_t z3 = stdlib_complex64( 7.0f, -8.0f ); stdlib_complex64_t out = stdlib_base_complex64_muladd( z1, z2, z3 ); diff --git a/lib/node_modules/@stdlib/datasets/us-states-names-capitals/README.md b/lib/node_modules/@stdlib/datasets/us-states-names-capitals/README.md index c949334250fd..1eba8b10751b 100644 --- a/lib/node_modules/@stdlib/datasets/us-states-names-capitals/README.md +++ b/lib/node_modules/@stdlib/datasets/us-states-names-capitals/README.md @@ -103,6 +103,7 @@ var t = table(); ```javascript +var format = require( '@stdlib/string/format' ); var capitalize = require( '@stdlib/string/capitalize' ); var table = require( '@stdlib/datasets/us-states-names-capitals' ); @@ -123,7 +124,7 @@ function getCapital( state ) { // Ensure a valid state name was provided... if ( capital === void 0 ) { - throw new Error( 'unrecognized state name. Value: `' + state + '`.' ); + throw new Error( format( 'unrecognized state name. Value: `%s`.', state ) ); } return capital; } diff --git a/lib/node_modules/@stdlib/datasets/us-states-names-capitals/examples/index.js b/lib/node_modules/@stdlib/datasets/us-states-names-capitals/examples/index.js index c58ac2623b95..e539127ca9d6 100644 --- a/lib/node_modules/@stdlib/datasets/us-states-names-capitals/examples/index.js +++ b/lib/node_modules/@stdlib/datasets/us-states-names-capitals/examples/index.js @@ -18,6 +18,7 @@ 'use strict'; +var format = require( '@stdlib/string/format' ); var capitalize = require( '@stdlib/string/capitalize' ); var table = require( './../lib' ); @@ -38,7 +39,7 @@ function getCapital( state ) { // Ensure a valid state name was provided... if ( capital === void 0 ) { - throw new Error( 'unrecognized state name. Value: `' + state + '`.' ); + throw new Error( format( 'unrecognized state name. Value: `%s`.', state ) ); } return capital; } diff --git a/lib/node_modules/@stdlib/error/tools/msg2id/lib/index.js b/lib/node_modules/@stdlib/error/tools/msg2id/lib/index.js index 8b8f704684a7..4a2c2d9a6155 100644 --- a/lib/node_modules/@stdlib/error/tools/msg2id/lib/index.js +++ b/lib/node_modules/@stdlib/error/tools/msg2id/lib/index.js @@ -27,7 +27,7 @@ * var msg2id = require( '@stdlib/error/tools/msg2id' ); * * var v = msg2id( 'invalid option. `%s` option must be an array. Option: `%s`.' ); -* // returns '8t' +* // returns '8Z' */ // MODULES // diff --git a/lib/node_modules/@stdlib/lapack/base/dge-trans/docs/types/index.d.ts b/lib/node_modules/@stdlib/lapack/base/dge-trans/docs/types/index.d.ts index 4872d0058efc..9206ef9b85c3 100644 --- a/lib/node_modules/@stdlib/lapack/base/dge-trans/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/lapack/base/dge-trans/docs/types/index.d.ts @@ -39,7 +39,7 @@ interface Routine { * @returns `out` * * @example - * var Float64Array = require( `@stdlib/array/float64` ); + * var Float64Array = require( '@stdlib/array/float64' ); * * var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var out = new Float64Array( 6 ); @@ -65,7 +65,7 @@ interface Routine { * @returns `out` * * @example - * var Float64Array = require( `@stdlib/array/float64` ); + * var Float64Array = require( '@stdlib/array/float64' ); * * var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var out = new Float64Array( 6 ); @@ -89,7 +89,7 @@ interface Routine { * @returns `out` * * @example -* var Float64Array = require( `@stdlib/array/float64` ); +* var Float64Array = require( '@stdlib/array/float64' ); * * var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var out = new Float64Array( 6 ); @@ -98,7 +98,7 @@ interface Routine { * // returns [ 1.0, 4.0, 2.0, 5.0, 3.0, 6.0 ] * * @example -* var Float64Array = require( `@stdlib/array/float64` ); +* var Float64Array = require( '@stdlib/array/float64' ); * * var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var out = new Float64Array( 6 ); diff --git a/lib/node_modules/@stdlib/lapack/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/lapack/base/docs/types/index.d.ts index b5153b00cceb..2da4696ee10e 100644 --- a/lib/node_modules/@stdlib/lapack/base/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/lapack/base/docs/types/index.d.ts @@ -253,7 +253,7 @@ interface Namespace { * @returns `out` * * @example - * var Float64Array = require( `@stdlib/array/float64` ); + * var Float64Array = require( '@stdlib/array/float64' ); * * var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var out = new Float64Array( 6 ); @@ -262,7 +262,7 @@ interface Namespace { * // returns [ 1.0, 4.0, 2.0, 5.0, 3.0, 6.0 ] * * @example - * var Float64Array = require( `@stdlib/array/float64` ); + * var Float64Array = require( '@stdlib/array/float64' ); * * var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var out = new Float64Array( 6 ); diff --git a/lib/node_modules/@stdlib/math/array/tools/unary-factory/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/math/array/tools/unary-factory/benchmark/benchmark.assign.js index 495f624ab65e..f345252f850f 100644 --- a/lib/node_modules/@stdlib/math/array/tools/unary-factory/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/math/array/tools/unary-factory/benchmark/benchmark.assign.js @@ -27,6 +27,7 @@ var identity = require( '@stdlib/number/float64/base/identity' ); var dtypes = require( '@stdlib/array/dtypes' ); var uniform = require( '@stdlib/random/array/uniform' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var factory = require( './../lib' ); @@ -108,7 +109,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:len='+len, f ); + bench( format( '%s:assign:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/array/tools/unary-factory/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/array/tools/unary-factory/benchmark/benchmark.js index 9b47162e6183..de48c79aa78a 100644 --- a/lib/node_modules/@stdlib/math/array/tools/unary-factory/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/array/tools/unary-factory/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var abs = require( '@stdlib/math/base/special/abs' ); var sin = require( '@stdlib/math/base/special/sin' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var factory = require( './../lib' ); // MAIN // -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var values; var dtypes; var v; diff --git a/lib/node_modules/@stdlib/math/array/tools/unary-factory/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/math/array/tools/unary-factory/benchmark/benchmark.length.js index 0a920e8190b4..0356d6955bd8 100644 --- a/lib/node_modules/@stdlib/math/array/tools/unary-factory/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/math/array/tools/unary-factory/benchmark/benchmark.length.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var identity = require( '@stdlib/number/float64/base/identity' ); var dtypes = require( '@stdlib/array/dtypes' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var factory = require( './../lib' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::apply:len='+len, f ); + bench( format( '%s::apply:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/array/tools/unary/benchmark/benchmark.apply.js b/lib/node_modules/@stdlib/math/array/tools/unary/benchmark/benchmark.apply.js index 191e05f4efc1..431b36880a77 100644 --- a/lib/node_modules/@stdlib/math/array/tools/unary/benchmark/benchmark.apply.js +++ b/lib/node_modules/@stdlib/math/array/tools/unary/benchmark/benchmark.apply.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var identity = require( '@stdlib/number/float64/base/identity' ); var dtypes = require( '@stdlib/array/dtypes' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Unary = require( './../lib' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':apply:len='+len, f ); + bench( format( '%s:apply:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/array/tools/unary/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/math/array/tools/unary/benchmark/benchmark.assign.js index 3f448234825e..767a06f658d3 100644 --- a/lib/node_modules/@stdlib/math/array/tools/unary/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/math/array/tools/unary/benchmark/benchmark.assign.js @@ -27,6 +27,7 @@ var identity = require( '@stdlib/number/float64/base/identity' ); var dtypes = require( '@stdlib/array/dtypes' ); var uniform = require( '@stdlib/random/array/uniform' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Unary = require( './../lib' ); @@ -108,7 +109,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:len='+len, f ); + bench( format( '%s:assign:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/array/tools/unary/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/array/tools/unary/benchmark/benchmark.js index bdfd357aa9a2..983f18dab23d 100644 --- a/lib/node_modules/@stdlib/math/array/tools/unary/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/array/tools/unary/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var abs = require( '@stdlib/math/base/special/abs' ); var sin = require( '@stdlib/math/base/special/sin' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Unary = require( './../lib' ); // MAIN // -bench( pkg+'::new', function benchmark( b ) { +bench( format( '%s::new', pkg ), function benchmark( b ) { var values; var dtypes; var v; @@ -59,7 +60,7 @@ bench( pkg+'::new', function benchmark( b ) { b.end(); }); -bench( pkg+'::no_new', function benchmark( b ) { +bench( format( '%s::no_new', pkg ), function benchmark( b ) { var values; var dtypes; var fcn; diff --git a/lib/node_modules/@stdlib/math/base/assert/is-composite/benchmark/benchmark.primes.js b/lib/node_modules/@stdlib/math/base/assert/is-composite/benchmark/benchmark.primes.js index b4075a54f648..530c2eccec39 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-composite/benchmark/benchmark.primes.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-composite/benchmark/benchmark.primes.js @@ -25,6 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var log10 = require( '@stdlib/math/base/special/log10' ); var floor = require( '@stdlib/math/base/special/floor' ); var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var PRIMES = require( './../test/fixtures/primes.js' ); var isComposite = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { j = pow( 10, i ) - 1; p = PRIMES[ j ]; f = createBenchmark( p ); - bench( pkg+':prime='+p, f ); + bench( format( '%s:prime=%d', pkg, p ), f ); } } diff --git a/lib/node_modules/@stdlib/math/base/assert/is-integer/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/base/assert/is-integer/benchmark/benchmark.js index 980f1099c05f..8227b195eac1 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-integer/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-integer/benchmark/benchmark.js @@ -22,13 +22,14 @@ var bench = require( '@stdlib/bench' ); var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var isInteger = require( './../lib' ); // MAIN // -bench( pkg+'::true', function benchmark( b ) { +bench( format( '%s::true', pkg ), function benchmark( b ) { var values; var bool; var i; @@ -75,7 +76,7 @@ bench( pkg+'::true', function benchmark( b ) { b.end(); }); -bench( pkg+'::false', function benchmark( b ) { +bench( format( '%s::false', pkg ), function benchmark( b ) { var values; var bool; var i; diff --git a/lib/node_modules/@stdlib/math/base/assert/is-integer/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/assert/is-integer/benchmark/benchmark.native.js index 72cf0d231cba..47f734f5326b 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-integer/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-integer/benchmark/benchmark.native.js @@ -24,6 +24,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -37,7 +38,7 @@ var opts = { // MAIN // -bench( pkg+'::native,true', opts, function benchmark( b ) { +bench( format( '%s::native,true', pkg ), opts, function benchmark( b ) { var values; var bool; var i; @@ -84,7 +85,7 @@ bench( pkg+'::native,true', opts, function benchmark( b ) { b.end(); }); -bench( pkg+'::native,false', opts, function benchmark( b ) { +bench( format( '%s::native,false', pkg ), opts, function benchmark( b ) { var values; var bool; var i; diff --git a/lib/node_modules/@stdlib/math/base/assert/is-integerf/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/base/assert/is-integerf/benchmark/benchmark.js index e64368e56797..d77e885b3ce9 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-integerf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-integerf/benchmark/benchmark.js @@ -22,13 +22,14 @@ var bench = require( '@stdlib/bench' ); var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var isIntegerf = require( './../lib' ); // MAIN // -bench( pkg+'::true', function benchmark( b ) { +bench( format( '%s::true', pkg ), function benchmark( b ) { var values; var bool; var i; @@ -75,7 +76,7 @@ bench( pkg+'::true', function benchmark( b ) { b.end(); }); -bench( pkg+'::false', function benchmark( b ) { +bench( format( '%s::false', pkg ), function benchmark( b ) { var values; var bool; var i; diff --git a/lib/node_modules/@stdlib/math/base/assert/is-integerf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/assert/is-integerf/benchmark/benchmark.native.js index 26c6c29ef5ba..0e4a1f847382 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-integerf/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-integerf/benchmark/benchmark.native.js @@ -24,6 +24,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -37,7 +38,7 @@ var opts = { // MAIN // -bench( pkg+'::native,true', opts, function benchmark( b ) { +bench( format( '%s::native,true', pkg ), opts, function benchmark( b ) { var values; var bool; var i; @@ -84,7 +85,7 @@ bench( pkg+'::native,true', opts, function benchmark( b ) { b.end(); }); -bench( pkg+'::native,false', opts, function benchmark( b ) { +bench( format( '%s::native,false', pkg ), opts, function benchmark( b ) { var values; var bool; var i; diff --git a/lib/node_modules/@stdlib/math/base/assert/is-prime/benchmark/benchmark.primes.js b/lib/node_modules/@stdlib/math/base/assert/is-prime/benchmark/benchmark.primes.js index e8590b71c1cd..f4db0bcace3e 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-prime/benchmark/benchmark.primes.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-prime/benchmark/benchmark.primes.js @@ -25,6 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var log10 = require( '@stdlib/math/base/special/log10' ); var floor = require( '@stdlib/math/base/special/floor' ); var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var PRIMES = require( './../test/fixtures/primes.js' ); var isPrime = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { j = pow( 10, i ) - 1; p = PRIMES[ j ]; f = createBenchmark( p ); - bench( pkg+':prime='+p, f ); + bench( format( '%s:prime=%d', pkg, p ), f ); } } diff --git a/lib/node_modules/@stdlib/math/base/special/acosh/test/test.js b/lib/node_modules/@stdlib/math/base/special/acosh/test/test.js index f441c0f3e90b..2823382e734f 100644 --- a/lib/node_modules/@stdlib/math/base/special/acosh/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/acosh/test/test.js @@ -25,7 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var randu = require( '@stdlib/random/base/randu' ); var EPS = require( '@stdlib/constants/float64/eps' ); var PINF = require( '@stdlib/constants/float64/pinf' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var isPositiveZero = require( '@stdlib/assert/is-positive-zero' ); var acosh = require( './../lib' ); @@ -48,8 +48,6 @@ tape( 'main export is a function', function test( t ) { tape( 'the function computes the hyperbolic arccosine on the interval [1.0,3.0]', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -59,21 +57,13 @@ tape( 'the function computes the hyperbolic arccosine on the interval [1.0,3.0]' for ( i = 0; i < x.length; i++ ) { y = acosh( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = 1.0 * EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the hyperbolic arccosine on the interval [3.0,28.0]', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -83,21 +73,13 @@ tape( 'the function computes the hyperbolic arccosine on the interval [3.0,28.0] for ( i = 0; i < x.length; i++ ) { y = acosh( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = 1.0 * EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the hyperbolic arccosine on the interval [28.0,100.0]', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -107,21 +89,13 @@ tape( 'the function computes the hyperbolic arccosine on the interval [28.0,100. for ( i = 0; i < x.length; i++ ) { y = acosh( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = 1.0 * EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the hyperbolic arccosine for huge values', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -131,13 +105,7 @@ tape( 'the function computes the hyperbolic arccosine for huge values', function for ( i = 0; i < x.length; i++ ) { y = acosh( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = 1.0 * EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/special/acosh/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/acosh/test/test.native.js index e3de12ae6c89..f847905ed8eb 100644 --- a/lib/node_modules/@stdlib/math/base/special/acosh/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/special/acosh/test/test.native.js @@ -26,7 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var randu = require( '@stdlib/random/base/randu' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var EPS = require( '@stdlib/constants/float64/eps' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var isPositiveZero = require( '@stdlib/assert/is-positive-zero' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -57,8 +57,6 @@ tape( 'main export is a function', opts, function test( t ) { tape( 'the function computes the hyperbolic arccosine on the interval [1.0,3.0]', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -68,21 +66,13 @@ tape( 'the function computes the hyperbolic arccosine on the interval [1.0,3.0]' for ( i = 0; i < x.length; i++ ) { y = acosh( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = 1.0 * EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the hyperbolic arccosine on the interval [3.0,28.0]', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -92,21 +82,13 @@ tape( 'the function computes the hyperbolic arccosine on the interval [3.0,28.0] for ( i = 0; i < x.length; i++ ) { y = acosh( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = 1.0 * EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the hyperbolic arccosine on the interval [28.0,100.0]', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -116,21 +98,13 @@ tape( 'the function computes the hyperbolic arccosine on the interval [28.0,100. for ( i = 0; i < x.length; i++ ) { y = acosh( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = 1.0 * EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the hyperbolic arccosine for huge values', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -140,13 +114,7 @@ tape( 'the function computes the hyperbolic arccosine for huge values', opts, fu for ( i = 0; i < x.length; i++ ) { y = acosh( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = 1.0 * EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/special/acotd/README.md b/lib/node_modules/@stdlib/math/base/special/acotd/README.md index 829092b881e1..4760db9ef127 100644 --- a/lib/node_modules/@stdlib/math/base/special/acotd/README.md +++ b/lib/node_modules/@stdlib/math/base/special/acotd/README.md @@ -114,7 +114,7 @@ double out = stdlib_base_acotd( 0.0 ); // returns 90.0 out = stdlib_base_acotd( 3.0 ); -// returns ~30.0 +// returns ~18.43495 ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/math/base/special/acotdf/README.md b/lib/node_modules/@stdlib/math/base/special/acotdf/README.md index e0ea3bd35495..2f76954bfb03 100644 --- a/lib/node_modules/@stdlib/math/base/special/acotdf/README.md +++ b/lib/node_modules/@stdlib/math/base/special/acotdf/README.md @@ -114,7 +114,7 @@ float out = stdlib_base_acotdf( 0.0f ); // returns 90.0f out = stdlib_base_acotdf( 3.0f ); -// returns ~30.0f +// returns 18.43495f ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/math/base/special/cceiln/README.md b/lib/node_modules/@stdlib/math/base/special/cceiln/README.md index 72dfb5126eef..befda7b2b10d 100644 --- a/lib/node_modules/@stdlib/math/base/special/cceiln/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cceiln/README.md @@ -36,50 +36,24 @@ Rounds each component of a double-precision complex floating-point number to the ```javascript var Complex128 = require( '@stdlib/complex/float64/ctor' ); -var real = require( '@stdlib/complex/float64/real' ); -var imag = require( '@stdlib/complex/float64/imag' ); // Round components to 2 decimal places: var z = new Complex128( -3.141592653589793, 3.141592653589793 ); var v = cceiln( z, -2 ); -// returns - -var re = real( v ); -// returns -3.14 - -var im = imag( v ); -// returns 3.15 +// returns [ -3.14, 3.15 ] // If n = 0, `cceiln` behaves like `cceil`: z = new Complex128( 9.99999, 0.1 ); v = cceiln( z, 0 ); -// returns - -re = real( v ); -// returns 10.0 - -im = imag( v ); -// returns 1.0 +// returns [ 10.0, 1.0 ] // Round components to the nearest thousand: z = new Complex128( 12368.0, -12368.0 ); v = cceiln( z, 3 ); -// returns - -re = real( v ); -// returns 13000.0 - -im = imag( v ); -// returns -12000.0 +// returns [ 13000.0, -12000.0 ] v = cceiln( new Complex128( NaN, NaN ), 2 ); -// returns - -re = real( v ); -// returns NaN - -im = imag( v ); -// returns NaN +// returns [ NaN, NaN ] ```
diff --git a/lib/node_modules/@stdlib/math/base/special/cceiln/docs/repl.txt b/lib/node_modules/@stdlib/math/base/special/cceiln/docs/repl.txt index b45365e512ec..5b018d05ef6d 100644 --- a/lib/node_modules/@stdlib/math/base/special/cceiln/docs/repl.txt +++ b/lib/node_modules/@stdlib/math/base/special/cceiln/docs/repl.txt @@ -19,11 +19,7 @@ Examples -------- > var out = {{alias}}( new {{alias:@stdlib/complex/float64/ctor}}( 5.555, -3.333 ), -2 ) - - > var re = {{alias:@stdlib/complex/float64/real}}( out ) - 5.56 - > var im = {{alias:@stdlib/complex/float64/imag}}( out ) - -3.33 + [ 5.56, -3.33 ] See Also -------- diff --git a/lib/node_modules/@stdlib/math/base/special/cceiln/docs/types/index.d.ts b/lib/node_modules/@stdlib/math/base/special/cceiln/docs/types/index.d.ts index 0df302a8f96d..83392b4bb1df 100644 --- a/lib/node_modules/@stdlib/math/base/special/cceiln/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/math/base/special/cceiln/docs/types/index.d.ts @@ -31,17 +31,9 @@ import { Complex128 } from '@stdlib/types/complex'; * * @example * var Complex128 = require( '@stdlib/complex/float64/ctor' ); -* var real = require( '@stdlib/complex/float64/real' ); -* var imag = require( '@stdlib/complex/float64/imag' ); * * var v = cceiln( new Complex128( 5.555, -3.333 ), -2 ); -* // returns -* -* var re = real( v ); -* // returns 5.56 -* -* var im = imag( v ); -* // returns -3.33 +* // returns [ 5.56, -3.33 ] */ declare function cceiln( z: Complex128, n: number ): Complex128; diff --git a/lib/node_modules/@stdlib/math/base/special/cceiln/lib/index.js b/lib/node_modules/@stdlib/math/base/special/cceiln/lib/index.js index 681ecd911f25..6a06391c83c6 100644 --- a/lib/node_modules/@stdlib/math/base/special/cceiln/lib/index.js +++ b/lib/node_modules/@stdlib/math/base/special/cceiln/lib/index.js @@ -25,51 +25,25 @@ * * @example * var Complex128 = require( '@stdlib/complex/float64/ctor' ); -* var real = require( '@stdlib/complex/float64/real' ); -* var imag = require( '@stdlib/complex/float64/imag' ); * var cceiln = require( '@stdlib/math/base/special/cceiln' ); * * // Round components to 2 decimal places: -* var z = new Complex128( -3.141592653589793, 3.141592653589793 ) +* var z = new Complex128( -3.141592653589793, 3.141592653589793 ); * var v = cceiln( z, -2 ); -* // returns -* -* var re = real( v ); -* // returns -3.14 -* -* var im = imag( v ); -* // returns 3.15 +* // returns [ -3.14, 3.15 ] * * // If n = 0, `cceiln` behaves like `cceil`: -* z = new Complex128( 9.99999, 0.1 ) +* z = new Complex128( 9.99999, 0.1 ); * v = cceiln( z, 0 ); -* // returns -* -* re = real( v ); -* // returns 10.0 -* -* im = imag( v ); -* // returns 1.0 +* // returns [ 10.0, 1.0 ] * * // Round components to the nearest thousand: -* z = new Complex128( 12368.0, -12368.0 ) +* z = new Complex128( 12368.0, -12368.0 ); * v = cceiln( z, 3 ); -* // returns -* -* re = real( v ); -* // returns 13000.0 -* -* im = imag( v ); -* // returns -12000.0 +* // returns [ 13000.0, -12000.0 ] * * v = cceiln( new Complex128( NaN, NaN ), 2 ); -* // returns -* -* re = real( v ); -* // returns NaN -* -* im = imag( v ); -* // returns NaN +* // returns [ NaN, NaN ] */ // MODULES // diff --git a/lib/node_modules/@stdlib/math/base/special/cceiln/lib/main.js b/lib/node_modules/@stdlib/math/base/special/cceiln/lib/main.js index 4107ec43d2d9..e63c2ec25904 100644 --- a/lib/node_modules/@stdlib/math/base/special/cceiln/lib/main.js +++ b/lib/node_modules/@stdlib/math/base/special/cceiln/lib/main.js @@ -37,50 +37,24 @@ var imag = require( '@stdlib/complex/float64/imag' ); * * @example * var Complex128 = require( '@stdlib/complex/float64/ctor' ); -* var real = require( '@stdlib/complex/float64/real' ); -* var imag = require( '@stdlib/complex/float64/imag' ); * * // Round components to 2 decimal places: -* var z = new Complex128( -3.141592653589793, 3.141592653589793 ) +* var z = new Complex128( -3.141592653589793, 3.141592653589793 ); * var v = cceiln( z, -2 ); -* // returns -* -* var re = real( v ); -* // returns -3.14 -* -* var im = imag( v ); -* // returns 3.15 +* // returns [ -3.14, 3.15 ] * * // If n = 0, `cceiln` behaves like `cceil`: -* z = new Complex128( 9.99999, 0.1 ) +* z = new Complex128( 9.99999, 0.1 ); * v = cceiln( z, 0 ); -* // returns -* -* re = real( v ); -* // returns 10.0 -* -* im = imag( v ); -* // returns 1.0 +* // returns [ 10.0, 1.0 ] * * // Round components to the nearest thousand: -* z = new Complex128( 12368.0, -12368.0 ) +* z = new Complex128( 12368.0, -12368.0 ); * v = cceiln( z, 3 ); -* // returns -* -* re = real( v ); -* // returns 13000.0 -* -* im = imag( v ); -* // returns -12000.0 +* // returns [ 13000.0, -12000.0 ] * * v = cceiln( new Complex128( NaN, NaN ), 2 ); -* // returns -* -* re = real( v ); -* // returns NaN -* -* im = imag( v ); -* // returns NaN +* // returns [ NaN, NaN ] */ function cceiln( z, n ) { return new Complex128( ceiln( real( z ), n ), ceiln( imag( z ), n ) ); diff --git a/lib/node_modules/@stdlib/math/base/special/cceiln/lib/native.js b/lib/node_modules/@stdlib/math/base/special/cceiln/lib/native.js index 847b54eae9a4..1e76a7369b98 100644 --- a/lib/node_modules/@stdlib/math/base/special/cceiln/lib/native.js +++ b/lib/node_modules/@stdlib/math/base/special/cceiln/lib/native.js @@ -36,50 +36,24 @@ var addon = require( './../src/addon.node' ); * * @example * var Complex128 = require( '@stdlib/complex/float64/ctor' ); -* var real = require( '@stdlib/complex/float64/real' ); -* var imag = require( '@stdlib/complex/float64/imag' ); * * // Round components to 2 decimal places: -* var z = new Complex128( -3.141592653589793, 3.141592653589793 ) +* var z = new Complex128( -3.141592653589793, 3.141592653589793 ); * var v = cceiln( z, -2 ); -* // returns -* -* var re = real( v ); -* // returns -3.14 -* -* var im = imag( v ); -* // returns 3.15 +* // returns [ -3.14, 3.15 ] * * // If n = 0, `cceiln` behaves like `cceil`: -* z = new Complex128( 9.99999, 0.1 ) +* z = new Complex128( 9.99999, 0.1 ); * v = cceiln( z, 0 ); -* // returns -* -* re = real( v ); -* // returns 10.0 -* -* im = imag( v ); -* // returns 1.0 +* // returns [ 10.0, 1.0 ] * * // Round components to the nearest thousand: -* z = new Complex128( 12368.0, -12368.0 ) +* z = new Complex128( 12368.0, -12368.0 ); * v = cceiln( z, 3 ); -* // returns -* -* re = real( v ); -* // returns 13000.0 -* -* im = imag( v ); -* // returns -12000.0 +* // returns [ 13000.0, -12000.0 ] * * v = cceiln( new Complex128( NaN, NaN ), 2 ); -* // returns -* -* re = real( v ); -* // returns NaN -* -* im = imag( v ); -* // returns NaN +* // returns [ NaN, NaN ] */ function cceiln( z, n ) { var v = addon( z, n ); diff --git a/lib/node_modules/@stdlib/math/base/special/ceiln/README.md b/lib/node_modules/@stdlib/math/base/special/ceiln/README.md index 1e92fe9ad0f4..2f5a5a0cdce9 100644 --- a/lib/node_modules/@stdlib/math/base/special/ceiln/README.md +++ b/lib/node_modules/@stdlib/math/base/special/ceiln/README.md @@ -134,11 +134,11 @@ double y = stdlib_base_ceiln( 3.141592653589793, -2 ); // returns 3.15 // If n = 0, `ceiln` behaves like `ceil`: -double y = stdlib_base_ceiln( 3.141592653589793, 0 ); +y = stdlib_base_ceiln( 3.141592653589793, 0 ); // returns 4.0 // Round a value to the nearest thousand: -double y = stdlib_base_ceiln( 12368.0, 3 ); +y = stdlib_base_ceiln( 12368.0, 3 ); // returns 13000.0 ``` diff --git a/lib/node_modules/@stdlib/math/base/special/cflipsign/README.md b/lib/node_modules/@stdlib/math/base/special/cflipsign/README.md index 65fe10322c4f..8fd0610d4ddb 100644 --- a/lib/node_modules/@stdlib/math/base/special/cflipsign/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cflipsign/README.md @@ -193,6 +193,7 @@ int main( void ) { stdlib_complex128_reim( v, &re1, &im1 ); stdlib_complex128_reim( y, &re2, &im2 ); printf( "cflipsign(%lf + %lfi, %lf) = %lf + %lfi\n", re1, im1, -1.0, re2, im2 ); + }; } ``` diff --git a/lib/node_modules/@stdlib/math/base/special/copysignf/README.md b/lib/node_modules/@stdlib/math/base/special/copysignf/README.md index e623fd31548f..df90de263420 100644 --- a/lib/node_modules/@stdlib/math/base/special/copysignf/README.md +++ b/lib/node_modules/@stdlib/math/base/special/copysignf/README.md @@ -124,7 +124,7 @@ Returns a [single-precision floating-point number][ieee754] with the magnitude o float v = stdlib_base_copysignf( -3.0f, 10.0f ); // returns 3.0f -float v = stdlib_base_copysignf( 3.0f, -1.0f ); +v = stdlib_base_copysignf( 3.0f, -1.0f ); // returns -3.0f ``` diff --git a/lib/node_modules/@stdlib/math/base/special/cosh/test/test.js b/lib/node_modules/@stdlib/math/base/special/cosh/test/test.js index 5c4ea7d5ab3b..308daea12051 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosh/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/cosh/test/test.js @@ -24,8 +24,7 @@ var tape = require( 'tape' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var NINF = require( '@stdlib/constants/float64/ninf' ); -var EPS = require( '@stdlib/constants/float64/eps' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var cosh = require( './../lib' ); @@ -46,8 +45,6 @@ tape( 'main export is a function', function test( t ) { tape( 'the function computes the hyperbolic cosine', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -57,21 +54,13 @@ tape( 'the function computes the hyperbolic cosine', function test( t ) { for ( i = 0; i < x.length; i++ ) { y = cosh( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. Value: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the hyperbolic cosine (tiny values)', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -81,21 +70,13 @@ tape( 'the function computes the hyperbolic cosine (tiny values)', function test for ( i = 0; i < x.length; i++ ) { y = cosh( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. Value: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the hyperbolic cosine (large values)', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -105,13 +86,7 @@ tape( 'the function computes the hyperbolic cosine (large values)', function tes for ( i = 0; i < x.length; i++ ) { y = cosh( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. Value: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/special/cosh/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/cosh/test/test.native.js index 8debda0decde..c84d74dfc19c 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosh/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/special/cosh/test/test.native.js @@ -25,8 +25,7 @@ var tape = require( 'tape' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var NINF = require( '@stdlib/constants/float64/ninf' ); -var EPS = require( '@stdlib/constants/float64/eps' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -55,8 +54,6 @@ tape( 'main export is a function', opts, function test( t ) { tape( 'the function computes the hyperbolic cosine', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -66,21 +63,13 @@ tape( 'the function computes the hyperbolic cosine', opts, function test( t ) { for ( i = 0; i < x.length; i++ ) { y = cosh( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. Value: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the hyperbolic cosine (tiny values)', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -90,21 +79,13 @@ tape( 'the function computes the hyperbolic cosine (tiny values)', opts, functio for ( i = 0; i < x.length; i++ ) { y = cosh( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. Value: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the hyperbolic cosine (large values)', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -114,13 +95,7 @@ tape( 'the function computes the hyperbolic cosine (large values)', opts, functi for ( i = 0; i < x.length; i++ ) { y = cosh( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. Value: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/special/coshf/README.md b/lib/node_modules/@stdlib/math/base/special/coshf/README.md index cccd1d073fb3..4baccf71b573 100644 --- a/lib/node_modules/@stdlib/math/base/special/coshf/README.md +++ b/lib/node_modules/@stdlib/math/base/special/coshf/README.md @@ -170,14 +170,6 @@ int main( void ) {
-* * * - -## See Also - -- [`@stdlib/math/base/special/cosh`][@stdlib/math/base/special/cosh]: compute the hyperbolic cosine of a double-precision floating-point number. -- [`@stdlib/math/base/special/sinf`][@stdlib/math/base/special/sinf]: compute the sine of a single-precision floating-point number. -- [`@stdlib/math/base/special/tanf`][@stdlib/math/base/special/tanf]: compute the tangent of a single-precision floating-point number. -
@@ -190,12 +182,6 @@ int main( void ) { -[@stdlib/math/base/special/cosh]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/cosh - -[@stdlib/math/base/special/sinf]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/sinf - -[@stdlib/math/base/special/tanf]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/tanf - diff --git a/lib/node_modules/@stdlib/math/base/special/cphase/README.md b/lib/node_modules/@stdlib/math/base/special/cphase/README.md index c5f4989c9645..ee2eda578420 100644 --- a/lib/node_modules/@stdlib/math/base/special/cphase/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cphase/README.md @@ -158,17 +158,14 @@ int main( void ) { }; stdlib_complex128_t v; - stdlib_complex128_t y; - double re1; - double im1; - double re2; - double im2; + double re; + double im; + double y; int i; for ( i = 0; i < 4; i++ ) { v = x[ i ]; y = stdlib_base_cphase( v ); - stdlib_complex128_reim( v, &re1, &im1 ); - stdlib_complex128_reim( y, &re2, &im2 ); + stdlib_complex128_reim( v, &re, &im ); printf( "cphase(%lf + %lfi) = %lf\n", re, im, y ); } } diff --git a/lib/node_modules/@stdlib/math/base/special/erf/test/test.js b/lib/node_modules/@stdlib/math/base/special/erf/test/test.js index 74d5e05db90a..b9409bed0091 100644 --- a/lib/node_modules/@stdlib/math/base/special/erf/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/erf/test/test.js @@ -26,8 +26,7 @@ var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var NINF = require( '@stdlib/constants/float64/ninf' ); var PINF = require( '@stdlib/constants/float64/pinf' ); -var EPS = require( '@stdlib/constants/float64/eps' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var erf = require( './../lib' ); @@ -57,8 +56,6 @@ tape( 'main export is a function', function test( t ) { tape( 'the function evaluates the error function for `x` on the interval `[-5,-100]', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -67,21 +64,13 @@ tape( 'the function evaluates the error function for `x` on the interval `[-5,-1 x = veryLargeNegative.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the error function for `x` on the interval `[5,100]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -90,21 +79,13 @@ tape( 'the function evaluates the error function for `x` on the interval `[5,100 x = veryLargePositive.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the error function for `x` on the interval `[-2.5,-5]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -113,21 +94,13 @@ tape( 'the function evaluates the error function for `x` on the interval `[-2.5, x = largeNegative.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the error function for `x` on the interval `[2.5,5]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -136,21 +109,13 @@ tape( 'the function evaluates the error function for `x` on the interval `[2.5,5 x = largePositive.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the error function for `x` on the interval `[-1,-3]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -159,21 +124,13 @@ tape( 'the function evaluates the error function for `x` on the interval `[-1,-3 x = mediumNegative.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the error function for `x` on the interval `[1,3]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -182,13 +139,7 @@ tape( 'the function evaluates the error function for `x` on the interval `[1,3]` x = mediumPositive.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/special/erf/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/erf/test/test.native.js index 117b82caafc1..399e180d2cc9 100644 --- a/lib/node_modules/@stdlib/math/base/special/erf/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/special/erf/test/test.native.js @@ -27,9 +27,8 @@ var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var NINF = require( '@stdlib/constants/float64/ninf' ); var PINF = require( '@stdlib/constants/float64/pinf' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var tryRequire = require( '@stdlib/utils/try-require' ); -var EPS = require( '@stdlib/constants/float64/eps' ); -var abs = require( '@stdlib/math/base/special/abs' ); // FIXTURES // @@ -66,8 +65,6 @@ tape( 'main export is a function', opts, function test( t ) { tape( 'the function evaluates the error function for `x` on the interval `[-5,-100]', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -76,21 +73,13 @@ tape( 'the function evaluates the error function for `x` on the interval `[-5,-1 x = veryLargeNegative.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the error function for `x` on the interval `[5,100]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -99,21 +88,13 @@ tape( 'the function evaluates the error function for `x` on the interval `[5,100 x = veryLargePositive.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the error function for `x` on the interval `[-2.5,-5]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -122,21 +103,13 @@ tape( 'the function evaluates the error function for `x` on the interval `[-2.5, x = largeNegative.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the error function for `x` on the interval `[2.5,5]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -145,21 +118,13 @@ tape( 'the function evaluates the error function for `x` on the interval `[2.5,5 x = largePositive.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the error function for `x` on the interval `[-1,-3]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -168,21 +133,13 @@ tape( 'the function evaluates the error function for `x` on the interval `[-1,-3 x = mediumNegative.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the error function for `x` on the interval `[1,3]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -191,21 +148,13 @@ tape( 'the function evaluates the error function for `x` on the interval `[1,3]` x = mediumPositive.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the error function for `x` on the interval `[-0.8,-1]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -214,21 +163,13 @@ tape( 'the function evaluates the error function for `x` on the interval `[-0.8, x = smallNegative.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the error function for `x` on the interval `[0.8,1]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -237,21 +178,13 @@ tape( 'the function evaluates the error function for `x` on the interval `[0.8,1 x = smallPositive.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the error function for `x` on the interval `[-0.8,0.8]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -260,21 +193,13 @@ tape( 'the function evaluates the error function for `x` on the interval `[-0.8, x = smaller.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the error function for `x` on the interval `[-1e-300,-1e-308]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -283,21 +208,13 @@ tape( 'the function evaluates the error function for `x` on the interval `[-1e-3 x = tinyNegative.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the error function for `x` on the interval `[1e-300,1e-308]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -306,21 +223,13 @@ tape( 'the function evaluates the error function for `x` on the interval `[1e-30 x = tinyPositive.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the error function for subnormal `x`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -329,13 +238,7 @@ tape( 'the function evaluates the error function for subnormal `x`', opts, funct x = subnormal.x; for ( i = 0; i < x.length; i++ ) { y = erf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/special/erfc/test/test.js b/lib/node_modules/@stdlib/math/base/special/erfc/test/test.js index ceb8d19b0c3a..d51338008876 100644 --- a/lib/node_modules/@stdlib/math/base/special/erfc/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/erfc/test/test.js @@ -24,8 +24,7 @@ var tape = require( 'tape' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var NINF = require( '@stdlib/constants/float64/ninf' ); var PINF = require( '@stdlib/constants/float64/pinf' ); -var EPS = require( '@stdlib/constants/float64/eps' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var erfc = require( './../lib' ); @@ -55,8 +54,6 @@ tape( 'main export is a function', function test( t ) { tape( 'the function evaluates the complementary error function for `x` on the interval `[-5,-100]', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -65,21 +62,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = largerNegative.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for `x` on the interval `[5,100]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -88,21 +77,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = largerPositive.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for `x` on the interval `[-2.5,-28]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -111,21 +92,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = largeNegative.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for `x` on the interval `[2.5,28]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -134,21 +107,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = largePositive.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for `x` on the interval `[-1,-3]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -157,21 +122,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = mediumNegative.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for `x` on the interval `[1,3]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -180,21 +137,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = mediumPositive.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for `x` on the interval `[-0.8,-1]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -203,13 +152,7 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = smallNegative.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/special/erfc/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/erfc/test/test.native.js index 549256b345b5..28d1fd039cde 100644 --- a/lib/node_modules/@stdlib/math/base/special/erfc/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/special/erfc/test/test.native.js @@ -26,8 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var NINF = require( '@stdlib/constants/float64/ninf' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var tryRequire = require( '@stdlib/utils/try-require' ); -var EPS = require( '@stdlib/constants/float64/eps' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); // FIXTURES // @@ -64,8 +63,6 @@ tape( 'main export is a function', opts, function test( t ) { tape( 'the function evaluates the complementary error function for `x` on the interval `[-5,-100]', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -74,21 +71,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = largerNegative.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = 2.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for `x` on the interval `[5,100]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -97,21 +86,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = largerPositive.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = 2.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for `x` on the interval `[-2.5,-28]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -120,21 +101,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = largeNegative.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = 2.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for `x` on the interval `[2.5,28]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -143,21 +116,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = largePositive.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = 2.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for `x` on the interval `[-1,-3]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -166,21 +131,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = mediumNegative.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = 2.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for `x` on the interval `[1,3]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -189,21 +146,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = mediumPositive.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = 2.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 2 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for `x` on the interval `[-0.8,-1]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -212,21 +161,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = smallNegative.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = 2.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for `x` on the interval `[0.8,1]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -235,21 +176,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = smallPositive.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = 2.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 2 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for `x` on the interval `[-0.8,0.8]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -258,21 +191,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = smaller.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = 2.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for `x` on the interval `[-1e-300,-1e-308]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -281,21 +206,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = tinyNegative.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = 1.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for `x` on the interval `[1e-300,1e-308]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -304,21 +221,13 @@ tape( 'the function evaluates the complementary error function for `x` on the in x = tinyPositive.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = 1.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the complementary error function for subnormal `x`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -327,13 +236,7 @@ tape( 'the function evaluates the complementary error function for subnormal `x` x = subnormal.x; for ( i = 0; i < x.length; i++ ) { y = erfc( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = 1.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/README.md b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/README.md index e95c8ed820a5..339ae8804cfe 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/README.md +++ b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/README.md @@ -161,7 +161,7 @@ for ( y = 0; y < 309; y++ ) { ### Usage ```c -#include "stdlib/math/base/special/fast/pow.h" +#include "stdlib/math/base/special/fast/pow_int.h" ``` #### stdlib_base_fast_pow( x, y ) @@ -204,7 +204,7 @@ double stdlib_base_fast_pow( const double x, const int32_t y ); ### Examples ```c -#include "stdlib/math/base/special/fast/pow.h" +#include "stdlib/math/base/special/fast/pow_int.h" #include #include #include diff --git a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/benchmark/c/native/benchmark.c index a8c03d15e0d9..cade20012701 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/benchmark/c/native/benchmark.c +++ b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/benchmark/c/native/benchmark.c @@ -16,7 +16,7 @@ * limitations under the License. */ -#include "stdlib/math/base/special/fast/pow.h" +#include "stdlib/math/base/special/fast/pow_int.h" #include #include #include diff --git a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/examples/c/example.c b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/examples/c/example.c index 99b8725c6ddd..67a6d7f4e2f9 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/examples/c/example.c +++ b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/examples/c/example.c @@ -16,7 +16,7 @@ * limitations under the License. */ -#include "stdlib/math/base/special/fast/pow.h" +#include "stdlib/math/base/special/fast/pow_int.h" #include #include diff --git a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/include/stdlib/math/base/special/fast/pow.h b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/include/stdlib/math/base/special/fast/pow_int.h similarity index 86% rename from lib/node_modules/@stdlib/math/base/special/fast/pow-int/include/stdlib/math/base/special/fast/pow.h rename to lib/node_modules/@stdlib/math/base/special/fast/pow-int/include/stdlib/math/base/special/fast/pow_int.h index 38fcf9dc8eaf..8fc8e2def639 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/include/stdlib/math/base/special/fast/pow.h +++ b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/include/stdlib/math/base/special/fast/pow_int.h @@ -16,8 +16,8 @@ * limitations under the License. */ -#ifndef STDLIB_MATH_BASE_SPECIAL_FAST_POW_H -#define STDLIB_MATH_BASE_SPECIAL_FAST_POW_H +#ifndef STDLIB_MATH_BASE_SPECIAL_FAST_POW_INT_H +#define STDLIB_MATH_BASE_SPECIAL_FAST_POW_INT_H #include @@ -37,4 +37,4 @@ double stdlib_base_fast_pow( const double x, const int32_t y ); } #endif -#endif // !STDLIB_MATH_BASE_SPECIAL_FAST_POW_H +#endif // !STDLIB_MATH_BASE_SPECIAL_FAST_POW_INT_H diff --git a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/src/addon.c b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/src/addon.c index 33b7bcc581f9..abec714831a2 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/src/addon.c +++ b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/src/addon.c @@ -16,7 +16,7 @@ * limitations under the License. */ -#include "stdlib/math/base/special/fast/pow.h" +#include "stdlib/math/base/special/fast/pow_int.h" #include "stdlib/math/base/napi/binary.h" STDLIB_MATH_BASE_NAPI_MODULE_DI_D( stdlib_base_fast_pow ) diff --git a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/src/main.c b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/src/main.c index 87d673f82789..b5ca5a2a4c3e 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/src/main.c @@ -16,7 +16,7 @@ * limitations under the License. */ -#include "stdlib/math/base/special/fast/pow.h" +#include "stdlib/math/base/special/fast/pow_int.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/constants/float64/pinf.h" diff --git a/lib/node_modules/@stdlib/math/base/special/flipsignf/README.md b/lib/node_modules/@stdlib/math/base/special/flipsignf/README.md index f50febe785fd..b02f15b47f81 100644 --- a/lib/node_modules/@stdlib/math/base/special/flipsignf/README.md +++ b/lib/node_modules/@stdlib/math/base/special/flipsignf/README.md @@ -127,7 +127,7 @@ Returns a [single-precision floating-point number][ieee754] with the magnitude o float v = stdlib_base_flipsignf( -3.0f, 10.0f ); // returns -3.0f -float v = stdlib_base_flipsignf( -3.0f, -1.0f ); +v = stdlib_base_flipsignf( -3.0f, -1.0f ); // returns 3.0f ``` diff --git a/lib/node_modules/@stdlib/math/base/special/fmod/README.md b/lib/node_modules/@stdlib/math/base/special/fmod/README.md index 5af3face8720..65dc6e4a5375 100644 --- a/lib/node_modules/@stdlib/math/base/special/fmod/README.md +++ b/lib/node_modules/@stdlib/math/base/special/fmod/README.md @@ -132,7 +132,7 @@ Evaluates the modulus function. ```c double out = stdlib_base_fmod( 8.9, 3.0 ); -// returns 2.9 +// returns ~2.9 out = stdlib_base_fmod( 4.0, 2.0 ); // returns 0.0 diff --git a/lib/node_modules/@stdlib/math/base/special/hyp2f1/lib/hyp2f1negcequalbc.js b/lib/node_modules/@stdlib/math/base/special/hyp2f1/lib/hyp2f1negcequalbc.js new file mode 100644 index 000000000000..0e1461365d77 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/hyp2f1/lib/hyp2f1negcequalbc.js @@ -0,0 +1,78 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +* +* +* ## Notice +* +* The original C code and copyright notice are from the [Cephes Mathematical Library]{@link https://www.netlib.org/cephes/}. The implementation has been modified for JavaScript. +* +* ```text +* (C) Copyright Stephen L. Moshier 1984, 1987, 1992, 2000. +* +* Use, modification and distribution are subject to the +* Cephes Mathematical Library License. (See accompanying file +* LICENSE or copy at https://smath.com/en-US/view/CephesMathLibrary/license) +* ``` +*/ + +'use strict'; + +// MODULES // + +var abs = require( '@stdlib/math/base/special/abs' ); +var max = require( '@stdlib/math/base/special/max' ); + + +// MAIN // + +/** +* Evaluates 2F1(a, b; b; x) when `b = c` is a negative integer using AMS55 #15.4.2. +* +* @private +* @param {number} a - first parameter +* @param {number} b - second parameter (equals c, a non-positive integer) +* @param {number} x - argument +* @returns {number} function value, or NaN if precision is insufficient +*/ +function hyp2f1NegCEqualBC( a, b, x ) { + var collectorMax; + var collector; + var sum; + var k; + + collectorMax = 1.0; + collector = 1.0; + sum = 1.0; + + if ( abs( b ) >= 1.0e5 ) { + return NaN; + } + for ( k = 1; k <= -b; k++ ) { + collector *= ( ( a + k - 1.0 ) * x ) / k; + collectorMax = max( abs( collector ), collectorMax ); + sum += collector; + } + if ( 1.0e-16 * ( 1.0 + ( collectorMax / abs( sum ) ) ) > 1.0e-7 ) { + return NaN; + } + return sum; +} + + +// EXPORTS // + +module.exports = hyp2f1NegCEqualBC; diff --git a/lib/node_modules/@stdlib/math/base/special/hyp2f1/lib/hyt2f1.js b/lib/node_modules/@stdlib/math/base/special/hyp2f1/lib/hyt2f1.js index 99ebf12a4314..046a505c05c5 100644 --- a/lib/node_modules/@stdlib/math/base/special/hyp2f1/lib/hyt2f1.js +++ b/lib/node_modules/@stdlib/math/base/special/hyp2f1/lib/hyt2f1.js @@ -122,7 +122,7 @@ function hyt2f1( a, b, c, x, loss ) { d = c - a - b; id = round( d ); - if ( x > 0.9 && !negIntA && !negIntB ) { + if ( x > 0.85 && !negIntA && !negIntB ) { if ( isInteger( d ) === false ) { // Try the power series first: y = hys2f1( a, b, c, x, err ); @@ -223,7 +223,11 @@ function hyt2f1( a, b, c, x, loss ) { y = -y; } q = pow( s, id ); - y = ( id > 0.0 ) ? y*q : y1*q; + if ( id > 0.0 ) { + y *= q; + } else { + y1 *= q; + } y += y1; } return { diff --git a/lib/node_modules/@stdlib/math/base/special/hyp2f1/lib/main.js b/lib/node_modules/@stdlib/math/base/special/hyp2f1/lib/main.js index 031ea18c7eeb..53fd4ef8fce6 100644 --- a/lib/node_modules/@stdlib/math/base/special/hyp2f1/lib/main.js +++ b/lib/node_modules/@stdlib/math/base/special/hyp2f1/lib/main.js @@ -40,6 +40,7 @@ var gamma = require( '@stdlib/math/base/special/gamma' ); var pow = require( '@stdlib/math/base/special/pow' ); var abs = require( '@stdlib/math/base/special/abs' ); var isNonPositiveInteger = require( './isnonpositiveinteger.js' ); +var hyp2f1NegCEqualBC = require( './hyp2f1negcequalbc.js' ); var isInteger = require( './isinteger.js' ); var hys2f1 = require( './hys2f1.js' ); var hyt2f1 = require( './hyt2f1.js' ); @@ -156,6 +157,10 @@ function hyp2f1( a, b, c, x ) { if ( ax < 1.0 || x === -1.0 ) { if ( b === c ) { // 2F1(a,b;b;x) = (1-x)**(-a): + if ( negIntB ) { + // For negative integer b=c use the finite polynomial (AMS55 #15.4.2): + return hyp2f1NegCEqualBC( a, b, x ); + } return pow( s, -a ); } if ( a === c ) { diff --git a/lib/node_modules/@stdlib/math/base/special/hyp2f1/manifest.json b/lib/node_modules/@stdlib/math/base/special/hyp2f1/manifest.json index 4d4c5368bcb6..a1de94f40482 100644 --- a/lib/node_modules/@stdlib/math/base/special/hyp2f1/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/hyp2f1/manifest.json @@ -47,6 +47,7 @@ "@stdlib/math/base/special/ln", "@stdlib/math/base/special/abs", "@stdlib/math/base/special/pow", + "@stdlib/math/base/special/max", "@stdlib/constants/float64/pinf", "@stdlib/constants/float64/nan" ] @@ -72,6 +73,7 @@ "@stdlib/math/base/special/ln", "@stdlib/math/base/special/abs", "@stdlib/math/base/special/pow", + "@stdlib/math/base/special/max", "@stdlib/constants/float64/pinf", "@stdlib/constants/float64/nan" ] @@ -97,6 +99,7 @@ "@stdlib/math/base/special/ln", "@stdlib/math/base/special/abs", "@stdlib/math/base/special/pow", + "@stdlib/math/base/special/max", "@stdlib/constants/float64/pinf", "@stdlib/constants/float64/nan" ] diff --git a/lib/node_modules/@stdlib/math/base/special/hyp2f1/src/main.c b/lib/node_modules/@stdlib/math/base/special/hyp2f1/src/main.c index d46cf833b0b2..f5c0a36aa457 100644 --- a/lib/node_modules/@stdlib/math/base/special/hyp2f1/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/hyp2f1/src/main.c @@ -39,6 +39,7 @@ #include "stdlib/math/base/special/ln.h" #include "stdlib/math/base/special/abs.h" #include "stdlib/math/base/special/pow.h" +#include "stdlib/math/base/special/max.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/nan.h" @@ -235,6 +236,38 @@ static double hys2f1( double a, double b, const double c, const double x, double return s; } +/** +* Evaluates 2F1(a, b; b; x) when `b = c` is a negative integer using AMS55 #15.4.2. +* +* @param a first parameter +* @param b second parameter (equals c, a non-positive integer) +* @param x argument +* @return function value, or NaN if precision is insufficient +*/ +static double hyp2f1NegCEqualBC( const double a, const double b, const double x ) { + double collectorMax; + double collector; + double sum; + double k; + + collectorMax = 1.0; + collector = 1.0; + sum = 1.0; + + if ( stdlib_base_abs( b ) >= 1.0e5 ) { + return STDLIB_CONSTANT_FLOAT64_NAN; + } + for ( k = 1.0; k <= -b; k ++ ) { + collector *= ( ( a + k - 1.0 ) * x ) / k; + collectorMax = stdlib_base_max( stdlib_base_abs( collector ), collectorMax ); + sum += collector; + } + if ( 1.0e-16 * ( 1.0 + ( collectorMax / stdlib_base_abs( sum ) ) ) > 1.0e-7 ) { + return STDLIB_CONSTANT_FLOAT64_NAN; + } + return sum; +} + /** * Applies transformations for `|x|` near unity before performing a power series expansion. * @@ -289,7 +322,7 @@ static double hyt2f1( const double a, const double b, const double c, const doub d = c - a - b; id = stdlib_base_round( d ); - if ( x > 0.9 && !negIntA && !negIntB ) { + if ( x > 0.85 && !negIntA && !negIntB ) { if ( isInteger( d ) == false ) { // Try the power series first: y = hys2f1( a, b, c, x, &err ); @@ -386,7 +419,11 @@ static double hyt2f1( const double a, const double b, const double c, const doub y = -y; } q = stdlib_base_pow( s, id ); - y = ( id > 0.0 ) ? y*q : y1*q; + if ( id > 0.0 ) { + y *= q; + } else { + y1 *= q; + } y += y1; } *loss = err; @@ -477,6 +514,11 @@ double stdlib_base_hyp2f1( const double a, const double b, const double c, const if ( ax < 1.0 || x == -1.0 ) { if ( b == c ) { // 2F1(a,b;b;x) = (1-x)**(-a): + if ( negIntB ) { + // For negative integer b=c use the finite polynomial (AMS55 #15.4.2): + y = hyp2f1NegCEqualBC( a, b, x ); + return y; + } y = stdlib_base_pow( s, -a ); return y; } diff --git a/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/edge_cases3.json b/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/edge_cases3.json index 34e12556d3f4..2929044cee21 100644 --- a/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/edge_cases3.json +++ b/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/edge_cases3.json @@ -1 +1 @@ -{"a": [-10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -5.0, -5.0, -5.0, -5.0, -5.0, -5.0, -5.0, -5.0, -5.0, -5.0, -5.0, -5.0, -5.0, -5.0, -5.0, -5.0, -5.0, -5.0, -5.0, -5.0, 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2.6666666666666665, 3.638888888888889, 11.0, 2.01, 1.99, 1.0, 0.4, 0.050000000000000044, 3.450980392156863, 1.2475490196078431, 1.2426470588235294, 1.0, 0.8529411764705882, 0.767156862745098, "PINF", "PINF", "PINF", 1.0, "PINF", "PINF", -0.08353419265652244, -2.042869924669208, -2.059998995886413, 1.0, 136331.67665422524, 5463862709345.7, 0.09090909090909091, 0.49751243781094534, 0.5025125628140703, 1.0, 2.5, 19.999999999999982, 0.31231583302819604, 0.8060197315453479, 0.8090585278662749, 1.0, 1.1776650101634791, 1.3226775937922093, "PINF", "PINF", "PINF", 1.0, "PINF", "PINF", -5.533085592635573e-05, -0.7615458563603548, -0.7388296643783832, 1.0, 39641245305.197495, 2.117911949843939e+24, 1.9665008108956757e-08, 0.005706228717414593, 0.006144509705799984, 1.0, 880.5541417890707, 4242501142.19516, 0.22917900193296076, 0.2347605917566327, 1.0, 3.7843863065139836, 12.898210811714453, "PINF", "PINF", "PINF", 1.0, "PINF", "PINF", 290992.80931441917, 893.5998258984249, 849.0433138129996, 1.0, -6806.570819087061, -948295068489.6099, 1754.1405556797163, 14.794924482626321, 14.32305432076869, 1.0, -0.02566968302658441, -0.44809210276874006, 89.93509035264425, 2.760525497921027, 2.7147819531818547, 1.0, 0.42524820142966624, 0.2230907142267818, -10.11111111111111, -0.12222222222222223, -0.10000000000000009, 1.0, 1.6666666666666665, 2.0555555555555554, -54.55555555555556, -4.611111111111111, -4.5, 1.0, 4.333333333333333, 6.277777777777778, 21.0, 3.02, 2.98, 1.0, -0.19999999999999996, -0.8999999999999999, 5.901960784313726, 1.4950980392156863, 1.4852941176470589, 1.0, 0.7058823529411764, 0.5343137254901961, "PINF", "PINF", "PINF", 1.0, "PINF", "PINF", -0.032701791132583626, -0.8414687633381505, 1.0, 75483608.47155939, 9.913045025317654e+19, 0.04282460317505117, 0.3153687356940052, 0.31983075108029946, 1.0, 13.465401785714302, 623612.0634920576, 0.17570582913847588, 0.6724658257490882, 0.6768068551393724, 1.0, 1.4289255390787534, 1.949346748033327, "PINF", "PINF", "PINF", 1.0, "PINF", "PINF", -3.0900882477227245e-07, 0.39839696496151483, 1.0, 156750282756516.1, 4.6094714349206136e+32, -9.198518549246854e-13, -6.087721831718218e-05, -6.748843653318489e-05, 1.0, 245653.93278956393, 5.8971216794061176e+16, 0.0605128935123625, 0.06323387211421305, 1.0, 17.421794032432604]} diff --git a/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/edge_cases5.json b/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/edge_cases5.json new file mode 100644 index 000000000000..b2ea986a0fd1 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/edge_cases5.json @@ -0,0 +1 @@ +{"a": [1.5, 1.5, 2.5, 0.5, 1.5, 0.5, 2.0, 1.5, 2.5, 1.5], "b": [2.5, 2.5, 1.5, 2.5, 2.5, 1.5, 3.0, 3.5, 2.5, 3.5], "c": [3.0, 3.0, 3.0, 2.0, 2.0, 1.0, 4.0, 4.0, 4.0, 3.0], "x": [0.9, 0.95, 0.9, 0.92, 0.91, 0.9, 0.9, 0.88, 0.93, 0.91], "expected": [14.663397526525134, 30.949523656432504, 14.663397526525134, 6.507774205759818, 106.96827020610523, 7.033214388515233, 21.78942310292968, 13.41253423166626, 36.54504530314331, 88.86455455103395]} diff --git a/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/edge_cases6.json b/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/edge_cases6.json new file mode 100644 index 000000000000..18cf8736eded --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/edge_cases6.json @@ -0,0 +1 @@ +{"a": [2.0, 2.0, 3.0, 0.5, 1.5, 2.0, 4.0, 0.5], "b": [-1.0, -2.0, -2.0, -3.0, -3.0, -4.0, -2.0, -1.0], "c": [-1.0, -2.0, -2.0, -3.0, -3.0, -4.0, -2.0, -1.0], "x": [0.5, 0.5, 0.3, 0.7, -0.5, 0.6, 0.8, -0.9], "expected": [2.0, 2.75, 2.44, 1.6409375, 0.4453125, 4.792, 10.600000000000001, 0.55]} diff --git a/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/outliers.json b/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/outliers.json index f20b6e9ded7c..0498a419a23a 100644 --- a/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/outliers.json +++ b/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/outliers.json @@ -1 +1 @@ -{"a": [-1.8, 1.8, 1.8, 1.8, 1.8, 5.0, 10.0, 10.0, 2.0, 2.0, -1.8, 1.8, 10.0, 10.0, 0.5, -8.0, -0.1156544430516313, -27.911722328444608, -10.184355055477743, -5.0083982772911, -0.7429095709749414, -14.55029516886238, -5.428179853908536, -1.8190858888165087, -0.9534205693212994, -31.70680212982947, -0.18350917503602782, -200.19574300099214, -8.837706832399117, -3.2052905962805456, -13.37614633859299], "b": [7.4, -2.5, 1.0, 7.4, 7.4, 7.4, 7.4, 7.4, 3.0, 2.5, -2.5, 7.4, 1.0, 7.4, -269.5, 18.016500331508873, 12.722140489351698, 14.018736008860946, 6.5450429328481174, 171.09919289684245, 11.725525989335528, 0.46553367087834685, 26.782963689614604, 21.025202609254364, 10.024920055648606, 0.11445767340979862, 14.696533286274349, 1.9444493115386567, 0.19096384651567044, 0.3048596186043564, 1.337786902832312], "c": [20.4, 20.4, 20.4, -1.8, 20.4, 20.4, 20.4, 20.4, 5.0, -3.25, 20.4, -1.8, -1.8, -1.8, 1.5, 10.805295997850628, -0.6030985338257255, -1.0168630024136034, -0.44051751620383994, -1.4923865283013589, -7.299203351011158, -0.5349901418098844, -4.162402828198655, -0.6960141045675334, -0.23845367675425955, -0.5570625216964069, -6.338990250643928, -0.6933677849479691, -2.3808990396202425, -0.7039276707364683, -0.05015281580946018], "x": [-10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, 0.95, 0.99, 0.999, -10.0, -1.01, -0.99, -0.99, 0.998001, 0.90875647507, -0.0005448214561780684, 0.6228483452847298, 0.6555896492302491, 0.7073764056574465, 0.11534401417791407, 0.6086682776938632, 0.10047548647104909, 0.2570211738060222, 0.4419851803780206, 0.020574313007314604, -0.9003519736816863, 0.24492811068225362, -0.27624718180517105, 0.8496565195400692, -0.0022109253176725296], "expected": [16.334204105729413, 5.883122144128727, 0.5820646473844754, 0.010147094307759376, 0.07291374137469146, 0.0011628419587190388, 8.042653908304492e-06, 566.0092271657466, 27.699347904322664, 2.183739328012162e+26, -0.5786871007671348, 0.10921062752340924, -0.8752587026378827, 0.4234752106080307, 0.053963052503373715, -3.566216341436626e-09, 0.998681836639102, 5.33299803869569, 1.1177709865124041, 3.491332086988064e+82, 1.132062691110089, -0.0006927158077474787, 98.41698380414908, -221.57018712798285, 43.53554136829992, 1.0540592696289446, 0.5371016318543966, 0.0028040224553278668, -2.4067466563131665, 0.028751519134363426, 0.18419839456905535]} +{"a": [-1.8, 1.8, 1.8, 1.8, 1.8, 5.0, 10.0, 10.0, 2.0, 2.0, -1.8, 1.8, 10.0, 10.0, 0.5, -8.0, -0.1156544430516313, -27.911722328444608, -10.184355055477743, -5.0083982772911, -0.7429095709749414, -14.55029516886238, -5.428179853908536, -1.8190858888165087, -0.9534205693212994, -31.70680212982947, -0.18350917503602782, -200.19574300099214, -8.837706832399117, -3.2052905962805456, -13.37614633859299], "b": [7.4, -2.5, 1.0, 7.4, 7.4, 7.4, 7.4, 7.4, 3.0, 2.5, -2.5, 7.4, 1.0, 7.4, -269.5, 18.016500331508873, 12.722140489351698, 14.018736008860946, 6.5450429328481174, 171.09919289684245, 11.725525989335528, 0.46553367087834685, 26.782963689614604, 21.025202609254364, 10.024920055648606, 0.11445767340979862, 14.696533286274349, 1.9444493115386567, 0.19096384651567044, 0.3048596186043564, 1.337786902832312], "c": [20.4, 20.4, 20.4, -1.8, 20.4, 20.4, 20.4, 20.4, 5.0, -3.25, 20.4, -1.8, -1.8, -1.8, 1.5, 10.805295997850628, -0.6030985338257255, -1.0168630024136034, -0.44051751620383994, -1.4923865283013589, -7.299203351011158, -0.5349901418098844, -4.162402828198655, -0.6960141045675334, -0.23845367675425955, -0.5570625216964069, -6.338990250643928, -0.6933677849479691, -2.3808990396202425, -0.7039276707364683, -0.05015281580946018], "x": [-10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, 0.95, 0.99, 0.999, -10.0, -1.01, -0.99, -0.99, 0.998001, 0.90875647507, -0.0005448214561780684, 0.6228483452847298, 0.6555896492302491, 0.7073764056574465, 0.11534401417791407, 0.6086682776938632, 0.10047548647104909, 0.2570211738060222, 0.4419851803780206, 0.020574313007314604, -0.9003519736816863, 0.24492811068225362, -0.27624718180517105, 0.8496565195400692, -0.0022109253176725296], "expected": [16.334204105729413, 5.883122144128727, 0.5820646473844754, 0.010147094307759376, 0.07291374137469146, 0.0011628419587190388, 8.042653908304492e-06, 566.0092271658314, 27.699347904322664, 2.1837393280121743e+26, -0.5786871007671348, 0.10921062752340924, -0.8752587026378827, 0.4234752106080307, 0.053963052503373715, -3.566216341436626e-09, 0.998681836639102, 5.33299803869569, 1.1177709865124041, 3.491332086988064e+82, 1.132062691110089, -0.0006927158077474787, 98.41698380414908, -221.57018712798285, 43.53554136829992, 1.0540592696289446, 0.5371016318543966, 0.0028040224553278668, -2.4067466563131665, 0.028751519134363426, 0.18419839456905535]} diff --git a/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/runner.py b/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/runner.py index ffa3fd2da195..01a2472c0ef4 100644 --- a/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/runner.py +++ b/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/fixtures/python/runner.py @@ -256,6 +256,46 @@ def main(): # Outliers: gen_outliers("outliers.json") + # Edge Cases #5 + # d = c - a - b is a negative integer, x > 0.85, a and b are positive integers. + pts = [ + (1.5, 2.5, 3.0, 0.90), + (1.5, 2.5, 3.0, 0.95), + (2.5, 1.5, 3.0, 0.90), + (0.5, 2.5, 2.0, 0.92), + (1.5, 2.5, 2.0, 0.91), + (0.5, 1.5, 1.0, 0.90), + (2.0, 3.0, 4.0, 0.90), + (1.5, 3.5, 4.0, 0.88), + (2.5, 2.5, 4.0, 0.93), + (1.5, 3.5, 3.0, 0.91), + ] + a, b, c, x = zip(*pts) + a = np.array(a) + b = np.array(b) + c = np.array(c) + x = np.array(x) + gen(a, b, c, x, "edge_cases5.json") + + # Edge Cases #6 + # b = c is a negative integer: 2F1(a, b; b; x) -> finite polynomial sum. + pts = [ + (2.0, -1.0, -1.0, 0.5), + (2.0, -2.0, -2.0, 0.5), + (3.0, -2.0, -2.0, 0.3), + (0.5, -3.0, -3.0, 0.7), + (1.5, -3.0, -3.0, -0.5), + (2.0, -4.0, -4.0, 0.6), + (4.0, -2.0, -2.0, 0.8), + (0.5, -1.0, -1.0, -0.9), + ] + a, b, c, x = zip(*pts) + a = np.array(a) + b = np.array(b) + c = np.array(c) + x = np.array(x) + gen(a, b, c, x, "edge_cases6.json") + if __name__ == "__main__": main() diff --git a/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/test.js b/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/test.js index 9265dc8bcf7a..18bfc160b8b6 100644 --- a/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/test.js @@ -21,7 +21,7 @@ // MODULES // var tape = require( 'tape' ); -var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var hyp2f1 = require( './../lib' ); @@ -34,6 +34,8 @@ var edgeCases1 = require( './fixtures/python/edge_cases1.json' ); var edgeCases2 = require( './fixtures/python/edge_cases2.json' ); var edgeCases3 = require( './fixtures/python/edge_cases3.json' ); var edgeCases4 = require( './fixtures/python/edge_cases4.json' ); +var edgeCases5 = require( './fixtures/python/edge_cases5.json' ); +var edgeCases6 = require( './fixtures/python/edge_cases6.json' ); var outliers = require( './fixtures/python/outliers.json' ); @@ -64,16 +66,16 @@ tape( 'the function returns `NaN` if provided `NaN`', function test( t ) { var v; v = hyp2f1( NaN, 3.0, 2.0, 0.5 ); - t.strictEqual( isnanf( v ), true, 'returns expected value' ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); v = hyp2f1( 0.0, NaN, 2.0, 0.5 ); - t.strictEqual( isnanf( v ), true, 'returns expected value' ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); v = hyp2f1( 0.0, 3.0, NaN, 0.5 ); - t.strictEqual( isnanf( v ), true, 'returns expected value' ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); v = hyp2f1( 0.0, 3.0, 2.0, NaN ); - t.strictEqual( isnanf( v ), true, 'returns expected value' ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); }); @@ -238,6 +240,50 @@ tape( 'the function correctly evaluates the hypergeometric function', function t t.end(); }); +tape( 'the function correctly evaluates the hypergeometric function', function test( t ) { + var expected; + var a; + var b; + var c; + var x; + var v; + var i; + + a = edgeCases5.a; + b = edgeCases5.b; + c = edgeCases5.c; + x = edgeCases5.x; + expected = edgeCases5.expected; + + for ( i = 0; i < x.length; i++ ) { + v = hyp2f1( a[ i ], b[ i ], c[ i ], x[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 12 ), true, 'returns expected value.' ); + } + t.end(); +}); + +tape( 'the function correctly evaluates the hypergeometric function', function test( t ) { + var expected; + var a; + var b; + var c; + var x; + var v; + var i; + + a = edgeCases6.a; + b = edgeCases6.b; + c = edgeCases6.c; + x = edgeCases6.x; + expected = edgeCases6.expected; + + for ( i = 0; i < x.length; i++ ) { + v = hyp2f1( a[ i ], b[ i ], c[ i ], x[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value.' ); + } + t.end(); +}); + tape( 'the function correctly evaluates the hypergeometric function', function test( t ) { var expected; var a; diff --git a/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/test.native.js index eff8f30c8372..d486d0b75f3e 100644 --- a/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/special/hyp2f1/test/test.native.js @@ -22,7 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -43,6 +43,8 @@ var edgeCases1 = require( './fixtures/python/edge_cases1.json' ); var edgeCases2 = require( './fixtures/python/edge_cases2.json' ); var edgeCases3 = require( './fixtures/python/edge_cases3.json' ); var edgeCases4 = require( './fixtures/python/edge_cases4.json' ); +var edgeCases5 = require( './fixtures/python/edge_cases5.json' ); +var edgeCases6 = require( './fixtures/python/edge_cases6.json' ); var outliers = require( './fixtures/python/outliers.json' ); @@ -73,16 +75,16 @@ tape( 'the function returns `NaN` if provided `NaN`', opts, function test( t ) { var v; v = hyp2f1( NaN, 3.0, 2.0, 0.5 ); - t.strictEqual( isnanf( v ), true, 'returns expected value' ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); v = hyp2f1( 0.0, NaN, 2.0, 0.5 ); - t.strictEqual( isnanf( v ), true, 'returns expected value' ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); v = hyp2f1( 0.0, 3.0, NaN, 0.5 ); - t.strictEqual( isnanf( v ), true, 'returns expected value' ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); v = hyp2f1( 0.0, 3.0, 2.0, NaN ); - t.strictEqual( isnanf( v ), true, 'returns expected value' ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); }); @@ -167,7 +169,8 @@ tape( 'the function correctly evaluates the hypergeometric function', opts, func t.strictEqual( v, PINF, 'returns expected value' ); continue; } - t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + // NOTE: the tolerance here is larger than for the JavaScript implementation due to compiler optimizations which may be performed resulting in result divergence. For discussion, see https://github.com/stdlib-js/stdlib/pull/2298#discussion_r1624765205 + t.strictEqual( isAlmostSameValue( v, expected[ i ], 2 ), true, 'returns expected value' ); } t.end(); }); @@ -193,7 +196,8 @@ tape( 'the function correctly evaluates the hypergeometric function', opts, func t.strictEqual( v, PINF, 'returns expected value' ); continue; } - t.strictEqual( isAlmostSameValue( v, expected[ i ], 7 ), true, 'returns expected value' ); + // NOTE: the tolerance here is larger than for the JavaScript implementation due to compiler optimizations which may be performed resulting in result divergence. For discussion, see https://github.com/stdlib-js/stdlib/pull/2298#discussion_r1624765205 + t.strictEqual( isAlmostSameValue( v, expected[ i ], 27 ), true, 'returns expected value' ); } t.end(); }); @@ -219,7 +223,8 @@ tape( 'the function correctly evaluates the hypergeometric function', opts, func t.strictEqual( v, PINF, 'returns expected value' ); continue; } - t.strictEqual( isAlmostSameValue( v, expected[ i ], 18 ), true, 'returns expected value' ); + // NOTE: the tolerance here is larger than for the JavaScript implementation due to compiler optimizations which may be performed resulting in result divergence. For discussion, see https://github.com/stdlib-js/stdlib/pull/2298#discussion_r1624765205 + t.strictEqual( isAlmostSameValue( v, expected[ i ], 45 ), true, 'returns expected value' ); } t.end(); }); @@ -245,7 +250,52 @@ tape( 'the function correctly evaluates the hypergeometric function', opts, func t.strictEqual( v, PINF, 'returns expected value' ); continue; } - t.strictEqual( isAlmostSameValue( v, expected[ i ], 33 ), true, 'returns expected value' ); + // NOTE: the tolerance here is larger than for the JavaScript implementation due to compiler optimizations which may be performed resulting in result divergence. For discussion, see https://github.com/stdlib-js/stdlib/pull/2298#discussion_r1624765205 + t.strictEqual( isAlmostSameValue( v, expected[ i ], 100 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function correctly evaluates the hypergeometric function', function test( t ) { + var expected; + var a; + var b; + var c; + var x; + var v; + var i; + + a = edgeCases5.a; + b = edgeCases5.b; + c = edgeCases5.c; + x = edgeCases5.x; + expected = edgeCases5.expected; + + for ( i = 0; i < x.length; i++ ) { + v = hyp2f1( a[ i ], b[ i ], c[ i ], x[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 12 ), true, 'returns expected value.' ); + } + t.end(); +}); + +tape( 'the function correctly evaluates the hypergeometric function (edge case 6)', function test( t ) { + var expected; + var a; + var b; + var c; + var x; + var v; + var i; + + a = edgeCases6.a; + b = edgeCases6.b; + c = edgeCases6.c; + x = edgeCases6.x; + expected = edgeCases6.expected; + + for ( i = 0; i < x.length; i++ ) { + v = hyp2f1( a[ i ], b[ i ], c[ i ], x[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value.' ); } t.end(); }); @@ -267,7 +317,9 @@ tape( 'the function correctly evaluates the hypergeometric function', opts, func for ( i = 0; i < x.length; i++ ) { v = hyp2f1( a[ i ], b[ i ], c[ i ], x[ i ] ); - t.strictEqual( isAlmostSameValue( v, expected[ i ], 294333 ), true, 'returns expected value' ); + + // NOTE: the tolerance here is larger than for the JavaScript implementation due to compiler optimizations which may be performed resulting in result divergence. For discussion, see https://github.com/stdlib-js/stdlib/pull/2298#discussion_r1624765205 + t.strictEqual( isAlmostSameValue( v, expected[ i ], 391554 ), true, 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/special/negalucas/README.md b/lib/node_modules/@stdlib/math/base/special/negalucas/README.md index 863cdb801dc2..2e6bb0fb637e 100644 --- a/lib/node_modules/@stdlib/math/base/special/negalucas/README.md +++ b/lib/node_modules/@stdlib/math/base/special/negalucas/README.md @@ -192,7 +192,7 @@ Computes the nth [negaLucas number][lucas-number]. ```c double out = stdlib_base_negalucas( 0.0 ); -// returns 0.0 +// returns 2.0 out = stdlib_base_negalucas( -1.0 ); // returns -1.0 diff --git a/lib/node_modules/@stdlib/math/base/special/negalucasf/README.md b/lib/node_modules/@stdlib/math/base/special/negalucasf/README.md index c2e806115e4f..58f4d800e60c 100644 --- a/lib/node_modules/@stdlib/math/base/special/negalucasf/README.md +++ b/lib/node_modules/@stdlib/math/base/special/negalucasf/README.md @@ -192,7 +192,7 @@ Computes the nth [negaLucas number][lucas-number] in single-precision floating-p ```c float out = stdlib_base_negalucasf( 0.0f ); -// returns 0.0f +// returns 2.0f out = stdlib_base_negalucasf( -1.0f ); // returns -1.0f diff --git a/lib/node_modules/@stdlib/math/base/special/roundb/test/test.js b/lib/node_modules/@stdlib/math/base/special/roundb/test/test.js index ddb755865abd..56f7631234d4 100644 --- a/lib/node_modules/@stdlib/math/base/special/roundb/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/roundb/test/test.js @@ -162,7 +162,7 @@ tape( 'the function supports rounding a numeric value to a desired number of dec tape( 'due to floating-point rounding error, rounding a numeric value can result in unexpected behavior', function test( t ) { var x; - x = 0.2 + 0.1; // => 0.30000000000000004 + x = 0.2 + 0.1; // returns 0.30000000000000004 t.strictEqual( roundb( x, -16, 10 ), 0.3000000000000001, 'equals 0.3000000000000001 and not 0.3' ); x = 24.616838129811768; diff --git a/lib/node_modules/@stdlib/math/base/special/sec/README.md b/lib/node_modules/@stdlib/math/base/special/sec/README.md index 7c87b1aed98d..8c1b685664a2 100644 --- a/lib/node_modules/@stdlib/math/base/special/sec/README.md +++ b/lib/node_modules/@stdlib/math/base/special/sec/README.md @@ -119,8 +119,8 @@ Evaluates the [secant][trigonometric-functions] of `x` (in radians). double out = stdlib_base_sec( 0.0 ); // returns 1.0 -out = stdlib_base_cos( 3.141592653589793 / 2.0 ); -// returns 6.123233995736766e-17 +out = stdlib_base_sec( 3.141592653589793 / 2.0 ); +// returns 16331239353195370.0 ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/math/base/special/vercosf/README.md b/lib/node_modules/@stdlib/math/base/special/vercosf/README.md index 0faba21cb70e..33f3c917f452 100644 --- a/lib/node_modules/@stdlib/math/base/special/vercosf/README.md +++ b/lib/node_modules/@stdlib/math/base/special/vercosf/README.md @@ -124,7 +124,7 @@ float out = stdlib_base_vercosf( 0.0f ); // returns 2.0f out = stdlib_base_vercosf( 3.141592653589793f / 2.0f ); -// returns 1.0f +// returns ~1.0f ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/math/base/tools/README.md b/lib/node_modules/@stdlib/math/base/tools/README.md index 956569a9d178..064389dccaf4 100644 --- a/lib/node_modules/@stdlib/math/base/tools/README.md +++ b/lib/node_modules/@stdlib/math/base/tools/README.md @@ -43,6 +43,7 @@ var o = tools;
+- [`chebyshevSeries( x, c )`][@stdlib/math/base/tools/chebyshev-series]: evaluate a Chebyshev series using double-precision floating-point arithmetic. - [`continuedFraction( generator[, options ] )`][@stdlib/math/base/tools/continued-fraction]: continued fraction approximation. - [`evalpoly( c, x )`][@stdlib/math/base/tools/evalpoly]: evaluate a polynomial using double-precision floating-point arithmetic. - [`evalpolyf( c, x )`][@stdlib/math/base/tools/evalpolyf]: evaluate a polynomial using single-precision floating-point arithmetic. @@ -96,6 +97,8 @@ console.log( objectKeys( tools ) ); +[@stdlib/math/base/tools/chebyshev-series]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/tools/chebyshev-series + [@stdlib/math/base/tools/continued-fraction]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/tools/continued-fraction [@stdlib/math/base/tools/evalpoly]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/tools/evalpoly diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/LICENSE b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/LICENSE new file mode 100644 index 000000000000..3e825d2f4fbe --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/LICENSE @@ -0,0 +1,196 @@ + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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What you see here may be used freely but it +comes with no support or guarantee. + +Stephen L. Moshier +moshier@na-net.ornl.gov diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/README.md b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/README.md new file mode 100644 index 000000000000..7ea6e93a803a --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/README.md @@ -0,0 +1,148 @@ + + +# Chebyshev Series + +> Evaluate a [Chebyshev series][chebyshev-series] using double-precision floating-point arithmetic. + +
+ +A [Chebyshev series][chebyshev-series] in a variable `x` can be expressed as + + + +```math +\sum_{i=0}^{n} c_i T_i(x/2) +``` + + + + + +where `c_n, c_{n-1}, ..., c_0` are constants and `T_i` are Chebyshev polynomials of the first kind. + +
+ + + +
+ +## Usage + +```javascript +var chebyshevSeries = require( '@stdlib/math/base/tools/chebyshev-series' ); +``` + +#### chebyshevSeries( x, c ) + +Evaluates a [Chebyshev series][chebyshev-series] having coefficients `c` at a value `x`. + +```javascript +var v = chebyshevSeries( 1.0, [ 1.0, 0.5 ] ); +// returns 0.75 +``` + +The function evaluates Chebyshev polynomials at `x/2`. + +#### chebyshevSeries.factory( c ) + +Uses code generation to in-line coefficients and return a function for evaluating a [Chebyshev series][chebyshev-series] using double-precision floating-point arithmetic. + +```javascript +var evaluate = chebyshevSeries.factory( [ 1.0, 0.5 ] ); + +// 0.5 * T_0(0.5) + 1.0 * T_1(0.5) +var v = evaluate( 1.0 ); +// returns 0.75 +``` + +The returned function evaluates Chebyshev polynomials at `x/2`. + +
+ + + +
+ +## Notes + +- The value at which to evaluate a Chebyshev series is expected to reside on the interval `[-2, 2]`. +- The coefficients `c` **must be** be ordered in **descending** degree. +- For hot code paths in which coefficients are invariant, a compiled function will be more performant than `chebyshevSeries()`. +- While code generation can boost performance, its use may be problematic in browser contexts enforcing a strict [content security policy][mdn-csp] (CSP). If running in or targeting an environment with a CSP, avoid using code generation. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var chebyshevSeries = require( '@stdlib/math/base/tools/chebyshev-series' ); + +// Create an array of random coefficients: +var coef = discreteUniform( 10, -100, 100 ); + +// Evaluate the series at random values using the direct function: +var v = uniform( 100, -2.0, 2.0 ); +var i; +for ( i = 0; i < v.length; i++ ) { + console.log( 'f(%d) = %d', v[ i ], chebyshevSeries( v[ i ], coef ) ); +} + +// Generate a chebyshev series evaluation function: +var evaluate = chebyshevSeries.factory( coef ); +var x = uniform( 100, -2.0, 2.0 ); +logEachMap( 'f(%d) = %d', x, evaluate ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[chebyshev-series]: https://en.wikipedia.org/wiki/Chebyshev_polynomials#Chebyshev_series + +[mdn-csp]: https://developer.mozilla.org/en-US/docs/Web/HTTP/CSP + +
+ + diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/benchmark/benchmark.factory.js b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/benchmark/benchmark.factory.js new file mode 100644 index 000000000000..cce6d388e222 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/benchmark/benchmark.factory.js @@ -0,0 +1,80 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var factory = require( './../lib/factory.js' ); + + +// MAIN // + +bench( format( '%s::create:factory', pkg ), function benchmark( b ) { + var values; + var f; + var i; + + values = [ + uniform( 10, 0.0, 100.0 ), + uniform( 10, 0.0, 100.0 ), + uniform( 10, 0.0, 100.0 ) + ]; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = factory( values[ i%values.length ] ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::evaluate:factory', pkg ), function benchmark( b ) { + var values; + var v; + var f; + var i; + + f = factory( uniform( 10, 0.0, 100.0 ) ); + values = uniform( 10, -2.0, 2.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = f( values[ i%values.length ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/benchmark/benchmark.factory.length.js b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/benchmark/benchmark.factory.length.js new file mode 100644 index 000000000000..bae226224dc5 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/benchmark/benchmark.factory.length.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var factory = require( './../lib/factory.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var evaluate = factory( uniform( len, 0.0, 100.0 ) ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var x; + var v; + var i; + + x = uniform( 10, -2.0, 2.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = evaluate( x[ i%x.length ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:factory:len=%u', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/benchmark/benchmark.js new file mode 100644 index 000000000000..97a44242ee14 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/benchmark/benchmark.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var chebyshevSeries = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var coefs; + var x; + var v; + var i; + + coefs = [ + uniform( 10, 0.0, 100.0 ), + uniform( 10, 0.0, 100.0 ), + uniform( 10, 0.0, 100.0 ) + ]; + x = uniform( 10, -2.0, 2.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = chebyshevSeries( x[ i%x.length ], coefs[ i%coefs.length ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/benchmark/benchmark.length.js new file mode 100644 index 000000000000..a449fd487686 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/benchmark/benchmark.length.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var chebyshevSeries = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var c = uniform( len, 0.0, 100.0 ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var x; + var v; + var i; + + x = uniform( 10, -2.0, 2.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = chebyshevSeries( x[ i%x.length ], c ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%u', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/docs/repl.txt b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/docs/repl.txt new file mode 100644 index 000000000000..fcedfadde21d --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/docs/repl.txt @@ -0,0 +1,55 @@ + +{{alias}}( x, c ) + Evaluates a Chebyshev series using double-precision floating-point + arithmetic. + The implementation uses Clenshaw's recurrence algorithm and follows the + convention where the constant term is halved and polynomials are evaluated + at x/2. + + Parameters + ---------- + x: number + Value at which to evaluate the Chebyshev series (expected to be in + [-2, 2]). + + c: Array + Chebyshev series coefficients ordered in descending degree. + + Returns + ------- + out: number + Evaluated Chebyshev series. + + Examples + -------- + > var c = [ 1.0, 0.5 ]; + > var v = {{alias}}( 1.0, c ) + 0.75 + + +{{alias}}.factory( c ) + Returns a function for evaluating a Chebyshev series using double-precision + floating-point arithmetic. + The returned function uses Clenshaw's recurrence algorithm and follows the + convention where the constant term is halved and polynomials are evaluated + at x/2. + + Parameters + ---------- + c: Array + Chebyshev series coefficients ordered in descending degree. + + Returns + ------- + fcn: Function + Function for evaluating a Chebyshev series. + + Examples + -------- + > var f = {{alias}}.factory( [ 1.0, 0.5 ] ); + > var v = f( 1.0 ) + 0.75 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/docs/types/index.d.ts b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/docs/types/index.d.ts new file mode 100644 index 000000000000..2873e8324570 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/docs/types/index.d.ts @@ -0,0 +1,108 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection } from '@stdlib/types/array'; + +/** +* Evaluates a Chebyshev series using double-precision floating-point arithmetic. +* +* @param x - value at which to evaluate a Chebyshev series +* @returns evaluated Chebyshev series +*/ +type ChebyshevSeriesFunction = ( x: number ) => number; + +/** +* Interface for evaluating Chebyshev series. +*/ +interface ChebyshevSeries { + /** + * Evaluates a Chebyshev series using double-precision floating-point arithmetic. + * + * ## Notes + * + * - The implementation uses [Clenshaw's recurrence algorithm][clenshaw]. + * - The function evaluates Chebyshev polynomials at `x/2`. + * + * [clenshaw]: https://en.wikipedia.org/wiki/Clenshaw_algorithm + * + * @param x - value at which to evaluate the Chebyshev series (expected to be in `[-2, 2]`) + * @param c - Chebyshev series coefficients ordered in descending degree + * @returns evaluated Chebyshev series + * + * @example + * var v = chebyshevSeries( 1.0, [ 1.0, 0.5 ] ); // 1*T_0(1/2) + 0.5*T_1(1/2) + * // returns 0.75 + */ + ( x: number, c: Collection ): number; + + /** + * Generates a function for evaluating a Chebyshev series using double-precision floating-point arithmetic. + * + * ## Notes + * + * - The compiled function uses [Clenshaw's recurrence algorithm][clenshaw]. + * - The function evaluates Chebyshev polynomials at `x/2`. + * + * [clenshaw]: https://en.wikipedia.org/wiki/Clenshaw_algorithm + * + * @param c - Chebyshev series coefficients ordered in descending degree + * @returns function for evaluating a Chebyshev series + * + * @example + * var evaluate = chebyshevSeries.factory( [ 1.0, 0.5 ] ); + * + * var v = evaluate( 1.0 ); + * // returns 0.75 + */ + factory( c: Collection ): ChebyshevSeriesFunction; +} + +/** +* Evaluates a Chebyshev series using double-precision floating-point arithmetic. +* +* ## Notes +* +* - The implementation uses [Clenshaw's recurrence algorithm][clenshaw]. +* - The function evaluates Chebyshev polynomials at `x/2`. +* +* [clenshaw]: https://en.wikipedia.org/wiki/Clenshaw_algorithm +* +* @param x - value at which to evaluate the Chebyshev series (expected to be in `[-2, 2]`) +* @param c - Chebyshev series coefficients ordered in descending degree +* @returns evaluated Chebyshev series +* +* @example +* var v = chebyshevSeries( 1.0, [ 1.0, 0.5 ] ); // 1*T_0(1/2) + 0.5*T_1(1/2) +* // returns 0.75 +* +* @example +* var evaluate = chebyshevSeries.factory( [ 1.0, 0.5 ] ); // 1*T_0(1/2) + 0.5*T_1(1/2) +* +* var v = evaluate( 1.0 ); +* // returns 0.75 +*/ +declare var chebyshevSeries: ChebyshevSeries; + + +// EXPORTS // + +export = chebyshevSeries; diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/docs/types/test.ts b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/docs/types/test.ts new file mode 100644 index 000000000000..5e5ef91a5bbb --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/docs/types/test.ts @@ -0,0 +1,103 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import chebyshevSeries = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + chebyshevSeries( 1.0, [ 1.0, 0.5 ] ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + chebyshevSeries( '5', [ 1.0, 2.0 ] ); // $ExpectError + chebyshevSeries( true, [ 1.0, 2.0 ] ); // $ExpectError + chebyshevSeries( false, [ 1.0, 2.0 ] ); // $ExpectError + chebyshevSeries( null, [ 1.0, 2.0 ] ); // $ExpectError + chebyshevSeries( undefined, [ 1.0, 2.0 ] ); // $ExpectError + chebyshevSeries( [], [ 1.0, 2.0 ] ); // $ExpectError + chebyshevSeries( {}, [ 1.0, 2.0 ] ); // $ExpectError + chebyshevSeries( ( x: number ): number => x, [ 1.0, 2.0 ] ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a collection... +{ + chebyshevSeries( 1.0, '5' ); // $ExpectError + chebyshevSeries( 1.0, true ); // $ExpectError + chebyshevSeries( 1.0, false ); // $ExpectError + chebyshevSeries( 1.0, null ); // $ExpectError + chebyshevSeries( 1.0, undefined ); // $ExpectError + chebyshevSeries( 1.0, {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + chebyshevSeries(); // $ExpectError + chebyshevSeries( 1.0 ); // $ExpectError + chebyshevSeries( 1.0, [ 1.0, 2.0 ], 3.0 ); // $ExpectError +} + +// Attached to main export is a `factory` method which returns a function... +{ + chebyshevSeries.factory( [ 1.0, 0.5 ] ); // $ExpectType ChebyshevSeriesFunction +} + +// The function returned by the `factory` method returns a number... +{ + const evaluate = chebyshevSeries.factory( [ 1.0, 0.5 ] ); + evaluate( 1.0 ); // $ExpectType number +} + +// The compiler throws an error if the `factory` method is provided an argument which is not a collection... +{ + chebyshevSeries.factory( 5 ); // $ExpectError + chebyshevSeries.factory( true ); // $ExpectError + chebyshevSeries.factory( false ); // $ExpectError + chebyshevSeries.factory( null ); // $ExpectError + chebyshevSeries.factory( undefined ); // $ExpectError + chebyshevSeries.factory( {} ); // $ExpectError +} + +// The compiler throws an error if the `factory` method is provided an unsupported number of arguments... +{ + chebyshevSeries.factory(); // $ExpectError + chebyshevSeries.factory( [ 1.0, 2.0 ], 3.0 ); // $ExpectError +} + +// The compiler throws an error if the function returned by the `factory` method is provided an argument which is not a number... +{ + const evaluate = chebyshevSeries.factory( [ 1.0, 0.5 ] ); + evaluate( '5' ); // $ExpectError + evaluate( true ); // $ExpectError + evaluate( false ); // $ExpectError + evaluate( null ); // $ExpectError + evaluate( undefined ); // $ExpectError + evaluate( [] ); // $ExpectError + evaluate( {} ); // $ExpectError + evaluate( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function returned by the `factory` method is provided an unsupported number of arguments... +{ + const evaluate = chebyshevSeries.factory( [ 1.0, 0.5 ] ); + evaluate(); // $ExpectError + evaluate( 1.0, 2.0 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/examples/index.js b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/examples/index.js new file mode 100644 index 000000000000..519b3d69cfa1 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/examples/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var chebyshevSeries = require( './../lib' ); + +// Create an array of random coefficients: +var coef = discreteUniform( 10, -100, 100 ); + +// Evaluate the series at random values using the direct function: +var v = uniform( 100, -2.0, 2.0 ); +var i; +console.log( 'Direct evaluation:' ); +for ( i = 0; i < v.length; i++ ) { + console.log( 'f(%d) = %d', v[ i ], chebyshevSeries( v[ i ], coef ) ); +} + +// Generate a chebyshev series evaluation function: +var evaluate = chebyshevSeries.factory( coef ); +var x = uniform( 100, -2.0, 2.0 ); +logEachMap( 'f(%d) = %d', x, evaluate ); diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/lib/factory.js b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/lib/factory.js new file mode 100644 index 000000000000..9227855150e5 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/lib/factory.js @@ -0,0 +1,115 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var Fcn = require( '@stdlib/function/ctor' ); +var chebyshevSeries = require( './main.js' ); + + +// MAIN // + +/** +* Generates a function for evaluating a Chebyshev series. +* +* ## Notes +* +* - The compiled function uses [Clenshaw's algorithm][clenshaw-algorithm] for efficient computation. +* +* [clenshaw-algorithm]: https://en.wikipedia.org/wiki/Clenshaw_algorithm +* +* @param {NumericArray} c - Chebyshev series coefficients in descending degree order +* @returns {Function} function for evaluating a Chebyshev series +* +* @example +* var polyval = factory( [ 1.0, 0.5 ] ); +* +* var v = polyval( 1.0 ); // 1*T_0(1/2) + 0.5*T_1(1/2) +* // returns 0.75 +* +* var v = polyval( 0.0 ); // 1*T_0(0) + 0.5*T_1(0) +* // returns 0.5 +*/ +function factory( c ) { + var f; + var n; + var i; + + // Use the general implementation if the number of coefficients is large: + if ( c.length > 500 ) { + return evaluate; + } + + n = c.length; + + // Code generation. Start with the function definition... + f = 'return function chebyshevSeries(x){'; + f += 'var b0;'; + f += 'var b1;'; + f += 'var b2;'; + + // If no coefficients, the function always returns zero... + if ( n === 0 ) { + f += 'return 0.0;'; + } + // If only one coefficient, the function always returns that coefficient... + else if ( n === 1 ) { + f += 'return ' + ( 0.5 * c[ 0 ] ) + ';'; + } + // If more than one coefficient, apply Clenshaw's algorithm... + else { + // Initialize: + f += 'b0 = ' + c[ 0 ] + ';'; + f += 'b1 = 0.0;'; + + // Recurrence: + for ( i = 1; i < n; i++ ) { + f += 'b2 = b1;'; + f += 'b1 = b0;'; + f += 'b0 = (x*b1) - b2 + ' + c[ i ] + ';'; + } + f += 'return 0.5 * (b0 - b2);'; + } + + // Close the function: + f += '};'; + + // Add a source directive for debugging: + f += '//# sourceURL=chebyshevSeries.factory.js'; + + // Create the function in the global scope: + return ( new Fcn( f ) )(); + + /** + * Evaluates a Chebyshev series. + * + * @private + * @param {number} x - evaluation point + * @returns {number} evaluated series + */ + function evaluate( x ) { + return chebyshevSeries( x, c ); + } +} + + +// EXPORTS // + +module.exports = factory; diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/lib/index.js b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/lib/index.js new file mode 100644 index 000000000000..8e6fc7889931 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/lib/index.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Evaluate a Chebyshev series using double-precision floating-point arithmetic. +* +* @module @stdlib/math/base/tools/chebyshev-series +* +* @example +* var chebyshevSeries = require( '@stdlib/math/base/tools/chebyshev-series' ); +* +* var v = chebyshevSeries( 1.0, [ 1.0, 0.5 ] ); // 1*T_0(1/2) + 0.5*T_1(1/2) +* // returns 0.75 +* +* @example +* var chebyshevSeries = require( '@stdlib/math/base/tools/chebyshev-series' ); +* +* var polyval = chebyshevSeries.factory( [ 1.0, 0.5 ] ); +* +* var v = polyval( 1.0 ); // 1*T_0(1/2) + 0.5*T_1(1/2) +* // returns 0.75 +* +* var v = polyval( 0.0 ); // 1*T_0(0) + 0.5*T_1(0) +* // returns 0.5 +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var factory = require( './factory.js' ); + + +// MAIN // + +setReadOnly( main, 'factory', factory ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/lib/main.js b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/lib/main.js new file mode 100644 index 000000000000..f83389e4bfe9 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/lib/main.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +* +* +* ## Notice +* +* The original C code, long comment, copyright, and license are from [Cephes]{@link http://www.netlib.org/cephes}. The implementation follows the original, but has been modified for JavaScript. +* +* ```text +* Copyright 1984, 1995, 2000 by Stephen L. Moshier +* +* Some software in this archive may be from the book _Methods and Programs for Mathematical Functions_ (Prentice-Hall or Simon & Schuster International, 1989) or from the Cephes Mathematical Library, a commercial product. In either event, it is copyrighted by the author. What you see here may be used freely but it comes with no support or guarantee. +* +* Stephen L. Moshier +* moshier@na-net.ornl.gov +* ``` +*/ + +'use strict'; + +// MAIN // + +/** +* Evaluates a Chebyshev series. +* +* ## Notes +* +* The function evaluates +* +* ```text +* N-1 +* - ' +* y = > c[i] T (x/2) +* - i +* i=0 +* ``` +* +* of Chebyshev polynomials `Ti` at argument `x/2`. +* +* A few comments: +* +* - Coefficients must be stored in reverse order (i.e., the zero order term is last in the array). Note `N` is the number of coefficients, not the order. +* - If coefficients are for the interval `a` to `b`, `x` must have been transformed to `x` -> `2(2x - b - a)/(b-a)` before entering the routine. This maps `x` from `(a, b)` to `(-1, 1)`, over which the Chebyshev polynomials are defined. +* - If the coefficients are for the inverted interval, in which `(a, b)` is mapped to `(1/b, 1/a)`, the transformation required is `x` -> `2(2ab/x - b - a)/(b-a)`. If `b` is infinity, this becomes `x` -> `4a/x - 1`. +* +* ### Performance +* +* - Taking advantage of the recurrence properties of the Chebyshev polynomials, the routine requires one more addition per loop than evaluating a nested polynomial of the same degree. +* +* @param {number} x - evaluation point +* @param {NumericArray} c - series coefficients in descending degree order +* @returns {number} evaluated series +* +* @example +* var v = chebyshevSeries( 1.0, [ 1.0, 0.5 ] ); +* // returns 0.75 +* +* @example +* var v = chebyshevSeries( 0.0, [ 1.0, 0.5, 0.25 ] ); +* // returns -0.875 +* +* @example +* var v = chebyshevSeries( 0.0, [] ); +* // returns 0.0 +*/ +function chebyshevSeries( x, c ) { + var b0; + var b1; + var b2; + var n; + var i; + + n = c.length; + if ( n === 0 ) { + return 0.0; + } + if ( n === 1 ) { + return 0.5 * c[ 0 ]; + } + b0 = c[ 0 ]; + b1 = 0.0; + for ( i = 1; i < n; i++ ) { + b2 = b1; + b1 = b0; + b0 = ( x * b1 ) - b2 + c[ i ]; + } + return 0.5 * ( b0 - b2 ); +} + + +// EXPORTS // + +module.exports = chebyshevSeries; diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/package.json b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/package.json new file mode 100644 index 000000000000..70ee1c809cc3 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/package.json @@ -0,0 +1,66 @@ +{ + "name": "@stdlib/math/base/tools/chebyshev-series", + "version": "0.0.0", + "description": "Evaluate a Chebyshev series.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "math", + "mathematics", + "chebyshev", + "series", + "polynomial", + "eval", + "evaluate", + "approximation", + "clenshaw", + "number", + "tool", + "tools" + ] +} diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/test/test.factory.js b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/test/test.factory.js new file mode 100644 index 000000000000..d63b9bbbdb1e --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/test/test.factory.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var factory = require( './../lib/factory.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof factory, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a function', function test( t ) { + var f = factory( [ 1.0, 2.0, 3.0 ] ); + t.strictEqual( typeof f, 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an empty coefficient array, the function returns a function which always returns `0.0`', function test( t ) { + var f; + var v; + var i; + + f = factory( [] ); + for ( i = 0; i < 100; i++ ) { + v = f( i ); + t.strictEqual( v, 0.0, 'returns expected value' ); + } + t.end(); +}); + +tape( 'if provided only one coefficient, the function returns a function which always returns the coefficient divided by two', function test( t ) { + var f; + var v; + var i; + + f = factory( [ 2.0 ] ); + for ( i = 0; i < 100; i++ ) { + v = f( i ); + t.strictEqual( v, 1.0, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns a function which evaluates a Chebyshev series', function test( t ) { + var f; + var v; + + f = factory( [ 0.5, 1.0 ] ); + v = f( 1.0 ); + t.strictEqual( v, 0.75, 'returns expected value' ); + + v = f( 2.0 ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + f = factory( [ 1.0, 0.0, 0.0 ] ); + v = f( 2.0 ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + v = f( 0.0 ); + t.strictEqual( v, -1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a function which evaluates a Chebyshev series (large number of coefficients)', function test( t ) { + var f; + var c; + var v; + var i; + + c = []; + for ( i = 0; i < 1000; i++ ) { + c.push( 0.0 ); + } + c[ 0 ] = 1.0; // Coefficient of highest degree (T_999) + f = factory( c ); + + // Chebyshev polynomials of the first kind always satisfy T_n(1) = 1 + v = f( 2.0 ); // T_999(2/2) = T_999(1) = 1 + t.strictEqual( v, 1.0, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/test/test.js b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/test/test.js new file mode 100644 index 000000000000..1577465a55cb --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var chebyshevSeries = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof chebyshevSeries, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a `factory` method', function test( t ) { + t.strictEqual( typeof chebyshevSeries.factory, 'function', 'has method' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/test/test.main.js b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/test/test.main.js new file mode 100644 index 000000000000..79cc81a7a0ca --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/tools/chebyshev-series/test/test.main.js @@ -0,0 +1,66 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var chebyshevSeries = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof chebyshevSeries, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided an empty coefficient array, the function returns `0.0`', function test( t ) { + var v = chebyshevSeries( 1.0, [] ); + t.strictEqual( v, 0.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided only one coefficient, the function returns the coefficient divided by two', function test( t ) { + var v = chebyshevSeries( 1.0, [ 2.0 ] ); + t.strictEqual( v, 1.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function evaluates a Chebyshev series', function test( t ) { + var c; + var v; + + c = [ 0.5, 1.0 ]; + v = chebyshevSeries( 1.0, c ); + t.strictEqual( v, 0.75, 'returns expected value' ); + + v = chebyshevSeries( 2.0, c ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + c = [ 1.0, 0.0, 0.0 ]; + v = chebyshevSeries( 2.0, c ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + v = chebyshevSeries( 0.0, c ); + t.strictEqual( v, -1.0, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/tools/lib/index.js b/lib/node_modules/@stdlib/math/base/tools/lib/index.js index fdc1ccdd7207..44d080bc3707 100644 --- a/lib/node_modules/@stdlib/math/base/tools/lib/index.js +++ b/lib/node_modules/@stdlib/math/base/tools/lib/index.js @@ -40,6 +40,15 @@ var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); */ var ns = {}; +/** +* @name chebyshevSeries +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/math/base/tools/chebyshev-series} +*/ +setReadOnly( ns, 'chebyshevSeries', require( '@stdlib/math/base/tools/chebyshev-series' ) ); + /** * @name continuedFraction * @memberof ns diff --git a/lib/node_modules/@stdlib/math/iter/ops/add/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/ops/add/benchmark/benchmark.js index ec797ab9c824..24a57e9431d0 100644 --- a/lib/node_modules/@stdlib/math/iter/ops/add/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/ops/add/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAdd = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/ops/divide/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/ops/divide/benchmark/benchmark.js index 88909736e953..994ffdad9b06 100644 --- a/lib/node_modules/@stdlib/math/iter/ops/divide/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/ops/divide/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterDivide = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/ops/mod/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/ops/mod/benchmark/benchmark.js index 4b647108a2ce..62faaff78d88 100644 --- a/lib/node_modules/@stdlib/math/iter/ops/mod/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/ops/mod/benchmark/benchmark.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/iter/randu' ); var iterConstant = require( '@stdlib/iter/constant' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterMod = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var scalar; var rand; var iter; diff --git a/lib/node_modules/@stdlib/math/iter/ops/multiply/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/ops/multiply/benchmark/benchmark.js index 414cd834b42c..d54f98d57d81 100644 --- a/lib/node_modules/@stdlib/math/iter/ops/multiply/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/ops/multiply/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterMultiply = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/ops/subtract/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/ops/subtract/benchmark/benchmark.js index c9679b00798e..84d552fc3042 100644 --- a/lib/node_modules/@stdlib/math/iter/ops/subtract/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/ops/subtract/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterSubtract = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/composites/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/composites/benchmark/benchmark.js index cfe3475b03e3..017ae407e438 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/composites/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/composites/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterCompositesSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/composites/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/math/iter/sequences/composites/benchmark/benchmark.length.js index 4cacabb1f19e..a587d7b6b774 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/composites/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/composites/benchmark/benchmark.length.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterCompositesSeq = require( './../lib' ); @@ -92,7 +93,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/iter/sequences/continued-fraction/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/continued-fraction/benchmark/benchmark.js index d861196b5591..68c9e0157030 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/continued-fraction/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/continued-fraction/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterContinuedFractionSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration,default', function benchmark( b ) { +bench( format( '%s::iteration,default', pkg ), function benchmark( b ) { var iter; var z; var i; @@ -70,7 +71,7 @@ bench( pkg+'::iteration,default', function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration,terms', function benchmark( b ) { +bench( format( '%s::iteration,terms', pkg ), function benchmark( b ) { var iter; var z; var i; @@ -94,7 +95,7 @@ bench( pkg+'::iteration,terms', function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration,convergents', function benchmark( b ) { +bench( format( '%s::iteration,convergents', pkg ), function benchmark( b ) { var iter; var z; var i; @@ -118,7 +119,7 @@ bench( pkg+'::iteration,convergents', function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration,both', function benchmark( b ) { +bench( format( '%s::iteration,both', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/cubes/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/cubes/benchmark/benchmark.js index 6922c4b81a5e..f1aedfe7982f 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/cubes/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/cubes/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterCubesSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/even-integers/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/even-integers/benchmark/benchmark.js index 2d2a57fc8dea..cc5c2b5be9fa 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/even-integers/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/even-integers/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterEvenIntegersSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/factorials/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/factorials/benchmark/benchmark.js index df12960323fb..d87c58a5c19c 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/factorials/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/factorials/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterFactorialsSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/fibonacci/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/fibonacci/benchmark/benchmark.js index 7c389b4b59db..1c13020d2315 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/fibonacci/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/fibonacci/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterFibonacciSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/fifth-powers/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/fifth-powers/benchmark/benchmark.js index 6a48c809902a..6a37e7ac31d0 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/fifth-powers/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/fifth-powers/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterFifthPowersSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/fourth-powers/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/fourth-powers/benchmark/benchmark.js index a5c61bde64df..db3d081c5f51 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/fourth-powers/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/fourth-powers/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterFourthPowersSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/integers/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/integers/benchmark/benchmark.js index 6fcaf88ff225..64de3cf77c69 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/integers/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/integers/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterIntegersSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/lucas/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/lucas/benchmark/benchmark.js index ef764934b85a..c44619b30177 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/lucas/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/lucas/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterLucasSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/negafibonacci/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/negafibonacci/benchmark/benchmark.js index 56e5020ebd6b..352127b73008 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/negafibonacci/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/negafibonacci/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterNegaFibonacciSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/negalucas/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/negalucas/benchmark/benchmark.js index 7ef8031cfba9..e5c3348d1599 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/negalucas/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/negalucas/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterNegaLucasSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/negative-even-integers/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/negative-even-integers/benchmark/benchmark.js index 936308509499..31b4e286d59c 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/negative-even-integers/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/negative-even-integers/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterNegativeEvenIntegersSeq = require( './../lib' ); // eslint-disable-line id-length @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/negative-integers/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/negative-integers/benchmark/benchmark.js index 6b5e6def6e09..5441fbc98ca4 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/negative-integers/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/negative-integers/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterNegativeIntegersSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/negative-odd-integers/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/negative-odd-integers/benchmark/benchmark.js index 5f870afd078c..0a70b1a70c89 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/negative-odd-integers/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/negative-odd-integers/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterNegativeOddIntegersSeq = require( './../lib' ); // eslint-disable-line id-length @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/nonfibonacci/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/nonfibonacci/benchmark/benchmark.js index 9c44aa3489f8..8acb96f86e25 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/nonfibonacci/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/nonfibonacci/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterNonFibonacciSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/nonnegative-even-integers/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/nonnegative-even-integers/benchmark/benchmark.js index 46934b82f397..772879507d93 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/nonnegative-even-integers/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/nonnegative-even-integers/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterNonNegativeEvenIntegersSeq = require( './../lib' ); // eslint-disable-line id-length @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/nonnegative-integers/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/nonnegative-integers/benchmark/benchmark.js index c7b6d63fdf7f..071a39a07320 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/nonnegative-integers/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/nonnegative-integers/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterNonNegativeIntegersSeq = require( './../lib' ); // eslint-disable-line id-length @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/nonpositive-even-integers/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/nonpositive-even-integers/benchmark/benchmark.js index 696f41b88caf..d8bd10c0c477 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/nonpositive-even-integers/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/nonpositive-even-integers/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterNonPositiveEvenIntegersSeq = require( './../lib' ); // eslint-disable-line id-length @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/nonpositive-integers/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/nonpositive-integers/benchmark/benchmark.js index 015a7f944285..44d6b448dc5b 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/nonpositive-integers/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/nonpositive-integers/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterNonPositiveIntegersSeq = require( './../lib' ); // eslint-disable-line id-length @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/nonsquares/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/nonsquares/benchmark/benchmark.js index 1729eb99c0c9..df2c250335f3 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/nonsquares/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/nonsquares/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterNonSquaresSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/odd-integers/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/odd-integers/benchmark/benchmark.js index 3b10346f6201..9b5ed0b597c3 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/odd-integers/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/odd-integers/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterOddIntegersSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/positive-even-integers/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/positive-even-integers/benchmark/benchmark.js index 35025e48d613..eafd949b9bb2 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/positive-even-integers/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/positive-even-integers/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterPositiveEvenIntegersSeq = require( './../lib' ); // eslint-disable-line id-length @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/positive-integers/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/positive-integers/benchmark/benchmark.js index 5bf7411efde0..66e2219cf75b 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/positive-integers/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/positive-integers/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterPositiveIntegersSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/positive-odd-integers/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/positive-odd-integers/benchmark/benchmark.js index 6e46d52b0806..b162b3fe4fcd 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/positive-odd-integers/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/positive-odd-integers/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterPositiveOddIntegersSeq = require( './../lib' ); // eslint-disable-line id-length @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/primes/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/primes/benchmark/benchmark.js index f85ecd4cce03..0c2ac06a4f1c 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/primes/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/primes/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterPrimesSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/primes/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/math/iter/sequences/primes/benchmark/benchmark.length.js index 6051a271c806..876c25ed5345 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/primes/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/primes/benchmark/benchmark.length.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterPrimesSeq = require( './../lib' ); @@ -92,7 +93,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/iter/sequences/squared-triangular/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/squared-triangular/benchmark/benchmark.js index c8d6d890018d..a8be90a4cb09 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/squared-triangular/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/squared-triangular/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterSquaredTriangularSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/squares/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/squares/benchmark/benchmark.js index 665fb96479e2..a77b0174df2f 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/squares/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/squares/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterSquaresSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/triangular/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/triangular/benchmark/benchmark.js index 2dae40ddbf4c..cf91575cd680 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/triangular/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/triangular/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterTriangularSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/sequences/tribonacci/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/sequences/tribonacci/benchmark/benchmark.js index 0258ee58b40a..fd269d41289d 100644 --- a/lib/node_modules/@stdlib/math/iter/sequences/tribonacci/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/sequences/tribonacci/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterTribonacciSeq = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var z; var i; diff --git a/lib/node_modules/@stdlib/math/iter/special/abs/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/abs/benchmark/benchmark.js index e6bb086315a4..90cd62493a22 100644 --- a/lib/node_modules/@stdlib/math/iter/special/abs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/abs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAbs = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/abs2/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/abs2/benchmark/benchmark.js index 1bf2b9fef4ae..db7ba4599ac1 100644 --- a/lib/node_modules/@stdlib/math/iter/special/abs2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/abs2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAbs2 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/acos/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/acos/benchmark/benchmark.js index b7bbd5baea1b..ea121503c3fe 100644 --- a/lib/node_modules/@stdlib/math/iter/special/acos/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/acos/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAcos = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/acosh/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/acosh/benchmark/benchmark.js index f1865a2105a8..cfbec0fbff91 100644 --- a/lib/node_modules/@stdlib/math/iter/special/acosh/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/acosh/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAcosh = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/acot/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/acot/benchmark/benchmark.js index ab6f78c906a6..76d3941a4d3b 100644 --- a/lib/node_modules/@stdlib/math/iter/special/acot/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/acot/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAcot = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/acoth/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/acoth/benchmark/benchmark.js index e59bb1dac1ae..024807dea6a8 100644 --- a/lib/node_modules/@stdlib/math/iter/special/acoth/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/acoth/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAcoth = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/acovercos/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/acovercos/benchmark/benchmark.js index 8ad25a092ad9..598060a7698b 100644 --- a/lib/node_modules/@stdlib/math/iter/special/acovercos/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/acovercos/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAcovercos = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/acoversin/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/acoversin/benchmark/benchmark.js index bb54b65f8738..184300ffabb0 100644 --- a/lib/node_modules/@stdlib/math/iter/special/acoversin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/acoversin/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAcoversin = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/ahavercos/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/ahavercos/benchmark/benchmark.js index 0058c5e3605b..2b0c2d08b597 100644 --- a/lib/node_modules/@stdlib/math/iter/special/ahavercos/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/ahavercos/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAhavercos = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/ahaversin/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/ahaversin/benchmark/benchmark.js index 817edb599291..9797347584a0 100644 --- a/lib/node_modules/@stdlib/math/iter/special/ahaversin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/ahaversin/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAhaversin = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/asin/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/asin/benchmark/benchmark.js index 33e598cd4a01..3a21250d7733 100644 --- a/lib/node_modules/@stdlib/math/iter/special/asin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/asin/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAsin = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/asinh/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/asinh/benchmark/benchmark.js index 8f982e933835..768896c8df75 100644 --- a/lib/node_modules/@stdlib/math/iter/special/asinh/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/asinh/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAsinh = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/atan/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/atan/benchmark/benchmark.js index 953dd13d2f8d..e2a21a368083 100644 --- a/lib/node_modules/@stdlib/math/iter/special/atan/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/atan/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAtan = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/atan2/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/atan2/benchmark/benchmark.js index 8e874dce2bf0..0b58dbde739b 100644 --- a/lib/node_modules/@stdlib/math/iter/special/atan2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/atan2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAtan2 = require( './../lib' ); @@ -54,7 +55,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand1; var rand2; var iter; diff --git a/lib/node_modules/@stdlib/math/iter/special/atanh/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/atanh/benchmark/benchmark.js index b9b2dfeaece1..2f68ac7d0bdb 100644 --- a/lib/node_modules/@stdlib/math/iter/special/atanh/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/atanh/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAtanh = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/avercos/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/avercos/benchmark/benchmark.js index 54328fbfd7ab..b2069a4dad6e 100644 --- a/lib/node_modules/@stdlib/math/iter/special/avercos/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/avercos/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAvercos = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/aversin/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/aversin/benchmark/benchmark.js index 185c48210cd0..ddf61d1f8254 100644 --- a/lib/node_modules/@stdlib/math/iter/special/aversin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/aversin/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterAversin = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/besselj0/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/besselj0/benchmark/benchmark.js index 244a842c109a..bd254edac76f 100644 --- a/lib/node_modules/@stdlib/math/iter/special/besselj0/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/besselj0/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterBesselj0 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/besselj1/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/besselj1/benchmark/benchmark.js index c65dff7e30be..00ca99aa5726 100644 --- a/lib/node_modules/@stdlib/math/iter/special/besselj1/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/besselj1/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterBesselj1 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/bessely0/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/bessely0/benchmark/benchmark.js index 933947be18ff..eaddcbca37d4 100644 --- a/lib/node_modules/@stdlib/math/iter/special/bessely0/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/bessely0/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterBessely0 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/bessely1/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/bessely1/benchmark/benchmark.js index 7cc0a0b17909..037c9f14e512 100644 --- a/lib/node_modules/@stdlib/math/iter/special/bessely1/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/bessely1/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterBessely1 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/beta/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/beta/benchmark/benchmark.js index e6449e2606a0..40c1a65e767a 100644 --- a/lib/node_modules/@stdlib/math/iter/special/beta/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/beta/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterBeta = require( './../lib' ); @@ -54,7 +55,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand1; var rand2; var iter; diff --git a/lib/node_modules/@stdlib/math/iter/special/betaln/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/betaln/benchmark/benchmark.js index 301de564ac0b..175052c4fb4c 100644 --- a/lib/node_modules/@stdlib/math/iter/special/betaln/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/betaln/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterBetaln = require( './../lib' ); @@ -54,7 +55,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand1; var rand2; var iter; diff --git a/lib/node_modules/@stdlib/math/iter/special/binet/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/binet/benchmark/benchmark.js index f7701d1268b4..bee93beedcee 100644 --- a/lib/node_modules/@stdlib/math/iter/special/binet/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/binet/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterBinet = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/cbrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/cbrt/benchmark/benchmark.js index 9dedfa57d91e..3b881bfc805e 100644 --- a/lib/node_modules/@stdlib/math/iter/special/cbrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/cbrt/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterCbrt = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/ceil/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/ceil/benchmark/benchmark.js index 188c00017e08..5fb0a4e6b2dc 100644 --- a/lib/node_modules/@stdlib/math/iter/special/ceil/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/ceil/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterCeil = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/ceil10/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/ceil10/benchmark/benchmark.js index a5c67b4b8de4..83a44d388ada 100644 --- a/lib/node_modules/@stdlib/math/iter/special/ceil10/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/ceil10/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterCeil10 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/ceil2/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/ceil2/benchmark/benchmark.js index 5af8377d519d..f41c6b11d1d5 100644 --- a/lib/node_modules/@stdlib/math/iter/special/ceil2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/ceil2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterCeil2 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/cos/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/cos/benchmark/benchmark.js index 38328a1bfa80..db0b5bd014fa 100644 --- a/lib/node_modules/@stdlib/math/iter/special/cos/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/cos/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterCos = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/cosh/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/cosh/benchmark/benchmark.js index 01ad246b7680..0ccdb08afe76 100644 --- a/lib/node_modules/@stdlib/math/iter/special/cosh/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/cosh/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterCosh = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/cosm1/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/cosm1/benchmark/benchmark.js index 7710ea5d3818..48c0ccb4a6a1 100644 --- a/lib/node_modules/@stdlib/math/iter/special/cosm1/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/cosm1/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterCosm1 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/cospi/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/cospi/benchmark/benchmark.js index b07829ad8675..72d9002c7ee5 100644 --- a/lib/node_modules/@stdlib/math/iter/special/cospi/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/cospi/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterCospi = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/covercos/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/covercos/benchmark/benchmark.js index 4211929b2fb3..cd2fe74d98b2 100644 --- a/lib/node_modules/@stdlib/math/iter/special/covercos/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/covercos/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterCovercos = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/coversin/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/coversin/benchmark/benchmark.js index 80aa621b63a1..43cc2d2188cc 100644 --- a/lib/node_modules/@stdlib/math/iter/special/coversin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/coversin/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterCoversin = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/deg2rad/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/deg2rad/benchmark/benchmark.js index f5307f302ccd..59bc4bb16107 100644 --- a/lib/node_modules/@stdlib/math/iter/special/deg2rad/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/deg2rad/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterDeg2rad = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/digamma/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/digamma/benchmark/benchmark.js index e8749f1d9fa4..43810cf4a981 100644 --- a/lib/node_modules/@stdlib/math/iter/special/digamma/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/digamma/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterDigamma = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/dirac-delta/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/dirac-delta/benchmark/benchmark.js index a178dbf89045..8a33714cb295 100644 --- a/lib/node_modules/@stdlib/math/iter/special/dirac-delta/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/dirac-delta/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterDiracDelta = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/dirichlet-eta/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/dirichlet-eta/benchmark/benchmark.js index 7a21cd85469f..ffa4bcb7d899 100644 --- a/lib/node_modules/@stdlib/math/iter/special/dirichlet-eta/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/dirichlet-eta/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterEta = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/ellipe/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/ellipe/benchmark/benchmark.js index eeb7a07959f6..65bbf344b920 100644 --- a/lib/node_modules/@stdlib/math/iter/special/ellipe/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/ellipe/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterEllipe = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/ellipk/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/ellipk/benchmark/benchmark.js index 4ef2d24da89d..df4baba1df29 100644 --- a/lib/node_modules/@stdlib/math/iter/special/ellipk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/ellipk/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterEllipk = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/erf/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/erf/benchmark/benchmark.js index e6cfdaf6aff4..11145a352d56 100644 --- a/lib/node_modules/@stdlib/math/iter/special/erf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/erf/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterErf = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/erfc/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/erfc/benchmark/benchmark.js index d3806ecc4b59..51a33cc20d8b 100644 --- a/lib/node_modules/@stdlib/math/iter/special/erfc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/erfc/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterErfc = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/erfcinv/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/erfcinv/benchmark/benchmark.js index 00ac37f769ea..3c408a79a9e0 100644 --- a/lib/node_modules/@stdlib/math/iter/special/erfcinv/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/erfcinv/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterErfcinv = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/erfinv/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/erfinv/benchmark/benchmark.js index cd175b5a97e4..9e42335fb891 100644 --- a/lib/node_modules/@stdlib/math/iter/special/erfinv/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/erfinv/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterErfinv = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/exp/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/exp/benchmark/benchmark.js index d80f6d45139d..42b9517a3526 100644 --- a/lib/node_modules/@stdlib/math/iter/special/exp/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/exp/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterExp = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/exp10/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/exp10/benchmark/benchmark.js index d3cabb5c3ec8..3285b09e07ad 100644 --- a/lib/node_modules/@stdlib/math/iter/special/exp10/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/exp10/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterExp10 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/exp2/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/exp2/benchmark/benchmark.js index a4367edb2c60..d920a62050f0 100644 --- a/lib/node_modules/@stdlib/math/iter/special/exp2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/exp2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterExp2 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/expit/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/expit/benchmark/benchmark.js index 8c6e215f93fa..f04a0ec319b2 100644 --- a/lib/node_modules/@stdlib/math/iter/special/expit/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/expit/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterExpit = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/expm1/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/expm1/benchmark/benchmark.js index bd74d00dc64d..13c22dc99b12 100644 --- a/lib/node_modules/@stdlib/math/iter/special/expm1/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/expm1/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterExpm1 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/expm1rel/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/expm1rel/benchmark/benchmark.js index 31f9451f6726..da5d4a128abc 100644 --- a/lib/node_modules/@stdlib/math/iter/special/expm1rel/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/expm1rel/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterExpm1rel = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/factorial/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/factorial/benchmark/benchmark.js index 3375d2ea4471..78bd7a356746 100644 --- a/lib/node_modules/@stdlib/math/iter/special/factorial/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/factorial/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterFactorial = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/factorialln/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/factorialln/benchmark/benchmark.js index 3eaeb7b3fe0e..1f032bd119c0 100644 --- a/lib/node_modules/@stdlib/math/iter/special/factorialln/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/factorialln/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterFactorialln = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/floor/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/floor/benchmark/benchmark.js index 2222e8a35079..d20a067c3763 100644 --- a/lib/node_modules/@stdlib/math/iter/special/floor/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/floor/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterFloor = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/floor10/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/floor10/benchmark/benchmark.js index da8bbc4c84da..e6785d1d3a7e 100644 --- a/lib/node_modules/@stdlib/math/iter/special/floor10/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/floor10/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterFloor10 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/floor2/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/floor2/benchmark/benchmark.js index 3af77d35f579..def83e89f53a 100644 --- a/lib/node_modules/@stdlib/math/iter/special/floor2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/floor2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterFloor2 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/fresnelc/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/fresnelc/benchmark/benchmark.js index ae1fffb42d47..261bc52b9311 100644 --- a/lib/node_modules/@stdlib/math/iter/special/fresnelc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/fresnelc/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterFresnelc = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/fresnels/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/fresnels/benchmark/benchmark.js index c579e26f7ef8..a0c6330932dc 100644 --- a/lib/node_modules/@stdlib/math/iter/special/fresnels/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/fresnels/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterFresnels = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/gamma/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/gamma/benchmark/benchmark.js index a756ca8c3692..3dc0fc7d3c1d 100644 --- a/lib/node_modules/@stdlib/math/iter/special/gamma/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/gamma/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterGamma = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/gamma1pm1/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/gamma1pm1/benchmark/benchmark.js index 743e2a3d4621..6608ff00bc6a 100644 --- a/lib/node_modules/@stdlib/math/iter/special/gamma1pm1/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/gamma1pm1/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterGamma1pm1 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/gammaln/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/gammaln/benchmark/benchmark.js index ee5a3ba724d9..e18716e4fbdb 100644 --- a/lib/node_modules/@stdlib/math/iter/special/gammaln/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/gammaln/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterGammaln = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/hacovercos/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/hacovercos/benchmark/benchmark.js index be2369cd07d2..c75ecf40178a 100644 --- a/lib/node_modules/@stdlib/math/iter/special/hacovercos/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/hacovercos/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterHacovercos = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/hacoversin/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/hacoversin/benchmark/benchmark.js index a3c7c57f65d5..5e0a5d031c02 100644 --- a/lib/node_modules/@stdlib/math/iter/special/hacoversin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/hacoversin/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterHacoversin = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/havercos/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/havercos/benchmark/benchmark.js index a49efcb1ea1e..59f4fe8b7965 100644 --- a/lib/node_modules/@stdlib/math/iter/special/havercos/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/havercos/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterHavercos = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/haversin/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/haversin/benchmark/benchmark.js index cefd4c3755e2..efee769353e3 100644 --- a/lib/node_modules/@stdlib/math/iter/special/haversin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/haversin/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterHaversin = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/inv/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/inv/benchmark/benchmark.js index afd41c1ddc00..b5d5985a76f4 100644 --- a/lib/node_modules/@stdlib/math/iter/special/inv/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/inv/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterInv = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/ln/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/ln/benchmark/benchmark.js index 37fe81fab115..4f4828fbe082 100644 --- a/lib/node_modules/@stdlib/math/iter/special/ln/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/ln/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterLn = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/log/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/log/benchmark/benchmark.js index 2b3be18653d2..71a86f0be9b2 100644 --- a/lib/node_modules/@stdlib/math/iter/special/log/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/log/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterLog = require( './../lib' ); @@ -54,7 +55,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand1; var rand2; var iter; diff --git a/lib/node_modules/@stdlib/math/iter/special/log10/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/log10/benchmark/benchmark.js index a85715e716d2..b8e696c6d4d7 100644 --- a/lib/node_modules/@stdlib/math/iter/special/log10/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/log10/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterLog10 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/log1mexp/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/log1mexp/benchmark/benchmark.js index 584d2e83ff5d..c93ff14f7a92 100644 --- a/lib/node_modules/@stdlib/math/iter/special/log1mexp/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/log1mexp/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterLog1mexp = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/log1p/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/log1p/benchmark/benchmark.js index abdb05e2f546..5ebd02d1ae46 100644 --- a/lib/node_modules/@stdlib/math/iter/special/log1p/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/log1p/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterLog1p = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/log1pexp/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/log1pexp/benchmark/benchmark.js index 90425ba8f788..07338b525fa8 100644 --- a/lib/node_modules/@stdlib/math/iter/special/log1pexp/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/log1pexp/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterLog1pexp = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/log2/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/log2/benchmark/benchmark.js index 5351fa066478..6d3a4140bee8 100644 --- a/lib/node_modules/@stdlib/math/iter/special/log2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/log2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterLog2 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/logit/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/logit/benchmark/benchmark.js index c6cef30a302b..31c9d69da8b9 100644 --- a/lib/node_modules/@stdlib/math/iter/special/logit/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/logit/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterLogit = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/pow/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/pow/benchmark/benchmark.js index a876f0537199..84c87ff2b413 100644 --- a/lib/node_modules/@stdlib/math/iter/special/pow/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/pow/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterPow = require( './../lib' ); @@ -54,7 +55,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand1; var rand2; var iter; diff --git a/lib/node_modules/@stdlib/math/iter/special/rad2deg/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/rad2deg/benchmark/benchmark.js index 1632b647faaf..3a0f0b72ee11 100644 --- a/lib/node_modules/@stdlib/math/iter/special/rad2deg/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/rad2deg/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterRad2deg = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/ramp/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/ramp/benchmark/benchmark.js index 305f59d31a7a..cd31f796061b 100644 --- a/lib/node_modules/@stdlib/math/iter/special/ramp/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/ramp/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterRamp = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/riemann-zeta/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/riemann-zeta/benchmark/benchmark.js index 91de903716ac..9fdd7462aca1 100644 --- a/lib/node_modules/@stdlib/math/iter/special/riemann-zeta/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/riemann-zeta/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterZeta = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/round/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/round/benchmark/benchmark.js index b88b2801548b..f8cb737ab772 100644 --- a/lib/node_modules/@stdlib/math/iter/special/round/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/round/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterRound = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/round10/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/round10/benchmark/benchmark.js index 3c1fc114e72a..1ccf3a89378a 100644 --- a/lib/node_modules/@stdlib/math/iter/special/round10/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/round10/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterRound10 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/round2/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/round2/benchmark/benchmark.js index bcb47c8de9f1..91cf5f20944c 100644 --- a/lib/node_modules/@stdlib/math/iter/special/round2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/round2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterRound2 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/rsqrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/rsqrt/benchmark/benchmark.js index 389567af3b6e..6e15cdb87ab8 100644 --- a/lib/node_modules/@stdlib/math/iter/special/rsqrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/rsqrt/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterRsqrt = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/signum/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/signum/benchmark/benchmark.js index 83ac5e941aec..f4ec0d3c63bf 100644 --- a/lib/node_modules/@stdlib/math/iter/special/signum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/signum/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterSignum = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/sin/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/sin/benchmark/benchmark.js index 27239d4c45af..a8daa14d139a 100644 --- a/lib/node_modules/@stdlib/math/iter/special/sin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/sin/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterSin = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/sinc/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/sinc/benchmark/benchmark.js index 15b4d8195e48..c7b7694e6488 100644 --- a/lib/node_modules/@stdlib/math/iter/special/sinc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/sinc/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterSinc = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/sinh/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/sinh/benchmark/benchmark.js index 9840406c42f7..1d5f714eac45 100644 --- a/lib/node_modules/@stdlib/math/iter/special/sinh/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/sinh/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterSinh = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/sinpi/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/sinpi/benchmark/benchmark.js index 25d43b7f8b84..b84eac575797 100644 --- a/lib/node_modules/@stdlib/math/iter/special/sinpi/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/sinpi/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterSinpi = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/spence/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/spence/benchmark/benchmark.js index 4163d0544a29..d3b204ee85bb 100644 --- a/lib/node_modules/@stdlib/math/iter/special/spence/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/spence/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterSpence = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/sqrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/sqrt/benchmark/benchmark.js index c81be79ff873..a2f1b8cbf93c 100644 --- a/lib/node_modules/@stdlib/math/iter/special/sqrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/sqrt/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterSqrt = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/sqrt1pm1/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/sqrt1pm1/benchmark/benchmark.js index 213e6ea906dd..1c30a5a44eb7 100644 --- a/lib/node_modules/@stdlib/math/iter/special/sqrt1pm1/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/sqrt1pm1/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterSqrt1pm1 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/tan/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/tan/benchmark/benchmark.js index dc7deadb276b..20c833cdc289 100644 --- a/lib/node_modules/@stdlib/math/iter/special/tan/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/tan/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterTan = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/tanh/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/tanh/benchmark/benchmark.js index d825474cc116..f960641c5ecb 100644 --- a/lib/node_modules/@stdlib/math/iter/special/tanh/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/tanh/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterTanh = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/trigamma/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/trigamma/benchmark/benchmark.js index 6e69beaa26a9..4f7bced5b405 100644 --- a/lib/node_modules/@stdlib/math/iter/special/trigamma/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/trigamma/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterTrigamma = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/trunc/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/trunc/benchmark/benchmark.js index 68bbfb5cf3ee..80cf9c1f24f1 100644 --- a/lib/node_modules/@stdlib/math/iter/special/trunc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/trunc/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterTrunc = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/trunc10/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/trunc10/benchmark/benchmark.js index 9f976a1d65a6..a24c02656301 100644 --- a/lib/node_modules/@stdlib/math/iter/special/trunc10/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/trunc10/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterTrunc10 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/trunc2/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/trunc2/benchmark/benchmark.js index ec6de3f1f026..7b3bc4ce23ed 100644 --- a/lib/node_modules/@stdlib/math/iter/special/trunc2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/trunc2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterTrunc2 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/vercos/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/vercos/benchmark/benchmark.js index e00aca2c6a86..ba736f582f07 100644 --- a/lib/node_modules/@stdlib/math/iter/special/vercos/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/vercos/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterVercos = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/special/versin/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/special/versin/benchmark/benchmark.js index 48060fba5b0f..4c47280e53cd 100644 --- a/lib/node_modules/@stdlib/math/iter/special/versin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/special/versin/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterVersin = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/tools/map/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/tools/map/benchmark/benchmark.js index d6df23a0c96f..03e52444b8b1 100644 --- a/lib/node_modules/@stdlib/math/iter/tools/map/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/tools/map/benchmark/benchmark.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var sin = require( '@stdlib/math/base/special/sin' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterMap = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/tools/map2/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/tools/map2/benchmark/benchmark.js index 24857a6387c0..49fd4d3b1831 100644 --- a/lib/node_modules/@stdlib/math/iter/tools/map2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/tools/map2/benchmark/benchmark.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/iter/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var copysign = require( '@stdlib/math/base/special/copysign' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterMap2 = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var iter; var z; diff --git a/lib/node_modules/@stdlib/math/iter/tools/map3/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/iter/tools/map3/benchmark/benchmark.js index 98d67108bd0b..84566a1dfdbb 100644 --- a/lib/node_modules/@stdlib/math/iter/tools/map3/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/iter/tools/map3/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/iter/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var clamp = require( '@stdlib/math/base/special/clamp' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterMap3 = require( './../lib' ); @@ -57,7 +58,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand1; var rand2; var rand3; diff --git a/lib/node_modules/@stdlib/math/strided/ops/add-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/ops/add-by/benchmark/benchmark.js index b6c564e81c30..d8a3eaa13e4e 100644 --- a/lib/node_modules/@stdlib/math/strided/ops/add-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/ops/add-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var addBy = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/ops/add-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/ops/add-by/benchmark/benchmark.ndarray.js index 7695904f808a..df3a0d68904a 100644 --- a/lib/node_modules/@stdlib/math/strided/ops/add-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/ops/add-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var addBy = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/ops/add/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/ops/add/benchmark/benchmark.js index 34614aeaebcf..1d9ca409e0b8 100644 --- a/lib/node_modules/@stdlib/math/strided/ops/add/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/ops/add/benchmark/benchmark.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var resolveStr = require( '@stdlib/strided/base/dtype-resolve-str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var strided = require( './../lib/main.js' ); var filledBy = require( './fixtures/filled_by.js' ); @@ -138,7 +139,7 @@ function main() { for ( i = min; i <= N; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2, t3 ); - bench( pkg+':len='+len+',xtype='+t1+',ytype='+t2+',ztype='+t3, f ); + bench( format( '%s:len=%d,xtype=%s,ytype=%s,ztype=%s', pkg, len, t1, t2, t3 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/ops/add/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/ops/add/benchmark/benchmark.native.js index ee76a5cf94a9..4722a211725d 100644 --- a/lib/node_modules/@stdlib/math/strided/ops/add/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/ops/add/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var resolveStr = require( '@stdlib/strided/base/dtype-resolve-str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var filledBy = require( './fixtures/filled_by.js' ); var filled = require( './fixtures/filled.js' ); @@ -133,7 +134,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2, t3 ); - bench( pkg+'::native:len='+len+',xtype='+t1+',ytype='+t2+',ztype='+t3, opts, f ); + bench( format( '%s::native:len=%d,xtype=%s,ytype=%s,ztype=%s', pkg, len, t1, t2, t3 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/ops/add/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/ops/add/benchmark/benchmark.ndarray.js index 049894d256cf..76634bedbbe5 100644 --- a/lib/node_modules/@stdlib/math/strided/ops/add/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/ops/add/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var resolveStr = require( '@stdlib/strided/base/dtype-resolve-str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var strided = require( './../lib/ndarray.js' ); var filledBy = require( './fixtures/filled_by.js' ); @@ -138,7 +139,7 @@ function main() { for ( i = min; i <= N; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2, t3 ); - bench( pkg+':ndarray:len='+len+',xtype='+t1+',ytype='+t2+',ztype='+t3, f ); + bench( format( '%s:ndarray:len=%d,xtype=%s,ytype=%s,ztype=%s', pkg, len, t1, t2, t3 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/ops/add/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/ops/add/benchmark/benchmark.ndarray.native.js index 8b590ccbc589..7b0d98b8ade0 100644 --- a/lib/node_modules/@stdlib/math/strided/ops/add/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/ops/add/benchmark/benchmark.ndarray.native.js @@ -29,6 +29,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var resolveStr = require( '@stdlib/strided/base/dtype-resolve-str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var filledBy = require( './fixtures/filled_by.js' ); var filled = require( './fixtures/filled.js' ); @@ -133,7 +134,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2, t3 ); - bench( pkg+'::native:ndarray:len='+len+',xtype='+t1+',ytype='+t2+',ztype='+t3, opts, f ); + bench( format( '%s::native:ndarray:len=%d,xtype=%s,ytype=%s,ztype=%s', pkg, len, t1, t2, t3 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/ops/mul-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/ops/mul-by/benchmark/benchmark.js index e78f965e9d64..2754eac691d1 100644 --- a/lib/node_modules/@stdlib/math/strided/ops/mul-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/ops/mul-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mulBy = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/ops/mul-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/ops/mul-by/benchmark/benchmark.ndarray.js index 25d391522878..07a5fe9e7f4c 100644 --- a/lib/node_modules/@stdlib/math/strided/ops/mul-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/ops/mul-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mulBy = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/ops/mul/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/ops/mul/benchmark/benchmark.js index 34614aeaebcf..1d9ca409e0b8 100644 --- a/lib/node_modules/@stdlib/math/strided/ops/mul/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/ops/mul/benchmark/benchmark.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var resolveStr = require( '@stdlib/strided/base/dtype-resolve-str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var strided = require( './../lib/main.js' ); var filledBy = require( './fixtures/filled_by.js' ); @@ -138,7 +139,7 @@ function main() { for ( i = min; i <= N; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2, t3 ); - bench( pkg+':len='+len+',xtype='+t1+',ytype='+t2+',ztype='+t3, f ); + bench( format( '%s:len=%d,xtype=%s,ytype=%s,ztype=%s', pkg, len, t1, t2, t3 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/ops/mul/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/ops/mul/benchmark/benchmark.native.js index 27f282d501da..fc260f8f3420 100644 --- a/lib/node_modules/@stdlib/math/strided/ops/mul/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/ops/mul/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var resolveStr = require( '@stdlib/strided/base/dtype-resolve-str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var filledBy = require( './fixtures/filled_by.js' ); var filled = require( './fixtures/filled.js' ); @@ -133,7 +134,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2, t3 ); - bench( pkg+'::native:len='+len+',xtype='+t1+',ytype='+t2+',ztype='+t3, opts, f ); + bench( format( '%s::native:len=%d,xtype=%s,ytype=%s,ztype=%s', pkg, len, t1, t2, t3 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/ops/mul/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/ops/mul/benchmark/benchmark.ndarray.js index 049894d256cf..76634bedbbe5 100644 --- a/lib/node_modules/@stdlib/math/strided/ops/mul/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/ops/mul/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var resolveStr = require( '@stdlib/strided/base/dtype-resolve-str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var strided = require( './../lib/ndarray.js' ); var filledBy = require( './fixtures/filled_by.js' ); @@ -138,7 +139,7 @@ function main() { for ( i = min; i <= N; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2, t3 ); - bench( pkg+':ndarray:len='+len+',xtype='+t1+',ytype='+t2+',ztype='+t3, f ); + bench( format( '%s:ndarray:len=%d,xtype=%s,ytype=%s,ztype=%s', pkg, len, t1, t2, t3 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/ops/mul/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/ops/mul/benchmark/benchmark.ndarray.native.js index 8b590ccbc589..7b0d98b8ade0 100644 --- a/lib/node_modules/@stdlib/math/strided/ops/mul/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/ops/mul/benchmark/benchmark.ndarray.native.js @@ -29,6 +29,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var resolveStr = require( '@stdlib/strided/base/dtype-resolve-str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var filledBy = require( './fixtures/filled_by.js' ); var filled = require( './fixtures/filled.js' ); @@ -133,7 +134,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2, t3 ); - bench( pkg+'::native:ndarray:len='+len+',xtype='+t1+',ytype='+t2+',ztype='+t3, opts, f ); + bench( format( '%s::native:ndarray:len=%d,xtype=%s,ytype=%s,ztype=%s', pkg, len, t1, t2, t3 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/ops/sub-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/ops/sub-by/benchmark/benchmark.js index d22e135bae58..d93b7f162771 100644 --- a/lib/node_modules/@stdlib/math/strided/ops/sub-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/ops/sub-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var subBy = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/ops/sub-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/ops/sub-by/benchmark/benchmark.ndarray.js index b69174426ea3..0ee62c6a4206 100644 --- a/lib/node_modules/@stdlib/math/strided/ops/sub-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/ops/sub-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var subBy = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/abs-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/abs-by/benchmark/benchmark.js index 26663ddefaeb..e710ffe88f93 100644 --- a/lib/node_modules/@stdlib/math/strided/special/abs-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/abs-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var absBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/abs-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/abs-by/benchmark/benchmark.ndarray.js index f348f365b191..104a71a8ad97 100644 --- a/lib/node_modules/@stdlib/math/strided/special/abs-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/abs-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var absBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/abs-by/benchmark/benchmark.two_pass_comparison.js b/lib/node_modules/@stdlib/math/strided/special/abs-by/benchmark/benchmark.two_pass_comparison.js index 3819a8173225..764aa000881e 100644 --- a/lib/node_modules/@stdlib/math/strided/special/abs-by/benchmark/benchmark.two_pass_comparison.js +++ b/lib/node_modules/@stdlib/math/strided/special/abs-by/benchmark/benchmark.two_pass_comparison.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var dabs = require( '@stdlib/math/strided/special/dabs' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -159,7 +160,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::two_pass_comparison:len='+len, f ); + bench( format( '%s::two_pass_comparison:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/abs2-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/abs2-by/benchmark/benchmark.js index ec6dc330897a..af62ad61f48a 100644 --- a/lib/node_modules/@stdlib/math/strided/special/abs2-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/abs2-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var abs2By = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/abs2-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/abs2-by/benchmark/benchmark.ndarray.js index 358d857f2ebf..d18294cb9b0c 100644 --- a/lib/node_modules/@stdlib/math/strided/special/abs2-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/abs2-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var abs2By = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/abs2/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/abs2/benchmark/benchmark.js index 0962b304a819..1172ad646d83 100644 --- a/lib/node_modules/@stdlib/math/strided/special/abs2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/abs2/benchmark/benchmark.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/abs2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/abs2/benchmark/benchmark.native.js index 3e962ab2d370..a004c8fd7e58 100644 --- a/lib/node_modules/@stdlib/math/strided/special/abs2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/abs2/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/abs2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/abs2/benchmark/benchmark.ndarray.js index 6de8b4798338..fa23271eea1d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/abs2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/abs2/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':ndarray:len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/abs2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/abs2/benchmark/benchmark.ndarray.native.js index 9bc097f85d7a..bef7b529a627 100644 --- a/lib/node_modules/@stdlib/math/strided/special/abs2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/abs2/benchmark/benchmark.ndarray.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:ndarray:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/acos-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/acos-by/benchmark/benchmark.js index 25fdc548f52e..d7e67e4eb257 100644 --- a/lib/node_modules/@stdlib/math/strided/special/acos-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/acos-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var acosBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/acos-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/acos-by/benchmark/benchmark.ndarray.js index a2b3f3da2770..8890ec6e6a0e 100644 --- a/lib/node_modules/@stdlib/math/strided/special/acos-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/acos-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var acosBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/acosh-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/acosh-by/benchmark/benchmark.js index 3c25fc8eb776..3c5c8b239d69 100644 --- a/lib/node_modules/@stdlib/math/strided/special/acosh-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/acosh-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var acoshBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/acosh-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/acosh-by/benchmark/benchmark.ndarray.js index d3312e9329f8..47b418379dec 100644 --- a/lib/node_modules/@stdlib/math/strided/special/acosh-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/acosh-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var acoshBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/acot-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/acot-by/benchmark/benchmark.js index 567b47094a59..32c21393c92c 100644 --- a/lib/node_modules/@stdlib/math/strided/special/acot-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/acot-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var acotBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/acot-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/acot-by/benchmark/benchmark.ndarray.js index 41fd2c88bb12..70a3d55fbcfa 100644 --- a/lib/node_modules/@stdlib/math/strided/special/acot-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/acot-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var acotBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/acoth-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/acoth-by/benchmark/benchmark.js index 66c560365469..3434e0aae330 100644 --- a/lib/node_modules/@stdlib/math/strided/special/acoth-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/acoth-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var acothBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/acoth-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/acoth-by/benchmark/benchmark.ndarray.js index 8d9aee1161cd..daf4e66096f5 100644 --- a/lib/node_modules/@stdlib/math/strided/special/acoth-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/acoth-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var acothBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/acovercos-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/acovercos-by/benchmark/benchmark.js index afc21a06c9b3..869cfaa15af6 100644 --- a/lib/node_modules/@stdlib/math/strided/special/acovercos-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/acovercos-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var acovercosBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/acovercos-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/acovercos-by/benchmark/benchmark.ndarray.js index 3a89b4d17f56..99147d278031 100644 --- a/lib/node_modules/@stdlib/math/strided/special/acovercos-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/acovercos-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var acovercosBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/acoversin-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/acoversin-by/benchmark/benchmark.js index b66f0466079b..c970dfa1ed99 100644 --- a/lib/node_modules/@stdlib/math/strided/special/acoversin-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/acoversin-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var acoversinBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/acoversin-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/acoversin-by/benchmark/benchmark.ndarray.js index 28b8d3f3b374..68036ba07700 100644 --- a/lib/node_modules/@stdlib/math/strided/special/acoversin-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/acoversin-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var acoversinBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ahavercos-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/ahavercos-by/benchmark/benchmark.js index 2ba9dce87471..f695a5dee13e 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ahavercos-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/ahavercos-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ahavercosBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ahavercos-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/ahavercos-by/benchmark/benchmark.ndarray.js index c140209b6f50..331ce6e38cc8 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ahavercos-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/ahavercos-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ahavercosBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ahaversin-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/ahaversin-by/benchmark/benchmark.js index c2b7484bbc3d..2ff91c825a9b 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ahaversin-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/ahaversin-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ahaversinBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ahaversin-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/ahaversin-by/benchmark/benchmark.ndarray.js index 35169f093381..966c2ec6ef22 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ahaversin-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/ahaversin-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ahaversinBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/asin-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/asin-by/benchmark/benchmark.js index 32c93e45602b..00a23d6940b5 100644 --- a/lib/node_modules/@stdlib/math/strided/special/asin-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/asin-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var asinBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/asin-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/asin-by/benchmark/benchmark.ndarray.js index 7d8051b3d770..95a0408c9817 100644 --- a/lib/node_modules/@stdlib/math/strided/special/asin-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/asin-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var asinBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/asinh-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/asinh-by/benchmark/benchmark.js index 2a0d0c8dd329..38cb41f8ce33 100644 --- a/lib/node_modules/@stdlib/math/strided/special/asinh-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/asinh-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var asinhBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/asinh-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/asinh-by/benchmark/benchmark.ndarray.js index b83318a30038..e5b3d67d782f 100644 --- a/lib/node_modules/@stdlib/math/strided/special/asinh-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/asinh-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var asinhBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/asinh-by/test/test.main.js b/lib/node_modules/@stdlib/math/strided/special/asinh-by/test/test.main.js index 25c53bc69db9..4c69b9305406 100644 --- a/lib/node_modules/@stdlib/math/strided/special/asinh-by/test/test.main.js +++ b/lib/node_modules/@stdlib/math/strided/special/asinh-by/test/test.main.js @@ -74,6 +74,7 @@ tape( 'the function computes the hyperbolic arcsine via a callback function', fu asinhBy( x.length, x, 1, y, 1, accessor ); t.deepEqual( y, expected, 'deep equal' ); + // eslint-disable-next-line stdlib/no-new-array x = new Array( 5 ); // sparse array y = [ 0.0, 0.0, 0.0, 0.0, 0.0 ]; @@ -82,6 +83,7 @@ tape( 'the function computes the hyperbolic arcsine via a callback function', fu asinhBy( x.length, x, 1, y, 1, accessor ); t.deepEqual( y, expected, 'deep equal' ); + // eslint-disable-next-line stdlib/no-new-array x = new Array( 5 ); // sparse array x[ 2 ] = rand(); y = [ 0.0, 0.0, 0.0, 0.0, 0.0 ]; diff --git a/lib/node_modules/@stdlib/math/strided/special/atan-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/atan-by/benchmark/benchmark.js index 26c0877edc9d..084f5b436e45 100644 --- a/lib/node_modules/@stdlib/math/strided/special/atan-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/atan-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var atanBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/atan-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/atan-by/benchmark/benchmark.ndarray.js index e68fd824bd84..1b1442b12c79 100644 --- a/lib/node_modules/@stdlib/math/strided/special/atan-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/atan-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var atanBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/atanh-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/atanh-by/benchmark/benchmark.js index 604a7557053c..ab943f02f9a8 100644 --- a/lib/node_modules/@stdlib/math/strided/special/atanh-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/atanh-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var atanhBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/atanh-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/atanh-by/benchmark/benchmark.ndarray.js index e7a9d5abca32..702095b6c42d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/atanh-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/atanh-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var atanhBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/avercos-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/avercos-by/benchmark/benchmark.js index 67e552a11a37..ffe912a8a718 100644 --- a/lib/node_modules/@stdlib/math/strided/special/avercos-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/avercos-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var avercosBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/avercos-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/avercos-by/benchmark/benchmark.ndarray.js index bc98dfb597b6..e718bb390455 100644 --- a/lib/node_modules/@stdlib/math/strided/special/avercos-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/avercos-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var avercosBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/aversin-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/aversin-by/benchmark/benchmark.js index 7e2132a2da9c..5c649333d6c4 100644 --- a/lib/node_modules/@stdlib/math/strided/special/aversin-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/aversin-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var aversinBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/aversin-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/aversin-by/benchmark/benchmark.ndarray.js index c9c4ac628fb5..ec1f6fadd2ff 100644 --- a/lib/node_modules/@stdlib/math/strided/special/aversin-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/aversin-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var aversinBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/besselj0-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/besselj0-by/benchmark/benchmark.js index d1c714194893..aa368e67342e 100644 --- a/lib/node_modules/@stdlib/math/strided/special/besselj0-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/besselj0-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var besselj0By = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/besselj0-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/besselj0-by/benchmark/benchmark.ndarray.js index 2d7d18bbc5b3..8172b7f026f9 100644 --- a/lib/node_modules/@stdlib/math/strided/special/besselj0-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/besselj0-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var besselj0By = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/besselj1-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/besselj1-by/benchmark/benchmark.js index f453c8879c4c..4dee0d1df55b 100644 --- a/lib/node_modules/@stdlib/math/strided/special/besselj1-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/besselj1-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var besselj1By = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/besselj1-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/besselj1-by/benchmark/benchmark.ndarray.js index d5d4e8b19e6a..b35db28bf5e1 100644 --- a/lib/node_modules/@stdlib/math/strided/special/besselj1-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/besselj1-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var besselj1By = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/bessely0-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/bessely0-by/benchmark/benchmark.js index 064d0f4d561c..39ea7420b586 100644 --- a/lib/node_modules/@stdlib/math/strided/special/bessely0-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/bessely0-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var bessely0By = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/bessely0-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/bessely0-by/benchmark/benchmark.ndarray.js index f28ba894d966..e8be30b9df38 100644 --- a/lib/node_modules/@stdlib/math/strided/special/bessely0-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/bessely0-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var bessely0By = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/bessely1-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/bessely1-by/benchmark/benchmark.js index 93ca6f5641d9..19cf6519b9ad 100644 --- a/lib/node_modules/@stdlib/math/strided/special/bessely1-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/bessely1-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var bessely1By = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/bessely1-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/bessely1-by/benchmark/benchmark.ndarray.js index 70bd4fa9d221..e06bddf5f930 100644 --- a/lib/node_modules/@stdlib/math/strided/special/bessely1-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/bessely1-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var bessely1By = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/binet-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/binet-by/benchmark/benchmark.js index d4736cde1532..4a5ad7c34a63 100644 --- a/lib/node_modules/@stdlib/math/strided/special/binet-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/binet-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var binetBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/binet-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/binet-by/benchmark/benchmark.ndarray.js index 6b9039fa4580..8eb01403167d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/binet-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/binet-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var binetBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/cbrt-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/cbrt-by/benchmark/benchmark.js index ed8b6ee36205..572f57081417 100644 --- a/lib/node_modules/@stdlib/math/strided/special/cbrt-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/cbrt-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cbrtBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/cbrt-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/cbrt-by/benchmark/benchmark.ndarray.js index f1cc7ff747d2..a17187ca61f6 100644 --- a/lib/node_modules/@stdlib/math/strided/special/cbrt-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/cbrt-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cbrtBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/cbrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/cbrt/benchmark/benchmark.js index a99024d3ce9b..90af7fc5a046 100644 --- a/lib/node_modules/@stdlib/math/strided/special/cbrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/cbrt/benchmark/benchmark.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/cbrt/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/cbrt/benchmark/benchmark.native.js index 0a3b5fa30857..e481b423511a 100644 --- a/lib/node_modules/@stdlib/math/strided/special/cbrt/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/cbrt/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/cbrt/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/cbrt/benchmark/benchmark.ndarray.js index 5e0d38e2102f..04414ac7a789 100644 --- a/lib/node_modules/@stdlib/math/strided/special/cbrt/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/cbrt/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':ndarray:len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/cbrt/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/cbrt/benchmark/benchmark.ndarray.native.js index 48f6d3237038..eae74d0d7c36 100644 --- a/lib/node_modules/@stdlib/math/strided/special/cbrt/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/cbrt/benchmark/benchmark.ndarray.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:ndarray:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ceil/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/ceil/benchmark/benchmark.js index a99024d3ce9b..90af7fc5a046 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ceil/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/ceil/benchmark/benchmark.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ceil/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/ceil/benchmark/benchmark.native.js index 27e6710a3892..af9c61d1c5d7 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ceil/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/ceil/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ceil/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/ceil/benchmark/benchmark.ndarray.js index 5e0d38e2102f..04414ac7a789 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ceil/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/ceil/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':ndarray:len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ceil/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/ceil/benchmark/benchmark.ndarray.native.js index 48f6d3237038..eae74d0d7c36 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ceil/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/ceil/benchmark/benchmark.ndarray.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:ndarray:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/cos-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/cos-by/benchmark/benchmark.js index 58d7fcac69d4..3b4be7160833 100644 --- a/lib/node_modules/@stdlib/math/strided/special/cos-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/cos-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cosBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/cos-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/cos-by/benchmark/benchmark.ndarray.js index b88e5d365d91..a5d4aa84da48 100644 --- a/lib/node_modules/@stdlib/math/strided/special/cos-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/cos-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cosBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dabs/benchmark/benchmark.js index 1e89e46cbfd5..f63cb871120c 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dabs/benchmark/benchmark.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dabs = require( './../lib/main.js' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dabs/benchmark/benchmark.native.js index 4a4a4595e106..dd6c2827e29b 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dabs/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dabs/benchmark/benchmark.ndarray.js index e446ab161dea..24656d98502c 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dabs/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dabs = require( './../lib/ndarray.js' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dabs/benchmark/benchmark.ndarray.native.js index 0ed6fbd2e040..7dccadafe723 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dabs/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dabs2/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dabs2/benchmark/benchmark.js index bb65f235bfb5..e7b1b0653121 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dabs2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dabs2/benchmark/benchmark.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dabs2 = require( './../lib/main.js' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dabs2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dabs2/benchmark/benchmark.native.js index 4d0946a76e77..bccd6c5671b9 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dabs2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dabs2/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dabs2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dabs2/benchmark/benchmark.ndarray.js index dea7d7bf7bb3..0088e438264c 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dabs2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dabs2/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dabs2 = require( './../lib/ndarray.js' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dabs2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dabs2/benchmark/benchmark.ndarray.native.js index c8c8375be67a..93e36ef0be8b 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dabs2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dabs2/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dcbrt-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dcbrt-by/benchmark/benchmark.js index 1a23635da1ed..a0904eaa2f43 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dcbrt-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dcbrt-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcbrtBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dcbrt-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dcbrt-by/benchmark/benchmark.ndarray.js index d5b4a84d808e..6d7c9d3e66bb 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dcbrt-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dcbrt-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcbrtBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dcbrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dcbrt/benchmark/benchmark.js index ff46d765079c..098772c0c4e8 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dcbrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dcbrt/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcbrt = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dcbrt/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dcbrt/benchmark/benchmark.native.js index b476380cc73c..51b364ff3765 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dcbrt/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dcbrt/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dcbrt/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dcbrt/benchmark/benchmark.ndarray.js index 1e47aa03fcb1..c1b0e0a029d3 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dcbrt/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dcbrt/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcbrt = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dcbrt/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dcbrt/benchmark/benchmark.ndarray.native.js index 76d83a00d653..2ed9986f6168 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dcbrt/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dcbrt/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dceil/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dceil/benchmark/benchmark.js index 67b11aa3a866..f11be2dc3de8 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dceil/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dceil/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dceil = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dceil/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dceil/benchmark/benchmark.native.js index fdfcfff746d1..67d69a3dd5dd 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dceil/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dceil/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dceil/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dceil/benchmark/benchmark.ndarray.js index 67f5fd4218f9..0f59d0800a5d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dceil/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dceil/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dceil = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dceil/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dceil/benchmark/benchmark.ndarray.native.js index 614915211876..aead03da1e24 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dceil/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dceil/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ddeg2rad/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/ddeg2rad/benchmark/benchmark.js index 963a0070a9ad..daaab841fc00 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ddeg2rad/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/ddeg2rad/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ddeg2rad = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ddeg2rad/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/ddeg2rad/benchmark/benchmark.native.js index 381409f1b70e..bd58bccd9ac3 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ddeg2rad/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/ddeg2rad/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ddeg2rad/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/ddeg2rad/benchmark/benchmark.ndarray.js index 653582e195c7..8bae7aab1410 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ddeg2rad/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/ddeg2rad/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ddeg2rad = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ddeg2rad/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/ddeg2rad/benchmark/benchmark.ndarray.native.js index ffb3b865e493..ad10a1192488 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ddeg2rad/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/ddeg2rad/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/deg2rad/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/deg2rad/benchmark/benchmark.js index 525f54c3588b..74a945e4024b 100644 --- a/lib/node_modules/@stdlib/math/strided/special/deg2rad/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/deg2rad/benchmark/benchmark.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/deg2rad/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/deg2rad/benchmark/benchmark.native.js index 96a7ffc75f4b..bdd4a99c9c7a 100644 --- a/lib/node_modules/@stdlib/math/strided/special/deg2rad/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/deg2rad/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/deg2rad/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/deg2rad/benchmark/benchmark.ndarray.js index 37861f939149..bfa94caaf297 100644 --- a/lib/node_modules/@stdlib/math/strided/special/deg2rad/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/deg2rad/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':ndarray:len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/deg2rad/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/deg2rad/benchmark/benchmark.ndarray.native.js index d5d841789bdc..269c05c691e8 100644 --- a/lib/node_modules/@stdlib/math/strided/special/deg2rad/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/deg2rad/benchmark/benchmark.ndarray.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:ndarray:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dfloor/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dfloor/benchmark/benchmark.js index 510b7823b77f..919235e4a996 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dfloor/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dfloor/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dfloor = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dfloor/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dfloor/benchmark/benchmark.native.js index 1133447971e1..8b57eede9e63 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dfloor/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dfloor/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dfloor/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dfloor/benchmark/benchmark.ndarray.js index e3f8a39e7c53..f78def9e6b36 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dfloor/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dfloor/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dfloor = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dfloor/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dfloor/benchmark/benchmark.ndarray.native.js index 1b3c2a00ac5d..6224c7b61318 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dfloor/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dfloor/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dinv/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dinv/benchmark/benchmark.js index 96801f75d400..9e1ce5764f6b 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dinv/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dinv/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dinv = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dinv/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dinv/benchmark/benchmark.native.js index 32f3d8efa726..d127f586d6f2 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dinv/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dinv/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dinv/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dinv/benchmark/benchmark.ndarray.js index 311a40006687..6a14285512e4 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dinv/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dinv/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dinv = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dinv/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dinv/benchmark/benchmark.ndarray.native.js index 03da183a3cec..d16ef3c427fb 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dinv/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dinv/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dmskabs/benchmark/benchmark.js index 050e237e6921..06605e56e424 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskabs/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskabs = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskabs/benchmark/benchmark.native.js index 7988a30d1eda..2bc7269d3751 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskabs/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dmskabs/benchmark/benchmark.ndarray.js index 99b1f7e7b0dd..6fa228a08cf9 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskabs/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskabs = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskabs/benchmark/benchmark.ndarray.native.js index 9301b14ee7d9..7d68b7223c38 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskabs/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskabs2/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dmskabs2/benchmark/benchmark.js index 320fed63c878..3e714bd2d6a3 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskabs2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskabs2/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskabs2 = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskabs2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskabs2/benchmark/benchmark.native.js index 7834bee2b4f0..dcefc4a6473d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskabs2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskabs2/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskabs2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dmskabs2/benchmark/benchmark.ndarray.js index b5228bbacbce..84682055829b 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskabs2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskabs2/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskabs2 = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskabs2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskabs2/benchmark/benchmark.ndarray.native.js index 360893880a8e..4b145b9a64ef 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskabs2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskabs2/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskcbrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dmskcbrt/benchmark/benchmark.js index 414b057d0a2b..a5b9b3a26883 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskcbrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskcbrt/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskcbrt = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskcbrt/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskcbrt/benchmark/benchmark.native.js index 9dd6edcd5d22..0fa72c6bef9e 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskcbrt/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskcbrt/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskcbrt/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dmskcbrt/benchmark/benchmark.ndarray.js index 81c08d91a4f2..d7267117ef3f 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskcbrt/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskcbrt/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskcbrt = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskcbrt/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskcbrt/benchmark/benchmark.ndarray.native.js index 15732f83cbfe..5f4b77bf755e 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskcbrt/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskcbrt/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskceil/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dmskceil/benchmark/benchmark.js index b82858c68977..5d51b521a580 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskceil/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskceil/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskceil = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskceil/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskceil/benchmark/benchmark.native.js index 364e0b03e0f0..9f89c7b0a2ee 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskceil/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskceil/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskceil/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dmskceil/benchmark/benchmark.ndarray.js index 2964063d219e..668d3bb481a0 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskceil/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskceil/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskceil = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskceil/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskceil/benchmark/benchmark.ndarray.native.js index 1cfc1e29f359..0fd81a7ff0b2 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskceil/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskceil/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskdeg2rad/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dmskdeg2rad/benchmark/benchmark.js index a13f364f3ce2..82157a9baabb 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskdeg2rad/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskdeg2rad/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskdeg2rad = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskdeg2rad/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskdeg2rad/benchmark/benchmark.native.js index ae47ee89c8fc..3f824d27a79a 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskdeg2rad/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskdeg2rad/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskdeg2rad/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dmskdeg2rad/benchmark/benchmark.ndarray.js index de7e5a31d889..039be3b6bd82 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskdeg2rad/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskdeg2rad/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskdeg2rad = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskdeg2rad/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskdeg2rad/benchmark/benchmark.ndarray.native.js index bce1e970d9c4..a4c39fbc89be 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskdeg2rad/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskdeg2rad/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskfloor/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dmskfloor/benchmark/benchmark.js index 5a6e9eccb3d5..e585f9bd5ad2 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskfloor/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskfloor/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskfloor = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskfloor/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskfloor/benchmark/benchmark.native.js index 4f4460c6c2f4..a3eb03f98965 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskfloor/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskfloor/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskfloor/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dmskfloor/benchmark/benchmark.ndarray.js index 1799e79f0df9..13b30b082f64 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskfloor/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskfloor/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskfloor = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskfloor/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskfloor/benchmark/benchmark.ndarray.native.js index e8dd2cb54c24..f244b449c8ff 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskfloor/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskfloor/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskinv/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dmskinv/benchmark/benchmark.js index b2a27914e7d4..cc436bc00a24 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskinv/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskinv/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskinv = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskinv/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskinv/benchmark/benchmark.native.js index 957da82513ad..43f3acb63e95 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskinv/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskinv/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskinv/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dmskinv/benchmark/benchmark.ndarray.js index 3e3370a1154f..366556a74791 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskinv/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskinv/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskinv = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskinv/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskinv/benchmark/benchmark.ndarray.native.js index 477faec0dd5c..035a15c1734d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskinv/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskinv/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskramp/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dmskramp/benchmark/benchmark.js index 88bb93b1a9ca..22c35437f90f 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskramp/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskramp/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskramp = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskramp/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskramp/benchmark/benchmark.native.js index 1d1af4f59494..095e0fb6d71f 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskramp/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskramp/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskramp/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dmskramp/benchmark/benchmark.ndarray.js index 5f670c46c983..154522c3a07f 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskramp/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskramp/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskramp = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskramp/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskramp/benchmark/benchmark.ndarray.native.js index 15dee654fa9f..857d9643d0e1 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskramp/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskramp/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskrsqrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dmskrsqrt/benchmark/benchmark.js index b714be739c1d..c9115aa324f9 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskrsqrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskrsqrt/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskrsqrt = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskrsqrt/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskrsqrt/benchmark/benchmark.native.js index 656db674b8d4..a6789887b791 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskrsqrt/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskrsqrt/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskrsqrt/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dmskrsqrt/benchmark/benchmark.ndarray.js index 0cadd9fa4625..49d6c0f79627 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskrsqrt/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskrsqrt/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskrsqrt = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmskrsqrt/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dmskrsqrt/benchmark/benchmark.ndarray.native.js index 8c4f25c512fa..d0ce816ef517 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmskrsqrt/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmskrsqrt/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmsksqrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dmsksqrt/benchmark/benchmark.js index 16bc955b984d..f5f2ffcc35cb 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmsksqrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmsksqrt/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmsksqrt = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmsksqrt/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dmsksqrt/benchmark/benchmark.native.js index a4d78efb3269..341cc8df06d8 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmsksqrt/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmsksqrt/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmsksqrt/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dmsksqrt/benchmark/benchmark.ndarray.js index b7ac907ff5a5..bbff8d9ef204 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmsksqrt/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmsksqrt/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmsksqrt = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmsksqrt/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dmsksqrt/benchmark/benchmark.ndarray.native.js index 1adce84867d4..67608768dd0e 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmsksqrt/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmsksqrt/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmsktrunc/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dmsktrunc/benchmark/benchmark.js index dedfde073102..9ea217b7625b 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmsktrunc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmsktrunc/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmsktrunc = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmsktrunc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dmsktrunc/benchmark/benchmark.native.js index fcbc069e5ccb..05fc302ccede 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmsktrunc/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmsktrunc/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmsktrunc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dmsktrunc/benchmark/benchmark.ndarray.js index f97f5fe808ba..642369f86ca0 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmsktrunc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmsktrunc/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmsktrunc = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dmsktrunc/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dmsktrunc/benchmark/benchmark.ndarray.native.js index 365098b5f4d8..0d1cce2f6cab 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dmsktrunc/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dmsktrunc/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dramp/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dramp/benchmark/benchmark.js index 4a010089f6e7..26248aa39147 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dramp/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dramp/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dramp = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dramp/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dramp/benchmark/benchmark.native.js index aab667e519a1..bdd50412f0bd 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dramp/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dramp/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dramp/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dramp/benchmark/benchmark.ndarray.js index 7cd3f8851f1b..223a0e57783e 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dramp/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dramp/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dramp = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dramp/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dramp/benchmark/benchmark.ndarray.native.js index b11b66ac0c59..31762273bb24 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dramp/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dramp/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/drsqrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/drsqrt/benchmark/benchmark.js index 0902767be23e..92013fe43a8b 100644 --- a/lib/node_modules/@stdlib/math/strided/special/drsqrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/drsqrt/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var drsqrt = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/drsqrt/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/drsqrt/benchmark/benchmark.native.js index 3d4341b6d9be..5ea6f67df54c 100644 --- a/lib/node_modules/@stdlib/math/strided/special/drsqrt/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/drsqrt/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/drsqrt/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/drsqrt/benchmark/benchmark.ndarray.js index 9fedd3095aa1..91e877eb358d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/drsqrt/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/drsqrt/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var drsqrt = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/drsqrt/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/drsqrt/benchmark/benchmark.ndarray.native.js index dcc1c4c6263f..b235dd391531 100644 --- a/lib/node_modules/@stdlib/math/strided/special/drsqrt/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/drsqrt/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dsqrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dsqrt/benchmark/benchmark.js index 3098d9da9cb1..2cbffcfe9f2a 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dsqrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dsqrt/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsqrt = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dsqrt/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dsqrt/benchmark/benchmark.native.js index 2c6b3259ace2..1e5da30cd118 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dsqrt/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dsqrt/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dsqrt/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dsqrt/benchmark/benchmark.ndarray.js index 130a775c711a..0adca1d47d8d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dsqrt/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dsqrt/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsqrt = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dsqrt/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dsqrt/benchmark/benchmark.ndarray.native.js index cc0de6ff3238..b2cb5dfc219a 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dsqrt/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dsqrt/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dtrunc/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/dtrunc/benchmark/benchmark.js index e2069ed88c8a..96b3acf1d39d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dtrunc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/dtrunc/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dtrunc = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dtrunc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/dtrunc/benchmark/benchmark.native.js index ed275be1dbe9..a49cf2bd5d9d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dtrunc/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dtrunc/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dtrunc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/dtrunc/benchmark/benchmark.ndarray.js index 5499cec0a766..4510d509392d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dtrunc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/dtrunc/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dtrunc = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/dtrunc/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/dtrunc/benchmark/benchmark.ndarray.native.js index f0098210bb2c..a3e4c8a7c40e 100644 --- a/lib/node_modules/@stdlib/math/strided/special/dtrunc/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/dtrunc/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/floor/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/floor/benchmark/benchmark.js index a99024d3ce9b..90af7fc5a046 100644 --- a/lib/node_modules/@stdlib/math/strided/special/floor/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/floor/benchmark/benchmark.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/floor/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/floor/benchmark/benchmark.native.js index d335b8d110fc..0a907bee5cb1 100644 --- a/lib/node_modules/@stdlib/math/strided/special/floor/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/floor/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/floor/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/floor/benchmark/benchmark.ndarray.js index 5e0d38e2102f..04414ac7a789 100644 --- a/lib/node_modules/@stdlib/math/strided/special/floor/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/floor/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':ndarray:len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/floor/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/floor/benchmark/benchmark.ndarray.native.js index 48f6d3237038..eae74d0d7c36 100644 --- a/lib/node_modules/@stdlib/math/strided/special/floor/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/floor/benchmark/benchmark.ndarray.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:ndarray:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/inv/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/inv/benchmark/benchmark.js index 1bfc674615b5..242d65e0be0b 100644 --- a/lib/node_modules/@stdlib/math/strided/special/inv/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/inv/benchmark/benchmark.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/inv/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/inv/benchmark/benchmark.native.js index 28a6478d2844..0af4738332bd 100644 --- a/lib/node_modules/@stdlib/math/strided/special/inv/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/inv/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/inv/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/inv/benchmark/benchmark.ndarray.js index 62a8ad7ef767..d8a567adba0c 100644 --- a/lib/node_modules/@stdlib/math/strided/special/inv/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/inv/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':ndarray:len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/inv/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/inv/benchmark/benchmark.ndarray.native.js index 36625974500b..6586acd2dc2e 100644 --- a/lib/node_modules/@stdlib/math/strided/special/inv/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/inv/benchmark/benchmark.ndarray.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:ndarray:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ramp/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/ramp/benchmark/benchmark.js index 69c39ff25393..c4683eaea3a7 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ramp/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/ramp/benchmark/benchmark.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ramp/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/ramp/benchmark/benchmark.native.js index dd8dbd1d04c2..182af9455eae 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ramp/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/ramp/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ramp/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/ramp/benchmark/benchmark.ndarray.js index 127a8691a589..13e50955be6d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ramp/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/ramp/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':ndarray:len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ramp/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/ramp/benchmark/benchmark.ndarray.native.js index 616df1c30a3f..12f0eb05a293 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ramp/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/ramp/benchmark/benchmark.ndarray.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:ndarray:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/rsqrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/rsqrt/benchmark/benchmark.js index df8f45b0f86a..9f575421cad8 100644 --- a/lib/node_modules/@stdlib/math/strided/special/rsqrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/rsqrt/benchmark/benchmark.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/rsqrt/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/rsqrt/benchmark/benchmark.native.js index 8cfc6a81a000..e013000a8a01 100644 --- a/lib/node_modules/@stdlib/math/strided/special/rsqrt/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/rsqrt/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/rsqrt/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/rsqrt/benchmark/benchmark.ndarray.js index a069487f1ce4..927a252bec43 100644 --- a/lib/node_modules/@stdlib/math/strided/special/rsqrt/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/rsqrt/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':ndarray:len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/rsqrt/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/rsqrt/benchmark/benchmark.ndarray.native.js index 34dfda5d17dd..58a7cab20a10 100644 --- a/lib/node_modules/@stdlib/math/strided/special/rsqrt/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/rsqrt/benchmark/benchmark.ndarray.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:ndarray:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/sabs/benchmark/benchmark.js index 33552e35e968..705f92765217 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/sabs/benchmark/benchmark.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sabs = require( './../lib/main.js' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/sabs/benchmark/benchmark.native.js index 88b0b01fcbd7..d276521a8146 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/sabs/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/sabs/benchmark/benchmark.ndarray.js index d9298197ac4d..55141e5342d3 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/sabs/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sabs = require( './../lib/ndarray.js' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/sabs/benchmark/benchmark.ndarray.native.js index 251a520df7ee..63201fe8bfbb 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/sabs/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sabs2/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/sabs2/benchmark/benchmark.js index f1b56f58ccfb..6c19782687f5 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sabs2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/sabs2/benchmark/benchmark.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sabs2 = require( './../lib/main.js' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sabs2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/sabs2/benchmark/benchmark.native.js index 1240e330bbaa..edc59b10f402 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sabs2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/sabs2/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sabs2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/sabs2/benchmark/benchmark.ndarray.js index bf90d3fa296c..bac6a1e47677 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sabs2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/sabs2/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sabs2 = require( './../lib/ndarray.js' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sabs2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/sabs2/benchmark/benchmark.ndarray.native.js index 53a93e45983f..c46ac78a3a0b 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sabs2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/sabs2/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/scbrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/scbrt/benchmark/benchmark.js index 4db0c914ad03..5a2c17d7aa1c 100644 --- a/lib/node_modules/@stdlib/math/strided/special/scbrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/scbrt/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scbrt = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/scbrt/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/scbrt/benchmark/benchmark.native.js index c93e7567c898..08513f639dbb 100644 --- a/lib/node_modules/@stdlib/math/strided/special/scbrt/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/scbrt/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/scbrt/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/scbrt/benchmark/benchmark.ndarray.js index 924107e16f33..b58c23e947ba 100644 --- a/lib/node_modules/@stdlib/math/strided/special/scbrt/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/scbrt/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scbrt = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/scbrt/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/scbrt/benchmark/benchmark.ndarray.native.js index 815a26150e01..fc8106e36bb8 100644 --- a/lib/node_modules/@stdlib/math/strided/special/scbrt/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/scbrt/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sceil/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/sceil/benchmark/benchmark.js index b533c73a162a..6851ce5096cc 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sceil/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/sceil/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sceil = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sceil/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/sceil/benchmark/benchmark.native.js index 9d1c2b227666..7f3bb3e6045b 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sceil/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/sceil/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sceil/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/sceil/benchmark/benchmark.ndarray.js index ae81faaffa25..4ba326816d6a 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sceil/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/sceil/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sceil = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sceil/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/sceil/benchmark/benchmark.ndarray.native.js index 830c85f589c6..695569ccf248 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sceil/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/sceil/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sdeg2rad/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/sdeg2rad/benchmark/benchmark.js index fbfea0e0bff5..026da0d4a8d5 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sdeg2rad/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/sdeg2rad/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdeg2rad = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sdeg2rad/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/sdeg2rad/benchmark/benchmark.native.js index 9f3510e3f82e..977c60d58c0e 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sdeg2rad/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/sdeg2rad/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sdeg2rad/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/sdeg2rad/benchmark/benchmark.ndarray.js index ed35aa9c32e8..e2d5551c01bf 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sdeg2rad/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/sdeg2rad/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdeg2rad = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sdeg2rad/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/sdeg2rad/benchmark/benchmark.ndarray.native.js index ce49406bdd4d..d05aaba1d48b 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sdeg2rad/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/sdeg2rad/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sfloor/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/sfloor/benchmark/benchmark.js index 15212da3351b..6785ac34d2e6 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sfloor/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/sfloor/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sfloor = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sfloor/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/sfloor/benchmark/benchmark.native.js index 4f7a9a2237af..5af505d1bdc0 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sfloor/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/sfloor/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sfloor/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/sfloor/benchmark/benchmark.ndarray.js index b2280ac8d6d3..0658c6211726 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sfloor/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/sfloor/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sfloor = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sfloor/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/sfloor/benchmark/benchmark.ndarray.native.js index c036bc983d99..b850ea688ecc 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sfloor/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/sfloor/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sin-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/sin-by/benchmark/benchmark.js index 6b9e100f4cb3..bdcc12741269 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sin-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/sin-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sinBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sin-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/sin-by/benchmark/benchmark.ndarray.js index de187c806ab2..c111da5f8388 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sin-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/sin-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sinBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sinv/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/sinv/benchmark/benchmark.js index 3da5c59ef32f..167d40d4d5f0 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sinv/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/sinv/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sinv = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sinv/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/sinv/benchmark/benchmark.native.js index 8d0c76638a4a..c0885fa7633f 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sinv/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/sinv/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sinv/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/sinv/benchmark/benchmark.ndarray.js index e6350ef1b145..44afe236c1ca 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sinv/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/sinv/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sinv = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sinv/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/sinv/benchmark/benchmark.ndarray.native.js index 394018c2e530..c3fd027882e1 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sinv/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/sinv/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/smskabs/benchmark/benchmark.js index 2b3859844feb..3610cd88d89d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskabs/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskabs = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/smskabs/benchmark/benchmark.native.js index 16701f810883..b069cbaf6b7e 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskabs/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/smskabs/benchmark/benchmark.ndarray.js index df0ab5de0d6c..6693ebf275c6 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskabs/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskabs = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/smskabs/benchmark/benchmark.ndarray.native.js index 7b4bd9e401db..2ddf9fbc1902 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskabs/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskabs2/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/smskabs2/benchmark/benchmark.js index 89a602f291bb..739d27ce2290 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskabs2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskabs2/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskabs2 = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskabs2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/smskabs2/benchmark/benchmark.native.js index 42e13aa82a2f..682deba2b59d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskabs2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskabs2/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskabs2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/smskabs2/benchmark/benchmark.ndarray.js index b2a0f9fcd17e..22307a127616 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskabs2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskabs2/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskabs2 = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskabs2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/smskabs2/benchmark/benchmark.ndarray.native.js index b2a0e47b64e0..0bca277b4b26 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskabs2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskabs2/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskcbrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/smskcbrt/benchmark/benchmark.js index 4e47f714c6b6..17b08c36f650 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskcbrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskcbrt/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskcbrt = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskcbrt/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/smskcbrt/benchmark/benchmark.native.js index 1ce55f631c84..7f330368770d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskcbrt/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskcbrt/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskcbrt/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/smskcbrt/benchmark/benchmark.ndarray.js index 7c95efae112c..e0a116c552fb 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskcbrt/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskcbrt/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskcbrt = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskcbrt/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/smskcbrt/benchmark/benchmark.ndarray.native.js index 5c18aaf8b5f7..c93e8aab17a5 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskcbrt/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskcbrt/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskceil/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/smskceil/benchmark/benchmark.js index e8490186df71..5cbf39e106e9 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskceil/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskceil/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskceil = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskceil/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/smskceil/benchmark/benchmark.native.js index eebdc8cc76df..ca2d7de5e654 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskceil/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskceil/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskceil/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/smskceil/benchmark/benchmark.ndarray.js index df7a1f808799..5855e0b24fb1 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskceil/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskceil/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskceil = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskceil/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/smskceil/benchmark/benchmark.ndarray.native.js index 14e9834d9aed..f059ee47b664 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskceil/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskceil/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskdeg2rad/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/smskdeg2rad/benchmark/benchmark.js index 3caa8dffa5d2..703552d1f46e 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskdeg2rad/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskdeg2rad/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskdeg2rad = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskdeg2rad/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/smskdeg2rad/benchmark/benchmark.native.js index b7935cfc6084..c4ff45d4a358 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskdeg2rad/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskdeg2rad/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskdeg2rad/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/smskdeg2rad/benchmark/benchmark.ndarray.js index ef26b2a9979b..d913a675f3e1 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskdeg2rad/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskdeg2rad/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskdeg2rad = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskdeg2rad/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/smskdeg2rad/benchmark/benchmark.ndarray.native.js index 0baabb9d2c8b..f55f6b8e0370 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskdeg2rad/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskdeg2rad/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskfloor/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/smskfloor/benchmark/benchmark.js index 4179148ba7e0..18c7a514c464 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskfloor/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskfloor/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskfloor = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskfloor/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/smskfloor/benchmark/benchmark.native.js index 6aad5b4743c4..715fc04af9a2 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskfloor/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskfloor/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskfloor/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/smskfloor/benchmark/benchmark.ndarray.js index 5bfbc9f75d4a..4cd4a951b06d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskfloor/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskfloor/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskfloor = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskfloor/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/smskfloor/benchmark/benchmark.ndarray.native.js index 7e6133b4c505..be2ea2001e7d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskfloor/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskfloor/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskinv/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/smskinv/benchmark/benchmark.js index 96479f289a3b..61344963e595 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskinv/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskinv/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskinv = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskinv/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/smskinv/benchmark/benchmark.native.js index 0506074988e3..8dac7a639333 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskinv/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskinv/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskinv/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/smskinv/benchmark/benchmark.ndarray.js index e6e86785d423..db6eabae2413 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskinv/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskinv/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskinv = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskinv/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/smskinv/benchmark/benchmark.ndarray.native.js index 8f20f3233a16..f4156ad1c79a 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskinv/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskinv/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskramp/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/smskramp/benchmark/benchmark.js index 5b78e78b48eb..6860396602d8 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskramp/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskramp/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskramp = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskramp/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/smskramp/benchmark/benchmark.native.js index a402b99f8383..de70a822bcbf 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskramp/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskramp/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskramp/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/smskramp/benchmark/benchmark.ndarray.js index 092793cb63d8..20d45e657c6c 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskramp/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskramp/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskramp = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskramp/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/smskramp/benchmark/benchmark.ndarray.native.js index b6f82e47e8b9..a93643c4bc7e 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskramp/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskramp/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskrsqrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/smskrsqrt/benchmark/benchmark.js index 46133b66a189..b5a46c72ef25 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskrsqrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskrsqrt/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskrsqrt = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskrsqrt/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/smskrsqrt/benchmark/benchmark.native.js index 7c67462696f1..93ff9b007818 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskrsqrt/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskrsqrt/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskrsqrt/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/smskrsqrt/benchmark/benchmark.ndarray.js index b6b303986047..8412bdd0a592 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskrsqrt/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskrsqrt/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskrsqrt = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smskrsqrt/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/smskrsqrt/benchmark/benchmark.ndarray.native.js index 5f691db88c2a..97db74c92b0a 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smskrsqrt/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smskrsqrt/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smsksqrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/smsksqrt/benchmark/benchmark.js index a8b68002daa2..14c12403366c 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smsksqrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/smsksqrt/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smsksqrt = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smsksqrt/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/smsksqrt/benchmark/benchmark.native.js index 0de156ebde4f..fbf9e71f274e 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smsksqrt/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smsksqrt/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smsksqrt/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/smsksqrt/benchmark/benchmark.ndarray.js index bd12ac4956cf..c9046481a19d 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smsksqrt/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/smsksqrt/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smsksqrt = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smsksqrt/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/smsksqrt/benchmark/benchmark.ndarray.native.js index 146a3f6cd67a..d4960e66f642 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smsksqrt/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smsksqrt/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smsktrunc/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/smsktrunc/benchmark/benchmark.js index d554a5edbb64..901f96c04359 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smsktrunc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/smsktrunc/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smsktrunc = require( './../lib/main.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smsktrunc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/smsktrunc/benchmark/benchmark.native.js index 6ca2f397cde5..b969a376346f 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smsktrunc/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smsktrunc/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smsktrunc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/smsktrunc/benchmark/benchmark.ndarray.js index b6cf4ceb156a..15474d495fca 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smsktrunc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/smsktrunc/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smsktrunc = require( './../lib/ndarray.js' ); @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/smsktrunc/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/smsktrunc/benchmark/benchmark.ndarray.native.js index b470f364a85e..32d24e84aa52 100644 --- a/lib/node_modules/@stdlib/math/strided/special/smsktrunc/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/smsktrunc/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sqrt-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/sqrt-by/benchmark/benchmark.js index c75cd16bf0bc..2b576c8a6e09 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sqrt-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/sqrt-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sqrtBy = require( './../lib/main.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sqrt-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/sqrt-by/benchmark/benchmark.ndarray.js index 9930794d729e..4950fcc7db37 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sqrt-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/sqrt-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sqrtBy = require( './../lib/ndarray.js' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sqrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/sqrt/benchmark/benchmark.js index df8f45b0f86a..9f575421cad8 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sqrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/sqrt/benchmark/benchmark.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sqrt/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/sqrt/benchmark/benchmark.native.js index d52b8d9b0b13..88a756fc742f 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sqrt/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/sqrt/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sqrt/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/sqrt/benchmark/benchmark.ndarray.js index a069487f1ce4..927a252bec43 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sqrt/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/sqrt/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':ndarray:len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sqrt/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/sqrt/benchmark/benchmark.ndarray.native.js index 34dfda5d17dd..58a7cab20a10 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sqrt/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/sqrt/benchmark/benchmark.ndarray.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:ndarray:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sramp/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/sramp/benchmark/benchmark.js index 8c13122a3513..04e11cba89e6 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sramp/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/sramp/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sramp = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sramp/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/sramp/benchmark/benchmark.native.js index 033a85b9466c..46e81442eb42 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sramp/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/sramp/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sramp/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/sramp/benchmark/benchmark.ndarray.js index e8adb2f1db62..6155786e8b58 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sramp/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/sramp/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sramp = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/sramp/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/sramp/benchmark/benchmark.ndarray.native.js index 63ac572e1c29..06b7e6414e96 100644 --- a/lib/node_modules/@stdlib/math/strided/special/sramp/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/sramp/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/srsqrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/srsqrt/benchmark/benchmark.js index c4d28c05cc34..b206a51644c0 100644 --- a/lib/node_modules/@stdlib/math/strided/special/srsqrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/srsqrt/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var srsqrt = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/srsqrt/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/srsqrt/benchmark/benchmark.native.js index 4519b51cd361..42fddcfee0da 100644 --- a/lib/node_modules/@stdlib/math/strided/special/srsqrt/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/srsqrt/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/srsqrt/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/srsqrt/benchmark/benchmark.ndarray.js index 483ec75914fb..7a828bead114 100644 --- a/lib/node_modules/@stdlib/math/strided/special/srsqrt/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/srsqrt/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var srsqrt = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/srsqrt/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/srsqrt/benchmark/benchmark.ndarray.native.js index 3cddb7d4007b..226c188d70be 100644 --- a/lib/node_modules/@stdlib/math/strided/special/srsqrt/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/srsqrt/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ssqrt/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/ssqrt/benchmark/benchmark.js index a06e63696c04..461f62dc8419 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ssqrt/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/ssqrt/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ssqrt = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ssqrt/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/ssqrt/benchmark/benchmark.native.js index f97ea26559b4..2f81d38175db 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ssqrt/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/ssqrt/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ssqrt/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/ssqrt/benchmark/benchmark.ndarray.js index 37ae349c64c3..66677bda67e0 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ssqrt/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/ssqrt/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ssqrt = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/ssqrt/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/ssqrt/benchmark/benchmark.ndarray.native.js index fb0d25f0b817..27e765678e69 100644 --- a/lib/node_modules/@stdlib/math/strided/special/ssqrt/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/ssqrt/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/strunc/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/strunc/benchmark/benchmark.js index 6acd5c0a6b63..b76556e3aa6b 100644 --- a/lib/node_modules/@stdlib/math/strided/special/strunc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/strunc/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var strunc = require( './../lib/main.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/strunc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/strunc/benchmark/benchmark.native.js index 13853cb277eb..215dd494a503 100644 --- a/lib/node_modules/@stdlib/math/strided/special/strunc/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/strunc/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/strunc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/strunc/benchmark/benchmark.ndarray.js index dc2993b98dac..1124830367c5 100644 --- a/lib/node_modules/@stdlib/math/strided/special/strunc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/strunc/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/base/uniform' ).factory; var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var strunc = require( './../lib/ndarray.js' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/strunc/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/strunc/benchmark/benchmark.ndarray.native.js index 2603de5dc12e..5e0ddabc01a1 100644 --- a/lib/node_modules/@stdlib/math/strided/special/strunc/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/strunc/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/math/strided/special/trunc/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/strided/special/trunc/benchmark/benchmark.js index a99024d3ce9b..90af7fc5a046 100644 --- a/lib/node_modules/@stdlib/math/strided/special/trunc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/strided/special/trunc/benchmark/benchmark.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/main.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/trunc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/strided/special/trunc/benchmark/benchmark.native.js index a8a2e4792ee0..8d88c7070e24 100644 --- a/lib/node_modules/@stdlib/math/strided/special/trunc/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/trunc/benchmark/benchmark.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/trunc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/math/strided/special/trunc/benchmark/benchmark.ndarray.js index 5e0d38e2102f..04414ac7a789 100644 --- a/lib/node_modules/@stdlib/math/strided/special/trunc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/math/strided/special/trunc/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); var strided = require( './../lib/ndarray.js' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+':ndarray:len='+len+',xtype='+t1+',ytype='+t2, f ); + bench( format( '%s:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), f ); } } } diff --git a/lib/node_modules/@stdlib/math/strided/special/trunc/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/math/strided/special/trunc/benchmark/benchmark.ndarray.native.js index 48f6d3237038..eae74d0d7c36 100644 --- a/lib/node_modules/@stdlib/math/strided/special/trunc/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/math/strided/special/trunc/benchmark/benchmark.ndarray.native.js @@ -29,6 +29,7 @@ var filledarray = require( '@stdlib/array/filled' ); var resolveEnum = require( '@stdlib/strided/base/dtype-resolve-enum' ); var enum2str = require( '@stdlib/strided/base/dtype-enum2str' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var types = require( './../lib/types.json' ); @@ -118,7 +119,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len, t1, t2 ); - bench( pkg+'::native:ndarray:len='+len+',xtype='+t1+',ytype='+t2, opts, f ); + bench( format( '%s::native:ndarray:len=%d,xtype=%s,ytype=%s', pkg, len, t1, t2 ), opts, f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/README.md b/lib/node_modules/@stdlib/ndarray/README.md index 96bfe83c61c5..11ff8acfc027 100644 --- a/lib/node_modules/@stdlib/ndarray/README.md +++ b/lib/node_modules/@stdlib/ndarray/README.md @@ -138,6 +138,7 @@ In addition, the namespace contains the following multidimensional array utility - [`promotionRules( [dtype1, dtype2] )`][@stdlib/ndarray/promotion-rules]: return the ndarray data type with the smallest size and closest "kind" to which ndarray data types can be **safely** cast. - [`push( x, ...values )`][@stdlib/ndarray/push]: return a one-dimensional ndarray formed by appending provided scalar values to a one-dimensional input ndarray. - [`reject( x[, options], predicate[, thisArg] )`][@stdlib/ndarray/reject]: return a shallow copy of an ndarray containing only those elements which fail a test implemented by a predicate function. +- [`removeSingletonDimensions( x )`][@stdlib/ndarray/remove-singleton-dimensions]: return a read-only view of an input ndarray with singleton dimensions removed. - [`reverseDimension( x, dim )`][@stdlib/ndarray/reverse-dimension]: return a **read-only** view of an input `ndarray` in which the order of elements along a specified dimension is reversed. - [`reverse( x )`][@stdlib/ndarray/reverse]: return a **read-only** view of an input `ndarray` in which the order of elements along each dimension is reversed. - [`safeCasts( [dtype] )`][@stdlib/ndarray/safe-casts]: return a list of ndarray data types to which a provided ndarray data type can be safely cast. @@ -347,6 +348,8 @@ console.log( objectKeys( ns ) ); [@stdlib/ndarray/reject]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/reject +[@stdlib/ndarray/remove-singleton-dimensions]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/remove-singleton-dimensions + [@stdlib/ndarray/reverse-dimension]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/reverse-dimension [@stdlib/ndarray/reverse]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/reverse diff --git a/lib/node_modules/@stdlib/ndarray/base/README.md b/lib/node_modules/@stdlib/ndarray/base/README.md index e398ba2835f8..0e13af3e8de3 100644 --- a/lib/node_modules/@stdlib/ndarray/base/README.md +++ b/lib/node_modules/@stdlib/ndarray/base/README.md @@ -111,6 +111,7 @@ var o = ns; - [`array2ndarray( buf, order )`][@stdlib/ndarray/base/from-array]: convert an array to a one-dimensional ndarray. - [`scalar2ndarrayLike( x, value )`][@stdlib/ndarray/base/from-scalar-like]: convert a scalar value to a zero-dimensional ndarray having the same data type as a provided ndarray. - [`scalar2ndarray( value, dtype, order )`][@stdlib/ndarray/base/from-scalar]: convert a scalar value to a zero-dimensional ndarray. +- [`fullBy( dtype, shape, order, clbk[, thisArg] )`][@stdlib/ndarray/base/full-by]: create an ndarray filled according to a callback function and having a specified shape and data type. - [`full( value, dtype, shape, order )`][@stdlib/ndarray/base/full]: create an ndarray filled with a specified value and having a specified shape and data type. - [`includes( arrays )`][@stdlib/ndarray/base/includes]: test whether an ndarray contains a specified value. - [`ind( idx, max, mode )`][@stdlib/ndarray/base/ind]: return an index given an index mode. @@ -164,6 +165,7 @@ var o = ns; - [`removeSingletonDimensions( x, writable )`][@stdlib/ndarray/base/remove-singleton-dimensions]: remove singleton dimensions. - [`reverseDimension( x, dim, writable )`][@stdlib/ndarray/base/reverse-dimension]: return a view of an input ndarray in which the order of elements along a specified dimension is reversed. - [`reverse( x, writable )`][@stdlib/ndarray/base/reverse]: return a view of an input ndarray in which the order of elements along each dimension is reversed. +- [`rotr90( x, k, writable )`][@stdlib/ndarray/base/rotr90]: rotate a matrix (or a stack of matrices) 90 degrees clockwise. - [`serializeMetaData( x )`][@stdlib/ndarray/base/serialize-meta-data]: serialize ndarray meta data. - [`shape( x, copy )`][@stdlib/ndarray/base/shape]: return the shape of a provided ndarray. - [`shape2strides( shape, order )`][@stdlib/ndarray/base/shape2strides]: generate a stride array from an array shape. @@ -219,6 +221,7 @@ var o = ns; - [`unaryBlockSize( dtypeX, dtypeY )`][@stdlib/ndarray/base/unary-tiling-block-size]: resolve a loop block size for multi-dimensional array tiled loops. - [`unary( arrays, fcn )`][@stdlib/ndarray/base/unary]: apply a unary callback to elements in an input ndarray and assign results to elements in an output ndarray. - [`unflattenShape( shape, dim, sizes )`][@stdlib/ndarray/base/unflatten-shape]: expand a dimension over multiple dimensions. +- [`unflatten( x, dim, sizes, writable )`][@stdlib/ndarray/base/unflatten]: return a view of an input ndarray in which a specified dimension is expanded over multiple dimensions. - [`vind2bind( shape, strides, offset, order, idx, mode )`][@stdlib/ndarray/base/vind2bind]: convert a linear index in an array view to a linear index in an underlying data buffer. - [`wrapIndex( idx, max )`][@stdlib/ndarray/base/wrap-index]: wrap an index on the interval `[0,max]`. - [`zerosLike( x )`][@stdlib/ndarray/base/zeros-like]: create a zero-filled ndarray having the same shape and data type as a provided ndarray. @@ -416,6 +419,8 @@ console.log( objectKeys( ns ) ); [@stdlib/ndarray/base/from-scalar]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/from-scalar +[@stdlib/ndarray/base/full-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/full-by + [@stdlib/ndarray/base/full]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/full [@stdlib/ndarray/base/includes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/includes @@ -522,6 +527,8 @@ console.log( objectKeys( ns ) ); [@stdlib/ndarray/base/reverse]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/reverse +[@stdlib/ndarray/base/rotr90]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/rotr90 + [@stdlib/ndarray/base/serialize-meta-data]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/serialize-meta-data [@stdlib/ndarray/base/shape]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/shape @@ -632,6 +639,8 @@ console.log( objectKeys( ns ) ); [@stdlib/ndarray/base/unflatten-shape]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unflatten-shape +[@stdlib/ndarray/base/unflatten]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unflatten + [@stdlib/ndarray/base/vind2bind]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/vind2bind [@stdlib/ndarray/base/wrap-index]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/wrap-index diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.10d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.10d_blocked_columnmajor.js index 8be1711b4b0c..17c919db03ff 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.10d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.10d_blocked_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/10d_blocked.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/10.0 ) ); sh = [ len, len, len, len, len, len, len, len, len, len ]; len *= pow( len, 9 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.10d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.10d_blocked_rowmajor.js index 1a937a766b31..cd3a7217ec3e 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.10d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.10d_blocked_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/10d_blocked.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/10.0 ) ); sh = [ len, len, len, len, len, len, len, len, len, len ]; len *= pow( len, 9 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.10d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.10d_columnmajor.js index 3049ccd5d455..8c2617f541ab 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.10d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.10d_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/10d.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/10.0 ) ); sh = [ len, len, len, len, len, len, len, len, len, len ]; len *= pow( len, 9 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.10d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.10d_rowmajor.js index 390480358153..a69324b0ec4b 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.10d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.10d_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/10d.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/10.0 ) ); sh = [ len, len, len, len, len, len, len, len, len, len ]; len *= pow( len, 9 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.11d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.11d_columnmajor.js index 299180b49b3e..a4f6fbdd0486 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.11d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.11d_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/nd.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/11.0 ) ); sh = [ len, len, len, len, len, len, len, len, len, len, len ]; len *= pow( len, 10 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.11d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.11d_rowmajor.js index 5b9a1535107c..6701dec60211 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.11d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.11d_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/nd.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/11.0 ) ); sh = [ len, len, len, len, len, len, len, len, len, len, len ]; len *= pow( len, 10 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.1d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.1d_columnmajor.js index e906de1eded6..116618e27877 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.1d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.1d_columnmajor.js @@ -25,6 +25,7 @@ var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; var pow = require( '@stdlib/math/base/special/pow' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib' ); @@ -124,7 +125,7 @@ function main() { sh = [ len ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.1d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.1d_rowmajor.js index 0f7b498e503a..c64d4b8f6b49 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.1d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.1d_rowmajor.js @@ -25,6 +25,7 @@ var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; var pow = require( '@stdlib/math/base/special/pow' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib' ); @@ -124,7 +125,7 @@ function main() { sh = [ len ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_blocked_columnmajor.js index b732297243d4..6bcb467ce8a1 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_blocked_columnmajor.js @@ -27,6 +27,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/2d_blocked.js' ); @@ -126,17 +127,17 @@ function main() { sh = [ len/2, 2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( sqrt( len ) ); sh = [ len, len ]; len *= len; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_blocked_rowmajor.js index 6fe3443a0aca..026037377a13 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_blocked_rowmajor.js @@ -27,6 +27,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/2d_blocked.js' ); @@ -126,17 +127,17 @@ function main() { sh = [ len/2, 2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( sqrt( len ) ); sh = [ len, len ]; len *= len; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_columnmajor.js index f6bd61f79b17..99cc553a5631 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_columnmajor.js @@ -27,6 +27,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/2d.js' ); @@ -126,17 +127,17 @@ function main() { sh = [ len/2, 2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( sqrt( len ) ); sh = [ len, len ]; len *= len; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_rowmajor.js index ebaf2dcc8fcb..24236aab9b18 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_rowmajor.js @@ -27,6 +27,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/2d.js' ); @@ -126,17 +127,17 @@ function main() { sh = [ len/2, 2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( sqrt( len ) ); sh = [ len, len ]; len *= len; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_rowmajor_accessors.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_rowmajor_accessors.js index 3e048782170f..6dfd47a613d7 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_rowmajor_accessors.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.2d_rowmajor_accessors.js @@ -27,6 +27,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/2d_accessors.js' ); @@ -152,17 +153,17 @@ function main() { sh = [ len/2, 2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::accessors:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::accessors:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::accessors:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::accessors:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( sqrt( len ) ); sh = [ len, len ]; len *= len; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::accessors:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::accessors:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.3d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.3d_blocked_columnmajor.js index b2de411a2d5f..dd47a4350c13 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.3d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.3d_blocked_columnmajor.js @@ -27,6 +27,7 @@ var cbrt = require( '@stdlib/math/base/special/cbrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/3d_blocked.js' ); @@ -126,17 +127,17 @@ function main() { sh = [ len/2, 2, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( cbrt( len ) ); sh = [ len, len, len ]; len *= len * len; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.3d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.3d_blocked_rowmajor.js index 24e484d37256..15bad342d54a 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.3d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.3d_blocked_rowmajor.js @@ -27,6 +27,7 @@ var cbrt = require( '@stdlib/math/base/special/cbrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/3d_blocked.js' ); @@ -126,17 +127,17 @@ function main() { sh = [ len/2, 2, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( cbrt( len ) ); sh = [ len, len, len ]; len *= len * len; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.3d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.3d_columnmajor.js index 31e3bb3edae0..74391627f1a5 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.3d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.3d_columnmajor.js @@ -27,6 +27,7 @@ var cbrt = require( '@stdlib/math/base/special/cbrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/3d.js' ); @@ -126,17 +127,17 @@ function main() { sh = [ len/2, 2, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( cbrt( len ) ); sh = [ len, len, len ]; len *= len * len; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.3d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.3d_rowmajor.js index cbc3c2d7ad91..7c76f0f9f94c 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.3d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.3d_rowmajor.js @@ -27,6 +27,7 @@ var cbrt = require( '@stdlib/math/base/special/cbrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/3d.js' ); @@ -126,17 +127,17 @@ function main() { sh = [ len/2, 2, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( cbrt( len ) ); sh = [ len, len, len ]; len *= len * len; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.4d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.4d_blocked_columnmajor.js index 93454fc60741..29eab0c1185f 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.4d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.4d_blocked_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/4d_blocked.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/4.0 ) ); sh = [ len, len, len, len ]; len *= len * len * len; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.4d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.4d_blocked_rowmajor.js index 07b8dd4c22a4..6911aebd2aca 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.4d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.4d_blocked_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/4d_blocked.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/4.0 ) ); sh = [ len, len, len, len ]; len *= len * len * len; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.4d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.4d_columnmajor.js index 631cd65e9408..4c7f369e7d88 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.4d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.4d_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/4d.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/4.0 ) ); sh = [ len, len, len, len ]; len *= len * len * len; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.4d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.4d_rowmajor.js index f4fc67689f83..02e62fb8c2ed 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.4d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.4d_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/4d.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/4.0 ) ); sh = [ len, len, len, len ]; len *= len * len * len; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.5d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.5d_blocked_columnmajor.js index d372944806aa..d68ef394e129 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.5d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.5d_blocked_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/5d_blocked.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/5.0 ) ); sh = [ len, len, len, len, len ]; len *= pow( len, 4 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.5d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.5d_blocked_rowmajor.js index 7610f3ca1adf..25467c5b72ff 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.5d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.5d_blocked_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/5d_blocked.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/5.0 ) ); sh = [ len, len, len, len, len ]; len *= pow( len, 4 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.5d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.5d_columnmajor.js index 39f3d620e4d1..58750b65a478 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.5d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.5d_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/5d.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/5.0 ) ); sh = [ len, len, len, len, len ]; len *= pow( len, 4 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.5d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.5d_rowmajor.js index 95ab2baa080a..8d23fc48a866 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.5d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.5d_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/5d.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/5.0 ) ); sh = [ len, len, len, len, len ]; len *= pow( len, 4 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.6d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.6d_blocked_columnmajor.js index 3d22c15eb582..3a3bebe9c8a0 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.6d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.6d_blocked_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/6d_blocked.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/6.0 ) ); sh = [ len, len, len, len, len, len ]; len *= pow( len, 5 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.6d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.6d_blocked_rowmajor.js index b96745afe87b..173f3c57efdf 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.6d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.6d_blocked_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/6d_blocked.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/6.0 ) ); sh = [ len, len, len, len, len, len ]; len *= pow( len, 5 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.6d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.6d_columnmajor.js index c5f9f47efa2e..27f49e0bf527 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.6d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.6d_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/6d.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/6.0 ) ); sh = [ len, len, len, len, len, len ]; len *= pow( len, 5 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.6d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.6d_rowmajor.js index e7c9121993ef..13d3c7b338bc 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.6d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.6d_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/6d.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/6.0 ) ); sh = [ len, len, len, len, len, len ]; len *= pow( len, 5 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.7d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.7d_blocked_columnmajor.js index 8053363170bd..755e7a53735f 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.7d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.7d_blocked_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/7d_blocked.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/7.0 ) ); sh = [ len, len, len, len, len, len, len ]; len *= pow( len, 6 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.7d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.7d_blocked_rowmajor.js index cf21ae14068d..395b528378f0 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.7d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.7d_blocked_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/7d_blocked.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/7.0 ) ); sh = [ len, len, len, len, len, len, len ]; len *= pow( len, 6 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.7d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.7d_columnmajor.js index 9347636441c9..a284872f242f 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.7d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.7d_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/7d.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/7.0 ) ); sh = [ len, len, len, len, len, len, len ]; len *= pow( len, 6 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.7d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.7d_rowmajor.js index bfe7ca9d008d..0a3b274596cc 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.7d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.7d_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/7d.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/7.0 ) ); sh = [ len, len, len, len, len, len, len ]; len *= pow( len, 6 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.8d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.8d_blocked_columnmajor.js index beace1cf14e9..5d0787d67737 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.8d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.8d_blocked_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/8d_blocked.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/8.0 ) ); sh = [ len, len, len, len, len, len, len, len ]; len *= pow( len, 7 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.8d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.8d_blocked_rowmajor.js index beace1cf14e9..5d0787d67737 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.8d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.8d_blocked_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/8d_blocked.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/8.0 ) ); sh = [ len, len, len, len, len, len, len, len ]; len *= pow( len, 7 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.8d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.8d_columnmajor.js index 0f931cfcbd64..ec026216bc6c 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.8d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.8d_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/8d.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/8.0 ) ); sh = [ len, len, len, len, len, len, len, len ]; len *= pow( len, 7 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.8d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.8d_rowmajor.js index 50a459a4073f..95497e514b04 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.8d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.8d_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/8d.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/8.0 ) ); sh = [ len, len, len, len, len, len, len, len ]; len *= pow( len, 7 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.9d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.9d_blocked_columnmajor.js index dba659a273cc..4e4a8e27c682 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.9d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.9d_blocked_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/9d_blocked.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/9.0 ) ); sh = [ len, len, len, len, len, len, len, len, len ]; len *= pow( len, 8 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.9d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.9d_blocked_rowmajor.js index 2bbd5355b5f8..d1e28dfdb27f 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.9d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.9d_blocked_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/9d_blocked.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/9.0 ) ); sh = [ len, len, len, len, len, len, len, len, len ]; len *= pow( len, 8 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.9d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.9d_columnmajor.js index 583166eb6e8b..b908592f4726 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.9d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.9d_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/9d.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/9.0 ) ); sh = [ len, len, len, len, len, len, len, len, len ]; len *= pow( len, 8 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.9d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.9d_rowmajor.js index 14639131aef2..1ea85141319b 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.9d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any-by/benchmark/benchmark.9d_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var anyBy = require( './../lib/9d.js' ); @@ -125,17 +126,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/9.0 ) ); sh = [ len, len, len, len, len, len, len, len, len ]; len *= pow( len, 8 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.10d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.10d_blocked_columnmajor.js index 6520dcb48c0f..f3d3a9edad74 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.10d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.10d_blocked_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/10d_blocked.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/10.0 ) ); sh = [ len, len, len, len, len, len, len, len, len, len ]; len *= pow( len, 9 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.10d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.10d_blocked_rowmajor.js index ea88c991d53e..3db006037819 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.10d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.10d_blocked_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/10d_blocked.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/10.0 ) ); sh = [ len, len, len, len, len, len, len, len, len, len ]; len *= pow( len, 9 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.10d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.10d_columnmajor.js index a594439008bb..498cef106506 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.10d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.10d_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/10d.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/10.0 ) ); sh = [ len, len, len, len, len, len, len, len, len, len ]; len *= pow( len, 9 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.10d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.10d_rowmajor.js index ef2cb5bc9edc..3c5f62f3febd 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.10d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.10d_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/10d.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/10.0 ) ); sh = [ len, len, len, len, len, len, len, len, len, len ]; len *= pow( len, 9 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.11d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.11d_columnmajor.js index 620023535c54..169c01c8bc95 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.11d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.11d_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/nd.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/11.0 ) ); sh = [ len, len, len, len, len, len, len, len, len, len, len ]; len *= pow( len, 10 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.11d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.11d_rowmajor.js index e53ee2e9e9a2..34ac8052e786 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.11d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.11d_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/nd.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/11.0 ) ); sh = [ len, len, len, len, len, len, len, len, len, len, len ]; len *= pow( len, 10 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.1d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.1d_columnmajor.js index 8925eb6d2253..2c5e34aacb9a 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.1d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.1d_columnmajor.js @@ -25,6 +25,7 @@ var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib' ); @@ -114,7 +115,7 @@ function main() { sh = [ len ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.1d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.1d_rowmajor.js index 3a7c457abde4..bbb8ef44ef37 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.1d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.1d_rowmajor.js @@ -25,6 +25,7 @@ var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib' ); @@ -114,7 +115,7 @@ function main() { sh = [ len ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_blocked_columnmajor.js index 8004a0db3986..a0e122c2fdf8 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_blocked_columnmajor.js @@ -27,6 +27,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/2d_blocked.js' ); @@ -116,17 +117,17 @@ function main() { sh = [ len/2, 2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( sqrt( len ) ); sh = [ len, len ]; len *= len; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_blocked_rowmajor.js index a9d6bc45fb49..a247d90dc4b4 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_blocked_rowmajor.js @@ -27,6 +27,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/2d_blocked.js' ); @@ -116,17 +117,17 @@ function main() { sh = [ len/2, 2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( sqrt( len ) ); sh = [ len, len ]; len *= len; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_columnmajor.js index cb5032322d81..ebb81046407b 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_columnmajor.js @@ -27,6 +27,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/2d.js' ); @@ -116,17 +117,17 @@ function main() { sh = [ len/2, 2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( sqrt( len ) ); sh = [ len, len ]; len *= len; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_rowmajor.js index 9601b5214d45..5d49d5f6ca1e 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_rowmajor.js @@ -27,6 +27,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/2d.js' ); @@ -116,17 +117,17 @@ function main() { sh = [ len/2, 2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( sqrt( len ) ); sh = [ len, len ]; len *= len; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_rowmajor_accessors.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_rowmajor_accessors.js index 927aae280493..ad478c46728e 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_rowmajor_accessors.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_rowmajor_accessors.js @@ -27,6 +27,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/2d_accessors.js' ); @@ -142,17 +143,17 @@ function main() { sh = [ len/2, 2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::accessors:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::accessors:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::accessors:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::accessors:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( sqrt( len ) ); sh = [ len, len ]; len *= len; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::accessors:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::accessors:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_rowmajor_accessors_complex.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_rowmajor_accessors_complex.js index f0530c3428d6..e728d9d3082f 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_rowmajor_accessors_complex.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.2d_rowmajor_accessors_complex.js @@ -28,6 +28,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var ctors = require( '@stdlib/array/typed-complex-ctors' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/2d_accessors.js' ); @@ -144,17 +145,17 @@ function main() { sh = [ len/2, 2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::accessors:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::accessors:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::accessors:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::accessors:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( sqrt( len ) ); sh = [ len, len ]; len *= len; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::accessors:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::accessors:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.3d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.3d_blocked_columnmajor.js index d754df7cca6f..19c250daa83d 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.3d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.3d_blocked_columnmajor.js @@ -27,6 +27,7 @@ var cbrt = require( '@stdlib/math/base/special/cbrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/3d_blocked.js' ); @@ -116,17 +117,17 @@ function main() { sh = [ len/2, 2, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( cbrt( len ) ); sh = [ len, len, len ]; len *= len * len; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.3d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.3d_blocked_rowmajor.js index e810430eca5d..b6b1e33340bd 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.3d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.3d_blocked_rowmajor.js @@ -27,6 +27,7 @@ var cbrt = require( '@stdlib/math/base/special/cbrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/3d_blocked.js' ); @@ -116,17 +117,17 @@ function main() { sh = [ len/2, 2, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( cbrt( len ) ); sh = [ len, len, len ]; len *= len * len; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.3d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.3d_columnmajor.js index fc3128bfe838..a5e26b8f17b4 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.3d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.3d_columnmajor.js @@ -27,6 +27,7 @@ var cbrt = require( '@stdlib/math/base/special/cbrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/3d.js' ); @@ -116,17 +117,17 @@ function main() { sh = [ len/2, 2, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( cbrt( len ) ); sh = [ len, len, len ]; len *= len * len; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.3d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.3d_rowmajor.js index 84a86c6a4566..3d27c82962c5 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.3d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.3d_rowmajor.js @@ -27,6 +27,7 @@ var cbrt = require( '@stdlib/math/base/special/cbrt' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/3d.js' ); @@ -116,17 +117,17 @@ function main() { sh = [ len/2, 2, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( cbrt( len ) ); sh = [ len, len, len ]; len *= len * len; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.4d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.4d_blocked_columnmajor.js index 9f7eb247a0e0..26f884ba55aa 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.4d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.4d_blocked_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/4d_blocked.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/4.0 ) ); sh = [ len, len, len, len ]; len *= len * len * len; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.4d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.4d_blocked_rowmajor.js index 770547927e81..05f936824d8c 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.4d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.4d_blocked_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/4d_blocked.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/4.0 ) ); sh = [ len, len, len, len ]; len *= len * len * len; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.4d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.4d_columnmajor.js index d160d660ee37..33df7af68019 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.4d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.4d_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/4d.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/4.0 ) ); sh = [ len, len, len, len ]; len *= len * len * len; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.4d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.4d_rowmajor.js index fe7557081acc..6145de72ff55 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.4d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.4d_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/4d.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/4.0 ) ); sh = [ len, len, len, len ]; len *= len * len * len; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.5d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.5d_blocked_columnmajor.js index e31a10c16126..62f1a293a7d3 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.5d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.5d_blocked_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/5d_blocked.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/5.0 ) ); sh = [ len, len, len, len, len ]; len *= pow( len, 4 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.5d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.5d_blocked_rowmajor.js index b159dcb0af68..5f8c7a0e1f25 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.5d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.5d_blocked_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/5d_blocked.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/5.0 ) ); sh = [ len, len, len, len, len ]; len *= pow( len, 4 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.5d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.5d_columnmajor.js index 3aeed7e6e5dd..469bd9c3f12c 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.5d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.5d_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/5d.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/5.0 ) ); sh = [ len, len, len, len, len ]; len *= pow( len, 4 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.5d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.5d_rowmajor.js index 5804b071bd8a..843017d28b90 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.5d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.5d_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/5d.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/5.0 ) ); sh = [ len, len, len, len, len ]; len *= pow( len, 4 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.6d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.6d_blocked_columnmajor.js index 826f82337fb4..b067d30f7fef 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.6d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.6d_blocked_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/6d_blocked.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/6.0 ) ); sh = [ len, len, len, len, len, len ]; len *= pow( len, 5 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.6d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.6d_blocked_rowmajor.js index 26b207901d63..abe120763d6d 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.6d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.6d_blocked_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/6d_blocked.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/6.0 ) ); sh = [ len, len, len, len, len, len ]; len *= pow( len, 5 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.6d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.6d_columnmajor.js index 121a9333dd16..9d335e44993e 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.6d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.6d_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/6d.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/6.0 ) ); sh = [ len, len, len, len, len, len ]; len *= pow( len, 5 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.6d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.6d_rowmajor.js index a0277e206a85..7571d02fc752 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.6d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.6d_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/6d.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/6.0 ) ); sh = [ len, len, len, len, len, len ]; len *= pow( len, 5 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.7d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.7d_blocked_columnmajor.js index b1486a65f8eb..6506c316828e 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.7d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.7d_blocked_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/7d_blocked.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/7.0 ) ); sh = [ len, len, len, len, len, len, len ]; len *= pow( len, 6 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.7d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.7d_blocked_rowmajor.js index c1180e3daec2..1999b92b6b47 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.7d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.7d_blocked_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/7d_blocked.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/7.0 ) ); sh = [ len, len, len, len, len, len, len ]; len *= pow( len, 6 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.7d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.7d_columnmajor.js index 06b3070593cc..2be145f9b970 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.7d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.7d_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/7d.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/7.0 ) ); sh = [ len, len, len, len, len, len, len ]; len *= pow( len, 6 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.7d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.7d_rowmajor.js index 2b56850421c3..cdc97389a8bb 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.7d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.7d_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/7d.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/7.0 ) ); sh = [ len, len, len, len, len, len, len ]; len *= pow( len, 6 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.8d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.8d_blocked_columnmajor.js index b23cccbea3fa..f4e960c81a36 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.8d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.8d_blocked_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/8d_blocked.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/8.0 ) ); sh = [ len, len, len, len, len, len, len, len ]; len *= pow( len, 7 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.8d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.8d_blocked_rowmajor.js index b23cccbea3fa..f4e960c81a36 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.8d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.8d_blocked_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/8d_blocked.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/8.0 ) ); sh = [ len, len, len, len, len, len, len, len ]; len *= pow( len, 7 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.8d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.8d_columnmajor.js index ac41426b32c4..d93612367977 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.8d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.8d_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/8d.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/8.0 ) ); sh = [ len, len, len, len, len, len, len, len ]; len *= pow( len, 7 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.8d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.8d_rowmajor.js index 654790885ba9..bf8612d2fc88 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.8d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.8d_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/8d.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/8.0 ) ); sh = [ len, len, len, len, len, len, len, len ]; len *= pow( len, 7 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.9d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.9d_blocked_columnmajor.js index d2eb70a3a9ed..bf238ea5258b 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.9d_blocked_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.9d_blocked_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/9d_blocked.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/9.0 ) ); sh = [ len, len, len, len, len, len, len, len, len ]; len *= pow( len, 8 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.9d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.9d_blocked_rowmajor.js index d42c3c05c551..e62def4847b1 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.9d_blocked_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.9d_blocked_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/9d_blocked.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/9.0 ) ); sh = [ len, len, len, len, len, len, len, len, len ]; len *= pow( len, 8 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s::blocked:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.9d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.9d_columnmajor.js index b9021e497d81..a4ae6bb63023 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.9d_columnmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.9d_columnmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/9d.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/9.0 ) ); sh = [ len, len, len, len, len, len, len, len, len ]; len *= pow( len, 8 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.9d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.9d_rowmajor.js index ef7438fc8b14..cb95f2c29996 100644 --- a/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.9d_rowmajor.js +++ b/lib/node_modules/@stdlib/ndarray/base/any/benchmark/benchmark.9d_rowmajor.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var zeros = require( '@stdlib/array/zeros' ); var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var any = require( './../lib/9d.js' ); @@ -115,17 +116,17 @@ function main() { sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); sh = [ 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); len = floor( pow( len, 1.0/9.0 ) ); sh = [ len, len, len, len, len, len, len, len, len ]; len *= pow( len, 8 ); f = createBenchmark( len, sh, t1 ); - bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + bench( format( '%s:ndims=%d,len=%d,shape=[%s],xorder=%s,xtype=%s', pkg, sh.length, len, sh.join(','), order, t1 ), f ); } } } diff --git a/lib/node_modules/@stdlib/ndarray/base/count-falsy/README.md b/lib/node_modules/@stdlib/ndarray/base/count-falsy/README.md index 5d2cc147f6e2..6b2080661510 100644 --- a/lib/node_modules/@stdlib/ndarray/base/count-falsy/README.md +++ b/lib/node_modules/@stdlib/ndarray/base/count-falsy/README.md @@ -2198,7 +2198,7 @@ int main( void ) { struct ndarray *arrays[] = { x, y }; // Perform operation: - int8_t status = stdlib_ndarray_count_falsy_b_i( arrays ); + int8_t status = stdlib_ndarray_count_falsy_b_i( arrays, NULL ); if ( status != 0 ) { fprintf( stderr, "Error during computation.\n" ); exit( EXIT_FAILURE ); diff --git a/lib/node_modules/@stdlib/ndarray/base/count-truthy/README.md b/lib/node_modules/@stdlib/ndarray/base/count-truthy/README.md index 549f5fc9f091..e825171c1f2b 100644 --- a/lib/node_modules/@stdlib/ndarray/base/count-truthy/README.md +++ b/lib/node_modules/@stdlib/ndarray/base/count-truthy/README.md @@ -2198,7 +2198,7 @@ int main( void ) { struct ndarray *arrays[] = { x, y }; // Perform operation: - int8_t status = stdlib_ndarray_count_truthy_b_i( arrays ); + int8_t status = stdlib_ndarray_count_truthy_b_i( arrays, NULL ); if ( status != 0 ) { fprintf( stderr, "Error during computation.\n" ); exit( EXIT_FAILURE ); diff --git a/lib/node_modules/@stdlib/ndarray/base/expand-dimensions/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/expand-dimensions/lib/main.js index 1828ebb0a355..d78731410017 100644 --- a/lib/node_modules/@stdlib/ndarray/base/expand-dimensions/lib/main.js +++ b/lib/node_modules/@stdlib/ndarray/base/expand-dimensions/lib/main.js @@ -20,8 +20,9 @@ // MODULES // -var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major-string' ); +var isRowMajorString = require( '@stdlib/ndarray/base/assert/is-row-major-string' ); var normalizeIndex = require( '@stdlib/ndarray/base/normalize-index' ); +var strides2order = require( '@stdlib/ndarray/base/strides2order' ); var getDType = require( '@stdlib/ndarray/base/dtype' ); var getShape = require( '@stdlib/ndarray/base/shape' ); var getStrides = require( '@stdlib/ndarray/base/strides' ); @@ -63,6 +64,7 @@ function expandDimensions( x, dim, writable ) { var sh; var st; var d; + var o; var N; var i; @@ -70,7 +72,13 @@ function expandDimensions( x, dim, writable ) { st = getStrides( x, false ); ord = getOrder( x ); - isrm = isRowMajor( ord ); + o = strides2order( st ); + if ( o === 0 || o === 3 ) { + // Fallback to stated layout when unable to infer the underlying physical layout: + isrm = isRowMajorString( ord ); + } else { + isrm = ( o === 1 ); + } N = sh.length; strides = []; diff --git a/lib/node_modules/@stdlib/ndarray/base/expand-dimensions/test/test.js b/lib/node_modules/@stdlib/ndarray/base/expand-dimensions/test/test.js index bd891562536f..61b81b6ba284 100644 --- a/lib/node_modules/@stdlib/ndarray/base/expand-dimensions/test/test.js +++ b/lib/node_modules/@stdlib/ndarray/base/expand-dimensions/test/test.js @@ -64,7 +64,30 @@ tape( 'the function throws an error if provided an invalid second argument', fun } }); -tape( 'the function prepends singleton dimensions', function test( t ) { +tape( 'the function prepends singleton dimensions (1d)', function test( t ) { + var x; + var y; + + x = array( [ 1, 2, 3, 4 ] ); + + y = expandDimensions( x, 0, false ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 1, 4 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), true, 'returns expected value' ); + + y = expandDimensions( x, 0, true ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 1, 4 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function prepends singleton dimensions (2d)', function test( t ) { var x; var y; @@ -110,7 +133,30 @@ tape( 'the function prepends singleton dimensions (negative index)', function te t.end(); }); -tape( 'the function appends singleton dimensions', function test( t ) { +tape( 'the function appends singleton dimensions (1d)', function test( t ) { + var x; + var y; + + x = array( [ 1, 2, 3, 4 ] ); + + y = expandDimensions( x, ndims( x ), false ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), true, 'returns expected value' ); + + y = expandDimensions( x, ndims( x ), true ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function appends singleton dimensions (2d)', function test( t ) { var x; var y; @@ -214,6 +260,15 @@ tape( 'the function prepends singleton dimensions (base; row-major)', function t t.deepEqual( getStrides( y ), [ 4, 2, 1 ], 'returns expected value' ); t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + // Transposed: + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 1, 2 ], 0, 'row-major' ); + y = expandDimensions( x, 0, false ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 1, 2, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 1, 2 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.end(); }); @@ -244,6 +299,15 @@ tape( 'the function prepends singleton dimensions (base; column-major)', functio t.deepEqual( getStrides( y ), [ 1, 1, 2 ], 'returns expected value' ); t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + // Transposed: + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'column-major' ); + y = expandDimensions( x, 0, false ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 1, 2, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 4, 2, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.end(); }); @@ -274,6 +338,15 @@ tape( 'the function appends singleton dimensions (base; row-major)', function te t.deepEqual( getStrides( y ), [ 2, 1, 1 ], 'returns expected value' ); t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + // Transposed: + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 1, 2 ], 0, 'row-major' ); + y = expandDimensions( x, ndims( x ), false ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 2, 1 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 2, 4 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.end(); }); @@ -304,6 +377,15 @@ tape( 'the function appends singleton dimensions (base; column-major)', function t.deepEqual( getStrides( y ), [ 1, 2, 4 ], 'returns expected value' ); t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + // Transposed: + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'column-major' ); + y = expandDimensions( x, ndims( x ), false ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 2, 1 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 2, 1, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.end(); }); @@ -334,6 +416,15 @@ tape( 'the function inserts singleton dimensions (base; row-major)', function te t.deepEqual( getStrides( y ), [ 2, 2, 1 ], 'returns expected value' ); t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + // Transposed: + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 1, 2 ], 0, 'row-major' ); + y = expandDimensions( x, 1, false ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 1, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 2, 2 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.end(); }); @@ -364,6 +455,15 @@ tape( 'the function inserts singleton dimensions (base; column-major)', function t.deepEqual( getStrides( y ), [ 1, 2, 2 ], 'returns expected value' ); t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + // Transposed: + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'column-major' ); + y = expandDimensions( x, 1, false ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 1, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 2, 2, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.end(); }); diff --git a/lib/node_modules/@stdlib/ndarray/base/flatten-shape-from/README.md b/lib/node_modules/@stdlib/ndarray/base/flatten-shape-from/README.md index 9a91d06d458b..7fe1cc131e00 100644 --- a/lib/node_modules/@stdlib/ndarray/base/flatten-shape-from/README.md +++ b/lib/node_modules/@stdlib/ndarray/base/flatten-shape-from/README.md @@ -153,7 +153,7 @@ const int64_t ndims = 3; const int64_t shape[] = { 2, 3, 10 }; int64_t out[ 2 ]; -stdlib_ndarray_flatten_shape( ndims, shape, 1, out ); +stdlib_ndarray_flatten_shape_from( ndims, shape, 1, out ); ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/ndarray/base/fliplr/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/fliplr/docs/repl.txt index 77928526584c..5b675a594cab 100644 --- a/lib/node_modules/@stdlib/ndarray/base/fliplr/docs/repl.txt +++ b/lib/node_modules/@stdlib/ndarray/base/fliplr/docs/repl.txt @@ -32,7 +32,6 @@ > {{alias:@stdlib/ndarray/shape}}( y ) [ 2, 2 ] - See Also -------- diff --git a/lib/node_modules/@stdlib/ndarray/base/flipud/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/flipud/docs/repl.txt index d3e56fa6a231..59d90e178695 100644 --- a/lib/node_modules/@stdlib/ndarray/base/flipud/docs/repl.txt +++ b/lib/node_modules/@stdlib/ndarray/base/flipud/docs/repl.txt @@ -35,7 +35,6 @@ > {{alias:@stdlib/ndarray/shape}}( y ) [ 2, 2 ] - See Also -------- diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/README.md b/lib/node_modules/@stdlib/ndarray/base/full-by/README.md new file mode 100644 index 000000000000..6f95edd4d2c0 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/README.md @@ -0,0 +1,161 @@ + + +# fullBy + +> Create an [ndarray][@stdlib/ndarray/base/ctor] filled according to a callback function and having a specified shape and [data type][@stdlib/ndarray/dtypes]. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var fullBy = require( '@stdlib/ndarray/base/full-by' ); +``` + +#### fullBy( dtype, shape, order, clbk\[, thisArg] ) + +Returns an [ndarray][@stdlib/ndarray/base/ctor] filled according to a callback function and having a specified shape and [data type][@stdlib/ndarray/dtypes]. + +```javascript +var getDType = require( '@stdlib/ndarray/dtype' ); + +function clbk() { + return 10.0; +} + +var arr = fullBy( 'float64', [ 2, 2 ], 'row-major', clbk ); +// returns [ [ 10.0, 10.0 ], [ 10.0, 10.0 ] ] + +var dt = String( getDType( arr ) ); +// returns 'float64' +``` + +This function accepts the following arguments: + +- **dtype**: underlying [data type][@stdlib/ndarray/dtypes]. +- **shape**: array shape. +- **order**: specifies whether an [ndarray][@stdlib/ndarray/base/ctor] is `'row-major'` (C-style) or `'column-major'` (Fortran-style). +- **clbk**: callback function. +- **thisArg**: callback function execution context (_optional_). + +The callback function is provided the following arguments: + +- **indices**: current array element indices. + +To set the callback function execution context, provide a `thisArg`. + +```javascript +var getDType = require( '@stdlib/ndarray/dtype' ); + +function clbk( indices ) { + return this.value * ( indices[ 0 ] + indices[ 1 ] ); // eslint-disable-line no-invalid-this +} + +var ctx = { + 'value': 10.0 +}; + +var arr = fullBy( 'float64', [ 2, 2 ], 'row-major', clbk, ctx ); +// returns [ [ 0.0, 10.0 ], [ 10.0, 20.0 ] ] + +var dt = String( getDType( arr ) ); +// returns 'float64' +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dtypes = require( '@stdlib/ndarray/dtypes' ); +var fullBy = require( '@stdlib/ndarray/base/full-by' ); + +// Get a list of data types: +var dt = dtypes( 'integer_and_generic' ); + +// Generate filled arrays... +var arr; +var i; +for ( i = 0; i < dt.length; i++ ) { + arr = fullBy( dt[ i ], [ 2, 2 ], 'row-major', discreteUniform( -100, 100 ) ); + console.log( ndarray2array( arr ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/ndarray/base/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/ctor + +[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/dtypes + +
+ + diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.js new file mode 100644 index 000000000000..ef2f00396dbf --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.js @@ -0,0 +1,318 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var fullBy = require( './../lib' ); + + +// MAIN // + +bench( format( '%s:dtype=float64', pkg ), function benchmark( b ) { + var arr; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'float64', [ 0 ], 'row-major', clbk ); + if ( arr.length !== 0 ) { + b.fail( 'should have length 0' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function clbk() { + return 10.0; + } +}); + +bench( format( '%s:dtype=float32', pkg ), function benchmark( b ) { + var arr; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'float32', [ 0 ], 'row-major', clbk ); + if ( arr.length !== 0 ) { + b.fail( 'should have length 0' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function clbk() { + return 10.0; + } +}); + +bench( format( '%s:dtype=complex128', pkg ), function benchmark( b ) { + var arr; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'complex128', [ 0 ], 'row-major', clbk ); + if ( arr.length !== 0 ) { + b.fail( 'should have length 0' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function clbk() { + return new Complex128( 10.0, 0.0 ); + } +}); + +bench( format( '%s:dtype=complex64', pkg ), function benchmark( b ) { + var arr; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'complex64', [ 0 ], 'row-major', clbk ); + if ( arr.length !== 0 ) { + b.fail( 'should have length 0' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function clbk() { + return new Complex64( 10.0, 0.0 ); + } +}); + +bench( format( '%s:dtype=int32', pkg ), function benchmark( b ) { + var arr; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'int32', [ 0 ], 'row-major', clbk ); + if ( arr.length !== 0 ) { + b.fail( 'should have length 0' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function clbk() { + return -10; + } +}); + +bench( format( '%s:dtype=uint32', pkg ), function benchmark( b ) { + var arr; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'uint32', [ 0 ], 'row-major', clbk ); + if ( arr.length !== 0 ) { + b.fail( 'should have length 0' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function clbk() { + return 10; + } +}); + +bench( format( '%s:dtype=int16', pkg ), function benchmark( b ) { + var arr; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'int16', [ 0 ], 'row-major', clbk ); + if ( arr.length !== 0 ) { + b.fail( 'should have length 0' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function clbk() { + return -10; + } +}); + +bench( format( '%s:dtype=uint16', pkg ), function benchmark( b ) { + var arr; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'uint16', [ 0 ], 'row-major', clbk ); + if ( arr.length !== 0 ) { + b.fail( 'should have length 0' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function clbk() { + return 10; + } +}); + +bench( format( '%s:dtype=int8', pkg ), function benchmark( b ) { + var arr; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'int8', [ 0 ], 'row-major', clbk ); + if ( arr.length !== 0 ) { + b.fail( 'should have length 0' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function clbk() { + return -10; + } +}); + +bench( format( '%s:dtype=uint8', pkg ), function benchmark( b ) { + var arr; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'uint8', [ 0 ], 'row-major', clbk ); + if ( arr.length !== 0 ) { + b.fail( 'should have length 0' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function clbk() { + return 10; + } +}); + +bench( format( '%s:dtype=uint8c', pkg ), function benchmark( b ) { + var arr; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'uint8c', [ 0 ], 'row-major', clbk ); + if ( arr.length !== 0 ) { + b.fail( 'should have length 0' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function clbk() { + return 10; + } +}); + +bench( format( '%s:dtype=bool', pkg ), function benchmark( b ) { + var arr; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'bool', [ 0 ], 'row-major', clbk ); + if ( arr.length !== 0 ) { + b.fail( 'should have length 0' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function clbk() { + return true; + } +}); + +bench( format( '%s:dtype=generic', pkg ), function benchmark( b ) { + var arr; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'generic', [ 0 ], 'row-major', clbk ); + if ( arr.length !== 0 ) { + b.fail( 'should have length 0' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function clbk() { + return 10.0; + } +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.bool.js b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.bool.js new file mode 100644 index 000000000000..1098b64f15c7 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.bool.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var fullBy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Callback function. +* +* @private +* @returns {*} fill value +*/ +function clbk() { + return true; +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var arr; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'bool', [ len ], 'row-major', clbk ); + if ( arr.length !== len ) { + b.fail( 'unexpected length' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=bool,size=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.complex128.js b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.complex128.js new file mode 100644 index 000000000000..242a2b8b1d61 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.complex128.js @@ -0,0 +1,105 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var fullBy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Callback function. +* +* @private +* @returns {*} fill value +*/ +function clbk() { + return new Complex128( 10.0, 0.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var arr; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'complex128', [ len ], 'row-major', clbk ); + if ( arr.length !== len ) { + b.fail( 'unexpected length' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=complex128,size=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.complex64.js b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.complex64.js new file mode 100644 index 000000000000..b60e51e33415 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.complex64.js @@ -0,0 +1,105 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var fullBy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Callback function. +* +* @private +* @returns {*} fill value +*/ +function clbk() { + return new Complex64( 10.0, 0.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var arr; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'complex64', [ len ], 'row-major', clbk ); + if ( arr.length !== len ) { + b.fail( 'unexpected length' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=complex64,size=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.float32.js b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.float32.js new file mode 100644 index 000000000000..a3dd9e40ec8d --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.float32.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var fullBy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Callback function. +* +* @private +* @returns {*} fill value +*/ +function clbk() { + return 10.0; +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var arr; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'float32', [ len ], 'row-major', clbk ); + if ( arr.length !== len ) { + b.fail( 'unexpected length' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=float32,size=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.float64.js b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.float64.js new file mode 100644 index 000000000000..a30d501d2667 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.float64.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var fullBy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Callback function. +* +* @private +* @returns {*} fill value +*/ +function clbk() { + return 10.0; +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var arr; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'float64', [ len ], 'row-major', clbk ); + if ( arr.length !== len ) { + b.fail( 'unexpected length' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=float64,size=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.generic.js b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.generic.js new file mode 100644 index 000000000000..e481facf2bc7 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.generic.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var fullBy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Callback function. +* +* @private +* @returns {*} fill value +*/ +function clbk() { + return 10.0; +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var arr; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'generic', [ len ], 'row-major', clbk ); + if ( arr.length !== len ) { + b.fail( 'unexpected length' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=generic,size=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.int16.js b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.int16.js new file mode 100644 index 000000000000..1b1c93bcdced --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.int16.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var fullBy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Callback function. +* +* @private +* @returns {*} fill value +*/ +function clbk() { + return -10; +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var arr; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'int16', [ len ], 'row-major', clbk ); + if ( arr.length !== len ) { + b.fail( 'unexpected length' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=int16,size=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.int32.js b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.int32.js new file mode 100644 index 000000000000..7cca62cee5a1 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.int32.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var fullBy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Callback function. +* +* @private +* @returns {*} fill value +*/ +function clbk() { + return -10; +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var arr; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'int32', [ len ], 'row-major', clbk ); + if ( arr.length !== len ) { + b.fail( 'unexpected length' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=int32,size=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.int8.js b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.int8.js new file mode 100644 index 000000000000..4411e799b5e2 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.int8.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var fullBy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Callback function. +* +* @private +* @returns {*} fill value +*/ +function clbk() { + return -10; +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var arr; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'int8', [ len ], 'row-major', clbk ); + if ( arr.length !== len ) { + b.fail( 'unexpected length' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=int8,size=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.uint16.js b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.uint16.js new file mode 100644 index 000000000000..209cfad82741 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.uint16.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var fullBy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Callback function. +* +* @private +* @returns {*} fill value +*/ +function clbk() { + return 10; +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var arr; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'uint16', [ len ], 'row-major', clbk ); + if ( arr.length !== len ) { + b.fail( 'unexpected length' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=uint16,size=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.uint32.js b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.uint32.js new file mode 100644 index 000000000000..b18116119652 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.uint32.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var fullBy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Callback function. +* +* @private +* @returns {*} fill value +*/ +function clbk() { + return 10; +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var arr; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'uint32', [ len ], 'row-major', clbk ); + if ( arr.length !== len ) { + b.fail( 'unexpected length' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=uint32,size=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.uint8.js b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.uint8.js new file mode 100644 index 000000000000..cb55307af75f --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.uint8.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var fullBy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Callback function. +* +* @private +* @returns {*} fill value +*/ +function clbk() { + return 10; +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var arr; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'uint8', [ len ], 'row-major', clbk ); + if ( arr.length !== len ) { + b.fail( 'unexpected length' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=uint8,size=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.uint8c.js b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.uint8c.js new file mode 100644 index 000000000000..064d82d562e4 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/benchmark/benchmark.size.uint8c.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var fullBy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Callback function. +* +* @private +* @returns {*} fill value +*/ +function clbk() { + return 10; +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var arr; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = fullBy( 'uint8c', [ len ], 'row-major', clbk ); + if ( arr.length !== len ) { + b.fail( 'unexpected length' ); + } + } + b.toc(); + if ( !isndarrayLike( arr ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=uint8c,size=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/full-by/docs/repl.txt new file mode 100644 index 000000000000..c35661a21ee1 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/docs/repl.txt @@ -0,0 +1,41 @@ + +{{alias}}( dtype, shape, order, clbk[, thisArg] ) + Returns an ndarray filled according to a callback function and having a + specified shape and data type. + + The callback function is provided the following arguments: + + - indices: current array element indices. + + Parameters + ---------- + dtype: string|DataType + Underlying data type. + + shape: ArrayLikeObject + Array shape. + + order: string + Specifies whether an array is row-major (C-style) or column-major + (Fortran-style). + + clbk: Function + Callback function. + + thisArg: any (optional) + Callback function execution context. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > function clbk() { return 10.0; }; + > var arr = {{alias}}( 'float64', [ 2, 2 ], 'row-major', clbk ) + [ [ 10.0, 10.0 ], [ 10.0, 10.0 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/base/full-by/docs/types/index.d.ts new file mode 100644 index 000000000000..078000bf0d64 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/docs/types/index.d.ts @@ -0,0 +1,404 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Shape, Order, typedndarray, float64ndarray, float32ndarray, int32ndarray, int16ndarray, int8ndarray, uint32ndarray, uint16ndarray, uint8ndarray, uint8cndarray, boolndarray, complex128ndarray, complex64ndarray, genericndarray, DataType, Float64DataType, Float32DataType, Complex128DataType, Complex64DataType, Int32DataType, Int16DataType, Int8DataType, Uint32DataType, Uint16DataType, Uint8DataType, Uint8cDataType, BooleanDataType, GenericDataType } from '@stdlib/types/ndarray'; +import { ComplexLike } from '@stdlib/types/complex'; + +/** +* Callback invoked for each ndarray element. +* +* @returns fill value +*/ +type Nullary = ( this: ThisArg ) => U; + +/** +* Callback invoked for each ndarray element. +* +* @param indices - current array element indices +* @returns fill value +*/ +type Unary = ( this: ThisArg, indices: Array ) => U; + +/** +* Callback invoked for each ndarray element. +* +* @param indices - current array element indices +* @returns fill value +*/ +type Callback = Nullary | Unary; + +/** +* Returns an ndarray filled according to a callback function and having a specified shape and data type. +* +* @param dtype - underlying data type +* @param shape - array shape +* @param order - specifies whether an array is row-major (C-style) or column-major (Fortran-style) +* @param clbk - callback function +* @param thisArg - callback function execution context +* @returns output array +* +* @example +* var getDType = require( '@stdlib/ndarray/dtype' ); +* +* function clbk() { +* return 10.0; +* } +* +* var arr = fullBy( 'float64', [ 2, 2 ], 'row-major', clbk ); +* // returns [ [ 10.0, 10.0 ], [ 10.0, 10.0 ] ] +* +* var dt = String( getDType( arr ) ); +* // returns 'float64' +*/ +declare function fullBy( dtype: Float64DataType, shape: Shape, order: Order, clbk: Callback, thisArg?: ThisArg ): float64ndarray; + +/** +* Returns an ndarray filled according to a callback function and having a specified shape and data type. +* +* @param dtype - underlying data type +* @param shape - array shape +* @param order - specifies whether an array is row-major (C-style) or column-major (Fortran-style) +* @param clbk - callback function +* @param thisArg - callback function execution context +* @returns output array +* +* @example +* var getDType = require( '@stdlib/ndarray/dtype' ); +* +* function clbk() { +* return 10.0; +* } +* +* var arr = fullBy( 'float32', [ 2, 2 ], 'row-major', clbk ); +* // returns [ [ 10.0, 10.0 ], [ 10.0, 10.0 ] ] +* +* var dt = String( getDType( arr ) ); +* // returns 'float32' +*/ +declare function fullBy( dtype: Float32DataType, shape: Shape, order: Order, clbk: Callback, thisArg?: ThisArg ): float32ndarray; + +/** +* Returns an ndarray filled according to a callback function and having a specified shape and data type. +* +* @param dtype - underlying data type +* @param shape - array shape +* @param order - specifies whether an array is row-major (C-style) or column-major (Fortran-style) +* @param clbk - callback function +* @param thisArg - callback function execution context +* @returns output array +* +* @example +* var getDType = require( '@stdlib/ndarray/dtype' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* +* function clbk() { +* return new Complex128( 3.0, 5.0 ); +* } +* +* var arr = fullBy( 'complex128', [ 2, 2 ], 'row-major', clbk ); +* // returns [ [ [ 3.0, 5.0 ], [ 3.0, 5.0 ] ], [ [ 3.0, 5.0 ], [ 3.0, 5.0 ] ] ] +* +* var dt = String( getDType( arr ) ); +* // returns 'complex128' +*/ +declare function fullBy( dtype: Complex128DataType, shape: Shape, order: Order, clbk: Callback, thisArg?: ThisArg ): complex128ndarray; + +/** +* Returns an ndarray filled according to a callback function and having a specified shape and data type. +* +* @param dtype - underlying data type +* @param shape - array shape +* @param order - specifies whether an array is row-major (C-style) or column-major (Fortran-style) +* @param clbk - callback function +* @param thisArg - callback function execution context +* @returns output array +* +* @example +* var getDType = require( '@stdlib/ndarray/dtype' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* +* function clbk() { +* return new Complex64( 3.0, 5.0 ); +* } +* +* var arr = fullBy( 'complex64', [ 2, 2 ], 'row-major', clbk ); +* // returns [ [ [ 3.0, 5.0 ], [ 3.0, 5.0 ] ], [ [ 3.0, 5.0 ], [ 3.0, 5.0 ] ] ] +* +* var dt = String( getDType( arr ) ); +* // returns 'complex64' +*/ +declare function fullBy( dtype: Complex64DataType, shape: Shape, order: Order, clbk: Callback, thisArg?: ThisArg ): complex64ndarray; + +/** +* Returns an ndarray filled according to a callback function and having a specified shape and data type. +* +* @param dtype - underlying data type +* @param shape - array shape +* @param order - specifies whether an array is row-major (C-style) or column-major (Fortran-style) +* @param clbk - callback function +* @param thisArg - callback function execution context +* @returns output array +* +* @example +* var getDType = require( '@stdlib/ndarray/dtype' ); +* +* function clbk() { +* return 10; +* } +* +* var arr = fullBy( 'int32', [ 2, 2 ], 'row-major', clbk ); +* // returns [ [ 10, 10 ], [ 10, 10 ] ] +* +* var dt = String( getDType( arr ) ); +* // returns 'int32' +*/ +declare function fullBy( dtype: Int32DataType, shape: Shape, order: Order, clbk: Callback, thisArg?: ThisArg ): int32ndarray; + +/** +* Returns an ndarray filled according to a callback function and having a specified shape and data type. +* +* @param dtype - underlying data type +* @param shape - array shape +* @param order - specifies whether an array is row-major (C-style) or column-major (Fortran-style) +* @param clbk - callback function +* @param thisArg - callback function execution context +* @returns output array +* +* @example +* var getDType = require( '@stdlib/ndarray/dtype' ); +* +* function clbk() { +* return 10; +* } +* +* var arr = fullBy( 'int16', [ 2, 2 ], 'row-major', clbk ); +* // returns [ [ 10, 10 ], [ 10, 10 ] ] +* +* var dt = String( getDType( arr ) ); +* // returns 'int16' +*/ +declare function fullBy( dtype: Int16DataType, shape: Shape, order: Order, clbk: Callback, thisArg?: ThisArg ): int16ndarray; + +/** +* Returns an ndarray filled according to a callback function and having a specified shape and data type. +* +* @param dtype - underlying data type +* @param shape - array shape +* @param order - specifies whether an array is row-major (C-style) or column-major (Fortran-style) +* @param clbk - callback function +* @param thisArg - callback function execution context +* @returns output array +* +* @example +* var getDType = require( '@stdlib/ndarray/dtype' ); +* +* function clbk() { +* return 10; +* } +* +* var arr = fullBy( 'int8', [ 2, 2 ], 'row-major', clbk ); +* // returns [ [ 10, 10 ], [ 10, 10 ] ] +* +* var dt = String( getDType( arr ) ); +* // returns 'int8' +*/ +declare function fullBy( dtype: Int8DataType, shape: Shape, order: Order, clbk: Callback, thisArg?: ThisArg ): int8ndarray; + +/** +* Returns an ndarray filled according to a callback function and having a specified shape and data type. +* +* @param dtype - underlying data type +* @param shape - array shape +* @param order - specifies whether an array is row-major (C-style) or column-major (Fortran-style) +* @param clbk - callback function +* @param thisArg - callback function execution context +* @returns output array +* +* @example +* var getDType = require( '@stdlib/ndarray/dtype' ); +* +* function clbk() { +* return 10; +* } +* +* var arr = fullBy( 'uint32', [ 2, 2 ], 'row-major', clbk ); +* // returns [ [ 10, 10 ], [ 10, 10 ] ] +* +* var dt = String( getDType( arr ) ); +* // returns 'uint32' +*/ +declare function fullBy( dtype: Uint32DataType, shape: Shape, order: Order, clbk: Callback, thisArg?: ThisArg ): uint32ndarray; + +/** +* Returns an ndarray filled according to a callback function and having a specified shape and data type. +* +* @param dtype - underlying data type +* @param shape - array shape +* @param order - specifies whether an array is row-major (C-style) or column-major (Fortran-style) +* @param clbk - callback function +* @param thisArg - callback function execution context +* @returns output array +* +* @example +* var getDType = require( '@stdlib/ndarray/dtype' ); +* +* function clbk() { +* return 10; +* } +* +* var arr = fullBy( 'uint16', [ 2, 2 ], 'row-major', clbk ); +* // returns [ [ 10, 10 ], [ 10, 10 ] ] +* +* var dt = String( getDType( arr ) ); +* // returns 'uint16' +*/ +declare function fullBy( dtype: Uint16DataType, shape: Shape, order: Order, clbk: Callback, thisArg?: ThisArg ): uint16ndarray; + +/** +* Returns an ndarray filled according to a callback function and having a specified shape and data type. +* +* @param dtype - underlying data type +* @param shape - array shape +* @param order - specifies whether an array is row-major (C-style) or column-major (Fortran-style) +* @param clbk - callback function +* @param thisArg - callback function execution context +* @returns output array +* +* @example +* var getDType = require( '@stdlib/ndarray/dtype' ); +* +* function clbk() { +* return 10; +* } +* +* var arr = fullBy( 'uint8', [ 2, 2 ], 'row-major', clbk ); +* // returns [ [ 10, 10 ], [ 10, 10 ] ] +* +* var dt = String( getDType( arr ) ); +* // returns 'uint8' +*/ +declare function fullBy( dtype: Uint8DataType, shape: Shape, order: Order, clbk: Callback, thisArg?: ThisArg ): uint8ndarray; + +/** +* Returns an ndarray filled according to a callback function and having a specified shape and data type. +* +* @param dtype - underlying data type +* @param shape - array shape +* @param order - specifies whether an array is row-major (C-style) or column-major (Fortran-style) +* @param clbk - callback function +* @param thisArg - callback function execution context +* @returns output array +* +* @example +* var getDType = require( '@stdlib/ndarray/dtype' ); +* +* function clbk() { +* return 10; +* } +* +* var arr = fullBy( 'uint8c', [ 2, 2 ], 'row-major', clbk ); +* // returns [ [ 10, 10 ], [ 10, 10 ] ] +* +* var dt = String( getDType( arr ) ); +* // returns 'uint8c' +*/ +declare function fullBy( dtype: Uint8cDataType, shape: Shape, order: Order, clbk: Callback, thisArg?: ThisArg ): uint8cndarray; + +/** +* Returns an ndarray filled according to a callback function and having a specified shape and data type. +* +* @param dtype - underlying data type +* @param shape - array shape +* @param order - specifies whether an array is row-major (C-style) or column-major (Fortran-style) +* @param clbk - callback function +* @param thisArg - callback function execution context +* @returns output array +* +* @example +* var getDType = require( '@stdlib/ndarray/dtype' ); +* +* function clbk() { +* return true; +* } +* +* var arr = fullBy( 'bool', [ 2, 2 ], 'row-major', clbk ); +* // returns [ [ true, true ], [ true, true ] ] +* +* var dt = String( getDType( arr ) ); +* // returns 'bool' +*/ +declare function fullBy( dtype: BooleanDataType, shape: Shape, order: Order, clbk: Callback, thisArg?: ThisArg ): boolndarray; + +/** +* Returns an ndarray filled according to a callback function and having a specified shape and data type. +* +* @param dtype - underlying data type +* @param shape - array shape +* @param order - specifies whether an array is row-major (C-style) or column-major (Fortran-style) +* @param clbk - callback function +* @param thisArg - callback function execution context +* @returns output array +* +* @example +* var getDType = require( '@stdlib/ndarray/dtype' ); +* +* function clbk() { +* return 10.0; +* } +* +* var arr = fullBy( 'generic', [ 2, 2 ], 'row-major', clbk ); +* // returns [ [ 10.0, 10.0 ], [ 10.0, 10.0 ] ] +* +* var dt = String( getDType( arr ) ); +* // returns 'generic' +*/ +declare function fullBy( dtype: GenericDataType, shape: Shape, order: Order, clbk: Callback, thisArg?: ThisArg ): genericndarray; + +/** +* Returns an ndarray filled according to a callback function and having a specified shape and data type. +* +* @param dtype - underlying data type +* @param shape - array shape +* @param order - specifies whether an array is row-major (C-style) or column-major (Fortran-style) +* @param clbk - callback function +* @param thisArg - callback function execution context +* @returns output array +* +* @example +* var getDType = require( '@stdlib/ndarray/dtype' ); +* +* function clbk() { +* return 10.0; +* } +* +* var arr = fullBy( 'float32', [ 2, 2 ], 'row-major', clbk ); +* // returns [ [ 10.0, 10.0 ], [ 10.0, 10.0 ] ] +* +* var dt = String( getDType( arr ) ); +* // returns 'float32' +*/ +declare function fullBy( dtype: DataType, shape: Shape, order: Order, clbk: Callback, thisArg?: ThisArg ): typedndarray; + + +// EXPORTS // + +export = fullBy; diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/base/full-by/docs/types/test.ts new file mode 100644 index 000000000000..4e82a5e77d0d --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/docs/types/test.ts @@ -0,0 +1,156 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import fullBy = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + fullBy( 'float64', [ 2, 2 ], 'row-major', () => 10.0 ); // $ExpectType float64ndarray + fullBy( 'float32', [ 2, 2 ], 'row-major', () => 10.0 ); // $ExpectType float32ndarray + fullBy( 'complex128', [ 2, 2 ], 'row-major', () => 10.0 ); // $ExpectType complex128ndarray + fullBy( 'complex64', [ 2, 2 ], 'row-major', () => 10.0 ); // $ExpectType complex64ndarray + fullBy( 'int32', [ 2, 2 ], 'row-major', () => 10 ); // $ExpectType int32ndarray + fullBy( 'int16', [ 2, 2 ], 'row-major', () => 10 ); // $ExpectType int16ndarray + fullBy( 'int8', [ 2, 2 ], 'row-major', () => 10 ); // $ExpectType int8ndarray + fullBy( 'uint32', [ 2, 2 ], 'row-major', () => 10 ); // $ExpectType uint32ndarray + fullBy( 'uint16', [ 2, 2 ], 'row-major', () => 10 ); // $ExpectType uint16ndarray + fullBy( 'uint8', [ 2, 2 ], 'row-major', () => 10 ); // $ExpectType uint8ndarray + fullBy( 'uint8c', [ 2, 2 ], 'row-major', () => 10 ); // $ExpectType uint8cndarray + fullBy( 'bool', [ 2, 2 ], 'row-major', () => true ); // $ExpectType boolndarray + fullBy( 'generic', [ 2, 2 ], 'row-major', () => 10.0 ); // $ExpectType genericndarray + + fullBy( 'float64', [ 2, 2 ], 'column-major', () => 10.0 ); // $ExpectType float64ndarray + fullBy( 'float32', [ 2, 2 ], 'column-major', () => 10.0 ); // $ExpectType float32ndarray + fullBy( 'complex128', [ 2, 2 ], 'column-major', () => 10.0 ); // $ExpectType complex128ndarray + fullBy( 'complex64', [ 2, 2 ], 'column-major', () => 10.0 ); // $ExpectType complex64ndarray + fullBy( 'int32', [ 2, 2 ], 'column-major', () => 10 ); // $ExpectType int32ndarray + fullBy( 'int16', [ 2, 2 ], 'column-major', () => 10 ); // $ExpectType int16ndarray + fullBy( 'int8', [ 2, 2 ], 'column-major', () => 10 ); // $ExpectType int8ndarray + fullBy( 'uint32', [ 2, 2 ], 'column-major', () => 10 ); // $ExpectType uint32ndarray + fullBy( 'uint16', [ 2, 2 ], 'column-major', () => 10 ); // $ExpectType uint16ndarray + fullBy( 'uint8', [ 2, 2 ], 'column-major', () => 10 ); // $ExpectType uint8ndarray + fullBy( 'uint8c', [ 2, 2 ], 'column-major', () => 10 ); // $ExpectType uint8cndarray + fullBy( 'bool', [ 2, 2 ], 'column-major', () => true ); // $ExpectType boolndarray + fullBy( 'generic', [ 2, 2 ], 'column-major', () => 10.0 ); // $ExpectType genericndarray + + fullBy( 'float64', [ 2, 2 ], 'row-major', () => 10.0, {} ); // $ExpectType float64ndarray + fullBy( 'float32', [ 2, 2 ], 'row-major', () => 10.0, {} ); // $ExpectType float32ndarray + fullBy( 'complex128', [ 2, 2 ], 'row-major', () => 10.0, {} ); // $ExpectType complex128ndarray + fullBy( 'complex64', [ 2, 2 ], 'row-major', () => 10.0, {} ); // $ExpectType complex64ndarray + fullBy( 'int32', [ 2, 2 ], 'row-major', () => 10, {} ); // $ExpectType int32ndarray + fullBy( 'int16', [ 2, 2 ], 'row-major', () => 10, {} ); // $ExpectType int16ndarray + fullBy( 'int8', [ 2, 2 ], 'row-major', () => 10, {} ); // $ExpectType int8ndarray + fullBy( 'uint32', [ 2, 2 ], 'row-major', () => 10, {} ); // $ExpectType uint32ndarray + fullBy( 'uint16', [ 2, 2 ], 'row-major', () => 10, {} ); // $ExpectType uint16ndarray + fullBy( 'uint8', [ 2, 2 ], 'row-major', () => 10, {} ); // $ExpectType uint8ndarray + fullBy( 'uint8c', [ 2, 2 ], 'row-major', () => 10, {} ); // $ExpectType uint8cndarray + fullBy( 'bool', [ 2, 2 ], 'row-major', () => true, {} ); // $ExpectType boolndarray + fullBy( 'generic', [ 2, 2 ], 'row-major', () => 10.0, {} ); // $ExpectType genericndarray +} + +// The compiler throws an error if the function is provided a first argument which is an unrecognized/unsupported data type... +{ + fullBy( '10', [ 2, 2 ], 'row-major', () => 10.0 ); // $ExpectError + fullBy( 10, [ 2, 2 ], 'row-major', () => 10.0 ); // $ExpectError + fullBy( false, [ 2, 2 ], 'row-major', () => 10.0 ); // $ExpectError + fullBy( true, [ 2, 2 ], 'row-major', () => 10.0 ); // $ExpectError + fullBy( null, [ 2, 2 ], 'row-major', () => 10.0 ); // $ExpectError + fullBy( [], [ 2, 2 ], 'row-major', () => 10.0 ); // $ExpectError + fullBy( {}, [ 2, 2 ], 'row-major', () => 10.0 ); // $ExpectError + fullBy( ( x: number ): number => x, [ 2, 2 ], 'row-major', () => 10.0 ); // $ExpectError + + fullBy( '10', [ 2, 2 ], 'row-major', () => 10.0, {} ); // $ExpectError + fullBy( 10, [ 2, 2 ], 'row-major', () => 10.0, {} ); // $ExpectError + fullBy( false, [ 2, 2 ], 'row-major', () => 10.0, {} ); // $ExpectError + fullBy( true, [ 2, 2 ], 'row-major', () => 10.0, {} ); // $ExpectError + fullBy( null, [ 2, 2 ], 'row-major', () => 10.0, {} ); // $ExpectError + fullBy( [], [ 2, 2 ], 'row-major', () => 10.0, {} ); // $ExpectError + fullBy( {}, [ 2, 2 ], 'row-major', () => 10.0, {} ); // $ExpectError + fullBy( ( x: number ): number => x, [ 2, 2 ], 'row-major', () => 10.0, {} ); // $ExpectError +} + +// The compiler throws an error if the function is not provided a valid shape for the second argument... +{ + fullBy( 'float32', '5', 'row-major', () => 10.0 ); // $ExpectError + fullBy( 'float32', false, 'row-major', () => 10.0 ); // $ExpectError + fullBy( 'float32', true, 'row-major', () => 10.0 ); // $ExpectError + fullBy( 'float32', null, 'row-major', () => 10.0 ); // $ExpectError + fullBy( 'float32', undefined, 'row-major', () => 10.0 ); // $ExpectError + fullBy( 'float32', [ '5' ], 'row-major', () => 10.0 ); // $ExpectError + fullBy( 'float32', {}, 'row-major', () => 10.0 ); // $ExpectError + fullBy( 'float32', ( x: number ): number => x, 'row-major', () => 10.0 ); // $ExpectError + + fullBy( 'float32', '5', 'row-major', () => 10.0, {} ); // $ExpectError + fullBy( 'float32', false, 'row-major', () => 10.0, {} ); // $ExpectError + fullBy( 'float32', true, 'row-major', () => 10.0, {} ); // $ExpectError + fullBy( 'float32', null, 'row-major', () => 10.0, {} ); // $ExpectError + fullBy( 'float32', undefined, 'row-major', () => 10.0, {} ); // $ExpectError + fullBy( 'float32', [ '5' ], 'row-major', () => 10.0, {} ); // $ExpectError + fullBy( 'float32', {}, 'row-major', () => 10.0, {} ); // $ExpectError + fullBy( 'float32', ( x: number ): number => x, 'row-major', () => 10.0, {} ); // $ExpectError +} + +// The compiler throws an error if the function is not provided a valid order for the third argument... +{ + fullBy( 'float32', [ 2, 2 ], '5', () => 10.0 ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], false, () => 10.0 ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], true, () => 10.0 ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], null, () => 10.0 ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], undefined, () => 10.0 ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], [ '5' ], () => 10.0 ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], {}, () => 10.0 ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], ( x: number ): number => x, () => 10.0 ); // $ExpectError + + fullBy( 'float32', [ 2, 2 ], '5', () => 10.0, {} ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], false, () => 10.0, {} ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], true, () => 10.0, {} ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], null, () => 10.0, {} ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], undefined, () => 10.0, {} ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], [ '5' ], () => 10.0, {} ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], {}, () => 10.0, {} ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], ( x: number ): number => x, () => 10.0, {} ); // $ExpectError +} + +// The compiler throws an error if the function is not provided a callback function for the fourth argument... +{ + fullBy( 'float32', [ 2, 2 ], 'row-major', '10' ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], 'row-major', 10 ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], 'row-major', false ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], 'row-major', true ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], 'row-major', null ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], 'row-major', [] ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], 'row-major', {} ); // $ExpectError + + fullBy( 'float32', [ 2, 2 ], 'row-major', '10', {} ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], 'row-major', 10, {} ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], 'row-major', false, {} ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], 'row-major', true, {} ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], 'row-major', null, {} ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], 'row-major', [], {} ); // $ExpectError + fullBy( 'float32', [ 2, 2 ], 'row-major', {}, {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + fullBy( 'float64' ); // $ExpectError + fullBy( 'float64', [ 2, 2 ] ); // $ExpectError + fullBy( 'float64', [ 2, 2 ], 'row-major' ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/examples/index.js b/lib/node_modules/@stdlib/ndarray/base/full-by/examples/index.js new file mode 100644 index 000000000000..6e800f06730a --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dtypes = require( '@stdlib/ndarray/dtypes' ); +var fullBy = require( './../lib' ); + +// Get a list of data types: +var dt = dtypes( 'integer_and_generic' ); + +// Generate filled arrays... +var arr; +var i; +for ( i = 0; i < dt.length; i++ ) { + arr = fullBy( dt[ i ], [ 2, 2 ], 'row-major', discreteUniform( -100, 100 ) ); + console.log( ndarray2array( arr ) ); +} diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/full-by/lib/index.js new file mode 100644 index 000000000000..5adb4fc0df14 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/lib/index.js @@ -0,0 +1,48 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Create an ndarray filled according to a callback function and having a specified shape and data type. +* +* @module @stdlib/ndarray/base/full-by +* +* @example +* var getDType = require( '@stdlib/ndarray/dtype' ); +* var fullBy = require( '@stdlib/ndarray/base/full-by' ); +* +* function clbk() { +* return 10.0; +* } +* +* var arr = fullBy( 'float64', [ 2, 2 ], 'row-major', clbk ); +* // returns [ [ 10.0, 10.0 ], [ 10.0, 10.0 ] ] +* +* var dt = String( getDType( arr ) ); +* // returns 'float64' +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/full-by/lib/main.js new file mode 100644 index 000000000000..1cc582db78c8 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/lib/main.js @@ -0,0 +1,80 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var empty = require( '@stdlib/ndarray/base/empty' ); +var map = require( '@stdlib/ndarray/base/map' ); + + +// MAIN // + +/** +* Returns an ndarray filled according to a callback function and having a specified shape and data type. +* +* @param {*} dtype - data type +* @param {NonNegativeIntegerArray} shape - array shape +* @param {string} order - array order +* @param {Function} clbk - callback function +* @param {*} [thisArg] - callback function execution context +* @throws {TypeError} first argument must be a recognized data type +* @returns {ndarray} ndarray +* +* @example +* var getDType = require( '@stdlib/ndarray/dtype' ); +* +* function clbk() { +* return 10.0; +* } +* +* var arr = fullBy( 'float64', [ 2, 2 ], 'row-major', clbk ); +* // returns [ [ 10.0, 10.0 ], [ 10.0, 10.0 ] ] +* +* var dt = String( getDType( arr ) ); +* // returns 'float64' +*/ +function fullBy( dtype, shape, order, clbk, thisArg ) { + var out; + + // Allocate an output array: + out = empty( dtype, shape, order ); + + // Fill the output ndarray according to a callback function: + map( [ out, out ], wrapper ); + + return out; + + /** + * Wraps a callback function so that only indices are passed. + * + * @private + * @param {*} value - current array element + * @param {NonNegativeIntegerArray} indices - current array element indices + * @returns {*} callback return value + */ + function wrapper( value, indices ) { + return clbk.call( thisArg, indices ); + } +} + + +// EXPORTS // + +module.exports = fullBy; diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/package.json b/lib/node_modules/@stdlib/ndarray/base/full-by/package.json new file mode 100644 index 000000000000..d3fe9262d812 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/package.json @@ -0,0 +1,69 @@ +{ + "name": "@stdlib/ndarray/base/full-by", + "version": "0.0.0", + "description": "Create an ndarray filled according to a callback function and having a specified shape and data type.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "types", + "base", + "data", + "structure", + "ndarray", + "matrix", + "vector", + "fill", + "filled", + "full", + "callback", + "map", + "apply" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ndarray/base/full-by/test/test.js b/lib/node_modules/@stdlib/ndarray/base/full-by/test/test.js new file mode 100644 index 000000000000..924f4b5302a2 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/full-by/test/test.js @@ -0,0 +1,950 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var Float32Array = require( '@stdlib/array/float32' ); +var Int32Array = require( '@stdlib/array/int32' ); +var Uint32Array = require( '@stdlib/array/uint32' ); +var Int16Array = require( '@stdlib/array/int16' ); +var Uint16Array = require( '@stdlib/array/uint16' ); +var Int8Array = require( '@stdlib/array/int8' ); +var Uint8Array = require( '@stdlib/array/uint8' ); +var Uint8ClampedArray = require( '@stdlib/array/uint8c' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var BooleanArray = require( '@stdlib/array/bool' ); +var Buffer = require( '@stdlib/buffer/ctor' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var isEqualBooleanArray = require( '@stdlib/assert/is-equal-booleanarray' ); +var instanceOf = require( '@stdlib/assert/instance-of' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getShape = require( '@stdlib/ndarray/base/shape' ); +var getOrder = require( '@stdlib/ndarray/base/order' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var getDType = require( '@stdlib/ndarray/base/dtype' ); +var fullBy = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof fullBy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided an unrecognized data type', function test( t ) { + var values; + var i; + + values = [ + '5', + 'beep', + 'empty', + 'Int32', + 'Uint32', + 'Int16', + 'Uint16', + 'Int8', + 'Uint8', + 'Uint8c', + 'uint8_clamped', + 'Float64', + 'Float32', + 'FLOAT64', + 'FLOAT32', + 'GENERIC' + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + fullBy( value, [ 2, 2 ], 'row-major', clbk ); + }; + } + + function clbk() { + return 10.0; + } +}); + +tape( 'the function returns a filled array (dtype=float64, order=row-major)', function test( t ) { + var expected; + var arr; + + expected = new Float64Array([ + 10.0, + 10.0, + 10.0, + 10.0 + ]); + + arr = fullBy( 'float64', [ 2, 2 ], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Float64Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'row-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10.0; + } +}); + +tape( 'the function returns a filled array (dtype=float64, order=column-major)', function test( t ) { + var expected; + var arr; + + expected = new Float64Array([ + 10.0, + 10.0, + 10.0, + 10.0 + ]); + + arr = fullBy( 'float64', [ 2, 2 ], 'column-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Float64Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'column-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10.0; + } +}); + +tape( 'the function returns a filled array (dtype=float32, order=row-major)', function test( t ) { + var expected; + var arr; + + expected = new Float32Array([ + 10.0, + 10.0, + 10.0, + 10.0 + ]); + + arr = fullBy( 'float32', [ 2, 2 ], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'float32', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Float32Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'row-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10.0; + } +}); + +tape( 'the function returns a filled array (dtype=float32, order=column-major)', function test( t ) { + var expected; + var arr; + + expected = new Float32Array([ + 10.0, + 10.0, + 10.0, + 10.0 + ]); + + arr = fullBy( 'float32', [ 2, 2 ], 'column-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'float32', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Float32Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'column-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10.0; + } +}); + +tape( 'the function returns a filled array (dtype=int32, order=row-major)', function test( t ) { + var expected; + var arr; + + expected = new Int32Array([ + 10, + 10, + 10, + 10 + ]); + + arr = fullBy( 'int32', [ 2, 2 ], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'int32', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Int32Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'row-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10; + } +}); + +tape( 'the function returns a filled array (dtype=int32, order=column-major)', function test( t ) { + var expected; + var arr; + + expected = new Int32Array([ + 10, + 10, + 10, + 10 + ]); + + arr = fullBy( 'int32', [ 2, 2 ], 'column-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'int32', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Int32Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'column-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10; + } +}); + +tape( 'the function returns a filled array (dtype=int16, order=row-major)', function test( t ) { + var expected; + var arr; + + expected = new Int16Array([ + 10, + 10, + 10, + 10 + ]); + + arr = fullBy( 'int16', [ 2, 2 ], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'int16', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Int16Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'row-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10; + } +}); + +tape( 'the function returns a filled array (dtype=int16, order=column-major)', function test( t ) { + var expected; + var arr; + + expected = new Int16Array([ + 10, + 10, + 10, + 10 + ]); + + arr = fullBy( 'int16', [ 2, 2 ], 'column-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'int16', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Int16Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'column-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10; + } +}); + +tape( 'the function returns a filled array (dtype=int8, order=row-major)', function test( t ) { + var expected; + var arr; + + expected = new Int8Array([ + 10, + 10, + 10, + 10 + ]); + + arr = fullBy( 'int8', [ 2, 2 ], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'int8', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Int8Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'row-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10; + } +}); + +tape( 'the function returns a filled array (dtype=int8, order=column-major)', function test( t ) { + var expected; + var arr; + + expected = new Int8Array([ + 10, + 10, + 10, + 10 + ]); + + arr = fullBy( 'int8', [ 2, 2 ], 'column-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'int8', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Int8Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'column-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10; + } +}); + +tape( 'the function returns a filled array (dtype=uint32, order=row-major)', function test( t ) { + var expected; + var arr; + + expected = new Uint32Array([ + 10, + 10, + 10, + 10 + ]); + + arr = fullBy( 'uint32', [ 2, 2 ], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'uint32', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Uint32Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'row-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10; + } +}); + +tape( 'the function returns a filled array (dtype=uint32, order=column-major)', function test( t ) { + var expected; + var arr; + + expected = new Uint32Array([ + 10, + 10, + 10, + 10 + ]); + + arr = fullBy( 'uint32', [ 2, 2 ], 'column-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'uint32', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Uint32Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'column-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10; + } +}); + +tape( 'the function returns a filled array (dtype=uint16, order=row-major)', function test( t ) { + var expected; + var arr; + + expected = new Uint16Array([ + 10, + 10, + 10, + 10 + ]); + + arr = fullBy( 'uint16', [ 2, 2 ], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'uint16', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Uint16Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'row-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10; + } +}); + +tape( 'the function returns a filled array (dtype=uint16, order=column-major)', function test( t ) { + var expected; + var arr; + + expected = new Uint16Array([ + 10, + 10, + 10, + 10 + ]); + + arr = fullBy( 'uint16', [ 2, 2 ], 'column-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'uint16', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Uint16Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'column-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10; + } +}); + +tape( 'the function returns a filled array (dtype=uint8, order=row-major)', function test( t ) { + var expected; + var arr; + + expected = new Uint8Array([ + 10, + 10, + 10, + 10 + ]); + + arr = fullBy( 'uint8', [ 2, 2 ], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'uint8', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Uint8Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'row-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10; + } +}); + +tape( 'the function returns a filled array (dtype=uint8, order=column-major)', function test( t ) { + var expected; + var arr; + + expected = new Uint8Array([ + 10, + 10, + 10, + 10 + ]); + + arr = fullBy( 'uint8', [ 2, 2 ], 'column-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'uint8', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Uint8Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'column-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10; + } +}); + +tape( 'the function returns a filled array (dtype=uint8c, order=row-major)', function test( t ) { + var expected; + var arr; + + expected = new Uint8ClampedArray([ + 10, + 10, + 10, + 10 + ]); + + arr = fullBy( 'uint8c', [ 2, 2 ], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'uint8c', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Uint8ClampedArray ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'row-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10; + } +}); + +tape( 'the function returns a filled array (dtype=uint8c, order=column-major)', function test( t ) { + var expected; + var arr; + + expected = new Uint8ClampedArray([ + 10, + 10, + 10, + 10 + ]); + + arr = fullBy( 'uint8c', [ 2, 2 ], 'column-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'uint8c', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Uint8ClampedArray ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'column-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10; + } +}); + +tape( 'the function returns a filled array (dtype=binary, order=row-major)', function test( t ) { + var expected; + var arr; + + expected = new Buffer([ + 1, + 1, + 1, + 1 + ]); + + arr = fullBy( 'binary', [ 2, 2 ], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'binary', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Buffer ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'row-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 1; + } +}); + +tape( 'the function returns a filled array (dtype=binary, order=column-major)', function test( t ) { + var expected; + var arr; + + expected = new Buffer([ + 1, + 1, + 1, + 1 + ]); + + arr = fullBy( 'binary', [ 2, 2 ], 'column-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'binary', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Buffer ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'column-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 1; + } +}); + +tape( 'the function returns a filled array (dtype=complex128, order=row-major)', function test( t ) { + var expected; + var arr; + + expected = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + 10.0, + 0.0, + 10.0, + 0.0 + ]); + + arr = fullBy( 'complex128', [ 2, 2 ], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'complex128', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Complex128Array ), true, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( getData( arr ), expected ), true, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'row-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return new Complex128( 10.0, 0.0 ); + } +}); + +tape( 'the function returns a filled array (dtype=complex128, order=column-major)', function test( t ) { + var expected; + var arr; + + expected = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + 10.0, + 0.0, + 10.0, + 0.0 + ]); + + arr = fullBy( 'complex128', [ 2, 2 ], 'column-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'complex128', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Complex128Array ), true, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( getData( arr ), expected ), true, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'column-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return new Complex128( 10.0, 0.0 ); + } +}); + +tape( 'the function returns a filled array (dtype=complex64, order=row-major)', function test( t ) { + var expected; + var arr; + + expected = new Complex64Array([ + 10.0, + 11.0, + 10.0, + 11.0, + 10.0, + 11.0, + 10.0, + 11.0 + ]); + + arr = fullBy( 'complex64', [ 2, 2 ], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'complex64', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Complex64Array ), true, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( arr ), expected ), true, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'row-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return new Complex64( 10.0, 11.0 ); + } +}); + +tape( 'the function returns a filled array (dtype=complex64, order=column-major)', function test( t ) { + var expected; + var arr; + + expected = new Complex64Array([ + 10.0, + 11.0, + 10.0, + 11.0, + 10.0, + 11.0, + 10.0, + 11.0 + ]); + + arr = fullBy( 'complex64', [ 2, 2 ], 'column-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'complex64', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Complex64Array ), true, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( arr ), expected ), true, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'column-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return new Complex64( 10.0, 11.0 ); + } +}); + +tape( 'the function returns a filled array (dtype=bool, order=row-major)', function test( t ) { + var expected; + var arr; + + expected = new BooleanArray([ + true, + true, + true, + true + ]); + + arr = fullBy( 'bool', [ 2, 2 ], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'bool', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), BooleanArray ), true, 'returns expected value' ); + t.strictEqual( isEqualBooleanArray( getData( arr ), expected ), true, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'row-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return true; + } +}); + +tape( 'the function returns a filled array (dtype=bool, order=column-major)', function test( t ) { + var expected; + var arr; + + expected = new BooleanArray([ + true, + true, + true, + true + ]); + + arr = fullBy( 'bool', [ 2, 2 ], 'column-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'bool', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), BooleanArray ), true, 'returns expected value' ); + t.strictEqual( isEqualBooleanArray( getData( arr ), expected ), true, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'column-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return true; + } +}); + +tape( 'the function returns a filled array (dtype=generic, order=row-major)', function test( t ) { + var expected; + var arr; + + expected = [ + 10.0, + 10.0, + 10.0, + 10.0 + ]; + + arr = fullBy( 'generic', [ 2, 2 ], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'row-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10.0; + } +}); + +tape( 'the function returns a filled array (dtype=generic, order=column-major)', function test( t ) { + var expected; + var arr; + + expected = [ + 10.0, + 10.0, + 10.0, + 10.0 + ]; + + arr = fullBy( 'generic', [ 2, 2 ], 'column-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'column-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10.0; + } +}); + +tape( 'the function supports zero-dimensional arrays', function test( t ) { + var expected; + var arr; + + expected = new Float64Array( [ 10.0 ] ); + + arr = fullBy( 'float64', [], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( arr ), [], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Float64Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'row-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10.0; + } +}); + +tape( 'the function supports empty arrays', function test( t ) { + var expected; + var arr; + + expected = new Float64Array( 0 ); + + arr = fullBy( 'float64', [ 2, 0, 2 ], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 0, 2 ], 'returns expected value' ); + t.strictEqual( instanceOf( getData( arr ), Float64Array ), true, 'returns expected value' ); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + t.strictEqual( getOrder( arr ), 'row-major', 'returns expected value' ); + + t.end(); + + function clbk() { + return 10.0; + } +}); + +tape( 'the function invokes the callback with the current array element indices', function test( t ) { + var expected; + var indices; + var arr; + + indices = []; + + arr = fullBy( 'float64', [ 3, 1, 2 ], 'row-major', clbk ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + + expected = [ + [ 0, 0, 0 ], + [ 0, 0, 1 ], + [ 1, 0, 0 ], + [ 1, 0, 1 ], + [ 2, 0, 0 ], + [ 2, 0, 1 ] + ]; + t.deepEqual( indices, expected, 'returns expected value' ); + t.end(); + + function clbk( idx ) { + indices.push( idx ); + return 10.0; + } +}); + +tape( 'the function supports providing an execution context', function test( t ) { + var expected; + var indices; + var arr; + var ctx; + + indices = []; + ctx = { + 'scalar': 10.0 + }; + + arr = fullBy( 'float64', [ 3, 1, 2 ], 'row-major', clbk, ctx ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + + expected = new Float64Array([ + 10.0, + 10.0, + 10.0, + 10.0, + 10.0, + 10.0 + ]); + t.deepEqual( getData( arr ), expected, 'returns expected value' ); + + expected = [ + [ 0, 0, 0 ], + [ 0, 0, 1 ], + [ 1, 0, 0 ], + [ 1, 0, 1 ], + [ 2, 0, 0 ], + [ 2, 0, 1 ] + ]; + t.deepEqual( indices, expected, 'returns expected value' ); + t.end(); + + function clbk( idx ) { + indices.push( idx ); + return this.scalar; // eslint-disable-line no-invalid-this + } +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/lib/index.js index ff8c1d9693c0..5a9e66489d95 100644 --- a/lib/node_modules/@stdlib/ndarray/base/lib/index.js +++ b/lib/node_modules/@stdlib/ndarray/base/lib/index.js @@ -670,6 +670,15 @@ setReadOnly( ns, 'scalar2ndarrayLike', require( '@stdlib/ndarray/base/from-scala */ setReadOnly( ns, 'full', require( '@stdlib/ndarray/base/full' ) ); +/** +* @name fullBy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/ndarray/base/full-by} +*/ +setReadOnly( ns, 'fullBy', require( '@stdlib/ndarray/base/full-by' ) ); + /** * @name includes * @memberof ns @@ -1138,6 +1147,15 @@ setReadOnly( ns, 'reverse', require( '@stdlib/ndarray/base/reverse' ) ); */ setReadOnly( ns, 'reverseDimension', require( '@stdlib/ndarray/base/reverse-dimension' ) ); +/** +* @name rotr90 +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/ndarray/base/rotr90} +*/ +setReadOnly( ns, 'rotr90', require( '@stdlib/ndarray/base/rotr90' ) ); + /** * @name serializeMetaData * @memberof ns @@ -1624,6 +1642,15 @@ setReadOnly( ns, 'unaryStrided1dDispatchFactory', require( '@stdlib/ndarray/base */ setReadOnly( ns, 'unaryBlockSize', require( '@stdlib/ndarray/base/unary-tiling-block-size' ) ); +/** +* @name unflatten +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/ndarray/base/unflatten} +*/ +setReadOnly( ns, 'unflatten', require( '@stdlib/ndarray/base/unflatten' ) ); + /** * @name unflattenShape * @memberof ns diff --git a/lib/node_modules/@stdlib/ndarray/base/rotr90/README.md b/lib/node_modules/@stdlib/ndarray/base/rotr90/README.md new file mode 100644 index 000000000000..87301db11274 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/rotr90/README.md @@ -0,0 +1,155 @@ + + +# rotr90 + +> Rotate a matrix (or a stack of matrices) 90 degrees clockwise. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var rotr90 = require( '@stdlib/ndarray/base/rotr90' ); +``` + +#### rotr90( x, k, writable ) + +Rotates a matrix (or a stack of matrices) 90 degrees clockwise. + +```javascript +var array = require( '@stdlib/ndarray/array' ); + +var x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); +// returns [ [ 1, 2 ], [ 3, 4 ] ] + +var y = rotr90( x, 1, false ); +// returns [ [ 3, 1 ], [ 4, 2 ] ] +``` + +The function accepts the following arguments: + +- **x**: input ndarray. +- **k**: number of times to rotate by 90 degrees. Positive values rotate clockwise. Negative values rotate counterclockwise. +- **writable**: boolean indicating whether a returned ndarray should be writable. + +
+ + + + + +
+ +## Notes + +- The `writable` parameter **only** applies to ndarray constructors supporting **read-only** instances. +- If `k > 0`, the function rotates the matrix clockwise. +- If `k < 0`, the function rotates the matrix counterclockwise. +- The returned ndarray is a **view** of the input ndarray. Accordingly, writing to the original ndarray will **mutate** the returned ndarray and vice versa. +- If provided an ndarray with fewer than two dimensions, the function does not perform rotation and simply returns a new view of the input ndarray. + +
+ + + + + +
+ +## Examples + + + +```javascript +var array = require( '@stdlib/ndarray/array' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var rotr90 = require( '@stdlib/ndarray/base/rotr90' ); + +// Create a 2x3 matrix: +var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] ); + +// Rotate 90 degrees clockwise: +var y = rotr90( x, 1, false ); +var arr = ndarray2array( y ); +// returns [ [ 4, 1 ], [ 5, 2 ], [ 6, 3 ] ] + +// Rotate 180 degrees: +y = rotr90( x, 2, false ); +arr = ndarray2array( y ); +// returns [ [ 6, 5, 4 ], [ 3, 2, 1 ] ] + +// Rotate 270 degrees clockwise (equivalent to 90 degrees counterclockwise): +y = rotr90( x, 3, false ); +arr = ndarray2array( y ); +// returns [ [ 3, 6 ], [ 2, 5 ], [ 1, 4 ] ] + +// Rotate 360 degrees (equivalent to no rotation): +y = rotr90( x, 4, false ); +arr = ndarray2array( y ); +// returns [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] + +// Rotate 90 degrees counterclockwise (equivalent to 270 degrees clockwise): +y = rotr90( x, -1, false ); +arr = ndarray2array( y ); +// returns [ [ 3, 6 ], [ 2, 5 ], [ 1, 4 ] ] +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ + + + + +
+ + diff --git a/lib/node_modules/@stdlib/ndarray/base/rotr90/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/base/rotr90/benchmark/benchmark.js new file mode 100644 index 000000000000..7c791d963ac7 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/rotr90/benchmark/benchmark.js @@ -0,0 +1,272 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var baseEmpty = require( '@stdlib/ndarray/base/empty' ); +var empty = require( '@stdlib/ndarray/empty' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var rotr90 = require( './../lib' ); + + +// MAIN // + +bench( format( '%s::2d,base', pkg ), function benchmark( b ) { + var values; + var v; + var i; + + values = [ + baseEmpty( 'float64', [ 2, 2 ], 'row-major' ), + baseEmpty( 'float32', [ 2, 2 ], 'row-major' ), + baseEmpty( 'int32', [ 2, 2 ], 'row-major' ), + baseEmpty( 'complex128', [ 2, 2 ], 'row-major' ), + baseEmpty( 'generic', [ 2, 2 ], 'row-major' ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = rotr90( values[ i%values.length ], 1, false ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( !isndarrayLike( v ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::2d,non-base', pkg ), function benchmark( b ) { + var values; + var v; + var i; + + /* eslint-disable object-curly-newline, stdlib/line-closing-bracket-spacing */ + + values = [ + empty( [ 2, 2 ], { 'dtype': 'float64' } ), + empty( [ 2, 2 ], { 'dtype': 'float32' } ), + empty( [ 2, 2 ], { 'dtype': 'int32' } ), + empty( [ 2, 2 ], { 'dtype': 'complex128' } ), + empty( [ 2, 2 ], { 'dtype': 'generic' } ) + ]; + + /* eslint-enable object-curly-newline, stdlib/line-closing-bracket-spacing */ + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = rotr90( values[ i%values.length ], 1, false ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( !isndarrayLike( v ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::3d,base', pkg ), function benchmark( b ) { + var values; + var v; + var i; + + values = [ + baseEmpty( 'float64', [ 2, 2, 2 ], 'row-major' ), + baseEmpty( 'float32', [ 2, 2, 2 ], 'row-major' ), + baseEmpty( 'int32', [ 2, 2, 2 ], 'row-major' ), + baseEmpty( 'complex128', [ 2, 2, 2 ], 'row-major' ), + baseEmpty( 'generic', [ 2, 2, 2 ], 'row-major' ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = rotr90( values[ i%values.length ], 1, false ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( !isndarrayLike( v ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::3d,non-base', pkg ), function benchmark( b ) { + var values; + var v; + var i; + + /* eslint-disable object-curly-newline, stdlib/line-closing-bracket-spacing */ + + values = [ + empty( [ 2, 2, 2 ], { 'dtype': 'float64' } ), + empty( [ 2, 2, 2 ], { 'dtype': 'float32' } ), + empty( [ 2, 2, 2 ], { 'dtype': 'int32' } ), + empty( [ 2, 2, 2 ], { 'dtype': 'complex128' } ), + empty( [ 2, 2, 2 ], { 'dtype': 'generic' } ) + ]; + + /* eslint-enable object-curly-newline, stdlib/line-closing-bracket-spacing */ + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = rotr90( values[ i%values.length ], 1, false ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( !isndarrayLike( v ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::4d,base', pkg ), function benchmark( b ) { + var values; + var v; + var i; + + values = [ + baseEmpty( 'float64', [ 2, 2, 2, 2 ], 'row-major' ), + baseEmpty( 'float32', [ 2, 2, 2, 2 ], 'row-major' ), + baseEmpty( 'int32', [ 2, 2, 2, 2 ], 'row-major' ), + baseEmpty( 'complex128', [ 2, 2, 2, 2 ], 'row-major' ), + baseEmpty( 'generic', [ 2, 2, 2, 2 ], 'row-major' ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = rotr90( values[ i%values.length ], 1, false ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( !isndarrayLike( v ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::4d,non-base', pkg ), function benchmark( b ) { + var values; + var v; + var i; + + /* eslint-disable object-curly-newline, stdlib/line-closing-bracket-spacing */ + + values = [ + empty( [ 2, 2, 2, 2 ], { 'dtype': 'float64' } ), + empty( [ 2, 2, 2, 2 ], { 'dtype': 'float32' } ), + empty( [ 2, 2, 2, 2 ], { 'dtype': 'int32' } ), + empty( [ 2, 2, 2, 2 ], { 'dtype': 'complex128' } ), + empty( [ 2, 2, 2, 2 ], { 'dtype': 'generic' } ) + ]; + + /* eslint-enable object-curly-newline, stdlib/line-closing-bracket-spacing */ + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = rotr90( values[ i%values.length ], 1, false ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( !isndarrayLike( v ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::5d,base', pkg ), function benchmark( b ) { + var values; + var v; + var i; + + values = [ + baseEmpty( 'float64', [ 2, 2, 2, 2, 2 ], 'row-major' ), + baseEmpty( 'float32', [ 2, 2, 2, 2, 2 ], 'row-major' ), + baseEmpty( 'int32', [ 2, 2, 2, 2, 2 ], 'row-major' ), + baseEmpty( 'complex128', [ 2, 2, 2, 2, 2 ], 'row-major' ), + baseEmpty( 'generic', [ 2, 2, 2, 2, 2 ], 'row-major' ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = rotr90( values[ i%values.length ], 1, false ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( !isndarrayLike( v ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::5d,non-base', pkg ), function benchmark( b ) { + var values; + var v; + var i; + + /* eslint-disable object-curly-newline, stdlib/line-closing-bracket-spacing */ + + values = [ + empty( [ 2, 2, 2, 2, 2 ], { 'dtype': 'float64' } ), + empty( [ 2, 2, 2, 2, 2 ], { 'dtype': 'float32' } ), + empty( [ 2, 2, 2, 2, 2 ], { 'dtype': 'int32' } ), + empty( [ 2, 2, 2, 2, 2 ], { 'dtype': 'complex128' } ), + empty( [ 2, 2, 2, 2, 2 ], { 'dtype': 'generic' } ) + ]; + + /* eslint-enable object-curly-newline, stdlib/line-closing-bracket-spacing */ + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = rotr90( values[ i%values.length ], 1, false ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( !isndarrayLike( v ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/rotr90/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/rotr90/docs/repl.txt new file mode 100644 index 000000000000..680a9844f460 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/rotr90/docs/repl.txt @@ -0,0 +1,45 @@ + +{{alias}}( x, k, writable ) + Rotates a matrix (or a stack of matrices) 90 degrees clockwise. + + If `k > 0`, the function rotates the matrix clockwise. If `k < 0`, the + function rotates the matrix counterclockwise. + + The returned ndarray is always a *view* of the input ndarray. Accordingly, + writing to the original ndarray will mutate the returned ndarray and vice + versa. + + If provided an ndarray with fewer than two dimensions, the function does not + perform a rotation and simply returns a new view of the input ndarray. + + Parameters + ---------- + x: ndarray + Input array. + + k: integer + Number of times to rotate by 90 degrees. + + writable: boolean + Boolean indicating whether a returned ndarray should be writable. This + parameter only applies to ndarray constructors which support read-only + instances. + + Returns + ------- + out: ndarray + Output array view. + + Examples + -------- + > var x = {{alias:@stdlib/ndarray/array}}( [ [ 1, 2 ], [ 3, 4 ] ] ) + [ [ 1, 2 ], [ 3, 4 ] ] + > var y = {{alias}}( x, 1, false ) + [ [ 3, 1 ], [ 4, 2 ] ] + > y = {{alias}}( x, 2, false ) + [ [ 4, 3 ], [ 2, 1 ] ] + > y = {{alias}}( x, 3, false ) + [ [ 2, 4 ], [ 1, 3 ] ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/ndarray/base/rotr90/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/base/rotr90/docs/types/index.d.ts new file mode 100644 index 000000000000..1c4c1a84b279 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/rotr90/docs/types/index.d.ts @@ -0,0 +1,47 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray } from '@stdlib/types/ndarray'; + +/** +* Rotates a matrix (or a stack of matrices) 90 degrees clockwise. +* +* @param x - input array +* @param k - number of times to rotate by 90 degrees +* @param writable - boolean indicating whether the returned ndarray should be writable +* @returns output array +* +* @example +* var array = require( '@stdlib/ndarray/array' ); +* +* var x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); +* // returns [ [ 1, 2 ], [ 3, 4 ] ] +* +* var y = rotr90( x, 1, false ); +* // returns [ [ 3, 1 ], [ 4, 2 ] ] +*/ +declare function rotr90 = typedndarray>( x: U, k: number, writable: boolean ): U; + + +// EXPORTS // + +export = rotr90; diff --git a/lib/node_modules/@stdlib/ndarray/base/rotr90/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/base/rotr90/docs/types/test.ts new file mode 100644 index 000000000000..b46b31a0d0ee --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/rotr90/docs/types/test.ts @@ -0,0 +1,90 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import zeros = require( '@stdlib/ndarray/base/zeros' ); +import rotr90 = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const sh = [ 2, 2 ]; + const ord = 'row-major'; + + rotr90( zeros( 'float64', sh, ord ), 1, false ); // $ExpectType float64ndarray + rotr90( zeros( 'float32', sh, ord ), 1, false ); // $ExpectType float32ndarray + rotr90( zeros( 'complex128', sh, ord ), 1, false ); // $ExpectType complex128ndarray + rotr90( zeros( 'complex64', sh, ord ), 1, false ); // $ExpectType complex64ndarray + rotr90( zeros( 'int32', sh, ord ), 1, false ); // $ExpectType int32ndarray + rotr90( zeros( 'int16', sh, ord ), 1, false ); // $ExpectType int16ndarray + rotr90( zeros( 'int8', sh, ord ), 1, false ); // $ExpectType int8ndarray + rotr90( zeros( 'uint32', sh, ord ), 1, false ); // $ExpectType uint32ndarray + rotr90( zeros( 'uint16', sh, ord ), 1, false ); // $ExpectType uint16ndarray + rotr90( zeros( 'uint8', sh, ord ), 1, false ); // $ExpectType uint8ndarray + rotr90( zeros( 'uint8c', sh, ord ), 1, false ); // $ExpectType uint8cndarray + rotr90( zeros( 'generic', sh, ord ), 1, false ); // $ExpectType genericndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an ndarray having a recognized/supported data type... +{ + rotr90( '10', 1, false ); // $ExpectError + rotr90( 10, 1, false ); // $ExpectError + rotr90( false, 1, false ); // $ExpectError + rotr90( true, 1, false ); // $ExpectError + rotr90( null, 1, false ); // $ExpectError + rotr90( void 0, 1, false ); // $ExpectError + rotr90( [], 1, false ); // $ExpectError + rotr90( {}, 1, false ); // $ExpectError + rotr90( ( x: number ): number => x, 1, false ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = zeros( 'float64', [ 2, 2 ], 'row-major' ); + + rotr90( x, '10', false ); // $ExpectError + rotr90( x, false, false ); // $ExpectError + rotr90( x, true, false ); // $ExpectError + rotr90( x, null, false ); // $ExpectError + rotr90( x, void 0, false ); // $ExpectError + rotr90( x, [], false ); // $ExpectError + rotr90( x, {}, false ); // $ExpectError + rotr90( x, ( x: number ): number => x, false ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a boolean... +{ + const x = zeros( 'float64', [ 2, 2 ], 'row-major' ); + + rotr90( x, 1, '10' ); // $ExpectError + rotr90( x, 1, 10 ); // $ExpectError + rotr90( x, 1, null ); // $ExpectError + rotr90( x, 1, void 0 ); // $ExpectError + rotr90( x, 1, [] ); // $ExpectError + rotr90( x, 1, {} ); // $ExpectError + rotr90( x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + rotr90(); // $ExpectError + rotr90( zeros( 'float64', [ 2, 2 ], 'row-major' ) ); // $ExpectError + rotr90( zeros( 'float64', [ 2, 2 ], 'row-major' ), 1 ); // $ExpectError + rotr90( zeros( 'float64', [ 2, 2 ], 'row-major' ), 1, false, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ndarray/base/rotr90/examples/index.js b/lib/node_modules/@stdlib/ndarray/base/rotr90/examples/index.js new file mode 100644 index 000000000000..bf9d2b615260 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/rotr90/examples/index.js @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var array = require( '@stdlib/ndarray/array' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var rotr90 = require( './../lib' ); + +// Create a 2x3 matrix: +var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] ); + +// Rotate 90 degrees clockwise: +var y = rotr90( x, 1, false ); +console.log( ndarray2array( y ) ); +// => [ [ 4, 1 ], [ 5, 2 ], [ 6, 3 ] ] + +// Rotate 180 degrees: +y = rotr90( x, 2, false ); +console.log( ndarray2array( y ) ); +// => [ [ 6, 5, 4 ], [ 3, 2, 1 ] ] + +// Rotate 270 degrees clockwise: +y = rotr90( x, 3, false ); +console.log( ndarray2array( y ) ); +// => [ [ 3, 6 ], [ 2, 5 ], [ 1, 4 ] ] + +// Rotate 360 degrees: +y = rotr90( x, 4, false ); +console.log( ndarray2array( y ) ); +// => [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] + +// Rotate 90 degrees counterclockwise (equivalent to k=3): +y = rotr90( x, -1, false ); +console.log( ndarray2array( y ) ); +// => [ [ 3, 6 ], [ 2, 5 ], [ 1, 4 ] ] diff --git a/lib/node_modules/@stdlib/ndarray/base/rotr90/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/rotr90/lib/index.js new file mode 100644 index 000000000000..8647408a8d05 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/rotr90/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Rotate a matrix (or a stack of matrices) 90 degrees clockwise. +* +* @module @stdlib/ndarray/base/rotr90 +* +* @example +* var array = require( '@stdlib/ndarray/array' ); +* var rotr90 = require( '@stdlib/ndarray/base/rotr90' ); +* +* var x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); +* // returns [ [ 1, 2 ], [ 3, 4 ] ] +* +* var y = rotr90( x, 1, false ); +* // returns [ [ 3, 1 ], [ 4, 2 ] ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ndarray/base/rotr90/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/rotr90/lib/main.js new file mode 100644 index 000000000000..b870d99e78ca --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/rotr90/lib/main.js @@ -0,0 +1,108 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var getDType = require( '@stdlib/ndarray/base/dtype' ); +var getShape = require( '@stdlib/ndarray/base/shape' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getOrder = require( '@stdlib/ndarray/base/order' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); + + +// MAIN // + +/** +* Rotates a matrix (or a stack of matrices) 90 degrees clockwise. +* +* @param {ndarray} x - input array +* @param {integer} k - number of times to rotate by 90 degrees +* @param {boolean} writable - boolean indicating whether the returned ndarray should be writable +* @returns {ndarray} ndarray view +* +* @example +* var array = require( '@stdlib/ndarray/array' ); +* +* var x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); +* // returns [ [ 1, 2 ], [ 3, 4 ] ] +* +* var y = rotr90( x, 1, false ); +* // returns [ [ 3, 1 ], [ 4, 2 ] ] +*/ +function rotr90( x, k, writable ) { + var offset; + var sh; + var st; + var sm; + var sn; + var M; + var N; + var d; + + sh = getShape( x, true ); + d = sh.length; + st = getStrides( x, true ); + offset = getOffset( x ); + + if ( d >= 2 ) { + // Normalize `k` to the interval [0, 3]: + k %= 4; + if ( k < 0 ) { + k += 4; + } + // Cache the original shape and stride values for the last two dimensions: + M = sh[ d-2 ]; + N = sh[ d-1 ]; + sm = st[ d-2 ]; + sn = st[ d-1 ]; + + // Case: rotate 90 deg clockwise + if ( k === 1 ) { + sh[ d-2 ] = N; + sh[ d-1 ] = M; + st[ d-2 ] = sn; + st[ d-1 ] = -sm; + offset += ( M - 1 ) * sm; + } + // Case: rotate 180 deg clockwise (i.e., reverse both dimensions) + else if ( k === 2 ) { + st[ d-2 ] = -sm; + st[ d-1 ] = -sn; + offset += ( ( M - 1 ) * sm ) + ( ( N - 1 ) * sn ); + } + // Case: rotate 270 deg clockwise + else if ( k === 3 ) { + sh[ d-2 ] = N; + sh[ d-1 ] = M; + st[ d-2 ] = -sn; + st[ d-1 ] = sm; + offset += ( N - 1 ) * sn; + } + } + return new x.constructor( getDType( x ), getData( x ), sh, st, offset, getOrder( x ), { // eslint-disable-line max-len + 'readonly': !writable + }); +} + + +// EXPORTS // + +module.exports = rotr90; diff --git a/lib/node_modules/@stdlib/ndarray/base/rotr90/package.json b/lib/node_modules/@stdlib/ndarray/base/rotr90/package.json new file mode 100644 index 000000000000..2ed04b6b5fea --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/rotr90/package.json @@ -0,0 +1,66 @@ +{ + "name": "@stdlib/ndarray/base/rotr90", + "version": "0.0.0", + "description": "Rotate a matrix (or a stack of matrices) 90 degrees clockwise.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "types", + "base", + "data", + "structure", + "ndarray", + "matrix", + "rotate", + "rotation", + "rotr90", + "clockwise", + "view" + ] +} diff --git a/lib/node_modules/@stdlib/ndarray/base/rotr90/test/test.js b/lib/node_modules/@stdlib/ndarray/base/rotr90/test/test.js new file mode 100644 index 000000000000..7022e7acede5 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/rotr90/test/test.js @@ -0,0 +1,604 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var Float32Array = require( '@stdlib/array/float32' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); +var instanceOf = require( '@stdlib/assert/instance-of' ); +var isReadOnly = require( '@stdlib/ndarray/base/assert/is-read-only' ); +var base = require( '@stdlib/ndarray/base/ctor' ); +var ndarray = require( '@stdlib/ndarray/ctor' ); +var array = require( '@stdlib/ndarray/array' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var getDType = require( '@stdlib/ndarray/dtype' ); +var getOrder = require( '@stdlib/ndarray/order' ); +var getShape = require( '@stdlib/ndarray/shape' ); +var getStrides = require( '@stdlib/ndarray/strides' ); +var rotr90 = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof rotr90, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a view if provided an ndarray having fewer than two dimensions (0d)', function test( t ) { + var arr; + var x; + + x = new ndarray( 'float64', new Float64Array( [ 5.0 ] ), [], [ 0 ], 0, 'row-major' ); + arr = rotr90( x, 1, false ); + t.notEqual( arr, x, 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + t.strictEqual( arr.get(), 5.0, 'returns expected value' ); + t.deepEqual( getShape( arr ), [], 'returns expected value' ); + t.deepEqual( getStrides( arr ), [ 0 ], 'returns expected value' ); + t.strictEqual( getOrder( arr ), getOrder( x ), 'returns expected value' ); + + x = new base( 'float64', new Float64Array( [ 5.0 ] ), [], [ 0 ], 0, 'row-major' ); + arr = rotr90( x, 1, false ); + t.notEqual( arr, x, 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + t.strictEqual( arr.get(), 5.0, 'returns expected value' ); + t.deepEqual( getShape( arr ), [], 'returns expected value' ); + t.deepEqual( getStrides( arr ), [ 0 ], 'returns expected value' ); + t.strictEqual( getOrder( arr ), getOrder( x ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a view if provided an ndarray having fewer than two dimensions (1d)', function test( t ) { + var arr; + var x; + + x = new ndarray( 'float64', new Float64Array( [ 1.0, 2.0, 3.0 ] ), [ 3 ], [ 1 ], 0, 'row-major' ); + arr = rotr90( x, 1, false ); + t.notEqual( arr, x, 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( arr ), [ 1.0, 2.0, 3.0 ], 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 3 ], 'returns expected value' ); + t.deepEqual( getStrides( arr ), [ 1 ], 'returns expected value' ); + t.strictEqual( getOrder( arr ), getOrder( x ), 'returns expected value' ); + + x = new base( 'float64', new Float64Array( [ 1.0, 2.0, 3.0 ] ), [ 3 ], [ 1 ], 0, 'row-major' ); + arr = rotr90( x, 1, false ); + t.notEqual( arr, x, 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( arr ), [ 1.0, 2.0, 3.0 ], 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 3 ], 'returns expected value' ); + t.deepEqual( getStrides( arr ), [ 1 ], 'returns expected value' ); + t.strictEqual( getOrder( arr ), getOrder( x ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function rotates a matrix clockwise for all values of k (dtype=float64, base, row-major)', function test( t ) { + var expected; + var arr; + var buf; + var x; + + buf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + x = new base( 'float64', buf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' ); + + // k=0 (no rotation): + arr = rotr90( x, 0, false ); + t.strictEqual( instanceOf( arr, base ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), String( getDType( x ) ), 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 3 ], 'returns expected value' ); + t.deepEqual( getStrides( arr ), [ 3, 1 ], 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + t.strictEqual( getOrder( arr ), getOrder( x ), 'returns expected value' ); + t.notEqual( arr, x, 'returns expected value' ); + expected = [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=1 (90 degrees clockwise): + arr = rotr90( x, 1, false ); + t.strictEqual( instanceOf( arr, base ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), String( getDType( x ) ), 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 3, 2 ], 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ [ 4.0, 1.0 ], [ 5.0, 2.0 ], [ 6.0, 3.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=2 (180 degrees): + arr = rotr90( x, 2, false ); + t.strictEqual( instanceOf( arr, base ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), String( getDType( x ) ), 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 3 ], 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ [ 6.0, 5.0, 4.0 ], [ 3.0, 2.0, 1.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=3 (270 degrees clockwise): + arr = rotr90( x, 3, false ); + t.strictEqual( instanceOf( arr, base ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), String( getDType( x ) ), 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 3, 2 ], 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ [ 3.0, 6.0 ], [ 2.0, 5.0 ], [ 1.0, 4.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function rotates a matrix clockwise for all values of k (dtype=float64, base, column-major)', function test( t ) { + var expected; + var arr; + var buf; + var x; + + buf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + x = new base( 'float64', buf, [ 2, 3 ], [ 1, 2 ], 0, 'column-major' ); + + // In column-major with strides [1,2], x = [ [ 1.0, 3.0, 5.0 ], [ 2.0, 4.0, 6.0 ] ] + + // k=1: + arr = rotr90( x, 1, false ); + t.strictEqual( instanceOf( arr, base ), true, 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 3, 2 ], 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ [ 2.0, 1.0 ], [ 4.0, 3.0 ], [ 6.0, 5.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=2: + arr = rotr90( x, 2, false ); + t.deepEqual( getShape( arr ), [ 2, 3 ], 'returns expected value' ); + expected = [ [ 6.0, 4.0, 2.0 ], [ 5.0, 3.0, 1.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=3: + arr = rotr90( x, 3, false ); + t.deepEqual( getShape( arr ), [ 3, 2 ], 'returns expected value' ); + expected = [ [ 5.0, 6.0 ], [ 3.0, 4.0 ], [ 1.0, 2.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function rotates a matrix clockwise for all values of k (dtype=float64, non-base)', function test( t ) { + var expected; + var arr; + var buf; + var x; + + buf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + x = array( buf, { + 'shape': [ 2, 3 ], + 'dtype': 'float64' + }); + + // k=0: + arr = rotr90( x, 0, false ); + t.strictEqual( instanceOf( arr, ndarray ), true, 'returns expected value' ); + t.strictEqual( isReadOnly( arr ), true, 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=1: + arr = rotr90( x, 1, false ); + t.strictEqual( isReadOnly( arr ), true, 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ [ 4.0, 1.0 ], [ 5.0, 2.0 ], [ 6.0, 3.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=2: + arr = rotr90( x, 2, false ); + t.strictEqual( isReadOnly( arr ), true, 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ [ 6.0, 5.0, 4.0 ], [ 3.0, 2.0, 1.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=3: + arr = rotr90( x, 3, false ); + t.strictEqual( isReadOnly( arr ), true, 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ [ 3.0, 6.0 ], [ 2.0, 5.0 ], [ 1.0, 4.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function rotates a matrix clockwise for all values of k (dtype=float32)', function test( t ) { + var expected; + var arr; + var buf; + var x; + + buf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + x = new base( 'float32', buf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' ); + + // k=1: + arr = rotr90( x, 1, false ); + t.strictEqual( instanceOf( arr, base ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), String( getDType( x ) ), 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 3, 2 ], 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ [ 4.0, 1.0 ], [ 5.0, 2.0 ], [ 6.0, 3.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=2: + arr = rotr90( x, 2, false ); + t.deepEqual( getShape( arr ), [ 2, 3 ], 'returns expected value' ); + expected = [ [ 6.0, 5.0, 4.0 ], [ 3.0, 2.0, 1.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=3: + arr = rotr90( x, 3, false ); + t.deepEqual( getShape( arr ), [ 3, 2 ], 'returns expected value' ); + expected = [ [ 3.0, 6.0 ], [ 2.0, 5.0 ], [ 1.0, 4.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // Non-base, k=1: + x = array( buf, { + 'shape': [ 2, 3 ], + 'dtype': 'float32' + }); + arr = rotr90( x, 1, false ); + t.strictEqual( isReadOnly( arr ), true, 'returns expected value' ); + expected = [ [ 4.0, 1.0 ], [ 5.0, 2.0 ], [ 6.0, 3.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // Non-base, k=1, writable: + arr = rotr90( x, 1, true ); + t.strictEqual( isReadOnly( arr ), false, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function rotates a matrix clockwise (dtype=complex128, base)', function test( t ) { + var arr; + var buf; + var v; + var x; + + buf = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 4.0, 4.0 ] ); + x = new base( 'complex128', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + // k=1 (90 degrees clockwise): + arr = rotr90( x, 1, false ); + t.strictEqual( instanceOf( arr, base ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), String( getDType( x ) ), 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + + v = arr.get( 0, 0 ); + t.strictEqual( real( v ), 3.0, 'returns expected value' ); + t.strictEqual( imag( v ), 3.0, 'returns expected value' ); + v = arr.get( 0, 1 ); + t.strictEqual( real( v ), 1.0, 'returns expected value' ); + t.strictEqual( imag( v ), 1.0, 'returns expected value' ); + v = arr.get( 1, 0 ); + t.strictEqual( real( v ), 4.0, 'returns expected value' ); + t.strictEqual( imag( v ), 4.0, 'returns expected value' ); + v = arr.get( 1, 1 ); + t.strictEqual( real( v ), 2.0, 'returns expected value' ); + t.strictEqual( imag( v ), 2.0, 'returns expected value' ); + + // k=2: + arr = rotr90( x, 2, false ); + v = arr.get( 0, 0 ); + t.strictEqual( real( v ), 4.0, 'returns expected value' ); + t.strictEqual( imag( v ), 4.0, 'returns expected value' ); + v = arr.get( 0, 1 ); + t.strictEqual( real( v ), 3.0, 'returns expected value' ); + t.strictEqual( imag( v ), 3.0, 'returns expected value' ); + v = arr.get( 1, 0 ); + t.strictEqual( real( v ), 2.0, 'returns expected value' ); + t.strictEqual( imag( v ), 2.0, 'returns expected value' ); + v = arr.get( 1, 1 ); + t.strictEqual( real( v ), 1.0, 'returns expected value' ); + t.strictEqual( imag( v ), 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function rotates a matrix clockwise (dtype=complex64, base)', function test( t ) { + var arr; + var buf; + var v; + var x; + + buf = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 4.0, 4.0 ] ); + x = new base( 'complex64', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + // k=1 (90 degrees clockwise): + arr = rotr90( x, 1, false ); + t.strictEqual( instanceOf( arr, base ), true, 'returns expected value' ); + t.strictEqual( String( getDType( arr ) ), String( getDType( x ) ), 'returns expected value' ); + t.deepEqual( getShape( arr ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + + v = arr.get( 0, 0 ); + t.strictEqual( realf( v ), 3.0, 'returns expected value' ); + t.strictEqual( imagf( v ), 3.0, 'returns expected value' ); + v = arr.get( 0, 1 ); + t.strictEqual( realf( v ), 1.0, 'returns expected value' ); + t.strictEqual( imagf( v ), 1.0, 'returns expected value' ); + v = arr.get( 1, 0 ); + t.strictEqual( realf( v ), 4.0, 'returns expected value' ); + t.strictEqual( imagf( v ), 4.0, 'returns expected value' ); + v = arr.get( 1, 1 ); + t.strictEqual( realf( v ), 2.0, 'returns expected value' ); + t.strictEqual( imagf( v ), 2.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function rotates a matrix clockwise for all values of k (dtype=generic)', function test( t ) { + var expected; + var arr; + var buf; + var x; + + buf = [ 1, 2, 3, 4, 5, 6 ]; + x = new base( 'generic', buf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' ); + + // k=0: + arr = rotr90( x, 0, false ); + t.strictEqual( instanceOf( arr, base ), true, 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=1: + arr = rotr90( x, 1, false ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ [ 4, 1 ], [ 5, 2 ], [ 6, 3 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=2: + arr = rotr90( x, 2, false ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ [ 6, 5, 4 ], [ 3, 2, 1 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=3: + arr = rotr90( x, 3, false ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ [ 3, 6 ], [ 2, 5 ], [ 1, 4 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // Non-base, k=1: + x = array( buf, { + 'shape': [ 2, 3 ], + 'dtype': 'generic' + }); + arr = rotr90( x, 1, false ); + t.strictEqual( isReadOnly( arr ), true, 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ [ 4, 1 ], [ 5, 2 ], [ 6, 3 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // Non-base, k=1, writable: + arr = rotr90( x, 1, true ); + t.strictEqual( isReadOnly( arr ), false, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative and large values of k', function test( t ) { + var expected; + var arr; + var buf; + var x; + + buf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + x = new base( 'float64', buf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' ); + + // k=-1 (90 degrees counterclockwise): + arr = rotr90( x, -1, false ); + expected = [ [ 3.0, 6.0 ], [ 2.0, 5.0 ], [ 1.0, 4.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=-2: + arr = rotr90( x, -2, false ); + expected = [ [ 6.0, 5.0, 4.0 ], [ 3.0, 2.0, 1.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=-3: + arr = rotr90( x, -3, false ); + expected = [ [ 4.0, 1.0 ], [ 5.0, 2.0 ], [ 6.0, 3.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=-4: + arr = rotr90( x, -4, false ); + expected = [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=5 (same as k=1): + arr = rotr90( x, 5, false ); + expected = [ [ 4.0, 1.0 ], [ 5.0, 2.0 ], [ 6.0, 3.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=8 (same as k=0): + arr = rotr90( x, 8, false ); + expected = [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=-5 (same as k=-1): + arr = rotr90( x, -5, false ); + expected = [ [ 3.0, 6.0 ], [ 2.0, 5.0 ], [ 1.0, 4.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=-8 (same as k=0): + arr = rotr90( x, -8, false ); + expected = [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a stack of matrices for all values of k', function test( t ) { + var expected; + var arr; + var buf; + var x; + + buf = [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 ]; + x = new base( 'generic', buf, [ 2, 2, 3 ], [ 6, 3, 1 ], 0, 'row-major' ); + + // k=0: + arr = rotr90( x, 0, false ); + t.deepEqual( getShape( arr ), [ 2, 2, 3 ], 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ + [ [ 1, 2, 3 ], [ 4, 5, 6 ] ], + [ [ 7, 8, 9 ], [ 10, 11, 12 ] ] + ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=1: + arr = rotr90( x, 1, false ); + t.deepEqual( getShape( arr ), [ 2, 3, 2 ], 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ + [ [ 4, 1 ], [ 5, 2 ], [ 6, 3 ] ], + [ [ 10, 7 ], [ 11, 8 ], [ 12, 9 ] ] + ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=2: + arr = rotr90( x, 2, false ); + t.deepEqual( getShape( arr ), [ 2, 2, 3 ], 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ + [ [ 6, 5, 4 ], [ 3, 2, 1 ] ], + [ [ 12, 11, 10 ], [ 9, 8, 7 ] ] + ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=3: + arr = rotr90( x, 3, false ); + t.deepEqual( getShape( arr ), [ 2, 3, 2 ], 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + expected = [ + [ [ 3, 6 ], [ 2, 5 ], [ 1, 4 ] ], + [ [ 9, 12 ], [ 8, 11 ], [ 7, 10 ] ] + ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `writable` parameter', function test( t ) { + var arr; + var buf; + var x; + + buf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + x = array( buf, { + 'shape': [ 2, 2 ], + 'dtype': 'float64' + }); + + // k=0: + arr = rotr90( x, 0, false ); + t.strictEqual( isReadOnly( arr ), true, 'returns expected value' ); + arr = rotr90( x, 0, true ); + t.strictEqual( isReadOnly( arr ), false, 'returns expected value' ); + + // k=1: + arr = rotr90( x, 1, false ); + t.strictEqual( isReadOnly( arr ), true, 'returns expected value' ); + arr = rotr90( x, 1, true ); + t.strictEqual( isReadOnly( arr ), false, 'returns expected value' ); + + // k=2: + arr = rotr90( x, 2, false ); + t.strictEqual( isReadOnly( arr ), true, 'returns expected value' ); + arr = rotr90( x, 2, true ); + t.strictEqual( isReadOnly( arr ), false, 'returns expected value' ); + + // k=3: + arr = rotr90( x, 3, false ); + t.strictEqual( isReadOnly( arr ), true, 'returns expected value' ); + arr = rotr90( x, 3, true ); + t.strictEqual( isReadOnly( arr ), false, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a non-zero offset', function test( t ) { + var expected; + var arr; + var buf; + var x; + + buf = new Float64Array( [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + x = new base( 'float64', buf, [ 2, 3 ], [ 3, 1 ], 2, 'row-major' ); + + // k=0: + arr = rotr90( x, 0, false ); + expected = [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=1: + arr = rotr90( x, 1, false ); + expected = [ [ 4.0, 1.0 ], [ 5.0, 2.0 ], [ 6.0, 3.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=2: + arr = rotr90( x, 2, false ); + expected = [ [ 6.0, 5.0, 4.0 ], [ 3.0, 2.0, 1.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + // k=3: + arr = rotr90( x, 3, false ); + expected = [ [ 3.0, 6.0 ], [ 2.0, 5.0 ], [ 1.0, 4.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'rotating four times returns the original arrangement', function test( t ) { + var expected; + var arr; + var buf; + var x; + + buf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + x = new base( 'float64', buf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' ); + + arr = rotr90( x, 1, false ); + arr = rotr90( arr, 1, false ); + arr = rotr90( arr, 1, false ); + arr = rotr90( arr, 1, false ); + + expected = [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ]; + t.deepEqual( ndarray2array( arr ), expected, 'returns expected value' ); + t.strictEqual( getData( arr ), getData( x ), 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/lib/main.js index cf583ea58c58..fb917087b16a 100644 --- a/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/lib/main.js +++ b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/lib/main.js @@ -20,9 +20,10 @@ // MODULES // -var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major-string' ); +var isRowMajorString = require( '@stdlib/ndarray/base/assert/is-row-major-string' ); var isSortedAscending = require( '@stdlib/array/base/assert/is-sorted-ascending' ); var toNormalizedIndices = require( '@stdlib/ndarray/base/to-unique-normalized-indices' ); +var strides2order = require( '@stdlib/ndarray/base/strides2order' ); var getDType = require( '@stdlib/ndarray/base/dtype' ); var getShape = require( '@stdlib/ndarray/base/shape' ); var getStrides = require( '@stdlib/ndarray/base/strides' ); @@ -91,19 +92,29 @@ function spreadDimensions( ndims, x, dims, writable ) { var ord; var sh; var st; + var N; var d; var S; var s; + var o; var i; var j; sh = getShape( x, false ); st = getStrides( x, false ); ord = getOrder( x ); - isrm = isRowMajor( ord ); - if ( sh.length > ndims ) { - throw new RangeError( format( 'invalid argument. First argument must be greater than or equal to the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `%d`.', sh.length, ndims ) ); + o = strides2order( st ); + if ( o === 0 || o === 3 ) { + // Fallback to stated layout when unable to infer the underlying physical layout: + isrm = isRowMajorString( ord ); + } else { + isrm = ( o === 1 ); + } + N = sh.length; + + if ( N > ndims ) { + throw new RangeError( format( 'invalid argument. First argument must be greater than or equal to the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `%d`.', N, ndims ) ); } // Resolve dimension indices... d = toNormalizedIndices( dims, ndims-1 ); @@ -113,14 +124,14 @@ function spreadDimensions( ndims, x, dims, writable ) { if ( d.length !== dims.length ) { throw new Error( format( 'invalid argument. Must provide unique dimension indices. Value: `[%s]`.', join( dims, ', ' ) ) ); } - if ( d.length !== sh.length ) { - throw new RangeError( format( 'invalid argument. Must provide the same number of dimension indices as the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `[%s]`.', sh.length, join( dims, ', ' ) ) ); + if ( d.length !== N ) { + throw new RangeError( format( 'invalid argument. Must provide the same number of dimension indices as the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `[%s]`.', N, join( dims, ', ' ) ) ); } if ( d.length && !isSortedAscending( d ) ) { throw new Error( format( 'invalid argument. Must provide dimension indices which resolve to nonnegative indices arranged in ascending order. Value: `[%s]`.', join( dims, ', ' ) ) ); } // When provided a zero-dimensional array, every expanded dimension is a singleton dimension having zero stride... - if ( sh.length === 0 ) { + if ( N === 0 ) { shape = ones( ndims ); strides = zeros( ndims ); } else { @@ -134,7 +145,7 @@ function spreadDimensions( ndims, x, dims, writable ) { S = sh[ j ]; s = st[ j ]; j += 1; - } else if ( j === sh.length ) { // append + } else if ( j === N ) { // append // We should only get here after exhausting all the dimension indices... S = 1; s = st[ j-1 ]; diff --git a/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/test/test.js b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/test/test.js index 652349c5260d..de5fa78e58b6 100644 --- a/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/test/test.js +++ b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/test/test.js @@ -156,7 +156,30 @@ tape( 'the function throws an error if not provided indices sorted in ascending } }); -tape( 'the function prepends singleton dimensions', function test( t ) { +tape( 'the function prepends singleton dimensions (1d)', function test( t ) { + var x; + var y; + + x = array( [ 1, 2, 3, 4 ] ); + + y = spreadDimensions( 3, x, [ 2 ], false ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 1, 1, 4 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), true, 'returns expected value' ); + + y = spreadDimensions( 3, x, [ 2 ], true ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 1, 1, 4 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function prepends singleton dimensions (2d)', function test( t ) { var x; var y; @@ -202,7 +225,30 @@ tape( 'the function prepends singleton dimensions (negative index)', function te t.end(); }); -tape( 'the function appends singleton dimensions', function test( t ) { +tape( 'the function appends singleton dimensions (1d)', function test( t ) { + var x; + var y; + + x = array( [ 1, 2, 3, 4 ] ); + + y = spreadDimensions( 3, x, [ 0 ], false ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 1, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), true, 'returns expected value' ); + + y = spreadDimensions( 3, x, [ 0 ], true ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 1, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function appends singleton dimensions (2d)', function test( t ) { var x; var y; @@ -307,6 +353,16 @@ tape( 'the function prepends singleton dimensions (base; row-major)', function t t.deepEqual( getStrides( y ), [ 4, 2, 1 ], 'returns expected value' ); t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + // Transposed: + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 1, 2 ], 0, 'row-major' ); + + y = spreadDimensions( 3, x, [ 1, 2 ], false ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 1, 2, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 1, 2 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.end(); }); @@ -339,6 +395,16 @@ tape( 'the function prepends singleton dimensions (base; column-major)', functio t.deepEqual( getStrides( y ), [ 1, 1, 2 ], 'returns expected value' ); t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + // Transposed: + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'column-major' ); + + y = spreadDimensions( 3, x, [ 1, 2 ], false ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 1, 2, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 4, 2, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.end(); }); @@ -371,6 +437,16 @@ tape( 'the function appends singleton dimensions (base; row-major)', function te t.deepEqual( getStrides( y ), [ 2, 1, 1 ], 'returns expected value' ); t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + // Transposed: + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 1, 2 ], 0, 'row-major' ); + + y = spreadDimensions( 3, x, [ 0, 1 ], false ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 2, 1 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 2, 4 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.end(); }); @@ -403,6 +479,16 @@ tape( 'the function appends singleton dimensions (base; column-major)', function t.deepEqual( getStrides( y ), [ 1, 2, 4 ], 'returns expected value' ); t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + // Transposed: + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'column-major' ); + + y = spreadDimensions( 3, x, [ 0, 1 ], false ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 2, 1 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 2, 1, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.end(); }); @@ -434,6 +520,16 @@ tape( 'the function inserts singleton dimensions (base; row-major)', function te t.deepEqual( getShape( y ), [ 2, 1, 2 ], 'returns expected value' ); t.deepEqual( getStrides( y ), [ 2, 2, 1 ], 'returns expected value' ); t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + + // Transposed: + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 1, 2 ], 0, 'row-major' ); + + y = spreadDimensions( 3, x, [ 0, 2 ], false ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 1, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 2, 2 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); t.end(); }); @@ -466,6 +562,16 @@ tape( 'the function inserts singleton dimensions (base; column-major)', function t.deepEqual( getStrides( y ), [ 1, 2, 2 ], 'returns expected value' ); t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + // Transposed: + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'column-major' ); + + y = spreadDimensions( 3, x, [ 0, 2 ], false ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 1, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 2, 2, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.end(); }); diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unflattened/README.md b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/README.md new file mode 100644 index 000000000000..5a3578c52ed9 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/README.md @@ -0,0 +1,121 @@ + + +# toUnflattened + +> Return a new ndarray in which a specified dimension of an input ndarray is expanded over multiple dimensions. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var toUnflattened = require( '@stdlib/ndarray/base/to-unflattened' ); +``` + +#### toUnflattened( x, dim, sizes ) + +Returns a new ndarray in which a specified dimension of an input ndarray is expanded over multiple dimensions. + +```javascript +var array = require( '@stdlib/ndarray/array' ); + +var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +// returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] + +var y = toUnflattened( x, 0, [ 2, 3 ] ); +// returns [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] +``` + +The function accepts the following arguments: + +- **x**: input ndarray. +- **dim**: dimension to be unflattened. If provided an integer less than zero, the dimension index is resolved relative to the last dimension, with the last dimension corresponding to the value `-1`. +- **sizes**: new shape of the unflattened dimension. + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var toUnflattened = require( '@stdlib/ndarray/base/to-unflattened' ); + +var x = uniform( [ 12 ], -100, 100 ); +console.log( ndarray2array( x ) ); + +var y = toUnflattened( x, 0, [ 3, 4 ] ); +console.log( ndarray2array( y ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unflattened/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/benchmark/benchmark.js new file mode 100644 index 000000000000..1e1538360597 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/benchmark/benchmark.js @@ -0,0 +1,205 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ndarrayBase = require( '@stdlib/ndarray/base/ctor' ); +var ndarray = require( '@stdlib/ndarray/ctor' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var toUnflattened = require( './../lib' ); + + +// MAIN // + +bench( format( '%s:ctor=base,ndims=2,order=row-major', pkg ), function benchmark( b ) { + var strides; + var values; + var buffer; + var offset; + var dtype; + var shape; + var order; + var sizes; + var out; + var i; + + dtype = 'float64'; + buffer = new Float64Array( 24 ); + shape = [ 2, 12 ]; + strides = [ 12, 1 ]; + offset = 0; + order = 'row-major'; + sizes = [ 3, 4 ]; + + values = [ + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = toUnflattened( values[ i%values.length ], 1, sizes ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isndarrayLike( out ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s:ctor=ndarray,ndims=2,order=row-major', pkg ), function benchmark( b ) { + var strides; + var values; + var buffer; + var offset; + var dtype; + var shape; + var order; + var sizes; + var out; + var i; + + dtype = 'float64'; + buffer = new Float64Array( 24 ); + shape = [ 2, 12 ]; + strides = [ 12, 1 ]; + offset = 0; + order = 'row-major'; + sizes = [ 3, 4 ]; + + values = [ + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = toUnflattened( values[ i%values.length ], 1, sizes ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isndarrayLike( out ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s:ctor=base,ndims=2,order=column-major', pkg ), function benchmark( b ) { + var strides; + var values; + var buffer; + var offset; + var dtype; + var shape; + var order; + var sizes; + var out; + var i; + + dtype = 'float64'; + buffer = new Float64Array( 24 ); + shape = [ 2, 12 ]; + strides = [ 1, 2 ]; + offset = 0; + order = 'column-major'; + sizes = [ 3, 4 ]; + + values = [ + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = toUnflattened( values[ i%values.length ], 1, sizes ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isndarrayLike( out ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s:ctor=ndarray,ndims=2,order=column-major', pkg ), function benchmark( b ) { + var strides; + var values; + var buffer; + var offset; + var dtype; + var shape; + var order; + var sizes; + var out; + var i; + + dtype = 'float64'; + buffer = new Float64Array( 24 ); + shape = [ 2, 12 ]; + strides = [ 1, 2 ]; + offset = 0; + order = 'column-major'; + sizes = [ 3, 4 ]; + + values = [ + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = toUnflattened( values[ i%values.length ], 1, sizes ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isndarrayLike( out ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unflattened/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/docs/repl.txt new file mode 100644 index 000000000000..81b40dfe3028 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/docs/repl.txt @@ -0,0 +1,33 @@ + +{{alias}}( x, dim, sizes ) + Returns a new ndarray in which a specified dimension of an input ndarray + is expanded over multiple dimensions. + + Parameters + ---------- + x: ndarray + Input array. + + dim: integer + Dimension to be unflattened. If provided an integer less than zero, + the dimension index is resolved relative to the last dimension, with + the last dimension corresponding to the value `-1`. + + sizes: ArrayLikeObject + New shape of the unflattened dimension. + + Returns + ------- + out: ndarray + Output array. + + Examples + -------- + > var x = {{alias:@stdlib/ndarray/array}}( [ 1, 2, 3, 4, 5, 6 ] ) + [ 1, 2, 3, 4, 5, 6 ] + > var y = {{alias}}( x, 0, [ 2, 3 ] ) + [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unflattened/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/docs/types/index.d.ts new file mode 100644 index 000000000000..0a896eb12281 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/docs/types/index.d.ts @@ -0,0 +1,47 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { ndarray } from '@stdlib/types/ndarray'; + +/** +* Returns a new ndarray in which a specified dimension of an input ndarray is expanded over multiple dimensions. +* +* @param x - input array +* @param dim - dimension to be unflattened +* @param sizes - new shape of the unflattened dimension +* @returns output array +* +* @example +* var array = require( `@stdlib/ndarray/array` ); +* +* var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* // returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] +* +* var y = toUnflattened( x, 0, [ 2, 3 ] ); +* // returns [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] +*/ +declare function toUnflattened( x: U, dim: number, sizes: ArrayLike ): U; + + +// EXPORTS // + +export = toUnflattened; diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unflattened/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/docs/types/test.ts new file mode 100644 index 000000000000..1ea05462edce --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/docs/types/test.ts @@ -0,0 +1,84 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import toUnflattened = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 2, 6 ], { + 'dtype': 'float64' + }); + + toUnflattened( x, 1, [ 2, 3 ] ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the function is not provided a first argument which is an ndarray... +{ + toUnflattened( true, 1, [ 2, 3 ] ); // $ExpectError + toUnflattened( false, 1, [ 2, 3 ] ); // $ExpectError + toUnflattened( null, 1, [ 2, 3 ] ); // $ExpectError + toUnflattened( undefined, 1, [ 2, 3 ] ); // $ExpectError + toUnflattened( '5', 1, [ 2, 3 ] ); // $ExpectError + toUnflattened( [ '1', '2' ], 1, [ 2, 3 ] ); // $ExpectError + toUnflattened( {}, 1, [ 2, 3 ] ); // $ExpectError + toUnflattened( ( x: number ): number => x, 1, [ 2, 3 ] ); // $ExpectError +} + +// The compiler throws an error if the function is not provided a second argument which is a number... +{ + const x = zeros( [ 2, 6 ] ); + + toUnflattened( x, true, [ 2, 3 ] ); // $ExpectError + toUnflattened( x, false, [ 2, 3 ] ); // $ExpectError + toUnflattened( x, null, [ 2, 3 ] ); // $ExpectError + toUnflattened( x, undefined, [ 2, 3 ] ); // $ExpectError + toUnflattened( x, '5', [ 2, 3 ] ); // $ExpectError + toUnflattened( x, [ '1', '2' ], [ 2, 3 ] ); // $ExpectError + toUnflattened( x, {}, [ 2, 3 ] ); // $ExpectError + toUnflattened( x, ( x: number ): number => x, [ 2, 3 ] ); // $ExpectError +} + +// The compiler throws an error if the function is not provided a third argument which is an array-like object of numbers... +{ + const x = zeros( [ 2, 6 ] ); + + toUnflattened( x, 1, true ); // $ExpectError + toUnflattened( x, 1, false ); // $ExpectError + toUnflattened( x, 1, null ); // $ExpectError + toUnflattened( x, 1, undefined ); // $ExpectError + toUnflattened( x, 1, '5' ); // $ExpectError + toUnflattened( x, 1, [ '1', '2' ] ); // $ExpectError + toUnflattened( x, 1, {} ); // $ExpectError + toUnflattened( x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 2, 6 ] ); + + toUnflattened(); // $ExpectError + toUnflattened( x ); // $ExpectError + toUnflattened( x, 1 ); // $ExpectError + toUnflattened( x, 1, [ 2, 3 ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unflattened/examples/index.js b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/examples/index.js new file mode 100644 index 000000000000..2b4eddc7e81a --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/examples/index.js @@ -0,0 +1,29 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var toUnflattened = require( './../lib' ); + +var x = uniform( [ 12 ], -100, 100 ); +console.log( ndarray2array( x ) ); + +var y = toUnflattened( x, 0, [ 3, 4 ] ); +console.log( ndarray2array( y ) ); diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unflattened/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/lib/index.js new file mode 100644 index 000000000000..986e55045eac --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return a new ndarray in which a specified dimension of an input ndarray is expanded over multiple dimensions. +* +* @module @stdlib/ndarray/base/to-unflattened +* +* @example +* var array = require( '@stdlib/ndarray/array' ); +* var toUnflattened = require( '@stdlib/ndarray/base/to-unflattened' ); +* +* var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* // returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] +* +* var y = toUnflattened( x, 0, [ 2, 3 ] ); +* // returns [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unflattened/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/lib/main.js new file mode 100644 index 000000000000..22faad24ecbb --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/lib/main.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var emptyLike = require( '@stdlib/ndarray/base/empty-like' ); +var unflatten = require( '@stdlib/ndarray/base/unflatten' ); +var assign = require( '@stdlib/ndarray/base/assign' ); + + +// MAIN // + +/** +* Returns a new ndarray in which a specified dimension of an input ndarray is expanded over multiple dimensions. +* +* @param {ndarray} x - input array +* @param {integer} dim - dimension index +* @param {NonNegativeIntegerArray} sizes - new shape of the unflattened dimension +* @throws {RangeError} must provide a valid dimension index +* @throws {RangeError} product of the sizes must be equal to the size of the dimension to be unflattened +* @returns {ndarray} output array +* +* @example +* var array = require( '@stdlib/ndarray/array' ); +* +* var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* // returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] +* +* var y = toUnflattened( x, 0, [ 2, 3 ] ); +* // returns [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] +*/ +function toUnflattened( x, dim, sizes ) { + var out; + var xv; + + // Create an unflattened view of the input ndarray: + xv = unflatten( x, dim, sizes, false ); + + // Create an output ndarray with the same data type as the input ndarray having the unflattened shape: + out = emptyLike( xv ); + + // Assign the elements of the unflattened input ndarray view to the output ndarray: + assign( [ xv, out ] ); + + return out; +} + + +// EXPORTS // + +module.exports = toUnflattened; diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unflattened/package.json b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/package.json new file mode 100644 index 000000000000..57af073af3f5 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/package.json @@ -0,0 +1,69 @@ +{ + "name": "@stdlib/ndarray/base/to-unflattened", + "version": "0.0.0", + "description": "Return a new ndarray in which a specified dimension of an input ndarray is expanded over multiple dimensions.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "types", + "base", + "ndarray", + "to-unflattened", + "unflatten", + "unflattened", + "reshape", + "multidimensional", + "array", + "utilities", + "utility", + "utils", + "util" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unflattened/test/test.js b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/test/test.js new file mode 100644 index 000000000000..ff9726345ee7 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unflattened/test/test.js @@ -0,0 +1,397 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var array = require( '@stdlib/ndarray/array' ); +var zeroTo = require( '@stdlib/array/zero-to' ); +var getShape = require( '@stdlib/ndarray/shape' ); +var getStrides = require( '@stdlib/ndarray/strides' ); +var getDType = require( '@stdlib/ndarray/dtype' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var isReadOnly = require( '@stdlib/ndarray/base/assert/is-read-only' ); +var toUnflattened = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof toUnflattened, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a new ndarray in which a specified dimension of an input ndarray is expanded over multiple dimensions (base; row-major)', function test( t ) { + var expected; + var buf; + var x; + var y; + + buf = zeroTo( 64 ); + x = ndarray( 'generic', buf, [ 4, 4, 4 ], [ 16, 4, 1 ], 0, 'row-major' ); + + // First dimension: + expected = [ + [ + [ + [ 0, 1, 2, 3 ], + [ 4, 5, 6, 7 ], + [ 8, 9, 10, 11 ], + [ 12, 13, 14, 15 ] + ], + [ + [ 16, 17, 18, 19 ], + [ 20, 21, 22, 23 ], + [ 24, 25, 26, 27 ], + [ 28, 29, 30, 31 ] + ] + ], + [ + [ + [ 32, 33, 34, 35 ], + [ 36, 37, 38, 39 ], + [ 40, 41, 42, 43 ], + [ 44, 45, 46, 47 ] + ], + [ + [ 48, 49, 50, 51 ], + [ 52, 53, 54, 55 ], + [ 56, 57, 58, 59 ], + [ 60, 61, 62, 63 ] + ] + ] + ]; + + y = toUnflattened( x, 0, [ 2, 2 ] ); + t.deepEqual( getShape( y ), [ 2, 2, 4, 4 ], 'returns expected value' ); + t.strictEqual( String( getDType( y ) ), String( getDType( x ) ), 'returns expected value' ); + t.notEqual( getData( y ), getData( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + // Middle dimension: + expected = [ + [ + [ + [ 0, 1, 2, 3 ], + [ 4, 5, 6, 7 ] + ], + [ + [ 8, 9, 10, 11 ], + [ 12, 13, 14, 15 ] + ] + ], + [ + [ + [ 16, 17, 18, 19 ], + [ 20, 21, 22, 23 ] + ], + [ + [ 24, 25, 26, 27 ], + [ 28, 29, 30, 31 ] + ] + ], + [ + [ + [ 32, 33, 34, 35 ], + [ 36, 37, 38, 39 ] + ], + [ + [ 40, 41, 42, 43 ], + [ 44, 45, 46, 47 ] + ] + ], + [ + [ + [ 48, 49, 50, 51 ], + [ 52, 53, 54, 55 ] + ], + [ + [ 56, 57, 58, 59 ], + [ 60, 61, 62, 63 ] + ] + ] + ]; + + y = toUnflattened( x, 1, [ 2, 2 ] ); + t.deepEqual( getShape( y ), [ 4, 2, 2, 4 ], 'returns expected value' ); + t.strictEqual( String( getDType( y ) ), String( getDType( x ) ), 'returns expected value' ); + t.notEqual( getData( y ), getData( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + // Last dimension: + expected = [ + [ + [ [ 0, 1 ], [ 2, 3 ] ], + [ [ 4, 5 ], [ 6, 7 ] ], + [ [ 8, 9 ], [ 10, 11 ] ], + [ [ 12, 13 ], [ 14, 15 ] ] + ], + [ + [ [ 16, 17 ], [ 18, 19 ] ], + [ [ 20, 21 ], [ 22, 23 ] ], + [ [ 24, 25 ], [ 26, 27 ] ], + [ [ 28, 29 ], [ 30, 31 ] ] + ], + [ + [ [ 32, 33 ], [ 34, 35 ] ], + [ [ 36, 37 ], [ 38, 39 ] ], + [ [ 40, 41 ], [ 42, 43 ] ], + [ [ 44, 45 ], [ 46, 47 ] ] + ], + [ + [ [ 48, 49 ], [ 50, 51 ] ], + [ [ 52, 53 ], [ 54, 55 ] ], + [ [ 56, 57 ], [ 58, 59 ] ], + [ [ 60, 61 ], [ 62, 63 ] ] + ] + ]; + + y = toUnflattened( x, 2, [ 2, 2 ] ); + t.deepEqual( getShape( y ), [ 4, 4, 2, 2 ], 'returns expected value' ); + t.strictEqual( String( getDType( y ) ), String( getDType( x ) ), 'returns expected value' ); + t.notEqual( getData( y ), getData( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a new ndarray in which a specified dimension of an input ndarray is expanded over multiple dimensions (base; row-major; negative dimension indices)', function test( t ) { + var expected; + var buf; + var x; + var y; + + buf = zeroTo( 64 ); + x = ndarray( 'generic', buf, [ 4, 4, 4 ], [ 16, 4, 1 ], 0, 'row-major' ); + + // First dimension: + expected = [ + [ + [ + [ 0, 1, 2, 3 ], + [ 4, 5, 6, 7 ], + [ 8, 9, 10, 11 ], + [ 12, 13, 14, 15 ] + ], + [ + [ 16, 17, 18, 19 ], + [ 20, 21, 22, 23 ], + [ 24, 25, 26, 27 ], + [ 28, 29, 30, 31 ] + ] + ], + [ + [ + [ 32, 33, 34, 35 ], + [ 36, 37, 38, 39 ], + [ 40, 41, 42, 43 ], + [ 44, 45, 46, 47 ] + ], + [ + [ 48, 49, 50, 51 ], + [ 52, 53, 54, 55 ], + [ 56, 57, 58, 59 ], + [ 60, 61, 62, 63 ] + ] + ] + ]; + + y = toUnflattened( x, -3, [ 2, 2 ] ); + t.deepEqual( getShape( y ), [ 2, 2, 4, 4 ], 'returns expected value' ); + t.strictEqual( String( getDType( y ) ), String( getDType( x ) ), 'returns expected value' ); + t.notEqual( getData( y ), getData( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + // Last dimension: + expected = [ + [ + [ [ 0, 1 ], [ 2, 3 ] ], + [ [ 4, 5 ], [ 6, 7 ] ], + [ [ 8, 9 ], [ 10, 11 ] ], + [ [ 12, 13 ], [ 14, 15 ] ] + ], + [ + [ [ 16, 17 ], [ 18, 19 ] ], + [ [ 20, 21 ], [ 22, 23 ] ], + [ [ 24, 25 ], [ 26, 27 ] ], + [ [ 28, 29 ], [ 30, 31 ] ] + ], + [ + [ [ 32, 33 ], [ 34, 35 ] ], + [ [ 36, 37 ], [ 38, 39 ] ], + [ [ 40, 41 ], [ 42, 43 ] ], + [ [ 44, 45 ], [ 46, 47 ] ] + ], + [ + [ [ 48, 49 ], [ 50, 51 ] ], + [ [ 52, 53 ], [ 54, 55 ] ], + [ [ 56, 57 ], [ 58, 59 ] ], + [ [ 60, 61 ], [ 62, 63 ] ] + ] + ]; + + y = toUnflattened( x, -1, [ 2, 2 ] ); + t.deepEqual( getShape( y ), [ 4, 4, 2, 2 ], 'returns expected value' ); + t.strictEqual( String( getDType( y ) ), String( getDType( x ) ), 'returns expected value' ); + t.notEqual( getData( y ), getData( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a new ndarray in which a specified dimension of an input ndarray is expanded over multiple dimensions (base; column-major)', function test( t ) { + var expected; + var buf; + var x; + var y; + + buf = zeroTo( 64 ); + x = ndarray( 'generic', buf, [ 4, 4, 4 ], [ 1, 4, 16 ], 0, 'column-major' ); + + // First dimension: + expected = [ + [ + [ + [ 0, 16, 32, 48 ], + [ 4, 20, 36, 52 ], + [ 8, 24, 40, 56 ], + [ 12, 28, 44, 60 ] + ], + [ + [ 2, 18, 34, 50 ], + [ 6, 22, 38, 54 ], + [ 10, 26, 42, 58 ], + [ 14, 30, 46, 62 ] + ] + ], + [ + [ + [ 1, 17, 33, 49 ], + [ 5, 21, 37, 53 ], + [ 9, 25, 41, 57 ], + [ 13, 29, 45, 61 ] + ], + [ + [ 3, 19, 35, 51 ], + [ 7, 23, 39, 55 ], + [ 11, 27, 43, 59 ], + [ 15, 31, 47, 63 ] + ] + ] + ]; + + y = toUnflattened( x, 0, [ 2, 2 ] ); + t.deepEqual( getShape( y ), [ 2, 2, 4, 4 ], 'returns expected value' ); + t.strictEqual( String( getDType( y ) ), String( getDType( x ) ), 'returns expected value' ); + t.notEqual( getData( y ), getData( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + // Last dimension: + expected = [ + [ + [ [ 0, 32 ], [ 16, 48 ] ], + [ [ 4, 36 ], [ 20, 52 ] ], + [ [ 8, 40 ], [ 24, 56 ] ], + [ [ 12, 44 ], [ 28, 60 ] ] + ], + [ + [ [ 1, 33 ], [ 17, 49 ] ], + [ [ 5, 37 ], [ 21, 53 ] ], + [ [ 9, 41 ], [ 25, 57 ] ], + [ [ 13, 45 ], [ 29, 61 ] ] + ], + [ + [ [ 2, 34 ], [ 18, 50 ] ], + [ [ 6, 38 ], [ 22, 54 ] ], + [ [ 10, 42 ], [ 26, 58 ] ], + [ [ 14, 46 ], [ 30, 62 ] ] + ], + [ + [ [ 3, 35 ], [ 19, 51 ] ], + [ [ 7, 39 ], [ 23, 55 ] ], + [ [ 11, 43 ], [ 27, 59 ] ], + [ [ 15, 47 ], [ 31, 63 ] ] + ] + ]; + + y = toUnflattened( x, 2, [ 2, 2 ] ); + t.deepEqual( getShape( y ), [ 4, 4, 2, 2 ], 'returns expected value' ); + t.strictEqual( String( getDType( y ) ), String( getDType( x ) ), 'returns expected value' ); + t.notEqual( getData( y ), getData( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a writable ndarray when the input is a read-only ndarray', function test( t ) { + var y; + var x; + + x = array( zeroTo( 12 ), { + 'shape': [ 12 ], + 'dtype': 'float64', + 'readonly': true + }); + + y = toUnflattened( x, 0, [ 3, 4 ] ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.notEqual( getData( y ), getData( x ), 'returns expected value' ); + t.deepEqual( getShape( y ), [ 3, 4 ], 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a new ndarray with contiguous strides (row-major)', function test( t ) { + var y; + var x; + + x = array( zeroTo( 12 ), { + 'shape': [ 12 ], + 'dtype': 'float64', + 'order': 'row-major' + }); + + y = toUnflattened( x, 0, [ 3, 4 ] ); + t.deepEqual( getShape( y ), [ 3, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 4, 1 ], 'returns expected value' ); + t.deepEqual( ndarray2array( y ), [ [ 0, 1, 2, 3 ], [ 4, 5, 6, 7 ], [ 8, 9, 10, 11 ] ], 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a new ndarray with contiguous strides (column-major)', function test( t ) { + var y; + var x; + + x = array( zeroTo( 12 ), { + 'shape': [ 12 ], + 'dtype': 'float64', + 'order': 'column-major' + }); + + y = toUnflattened( x, 0, [ 3, 4 ] ); + t.deepEqual( getShape( y ), [ 3, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 3 ], 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/dispatch.c b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/dispatch.c index e0ec04c456d9..83330f55d817 100644 --- a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/dispatch.c +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/dispatch.c @@ -228,11 +228,11 @@ int8_t stdlib_ndarray_unary_accumulate_dispatch( const struct ndarrayUnaryAccumu struct ndarray *x1; struct ndarray *x2; struct ndarray *x3; + const int64_t *s1; int8_t status; int64_t ndims; int64_t mab1; int64_t mib1; - int64_t *s1; int64_t len; int64_t bp1; int8_t io1; diff --git a/lib/node_modules/@stdlib/ndarray/base/unflatten/README.md b/lib/node_modules/@stdlib/ndarray/base/unflatten/README.md new file mode 100644 index 000000000000..f4704605d411 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unflatten/README.md @@ -0,0 +1,126 @@ + + +# unflatten + +> Return a view of an input ndarray in which a specified dimension is expanded over multiple dimensions. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var unflatten = require( '@stdlib/ndarray/base/unflatten' ); +``` + +#### unflatten( x, dim, sizes, writable ) + +Returns a view of an input ndarray in which a specified dimension is expanded over multiple dimensions. + +```javascript +var array = require( '@stdlib/ndarray/array' ); + +var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +// returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] + +var out = unflatten( x, 0, [ 2, 3 ], false ); +// returns [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] +``` + +The function accepts the following arguments: + +- **x**: input ndarray. +- **dim**: dimension to be unflattened. If provided an integer less than zero, the dimension index is resolved relative to the last dimension, with the last dimension corresponding to the value `-1`. +- **sizes**: new shape of the unflattened dimension. +- **writable**: boolean indicating whether a returned ndarray should be writable. + +
+ + + + + +
+ +## Notes + +- The `writable` parameter **only** applies to ndarray constructors supporting **read-only** instances. + +
+ + + + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var unflatten = require( '@stdlib/ndarray/base/unflatten' ); + +var x = uniform( [ 12 ], -100, 100 ); +console.log( ndarray2array( x ) ); + +var out = unflatten( x, 0, [ 3, 4 ], false ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ndarray/base/unflatten/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/base/unflatten/benchmark/benchmark.js new file mode 100644 index 000000000000..96ac01bf0f37 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unflatten/benchmark/benchmark.js @@ -0,0 +1,205 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ndarrayBase = require( '@stdlib/ndarray/base/ctor' ); +var ndarray = require( '@stdlib/ndarray/ctor' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var unflatten = require( './../lib' ); + + +// MAIN // + +bench( format( '%s:ctor=base,ndims=2,order=row-major', pkg ), function benchmark( b ) { + var strides; + var values; + var buffer; + var offset; + var dtype; + var shape; + var order; + var sizes; + var out; + var i; + + dtype = 'float64'; + buffer = new Float64Array( 24 ); + shape = [ 2, 12 ]; + strides = [ 12, 1 ]; + offset = 0; + order = 'row-major'; + sizes = [ 3, 4 ]; + + values = [ + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = unflatten( values[ i%values.length ], 1, sizes, false ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isndarrayLike( out ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s:ctor=ndarray,ndims=2,order=row-major', pkg ), function benchmark( b ) { + var strides; + var values; + var buffer; + var offset; + var dtype; + var shape; + var order; + var sizes; + var out; + var i; + + dtype = 'float64'; + buffer = new Float64Array( 24 ); + shape = [ 2, 12 ]; + strides = [ 12, 1 ]; + offset = 0; + order = 'row-major'; + sizes = [ 3, 4 ]; + + values = [ + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = unflatten( values[ i%values.length ], 1, sizes, false ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isndarrayLike( out ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s:ctor=base,ndims=2,order=column-major', pkg ), function benchmark( b ) { + var strides; + var values; + var buffer; + var offset; + var dtype; + var shape; + var order; + var sizes; + var out; + var i; + + dtype = 'float64'; + buffer = new Float64Array( 24 ); + shape = [ 2, 12 ]; + strides = [ 1, 2 ]; + offset = 0; + order = 'column-major'; + sizes = [ 3, 4 ]; + + values = [ + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = unflatten( values[ i%values.length ], 1, sizes, false ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isndarrayLike( out ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s:ctor=ndarray,ndims=2,order=column-major', pkg ), function benchmark( b ) { + var strides; + var values; + var buffer; + var offset; + var dtype; + var shape; + var order; + var sizes; + var out; + var i; + + dtype = 'float64'; + buffer = new Float64Array( 24 ); + shape = [ 2, 12 ]; + strides = [ 1, 2 ]; + offset = 0; + order = 'column-major'; + sizes = [ 3, 4 ]; + + values = [ + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = unflatten( values[ i%values.length ], 1, sizes, false ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isndarrayLike( out ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/unflatten/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/unflatten/docs/repl.txt new file mode 100644 index 000000000000..65ba2d5c86f2 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unflatten/docs/repl.txt @@ -0,0 +1,35 @@ + +{{alias}}( x, dim, sizes, writable ) + Returns a view of an input ndarray in which a specified dimension is + expanded over multiple dimensions. + + Parameters + ---------- + x: ndarray + Input array. + + dim: integer + Dimension to be unflattened. If provided an integer less than zero, + the dimension index is resolved relative to the last dimension, with + the last dimension corresponding to the value `-1`. + + sizes: ArrayLikeObject + New shape of the unflattened dimension. + + writable: boolean + Boolean indicating whether the returned ndarray should be writable. + + Returns + ------- + out: ndarray + Output array. + + Examples + -------- + > var x = {{alias:@stdlib/ndarray/array}}( [ 1, 2, 3, 4, 5, 6 ] ) + [ 1, 2, 3, 4, 5, 6 ] + > var out = {{alias}}( x, 0, [ 2, 3 ], false ) + [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/ndarray/base/unflatten/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/base/unflatten/docs/types/index.d.ts new file mode 100644 index 000000000000..a07e6b9a8026 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unflatten/docs/types/index.d.ts @@ -0,0 +1,48 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { ndarray } from '@stdlib/types/ndarray'; + +/** +* Returns a view of an input ndarray in which a specified dimension is expanded over multiple dimensions. +* +* @param x - input array +* @param dim - dimension to be unflattened +* @param sizes - new shape of the unflattened dimension +* @param writable - boolean indicating whether the returned ndarray should be writable +* @returns output array +* +* @example +* var array = require( `@stdlib/ndarray/array` ); +* +* var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* // returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] +* +* var out = unflatten( x, 0, [ 2, 3 ], false ); +* // returns [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] +*/ +declare function unflatten( x: U, dim: number, sizes: ArrayLike, writable: boolean ): U; + + +// EXPORTS // + +export = unflatten; diff --git a/lib/node_modules/@stdlib/ndarray/base/unflatten/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/base/unflatten/docs/types/test.ts new file mode 100644 index 000000000000..fada438bd7fa --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unflatten/docs/types/test.ts @@ -0,0 +1,99 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import unflatten = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 2, 6 ], { + 'dtype': 'float64' + }); + + unflatten( x, 1, [ 2, 3 ], false ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the function is not provided a first argument which is an ndarray... +{ + unflatten( '5', 1, [ 2, 3 ], false ); // $ExpectError + unflatten( 5, 1, [ 2, 3 ], false ); // $ExpectError + unflatten( true, 1, [ 2, 3 ], false ); // $ExpectError + unflatten( false, 1, [ 2, 3 ], false ); // $ExpectError + unflatten( void 0, 1, [ 2, 3 ], false ); // $ExpectError + unflatten( null, 1, [ 2, 3 ], false ); // $ExpectError + unflatten( {}, 1, [ 2, 3 ], false ); // $ExpectError + unflatten( [ '5' ], 1, [ 2, 3 ], false ); // $ExpectError + unflatten( ( x: number ): number => x, 1, [ 2, 3 ], false ); // $ExpectError +} + +// The compiler throws an error if the function is not provided a second argument which is a number... +{ + const x = zeros( [ 2, 6 ] ); + + unflatten( x, '5', [ 2, 3 ], false ); // $ExpectError + unflatten( x, true, [ 2, 3 ], false ); // $ExpectError + unflatten( x, false, [ 2, 3 ], false ); // $ExpectError + unflatten( x, void 0, [ 2, 3 ], false ); // $ExpectError + unflatten( x, null, [ 2, 3 ], false ); // $ExpectError + unflatten( x, {}, [ 2, 3 ], false ); // $ExpectError + unflatten( x, [ '5' ], [ 2, 3 ], false ); // $ExpectError + unflatten( x, ( x: number ): number => x, [ 2, 3 ], false ); // $ExpectError +} + +// The compiler throws an error if the function is not provided a third argument which is an array-like object of numbers... +{ + const x = zeros( [ 2, 6 ] ); + + unflatten( x, 1, '5', false ); // $ExpectError + unflatten( x, 1, 5, false ); // $ExpectError + unflatten( x, 1, true, false ); // $ExpectError + unflatten( x, 1, false, false ); // $ExpectError + unflatten( x, 1, void 0, false ); // $ExpectError + unflatten( x, 1, null, false ); // $ExpectError + unflatten( x, 1, {}, false ); // $ExpectError + unflatten( x, 1, ( x: number ): number => x, false ); // $ExpectError +} + +// The compiler throws an error if the function is not provided a fourth argument which is a boolean... +{ + const x = zeros( [ 2, 6 ] ); + + unflatten( x, 1, [ 2, 3 ], '5' ); // $ExpectError + unflatten( x, 1, [ 2, 3 ], 5 ); // $ExpectError + unflatten( x, 1, [ 2, 3 ], void 0 ); // $ExpectError + unflatten( x, 1, [ 2, 3 ], null ); // $ExpectError + unflatten( x, 1, [ 2, 3 ], {} ); // $ExpectError + unflatten( x, 1, [ 2, 3 ], [ '5' ] ); // $ExpectError + unflatten( x, 1, [ 2, 3 ], ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 2, 6 ] ); + + unflatten(); // $ExpectError + unflatten( x ); // $ExpectError + unflatten( x, 1 ); // $ExpectError + unflatten( x, 1, [ 2, 3 ] ); // $ExpectError + unflatten( x, 1, [ 2, 3 ], false, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ndarray/base/unflatten/examples/index.js b/lib/node_modules/@stdlib/ndarray/base/unflatten/examples/index.js new file mode 100644 index 000000000000..3fdab1380a34 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unflatten/examples/index.js @@ -0,0 +1,29 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var unflatten = require( './../lib' ); + +var x = uniform( [ 12 ], -100, 100 ); +console.log( ndarray2array( x ) ); + +var out = unflatten( x, 0, [ 3, 4 ], false ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/ndarray/base/unflatten/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/unflatten/lib/index.js new file mode 100644 index 000000000000..329dde65a460 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unflatten/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return a view of an input ndarray in which a specified dimension is expanded over multiple dimensions. +* +* @module @stdlib/ndarray/base/unflatten +* +* @example +* var array = require( '@stdlib/ndarray/array' ); +* var unflatten = require( '@stdlib/ndarray/base/unflatten' ); +* +* var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* // returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] +* +* var out = unflatten( x, 0, [ 2, 3 ], false ); +* // returns [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ndarray/base/unflatten/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/unflatten/lib/main.js new file mode 100644 index 000000000000..660b7cb314bf --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unflatten/lib/main.js @@ -0,0 +1,118 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isRowMajorString = require( '@stdlib/ndarray/base/assert/is-row-major-string' ); +var strides2order = require( '@stdlib/ndarray/base/strides2order' ); +var normalizeIndex = require( '@stdlib/ndarray/base/normalize-index' ); +var getDType = require( '@stdlib/ndarray/base/dtype' ); +var getShape = require( '@stdlib/ndarray/base/shape' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getOrder = require( '@stdlib/ndarray/base/order' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var unflattenShape = require( '@stdlib/ndarray/base/unflatten-shape' ); + + +// MAIN // + +/** +* Returns a view of an input ndarray in which a specified dimension is expanded over multiple dimensions. +* +* @param {ndarray} x - input array +* @param {integer} dim - dimension index +* @param {NonNegativeIntegerArray} sizes - new shape of the unflattened dimension +* @param {boolean} writable - boolean indicating whether the returned ndarray should be writable +* @throws {RangeError} must provide a valid dimension index +* @throws {RangeError} product of the sizes must be equal to the size of the dimension to be unflattened +* @returns {ndarray} output array +* +* @example +* var array = require( '@stdlib/ndarray/array' ); +* +* var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* // returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] +* +* var out = unflatten( x, 0, [ 2, 3 ], false ); +* // returns [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] +*/ +function unflatten( x, dim, sizes, writable ) { + var strides; + var shape; + var isrm; + var ord; + var sh; + var st; + var S2; + var o; + var d; + var i; + + sh = getShape( x, false ); + st = getStrides( x, false ); + ord = getOrder( x ); + o = strides2order( st ); + if ( o === 0 || o === 3 ) { + // Fallback to stated layout when unable to infer the underlying physical layout: + isrm = isRowMajorString( ord ); + } else { + isrm = ( o === 1 ); + } + + // Normalize the dimension to be unflattened: + d = normalizeIndex( dim, sh.length-1 ); + + // Compute the output shape: + shape = unflattenShape( sh, d, sizes ); + + // Resolve the output strides: + strides = []; + S2 = sizes.length; + for ( i = 0; i < d; i++ ) { + strides.push( st[ i ] ); + } + for ( i = 0; i < S2; i++ ) { + strides.push( 0 ); + } + for ( i = d+1; i < sh.length; i++ ) { + strides.push( st[ i ] ); + } + // Compute strides for the unflattened dimensions... + if ( isrm ) { + strides[ d+S2-1 ] = st[ d ]; + for ( i = S2-1; i > 0; i-- ) { + strides[ d+i-1 ] = strides[ d+i ] * sizes[ i ]; + } + } else { + strides[ d ] = st[ d ]; + for ( i = 0; i < S2-1; i++ ) { + strides[ d+i+1 ] = strides[ d+i ] * sizes[ i ]; + } + } + return new x.constructor( getDType( x ), getData( x ), shape, strides, getOffset( x ), ord, { // eslint-disable-line max-len + 'readonly': !writable + }); +} + + +// EXPORTS // + +module.exports = unflatten; diff --git a/lib/node_modules/@stdlib/ndarray/base/unflatten/package.json b/lib/node_modules/@stdlib/ndarray/base/unflatten/package.json new file mode 100644 index 000000000000..e0cd229dce96 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unflatten/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/ndarray/base/unflatten", + "version": "0.0.0", + "description": "Return a view of an input ndarray in which a specified dimension is expanded over multiple dimensions.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "types", + "base", + "ndarray", + "unflatten", + "reshape", + "multidimensional", + "array", + "utilities", + "utility", + "utils", + "util" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ndarray/base/unflatten/test/test.js b/lib/node_modules/@stdlib/ndarray/base/unflatten/test/test.js new file mode 100644 index 000000000000..31641eeb1132 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unflatten/test/test.js @@ -0,0 +1,1025 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var array = require( '@stdlib/ndarray/array' ); +var zeroTo = require( '@stdlib/array/zero-to' ); +var getShape = require( '@stdlib/ndarray/shape' ); +var getStrides = require( '@stdlib/ndarray/strides' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var isReadOnly = require( '@stdlib/ndarray/base/assert/is-read-only' ); +var unflatten = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof unflatten, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a view of an input ndarray in which a specified dimension is expanded over multiple dimensions (base; row-major)', function test( t ) { + var expected; + var buf; + var x; + var y; + + buf = zeroTo( 64 ); + x = ndarray( 'generic', buf, [ 4, 4, 4 ], [ 16, 4, 1 ], 0, 'row-major' ); + + // First dimension: + expected = [ + [ + [ + [ 0, 1, 2, 3 ], + [ 4, 5, 6, 7 ], + [ 8, 9, 10, 11 ], + [ 12, 13, 14, 15 ] + ], + [ + [ 16, 17, 18, 19 ], + [ 20, 21, 22, 23 ], + [ 24, 25, 26, 27 ], + [ 28, 29, 30, 31 ] + ] + ], + [ + [ + [ 32, 33, 34, 35 ], + [ 36, 37, 38, 39 ], + [ 40, 41, 42, 43 ], + [ 44, 45, 46, 47 ] + ], + [ + [ 48, 49, 50, 51 ], + [ 52, 53, 54, 55 ], + [ 56, 57, 58, 59 ], + [ 60, 61, 62, 63 ] + ] + ] + ]; + + y = unflatten( x, 0, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 2, 4, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 32, 16, 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, 0, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 2, 4, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 32, 16, 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + // Middle dimension: + expected = [ + [ + [ + [ 0, 1, 2, 3 ], + [ 4, 5, 6, 7 ] + ], + [ + [ 8, 9, 10, 11 ], + [ 12, 13, 14, 15 ] + ] + ], + [ + [ + [ 16, 17, 18, 19 ], + [ 20, 21, 22, 23 ] + ], + [ + [ 24, 25, 26, 27 ], + [ 28, 29, 30, 31 ] + ] + ], + [ + [ + [ 32, 33, 34, 35 ], + [ 36, 37, 38, 39 ] + ], + [ + [ 40, 41, 42, 43 ], + [ 44, 45, 46, 47 ] + ] + ], + [ + [ + [ 48, 49, 50, 51 ], + [ 52, 53, 54, 55 ] + ], + [ + [ 56, 57, 58, 59 ], + [ 60, 61, 62, 63 ] + ] + ] + ]; + + y = unflatten( x, 1, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 2, 2, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 16, 8, 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, 1, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 2, 2, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 16, 8, 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + // Last dimension: + expected = [ + [ + [ [ 0, 1 ], [ 2, 3 ] ], + [ [ 4, 5 ], [ 6, 7 ] ], + [ [ 8, 9 ], [ 10, 11 ] ], + [ [ 12, 13 ], [ 14, 15 ] ] + ], + [ + [ [ 16, 17 ], [ 18, 19 ] ], + [ [ 20, 21 ], [ 22, 23 ] ], + [ [ 24, 25 ], [ 26, 27 ] ], + [ [ 28, 29 ], [ 30, 31 ] ] + ], + [ + [ [ 32, 33 ], [ 34, 35 ] ], + [ [ 36, 37 ], [ 38, 39 ] ], + [ [ 40, 41 ], [ 42, 43 ] ], + [ [ 44, 45 ], [ 46, 47 ] ] + ], + [ + [ [ 48, 49 ], [ 50, 51 ] ], + [ [ 52, 53 ], [ 54, 55 ] ], + [ [ 56, 57 ], [ 58, 59 ] ], + [ [ 60, 61 ], [ 62, 63 ] ] + ] + ]; + + y = unflatten( x, 2, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 4, 2, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 16, 4, 2, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, 2, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 4, 2, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 16, 4, 2, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a view of an input ndarray in which a specified dimension is expanded over multiple dimensions (base; row-major; negative dimension indices)', function test( t ) { + var expected; + var buf; + var x; + var y; + + buf = zeroTo( 64 ); + x = ndarray( 'generic', buf, [ 4, 4, 4 ], [ 16, 4, 1 ], 0, 'row-major' ); + + // First dimension: + expected = [ + [ + [ + [ 0, 1, 2, 3 ], + [ 4, 5, 6, 7 ], + [ 8, 9, 10, 11 ], + [ 12, 13, 14, 15 ] + ], + [ + [ 16, 17, 18, 19 ], + [ 20, 21, 22, 23 ], + [ 24, 25, 26, 27 ], + [ 28, 29, 30, 31 ] + ] + ], + [ + [ + [ 32, 33, 34, 35 ], + [ 36, 37, 38, 39 ], + [ 40, 41, 42, 43 ], + [ 44, 45, 46, 47 ] + ], + [ + [ 48, 49, 50, 51 ], + [ 52, 53, 54, 55 ], + [ 56, 57, 58, 59 ], + [ 60, 61, 62, 63 ] + ] + ] + ]; + + y = unflatten( x, -3, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 2, 4, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 32, 16, 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, -3, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 2, 4, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 32, 16, 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + // Middle dimension: + expected = [ + [ + [ + [ 0, 1, 2, 3 ], + [ 4, 5, 6, 7 ] + ], + [ + [ 8, 9, 10, 11 ], + [ 12, 13, 14, 15 ] + ] + ], + [ + [ + [ 16, 17, 18, 19 ], + [ 20, 21, 22, 23 ] + ], + [ + [ 24, 25, 26, 27 ], + [ 28, 29, 30, 31 ] + ] + ], + [ + [ + [ 32, 33, 34, 35 ], + [ 36, 37, 38, 39 ] + ], + [ + [ 40, 41, 42, 43 ], + [ 44, 45, 46, 47 ] + ] + ], + [ + [ + [ 48, 49, 50, 51 ], + [ 52, 53, 54, 55 ] + ], + [ + [ 56, 57, 58, 59 ], + [ 60, 61, 62, 63 ] + ] + ] + ]; + + y = unflatten( x, -2, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 2, 2, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 16, 8, 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, -2, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 2, 2, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 16, 8, 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + // Last dimension: + expected = [ + [ + [ [ 0, 1 ], [ 2, 3 ] ], + [ [ 4, 5 ], [ 6, 7 ] ], + [ [ 8, 9 ], [ 10, 11 ] ], + [ [ 12, 13 ], [ 14, 15 ] ] + ], + [ + [ [ 16, 17 ], [ 18, 19 ] ], + [ [ 20, 21 ], [ 22, 23 ] ], + [ [ 24, 25 ], [ 26, 27 ] ], + [ [ 28, 29 ], [ 30, 31 ] ] + ], + [ + [ [ 32, 33 ], [ 34, 35 ] ], + [ [ 36, 37 ], [ 38, 39 ] ], + [ [ 40, 41 ], [ 42, 43 ] ], + [ [ 44, 45 ], [ 46, 47 ] ] + ], + [ + [ [ 48, 49 ], [ 50, 51 ] ], + [ [ 52, 53 ], [ 54, 55 ] ], + [ [ 56, 57 ], [ 58, 59 ] ], + [ [ 60, 61 ], [ 62, 63 ] ] + ] + ]; + + y = unflatten( x, -1, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 4, 2, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 16, 4, 2, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, -1, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 4, 2, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 16, 4, 2, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a view of an input ndarray in which a specified dimension is expanded over multiple dimensions (base; column-major)', function test( t ) { + var expected; + var buf; + var x; + var y; + + buf = zeroTo( 64 ); + x = ndarray( 'generic', buf, [ 4, 4, 4 ], [ 1, 4, 16 ], 0, 'column-major' ); + + // First dimension: + expected = [ + [ + [ + [ 0, 16, 32, 48 ], + [ 4, 20, 36, 52 ], + [ 8, 24, 40, 56 ], + [ 12, 28, 44, 60 ] + ], + [ + [ 2, 18, 34, 50 ], + [ 6, 22, 38, 54 ], + [ 10, 26, 42, 58 ], + [ 14, 30, 46, 62 ] + ] + ], + [ + [ + [ 1, 17, 33, 49 ], + [ 5, 21, 37, 53 ], + [ 9, 25, 41, 57 ], + [ 13, 29, 45, 61 ] + ], + [ + [ 3, 19, 35, 51 ], + [ 7, 23, 39, 55 ], + [ 11, 27, 43, 59 ], + [ 15, 31, 47, 63 ] + ] + ] + ]; + + y = unflatten( x, 0, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 2, 4, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 2, 4, 16 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, 0, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 2, 4, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 2, 4, 16 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + // Middle dimension: + expected = [ + [ + [ + [ 0, 16, 32, 48 ], + [ 8, 24, 40, 56 ] + ], + [ + [ 4, 20, 36, 52 ], + [ 12, 28, 44, 60 ] + ] + ], + [ + [ + [ 1, 17, 33, 49 ], + [ 9, 25, 41, 57 ] + ], + [ + [ 5, 21, 37, 53 ], + [ 13, 29, 45, 61 ] + ] + ], + [ + [ + [ 2, 18, 34, 50 ], + [ 10, 26, 42, 58 ] + ], + [ + [ 6, 22, 38, 54 ], + [ 14, 30, 46, 62 ] + ] + ], + [ + [ + [ 3, 19, 35, 51 ], + [ 11, 27, 43, 59 ] + ], + [ + [ 7, 23, 39, 55 ], + [ 15, 31, 47, 63 ] + ] + ] + ]; + + y = unflatten( x, 1, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 2, 2, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 4, 8, 16 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, 1, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 2, 2, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 4, 8, 16 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + // Last dimension: + expected = [ + [ + [ [ 0, 32 ], [ 16, 48 ] ], + [ [ 4, 36 ], [ 20, 52 ] ], + [ [ 8, 40 ], [ 24, 56 ] ], + [ [ 12, 44 ], [ 28, 60 ] ] + ], + [ + [ [ 1, 33 ], [ 17, 49 ] ], + [ [ 5, 37 ], [ 21, 53 ] ], + [ [ 9, 41 ], [ 25, 57 ] ], + [ [ 13, 45 ], [ 29, 61 ] ] + ], + [ + [ [ 2, 34 ], [ 18, 50 ] ], + [ [ 6, 38 ], [ 22, 54 ] ], + [ [ 10, 42 ], [ 26, 58 ] ], + [ [ 14, 46 ], [ 30, 62 ] ] + ], + [ + [ [ 3, 35 ], [ 19, 51 ] ], + [ [ 7, 39 ], [ 23, 55 ] ], + [ [ 11, 43 ], [ 27, 59 ] ], + [ [ 15, 47 ], [ 31, 63 ] ] + ] + ]; + + y = unflatten( x, 2, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 4, 2, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 4, 16, 32 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, 2, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 4, 2, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 4, 16, 32 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a view of an input ndarray in which a specified dimension is expanded over multiple dimensions (base; column-major; negative dimension indices)', function test( t ) { + var expected; + var buf; + var x; + var y; + + buf = zeroTo( 64 ); + x = ndarray( 'generic', buf, [ 4, 4, 4 ], [ 1, 4, 16 ], 0, 'column-major' ); + + // First dimension: + expected = [ + [ + [ + [ 0, 16, 32, 48 ], + [ 4, 20, 36, 52 ], + [ 8, 24, 40, 56 ], + [ 12, 28, 44, 60 ] + ], + [ + [ 2, 18, 34, 50 ], + [ 6, 22, 38, 54 ], + [ 10, 26, 42, 58 ], + [ 14, 30, 46, 62 ] + ] + ], + [ + [ + [ 1, 17, 33, 49 ], + [ 5, 21, 37, 53 ], + [ 9, 25, 41, 57 ], + [ 13, 29, 45, 61 ] + ], + [ + [ 3, 19, 35, 51 ], + [ 7, 23, 39, 55 ], + [ 11, 27, 43, 59 ], + [ 15, 31, 47, 63 ] + ] + ] + ]; + + y = unflatten( x, -3, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 2, 4, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 2, 4, 16 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, -3, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 2, 4, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 2, 4, 16 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + // Middle dimension: + expected = [ + [ + [ + [ 0, 16, 32, 48 ], + [ 8, 24, 40, 56 ] + ], + [ + [ 4, 20, 36, 52 ], + [ 12, 28, 44, 60 ] + ] + ], + [ + [ + [ 1, 17, 33, 49 ], + [ 9, 25, 41, 57 ] + ], + [ + [ 5, 21, 37, 53 ], + [ 13, 29, 45, 61 ] + ] + ], + [ + [ + [ 2, 18, 34, 50 ], + [ 10, 26, 42, 58 ] + ], + [ + [ 6, 22, 38, 54 ], + [ 14, 30, 46, 62 ] + ] + ], + [ + [ + [ 3, 19, 35, 51 ], + [ 11, 27, 43, 59 ] + ], + [ + [ 7, 23, 39, 55 ], + [ 15, 31, 47, 63 ] + ] + ] + ]; + + y = unflatten( x, -2, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 2, 2, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 4, 8, 16 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, -2, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 2, 2, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 4, 8, 16 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + // Last dimension: + expected = [ + [ + [ [ 0, 32 ], [ 16, 48 ] ], + [ [ 4, 36 ], [ 20, 52 ] ], + [ [ 8, 40 ], [ 24, 56 ] ], + [ [ 12, 44 ], [ 28, 60 ] ] + ], + [ + [ [ 1, 33 ], [ 17, 49 ] ], + [ [ 5, 37 ], [ 21, 53 ] ], + [ [ 9, 41 ], [ 25, 57 ] ], + [ [ 13, 45 ], [ 29, 61 ] ] + ], + [ + [ [ 2, 34 ], [ 18, 50 ] ], + [ [ 6, 38 ], [ 22, 54 ] ], + [ [ 10, 42 ], [ 26, 58 ] ], + [ [ 14, 46 ], [ 30, 62 ] ] + ], + [ + [ [ 3, 35 ], [ 19, 51 ] ], + [ [ 7, 39 ], [ 23, 55 ] ], + [ [ 11, 43 ], [ 27, 59 ] ], + [ [ 15, 47 ], [ 31, 63 ] ] + ] + ]; + + y = unflatten( x, -1, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 4, 2, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 4, 16, 32 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, -1, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 4, 2, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 1, 4, 16, 32 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a view of an input ndarray in which a specified dimension is expanded over multiple dimensions (row-major)', function test( t ) { + var expected; + var x; + var y; + + x = array( zeroTo( 64 ), { + 'shape': [ 4, 4, 4 ] + }); + + // First dimension: + expected = [ + [ + [ + [ 0, 1, 2, 3 ], + [ 4, 5, 6, 7 ], + [ 8, 9, 10, 11 ], + [ 12, 13, 14, 15 ] + ], + [ + [ 16, 17, 18, 19 ], + [ 20, 21, 22, 23 ], + [ 24, 25, 26, 27 ], + [ 28, 29, 30, 31 ] + ] + ], + [ + [ + [ 32, 33, 34, 35 ], + [ 36, 37, 38, 39 ], + [ 40, 41, 42, 43 ], + [ 44, 45, 46, 47 ] + ], + [ + [ 48, 49, 50, 51 ], + [ 52, 53, 54, 55 ], + [ 56, 57, 58, 59 ], + [ 60, 61, 62, 63 ] + ] + ] + ]; + + y = unflatten( x, 0, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 2, 4, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 32, 16, 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), true, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, 0, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 2, 4, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 32, 16, 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + // Middle dimension: + expected = [ + [ + [ + [ 0, 1, 2, 3 ], + [ 4, 5, 6, 7 ] + ], + [ + [ 8, 9, 10, 11 ], + [ 12, 13, 14, 15 ] + ] + ], + [ + [ + [ 16, 17, 18, 19 ], + [ 20, 21, 22, 23 ] + ], + [ + [ 24, 25, 26, 27 ], + [ 28, 29, 30, 31 ] + ] + ], + [ + [ + [ 32, 33, 34, 35 ], + [ 36, 37, 38, 39 ] + ], + [ + [ 40, 41, 42, 43 ], + [ 44, 45, 46, 47 ] + ] + ], + [ + [ + [ 48, 49, 50, 51 ], + [ 52, 53, 54, 55 ] + ], + [ + [ 56, 57, 58, 59 ], + [ 60, 61, 62, 63 ] + ] + ] + ]; + + y = unflatten( x, 1, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 2, 2, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 16, 8, 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), true, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, 1, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 2, 2, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 16, 8, 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + // Last dimension: + expected = [ + [ + [ [ 0, 1 ], [ 2, 3 ] ], + [ [ 4, 5 ], [ 6, 7 ] ], + [ [ 8, 9 ], [ 10, 11 ] ], + [ [ 12, 13 ], [ 14, 15 ] ] + ], + [ + [ [ 16, 17 ], [ 18, 19 ] ], + [ [ 20, 21 ], [ 22, 23 ] ], + [ [ 24, 25 ], [ 26, 27 ] ], + [ [ 28, 29 ], [ 30, 31 ] ] + ], + [ + [ [ 32, 33 ], [ 34, 35 ] ], + [ [ 36, 37 ], [ 38, 39 ] ], + [ [ 40, 41 ], [ 42, 43 ] ], + [ [ 44, 45 ], [ 46, 47 ] ] + ], + [ + [ [ 48, 49 ], [ 50, 51 ] ], + [ [ 52, 53 ], [ 54, 55 ] ], + [ [ 56, 57 ], [ 58, 59 ] ], + [ [ 60, 61 ], [ 62, 63 ] ] + ] + ]; + + y = unflatten( x, 2, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 4, 2, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 16, 4, 2, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), true, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, 2, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 4, 2, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 16, 4, 2, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a view of an input ndarray in which a specified dimension is expanded over multiple dimensions (row-major; negative dimension indices)', function test( t ) { + var expected; + var x; + var y; + + x = array( zeroTo( 64 ), { + 'shape': [ 4, 4, 4 ] + }); + + // First dimension: + expected = [ + [ + [ + [ 0, 1, 2, 3 ], + [ 4, 5, 6, 7 ], + [ 8, 9, 10, 11 ], + [ 12, 13, 14, 15 ] + ], + [ + [ 16, 17, 18, 19 ], + [ 20, 21, 22, 23 ], + [ 24, 25, 26, 27 ], + [ 28, 29, 30, 31 ] + ] + ], + [ + [ + [ 32, 33, 34, 35 ], + [ 36, 37, 38, 39 ], + [ 40, 41, 42, 43 ], + [ 44, 45, 46, 47 ] + ], + [ + [ 48, 49, 50, 51 ], + [ 52, 53, 54, 55 ], + [ 56, 57, 58, 59 ], + [ 60, 61, 62, 63 ] + ] + ] + ]; + + y = unflatten( x, -3, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 2, 4, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 32, 16, 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), true, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, -3, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 2, 2, 4, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 32, 16, 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + // Middle dimension: + expected = [ + [ + [ + [ 0, 1, 2, 3 ], + [ 4, 5, 6, 7 ] + ], + [ + [ 8, 9, 10, 11 ], + [ 12, 13, 14, 15 ] + ] + ], + [ + [ + [ 16, 17, 18, 19 ], + [ 20, 21, 22, 23 ] + ], + [ + [ 24, 25, 26, 27 ], + [ 28, 29, 30, 31 ] + ] + ], + [ + [ + [ 32, 33, 34, 35 ], + [ 36, 37, 38, 39 ] + ], + [ + [ 40, 41, 42, 43 ], + [ 44, 45, 46, 47 ] + ] + ], + [ + [ + [ 48, 49, 50, 51 ], + [ 52, 53, 54, 55 ] + ], + [ + [ 56, 57, 58, 59 ], + [ 60, 61, 62, 63 ] + ] + ] + ]; + + y = unflatten( x, -2, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 2, 2, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 16, 8, 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), true, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, -2, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 2, 2, 4 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 16, 8, 4, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + // Last dimension: + expected = [ + [ + [ [ 0, 1 ], [ 2, 3 ] ], + [ [ 4, 5 ], [ 6, 7 ] ], + [ [ 8, 9 ], [ 10, 11 ] ], + [ [ 12, 13 ], [ 14, 15 ] ] + ], + [ + [ [ 16, 17 ], [ 18, 19 ] ], + [ [ 20, 21 ], [ 22, 23 ] ], + [ [ 24, 25 ], [ 26, 27 ] ], + [ [ 28, 29 ], [ 30, 31 ] ] + ], + [ + [ [ 32, 33 ], [ 34, 35 ] ], + [ [ 36, 37 ], [ 38, 39 ] ], + [ [ 40, 41 ], [ 42, 43 ] ], + [ [ 44, 45 ], [ 46, 47 ] ] + ], + [ + [ [ 48, 49 ], [ 50, 51 ] ], + [ [ 52, 53 ], [ 54, 55 ] ], + [ [ 56, 57 ], [ 58, 59 ] ], + [ [ 60, 61 ], [ 62, 63 ] ] + ] + ]; + + y = unflatten( x, -1, [ 2, 2 ], false ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 4, 2, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 16, 4, 2, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), true, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + y = unflatten( x, -1, [ 2, 2 ], true ); + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( getShape( y ), [ 4, 4, 2, 2 ], 'returns expected value' ); + t.deepEqual( getStrides( y ), [ 16, 4, 2, 1 ], 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + t.deepEqual( ndarray2array( y ), expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/concat/test/test.assign.js b/lib/node_modules/@stdlib/ndarray/concat/test/test.assign.js index dcae9c6410a3..402efbbe572b 100644 --- a/lib/node_modules/@stdlib/ndarray/concat/test/test.assign.js +++ b/lib/node_modules/@stdlib/ndarray/concat/test/test.assign.js @@ -322,7 +322,7 @@ tape( 'the function throws an error if provided a second argument which has a da }) ] ]; - out = zeros( [ 4 ], { + out = empty( [ 4 ], { 'dtype': 'bool' }); @@ -353,7 +353,7 @@ tape( 'the function throws an error if provided a second argument which has a da }) ] ]; - out = zeros( [ 4 ], { + out = empty( [ 4 ], { 'dtype': 'bool' }); diff --git a/lib/node_modules/@stdlib/ndarray/fancy/test/test.instance.tostring.js b/lib/node_modules/@stdlib/ndarray/fancy/test/test.instance.tostring.js index d65f5612e9fe..4e258059f589 100644 --- a/lib/node_modules/@stdlib/ndarray/fancy/test/test.instance.tostring.js +++ b/lib/node_modules/@stdlib/ndarray/fancy/test/test.instance.tostring.js @@ -175,7 +175,8 @@ tape( 'a FancyArray constructor returns an instance which has a custom `toString var arr; dtype = 'generic'; - buffer = new Array( 1e4 ); + buffer = []; + buffer.length = 1e4; shape = [ buffer.length ]; order = 'row-major'; strides = [ 1 ]; diff --git a/lib/node_modules/@stdlib/ndarray/lib/index.js b/lib/node_modules/@stdlib/ndarray/lib/index.js index eb3c631cf629..4d64d8733f73 100644 --- a/lib/node_modules/@stdlib/ndarray/lib/index.js +++ b/lib/node_modules/@stdlib/ndarray/lib/index.js @@ -675,6 +675,15 @@ setReadOnly( ns, 'push', require( '@stdlib/ndarray/push' ) ); */ setReadOnly( ns, 'reject', require( '@stdlib/ndarray/reject' ) ); +/** +* @name removeSingletonDimensions +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/ndarray/remove-singleton-dimensions} +*/ +setReadOnly( ns, 'removeSingletonDimensions', require( '@stdlib/ndarray/remove-singleton-dimensions' ) ); + /** * @name reverse * @memberof ns diff --git a/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/README.md b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/README.md new file mode 100644 index 000000000000..745c6893ec62 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/README.md @@ -0,0 +1,131 @@ + + +# removeSingletonDimensions + +> Return a read-only view of an input [ndarray][@stdlib/ndarray/ctor] with singleton dimensions removed. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var removeSingletonDimensions = require( '@stdlib/ndarray/remove-singleton-dimensions' ); +``` + +#### removeSingletonDimensions( x ) + +Returns a read-only view of an input [ndarray][@stdlib/ndarray/ctor] with singleton dimensions removed. + +```javascript +var array = require( '@stdlib/ndarray/array' ); + +// Create a 1x2x2 ndarray: +var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] ); +// returns [ [ [ 1, 2 ], [ 3, 4 ] ] ] + +// Remove singleton dimensions: +var y = removeSingletonDimensions( x ); +// returns [ [ 1, 2 ], [ 3, 4 ] ] +``` + +The function accepts the following arguments: + +- **x**: input [ndarray][@stdlib/ndarray/ctor]. + +
+ + + + + +
+ +## Notes + +- The function always returns a new ndarray instance even if the input ndarray does not contain any singleton dimensions. + +
+ + + + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var removeSingletonDimensions = require( '@stdlib/ndarray/remove-singleton-dimensions' ); + +var x = uniform( [ 1, 1, 3, 3, 3 ], -10.0, 10.0 ); +console.log( ndarray2array( x ) ); + +var y = removeSingletonDimensions( x ); +console.log( ndarray2array( y ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/benchmark/benchmark.js new file mode 100644 index 000000000000..f37ffe56630f --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/benchmark/benchmark.js @@ -0,0 +1,159 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var empty = require( '@stdlib/ndarray/empty' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var removeSingletonDimensions = require( './../lib' ); + + +// MAIN // + +bench( format( '%s::no_singletons,1d', pkg ), function benchmark( b ) { + var values; + var v; + var i; + + /* eslint-disable object-curly-newline, stdlib/line-closing-bracket-spacing */ + + values = [ + empty( [ 2 ], { 'dtype': 'float64' } ), + empty( [ 2 ], { 'dtype': 'float32' } ), + empty( [ 2 ], { 'dtype': 'int32' } ), + empty( [ 2 ], { 'dtype': 'complex128' } ), + empty( [ 2 ], { 'dtype': 'generic' } ) + ]; + + /* eslint-enable object-curly-newline, stdlib/line-closing-bracket-spacing */ + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = removeSingletonDimensions( values[ i%values.length ] ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isndarrayLike( v ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::no_singletons,2d', pkg ), function benchmark( b ) { + var values; + var v; + var i; + + /* eslint-disable object-curly-newline, stdlib/line-closing-bracket-spacing */ + + values = [ + empty( [ 2, 2 ], { 'dtype': 'float64' } ), + empty( [ 2, 2 ], { 'dtype': 'float32' } ), + empty( [ 2, 2 ], { 'dtype': 'int32' } ), + empty( [ 2, 2 ], { 'dtype': 'complex128' } ), + empty( [ 2, 2 ], { 'dtype': 'generic' } ) + ]; + + /* eslint-enable object-curly-newline, stdlib/line-closing-bracket-spacing */ + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = removeSingletonDimensions( values[ i%values.length ] ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isndarrayLike( v ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::singletons,2d', pkg ), function benchmark( b ) { + var values; + var v; + var i; + + /* eslint-disable object-curly-newline, stdlib/line-closing-bracket-spacing */ + + values = [ + empty( [ 1, 2 ], { 'dtype': 'float64' } ), + empty( [ 1, 2 ], { 'dtype': 'float32' } ), + empty( [ 1, 2 ], { 'dtype': 'int32' } ), + empty( [ 1, 2 ], { 'dtype': 'complex128' } ), + empty( [ 1, 2 ], { 'dtype': 'generic' } ) + ]; + + /* eslint-enable object-curly-newline, stdlib/line-closing-bracket-spacing */ + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = removeSingletonDimensions( values[ i%values.length ] ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isndarrayLike( v ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::singletons,3d', pkg ), function benchmark( b ) { + var values; + var v; + var i; + + /* eslint-disable object-curly-newline, stdlib/line-closing-bracket-spacing */ + + values = [ + empty( [ 1, 2, 2 ], { 'dtype': 'float64' } ), + empty( [ 1, 2, 2 ], { 'dtype': 'float32' } ), + empty( [ 1, 2, 2 ], { 'dtype': 'int32' } ), + empty( [ 1, 2, 2 ], { 'dtype': 'complex128' } ), + empty( [ 1, 2, 2 ], { 'dtype': 'generic' } ) + ]; + + /* eslint-enable object-curly-newline, stdlib/line-closing-bracket-spacing */ + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = removeSingletonDimensions( values[ i%values.length ] ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isndarrayLike( v ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/docs/repl.txt new file mode 100644 index 000000000000..4444613df3fc --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/docs/repl.txt @@ -0,0 +1,29 @@ + +{{alias}}( x ) + Returns a read-only view of an input ndarray with singleton dimensions + removed. + + The function always returns a new ndarray instance even if the input ndarray + does not contain any singleton dimensions. + + Parameters + ---------- + x: ndarray + Input array. + + Returns + ------- + out: ndarray + Output array. + + Examples + -------- + > var opts = { 'ndmin': 5 }; + > var x = {{alias:@stdlib/ndarray/array}}( [ [ 1, 2 ], [ 3, 4 ] ], opts ) + [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] + > var y = {{alias}}( x ) + [ [ 1, 2 ], [ 3, 4 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/docs/types/index.d.ts new file mode 100644 index 000000000000..e8fa1fb222fe --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/docs/types/index.d.ts @@ -0,0 +1,47 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray } from '@stdlib/types/ndarray'; + +/** +* Returns a read-only view of an input ndarray with singleton dimensions removed. +* +* @param x - input array +* @returns output array +* +* @example +* var array = require( `@stdlib/ndarray/array` ); +* +* var x = array( [ [ 1, 2 ], [ 3, 4 ] ], { +* 'ndmin': 5 +* }); +* // returns [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] +* +* var y = removeSingletonDimensions( x ); +* // returns [ [ 1, 2 ], [ 3, 4 ] ] +*/ +declare function removeSingletonDimensions = typedndarray>( x: U ): U; + + +// EXPORTS // + +export = removeSingletonDimensions; diff --git a/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/docs/types/test.ts new file mode 100644 index 000000000000..5356e4bc6eea --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/docs/types/test.ts @@ -0,0 +1,56 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import removeSingletonDimensions = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 1, 1, 2, 2 ], { + 'dtype': 'float64' + }); + + removeSingletonDimensions( x ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the function is not provided a first argument which is an ndarray... +{ + removeSingletonDimensions( '5' ); // $ExpectError + removeSingletonDimensions( 5 ); // $ExpectError + removeSingletonDimensions( true ); // $ExpectError + removeSingletonDimensions( false ); // $ExpectError + removeSingletonDimensions( null ); // $ExpectError + removeSingletonDimensions( {} ); // $ExpectError + removeSingletonDimensions( [ '5' ] ); // $ExpectError + removeSingletonDimensions( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 1, 1, 2, 2 ], { + 'dtype': 'float64' + }); + + removeSingletonDimensions(); // $ExpectError + removeSingletonDimensions( x, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/examples/index.js b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/examples/index.js new file mode 100644 index 000000000000..4d9daac8dfd6 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/examples/index.js @@ -0,0 +1,29 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var removeSingletonDimensions = require( './../lib' ); + +var x = uniform( [ 1, 1, 3, 3, 3 ], -10.0, 10.0 ); +console.log( ndarray2array( x ) ); + +var y = removeSingletonDimensions( x ); +console.log( ndarray2array( y ) ); diff --git a/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/lib/index.js b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/lib/index.js new file mode 100644 index 000000000000..d6efae763959 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/lib/index.js @@ -0,0 +1,46 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return a read-only view of an input ndarray with singleton dimensions removed. +* +* @module @stdlib/ndarray/remove-singleton-dimensions +* +* @example +* var array = require( '@stdlib/ndarray/array' ); +* var removeSingletonDimensions = require( '@stdlib/ndarray/remove-singleton-dimensions' ); +* +* var x = array( [ [ 1, 2 ], [ 3, 4 ] ], { +* 'ndmin': 5 +* }); +* // returns [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] +* +* var y = removeSingletonDimensions( x ); +* // returns [ [ 1, 2 ], [ 3, 4 ] ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/lib/main.js b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/lib/main.js new file mode 100644 index 000000000000..ec5992ee6e62 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/lib/main.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var base = require( '@stdlib/ndarray/base/remove-singleton-dimensions' ); +var format = require( '@stdlib/string/format' ); + + +// MAIN // + +/** +* Returns a read-only view of an input ndarray with singleton dimensions removed. +* +* @param {ndarray} x - input array +* @throws {TypeError} first argument must be an ndarray +* @returns {ndarray} ndarray view +* +* @example +* var array = require( '@stdlib/ndarray/array' ); +* +* var x = array( [ [ 1, 2 ], [ 3, 4 ] ], { +* 'ndmin': 5 +* }); +* // returns [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] +* +* var y = removeSingletonDimensions( x ); +* // returns [ [ 1, 2 ], [ 3, 4 ] ] +*/ +function removeSingletonDimensions( x ) { + if ( !isndarrayLike( x ) ) { + throw new TypeError( format( 'invalid argument. First argument must be an ndarray. Value: `%s`.', x ) ); + } + return base( x, false ); +} + + +// EXPORTS // + +module.exports = removeSingletonDimensions; diff --git a/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/package.json b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/package.json new file mode 100644 index 000000000000..a61f4097ad6e --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/ndarray/remove-singleton-dimensions", + "version": "0.0.0", + "description": "Return a read-only view of an input ndarray with singleton dimensions removed.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "types", + "data", + "structure", + "vector", + "ndarray", + "matrix", + "remove", + "squeeze", + "reshape", + "singleton", + "dimensions", + "multidimensional" + ] +} diff --git a/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/test/test.js b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/test/test.js new file mode 100644 index 000000000000..968c90425c33 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/remove-singleton-dimensions/test/test.js @@ -0,0 +1,117 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isReadOnly = require( '@stdlib/ndarray/base/assert/is-read-only' ); +var array = require( '@stdlib/ndarray/array' ); +var getShape = require( '@stdlib/ndarray/shape' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var removeSingletonDimensions = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof removeSingletonDimensions, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray', function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + removeSingletonDimensions( value ); + }; + } +}); + +tape( 'the function removes singleton dimensions', function test( t ) { + var expected; + var x; + var y; + + x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); + y = removeSingletonDimensions( x ); + + expected = [ 2, 2 ]; + + t.deepEqual( getShape( y ), expected, 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.notEqual( y, x, 'returns expected value' ); + t.strictEqual( isReadOnly( y ), true, 'returns expected value' ); + + x = array( [ [ 1, 2 ], [ 3, 4 ] ], { + 'ndmin': 5 + }); + y = removeSingletonDimensions( x ); + + expected = [ 2, 2 ]; + + t.deepEqual( getShape( y ), expected, 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.notEqual( y, x, 'returns expected value' ); + t.strictEqual( isReadOnly( y ), true, 'returns expected value' ); + + x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] ); + y = removeSingletonDimensions( x ); + + expected = [ 2, 2 ]; + + t.deepEqual( getShape( y ), expected, 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.notEqual( y, x, 'returns expected value' ); + t.strictEqual( isReadOnly( y ), true, 'returns expected value' ); + + x = array( [ [ 1, 2 ], [ 3, 4 ] ], { + 'ndmin': 3 + }); + y = removeSingletonDimensions( x ); + + expected = [ 2, 2 ]; + + t.deepEqual( getShape( y ), expected, 'returns expected value' ); + t.strictEqual( getData( y ), getData( x ), 'returns expected value' ); + t.notEqual( y, x, 'returns expected value' ); + t.strictEqual( isReadOnly( y ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/to-fancy/examples/set_slice.3d.js b/lib/node_modules/@stdlib/ndarray/to-fancy/examples/set_slice.3d.js index 4887033585ba..5385ba006ae1 100644 --- a/lib/node_modules/@stdlib/ndarray/to-fancy/examples/set_slice.3d.js +++ b/lib/node_modules/@stdlib/ndarray/to-fancy/examples/set_slice.3d.js @@ -65,18 +65,18 @@ var s = E( 1, S(0,_,2), _ ); y[ s ] = 100; console.log( toArray( y ) ); /* => - [ - [ - [ 3, 4 ], - [ 5, 6 ], - [ 7, 8 ] - ], - [ - [ 100, 100 ], - [ 11, 12 ], - [ 100, 100 ] - ] - ] + [ + [ + [ 3, 4 ], + [ 5, 6 ], + [ 7, 8 ] + ], + [ + [ 100, 100 ], + [ 11, 12 ], + [ 100, 100 ] + ] + ] */ // Create a vector of zeros: @@ -87,16 +87,16 @@ var z = ndzeros( [ 2 ] ); y[ '0,:,:' ] = z; console.log( toArray( y ) ); /* => - [ - [ - [ 0, 0 ], - [ 0, 0 ], - [ 0, 0 ] - ], - [ - [ 100, 100 ], - [ 11, 12 ], - [ 100, 100 ] - ] - ] + [ + [ + [ 0, 0 ], + [ 0, 0 ], + [ 0, 0 ] + ], + [ + [ 100, 100 ], + [ 11, 12 ], + [ 100, 100 ] + ] + ] */ diff --git a/lib/node_modules/@stdlib/ndarray/to-string/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/to-string/docs/types/index.d.ts index 34843ec46261..e6a14d5449ab 100644 --- a/lib/node_modules/@stdlib/ndarray/to-string/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/ndarray/to-string/docs/types/index.d.ts @@ -33,7 +33,7 @@ import { ndarray } from '@stdlib/types/ndarray'; * @returns string representation * * @example -* var array = require( `@stdlib/ndarray/array` ); +* var array = require( '@stdlib/ndarray/array' ); * * var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); * // returns diff --git a/lib/node_modules/@stdlib/ndarray/with/README.md b/lib/node_modules/@stdlib/ndarray/with/README.md index 323d75611679..f25aea958a7b 100644 --- a/lib/node_modules/@stdlib/ndarray/with/README.md +++ b/lib/node_modules/@stdlib/ndarray/with/README.md @@ -53,10 +53,7 @@ var x = zeros( [ 2, 2 ], { // returns var out = ndarrayWith( x, [ 0, 0 ], 1.0 ); -// returns - -var v = out.get( 0, 0 ); -// returns 1.0 +// returns [ [ 1, 0 ], [ 0, 0 ] ] ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/ndarray/with/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/with/docs/repl.txt index b150afdae620..d6924840b942 100644 --- a/lib/node_modules/@stdlib/ndarray/with/docs/repl.txt +++ b/lib/node_modules/@stdlib/ndarray/with/docs/repl.txt @@ -22,9 +22,8 @@ Examples -------- > var x = {{alias:@stdlib/ndarray/array}}( [ [ 1, 2 ], [ 3, 4 ] ] ); - > var out = {{alias}}( x, [ 0, 0 ], 5 ); - > var v = out.get( 0, 0 ) - 5 + > var out = {{alias}}( x, [ 0, 0 ], 5 ) + [ [ 5, 2 ], [ 3, 4 ] ] See Also -------- diff --git a/lib/node_modules/@stdlib/ndarray/with/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/with/docs/types/index.d.ts index dbb5485f685c..ee6298bb9ad9 100644 --- a/lib/node_modules/@stdlib/ndarray/with/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/ndarray/with/docs/types/index.d.ts @@ -42,10 +42,7 @@ import { typedndarray } from '@stdlib/types/ndarray'; * var x = ndarray( 'generic', buffer, shape, strides, offset, order ); * * var out = ndarrayWith( x, [ 0, 0 ], 5 ); -* // returns -* -* var v = out.get( 0, 0 ); -* // returns 5 +* // returns [ [ 5, 2 ], [ 3, 4 ] ] */ declare function ndarrayWith = typedndarray>( x: typedndarray, indices: Array, value: T ): U; diff --git a/lib/node_modules/@stdlib/ndarray/with/lib/index.js b/lib/node_modules/@stdlib/ndarray/with/lib/index.js index 308b608a819e..1a508ec879ee 100644 --- a/lib/node_modules/@stdlib/ndarray/with/lib/index.js +++ b/lib/node_modules/@stdlib/ndarray/with/lib/index.js @@ -37,10 +37,7 @@ * // returns * * var out = ndarrayWith( x, [ 0, 0 ], 5 ); -* // returns -* -* var v = out.get( 0, 0 ); -* // returns 5 +* // returns [ [ 5, 2 ], [ 3, 4 ] ] */ // MODULES // diff --git a/lib/node_modules/@stdlib/ndarray/with/lib/main.js b/lib/node_modules/@stdlib/ndarray/with/lib/main.js index dae26435a0fb..15e48eb0d75f 100644 --- a/lib/node_modules/@stdlib/ndarray/with/lib/main.js +++ b/lib/node_modules/@stdlib/ndarray/with/lib/main.js @@ -58,10 +58,7 @@ var format = require( '@stdlib/string/format' ); * var x = ndarray( 'generic', buffer, shape, strides, offset, order ); * * var out = ndarrayWith( x, [ 0, 0 ], 5 ); -* // returns -* -* var v = out.get( 0, 0 ); -* // returns 5 +* // returns [ [ 5, 2 ], [ 3, 4 ] ] */ function ndarrayWith( x, indices, value ) { var args; diff --git a/lib/node_modules/@stdlib/number/float32/base/add/README.md b/lib/node_modules/@stdlib/number/float32/base/add/README.md index a2c0b3df9e57..35f0c20a46dc 100644 --- a/lib/node_modules/@stdlib/number/float32/base/add/README.md +++ b/lib/node_modules/@stdlib/number/float32/base/add/README.md @@ -82,18 +82,14 @@ v = addf( NaN, NaN ); ```javascript -var rand = require( '@stdlib/random/base/discrete-uniform' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var addf = require( '@stdlib/number/float32/base/add' ); -var x; -var y; -var i; +var x = discreteUniform( 100, -50, 50 ); +var y = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - x = rand( -50, 50 ); - y = rand( -50, 50 ); - console.log( '%d + %d = %d', x, y, addf( x, y ) ); -} +logEachMap( '%d + %d = %d', x, y, addf ); ``` diff --git a/lib/node_modules/@stdlib/number/float32/base/add/examples/index.js b/lib/node_modules/@stdlib/number/float32/base/add/examples/index.js index 0e7cac963837..dcd1d9f6c548 100644 --- a/lib/node_modules/@stdlib/number/float32/base/add/examples/index.js +++ b/lib/node_modules/@stdlib/number/float32/base/add/examples/index.js @@ -18,15 +18,11 @@ 'use strict'; -var rand = require( '@stdlib/random/base/discrete-uniform' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var addf = require( './../lib' ); -var x; -var y; -var i; +var x = discreteUniform( 100, -50, 50 ); +var y = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - x = rand( -50, 50 ); - y = rand( -50, 50 ); - console.log( '%d + %d = %d', x, y, addf( x, y ) ); -} +logEachMap( '%d + %d = %d', x, y, addf ); diff --git a/lib/node_modules/@stdlib/number/float32/base/div/README.md b/lib/node_modules/@stdlib/number/float32/base/div/README.md index c82ab09619d2..6f44c5d1b1f8 100644 --- a/lib/node_modules/@stdlib/number/float32/base/div/README.md +++ b/lib/node_modules/@stdlib/number/float32/base/div/README.md @@ -82,18 +82,14 @@ v = divf( NaN, NaN ); ```javascript -var rand = require( '@stdlib/random/base/discrete-uniform' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var divf = require( '@stdlib/number/float32/base/div' ); -var x; -var y; -var i; +var x = discreteUniform( 100, -50, 50 ); +var y = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - x = rand( -50, 50 ); - y = rand( -50, 50 ); - console.log( '%d / %d = %d', x, y, divf( x, y ) ); -} +logEachMap( '%d / %d = %d', x, y, divf ); ``` diff --git a/lib/node_modules/@stdlib/number/float32/base/div/examples/index.js b/lib/node_modules/@stdlib/number/float32/base/div/examples/index.js index bc94ca0d73ef..f60da10165f4 100644 --- a/lib/node_modules/@stdlib/number/float32/base/div/examples/index.js +++ b/lib/node_modules/@stdlib/number/float32/base/div/examples/index.js @@ -18,15 +18,11 @@ 'use strict'; -var rand = require( '@stdlib/random/base/discrete-uniform' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var divf = require( './../lib' ); -var x; -var y; -var i; +var x = discreteUniform( 100, -50, 50 ); +var y = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - x = rand( -50, 50 ); - y = rand( -50, 50 ); - console.log( '%d / %d = %d', x, y, divf( x, y ) ); -} +logEachMap( '%d / %d = %d', x, y, divf ); diff --git a/lib/node_modules/@stdlib/number/float32/base/identity/README.md b/lib/node_modules/@stdlib/number/float32/base/identity/README.md index 9585b09f0809..b9ddc378a4f4 100644 --- a/lib/node_modules/@stdlib/number/float32/base/identity/README.md +++ b/lib/node_modules/@stdlib/number/float32/base/identity/README.md @@ -85,17 +85,13 @@ v = identityf( NaN ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var identityf = require( '@stdlib/number/float32/base/identity' ); -var rand; -var i; +var x = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - rand = round( randu() * 100.0 ) - 50.0; - console.log( 'identity(%d) = %d', rand, identityf( rand ) ); -} +logEachMap( 'identity(%d) = %d', x, identityf ); ``` diff --git a/lib/node_modules/@stdlib/number/float32/base/identity/examples/index.js b/lib/node_modules/@stdlib/number/float32/base/identity/examples/index.js index 34ef0d803252..e99a2df14808 100644 --- a/lib/node_modules/@stdlib/number/float32/base/identity/examples/index.js +++ b/lib/node_modules/@stdlib/number/float32/base/identity/examples/index.js @@ -18,14 +18,10 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var identityf = require( './../lib' ); -var rand; -var i; +var x = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - rand = round( randu() * 100.0 ) - 50.0; - console.log( 'identity(%d) = %d', rand, identityf( rand ) ); -} +logEachMap( 'identity(%d) = %d', x, identityf ); diff --git a/lib/node_modules/@stdlib/number/float32/base/mul/README.md b/lib/node_modules/@stdlib/number/float32/base/mul/README.md index fe37fec1dc8f..1607fbb8a8d9 100644 --- a/lib/node_modules/@stdlib/number/float32/base/mul/README.md +++ b/lib/node_modules/@stdlib/number/float32/base/mul/README.md @@ -82,18 +82,14 @@ v = mulf( NaN, NaN ); ```javascript -var rand = require( '@stdlib/random/base/discrete-uniform' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var mulf = require( '@stdlib/number/float32/base/mul' ); -var x; -var y; -var i; +var x = discreteUniform( 100, -50, 50 ); +var y = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - x = rand( -50, 50 ); - y = rand( -50, 50 ); - console.log( '%d x %d = %d', x, y, mulf( x, y ) ); -} +logEachMap( '%d x %d = %d', x, y, mulf ); ``` diff --git a/lib/node_modules/@stdlib/number/float32/base/mul/examples/index.js b/lib/node_modules/@stdlib/number/float32/base/mul/examples/index.js index 470cf7adceab..bbe377a5876b 100644 --- a/lib/node_modules/@stdlib/number/float32/base/mul/examples/index.js +++ b/lib/node_modules/@stdlib/number/float32/base/mul/examples/index.js @@ -18,15 +18,11 @@ 'use strict'; -var rand = require( '@stdlib/random/base/discrete-uniform' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var mulf = require( './../lib' ); -var x; -var y; -var i; +var x = discreteUniform( 100, -50, 50 ); +var y = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - x = rand( -50, 50 ); - y = rand( -50, 50 ); - console.log( '%d x %d = %d', x, y, mulf( x, y ) ); -} +logEachMap( '%d x %d = %d', x, y, mulf ); diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/README.md b/lib/node_modules/@stdlib/number/float32/base/signbit/README.md index 74224616c756..aa1de3440726 100644 --- a/lib/node_modules/@stdlib/number/float32/base/signbit/README.md +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/README.md @@ -156,7 +156,7 @@ int main( void ) { int8_t out; int i; for ( i = 0; i < 9; i++ ) { - stdlib_base_float32_signbit( x[ i ], &out ); + out = stdlib_base_float32_signbit( x[ i ] ); printf( "%f => signbit: %" PRId8 "\n", x[ i ], out ); } } diff --git a/lib/node_modules/@stdlib/number/float32/base/sub/README.md b/lib/node_modules/@stdlib/number/float32/base/sub/README.md index f425e8162f97..de4d2b6031f9 100644 --- a/lib/node_modules/@stdlib/number/float32/base/sub/README.md +++ b/lib/node_modules/@stdlib/number/float32/base/sub/README.md @@ -82,18 +82,14 @@ v = subf( NaN, NaN ); ```javascript -var rand = require( '@stdlib/random/base/discrete-uniform' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var subf = require( '@stdlib/number/float32/base/sub' ); -var x; -var y; -var i; +var x = discreteUniform( 100, -50, 50 ); +var y = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - x = rand( -50, 50 ); - y = rand( -50, 50 ); - console.log( '%d - %d = %d', x, y, subf( x, y ) ); -} +logEachMap( '%d - %d = %d', x, y, subf ); ``` diff --git a/lib/node_modules/@stdlib/number/float32/base/sub/examples/index.js b/lib/node_modules/@stdlib/number/float32/base/sub/examples/index.js index 858f3b57cc7a..81d54513d036 100644 --- a/lib/node_modules/@stdlib/number/float32/base/sub/examples/index.js +++ b/lib/node_modules/@stdlib/number/float32/base/sub/examples/index.js @@ -18,15 +18,11 @@ 'use strict'; -var rand = require( '@stdlib/random/base/discrete-uniform' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var subf = require( './../lib' ); -var x; -var y; -var i; +var x = discreteUniform( 100, -50, 50 ); +var y = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - x = rand( -50, 50 ); - y = rand( -50, 50 ); - console.log( '%d - %d = %d', x, y, subf( x, y ) ); -} +logEachMap( '%d - %d = %d', x, y, subf ); diff --git a/lib/node_modules/@stdlib/number/float64/base/div/README.md b/lib/node_modules/@stdlib/number/float64/base/div/README.md index e70925e70659..4248b5262052 100644 --- a/lib/node_modules/@stdlib/number/float64/base/div/README.md +++ b/lib/node_modules/@stdlib/number/float64/base/div/README.md @@ -82,18 +82,14 @@ v = div( NaN, NaN ); ```javascript -var rand = require( '@stdlib/random/base/discrete-uniform' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var div = require( '@stdlib/number/float64/base/div' ); -var x; -var y; -var i; +var x = discreteUniform( 100, -50, 50 ); +var y = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - x = rand( -50, 50 ); - y = rand( -50, 50 ); - console.log( '%d / %d = %d', x, y, div( x, y ) ); -} +logEachMap( '%d / %d = %d', x, y, div ); ``` diff --git a/lib/node_modules/@stdlib/number/float64/base/div/examples/index.js b/lib/node_modules/@stdlib/number/float64/base/div/examples/index.js index 063225596c06..2bab683279c4 100644 --- a/lib/node_modules/@stdlib/number/float64/base/div/examples/index.js +++ b/lib/node_modules/@stdlib/number/float64/base/div/examples/index.js @@ -18,15 +18,11 @@ 'use strict'; -var rand = require( '@stdlib/random/base/discrete-uniform' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var div = require( './../lib' ); -var x; -var y; -var i; +var x = discreteUniform( 100, -50, 50 ); +var y = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - x = rand( -50, 50 ); - y = rand( -50, 50 ); - console.log( '%d / %d = %d', x, y, div( x, y ) ); -} +logEachMap( '%d / %d = %d', x, y, div ); diff --git a/lib/node_modules/@stdlib/number/float64/base/identity/README.md b/lib/node_modules/@stdlib/number/float64/base/identity/README.md index 3875f15ab2f4..b103c91ff19f 100644 --- a/lib/node_modules/@stdlib/number/float64/base/identity/README.md +++ b/lib/node_modules/@stdlib/number/float64/base/identity/README.md @@ -85,17 +85,13 @@ v = identity( NaN ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var identity = require( '@stdlib/number/float64/base/identity' ); -var rand; -var i; +var x = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - rand = round( randu() * 100.0 ) - 50.0; - console.log( 'identity(%d) = %d', rand, identity( rand ) ); -} +logEachMap( 'identity(%d) = %d', x, identity ); ``` diff --git a/lib/node_modules/@stdlib/number/float64/base/identity/examples/index.js b/lib/node_modules/@stdlib/number/float64/base/identity/examples/index.js index 85da24b6c4c9..c611d5dd7898 100644 --- a/lib/node_modules/@stdlib/number/float64/base/identity/examples/index.js +++ b/lib/node_modules/@stdlib/number/float64/base/identity/examples/index.js @@ -18,14 +18,10 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var identity = require( './../lib' ); -var rand; -var i; +var x = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - rand = round( randu() * 100.0 ) - 50.0; - console.log( 'identity(%d) = %d', rand, identity( rand ) ); -} +logEachMap( 'identity(%d) = %d', x, identity ); diff --git a/lib/node_modules/@stdlib/number/float64/base/mul/README.md b/lib/node_modules/@stdlib/number/float64/base/mul/README.md index a44ca7c2a5fc..628b60cac4a6 100644 --- a/lib/node_modules/@stdlib/number/float64/base/mul/README.md +++ b/lib/node_modules/@stdlib/number/float64/base/mul/README.md @@ -82,18 +82,14 @@ v = mul( NaN, NaN ); ```javascript -var rand = require( '@stdlib/random/base/discrete-uniform' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var mul = require( '@stdlib/number/float64/base/mul' ); -var x; -var y; -var i; +var x = discreteUniform( 100, -50, 50 ); +var y = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - x = rand( -50, 50 ); - y = rand( -50, 50 ); - console.log( '%d x %d = %d', x, y, mul( x, y ) ); -} +logEachMap( '%d x %d = %d', x, y, mul ); ``` diff --git a/lib/node_modules/@stdlib/number/float64/base/mul/examples/index.js b/lib/node_modules/@stdlib/number/float64/base/mul/examples/index.js index dbbc2d747878..5f2a6603dd4e 100644 --- a/lib/node_modules/@stdlib/number/float64/base/mul/examples/index.js +++ b/lib/node_modules/@stdlib/number/float64/base/mul/examples/index.js @@ -18,15 +18,11 @@ 'use strict'; -var rand = require( '@stdlib/random/base/discrete-uniform' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var mul = require( './../lib' ); -var x; -var y; -var i; +var x = discreteUniform( 100, -50, 50 ); +var y = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - x = rand( -50, 50 ); - y = rand( -50, 50 ); - console.log( '%d x %d = %d', x, y, mul( x, y ) ); -} +logEachMap( '%d x %d = %d', x, y, mul ); diff --git a/lib/node_modules/@stdlib/number/float64/base/signbit/README.md b/lib/node_modules/@stdlib/number/float64/base/signbit/README.md index 916aae7ec6c9..8be728bd60ea 100644 --- a/lib/node_modules/@stdlib/number/float64/base/signbit/README.md +++ b/lib/node_modules/@stdlib/number/float64/base/signbit/README.md @@ -152,7 +152,7 @@ int main( void ) { int8_t out; int i; for ( i = 0; i < 9; i++ ) { - stdlib_base_float64_signbit( x[ i ], &out ); + out = stdlib_base_float64_signbit( x[ i ] ); printf( "%lf => signbit: %" PRId8 "\n", x[ i ], out ); } } diff --git a/lib/node_modules/@stdlib/number/float64/base/sub/README.md b/lib/node_modules/@stdlib/number/float64/base/sub/README.md index e34ab67134bf..89ea81915454 100644 --- a/lib/node_modules/@stdlib/number/float64/base/sub/README.md +++ b/lib/node_modules/@stdlib/number/float64/base/sub/README.md @@ -82,18 +82,14 @@ v = sub( NaN, NaN ); ```javascript -var rand = require( '@stdlib/random/base/discrete-uniform' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var sub = require( '@stdlib/number/float64/base/sub' ); -var x; -var y; -var i; +var x = discreteUniform( 100, -50, 50 ); +var y = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - x = rand( -50, 50 ); - y = rand( -50, 50 ); - console.log( '%d - %d = %d', x, y, sub( x, y ) ); -} +logEachMap( '%d - %d = %d', x, y, sub ); ``` diff --git a/lib/node_modules/@stdlib/number/float64/base/sub/examples/index.js b/lib/node_modules/@stdlib/number/float64/base/sub/examples/index.js index d88b585883c7..56cc3a6852b3 100644 --- a/lib/node_modules/@stdlib/number/float64/base/sub/examples/index.js +++ b/lib/node_modules/@stdlib/number/float64/base/sub/examples/index.js @@ -18,15 +18,11 @@ 'use strict'; -var rand = require( '@stdlib/random/base/discrete-uniform' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var sub = require( './../lib' ); -var x; -var y; -var i; +var x = discreteUniform( 100, -50, 50 ); +var y = discreteUniform( 100, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - x = rand( -50, 50 ); - y = rand( -50, 50 ); - console.log( '%d - %d = %d', x, y, sub( x, y ) ); -} +logEachMap( '%d - %d = %d', x, y, sub ); diff --git a/lib/node_modules/@stdlib/number/int32/base/mul/benchmark/benchmark.js b/lib/node_modules/@stdlib/number/int32/base/mul/benchmark/benchmark.js index 71dd50ce207e..23d55712f3d3 100644 --- a/lib/node_modules/@stdlib/number/int32/base/mul/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/number/int32/base/mul/benchmark/benchmark.js @@ -21,8 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var minstd = require( '@stdlib/random/base/minstd' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var imul = require( './../lib' ); var polyfill = require( './../lib/polyfill.js' ); @@ -35,59 +35,68 @@ bench( pkg, function benchmark( b ) { var y; var i; + x = discreteUniform( 100, 0, 10, { + 'dtype': 'int32' + }); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = minstd(); - y = imul( x|0, x|0 ); - if ( isnan( y ) ) { - b.fail( 'should not return NaN' ); + y = imul( x[ i%x.length ], 10 ); + if ( y > 100 ) { + b.fail( 'unexpected result' ); } } b.toc(); - if ( isnan( y ) ) { - b.fail( 'should not return NaN' ); + if ( y > 100 ) { + b.fail( 'unexpected result' ); } b.pass( 'benchmark finished' ); b.end(); }); -bench( pkg+'::polyfill', function benchmark( b ) { +bench( format( '%s::polyfill', pkg ), function benchmark( b ) { var x; var y; var i; + x = discreteUniform( 100, 0, 10, { + 'dtype': 'int32' + }); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = minstd(); - y = polyfill( x|0, x|0 ); - if ( isnan( y ) ) { - b.fail( 'should not return NaN' ); + y = polyfill( x[ i%x.length ], 10 ); + if ( y > 100 ) { + b.fail( 'unexpected result' ); } } b.toc(); - if ( isnan( y ) ) { - b.fail( 'should not return NaN' ); + if ( y > 100 ) { + b.fail( 'unexpected result' ); } b.pass( 'benchmark finished' ); b.end(); }); -bench( pkg+'::naive_multiplication', function benchmark( b ) { +bench( format( '%s::inline', pkg ), function benchmark( b ) { var x; var y; var i; + x = discreteUniform( 100, 0, 10, { + 'dtype': 'int32' + }); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = minstd(); - y = ( x|0 ) * ( x|0 ); - if ( isnan( y ) ) { - b.fail( 'should not return NaN' ); + y = ( ( x[ i%x.length ] ) * 5 ) | 0; + if ( y > 100 ) { + b.fail( 'unexpected result' ); } } b.toc(); - if ( isnan( y ) ) { - b.fail( 'should not return NaN' ); + if ( y > 100 ) { + b.fail( 'unexpected result' ); } b.pass( 'benchmark finished' ); b.end(); diff --git a/lib/node_modules/@stdlib/plot/components/svg/graph/lib/defaults.json b/lib/node_modules/@stdlib/plot/components/svg/graph/lib/defaults.json index 983fe3639930..fd6cfa979650 100644 --- a/lib/node_modules/@stdlib/plot/components/svg/graph/lib/defaults.json +++ b/lib/node_modules/@stdlib/plot/components/svg/graph/lib/defaults.json @@ -1,5 +1,5 @@ { - "translateX": 0, - "translateY": 0, - "autoRender": false + "translateX": 0, + "translateY": 0, + "autoRender": false } diff --git a/lib/node_modules/@stdlib/process/umask/scripts/binary_to_symbolic.js b/lib/node_modules/@stdlib/process/umask/scripts/binary_to_symbolic.js index f2d67aad14e8..ab494ff5cbdf 100644 --- a/lib/node_modules/@stdlib/process/umask/scripts/binary_to_symbolic.js +++ b/lib/node_modules/@stdlib/process/umask/scripts/binary_to_symbolic.js @@ -37,7 +37,7 @@ var j; TOTAL = 8 * 8 * 8 * 8; // For each integer value (octal number), determine the symbolic notation equivalent to the value's binary representation... -masks = new Array( TOTAL ); +masks = []; for ( i = 0; i < TOTAL; i++ ) { tmp = ''; @@ -79,7 +79,7 @@ for ( i = 0; i < TOTAL; i++ ) { } } // [ integer, octal, binary_string, symbolic_notation ] - masks[ i ] = [ i, lpad( i.toString( 8 ), 4, '0' ), bstr, tmp ]; + masks.push( [ i, lpad( i.toString( 8 ), 4, '0' ), bstr, tmp ] ); } if ( PRETTY_PRINT ) { diff --git a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float32.assign.js index be59b467f68c..19ad424c41fa 100644 --- a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float32.factory.js index 5e5f859868ba..15724026b6bc 100644 --- a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float32.js index ae07aaae37ed..f518a82cdd1c 100644 --- a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float64.assign.js index e426989fe507..24f465c3a7e8 100644 --- a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float64.factory.js index da9cd5c39671..994bcbb3b212 100644 --- a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float64.js index bd305a42579e..afcd7a9b8d6d 100644 --- a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.generic.assign.js index 1db4418c6880..880d0062e11d 100644 --- a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.generic.factory.js index 422d3f7eee26..e4325465fac9 100644 --- a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.generic.js index d008ca3ea1d1..a46e5229c742 100644 --- a/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/arcsine/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float32.assign.js index b1f29c4766ce..beac60020353 100644 --- a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float32.factory.js index 9b8f13c2a618..ec9606401081 100644 --- a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float32.js index 92f2551c21a5..67d450762cc7 100644 --- a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float64.assign.js index c27be97fe8b9..94b2887119b0 100644 --- a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float64.factory.js index 9afd49e246e3..b8f6cc887ff2 100644 --- a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float64.js index 32a3a3f55f7c..b7ed1b948899 100644 --- a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.generic.assign.js index 7dbdf4bed4d4..cdfb6eb5000e 100644 --- a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.generic.factory.js index a2be86368854..64d46f52ac22 100644 --- a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.generic.js index fa9690754f2f..099aa60c2c23 100644 --- a/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/bernoulli/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float32.assign.js index be59b467f68c..19ad424c41fa 100644 --- a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float32.factory.js index 5e5f859868ba..15724026b6bc 100644 --- a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float32.js index ae07aaae37ed..f518a82cdd1c 100644 --- a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float64.assign.js index e426989fe507..24f465c3a7e8 100644 --- a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float64.factory.js index da9cd5c39671..994bcbb3b212 100644 --- a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float64.js index bd305a42579e..afcd7a9b8d6d 100644 --- a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.generic.assign.js index 1db4418c6880..880d0062e11d 100644 --- a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.generic.factory.js index 422d3f7eee26..e4325465fac9 100644 --- a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.generic.js index d008ca3ea1d1..a46e5229c742 100644 --- a/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/beta/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float32.assign.js index be59b467f68c..19ad424c41fa 100644 --- a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float32.factory.js index 5e5f859868ba..15724026b6bc 100644 --- a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float32.js index ae07aaae37ed..f518a82cdd1c 100644 --- a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float64.assign.js index e426989fe507..24f465c3a7e8 100644 --- a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float64.factory.js index da9cd5c39671..994bcbb3b212 100644 --- a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float64.js index bd305a42579e..afcd7a9b8d6d 100644 --- a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.generic.assign.js index 1db4418c6880..880d0062e11d 100644 --- a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.generic.factory.js index 422d3f7eee26..e4325465fac9 100644 --- a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.generic.js index d008ca3ea1d1..a46e5229c742 100644 --- a/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/betaprime/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float32.assign.js index ba2a34a0d03d..384ee32a0766 100644 --- a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float32.factory.js index 264f3f53b42e..68d361cf9638 100644 --- a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float32.js index 55884be484e7..8dccee763442 100644 --- a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float64.assign.js index a0b15887e5d7..5a46ae1a5f88 100644 --- a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float64.factory.js index 4b20dfe70827..178a8f074901 100644 --- a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float64.js index aa92fdc8b2b1..b3b589c98591 100644 --- a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.generic.assign.js index 9b9235a0b52a..c17f89a65f48 100644 --- a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.generic.factory.js index 4940c499d6d1..e1b4c04daec1 100644 --- a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.generic.js index 96a88585e536..e659aaa1e600 100644 --- a/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/binomial/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float32.assign.js index a6f03361a308..fef197d3b754 100644 --- a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float32.factory.js index 7648ac245f3f..35f89d901a46 100644 --- a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float32.js index b8f47aee7a37..b596f4d887d0 100644 --- a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float64.assign.js index 11ada9ca7a4e..9ebbca8a3911 100644 --- a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float64.factory.js index 95ba6fd7a24d..4e2260012d52 100644 --- a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float64.js index 7f4781237829..79234afafb54 100644 --- a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.generic.assign.js index 250dbd773f39..459bfaa2868f 100644 --- a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.generic.factory.js index cddfc35b8f96..4bb13f96adb2 100644 --- a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.generic.js index 3471ff3ee389..0a5b0e300bc9 100644 --- a/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/cauchy/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float32.assign.js index 0834f9773116..8c7a465ab58b 100644 --- a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float32.factory.js index c8875c96280d..0d36bfd8a2de 100644 --- a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float32.js index f25baa03fc62..039a0ad439ca 100644 --- a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float64.assign.js index 326d5af6c588..b80c20b20fff 100644 --- a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float64.factory.js index a5d9df903706..cbd26ec6182b 100644 --- a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float64.js index d39b56dbe085..c214f6459f36 100644 --- a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.generic.assign.js index b4d0dcdf44db..4f2258773651 100644 --- a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.generic.factory.js index 8ce0cb9eb8cd..4e3c24a73b14 100644 --- a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.generic.js index ef4e9efb3175..afd9ba37ec6c 100644 --- a/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/chi/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float32.assign.js index 0834f9773116..8c7a465ab58b 100644 --- a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float32.factory.js index c8875c96280d..0d36bfd8a2de 100644 --- a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float32.js index f25baa03fc62..039a0ad439ca 100644 --- a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float64.assign.js index 326d5af6c588..b80c20b20fff 100644 --- a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float64.factory.js index a5d9df903706..cbd26ec6182b 100644 --- a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float64.js index d39b56dbe085..c214f6459f36 100644 --- a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.generic.assign.js index b4d0dcdf44db..4f2258773651 100644 --- a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.generic.factory.js index 8ce0cb9eb8cd..4e3c24a73b14 100644 --- a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.generic.js index ef4e9efb3175..afd9ba37ec6c 100644 --- a/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/chisquare/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float32.assign.js index be59b467f68c..19ad424c41fa 100644 --- a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float32.factory.js index 5e5f859868ba..15724026b6bc 100644 --- a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float32.js index ae07aaae37ed..f518a82cdd1c 100644 --- a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float64.assign.js index e426989fe507..24f465c3a7e8 100644 --- a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float64.factory.js index da9cd5c39671..994bcbb3b212 100644 --- a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float64.js index bd305a42579e..afcd7a9b8d6d 100644 --- a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.generic.assign.js index 1db4418c6880..880d0062e11d 100644 --- a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.generic.factory.js index 422d3f7eee26..e4325465fac9 100644 --- a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.generic.js index d008ca3ea1d1..a46e5229c742 100644 --- a/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/cosine/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float32.assign.js index 5b6a9b8d7ed0..e04a58091805 100644 --- a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float32.factory.js index f0874a4549e6..38554a96aa35 100644 --- a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float32.js index da08a9ddd5e1..14c2fc94f590 100644 --- a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float64.assign.js index 4f201091b606..07309ff2144c 100644 --- a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float64.factory.js index 54f72674283f..9810f13292bb 100644 --- a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float64.js index 4cc4f06e5ee0..695374b869df 100644 --- a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.generic.assign.js index cd701c398582..32d300659f71 100644 --- a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.generic.factory.js index c74789945630..64b3d7133eef 100644 --- a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.generic.js index d015d25afdcb..c0e78804070d 100644 --- a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.int32.assign.js b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.int32.assign.js index 8a114e72ac69..4553996185cc 100644 --- a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.int32.assign.js +++ b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.int32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=int32,len='+len, f ); + bench( format( '%s:assign:dtype=int32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.int32.factory.js b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.int32.factory.js index 3d94fa21db48..25bb7e8587e1 100644 --- a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.int32.factory.js +++ b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.int32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=int32,len='+len, f ); + bench( format( '%s::factory:dtype=int32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.int32.js b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.int32.js index f3c0bb9d5297..d23f31dd6d34 100644 --- a/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.int32.js +++ b/lib/node_modules/@stdlib/random/array/discrete-uniform/benchmark/benchmark.int32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=int32,len='+len, f ); + bench( format( '%s:dtype=int32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float32.assign.js index 606757c3c389..478918cd3606 100644 --- a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float32.factory.js index 04e8b886c81d..b9a18f4fabda 100644 --- a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float32.js index dc96b3b93dc5..fc532bf96f00 100644 --- a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float64.assign.js index 3fa9e6352b76..f202ea8f6d2a 100644 --- a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float64.factory.js index d799b038d426..35d19b95fd3f 100644 --- a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float64.js index 79254f403667..9e941f1cd6f5 100644 --- a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.generic.assign.js index 177bce769109..619b7f640b75 100644 --- a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.generic.factory.js index 03ac4abc7f3e..a085c39a87ef 100644 --- a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.generic.js index 6bec6bd8a8b6..2c2a083136e8 100644 --- a/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/erlang/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float32.assign.js index 0834f9773116..8c7a465ab58b 100644 --- a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float32.factory.js index c8875c96280d..0d36bfd8a2de 100644 --- a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float32.js index f25baa03fc62..039a0ad439ca 100644 --- a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float64.assign.js index 326d5af6c588..b80c20b20fff 100644 --- a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float64.factory.js index a5d9df903706..cbd26ec6182b 100644 --- a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float64.js index d39b56dbe085..c214f6459f36 100644 --- a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.generic.assign.js index b4d0dcdf44db..4f2258773651 100644 --- a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.generic.factory.js index 8ce0cb9eb8cd..4e3c24a73b14 100644 --- a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.generic.js index ef4e9efb3175..afd9ba37ec6c 100644 --- a/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/exponential/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float32.assign.js index a6f03361a308..fef197d3b754 100644 --- a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float32.factory.js index 7648ac245f3f..35f89d901a46 100644 --- a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float32.js index b8f47aee7a37..b596f4d887d0 100644 --- a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float64.assign.js index 11ada9ca7a4e..9ebbca8a3911 100644 --- a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float64.factory.js index 95ba6fd7a24d..4e2260012d52 100644 --- a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float64.js index 7f4781237829..79234afafb54 100644 --- a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.generic.assign.js index 250dbd773f39..459bfaa2868f 100644 --- a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.generic.factory.js index cddfc35b8f96..4bb13f96adb2 100644 --- a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.generic.js index 3471ff3ee389..0a5b0e300bc9 100644 --- a/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/f/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float32.assign.js index 7bd9f730a1ce..3001b82a97b8 100644 --- a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float32.factory.js index d27d84118a11..b90d7c91c166 100644 --- a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float32.js index 7a327c4cc1db..dfa3d2fc80f9 100644 --- a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float64.assign.js index d4bed407a848..01d3300bd0cf 100644 --- a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float64.factory.js index 772765afdb6f..8af2e8a900c2 100644 --- a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float64.js index af2ae09aaabf..99ae76bb47e6 100644 --- a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.generic.assign.js index ce55918ab082..be2388ede303 100644 --- a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.generic.factory.js index cc3974d32f47..6efa00a98ade 100644 --- a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.generic.js index d0234e9eefde..42f1371af49c 100644 --- a/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/frechet/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float32.assign.js index be59b467f68c..19ad424c41fa 100644 --- a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float32.factory.js index 5e5f859868ba..15724026b6bc 100644 --- a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float32.js index ae07aaae37ed..f518a82cdd1c 100644 --- a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float64.assign.js index e426989fe507..24f465c3a7e8 100644 --- a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float64.factory.js index da9cd5c39671..994bcbb3b212 100644 --- a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float64.js index bd305a42579e..afcd7a9b8d6d 100644 --- a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.generic.assign.js index 1db4418c6880..880d0062e11d 100644 --- a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.generic.factory.js index 422d3f7eee26..e4325465fac9 100644 --- a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.generic.js index d008ca3ea1d1..a46e5229c742 100644 --- a/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/gamma/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float32.assign.js index 626402b21060..f66c8b2e608a 100644 --- a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float32.factory.js index 090a4885afc7..174649f6c3a8 100644 --- a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float32.js index 986f7de8d84f..a6a3f41bd573 100644 --- a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float64.assign.js index a9f944a7fed6..f2cf1c9c66cb 100644 --- a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float64.factory.js index 963a5b77583d..9754a3fb1ad7 100644 --- a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float64.js index edf76d9b3cfa..693900ce0521 100644 --- a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.generic.assign.js index 07494ac2cb9d..ed85b7beca58 100644 --- a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.generic.factory.js index 92379f54d8f5..1cab37dd5572 100644 --- a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.generic.js index 3c3395fc6fc7..a0fc1d0da06a 100644 --- a/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/geometric/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float32.assign.js index a6f03361a308..fef197d3b754 100644 --- a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float32.factory.js index 7648ac245f3f..35f89d901a46 100644 --- a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float32.js index b8f47aee7a37..b596f4d887d0 100644 --- a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float64.assign.js index 11ada9ca7a4e..9ebbca8a3911 100644 --- a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float64.factory.js index 95ba6fd7a24d..4e2260012d52 100644 --- a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float64.js index 7f4781237829..79234afafb54 100644 --- a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.generic.assign.js index 250dbd773f39..459bfaa2868f 100644 --- a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.generic.factory.js index cddfc35b8f96..4bb13f96adb2 100644 --- a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.generic.js index 3471ff3ee389..0a5b0e300bc9 100644 --- a/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/gumbel/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float32.assign.js index fae7c1a3005e..378f0cb22a11 100644 --- a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float32.factory.js index e410bb93e0f4..199c7baab797 100644 --- a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float32.js index 7440e1123324..d2da2a4e521a 100644 --- a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float64.assign.js index 0149e1064b03..5dc9ba94c861 100644 --- a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float64.factory.js index d7ce9211d271..da5df329d7ac 100644 --- a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float64.js index 958d7d4b814b..d9b2553e034f 100644 --- a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.generic.assign.js index cc9fde9caa7d..d0d71c23a9fb 100644 --- a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.generic.factory.js index 7effeaf48069..bbb041905455 100644 --- a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.generic.js index 283d5ba231fc..e931d7b371d0 100644 --- a/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/hypergeometric/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float32.assign.js index be59b467f68c..19ad424c41fa 100644 --- a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float32.factory.js index 5e5f859868ba..15724026b6bc 100644 --- a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float32.js index ae07aaae37ed..f518a82cdd1c 100644 --- a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float64.assign.js index e426989fe507..24f465c3a7e8 100644 --- a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float64.factory.js index da9cd5c39671..994bcbb3b212 100644 --- a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float64.js index bd305a42579e..afcd7a9b8d6d 100644 --- a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.generic.assign.js index 1db4418c6880..880d0062e11d 100644 --- a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.generic.factory.js index 422d3f7eee26..e4325465fac9 100644 --- a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.generic.js index d008ca3ea1d1..a46e5229c742 100644 --- a/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/invgamma/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float32.assign.js index a6f03361a308..fef197d3b754 100644 --- a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float32.factory.js index 7648ac245f3f..35f89d901a46 100644 --- a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float32.js index b8f47aee7a37..b596f4d887d0 100644 --- a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float64.assign.js index 11ada9ca7a4e..9ebbca8a3911 100644 --- a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float64.factory.js index 95ba6fd7a24d..4e2260012d52 100644 --- a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float64.js index 7f4781237829..79234afafb54 100644 --- a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.generic.assign.js index 250dbd773f39..459bfaa2868f 100644 --- a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.generic.factory.js index cddfc35b8f96..4bb13f96adb2 100644 --- a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.generic.js index 3471ff3ee389..0a5b0e300bc9 100644 --- a/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/kumaraswamy/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float32.assign.js index a6f03361a308..fef197d3b754 100644 --- a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float32.factory.js index 7648ac245f3f..35f89d901a46 100644 --- a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float32.js index b8f47aee7a37..b596f4d887d0 100644 --- a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float64.assign.js index 11ada9ca7a4e..9ebbca8a3911 100644 --- a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float64.factory.js index 95ba6fd7a24d..4e2260012d52 100644 --- a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float64.js index 7f4781237829..79234afafb54 100644 --- a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.generic.assign.js index 250dbd773f39..459bfaa2868f 100644 --- a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.generic.factory.js index cddfc35b8f96..4bb13f96adb2 100644 --- a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.generic.js index 3471ff3ee389..0a5b0e300bc9 100644 --- a/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/laplace/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float32.assign.js index a6f03361a308..fef197d3b754 100644 --- a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float32.factory.js index 7648ac245f3f..35f89d901a46 100644 --- a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float32.js index b8f47aee7a37..b596f4d887d0 100644 --- a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float64.assign.js index 11ada9ca7a4e..9ebbca8a3911 100644 --- a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float64.factory.js index 95ba6fd7a24d..4e2260012d52 100644 --- a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float64.js index 7f4781237829..79234afafb54 100644 --- a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.generic.assign.js index 250dbd773f39..459bfaa2868f 100644 --- a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.generic.factory.js index cddfc35b8f96..4bb13f96adb2 100644 --- a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.generic.js index 3471ff3ee389..0a5b0e300bc9 100644 --- a/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/levy/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float32.assign.js index a6f03361a308..fef197d3b754 100644 --- a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float32.factory.js index 7648ac245f3f..35f89d901a46 100644 --- a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float32.js index b8f47aee7a37..b596f4d887d0 100644 --- a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float64.assign.js index 11ada9ca7a4e..9ebbca8a3911 100644 --- a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float64.factory.js index 95ba6fd7a24d..4e2260012d52 100644 --- a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float64.js index 7f4781237829..79234afafb54 100644 --- a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.generic.assign.js index 250dbd773f39..459bfaa2868f 100644 --- a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.generic.factory.js index cddfc35b8f96..4bb13f96adb2 100644 --- a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.generic.js index 3471ff3ee389..0a5b0e300bc9 100644 --- a/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/logistic/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float32.assign.js index be59b467f68c..19ad424c41fa 100644 --- a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float32.factory.js index 5e5f859868ba..15724026b6bc 100644 --- a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float32.js index ae07aaae37ed..f518a82cdd1c 100644 --- a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float64.assign.js index e426989fe507..24f465c3a7e8 100644 --- a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float64.factory.js index da9cd5c39671..994bcbb3b212 100644 --- a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float64.js index bd305a42579e..afcd7a9b8d6d 100644 --- a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.generic.assign.js index 1db4418c6880..880d0062e11d 100644 --- a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.generic.factory.js index 422d3f7eee26..e4325465fac9 100644 --- a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.generic.js index d008ca3ea1d1..a46e5229c742 100644 --- a/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/lognormal/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.float32.factory.js index a539fc8ecd20..44dbc5fdfa96 100644 --- a/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.float32.js index 6941fb6db721..bae50b54ad55 100644 --- a/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.float64.factory.js index 6d9bc3717b53..004efbd722e0 100644 --- a/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.float64.js index 98419669d95b..6f6fc8dbb66b 100644 --- a/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.generic.factory.js index 4c7da38fc4f4..7ae54a2ef470 100644 --- a/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.generic.js index f4a85dd6fb49..b8646a42f473 100644 --- a/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/minstd-shuffle/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.float32.factory.js index a539fc8ecd20..44dbc5fdfa96 100644 --- a/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.float32.js index 6941fb6db721..bae50b54ad55 100644 --- a/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.float64.factory.js index 6d9bc3717b53..004efbd722e0 100644 --- a/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.float64.js index 98419669d95b..6f6fc8dbb66b 100644 --- a/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.generic.factory.js index 4c7da38fc4f4..7ae54a2ef470 100644 --- a/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.generic.js index f4a85dd6fb49..b8646a42f473 100644 --- a/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/minstd/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.float32.factory.js index dd49a974f424..f85b57f23a6e 100644 --- a/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mt19937 = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.float32.js index 2852026d60d0..e58e7a5ae35b 100644 --- a/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mt19937 = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.float64.factory.js index 9d33e2afa0ab..1643b9c4b241 100644 --- a/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mt19937 = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.float64.js index 97933011803d..0175857bdee5 100644 --- a/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mt19937 = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.generic.factory.js index 0f1bed311492..0d12dd34b8c6 100644 --- a/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mt19937 = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.generic.js index 49615833cf92..90e1d83d5d57 100644 --- a/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/mt19937/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mt19937 = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float32.assign.js index 39124b8dc811..97ad85f9d30c 100644 --- a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float32.factory.js index 16e004721172..1e6137b47f7b 100644 --- a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float32.js index 96bc0711ec21..c7913776dc7f 100644 --- a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float64.assign.js index 5e3e7f4e5b8b..a02671d4dd7a 100644 --- a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float64.factory.js index bef402532632..cf411f560953 100644 --- a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float64.js index 51e7ca4ad73c..0461c5c423c9 100644 --- a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.generic.assign.js index d10ae409d0fa..55e2b423dd51 100644 --- a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.generic.factory.js index ffcac23773de..baec0f50d19c 100644 --- a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.generic.js index 8567864472e4..38a3ae3aa3dd 100644 --- a/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/negative-binomial/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float32.assign.js index be59b467f68c..19ad424c41fa 100644 --- a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float32.factory.js index 5e5f859868ba..15724026b6bc 100644 --- a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float32.js index ae07aaae37ed..f518a82cdd1c 100644 --- a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float64.assign.js index e426989fe507..24f465c3a7e8 100644 --- a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float64.factory.js index da9cd5c39671..994bcbb3b212 100644 --- a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float64.js index bd305a42579e..afcd7a9b8d6d 100644 --- a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.generic.assign.js index 1db4418c6880..880d0062e11d 100644 --- a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.generic.factory.js index 422d3f7eee26..e4325465fac9 100644 --- a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.generic.js index d008ca3ea1d1..a46e5229c742 100644 --- a/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/normal/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float32.assign.js index a6f03361a308..fef197d3b754 100644 --- a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float32.factory.js index 7648ac245f3f..35f89d901a46 100644 --- a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float32.js index b8f47aee7a37..b596f4d887d0 100644 --- a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float64.assign.js index 11ada9ca7a4e..9ebbca8a3911 100644 --- a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float64.factory.js index 95ba6fd7a24d..4e2260012d52 100644 --- a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float64.js index 7f4781237829..79234afafb54 100644 --- a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.generic.assign.js index 250dbd773f39..459bfaa2868f 100644 --- a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.generic.factory.js index cddfc35b8f96..4bb13f96adb2 100644 --- a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.generic.js index 3471ff3ee389..0a5b0e300bc9 100644 --- a/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/pareto-type1/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float32.assign.js index 0834f9773116..8c7a465ab58b 100644 --- a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float32.factory.js index c8875c96280d..0d36bfd8a2de 100644 --- a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float32.js index f25baa03fc62..039a0ad439ca 100644 --- a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float64.assign.js index 326d5af6c588..b80c20b20fff 100644 --- a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float64.factory.js index a5d9df903706..cbd26ec6182b 100644 --- a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float64.js index d39b56dbe085..c214f6459f36 100644 --- a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.generic.assign.js index b4d0dcdf44db..4f2258773651 100644 --- a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.generic.factory.js index 8ce0cb9eb8cd..4e3c24a73b14 100644 --- a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.generic.js index ef4e9efb3175..afd9ba37ec6c 100644 --- a/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/poisson/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.float32.factory.js index a1b413ef5c84..eb9ece69807b 100644 --- a/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randu = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.float32.js index 8d24981e9968..f9d1a5173a93 100644 --- a/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randu = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.float64.factory.js index b2d485d96ae7..42c1cdeaaa84 100644 --- a/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randu = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.float64.js index 40bd03df7d4b..49792dc77889 100644 --- a/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randu = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.generic.factory.js index 01216b0b252e..c4d6193fbc99 100644 --- a/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randu = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.generic.js index 776468e463a0..8b54d994bfde 100644 --- a/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/randu/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randu = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float32.assign.js index 0834f9773116..8c7a465ab58b 100644 --- a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float32.factory.js index c8875c96280d..0d36bfd8a2de 100644 --- a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float32.js index f25baa03fc62..039a0ad439ca 100644 --- a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float64.assign.js index 326d5af6c588..b80c20b20fff 100644 --- a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float64.factory.js index a5d9df903706..cbd26ec6182b 100644 --- a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float64.js index d39b56dbe085..c214f6459f36 100644 --- a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.generic.assign.js index b4d0dcdf44db..4f2258773651 100644 --- a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.generic.factory.js index 8ce0cb9eb8cd..4e3c24a73b14 100644 --- a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.generic.js index ef4e9efb3175..afd9ba37ec6c 100644 --- a/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/rayleigh/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float32.assign.js index 0834f9773116..8c7a465ab58b 100644 --- a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float32.factory.js index c8875c96280d..0d36bfd8a2de 100644 --- a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float32.js index f25baa03fc62..039a0ad439ca 100644 --- a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float64.assign.js index 326d5af6c588..b80c20b20fff 100644 --- a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float64.factory.js index a5d9df903706..cbd26ec6182b 100644 --- a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float64.js index d39b56dbe085..c214f6459f36 100644 --- a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.generic.assign.js index b4d0dcdf44db..4f2258773651 100644 --- a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.generic.factory.js index 8ce0cb9eb8cd..4e3c24a73b14 100644 --- a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.generic.js index ef4e9efb3175..afd9ba37ec6c 100644 --- a/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/t/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/tools/binary-factory/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/random/array/tools/binary-factory/benchmark/benchmark.assign.js index d1c8d32d3deb..dc161e5ae3c8 100644 --- a/lib/node_modules/@stdlib/random/array/tools/binary-factory/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/random/array/tools/binary-factory/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var arcsine = require( '@stdlib/random/base/arcsine' ); var dtypes = require( '@stdlib/array/dtypes' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var binaryFactory = require( './../lib' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::generate:assign:len='+len, f ); + bench( format( '%s::generate:assign:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/tools/binary-factory/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/array/tools/binary-factory/benchmark/benchmark.js index dafc0dad5445..d2e8faf4cb69 100644 --- a/lib/node_modules/@stdlib/random/array/tools/binary-factory/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/array/tools/binary-factory/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var arcsine = require( '@stdlib/random/base/arcsine' ); var normal = require( '@stdlib/random/base/normal' ); var isFunction = require( '@stdlib/assert/is-function' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var binaryFactory = require( './../lib' ); @@ -60,7 +61,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var dtypes; var rand; var f; @@ -88,7 +89,7 @@ bench( pkg+'::factory', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory,partial_application', function benchmark( b ) { +bench( format( '%s::factory,partial_application', pkg ), function benchmark( b ) { var values; var dtypes; var rand; diff --git a/lib/node_modules/@stdlib/random/array/tools/binary-factory/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/random/array/tools/binary-factory/benchmark/benchmark.length.js index a0211c897e73..3592117539e4 100644 --- a/lib/node_modules/@stdlib/random/array/tools/binary-factory/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/random/array/tools/binary-factory/benchmark/benchmark.length.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var arcsine = require( '@stdlib/random/base/arcsine' ); var dtypes = require( '@stdlib/array/dtypes' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var binaryFactory = require( './../lib' ); @@ -96,7 +97,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::generate:len='+len, f ); + bench( format( '%s::generate:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/tools/binary/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/random/array/tools/binary/benchmark/benchmark.assign.js index 7623987a3052..f20c64834522 100644 --- a/lib/node_modules/@stdlib/random/array/tools/binary/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/random/array/tools/binary/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var arcsine = require( '@stdlib/random/base/arcsine' ); var dtypes = require( '@stdlib/array/dtypes' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Random = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:len='+len, f ); + bench( format( '%s:assign:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/tools/binary/benchmark/benchmark.generate.js b/lib/node_modules/@stdlib/random/array/tools/binary/benchmark/benchmark.generate.js index a600ed22bbd2..d29ad2394718 100644 --- a/lib/node_modules/@stdlib/random/array/tools/binary/benchmark/benchmark.generate.js +++ b/lib/node_modules/@stdlib/random/array/tools/binary/benchmark/benchmark.generate.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var arcsine = require( '@stdlib/random/base/arcsine' ); var dtypes = require( '@stdlib/array/dtypes' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Random = require( './../lib' ); @@ -94,7 +95,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':generate:len='+len, f ); + bench( format( '%s:generate:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/tools/binary/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/array/tools/binary/benchmark/benchmark.js index 843771244974..841e7bb4dbdb 100644 --- a/lib/node_modules/@stdlib/random/array/tools/binary/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/array/tools/binary/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var arcsine = require( '@stdlib/random/base/arcsine' ); var normal = require( '@stdlib/random/base/normal' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Random = require( './../lib' ); // MAIN // -bench( pkg+'::new', function benchmark( b ) { +bench( format( '%s::new', pkg ), function benchmark( b ) { var values; var dtypes; var v; @@ -59,7 +60,7 @@ bench( pkg+'::new', function benchmark( b ) { b.end(); }); -bench( pkg+'::no_new', function benchmark( b ) { +bench( format( '%s::no_new', pkg ), function benchmark( b ) { var values; var dtypes; var random; diff --git a/lib/node_modules/@stdlib/random/array/tools/nullary/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/random/array/tools/nullary/benchmark/benchmark.assign.js index 54709ecfdcc0..0fd644f988f3 100644 --- a/lib/node_modules/@stdlib/random/array/tools/nullary/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/random/array/tools/nullary/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var exponential = require( '@stdlib/random/base/exponential' ); var dtypes = require( '@stdlib/array/dtypes' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Random = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:len='+len, f ); + bench( format( '%s:assign:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/tools/nullary/benchmark/benchmark.generate.js b/lib/node_modules/@stdlib/random/array/tools/nullary/benchmark/benchmark.generate.js index 65d1307fbe4d..fed3efe58ea8 100644 --- a/lib/node_modules/@stdlib/random/array/tools/nullary/benchmark/benchmark.generate.js +++ b/lib/node_modules/@stdlib/random/array/tools/nullary/benchmark/benchmark.generate.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var exponential = require( '@stdlib/random/base/exponential' ); var dtypes = require( '@stdlib/array/dtypes' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Random = require( './../lib' ); @@ -94,7 +95,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':generate:len='+len, f ); + bench( format( '%s:generate:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/tools/nullary/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/array/tools/nullary/benchmark/benchmark.js index 4923adddf297..5f7331ee591a 100644 --- a/lib/node_modules/@stdlib/random/array/tools/nullary/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/array/tools/nullary/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var exponential = require( '@stdlib/random/base/exponential' ); var geometric = require( '@stdlib/random/base/geometric' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Random = require( './../lib' ); // MAIN // -bench( pkg+'::new', function benchmark( b ) { +bench( format( '%s::new', pkg ), function benchmark( b ) { var values; var dtypes; var v; @@ -59,7 +60,7 @@ bench( pkg+'::new', function benchmark( b ) { b.end(); }); -bench( pkg+'::no_new', function benchmark( b ) { +bench( format( '%s::no_new', pkg ), function benchmark( b ) { var values; var dtypes; var random; diff --git a/lib/node_modules/@stdlib/random/array/tools/ternary-factory/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/random/array/tools/ternary-factory/benchmark/benchmark.assign.js index 2aa0327ae0b7..9b745cf99725 100644 --- a/lib/node_modules/@stdlib/random/array/tools/ternary-factory/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/random/array/tools/ternary-factory/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var triangular = require( '@stdlib/random/base/triangular' ); var dtypes = require( '@stdlib/array/dtypes' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ternaryFactory = require( './../lib' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::generate:assign:len='+len, f ); + bench( format( '%s::generate:assign:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/tools/ternary-factory/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/array/tools/ternary-factory/benchmark/benchmark.js index cb33c0112b75..a4445f2cb792 100644 --- a/lib/node_modules/@stdlib/random/array/tools/ternary-factory/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/array/tools/ternary-factory/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var triangular = require( '@stdlib/random/base/triangular' ); var hypergeometric = require( '@stdlib/random/base/hypergeometric' ); var isFunction = require( '@stdlib/assert/is-function' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ternaryFactory = require( './../lib' ); @@ -60,7 +61,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var dtypes; var rand; var f; @@ -88,7 +89,7 @@ bench( pkg+'::factory', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory,partial_application', function benchmark( b ) { +bench( format( '%s::factory,partial_application', pkg ), function benchmark( b ) { var values; var dtypes; var rand; diff --git a/lib/node_modules/@stdlib/random/array/tools/ternary-factory/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/random/array/tools/ternary-factory/benchmark/benchmark.length.js index 508747d22a59..b0f66e5c24a1 100644 --- a/lib/node_modules/@stdlib/random/array/tools/ternary-factory/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/random/array/tools/ternary-factory/benchmark/benchmark.length.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var triangular = require( '@stdlib/random/base/triangular' ); var dtypes = require( '@stdlib/array/dtypes' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ternaryFactory = require( './../lib' ); @@ -96,7 +97,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::generate:len='+len, f ); + bench( format( '%s::generate:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/tools/ternary/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/random/array/tools/ternary/benchmark/benchmark.assign.js index 0b696335507b..c469dcb204a4 100644 --- a/lib/node_modules/@stdlib/random/array/tools/ternary/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/random/array/tools/ternary/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var triangular = require( '@stdlib/random/base/triangular' ); var dtypes = require( '@stdlib/array/dtypes' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Random = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:len='+len, f ); + bench( format( '%s:assign:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/tools/ternary/benchmark/benchmark.generate.js b/lib/node_modules/@stdlib/random/array/tools/ternary/benchmark/benchmark.generate.js index 935add781b19..42be644d8e23 100644 --- a/lib/node_modules/@stdlib/random/array/tools/ternary/benchmark/benchmark.generate.js +++ b/lib/node_modules/@stdlib/random/array/tools/ternary/benchmark/benchmark.generate.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var triangular = require( '@stdlib/random/base/triangular' ); var dtypes = require( '@stdlib/array/dtypes' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Random = require( './../lib' ); @@ -94,7 +95,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':generate:len='+len, f ); + bench( format( '%s:generate:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/tools/ternary/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/array/tools/ternary/benchmark/benchmark.js index 4909dba34b7a..731b2b5dc322 100644 --- a/lib/node_modules/@stdlib/random/array/tools/ternary/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/array/tools/ternary/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var triangular = require( '@stdlib/random/base/triangular' ); var hypergeometric = require( '@stdlib/random/base/hypergeometric' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Random = require( './../lib' ); // MAIN // -bench( pkg+'::new', function benchmark( b ) { +bench( format( '%s::new', pkg ), function benchmark( b ) { var values; var dtypes; var v; @@ -59,7 +60,7 @@ bench( pkg+'::new', function benchmark( b ) { b.end(); }); -bench( pkg+'::no_new', function benchmark( b ) { +bench( format( '%s::no_new', pkg ), function benchmark( b ) { var values; var dtypes; var random; diff --git a/lib/node_modules/@stdlib/random/array/tools/unary-factory/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/random/array/tools/unary-factory/benchmark/benchmark.assign.js index da3a0934569e..7cf97f195a75 100644 --- a/lib/node_modules/@stdlib/random/array/tools/unary-factory/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/random/array/tools/unary-factory/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var exponential = require( '@stdlib/random/base/exponential' ); var dtypes = require( '@stdlib/array/dtypes' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var unaryFactory = require( './../lib' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::generate:assign:len='+len, f ); + bench( format( '%s::generate:assign:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/tools/unary-factory/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/array/tools/unary-factory/benchmark/benchmark.js index d34860d95693..9948da77a02c 100644 --- a/lib/node_modules/@stdlib/random/array/tools/unary-factory/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/array/tools/unary-factory/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var exponential = require( '@stdlib/random/base/exponential' ); var geometric = require( '@stdlib/random/base/geometric' ); var isFunction = require( '@stdlib/assert/is-function' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var unaryFactory = require( './../lib' ); @@ -60,7 +61,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var dtypes; var rand; var f; @@ -88,7 +89,7 @@ bench( pkg+'::factory', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory,partial_application', function benchmark( b ) { +bench( format( '%s::factory,partial_application', pkg ), function benchmark( b ) { var values; var dtypes; var rand; diff --git a/lib/node_modules/@stdlib/random/array/tools/unary-factory/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/random/array/tools/unary-factory/benchmark/benchmark.length.js index ba438b247ac1..561355dfef7b 100644 --- a/lib/node_modules/@stdlib/random/array/tools/unary-factory/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/random/array/tools/unary-factory/benchmark/benchmark.length.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var exponential = require( '@stdlib/random/base/exponential' ); var dtypes = require( '@stdlib/array/dtypes' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var unaryFactory = require( './../lib' ); @@ -96,7 +97,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::generate:len='+len, f ); + bench( format( '%s::generate:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/tools/unary/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/random/array/tools/unary/benchmark/benchmark.assign.js index bc0994b67b53..86b933b342fb 100644 --- a/lib/node_modules/@stdlib/random/array/tools/unary/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/random/array/tools/unary/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var exponential = require( '@stdlib/random/base/exponential' ); var dtypes = require( '@stdlib/array/dtypes' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Random = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:len='+len, f ); + bench( format( '%s:assign:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/tools/unary/benchmark/benchmark.generate.js b/lib/node_modules/@stdlib/random/array/tools/unary/benchmark/benchmark.generate.js index 2912f21dbd5c..8290c77974d4 100644 --- a/lib/node_modules/@stdlib/random/array/tools/unary/benchmark/benchmark.generate.js +++ b/lib/node_modules/@stdlib/random/array/tools/unary/benchmark/benchmark.generate.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var exponential = require( '@stdlib/random/base/exponential' ); var dtypes = require( '@stdlib/array/dtypes' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Random = require( './../lib' ); @@ -94,7 +95,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':generate:len='+len, f ); + bench( format( '%s:generate:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/tools/unary/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/array/tools/unary/benchmark/benchmark.js index f1933fc9ef65..ab150555b76c 100644 --- a/lib/node_modules/@stdlib/random/array/tools/unary/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/array/tools/unary/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var exponential = require( '@stdlib/random/base/exponential' ); var geometric = require( '@stdlib/random/base/geometric' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Random = require( './../lib' ); // MAIN // -bench( pkg+'::new', function benchmark( b ) { +bench( format( '%s::new', pkg ), function benchmark( b ) { var values; var dtypes; var v; @@ -59,7 +60,7 @@ bench( pkg+'::new', function benchmark( b ) { b.end(); }); -bench( pkg+'::no_new', function benchmark( b ) { +bench( format( '%s::no_new', pkg ), function benchmark( b ) { var values; var dtypes; var random; diff --git a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float32.assign.js index 7bd9f730a1ce..3001b82a97b8 100644 --- a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float32.factory.js index d27d84118a11..b90d7c91c166 100644 --- a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float32.js index 7a327c4cc1db..dfa3d2fc80f9 100644 --- a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float64.assign.js index d4bed407a848..01d3300bd0cf 100644 --- a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float64.factory.js index 772765afdb6f..8af2e8a900c2 100644 --- a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float64.js index af2ae09aaabf..99ae76bb47e6 100644 --- a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.generic.assign.js index ce55918ab082..be2388ede303 100644 --- a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.generic.factory.js index cc3974d32f47..6efa00a98ade 100644 --- a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.generic.js index d0234e9eefde..42f1371af49c 100644 --- a/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/triangular/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float32.assign.js index be59b467f68c..19ad424c41fa 100644 --- a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float32.factory.js index 5e5f859868ba..15724026b6bc 100644 --- a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float32.js index ae07aaae37ed..f518a82cdd1c 100644 --- a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float64.assign.js index e426989fe507..24f465c3a7e8 100644 --- a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float64.factory.js index da9cd5c39671..994bcbb3b212 100644 --- a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float64.js index bd305a42579e..afcd7a9b8d6d 100644 --- a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.generic.assign.js index 1db4418c6880..880d0062e11d 100644 --- a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.generic.factory.js index 422d3f7eee26..e4325465fac9 100644 --- a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.generic.js index d008ca3ea1d1..a46e5229c742 100644 --- a/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/uniform/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float32.assign.js b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float32.assign.js index a6f03361a308..fef197d3b754 100644 --- a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float32.assign.js +++ b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float32.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float32,len='+len, f ); + bench( format( '%s:assign:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float32.factory.js b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float32.factory.js index 7648ac245f3f..35f89d901a46 100644 --- a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float32.factory.js +++ b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float32.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float32,len='+len, f ); + bench( format( '%s::factory:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float32.js index b8f47aee7a37..b596f4d887d0 100644 --- a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float32.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float64.assign.js b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float64.assign.js index 11ada9ca7a4e..9ebbca8a3911 100644 --- a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float64.assign.js +++ b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float64.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=float64,len='+len, f ); + bench( format( '%s:assign:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float64.factory.js b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float64.factory.js index 95ba6fd7a24d..4e2260012d52 100644 --- a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float64.factory.js +++ b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float64.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=float64,len='+len, f ); + bench( format( '%s::factory:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float64.js index 7f4781237829..79234afafb54 100644 --- a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.float64.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.generic.assign.js b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.generic.assign.js index 250dbd773f39..459bfaa2868f 100644 --- a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.generic.assign.js +++ b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.generic.assign.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -90,7 +91,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype=generic,len='+len, f ); + bench( format( '%s:assign:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.generic.factory.js b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.generic.factory.js index cddfc35b8f96..4bb13f96adb2 100644 --- a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.generic.factory.js +++ b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.generic.factory.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::factory:dtype=generic,len='+len, f ); + bench( format( '%s::factory:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.generic.js index 3471ff3ee389..0a5b0e300bc9 100644 --- a/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/array/weibull/benchmark/benchmark.generic.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -91,7 +92,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/iter/arcsine/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/arcsine/benchmark/benchmark.js index fb8f8a383f42..30d65fc9b6f2 100644 --- a/lib/node_modules/@stdlib/random/iter/arcsine/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/arcsine/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( assert ) { assert.end(); }); -bench( pkg+'::iteration', function benchmark( assert ) { +bench( format( '%s::iteration', pkg ), function benchmark( assert ) { var rand; var a; var b; diff --git a/lib/node_modules/@stdlib/random/iter/bernoulli/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/bernoulli/benchmark/benchmark.js index f9671f2552ac..a7e2ffba689a 100644 --- a/lib/node_modules/@stdlib/random/iter/bernoulli/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/bernoulli/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -50,7 +51,7 @@ bench( pkg, function benchmark( assert ) { assert.end(); }); -bench( pkg+'::iteration', function benchmark( assert ) { +bench( format( '%s::iteration', pkg ), function benchmark( assert ) { var rand; var p; var z; diff --git a/lib/node_modules/@stdlib/random/iter/beta/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/beta/benchmark/benchmark.js index 2b1247c9064f..7be63ffb8966 100644 --- a/lib/node_modules/@stdlib/random/iter/beta/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/beta/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var alpha; var beta; var rand; diff --git a/lib/node_modules/@stdlib/random/iter/betaprime/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/betaprime/benchmark/benchmark.js index 2b1247c9064f..7be63ffb8966 100644 --- a/lib/node_modules/@stdlib/random/iter/betaprime/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/betaprime/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var alpha; var beta; var rand; diff --git a/lib/node_modules/@stdlib/random/iter/binomial/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/binomial/benchmark/benchmark.js index 67efab657b40..81dab63d2bcf 100644 --- a/lib/node_modules/@stdlib/random/iter/binomial/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/binomial/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var ceil = require( '@stdlib/math/base/special/ceil' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( assert ) { assert.end(); }); -bench( pkg+'::iteration', function benchmark( assert ) { +bench( format( '%s::iteration', pkg ), function benchmark( assert ) { var rand; var n; var p; diff --git a/lib/node_modules/@stdlib/random/iter/box-muller/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/box-muller/benchmark/benchmark.js index 7af69a9f97ca..de6a784e134c 100644 --- a/lib/node_modules/@stdlib/random/iter/box-muller/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/box-muller/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var z; var i; diff --git a/lib/node_modules/@stdlib/random/iter/cauchy/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/cauchy/benchmark/benchmark.js index 2fd78ebb76da..92147d763921 100644 --- a/lib/node_modules/@stdlib/random/iter/cauchy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/cauchy/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var gamma; var rand; var x0; diff --git a/lib/node_modules/@stdlib/random/iter/chi/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/chi/benchmark/benchmark.js index 1e827a90741b..43d3a10467d3 100644 --- a/lib/node_modules/@stdlib/random/iter/chi/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/chi/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -51,7 +52,7 @@ bench( pkg, function benchmark( assert ) { assert.end(); }); -bench( pkg+'::iteration', function benchmark( assert ) { +bench( format( '%s::iteration', pkg ), function benchmark( assert ) { var rand; var k; var z; diff --git a/lib/node_modules/@stdlib/random/iter/chisquare/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/chisquare/benchmark/benchmark.js index 1e827a90741b..43d3a10467d3 100644 --- a/lib/node_modules/@stdlib/random/iter/chisquare/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/chisquare/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -51,7 +52,7 @@ bench( pkg, function benchmark( assert ) { assert.end(); }); -bench( pkg+'::iteration', function benchmark( assert ) { +bench( format( '%s::iteration', pkg ), function benchmark( assert ) { var rand; var k; var z; diff --git a/lib/node_modules/@stdlib/random/iter/cosine/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/cosine/benchmark/benchmark.js index feaca53c7c89..7334465813e3 100644 --- a/lib/node_modules/@stdlib/random/iter/cosine/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/cosine/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var mu; var s; diff --git a/lib/node_modules/@stdlib/random/iter/discrete-uniform/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/discrete-uniform/benchmark/benchmark.js index 3ac18051b815..9d67a168c530 100644 --- a/lib/node_modules/@stdlib/random/iter/discrete-uniform/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/discrete-uniform/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( assert ) { assert.end(); }); -bench( pkg+'::iteration', function benchmark( assert ) { +bench( format( '%s::iteration', pkg ), function benchmark( assert ) { var rand; var a; var b; diff --git a/lib/node_modules/@stdlib/random/iter/erlang/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/erlang/benchmark/benchmark.js index 5f77dc0e7a18..0896d947acce 100644 --- a/lib/node_modules/@stdlib/random/iter/erlang/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/erlang/benchmark/benchmark.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var ceil = require( '@stdlib/math/base/special/ceil' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -54,7 +55,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var lambda; var rand; var k; diff --git a/lib/node_modules/@stdlib/random/iter/exponential/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/exponential/benchmark/benchmark.js index f90b847cbaa5..1738c077be24 100644 --- a/lib/node_modules/@stdlib/random/iter/exponential/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/exponential/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -51,7 +52,7 @@ bench( pkg, function benchmark( assert ) { assert.end(); }); -bench( pkg+'::iteration', function benchmark( assert ) { +bench( format( '%s::iteration', pkg ), function benchmark( assert ) { var lambda; var rand; var z; diff --git a/lib/node_modules/@stdlib/random/iter/f/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/f/benchmark/benchmark.js index 8dde10160918..f1114f403900 100644 --- a/lib/node_modules/@stdlib/random/iter/f/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/f/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var d1; var d2; diff --git a/lib/node_modules/@stdlib/random/iter/frechet/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/frechet/benchmark/benchmark.js index 80802f28b48c..d1076c76a9b1 100644 --- a/lib/node_modules/@stdlib/random/iter/frechet/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/frechet/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -55,7 +56,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var alpha; var rand; var s; diff --git a/lib/node_modules/@stdlib/random/iter/gamma/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/gamma/benchmark/benchmark.js index 2b1247c9064f..7be63ffb8966 100644 --- a/lib/node_modules/@stdlib/random/iter/gamma/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/gamma/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var alpha; var beta; var rand; diff --git a/lib/node_modules/@stdlib/random/iter/geometric/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/geometric/benchmark/benchmark.js index f9671f2552ac..a7e2ffba689a 100644 --- a/lib/node_modules/@stdlib/random/iter/geometric/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/geometric/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -50,7 +51,7 @@ bench( pkg, function benchmark( assert ) { assert.end(); }); -bench( pkg+'::iteration', function benchmark( assert ) { +bench( format( '%s::iteration', pkg ), function benchmark( assert ) { var rand; var p; var z; diff --git a/lib/node_modules/@stdlib/random/iter/gumbel/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/gumbel/benchmark/benchmark.js index df8608ab3413..de86512ebef9 100644 --- a/lib/node_modules/@stdlib/random/iter/gumbel/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/gumbel/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var beta; var rand; var mu; diff --git a/lib/node_modules/@stdlib/random/iter/hypergeometric/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/hypergeometric/benchmark/benchmark.js index 1969717c144c..3f52ed27af4c 100644 --- a/lib/node_modules/@stdlib/random/iter/hypergeometric/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/hypergeometric/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var ceil = require( '@stdlib/math/base/special/ceil' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -55,7 +56,7 @@ bench( pkg, function benchmark( assert ) { assert.end(); }); -bench( pkg+'::iteration', function benchmark( assert ) { +bench( format( '%s::iteration', pkg ), function benchmark( assert ) { var rand; var N; var K; diff --git a/lib/node_modules/@stdlib/random/iter/improved-ziggurat/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/improved-ziggurat/benchmark/benchmark.js index 7af69a9f97ca..de6a784e134c 100644 --- a/lib/node_modules/@stdlib/random/iter/improved-ziggurat/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/improved-ziggurat/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var z; var i; diff --git a/lib/node_modules/@stdlib/random/iter/invgamma/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/invgamma/benchmark/benchmark.js index 2b1247c9064f..7be63ffb8966 100644 --- a/lib/node_modules/@stdlib/random/iter/invgamma/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/invgamma/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var alpha; var beta; var rand; diff --git a/lib/node_modules/@stdlib/random/iter/kumaraswamy/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/kumaraswamy/benchmark/benchmark.js index 2b1247c9064f..7be63ffb8966 100644 --- a/lib/node_modules/@stdlib/random/iter/kumaraswamy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/kumaraswamy/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var alpha; var beta; var rand; diff --git a/lib/node_modules/@stdlib/random/iter/laplace/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/laplace/benchmark/benchmark.js index bd7f386d4d32..669777339789 100644 --- a/lib/node_modules/@stdlib/random/iter/laplace/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/laplace/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( assert ) { assert.end(); }); -bench( pkg+'::iteration', function benchmark( assert ) { +bench( format( '%s::iteration', pkg ), function benchmark( assert ) { var rand; var mu; var b; diff --git a/lib/node_modules/@stdlib/random/iter/levy/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/levy/benchmark/benchmark.js index af1629c8f2a3..c98b8232b74e 100644 --- a/lib/node_modules/@stdlib/random/iter/levy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/levy/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var mu; var c; diff --git a/lib/node_modules/@stdlib/random/iter/logistic/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/logistic/benchmark/benchmark.js index ee3080188668..8d4cd084d8c9 100644 --- a/lib/node_modules/@stdlib/random/iter/logistic/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/logistic/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var mu; var s; diff --git a/lib/node_modules/@stdlib/random/iter/lognormal/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/lognormal/benchmark/benchmark.js index 0193d616fbec..40eb50ae4bd0 100644 --- a/lib/node_modules/@stdlib/random/iter/lognormal/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/lognormal/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var sigma; var rand; var mu; diff --git a/lib/node_modules/@stdlib/random/iter/minstd-shuffle/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/minstd-shuffle/benchmark/benchmark.js index 7af69a9f97ca..de6a784e134c 100644 --- a/lib/node_modules/@stdlib/random/iter/minstd-shuffle/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/minstd-shuffle/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var z; var i; diff --git a/lib/node_modules/@stdlib/random/iter/minstd/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/minstd/benchmark/benchmark.js index 7af69a9f97ca..de6a784e134c 100644 --- a/lib/node_modules/@stdlib/random/iter/minstd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/minstd/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var z; var i; diff --git a/lib/node_modules/@stdlib/random/iter/mt19937/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/mt19937/benchmark/benchmark.js index 7af69a9f97ca..de6a784e134c 100644 --- a/lib/node_modules/@stdlib/random/iter/mt19937/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/mt19937/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var z; var i; diff --git a/lib/node_modules/@stdlib/random/iter/negative-binomial/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/negative-binomial/benchmark/benchmark.js index 9618c6514199..4c3421a5eb30 100644 --- a/lib/node_modules/@stdlib/random/iter/negative-binomial/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/negative-binomial/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var ceil = require( '@stdlib/math/base/special/ceil' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( assert ) { assert.end(); }); -bench( pkg+'::iteration', function benchmark( assert ) { +bench( format( '%s::iteration', pkg ), function benchmark( assert ) { var rand; var r; var p; diff --git a/lib/node_modules/@stdlib/random/iter/normal/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/normal/benchmark/benchmark.js index 0193d616fbec..40eb50ae4bd0 100644 --- a/lib/node_modules/@stdlib/random/iter/normal/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/normal/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var sigma; var rand; var mu; diff --git a/lib/node_modules/@stdlib/random/iter/pareto-type1/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/pareto-type1/benchmark/benchmark.js index 2b1247c9064f..7be63ffb8966 100644 --- a/lib/node_modules/@stdlib/random/iter/pareto-type1/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/pareto-type1/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var alpha; var beta; var rand; diff --git a/lib/node_modules/@stdlib/random/iter/poisson/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/poisson/benchmark/benchmark.js index 85c2a1475409..57be425ebc07 100644 --- a/lib/node_modules/@stdlib/random/iter/poisson/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/poisson/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -51,7 +52,7 @@ bench( pkg, function benchmark( assert ) { assert.end(); }); -bench( pkg+'::iteration', function benchmark( assert ) { +bench( format( '%s::iteration', pkg ), function benchmark( assert ) { var lambda; var rand; var z; diff --git a/lib/node_modules/@stdlib/random/iter/randi/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/randi/benchmark/benchmark.js index 7af69a9f97ca..de6a784e134c 100644 --- a/lib/node_modules/@stdlib/random/iter/randi/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/randi/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var z; var i; diff --git a/lib/node_modules/@stdlib/random/iter/randn/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/randn/benchmark/benchmark.js index 7af69a9f97ca..de6a784e134c 100644 --- a/lib/node_modules/@stdlib/random/iter/randn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/randn/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var z; var i; diff --git a/lib/node_modules/@stdlib/random/iter/randu/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/randu/benchmark/benchmark.js index 7af69a9f97ca..de6a784e134c 100644 --- a/lib/node_modules/@stdlib/random/iter/randu/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/randu/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var rand; var z; var i; diff --git a/lib/node_modules/@stdlib/random/iter/rayleigh/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/rayleigh/benchmark/benchmark.js index e323b8c7aea5..9d870e50e3d7 100644 --- a/lib/node_modules/@stdlib/random/iter/rayleigh/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/rayleigh/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -51,7 +52,7 @@ bench( pkg, function benchmark( assert ) { assert.end(); }); -bench( pkg+'::iteration', function benchmark( assert ) { +bench( format( '%s::iteration', pkg ), function benchmark( assert ) { var sigma; var rand; var z; diff --git a/lib/node_modules/@stdlib/random/iter/t/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/t/benchmark/benchmark.js index d4ca1711b8b1..6d3074a07c98 100644 --- a/lib/node_modules/@stdlib/random/iter/t/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/t/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -51,7 +52,7 @@ bench( pkg, function benchmark( assert ) { assert.end(); }); -bench( pkg+'::iteration', function benchmark( assert ) { +bench( format( '%s::iteration', pkg ), function benchmark( assert ) { var rand; var v; var z; diff --git a/lib/node_modules/@stdlib/random/iter/triangular/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/triangular/benchmark/benchmark.js index 25a387fa8689..f1fcaae990c1 100644 --- a/lib/node_modules/@stdlib/random/iter/triangular/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/triangular/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -54,7 +55,7 @@ bench( pkg, function benchmark( assert ) { assert.end(); }); -bench( pkg+'::iteration', function benchmark( assert ) { +bench( format( '%s::iteration', pkg ), function benchmark( assert ) { var rand; var a; var b; diff --git a/lib/node_modules/@stdlib/random/iter/uniform/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/uniform/benchmark/benchmark.js index fb8f8a383f42..30d65fc9b6f2 100644 --- a/lib/node_modules/@stdlib/random/iter/uniform/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/uniform/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( assert ) { assert.end(); }); -bench( pkg+'::iteration', function benchmark( assert ) { +bench( format( '%s::iteration', pkg ), function benchmark( assert ) { var rand; var a; var b; diff --git a/lib/node_modules/@stdlib/random/iter/weibull/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/iter/weibull/benchmark/benchmark.js index 8cc25842e63f..c37435c6627b 100644 --- a/lib/node_modules/@stdlib/random/iter/weibull/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/iter/weibull/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var iterator = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var lambda; var rand; var k; diff --git a/lib/node_modules/@stdlib/random/streams/arcsine/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/arcsine/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/arcsine/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/arcsine/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/arcsine/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/arcsine/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/arcsine/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/arcsine/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/bernoulli/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/bernoulli/benchmark/benchmark.js index aee8c35a550f..72e11e863b78 100644 --- a/lib/node_modules/@stdlib/random/streams/bernoulli/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/bernoulli/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/bernoulli/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/bernoulli/benchmark/benchmark.throughput.js index 2d0493d9a569..7906f90d4159 100644 --- a/lib/node_modules/@stdlib/random/streams/bernoulli/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/bernoulli/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/beta/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/beta/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/beta/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/beta/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/beta/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/beta/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/beta/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/beta/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/betaprime/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/betaprime/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/betaprime/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/betaprime/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/betaprime/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/betaprime/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/betaprime/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/betaprime/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/binomial/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/binomial/benchmark/benchmark.js index 062eb6674b9d..682176b5d13c 100644 --- a/lib/node_modules/@stdlib/random/streams/binomial/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/binomial/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/binomial/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/binomial/benchmark/benchmark.throughput.js index 183d516daa06..a39eb26998a8 100644 --- a/lib/node_modules/@stdlib/random/streams/binomial/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/binomial/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/box-muller/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/box-muller/benchmark/benchmark.js index 18e78f0dac0c..2a7833f27bfb 100644 --- a/lib/node_modules/@stdlib/random/streams/box-muller/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/box-muller/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/box-muller/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/box-muller/benchmark/benchmark.throughput.js index ac7e6ebc4e4c..274426a9cf66 100644 --- a/lib/node_modules/@stdlib/random/streams/box-muller/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/box-muller/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/cauchy/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/cauchy/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/cauchy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/cauchy/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/cauchy/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/cauchy/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/cauchy/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/cauchy/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/chi/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/chi/benchmark/benchmark.js index 4fb679ab6cae..3d2e8ed814ea 100644 --- a/lib/node_modules/@stdlib/random/streams/chi/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/chi/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/chi/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/chi/benchmark/benchmark.throughput.js index 233963533f9f..0325c0c96526 100644 --- a/lib/node_modules/@stdlib/random/streams/chi/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/chi/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/chisquare/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/chisquare/benchmark/benchmark.js index 4fb679ab6cae..3d2e8ed814ea 100644 --- a/lib/node_modules/@stdlib/random/streams/chisquare/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/chisquare/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/chisquare/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/chisquare/benchmark/benchmark.throughput.js index 233963533f9f..0325c0c96526 100644 --- a/lib/node_modules/@stdlib/random/streams/chisquare/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/chisquare/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/cosine/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/cosine/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/cosine/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/cosine/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/cosine/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/cosine/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/cosine/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/cosine/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/discrete-uniform/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/discrete-uniform/benchmark/benchmark.js index 863d11a9618a..66156db505f2 100644 --- a/lib/node_modules/@stdlib/random/streams/discrete-uniform/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/discrete-uniform/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/discrete-uniform/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/discrete-uniform/benchmark/benchmark.throughput.js index 892d89df777d..87a9869adb69 100644 --- a/lib/node_modules/@stdlib/random/streams/discrete-uniform/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/discrete-uniform/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/erlang/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/erlang/benchmark/benchmark.js index 33959c9f5260..dd5b7d19f3b2 100644 --- a/lib/node_modules/@stdlib/random/streams/erlang/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/erlang/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/erlang/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/erlang/benchmark/benchmark.throughput.js index 84c894523d30..ef61b8d793ad 100644 --- a/lib/node_modules/@stdlib/random/streams/erlang/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/erlang/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/exponential/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/exponential/benchmark/benchmark.js index 4fb679ab6cae..3d2e8ed814ea 100644 --- a/lib/node_modules/@stdlib/random/streams/exponential/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/exponential/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/exponential/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/exponential/benchmark/benchmark.throughput.js index 233963533f9f..0325c0c96526 100644 --- a/lib/node_modules/@stdlib/random/streams/exponential/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/exponential/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/f/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/f/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/f/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/f/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/f/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/f/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/f/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/f/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/frechet/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/frechet/benchmark/benchmark.js index 888c1aaba2f7..76fdce8a99b9 100644 --- a/lib/node_modules/@stdlib/random/streams/frechet/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/frechet/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/frechet/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/frechet/benchmark/benchmark.throughput.js index ba13f7d0d8c6..74beb774c6ee 100644 --- a/lib/node_modules/@stdlib/random/streams/frechet/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/frechet/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/gamma/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/gamma/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/gamma/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/gamma/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/gamma/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/gamma/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/gamma/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/gamma/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/geometric/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/geometric/benchmark/benchmark.js index aee8c35a550f..72e11e863b78 100644 --- a/lib/node_modules/@stdlib/random/streams/geometric/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/geometric/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/geometric/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/geometric/benchmark/benchmark.throughput.js index 2d0493d9a569..7906f90d4159 100644 --- a/lib/node_modules/@stdlib/random/streams/geometric/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/geometric/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/gumbel/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/gumbel/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/gumbel/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/gumbel/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/gumbel/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/gumbel/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/gumbel/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/gumbel/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/hypergeometric/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/hypergeometric/benchmark/benchmark.js index 3bcfb482519d..ad71b87dff6e 100644 --- a/lib/node_modules/@stdlib/random/streams/hypergeometric/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/hypergeometric/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/hypergeometric/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/hypergeometric/benchmark/benchmark.throughput.js index 7a230120cec7..1e905ef2ef7f 100644 --- a/lib/node_modules/@stdlib/random/streams/hypergeometric/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/hypergeometric/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/improved-ziggurat/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/improved-ziggurat/benchmark/benchmark.js index 18e78f0dac0c..2a7833f27bfb 100644 --- a/lib/node_modules/@stdlib/random/streams/improved-ziggurat/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/improved-ziggurat/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/improved-ziggurat/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/improved-ziggurat/benchmark/benchmark.throughput.js index ac7e6ebc4e4c..274426a9cf66 100644 --- a/lib/node_modules/@stdlib/random/streams/improved-ziggurat/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/improved-ziggurat/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/invgamma/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/invgamma/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/invgamma/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/invgamma/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/invgamma/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/invgamma/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/invgamma/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/invgamma/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/kumaraswamy/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/kumaraswamy/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/kumaraswamy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/kumaraswamy/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/kumaraswamy/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/kumaraswamy/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/kumaraswamy/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/kumaraswamy/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/laplace/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/laplace/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/laplace/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/laplace/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/laplace/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/laplace/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/laplace/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/laplace/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/levy/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/levy/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/levy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/levy/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/levy/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/levy/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/levy/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/levy/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/logistic/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/logistic/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/logistic/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/logistic/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/logistic/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/logistic/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/logistic/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/logistic/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/lognormal/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/lognormal/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/lognormal/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/lognormal/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/lognormal/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/lognormal/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/lognormal/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/lognormal/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/minstd-shuffle/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/minstd-shuffle/benchmark/benchmark.js index 18e78f0dac0c..2a7833f27bfb 100644 --- a/lib/node_modules/@stdlib/random/streams/minstd-shuffle/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/minstd-shuffle/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/minstd-shuffle/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/minstd-shuffle/benchmark/benchmark.throughput.js index ac7e6ebc4e4c..274426a9cf66 100644 --- a/lib/node_modules/@stdlib/random/streams/minstd-shuffle/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/minstd-shuffle/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/minstd/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/minstd/benchmark/benchmark.js index 18e78f0dac0c..2a7833f27bfb 100644 --- a/lib/node_modules/@stdlib/random/streams/minstd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/minstd/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/minstd/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/minstd/benchmark/benchmark.throughput.js index ac7e6ebc4e4c..274426a9cf66 100644 --- a/lib/node_modules/@stdlib/random/streams/minstd/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/minstd/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/mt19937/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/mt19937/benchmark/benchmark.js index 18e78f0dac0c..2a7833f27bfb 100644 --- a/lib/node_modules/@stdlib/random/streams/mt19937/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/mt19937/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/mt19937/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/mt19937/benchmark/benchmark.throughput.js index ac7e6ebc4e4c..274426a9cf66 100644 --- a/lib/node_modules/@stdlib/random/streams/mt19937/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/mt19937/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/negative-binomial/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/negative-binomial/benchmark/benchmark.js index 3c409c74e211..6c9a18c97a2d 100644 --- a/lib/node_modules/@stdlib/random/streams/negative-binomial/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/negative-binomial/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/negative-binomial/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/negative-binomial/benchmark/benchmark.throughput.js index b67227aa2308..3ad26dceac1f 100644 --- a/lib/node_modules/@stdlib/random/streams/negative-binomial/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/negative-binomial/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/normal/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/normal/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/normal/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/normal/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/normal/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/normal/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/normal/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/normal/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/pareto-type1/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/pareto-type1/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/pareto-type1/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/pareto-type1/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/pareto-type1/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/pareto-type1/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/pareto-type1/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/pareto-type1/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/poisson/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/poisson/benchmark/benchmark.js index 4fb679ab6cae..3d2e8ed814ea 100644 --- a/lib/node_modules/@stdlib/random/streams/poisson/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/poisson/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/poisson/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/poisson/benchmark/benchmark.throughput.js index 233963533f9f..0325c0c96526 100644 --- a/lib/node_modules/@stdlib/random/streams/poisson/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/poisson/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/randi/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/randi/benchmark/benchmark.js index 18e78f0dac0c..2a7833f27bfb 100644 --- a/lib/node_modules/@stdlib/random/streams/randi/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/randi/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/randi/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/randi/benchmark/benchmark.throughput.js index ac7e6ebc4e4c..274426a9cf66 100644 --- a/lib/node_modules/@stdlib/random/streams/randi/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/randi/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/randn/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/randn/benchmark/benchmark.js index 18e78f0dac0c..2a7833f27bfb 100644 --- a/lib/node_modules/@stdlib/random/streams/randn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/randn/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/randn/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/randn/benchmark/benchmark.throughput.js index ac7e6ebc4e4c..274426a9cf66 100644 --- a/lib/node_modules/@stdlib/random/streams/randn/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/randn/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/randu/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/randu/benchmark/benchmark.js index 18e78f0dac0c..2a7833f27bfb 100644 --- a/lib/node_modules/@stdlib/random/streams/randu/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/randu/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/randu/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/randu/benchmark/benchmark.throughput.js index ac7e6ebc4e4c..274426a9cf66 100644 --- a/lib/node_modules/@stdlib/random/streams/randu/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/randu/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/rayleigh/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/rayleigh/benchmark/benchmark.js index 4fb679ab6cae..3d2e8ed814ea 100644 --- a/lib/node_modules/@stdlib/random/streams/rayleigh/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/rayleigh/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/rayleigh/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/rayleigh/benchmark/benchmark.throughput.js index 233963533f9f..0325c0c96526 100644 --- a/lib/node_modules/@stdlib/random/streams/rayleigh/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/rayleigh/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/t/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/t/benchmark/benchmark.js index 4fb679ab6cae..3d2e8ed814ea 100644 --- a/lib/node_modules/@stdlib/random/streams/t/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/t/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/t/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/t/benchmark/benchmark.throughput.js index 233963533f9f..0325c0c96526 100644 --- a/lib/node_modules/@stdlib/random/streams/t/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/t/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/triangular/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/triangular/benchmark/benchmark.js index cee744995c59..70b7a14cd29c 100644 --- a/lib/node_modules/@stdlib/random/streams/triangular/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/triangular/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/triangular/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/triangular/benchmark/benchmark.throughput.js index 6ed1a5c3206f..75c1126c8d3b 100644 --- a/lib/node_modules/@stdlib/random/streams/triangular/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/triangular/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/uniform/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/uniform/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/uniform/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/uniform/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/uniform/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/uniform/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/uniform/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/uniform/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/streams/weibull/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/streams/weibull/benchmark/benchmark.js index 542ae91e4bec..5c754b848f93 100644 --- a/lib/node_modules/@stdlib/random/streams/weibull/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/streams/weibull/benchmark/benchmark.js @@ -22,6 +22,7 @@ var Readable = require( 'readable-stream' ).Readable; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randomStream = require( './../lib' ); @@ -47,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::seed', function benchmark( b ) { +bench( format( '%s::seed', pkg ), function benchmark( b ) { var opts; var s; var i; @@ -71,7 +72,7 @@ bench( pkg+'::seed', function benchmark( b ) { b.end(); }); -bench( pkg+':objectMode', function benchmark( b ) { +bench( format( '%s:objectMode', pkg ), function benchmark( b ) { var s; var i; @@ -90,7 +91,7 @@ bench( pkg+':objectMode', function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var createStream; var s; var i; diff --git a/lib/node_modules/@stdlib/random/streams/weibull/benchmark/benchmark.throughput.js b/lib/node_modules/@stdlib/random/streams/weibull/benchmark/benchmark.throughput.js index 4123b98fa57f..28879ef58cf6 100644 --- a/lib/node_modules/@stdlib/random/streams/weibull/benchmark/benchmark.throughput.js +++ b/lib/node_modules/@stdlib/random/streams/weibull/benchmark/benchmark.throughput.js @@ -22,6 +22,7 @@ var WritableStream = require( 'readable-stream' ).Writable; // eslint-disable-line stdlib/no-redeclare var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var inherit = require( '@stdlib/utils/inherit' ); var nextTick = require( '@stdlib/utils/next-tick' ); var pkg = require( './../package.json' ).name; @@ -30,7 +31,7 @@ var randomStream = require( './../lib' ); // MAIN // -bench( pkg+'::throughput,baseline', function benchmark( b ) { +bench( format( '%s::throughput,baseline', pkg ), function benchmark( b ) { var i; i = 0; @@ -56,7 +57,7 @@ bench( pkg+'::throughput,baseline', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -101,7 +102,7 @@ bench( pkg+'::throughput:highWaterMark=', function benchmark( b ) { } }); -bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -148,7 +149,7 @@ bench( pkg+'::throughput:highWaterMark=0', function benchmark( b ) { } }); -bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; @@ -195,7 +196,7 @@ bench( pkg+'::throughput,object_mode:highWaterMark=', function benchmar } }); -bench( pkg+'::throughput,object_mode:highWaterMark=0', function benchmark( b ) { +bench( format( '%s::throughput,object_mode:highWaterMark=0', pkg ), function benchmark( b ) { var rStream; var wStream; var opts; diff --git a/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float32.broadcast.js index e0d3e5933a08..a9325d872468 100644 --- a/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var arcsine = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float32.js index 97a9e84de4c3..9cff5a657166 100644 --- a/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var arcsine = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float64.broadcast.js index 08f080682cf9..f15b833a84fb 100644 --- a/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var arcsine = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float64.broadcast.options.js b/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float64.broadcast.options.js index 9206b0dc5a2e..c5f41a43d060 100644 --- a/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float64.broadcast.options.js +++ b/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float64.broadcast.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var arcsine = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast,options:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast,options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float64.js index ffc00d581cb4..cbd84781f732 100644 --- a/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var arcsine = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float64.options.js b/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float64.options.js index d23fcf01afaf..532af6e63f29 100644 --- a/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float64.options.js +++ b/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.float64.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var arcsine = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::options:dtype=float64,len='+len, f ); + bench( format( '%s::options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.generic.broadcast.js index bec84af29f19..b4e5777ab715 100644 --- a/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var arcsine = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.generic.js index 4d1a6239d461..724049d886a1 100644 --- a/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/arcsine/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var arcsine = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.float32.broadcast.js index b5a1c6cb07e4..03613cba945b 100644 --- a/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.float32.js index 3deb93501717..100095b4e79f 100644 --- a/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.float64.broadcast.js index 1830f44f3246..7816913f0c8f 100644 --- a/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.float64.js index b7589113232b..9c3954c801ba 100644 --- a/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.generic.broadcast.js index 467cec20987e..c13436e201b0 100644 --- a/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.generic.js index 57c26b3523be..f02ff23fcf51 100644 --- a/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/bernoulli/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float32.broadcast.js index 44c337083b40..3f4df0e1c47c 100644 --- a/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var beta = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float32.js index 7fc7ada05219..193d6a334936 100644 --- a/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var beta = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float64.broadcast.js index c64ff9268966..b2603e3376d1 100644 --- a/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var beta = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float64.broadcast.options.js b/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float64.broadcast.options.js index faa18a05cb48..df1aa1687f46 100644 --- a/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float64.broadcast.options.js +++ b/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float64.broadcast.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var beta = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast,options:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast,options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float64.js index 0cb7880d61db..645be2fb0bec 100644 --- a/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var beta = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float64.options.js b/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float64.options.js index 479bf8bf6d04..3c50fea9938b 100644 --- a/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float64.options.js +++ b/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.float64.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var beta = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::options:dtype=float64,len='+len, f ); + bench( format( '%s::options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.generic.broadcast.js index a56aa792cf5c..c6b09ae0747b 100644 --- a/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var beta = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.generic.js index 5ec1417b6b2d..4748f087668b 100644 --- a/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/beta/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var beta = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float32.broadcast.js index e303905fb99c..2d5e645df4ff 100644 --- a/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var betaprime = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float32.js index efa6a06034d2..ad151b99c09e 100644 --- a/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var betaprime = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float64.broadcast.js index 8e86ee960049..49edabb0adae 100644 --- a/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var betaprime = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float64.broadcast.options.js b/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float64.broadcast.options.js index 6d8632b0076f..b4257c896f9e 100644 --- a/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float64.broadcast.options.js +++ b/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float64.broadcast.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var betaprime = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast,options:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast,options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float64.js index 1e96447169b8..d0a13340f7aa 100644 --- a/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var betaprime = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float64.options.js b/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float64.options.js index 3fddc1b48427..6ae9e440de51 100644 --- a/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float64.options.js +++ b/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.float64.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var betaprime = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::options:dtype=float64,len='+len, f ); + bench( format( '%s::options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.generic.broadcast.js index 76a317fc200c..ba86e7c44843 100644 --- a/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var betaprime = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.generic.js index 61b5e7c0a03b..1f5f95b38299 100644 --- a/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/betaprime/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var betaprime = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.float32.broadcast.js index 2134d30d0c91..efc361c18e55 100644 --- a/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.float32.js index 5e989730ecfa..26c2a5794e6f 100644 --- a/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.float64.broadcast.js index b7d33b2f2e7c..250bc3e4552d 100644 --- a/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.float64.js index ef48824a55f9..6266bebdd002 100644 --- a/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.generic.broadcast.js index ceebbc0cd23b..16120f7b34e8 100644 --- a/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.generic.js index 151a3e0604e6..5f90250332eb 100644 --- a/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/chi/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.float32.broadcast.js index 2134d30d0c91..efc361c18e55 100644 --- a/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.float32.js index 5e989730ecfa..26c2a5794e6f 100644 --- a/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.float64.broadcast.js index b7d33b2f2e7c..250bc3e4552d 100644 --- a/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.float64.js index ef48824a55f9..6266bebdd002 100644 --- a/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.generic.broadcast.js index ceebbc0cd23b..16120f7b34e8 100644 --- a/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.generic.js index 151a3e0604e6..5f90250332eb 100644 --- a/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/chisquare/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float32.broadcast.js index 6f192b7454e2..9599142ffaf4 100644 --- a/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cosine = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float32.js index 9c1ab1fa6b78..d6dcfd3d9f7e 100644 --- a/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cosine = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float64.broadcast.js index e9ebf4772381..7eb6cb9a8d77 100644 --- a/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cosine = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float64.broadcast.options.js b/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float64.broadcast.options.js index 6d523254349d..0ebb72ccf723 100644 --- a/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float64.broadcast.options.js +++ b/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float64.broadcast.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cosine = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast,options:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast,options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float64.js index 22887c755343..453b22c3a5c2 100644 --- a/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cosine = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float64.options.js b/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float64.options.js index 40e588bfcaa7..894b092f3162 100644 --- a/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float64.options.js +++ b/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.float64.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cosine = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::options:dtype=float64,len='+len, f ); + bench( format( '%s::options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.generic.broadcast.js index dc5f4e1b2508..83f951fc01b0 100644 --- a/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cosine = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.generic.js index 5418a0470c8b..5dbba18f41d3 100644 --- a/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/cosine/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cosine = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float32.broadcast.js index 2ee60083bb60..4f1915b9eb47 100644 --- a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var discreteUniform = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float32.js index 5550b8377676..0aa192c935df 100644 --- a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var discreteUniform = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float64.broadcast.js index 3585e9f36b35..c7a7918e9846 100644 --- a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var discreteUniform = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float64.broadcast.options.js b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float64.broadcast.options.js index 2da9254293ba..13defe218918 100644 --- a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float64.broadcast.options.js +++ b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float64.broadcast.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var discreteUniform = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast,options:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast,options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float64.js index 7d95c44dc1f9..a9c2cf26162f 100644 --- a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var discreteUniform = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float64.options.js b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float64.options.js index 8fd83a463f0d..0afedf1e9b7b 100644 --- a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float64.options.js +++ b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.float64.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var discreteUniform = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::options:dtype=float64,len='+len, f ); + bench( format( '%s::options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.generic.broadcast.js index bffc4976b959..ab36c9fb67ea 100644 --- a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var discreteUniform = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.generic.js index 01419ac5f085..9ac2e6d66e29 100644 --- a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var discreteUniform = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.int32.broadcast.js b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.int32.broadcast.js index d8c30c9ec60b..6cc8c6e640b5 100644 --- a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.int32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.int32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var discreteUniform = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=int32,len='+len, f ); + bench( format( '%s::broadcast:dtype=int32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.int32.js b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.int32.js index 858048e05e99..c6b81d29c973 100644 --- a/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.int32.js +++ b/lib/node_modules/@stdlib/random/strided/discrete-uniform/benchmark/benchmark.int32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var discreteUniform = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=int32,len='+len, f ); + bench( format( '%s:dtype=int32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.float32.broadcast.js index 38cea4fdbbd6..846f12152287 100644 --- a/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.float32.js index e057b9691f8b..e5fb4a90ba8b 100644 --- a/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.float64.broadcast.js index bf50f202cdc2..2347256dcae8 100644 --- a/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.float64.js index e89f00ec7143..803c766ab4d3 100644 --- a/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.generic.broadcast.js index 1cb76a5e56fa..46a01f6db790 100644 --- a/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.generic.js index 383876d8dbcc..2ee13218403f 100644 --- a/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/exponential/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float32.broadcast.js index 8240e04d72d4..ad564924c536 100644 --- a/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gamma = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float32.js index eb1f69928c3b..f70cebfd671c 100644 --- a/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gamma = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float64.broadcast.js index 17dc347b107f..f1cca2cf2519 100644 --- a/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gamma = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float64.broadcast.options.js b/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float64.broadcast.options.js index ae6f8158b428..ea311b570d09 100644 --- a/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float64.broadcast.options.js +++ b/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float64.broadcast.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gamma = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast,options:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast,options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float64.js index 9a7d048807e4..ffb16ee43351 100644 --- a/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gamma = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float64.options.js b/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float64.options.js index a79594c70f87..1465002560ac 100644 --- a/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float64.options.js +++ b/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.float64.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gamma = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::options:dtype=float64,len='+len, f ); + bench( format( '%s::options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.generic.broadcast.js index 4b12fbcc32e8..861a17241635 100644 --- a/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gamma = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.generic.js index d03a3e34fe4b..bbcf1fd94af9 100644 --- a/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/gamma/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var gamma = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.float32.broadcast.js index bd95e4c24d60..84171a38a3f6 100644 --- a/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.float32.js index b44e53fc8431..8f3a32260848 100644 --- a/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.float64.broadcast.js index 14f8828d88ae..5ebbe4745f78 100644 --- a/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.float64.js index 62538a83892a..b71b849dcb52 100644 --- a/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.generic.broadcast.js index b994530f29a2..fcf7a6747a62 100644 --- a/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.generic.js index 319580cc084b..b0a2afb4706e 100644 --- a/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/geometric/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float32.broadcast.js index 30b9410bab46..e7a500167b39 100644 --- a/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var invgamma = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float32.js index 80b82b1e1134..073a14354f48 100644 --- a/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var invgamma = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float64.broadcast.js index 4068c9695c31..1c5ba6c3c701 100644 --- a/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var invgamma = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float64.broadcast.options.js b/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float64.broadcast.options.js index 3a75b38047ed..d0a80225b61c 100644 --- a/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float64.broadcast.options.js +++ b/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float64.broadcast.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var invgamma = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast,options:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast,options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float64.js index cdeed5a74ab5..c294cf732027 100644 --- a/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var invgamma = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float64.options.js b/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float64.options.js index e15acea21558..ee2be9a0915a 100644 --- a/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float64.options.js +++ b/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.float64.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var invgamma = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::options:dtype=float64,len='+len, f ); + bench( format( '%s::options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.generic.broadcast.js index 5f8b4af981bf..d49bf0d453b3 100644 --- a/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var invgamma = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.generic.js index 0ba486edfaa1..5d6587b5ee0a 100644 --- a/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/invgamma/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var invgamma = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float32.broadcast.js index 6d8c2237cd36..c601217025ba 100644 --- a/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var lognormal = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float32.js index 03acc304b133..74261d1c349e 100644 --- a/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var lognormal = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float64.broadcast.js index 59203f734c61..6f1050454a10 100644 --- a/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var lognormal = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float64.broadcast.options.js b/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float64.broadcast.options.js index a18a7277bda5..86a678e5d71d 100644 --- a/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float64.broadcast.options.js +++ b/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float64.broadcast.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var lognormal = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast,options:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast,options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float64.js index a2203122ec3e..a81fde949f9b 100644 --- a/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var lognormal = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float64.options.js b/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float64.options.js index 7c67b739d32d..42265ca45d50 100644 --- a/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float64.options.js +++ b/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.float64.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var lognormal = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::options:dtype=float64,len='+len, f ); + bench( format( '%s::options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.generic.broadcast.js index d4b6183bf124..cca27e34b08f 100644 --- a/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var lognormal = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.generic.js index 62c717d12243..1e8597441a91 100644 --- a/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/lognormal/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var lognormal = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.float32.js index a8405d0ebb6a..a934e525f15c 100644 --- a/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.float64.js index b6fbcfe325de..39a8f9d66740 100644 --- a/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.float64.normalized.js b/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.float64.normalized.js index b78e9a85882a..dd149a04e4cc 100644 --- a/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.float64.normalized.js +++ b/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.float64.normalized.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ).normalized; @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.float64.options.js b/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.float64.options.js index 481aba2492b3..77e86ad602c8 100644 --- a/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.float64.options.js +++ b/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.float64.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::options:dtype=float64,len='+len, f ); + bench( format( '%s::options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.generic.js index 1be46968df26..b068e8152c06 100644 --- a/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/minstd-shuffle/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.float32.js index a8405d0ebb6a..a934e525f15c 100644 --- a/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.float64.js index b6fbcfe325de..39a8f9d66740 100644 --- a/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.float64.normalized.js b/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.float64.normalized.js index b78e9a85882a..dd149a04e4cc 100644 --- a/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.float64.normalized.js +++ b/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.float64.normalized.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ).normalized; @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.float64.options.js b/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.float64.options.js index 481aba2492b3..77e86ad602c8 100644 --- a/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.float64.options.js +++ b/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.float64.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::options:dtype=float64,len='+len, f ); + bench( format( '%s::options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.generic.js index 1be46968df26..b068e8152c06 100644 --- a/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/minstd/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minstd = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.float32.js index bd1d39ec063f..ba274d4122cc 100644 --- a/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mt19937 = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.float64.js index 8f3ff94e9820..5571ff1b0f99 100644 --- a/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mt19937 = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.float64.normalized.js b/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.float64.normalized.js index e055e8ac3ac2..b1efd74e353d 100644 --- a/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.float64.normalized.js +++ b/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.float64.normalized.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mt19937 = require( './../lib' ).normalized; @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.float64.options.js b/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.float64.options.js index 1e24f80753f4..a6544c737471 100644 --- a/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.float64.options.js +++ b/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.float64.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mt19937 = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::options:dtype=float64,len='+len, f ); + bench( format( '%s::options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.generic.js index 8ab118dc269a..5df430cf45e8 100644 --- a/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/mt19937/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mt19937 = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float32.broadcast.js index 3813429e79d6..2653b3f40a4c 100644 --- a/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var normal = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float32.js index 575f77319b77..656fb4a158fc 100644 --- a/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var normal = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float64.broadcast.js index 8544d4af8963..f71d8c1bcdbe 100644 --- a/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var normal = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float64.broadcast.options.js b/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float64.broadcast.options.js index f359e31a3bd5..74d68159943f 100644 --- a/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float64.broadcast.options.js +++ b/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float64.broadcast.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var normal = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast,options:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast,options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float64.js index 7a035d2f8e97..41082e4c1809 100644 --- a/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var normal = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float64.options.js b/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float64.options.js index f6c31b62e869..e163971dd795 100644 --- a/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float64.options.js +++ b/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.float64.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var normal = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::options:dtype=float64,len='+len, f ); + bench( format( '%s::options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.generic.broadcast.js index ccfe112b4879..efaf56c2b765 100644 --- a/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var normal = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.generic.js index 0599a58bb5b4..7496acdf2a11 100644 --- a/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/normal/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var normal = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.float32.broadcast.js index 2134d30d0c91..efc361c18e55 100644 --- a/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.float32.js index 5e989730ecfa..26c2a5794e6f 100644 --- a/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.float64.broadcast.js index b7d33b2f2e7c..250bc3e4552d 100644 --- a/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.float64.js index ef48824a55f9..6266bebdd002 100644 --- a/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.generic.broadcast.js index ceebbc0cd23b..16120f7b34e8 100644 --- a/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.generic.js index 151a3e0604e6..5f90250332eb 100644 --- a/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/poisson/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/randu/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/randu/benchmark/benchmark.float32.js index 374fd9003e0a..a9851f9c3231 100644 --- a/lib/node_modules/@stdlib/random/strided/randu/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/randu/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randu = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/randu/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/randu/benchmark/benchmark.float64.js index 8a181f93df12..98435c25a177 100644 --- a/lib/node_modules/@stdlib/random/strided/randu/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/randu/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randu = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/randu/benchmark/benchmark.float64.options.js b/lib/node_modules/@stdlib/random/strided/randu/benchmark/benchmark.float64.options.js index 64e1d4b6972c..bd2c9dc94541 100644 --- a/lib/node_modules/@stdlib/random/strided/randu/benchmark/benchmark.float64.options.js +++ b/lib/node_modules/@stdlib/random/strided/randu/benchmark/benchmark.float64.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randu = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::options:dtype=float64,len='+len, f ); + bench( format( '%s::options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/randu/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/randu/benchmark/benchmark.generic.js index 0c64c98362a8..b5ba70ce9683 100644 --- a/lib/node_modules/@stdlib/random/strided/randu/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/randu/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var randu = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.float32.broadcast.js index 2134d30d0c91..efc361c18e55 100644 --- a/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.float32.js index 5e989730ecfa..26c2a5794e6f 100644 --- a/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.float64.broadcast.js index b7d33b2f2e7c..250bc3e4552d 100644 --- a/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.float64.js index ef48824a55f9..6266bebdd002 100644 --- a/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.generic.broadcast.js index ceebbc0cd23b..16120f7b34e8 100644 --- a/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.generic.js index 151a3e0604e6..5f90250332eb 100644 --- a/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/rayleigh/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.float32.broadcast.js index 2134d30d0c91..efc361c18e55 100644 --- a/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.float32.js index 5e989730ecfa..26c2a5794e6f 100644 --- a/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.float64.broadcast.js index b7d33b2f2e7c..250bc3e4552d 100644 --- a/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.float64.js index ef48824a55f9..6266bebdd002 100644 --- a/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.generic.broadcast.js index ceebbc0cd23b..16120f7b34e8 100644 --- a/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.generic.js index 151a3e0604e6..5f90250332eb 100644 --- a/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/t/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var random = require( './../lib' ); @@ -93,7 +94,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.broadcast.length.js b/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.broadcast.length.js index 09506f9fa5bf..2dbfe38b89db 100644 --- a/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.broadcast.length.js +++ b/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.broadcast.length.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var arcsine = require( '@stdlib/random/base/arcsine' ); var filledarray = require( '@stdlib/array/filled' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var binaryFactory = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::fill,broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::fill,broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.js index c30a193a6740..717fcbac24d0 100644 --- a/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var arcsine = require( '@stdlib/random/base/arcsine' ); var normal = require( '@stdlib/random/base/normal' ); var isFunction = require( '@stdlib/assert/is-function' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var binaryFactory = require( './../lib' ); @@ -55,7 +56,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var rand; var f; var i; diff --git a/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.length.js index e4a767ec36bd..360833913d95 100644 --- a/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.length.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var arcsine = require( '@stdlib/random/base/arcsine' ); var filledarray = require( '@stdlib/array/filled' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var binaryFactory = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::fill:dtype=float64,len='+len, f ); + bench( format( '%s::fill:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.ndarray.broadcast.length.js b/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.ndarray.broadcast.length.js index b684a7fad3c3..499c7566a4f6 100644 --- a/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.ndarray.broadcast.length.js +++ b/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.ndarray.broadcast.length.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var arcsine = require( '@stdlib/random/base/arcsine' ); var filledarray = require( '@stdlib/array/filled' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var binaryFactory = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::fill,broadcast:ndarray:dtype=float64,len='+len, f ); + bench( format( '%s::fill,broadcast:ndarray:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.ndarray.length.js b/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.ndarray.length.js index 0830bc7f24b0..822a450388c2 100644 --- a/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.ndarray.length.js +++ b/lib/node_modules/@stdlib/random/strided/tools/binary-factory/benchmark/benchmark.ndarray.length.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var arcsine = require( '@stdlib/random/base/arcsine' ); var filledarray = require( '@stdlib/array/filled' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var binaryFactory = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::fill:ndarray:dtype=float64,len='+len, f ); + bench( format( '%s::fill:ndarray:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.broadcast.length.js b/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.broadcast.length.js index 476994ebf7a7..a4630d5f91aa 100644 --- a/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.broadcast.length.js +++ b/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.broadcast.length.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var triangular = require( '@stdlib/random/base/triangular' ); var filledarray = require( '@stdlib/array/filled' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ternaryFactory = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::fill,broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::fill,broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.js index 2a72bce622ad..d44f562aefeb 100644 --- a/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var triangular = require( '@stdlib/random/base/triangular' ); var hypergeometric = require( '@stdlib/random/base/hypergeometric' ); var isFunction = require( '@stdlib/assert/is-function' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ternaryFactory = require( './../lib' ); @@ -55,7 +56,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var rand; var f; var i; diff --git a/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.length.js index d81d6d9acd3f..cb670c09077c 100644 --- a/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.length.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var triangular = require( '@stdlib/random/base/triangular' ); var filledarray = require( '@stdlib/array/filled' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ternaryFactory = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::fill:dtype=float64,len='+len, f ); + bench( format( '%s::fill:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.ndarray.broadcast.length.js b/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.ndarray.broadcast.length.js index ae4f4ea20241..2be02d868b14 100644 --- a/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.ndarray.broadcast.length.js +++ b/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.ndarray.broadcast.length.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var triangular = require( '@stdlib/random/base/triangular' ); var filledarray = require( '@stdlib/array/filled' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ternaryFactory = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::fill,broadcast:ndarray:dtype=float64,len='+len, f ); + bench( format( '%s::fill,broadcast:ndarray:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.ndarray.length.js b/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.ndarray.length.js index 039e0de9e241..cda08a3c9d82 100644 --- a/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.ndarray.length.js +++ b/lib/node_modules/@stdlib/random/strided/tools/ternary-factory/benchmark/benchmark.ndarray.length.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var triangular = require( '@stdlib/random/base/triangular' ); var filledarray = require( '@stdlib/array/filled' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ternaryFactory = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::fill:ndarray:dtype=float64,len='+len, f ); + bench( format( '%s::fill:ndarray:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.broadcast.length.js b/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.broadcast.length.js index 443a7e736e4d..5c882ea504df 100644 --- a/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.broadcast.length.js +++ b/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.broadcast.length.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var exponential = require( '@stdlib/random/base/exponential' ); var filledarray = require( '@stdlib/array/filled' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var unaryFactory = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::fill,broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::fill,broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.js b/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.js index da76473687ce..be42211b4ce4 100644 --- a/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var exponential = require( '@stdlib/random/base/exponential' ); var geometric = require( '@stdlib/random/base/geometric' ); var isFunction = require( '@stdlib/assert/is-function' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var unaryFactory = require( './../lib' ); @@ -55,7 +56,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::factory', function benchmark( b ) { +bench( format( '%s::factory', pkg ), function benchmark( b ) { var rand; var f; var i; diff --git a/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.length.js index c118ea0b477c..120a5bfa60be 100644 --- a/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.length.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var exponential = require( '@stdlib/random/base/exponential' ); var filledarray = require( '@stdlib/array/filled' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var unaryFactory = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::fill:dtype=float64,len='+len, f ); + bench( format( '%s::fill:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.ndarray.broadcast.length.js b/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.ndarray.broadcast.length.js index 58b95077a2c0..d48d0334d1c1 100644 --- a/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.ndarray.broadcast.length.js +++ b/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.ndarray.broadcast.length.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var exponential = require( '@stdlib/random/base/exponential' ); var filledarray = require( '@stdlib/array/filled' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var unaryFactory = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::fill,broadcast:ndarray:dtype=float64,len='+len, f ); + bench( format( '%s::fill,broadcast:ndarray:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.ndarray.length.js b/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.ndarray.length.js index 10b6e987e17a..68b8357670ad 100644 --- a/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.ndarray.length.js +++ b/lib/node_modules/@stdlib/random/strided/tools/unary-factory/benchmark/benchmark.ndarray.length.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var exponential = require( '@stdlib/random/base/exponential' ); var filledarray = require( '@stdlib/array/filled' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var unaryFactory = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::fill:ndarray:dtype=float64,len='+len, f ); + bench( format( '%s::fill:ndarray:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float32.broadcast.js index 2e5a00f2a451..8a6fa990605d 100644 --- a/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var uniform = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float32.js index 0f07c382810c..ddddb35ac8f1 100644 --- a/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var uniform = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float64.broadcast.js index ed3e0bb02a87..178f8bba0d54 100644 --- a/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var uniform = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float64.broadcast.options.js b/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float64.broadcast.options.js index f88b3065fbed..63e730fe137b 100644 --- a/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float64.broadcast.options.js +++ b/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float64.broadcast.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var uniform = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast,options:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast,options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float64.js index 209c06e85929..fdc4349c1bd7 100644 --- a/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var uniform = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float64.options.js b/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float64.options.js index a914eaa00756..5cf80faf7ba6 100644 --- a/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float64.options.js +++ b/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.float64.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var uniform = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::options:dtype=float64,len='+len, f ); + bench( format( '%s::options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.generic.broadcast.js index f42e75127efc..7a299a4af265 100644 --- a/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var uniform = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.generic.js index 7310aea31ce8..f142b8afbf29 100644 --- a/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/uniform/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var uniform = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float32.broadcast.js b/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float32.broadcast.js index 9463ceaadc8a..c2da53fdffb3 100644 --- a/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float32.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float32.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var weibull = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float32,len='+len, f ); + bench( format( '%s::broadcast:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float32.js b/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float32.js index 5ea50155b630..cd2cb69e2bd1 100644 --- a/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float32.js +++ b/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float32.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var weibull = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float32,len='+len, f ); + bench( format( '%s:dtype=float32,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float64.broadcast.js b/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float64.broadcast.js index 794022e0da3b..40b666b1a3a0 100644 --- a/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float64.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float64.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var weibull = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float64.broadcast.options.js b/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float64.broadcast.options.js index e56b601cb68a..fb0cfbc5c87e 100644 --- a/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float64.broadcast.options.js +++ b/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float64.broadcast.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var weibull = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast,options:dtype=float64,len='+len, f ); + bench( format( '%s::broadcast,options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float64.js b/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float64.js index aeb67a01aafd..fb5796fc25a9 100644 --- a/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float64.js +++ b/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float64.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var weibull = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=float64,len='+len, f ); + bench( format( '%s:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float64.options.js b/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float64.options.js index 14be80147ed9..d4b24d25fb6e 100644 --- a/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float64.options.js +++ b/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.float64.options.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var weibull = require( './../lib' ); @@ -102,7 +103,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::options:dtype=float64,len='+len, f ); + bench( format( '%s::options:dtype=float64,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.generic.broadcast.js b/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.generic.broadcast.js index b6fb7dc4be7b..01471730c058 100644 --- a/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.generic.broadcast.js +++ b/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.generic.broadcast.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var weibull = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::broadcast:dtype=generic,len='+len, f ); + bench( format( '%s::broadcast:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.generic.js b/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.generic.js index d1462b857d40..dbc4aeec1b5a 100644 --- a/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.generic.js +++ b/lib/node_modules/@stdlib/random/strided/weibull/benchmark/benchmark.generic.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var filledarray = require( '@stdlib/array/filled' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var weibull = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype=generic,len='+len, f ); + bench( format( '%s:dtype=generic,len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv b/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv index 3622c3ee3197..1b7d7cd685f3 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv +++ b/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv @@ -229,7 +229,7 @@ base.cbrt,"var y = base.cbrt( 64.0 )\ny = base.cbrt( 27.0 )\ny = base.cbrt( 0.0 base.cbrtf,"var y = base.cbrtf( 64.0 )\ny = base.cbrtf( 27.0 )\ny = base.cbrtf( 0.0 )\ny = base.cbrtf( -0.0 )\ny = base.cbrtf( -9.0 )\ny = base.cbrtf( NaN )\n" base.cceil,"var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n" base.cceilf,"var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n" -base.cceiln,"var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( out )\nvar im = imag( out )\n" +base.cceiln,"var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n" base.ccis,"var y = base.ccis( new Complex128( 0.0, 0.0 ) )\ny = base.ccis( new Complex128( 1.0, 0.0 ) )\n" base.cdiv,"var z1 = new Complex128( -13.0, -1.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar y = base.cdiv( z1, z2 )\nvar re = real( y )\nvar im = imag( y )\n" base.cdiv.assign,"var out = new Float64Array( 2 );\nbase.cdiv.assign( -13.0, -1.0, -2.0, 1.0, out, 1, 0 )\n" @@ -2713,8 +2713,8 @@ COMPLEX128_NAN,"COMPLEX128_NAN\n" COMPLEX128_NUM_BYTES,"COMPLEX128_NUM_BYTES\n" COMPLEX128_ZERO,"COMPLEX128_ZERO\n" Complex128Array,"var arr = new Complex128Array()\nvar arr = new Complex128Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex128Array( arr1 )\nvar len = arr2.length\nvar buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex128Array( buf )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\nvar arr2 = new Complex128Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 480 );\nvar arr1 = new Complex128Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex128Array( buf, 16 )\nlen = arr2.length\nvar arr3 = new Complex128Array( buf, 16, 20 )\nlen = arr3.length\n" -Complex128Array.from,"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n" -Complex128Array.of,"var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex128( 1.0, -1.0 );\nvar z2 = new Complex128( 2.0, -2.0 );\narr = Complex128Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n" +Complex128Array.from,"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\n" +Complex128Array.of,"var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex128( 1.0, -1.0 );\nvar z2 = new Complex128( 2.0, -2.0 );\narr = Complex128Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\n" Complex128Array.BYTES_PER_ELEMENT,"var nbytes = Complex128Array.BYTES_PER_ELEMENT\n" Complex128Array.name,"var str = Complex128Array.name\n" Complex128Array.prototype.buffer,"var arr = new Complex128Array( 2 )\nvar buf = arr.buffer\n" @@ -2722,31 +2722,31 @@ Complex128Array.prototype.byteLength,"var arr = new Complex128Array( 10 )\nvar n Complex128Array.prototype.byteOffset,"var arr = new Complex128Array( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 480 );\narr = new Complex128Array( buf, 128 )\noffset = arr.byteOffset\n" Complex128Array.prototype.BYTES_PER_ELEMENT,"var arr = new Complex128Array( 10 )\narr.BYTES_PER_ELEMENT\n" Complex128Array.prototype.length,"var arr = new Complex128Array( 10 )\nvar len = arr.length\n" -Complex128Array.prototype.at,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\nvar re = real( z )\nvar im = imag( z )\n" -Complex128Array.prototype.copyWithin,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n" -Complex128Array.prototype.entries,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nvar re = real( v[ 1 ] )\nvar im = imag( v[ 1 ] )\nv = it.next().value\nre = real( v[ 1 ] )\nim = imag( v[ 1 ] )\nv = it.next().value\nre = real( v[ 1 ] )\nim = imag( v[ 1 ] )\nvar bool = it.next().done\n" +Complex128Array.prototype.at,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\n" +Complex128Array.prototype.copyWithin,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\n" +Complex128Array.prototype.entries,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n" Complex128Array.prototype.every,"function predicate( v ) { return ( real( v ) > 0.0 ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n" -Complex128Array.prototype.fill,"var arr = new Complex128Array( 3 )\narr.fill( new Complex128( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n" -Complex128Array.prototype.filter,"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n" -Complex128Array.prototype.find,"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\nvar re = real( z )\nvar im = imag( z )\n" +Complex128Array.prototype.fill,"var arr = new Complex128Array( 3 )\narr.fill( new Complex128( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n" +Complex128Array.prototype.filter,"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\n" +Complex128Array.prototype.find,"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\n" Complex128Array.prototype.findIndex,"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n" -Complex128Array.prototype.findLast,"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\nvar re = real( z )\nvar im = imag( z )\n" +Complex128Array.prototype.findLast,"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\n" Complex128Array.prototype.findLastIndex,"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n" Complex128Array.prototype.forEach,"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n" -Complex128Array.prototype.get,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\nvar re = real( z )\nvar im = imag( z )\n" +Complex128Array.prototype.get,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\n" Complex128Array.prototype.includes,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex128( 3.0, -3.0 ) )\nbool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n" Complex128Array.prototype.indexOf,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n" Complex128Array.prototype.join,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n" Complex128Array.prototype.keys,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n" Complex128Array.prototype.lastIndexOf,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n" -Complex128Array.prototype.map,"function clbk( v ) { return v; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n" -Complex128Array.prototype.reduce,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.cadd )\nvar re = real( z )\nvar im = imag( z )\n" -Complex128Array.prototype.reduceRight,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.cadd )\nvar re = real( z )\nvar im = imag( z )\n" -Complex128Array.prototype.reverse,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n" -Complex128Array.prototype.set,"var arr = new Complex128Array( 2 )\narr.set( new Complex128( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\narr.set( new Complex128( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\n" -Complex128Array.prototype.slice,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n" +Complex128Array.prototype.map,"function clbk( v ) { return v; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nz = out.get( 1 )\n" +Complex128Array.prototype.reduce,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.cadd )\n" +Complex128Array.prototype.reduceRight,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.cadd )\n" +Complex128Array.prototype.reverse,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n" +Complex128Array.prototype.set,"var arr = new Complex128Array( 2 )\narr.set( new Complex128( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\narr.set( new Complex128( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\n" +Complex128Array.prototype.slice,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nz = out.get( 1 )\n" Complex128Array.prototype.some,"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n" -Complex128Array.prototype.sort,"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n" +Complex128Array.prototype.sort,"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n" Complex128Array.prototype.subarray,"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n" Complex128Array.prototype.toLocaleString,"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n" Complex128Array.prototype.toReversed,"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n" diff --git a/lib/node_modules/@stdlib/repl/code-blocks/data/data.json b/lib/node_modules/@stdlib/repl/code-blocks/data/data.json index f6842d052cb9..9d091c44f907 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/data/data.json +++ b/lib/node_modules/@stdlib/repl/code-blocks/data/data.json @@ -1 +1 @@ -{"abs":"var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\nvar x = array( arr );\nvar y = abs( x )\n","abs.assign":"var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\nvar x = array( arr );\nvar sh = ndarrayShape( x );\nvar y = ndzeros( sh );\nvar out = abs.assign( x, y )\nvar bool = ( out === y )\n","acartesianPower":"var x = [ 1, 2 ];\nvar out = acartesianPower( x, 2 )\n","acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = acartesianProduct( x1, x2 )\n","acartesianSquare":"var out = acartesianSquare( [ 1, 2 ] )\n","acronym":"var out = acronym( 'the quick brown fox' )\nout = acronym( 'Hard-boiled eggs' )\n","aempty":"var arr = aempty( 2 )\narr = aempty( 2, 'float32' )\n","aemptyLike":"var x = new Float64Array( 2 );\nvar arr = aemptyLike( x )\narr = aemptyLike( x, 'float32' )\n","AFINN_96":"var list = AFINN_96()\n","AFINN_111":"var list = AFINN_111()\n","afull":"var arr = afull( 2, 1.0 )\narr = afull( 2, 1.0, 'float32' )\n","afullLike":"var x = new Float64Array( 2 );\nvar y = afullLike( x, 1.0 )\ny = afullLike( x, 1.0, 'float32' )\n","alias2pkg":"var v = alias2pkg( 'base.sin' )\n","alias2related":"var v = alias2related( 'base.sin' )\n","alias2standalone":"var v = alias2standalone( 'base.sin' )\n","aliases":"var o = aliases()\no = aliases( '@stdlib/math/base/special' )\n","allocUnsafe":"var buf = allocUnsafe( 100 )\n","amskfilter":"var x = [ 1, 2, 3, 4 ];\nvar y = amskfilter( x, [ 0, 1, 0, 1 ] )\n","amskput":"var x = [ 1, 2, 3, 4 ];\nvar out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","amskreject":"var x = [ 1, 2, 3, 4 ];\nvar y = amskreject( x, [ 0, 1, 0, 1 ] )\n","anans":"var arr = anans( 2 )\narr = anans( 2, 'float32' )\n","anansLike":"var x = new Float64Array( 2 );\nvar y = anansLike( x )\ny = anansLike( x, 'float32' )\n","anova1":"var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nvar f = [\n 'control', 'treatA', 'treatB', 'treatC', 'control',\n 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ];\nvar out = anova1( x, f )\n","ANSCOMBES_QUARTET":"var d = ANSCOMBES_QUARTET()\n","any":"var arr = [ 0, 0, 0, 0, 1 ];\nvar bool = any( arr )\n","anyBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4, -1 ];\nvar bool = anyBy( arr, negative )\n","anyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n","anyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","anyByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, 2, 3, 4 ];\nvar bool = anyByRight( arr, negative )\n","anyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n","anyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","anyInBy":"function isNegative(value) { return value < 0 }\nvar obj = { a: 1, b: -2, c: 3, d: 4 }\nvar result = anyInBy(obj, isNegative)\n","anyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': -1, 'b': 2, 'c': -3 };\nvar bool = anyOwnBy( obj, positive )\n","aones":"var arr = aones( 2 )\narr = aones( 2, 'float32' )\n","aonesLike":"var x = new Float64Array( 2 );\nvar y = aonesLike( x )\ny = aonesLike( x, 'float32' )\n","aoneTo":"var arr = aoneTo( 2 )\narr = aoneTo( 2, 'float32' )\n","aoneToLike":"var arr = aoneToLike( [ 0, 0 ] )\narr = aoneToLike( [ 0, 0 ], 'float32' )\n","APERY":"APERY\n","aplace":"var x = [ 1, 2, 3, 4 ];\nvar out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","append":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = append( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = append( arr, [ 3.0, 4.0 ] )\narr = { 'length': 0 };\narr = append( arr, [ 1.0, 2.0 ] )\n","aput":"var x = [ 1, 2, 3, 4 ];\nvar out = aput( x, [ 1, 3 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","ARCH":"ARCH\n","argumentFunction":"var argn = argumentFunction( 1 );\nvar v = argn( 3.14, -3.14, 0.0 )\nv = argn( -1.0, -0.0, 1.0 )\nv = argn( 'beep', 'boop', 'bop' )\nv = argn( 'beep' )\n","ARGV":"var execPath = ARGV[ 0 ]\n","array":"var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","array2buffer":"var buf = array2buffer( [ 1, 2, 3, 4 ] )\n","array2fancy":"var y = array2fancy( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.factory":"var f = array2fancy.factory();\nvar y = f( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.idx":"var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n","array2iterator":"var it = array2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","array2iteratorRight":"var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","ArrayBuffer":"var buf = new ArrayBuffer( 5 )\n","ArrayBuffer.length":"ArrayBuffer.length\n","ArrayBuffer.isView":"var arr = new Float64Array( 10 );\nArrayBuffer.isView( arr )\n","ArrayBuffer.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nbuf.byteLength\n","ArrayBuffer.prototype.slice":"var b1 = new ArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","arraybuffer2buffer":"var ab = new ArrayBuffer( 10 )\nvar buf = arraybuffer2buffer( ab )\nvar len = buf.length\nbuf = arraybuffer2buffer( ab, 2, 6 )\nlen = buf.length\n","arrayCtors":"var ctor = arrayCtors( 'float64' )\nctor = arrayCtors( 'float' )\n","arrayDataType":"var arr = new Float64Array( 10 );\nvar dt = arrayDataType( arr )\ndt = arrayDataType( 'beep' )\n","arrayDataTypes":"var out = arrayDataTypes()\nout = arrayDataTypes( 'floating_point' )\nout = arrayDataTypes( 'floating_point_and_generic' )\n","ArrayIndex":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n","ArrayIndex.free":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.free( idx.id )\n","ArrayIndex.get":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.get( idx.id )\n","ArrayIndex.prototype.data":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.data\n","ArrayIndex.prototype.dtype":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.dtype\n","ArrayIndex.prototype.id":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.id\n","ArrayIndex.prototype.isCached":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.isCached\n","ArrayIndex.prototype.type":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.type\n","ArrayIndex.prototype.toString":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toString()\n","ArrayIndex.prototype.toJSON":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toJSON()\n","arrayMinDataType":"var dt = arrayMinDataType( 3.141592653589793 )\ndt = arrayMinDataType( 3 )\ndt = arrayMinDataType( -3 )\ndt = arrayMinDataType( '-3' )\n","arrayMostlySafeCasts":"var out = arrayMostlySafeCasts( 'float32' )\n","arrayNextDataType":"var out = arrayNextDataType( 'float32' )\n","arrayPromotionRules":"var out = arrayPromotionRules( 'float32', 'int32' )\n","arraySafeCasts":"var out = arraySafeCasts( 'float32' )\n","arraySameKindCasts":"var out = arraySameKindCasts( 'float32' )\n","arrayShape":"var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n","arrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = arrayStream( [ 1, 2, 3 ] );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","arrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = arrayStream.factory( opts );\n","arrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = arrayStream.objectMode( [ 1, 2, 3 ] );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","arrayview2iterator":"var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","arrayview2iteratorRight":"var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","aslice":"var out = aslice( [ 1, 2, 3, 4 ] )\nout = aslice( [ 1, 2, 3, 4 ], 1 )\nout = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n","AsyncIteratorSymbol":"var s = AsyncIteratorSymbol\n","atake":"var x = [ 1, 2, 3, 4 ];\nvar y = atake( x, [ 1, 3 ] )\n","azeros":"var arr = azeros( 2 )\narr = azeros( 2, 'float32' )\n","azerosLike":"var x = new Float64Array( 2 );\nvar y = azerosLike( x )\ny = azerosLike( x, 'float32' )\n","azeroTo":"var arr = azeroTo( 2 )\narr = azeroTo( 2, 'float32' )\n","azeroToLike":"var arr = azeroToLike( [ 0, 0 ] )\narr = azeroToLike( [ 0, 0 ], 'float32' )\n","bartlettTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = bartlettTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = bartlettTest( arr, { 'groups': groups } )\n","base.abs":"var y = base.abs( -1.0 )\ny = base.abs( 2.0 )\ny = base.abs( 0.0 )\ny = base.abs( -0.0 )\ny = base.abs( NaN )\n","base.abs2":"var y = base.abs2( -1.0 )\ny = base.abs2( 2.0 )\ny = base.abs2( 0.0 )\ny = base.abs2( -0.0 )\ny = base.abs2( NaN )\n","base.abs2f":"var y = base.abs2f( -1.0 )\ny = base.abs2f( 2.0 )\ny = base.abs2f( 0.0 )\ny = base.abs2f( -0.0 )\ny = base.abs2f( NaN )\n","base.absdiff":"var d = base.absdiff( 2.0, 5.0 )\nd = base.absdiff( -1.0, 3.14 )\nd = base.absdiff( 10.1, -2.05 )\nd = base.absdiff( -0.0, 0.0 )\nd = base.absdiff( NaN, 5.0 )\nd = base.absdiff( PINF, NINF )\nd = base.absdiff( PINF, PINF )\n","base.absf":"var y = base.absf( -1.0 )\ny = base.absf( 2.0 )\ny = base.absf( 0.0 )\ny = base.absf( -0.0 )\ny = base.absf( NaN )\n","base.acartesianPower":"var x = [ 1, 2 ];\nvar out = base.acartesianPower( x, 2 )\n","base.acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = base.acartesianProduct( x1, x2 )\n","base.acartesianSquare":"var x = [ 1, 2 ];\nvar out = base.acartesianSquare( x )\n","base.acos":"var y = base.acos( 1.0 )\ny = base.acos( 0.707 )\ny = base.acos( NaN )\n","base.acosd":"var y = base.acosd( 0.0 )\ny = base.acosd( PI/6.0 )\ny = base.acosd( NaN )\n","base.acosdf":"var y = base.acosdf( 0.0 )\ny = base.acosdf( FLOAT32_PI / 6.0 )\ny = base.acosdf( NaN )\n","base.acosf":"var y = base.acosf( 1.0 )\ny = base.acosf( 0.707 )\ny = base.acosf( NaN )\n","base.acosh":"var y = base.acosh( 1.0 )\ny = base.acosh( 2.0 )\ny = base.acosh( NaN )\n","base.acot":"var y = base.acot( 2.0 )\ny = base.acot( 0.0 )\ny = base.acot( 0.5 )\ny = base.acot( 1.0 )\ny = base.acot( NaN )\n","base.acotd":"var y = base.acotd( 0.0 )\ny = base.acotd( PI/6.0 )\ny = base.acotd( NaN )\n","base.acotdf":"var y = base.acotdf( 0.0 )\ny = base.acotdf( FLOAT32_PI/6.0 )\ny = base.acotdf( NaN )\n","base.acotf":"var y = base.acotf( 2.0 )\ny = base.acotf( 0.0 )\ny = base.acotf( 0.5 )\ny = base.acotf( 1.0 )\ny = base.acotf( NaN )\n","base.acoth":"var y = base.acoth( 2.0 )\ny = base.acoth( 0.0 )\ny = base.acoth( 0.5 )\ny = base.acoth( 1.0 )\ny = base.acoth( NaN )\n","base.acovercos":"var y = base.acovercos( 1.5 )\ny = base.acovercos( -0.0 )\n","base.acoversin":"var y = base.acoversin( 1.5 )\ny = base.acoversin( 0.0 )\n","base.acsc":"var y = base.acsc( 1.0 )\ny = base.acsc( PI )\ny = base.acsc( -PI )\ny = base.acsc( NaN )\n","base.acscd":"var y = base.acscd( 0.0 )\ny = base.acscd( PI/6.0 )\ny = base.acscd( 1 )\ny = base.acscd( NaN )\n","base.acscdf":"var y = base.acscdf( 0.0 )\ny = base.acscdf( 3.1415927410125732 / 6.0 )\ny = base.acscdf( 1.0 )\ny = base.acscdf( NaN )\n","base.acscf":"var y = base.acscf( 1.0 )\ny = base.acscf( 3.141592653589793 )\ny = base.acscf( -3.141592653589793 )\ny = base.acscf( NaN )\n","base.acsch":"var y = base.acsch( 0.0 )\ny = base.acsch( -1.0 )\ny = base.acsch( NaN )\n","base.add":"var v = base.add( -1.0, 5.0 )\nv = base.add( 2.0, 5.0 )\nv = base.add( 0.0, 5.0 )\nv = base.add( -0.0, 0.0 )\nv = base.add( NaN, NaN )\n","base.add3":"var v = base.add3( -1.0, 5.0, 2.0 )\nv = base.add3( 2.0, 5.0, 2.0 )\nv = base.add3( 0.0, 5.0, 2.0 )\nv = base.add3( -0.0, 0.0, -0.0 )\nv = base.add3( NaN, NaN, NaN )\n","base.add4":"var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\nv = base.add4( 2.0, 5.0, 2.0, -3.0 )\nv = base.add4( 0.0, 5.0, 2.0, -3.0 )\nv = base.add4( -0.0, 0.0, -0.0, -0.0 )\nv = base.add4( NaN, NaN, NaN, NaN )\n","base.add5":"var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\nv = base.add5( NaN, NaN, NaN, NaN, NaN )\n","base.addf":"var v = base.addf( -1.0, 5.0 )\nv = base.addf( 2.0, 5.0 )\nv = base.addf( 0.0, 5.0 )\nv = base.addf( -0.0, 0.0 )\nv = base.addf( NaN, NaN )\n","base.afilled":"var out = base.afilled( 0.0, 3 )\n","base.afilled2d":"var out = base.afilled2d( 0.0, [ 1, 3 ] )\n","base.afilled2dBy":"function clbk() { return 1.0; };\nvar out = base.afilled2dBy( [ 1, 3 ], clbk )\n","base.afilled3d":"var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n","base.afilled3dBy":"function clbk() { return 1.0; };\nvar out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n","base.afilled4d":"var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n","base.afilled4dBy":"function clbk() { return 1.0; };\nvar out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n","base.afilled5d":"var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n","base.afilled5dBy":"function clbk() { return 1.0; };\nvar out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n","base.afilledBy":"function clbk() { return 1.0; };\nvar out = base.afilledBy( 3, clbk )\n","base.afillednd":"var out = base.afillednd( 0.0, [ 1, 3 ] )\n","base.afilledndBy":"function clbk() { return 1.0; };\nvar out = base.afilledndBy( [ 1, 3 ], clbk )\n","base.afilter":"function f( v ) { return ( v > 0 ); };\nvar x = [ 1, -2, -3, 4 ];\nvar out = base.afilter( x, f )\n","base.afirst":"var out = base.afirst( [ 1, 2, 3 ] )\n","base.aflatten":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten( x, [ 2, 2 ], false )\nout = base.aflatten( x, [ 2, 2 ], true )\n","base.aflatten.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2d":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2d( x, [ 2, 2 ], false )\nout = base.aflatten2d( x, [ 2, 2 ], true )\n","base.aflatten2d.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\nout = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n","base.aflatten2dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten3d":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3d( x, [ 2, 1, 2 ], false )\nout = base.aflatten3d( x, [ 2, 1, 2 ], true )\n","base.aflatten3d.assign":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten3dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\nout = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n","base.aflatten3dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten4d":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\nout = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n","base.aflatten4d.assign":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten4dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\nout = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n","base.aflatten4dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten5d":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\nout = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n","base.aflatten5d.assign":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten5dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\nout = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n","base.aflatten5dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflattenBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\nout = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n","base.aflattenBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.afliplr2d":"var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.afliplr3d":"var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.afliplr4d":"var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.afliplr5d":"var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.aflipud2d":"var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.aflipud3d":"var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.aflipud4d":"var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.aflipud5d":"var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.ahavercos":"var y = base.ahavercos( 0.5 )\ny = base.ahavercos( 0.0 )\n","base.ahaversin":"var y = base.ahaversin( 0.5 )\ny = base.ahaversin( 0.0 )\n","base.altcase":"var out = base.altcase( 'Hello World!' )\nout = base.altcase( 'I am a tiny little teapot' )\n","base.aones":"var out = base.aones( 3 )\n","base.aones2d":"var out = base.aones2d( [ 1, 3 ] )\n","base.aones3d":"var out = base.aones3d( [ 1, 1, 3 ] )\n","base.aones4d":"var out = base.aones4d( [ 1, 1, 1, 3 ] )\n","base.aones5d":"var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n","base.aonesnd":"var out = base.aonesnd( [ 1, 3 ] )\n","base.aoneTo":"var arr = base.aoneTo( 6 )\n","base.aoneTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.aoneTo.assign( out, -1, out.length-1 );\nout\n","base.args2multislice":"var args = [ null, null, null ];\nvar s = new base.args2multislice( args );\ns.data\nargs = [ 10, new Slice( 0, 10, 1 ), null ];\ns = new base.args2multislice( args );\ns.data\n","base.asec":"var y = base.asec( 1.0 )\ny = base.asec( 2.0 )\ny = base.asec( NaN )\n","base.asecd":"var y = base.asecd( 0.0 )\ny = base.asecd( 2 )\ny = base.asecd( NaN )\n","base.asecdf":"var y = base.asecdf( 2.0 )\ny = base.asecdf( 0.0 )\ny = base.asecdf( NaN )\n","base.asecf":"var y = base.asecf( 1.0 )\ny = base.asecf( 2.0 )\ny = base.asecf( NaN )\n","base.asech":"var y = base.asech( 1.0 )\ny = base.asech( 0.5 )\ny = base.asech( NaN )\n","base.asin":"var y = base.asin( 0.0 )\ny = base.asin( -PI/6.0 )\ny = base.asin( NaN )\n","base.asind":"var y = base.asind( 0.0 )\ny = base.asind( PI / 6.0 )\ny = base.asind( NaN )\n","base.asindf":"var y = base.asindf( 0.0 )\ny = base.asindf( 3.1415927410125732 / 6.0 )\ny = base.asindf( NaN )\n","base.asinf":"var y = base.asinf( 0.0 )\ny = base.asinf( -3.14/6.0 )\ny = base.asinf( NaN )\n","base.asinh":"var y = base.asinh( 0.0 )\ny = base.asinh( 2.0 )\ny = base.asinh( -2.0 )\ny = base.asinh( NaN )\ny = base.asinh( NINF )\ny = base.asinh( PINF )\n","base.atan":"var y = base.atan( 0.0 )\ny = base.atan( -PI/2.0 )\ny = base.atan( PI/2.0 )\ny = base.atan( NaN )\n","base.atan2":"var v = base.atan2( 2.0, 2.0 )\nv = base.atan2( 6.0, 2.0 )\nv = base.atan2( -1.0, -1.0 )\nv = base.atan2( 3.0, 0.0 )\nv = base.atan2( -2.0, 0.0 )\nv = base.atan2( 0.0, 0.0 )\nv = base.atan2( 3.0, NaN )\nv = base.atan2( NaN, 2.0 )\n","base.atand":"var y = base.atand( 0.0 )\ny = base.atand( PI/6.0 )\ny = base.atand( NaN )\n","base.atanf":"var y = base.atanf( 0.0 )\ny = base.atanf( -3.14/4.0 )\ny = base.atanf( 3.14/4.0 )\ny = base.atanf( NaN )\n","base.atanh":"var y = base.atanh( 0.0 )\ny = base.atanh( 0.9 )\ny = base.atanh( 1.0 )\ny = base.atanh( -1.0 )\ny = base.atanh( NaN )\n","base.avercos":"var y = base.avercos( -1.5 )\ny = base.avercos( -0.0 )\n","base.aversin":"var y = base.aversin( 1.5 )\ny = base.aversin( 0.0 )\n","base.azeros":"var out = base.azeros( 3 )\n","base.azeros2d":"var out = base.azeros2d( [ 1, 3 ] )\n","base.azeros3d":"var out = base.azeros3d( [ 1, 1, 3 ] )\n","base.azeros4d":"var out = base.azeros4d( [ 1, 1, 1, 3 ] )\n","base.azeros5d":"var out = base.azeros5d( [ 1, 1, 1, 1, 3 ] )\n","base.azerosnd":"var out = base.azerosnd( [ 1, 3 ] )\n","base.azeroTo":"var arr = base.azeroTo( 6 )\n","base.azeroTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.azeroTo.assign( out, -1, out.length-1 );\nout\n","base.bernoulli":"var y = base.bernoulli( 0 )\ny = base.bernoulli( 1 )\ny = base.bernoulli( 2 )\ny = base.bernoulli( 3 )\ny = base.bernoulli( 4 )\ny = base.bernoulli( 5 )\ny = base.bernoulli( 20 )\ny = base.bernoulli( 260 )\ny = base.bernoulli( 262 )\ny = base.bernoulli( NaN )\n","base.besselj0":"var y = base.besselj0( 0.0 )\ny = base.besselj0( 1.0 )\ny = base.besselj0( PINF )\ny = base.besselj0( NINF )\ny = base.besselj0( NaN )\n","base.besselj1":"var y = base.besselj1( 0.0 )\ny = base.besselj1( 1.0 )\ny = base.besselj1( PINF )\ny = base.besselj1( NINF )\ny = base.besselj1( NaN )\n","base.bessely0":"var y = base.bessely0( 0.0 )\ny = base.bessely0( 1.0 )\ny = base.bessely0( -1.0 )\ny = base.bessely0( PINF )\ny = base.bessely0( NINF )\ny = base.bessely0( NaN )\n","base.bessely1":"var y = base.bessely1( 0.0 )\ny = base.bessely1( 1.0 )\ny = base.bessely1( -1.0 )\ny = base.bessely1( PINF )\ny = base.bessely1( NINF )\ny = base.bessely1( NaN )\n","base.beta":"var v = base.beta( 0.0, 0.5 )\nv = base.beta( 1.0, 1.0 )\nv = base.beta( -1.0, 2.0 )\nv = base.beta( 5.0, 0.2 )\nv = base.beta( 4.0, 1.0 )\nv = base.beta( NaN, 2.0 )\n","base.betainc":"var y = base.betainc( 0.5, 2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, 2.0, false )\ny = base.betainc( 0.2, 1.0, 2.0 )\ny = base.betainc( 0.2, 1.0, 2.0, true, true )\ny = base.betainc( NaN, 1.0, 1.0 )\ny = base.betainc( 0.8, NaN, 1.0 )\ny = base.betainc( 0.8, 1.0, NaN )\ny = base.betainc( 1.5, 1.0, 1.0 )\ny = base.betainc( -0.5, 1.0, 1.0 )\ny = base.betainc( 0.5, -2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, -2.0 )\n","base.betaincinv":"var y = base.betaincinv( 0.2, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0, true )\ny = base.betaincinv( 0.4, 1.0, 6.0 )\ny = base.betaincinv( 0.8, 1.0, 6.0 )\ny = base.betaincinv( NaN, 1.0, 1.0 )\ny = base.betaincinv( 0.5, NaN, 1.0 )\ny = base.betaincinv( 0.5, 1.0, NaN )\ny = base.betaincinv( 1.2, 1.0, 1.0 )\ny = base.betaincinv( -0.5, 1.0, 1.0 )\ny = base.betaincinv( 0.5, -2.0, 2.0 )\ny = base.betaincinv( 0.5, 0.0, 2.0 )\ny = base.betaincinv( 0.5, 2.0, -2.0 )\ny = base.betaincinv( 0.5, 2.0, 0.0 )\n","base.betaln":"var v = base.betaln( 0.0, 0.0 )\nv = base.betaln( 1.0, 1.0 )\nv = base.betaln( -1.0, 2.0 )\nv = base.betaln( 5.0, 0.2 )\nv = base.betaln( 4.0, 1.0 )\nv = base.betaln( NaN, 2.0 )\n","base.binet":"var y = base.binet( 0.0 )\ny = base.binet( 1.0 )\ny = base.binet( 2.0 )\ny = base.binet( 3.0 )\ny = base.binet( 4.0 )\ny = base.binet( 5.0 )\ny = base.binet( NaN )\n","base.binomcoef":"var v = base.binomcoef( 8, 2 )\nv = base.binomcoef( 0, 0 )\nv = base.binomcoef( -4, 2 )\nv = base.binomcoef( 5, 3 )\nv = base.binomcoef( NaN, 3 )\nv = base.binomcoef( 5, NaN )\nv = base.binomcoef( NaN, NaN )\n","base.binomcoefln":"var v = base.binomcoefln( 8, 2 )\nv = base.binomcoefln( 0, 0 )\nv = base.binomcoefln( -4, 2 )\nv = base.binomcoefln( 88, 3 )\nv = base.binomcoefln( NaN, 3 )\nv = base.binomcoefln( 5, NaN )\nv = base.binomcoefln( NaN, NaN )\n","base.boxcox":"var v = base.boxcox( 1.0, 2.5 )\nv = base.boxcox( 4.0, 2.5 )\nv = base.boxcox( 10.0, 2.5 )\nv = base.boxcox( 2.0, 0.0 )\nv = base.boxcox( -1.0, 2.5 )\nv = base.boxcox( 0.0, -1.0 )\n","base.boxcox1p":"var v = base.boxcox1p( 1.0, 2.5 )\nv = base.boxcox1p( 4.0, 2.5 )\nv = base.boxcox1p( 10.0, 2.5 )\nv = base.boxcox1p( 2.0, 0.0 )\nv = base.boxcox1p( -1.0, 2.5 )\nv = base.boxcox1p( 0.0, -1.0 )\nv = base.boxcox1p( -1.0, -1.0 )\n","base.boxcox1pinv":"var v = base.boxcox1pinv( 1.0, 2.5 )\nv = base.boxcox1pinv( 4.0, 2.5 )\nv = base.boxcox1pinv( 10.0, 2.5 )\nv = base.boxcox1pinv( 2.0, 0.0 )\nv = base.boxcox1pinv( -1.0, 2.5 )\nv = base.boxcox1pinv( 0.0, -1.0 )\nv = base.boxcox1pinv( 1.0, NaN )\nv = base.boxcox1pinv( NaN, 3.1 )\n","base.boxcoxinv":"var v = base.boxcoxinv( 1.0, 2.5 )\nv = base.boxcoxinv( 4.0, 2.5 )\nv = base.boxcoxinv( 10.0, 2.5 )\nv = base.boxcoxinv( 2.0, 0.0 )\nv = base.boxcoxinv( -1.0, 2.5 )\nv = base.boxcoxinv( 0.0, -1.0 )\nv = base.boxcoxinv( 1.0, NaN )\nv = base.boxcoxinv( NaN, 3.1 )\n","base.cabs":"var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n","base.cabs2":"var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n","base.cabs2f":"var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n","base.cabsf":"var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n","base.cadd":"var z = new Complex128( 5.0, 3.0 )\nvar out = base.cadd( z, z )\nvar re = real( out )\nvar im = imag( out )\n","base.cadd.assign":"var out = new Float64Array( 2 );\nbase.cadd.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.cadd.strided":"var z1 = new Float64Array( [ 5.0, 3.0 ] );\nvar z2 = new Float64Array( [ -2.0, 1.0 ] );\nvar out = new Float64Array( 2 );\nbase.cadd.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.caddf":"var z = new Complex64( 5.0, 3.0 )\nvar out = base.caddf( z, z )\nvar re = realf( out )\nvar im = imagf( out )\n","base.caddf.assign":"var out = new Float32Array( 2 );\nbase.caddf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.caddf.strided":"var z1 = new Float32Array( [ 5.0, 3.0 ] );\nvar z2 = new Float32Array( [ -2.0, 1.0 ] );\nvar out = new Float32Array( 2 );\nbase.caddf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.camelcase":"var out = base.camelcase( 'Hello World!' )\nout = base.camelcase( 'beep boop' )\n","base.capitalize":"var out = base.capitalize( 'beep' )\nout = base.capitalize( 'Boop' )\n","base.cbrt":"var y = base.cbrt( 64.0 )\ny = base.cbrt( 27.0 )\ny = base.cbrt( 0.0 )\ny = base.cbrt( -0.0 )\ny = base.cbrt( -9.0 )\ny = base.cbrt( NaN )\n","base.cbrtf":"var y = base.cbrtf( 64.0 )\ny = base.cbrtf( 27.0 )\ny = base.cbrtf( 0.0 )\ny = base.cbrtf( -0.0 )\ny = base.cbrtf( -9.0 )\ny = base.cbrtf( NaN )\n","base.cceil":"var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n","base.cceilf":"var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n","base.cceiln":"var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( out )\nvar im = imag( out )\n","base.ccis":"var y = base.ccis( new Complex128( 0.0, 0.0 ) )\ny = base.ccis( new Complex128( 1.0, 0.0 ) )\n","base.cdiv":"var z1 = new Complex128( -13.0, -1.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar y = base.cdiv( z1, z2 )\nvar re = real( y )\nvar im = imag( y )\n","base.cdiv.assign":"var out = new Float64Array( 2 );\nbase.cdiv.assign( -13.0, -1.0, -2.0, 1.0, out, 1, 0 )\n","base.cdiv.strided":"var z1 = new Float64Array( [ -13.0, -1.0 ] );\nvar z2 = new Float64Array( [ -2.0, 1.0 ] );\nvar out = new Float64Array( 2 );\nbase.cdiv.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.ceil":"var y = base.ceil( 3.14 )\ny = base.ceil( -4.2 )\ny = base.ceil( -4.6 )\ny = base.ceil( 9.5 )\ny = base.ceil( -0.0 )\n","base.ceil2":"var y = base.ceil2( 3.14 )\ny = base.ceil2( -4.2 )\ny = base.ceil2( -4.6 )\ny = base.ceil2( 9.5 )\ny = base.ceil2( 13.0 )\ny = base.ceil2( -13.0 )\ny = base.ceil2( -0.0 )\n","base.ceil10":"var y = base.ceil10( 3.14 )\ny = base.ceil10( -4.2 )\ny = base.ceil10( -4.6 )\ny = base.ceil10( 9.5 )\ny = base.ceil10( 13.0 )\ny = base.ceil10( -13.0 )\ny = base.ceil10( -0.0 )\n","base.ceilb":"var y = base.ceilb( 3.14159, -4, 10 )\ny = base.ceilb( 3.14159, 0, 2 )\ny = base.ceilb( 5.0, 1, 2 )\n","base.ceilf":"var y = base.ceilf( 3.14 )\ny = base.ceilf( -4.2 )\ny = base.ceilf( -4.6 )\ny = base.ceilf( 9.5 )\ny = base.ceilf( -0.0 )\n","base.ceiln":"var y = base.ceiln( 3.14159, -2 )\ny = base.ceiln( 3.14159, 0 )\ny = base.ceiln( 12368.0, 3 )\n","base.ceilsd":"var y = base.ceilsd( 3.14159, 5, 10 )\ny = base.ceilsd( 3.14159, 1, 10 )\ny = base.ceilsd( 12368.0, 2, 10 )\ny = base.ceilsd( 0.0313, 2, 2 )\n","base.cexp":"var y = base.cexp( new Complex128( 0.0, 0.0 ) )\ny = base.cexp( new Complex128( 0.0, 1.0 ) )\n","base.cflipsign":"var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\n","base.cflipsignf":"var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\n","base.cfloor":"var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\n","base.cfloorn":"var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\n","base.cidentity":"var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\nvar re = real( v )\nvar img = imag( v )\n","base.cidentityf":"var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\nvar re = realf( v )\nvar img = imagf( v )\n","base.cinv":"var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n","base.cinvf":"var v = base.cinvf( new Complex64( 2.0, 4.0 ) )\n","base.clamp":"var y = base.clamp( 3.14, 0.0, 5.0 )\ny = base.clamp( -3.14, 0.0, 5.0 )\ny = base.clamp( 3.14, 0.0, 3.0 )\ny = base.clamp( -0.0, 0.0, 5.0 )\ny = base.clamp( 0.0, -3.14, -0.0 )\ny = base.clamp( NaN, 0.0, 5.0 )\n","base.clampf":"var y = base.clampf( 3.14, 0.0, 5.0 )\ny = base.clampf( -3.14, 0.0, 5.0 )\ny = base.clampf( 3.14, 0.0, 3.0 )\ny = base.clampf( -0.0, 0.0, 5.0 )\ny = base.clampf( 0.0, -3.14, -0.0 )\ny = base.clampf( NaN, 0.0, 5.0 )\n","base.cmul":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.cmul( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.cmul.assign":"var out = new Float64Array( 2 );\nbase.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.cmul.strided":"var z1 = new Float64Array( [ 5.0, 3.0 ] );\nvar z2 = new Float64Array( [ -2.0, 1.0 ] );\nvar out = new Float64Array( 2 );\nbase.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.cmulf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.cmulf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.cmulf.assign":"var out = new Float32Array( 2 );\nbase.cmulf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.cmulf.strided":"var z1 = new Float32Array( [ 5.0, 3.0 ] );\nvar z2 = new Float32Array( [ -2.0, 1.0 ] );\nvar out = new Float32Array( 2 );\nbase.cmulf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.cneg":"var z = new Complex128( -4.2, 5.5 )\nvar v = base.cneg( z )\nvar re = real( v )\nvar im = imag( v )\n","base.cnegf":"var z = new Complex64( -4.0, 5.0 )\nvar v = base.cnegf( z )\nvar re = realf( v )\nvar im = imagf( v )\n","base.codePointAt":"var out = base.codePointAt( 'last man standing', 4, false )\nout = base.codePointAt( 'presidential election', 8, true )\nout = base.codePointAt( 'अनुच्छेद', 2, false )\nout = base.codePointAt( '🌷', 1, true )\n","base.constantcase":"var out = base.constantcase( 'Hello World!' )\nout = base.constantcase( 'I am a tiny little teapot' )\n","base.continuedFraction":"function closure() {\nvar i = 0;\nreturn function() {\n i += 1;\n return [ i, i ];\n};\n };\nvar gen = closure();\nvar out = base.continuedFraction( gen )\nfunction* generator() {\n var i = 0;\n while ( true ) {\n i += 1;\n yield [ i, i ];\n }\n };\ngen = generator();\nout = base.continuedFraction( gen )\nout = base.continuedFraction( generator(), { 'keep': true } )\nout = base.continuedFraction( generator(), { 'maxIter': 10 } )\nout = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n","base.copysign":"var z = base.copysign( -3.14, 10.0 )\nz = base.copysign( 3.14, -1.0 )\nz = base.copysign( 1.0, -0.0 )\nz = base.copysign( -3.14, -0.0 )\nz = base.copysign( -0.0, 1.0 )\n","base.copysignf":"var z = base.copysignf( -3.0, 10.0 )\nz = base.copysignf( 3.0, -1.0 )\nz = base.copysignf( 1.0, -0.0 )\nz = base.copysignf( -3.0, -0.0 )\nz = base.copysignf( -0.0, 1.0 )\n","base.cos":"var y = base.cos( 0.0 )\ny = base.cos( PI/4.0 )\ny = base.cos( -PI/6.0 )\ny = base.cos( NaN )\n","base.cosd":"var y = base.cosd( 0.0 )\ny = base.cosd( 90.0 )\ny = base.cosd( 60.0 )\ny = base.cosd( NaN )\n","base.cosh":"var y = base.cosh( 0.0 )\ny = base.cosh( 2.0 )\ny = base.cosh( -2.0 )\ny = base.cosh( NaN )\n","base.cosm1":"var y = base.cosm1( 0.0 )\ny = base.cosm1( PI/4.0 )\ny = base.cosm1( -PI/6.0 )\ny = base.cosm1( NaN )\n","base.cospi":"var y = base.cospi( 0.0 )\ny = base.cospi( 0.5 )\ny = base.cospi( 0.1 )\ny = base.cospi( NaN )\n","base.cot":"var y = base.cot( 0.0 )\ny = base.cot( -PI/4.0 )\ny = base.cot( PI/4.0 )\ny = base.cot( NaN )\n","base.cotd":"var y = base.cotd( 0.0 )\ny = base.cotd( 90.0 )\ny = base.cotd( 60.0 )\ny = base.cotd( NaN )\n","base.coth":"var y = base.coth( 0.0 )\ny = base.coth( -0.0 )\ny = base.coth( 2.0 )\ny = base.coth( -2.0 )\ny = base.coth( +Infinity )\ny = base.coth( -Infinity )\ny = base.coth( NaN )\n","base.covercos":"var y = base.covercos( 3.14 )\ny = base.covercos( -4.2 )\ny = base.covercos( -4.6 )\ny = base.covercos( 9.5 )\ny = base.covercos( -0.0 )\n","base.coversin":"var y = base.coversin( 3.14 )\ny = base.coversin( -4.2 )\ny = base.coversin( -4.6 )\ny = base.coversin( 9.5 )\ny = base.coversin( -0.0 )\n","base.cphase":"var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n","base.cpolar":"var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n","base.cpolar.assign":"var out = new Float64Array( 2 );\nvar v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\nvar bool = ( v === out )\n","base.cround":"var v = base.cround( new Complex128( 5.5, 3.3 ) )\n","base.croundn":"var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\n","base.csc":"var y = base.csc( 0.0 )\ny = base.csc( PI/2.0 )\ny = base.csc( -PI/6.0 )\ny = base.csc( NaN )\n","base.cscd":"var y = base.cscd( 1.0 )\ny = base.cscd( PI )\ny = base.cscd( -PI )\ny = base.cscd( NaN )\n","base.csch":"var y = base.csch( +0.0 )\nvar y = base.csch( -0.0 )\nvar y = base.csch( +Infinity )\nvar y = base.csch( -Infinity )\ny = base.csch( 2.0 )\ny = base.csch( -2.0 )\ny = base.csch( NaN )\n","base.csignum":"var v = base.csignum( new Complex128( -4.2, 5.5 ) )\n","base.csub":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.csub( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.csubf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.csubf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.deg2rad":"var r = base.deg2rad( 90.0 )\nr = base.deg2rad( -45.0 )\nr = base.deg2rad( NaN )\n","base.deg2radf":"var r = base.deg2radf( 90.0 )\nr = base.deg2radf( -45.0 )\nr = base.deg2radf( NaN )\n","base.digamma":"var y = base.digamma( -2.5 )\ny = base.digamma( 1.0 )\ny = base.digamma( 10.0 )\ny = base.digamma( NaN )\ny = base.digamma( -1.0 )\n","base.diracDelta":"var y = base.diracDelta( 3.14 )\ny = base.diracDelta( 0.0 )\n","base.div":"var v = base.div( -1.0, 5.0 )\nv = base.div( 2.0, 5.0 )\nv = base.div( 0.0, 5.0 )\nv = base.div( -0.0, 5.0 )\nv = base.div( NaN, NaN )\n","base.divf":"var v = base.divf( -1.0, 5.0 )\nv = base.divf( 2.0, 5.0 )\nv = base.divf( 0.0, 5.0 )\nv = base.divf( -0.0, 5.0 )\nv = base.divf( NaN, NaN )\n","base.dotcase":"var out = base.dotcase( 'Hello World!' )\nout = base.dotcase( 'I am a tiny little teapot' )\n","base.dists.arcsine.Arcsine":"var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\narcsine.a\narcsine.b\narcsine.entropy\narcsine.kurtosis\narcsine.mean\narcsine.median\narcsine.mode\narcsine.skewness\narcsine.stdev\narcsine.variance\narcsine.cdf( 0.8 )\narcsine.logcdf( 0.8 )\narcsine.logpdf( 0.4 )\narcsine.pdf( 0.8 )\narcsine.quantile( 0.8 )\n","base.dists.arcsine.cdf":"var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.cdf.factory":"var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.arcsine.entropy":"var v = base.dists.arcsine.entropy( 0.0, 1.0 )\nv = base.dists.arcsine.entropy( 4.0, 12.0 )\nv = base.dists.arcsine.entropy( 2.0, 8.0 )\n","base.dists.arcsine.kurtosis":"var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\nv = base.dists.arcsine.kurtosis( 4.0, 12.0 )\nv = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n","base.dists.arcsine.logcdf":"var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.logcdf.factory":"var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.arcsine.logpdf":"var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.logpdf.factory":"var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.arcsine.mean":"var v = base.dists.arcsine.mean( 0.0, 1.0 )\nv = base.dists.arcsine.mean( 4.0, 12.0 )\nv = base.dists.arcsine.mean( 2.0, 8.0 )\n","base.dists.arcsine.median":"var v = base.dists.arcsine.median( 0.0, 1.0 )\nv = base.dists.arcsine.median( 4.0, 12.0 )\nv = base.dists.arcsine.median( 2.0, 8.0 )\n","base.dists.arcsine.mode":"var v = base.dists.arcsine.mode( 0.0, 1.0 )\nv = base.dists.arcsine.mode( 4.0, 12.0 )\nv = base.dists.arcsine.mode( 2.0, 8.0 )\n","base.dists.arcsine.pdf":"var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.pdf.factory":"var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.arcsine.quantile":"var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\ny = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n","base.dists.arcsine.quantile.factory":"var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.arcsine.skewness":"var v = base.dists.arcsine.skewness( 0.0, 1.0 )\nv = base.dists.arcsine.skewness( 4.0, 12.0 )\nv = base.dists.arcsine.skewness( 2.0, 8.0 )\n","base.dists.arcsine.stdev":"var v = base.dists.arcsine.stdev( 0.0, 1.0 )\nv = base.dists.arcsine.stdev( 4.0, 12.0 )\nv = base.dists.arcsine.stdev( 2.0, 8.0 )\n","base.dists.arcsine.variance":"var v = base.dists.arcsine.variance( 0.0, 1.0 )\nv = base.dists.arcsine.variance( 4.0, 12.0 )\nv = base.dists.arcsine.variance( 2.0, 8.0 )\n","base.dists.bernoulli.Bernoulli":"var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\nbernoulli.p\nbernoulli.entropy\nbernoulli.kurtosis\nbernoulli.mean\nbernoulli.median\nbernoulli.skewness\nbernoulli.stdev\nbernoulli.variance\nbernoulli.cdf( 0.5 )\nbernoulli.mgf( 3.0 )\nbernoulli.pmf( 0.0 )\nbernoulli.quantile( 0.7 )\n","base.dists.bernoulli.cdf":"var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\ny = base.dists.bernoulli.cdf( 0.8, 0.1 )\ny = base.dists.bernoulli.cdf( -1.0, 0.4 )\ny = base.dists.bernoulli.cdf( 1.5, 0.4 )\ny = base.dists.bernoulli.cdf( NaN, 0.5 )\ny = base.dists.bernoulli.cdf( 0.0, NaN )\ny = base.dists.bernoulli.cdf( 2.0, 1.4 )\n","base.dists.bernoulli.cdf.factory":"var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 0.7 )\n","base.dists.bernoulli.entropy":"var v = base.dists.bernoulli.entropy( 0.1 )\nv = base.dists.bernoulli.entropy( 0.5 )\n","base.dists.bernoulli.kurtosis":"var v = base.dists.bernoulli.kurtosis( 0.1 )\nv = base.dists.bernoulli.kurtosis( 0.5 )\n","base.dists.bernoulli.mean":"var v = base.dists.bernoulli.mean( 0.1 )\nv = base.dists.bernoulli.mean( 0.5 )\n","base.dists.bernoulli.median":"var v = base.dists.bernoulli.median( 0.1 )\nv = base.dists.bernoulli.median( 0.8 )\n","base.dists.bernoulli.mgf":"var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\ny = base.dists.bernoulli.mgf( 0.4, 0.5 )\ny = base.dists.bernoulli.mgf( NaN, 0.0 )\ny = base.dists.bernoulli.mgf( 0.0, NaN )\ny = base.dists.bernoulli.mgf( -2.0, -1.0 )\ny = base.dists.bernoulli.mgf( 0.2, 2.0 )\n","base.dists.bernoulli.mgf.factory":"var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.bernoulli.mode":"var v = base.dists.bernoulli.mode( 0.1 )\nv = base.dists.bernoulli.mode( 0.8 )\n","base.dists.bernoulli.pmf":"var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\ny = base.dists.bernoulli.pmf( 0.0, 0.7 )\ny = base.dists.bernoulli.pmf( -1.0, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, NaN )\ny = base.dists.bernoulli.pmf( NaN, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, 1.5 )\n","base.dists.bernoulli.pmf.factory":"var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\nvar y = mypmf( 1.0 )\ny = mypmf( 0.0 )\n","base.dists.bernoulli.quantile":"var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\ny = base.dists.bernoulli.quantile( 0.5, 0.4 )\ny = base.dists.bernoulli.quantile( 0.9, 0.1 )\ny = base.dists.bernoulli.quantile( -0.2, 0.1 )\ny = base.dists.bernoulli.quantile( NaN, 0.8 )\ny = base.dists.bernoulli.quantile( 0.4, NaN )\ny = base.dists.bernoulli.quantile( 0.5, -1.0 )\ny = base.dists.bernoulli.quantile( 0.5, 1.5 )\n","base.dists.bernoulli.quantile.factory":"var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.bernoulli.skewness":"var v = base.dists.bernoulli.skewness( 0.1 )\nv = base.dists.bernoulli.skewness( 0.5 )\n","base.dists.bernoulli.stdev":"var v = base.dists.bernoulli.stdev( 0.1 )\nv = base.dists.bernoulli.stdev( 0.5 )\n","base.dists.bernoulli.variance":"var v = base.dists.bernoulli.variance( 0.1 )\nv = base.dists.bernoulli.variance( 0.5 )\n","base.dists.beta.Beta":"var beta = base.dists.beta.Beta( 1.0, 1.0 );\nbeta.alpha\nbeta.beta\nbeta.entropy\nbeta.kurtosis\nbeta.mean\nbeta.median\nbeta.mode\nbeta.skewness\nbeta.stdev\nbeta.variance\nbeta.cdf( 0.8 )\nbeta.logcdf( 0.8 )\nbeta.logpdf( 1.0 )\nbeta.mgf( 3.14 )\nbeta.pdf( 1.0 )\nbeta.quantile( 0.8 )\n","base.dists.beta.cdf":"var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.cdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.cdf( 0.0, 1.0, NaN )\n","base.dists.beta.cdf.factory":"var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.beta.entropy":"var v = base.dists.beta.entropy( 1.0, 1.0 )\nv = base.dists.beta.entropy( 4.0, 12.0 )\nv = base.dists.beta.entropy( 8.0, 2.0 )\nv = base.dists.beta.entropy( 1.0, -0.1 )\nv = base.dists.beta.entropy( -0.1, 1.0 )\nv = base.dists.beta.entropy( 2.0, NaN )\nv = base.dists.beta.entropy( NaN, 2.0 )\n","base.dists.beta.kurtosis":"var v = base.dists.beta.kurtosis( 1.0, 1.0 )\nv = base.dists.beta.kurtosis( 4.0, 12.0 )\nv = base.dists.beta.kurtosis( 8.0, 2.0 )\nv = base.dists.beta.kurtosis( 1.0, -0.1 )\nv = base.dists.beta.kurtosis( -0.1, 1.0 )\nv = base.dists.beta.kurtosis( 2.0, NaN )\nv = base.dists.beta.kurtosis( NaN, 2.0 )\n","base.dists.beta.logcdf":"var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n","base.dists.beta.logcdf.factory":"var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.beta.logpdf":"var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n","base.dists.beta.logpdf.factory":"var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.beta.mean":"var v = base.dists.beta.mean( 1.0, 1.0 )\nv = base.dists.beta.mean( 4.0, 12.0 )\nv = base.dists.beta.mean( 8.0, 2.0 )\n","base.dists.beta.median":"var v = base.dists.beta.median( 1.0, 1.0 )\nv = base.dists.beta.median( 4.0, 12.0 )\nv = base.dists.beta.median( 8.0, 2.0 )\nv = base.dists.beta.median( 1.0, -0.1 )\nv = base.dists.beta.median( -0.1, 1.0 )\nv = base.dists.beta.median( 2.0, NaN )\nv = base.dists.beta.median( NaN, 2.0 )\n","base.dists.beta.mgf":"var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\ny = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\ny = base.dists.beta.mgf( NaN, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.0, NaN, 1.0 )\ny = base.dists.beta.mgf( 0.0, 1.0, NaN )\ny = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n","base.dists.beta.mgf.factory":"var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.3 )\n","base.dists.beta.mode":"var v = base.dists.beta.mode( 4.0, 12.0 )\nv = base.dists.beta.mode( 8.0, 2.0 )\nv = base.dists.beta.mode( 1.0, 1.0 )\n","base.dists.beta.pdf":"var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.pdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.pdf( 0.5, 1.0, NaN )\n","base.dists.beta.pdf.factory":"var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.beta.quantile":"var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.beta.quantile( NaN, 1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, NaN, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, NaN )\ny = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n","base.dists.beta.quantile.factory":"var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\ny = myquantile( 0.8 )\ny = myquantile( 0.4 )\n","base.dists.beta.skewness":"var v = base.dists.beta.skewness( 1.0, 1.0 )\nv = base.dists.beta.skewness( 4.0, 12.0 )\nv = base.dists.beta.skewness( 8.0, 2.0 )\nv = base.dists.beta.skewness( 1.0, -0.1 )\nv = base.dists.beta.skewness( -0.1, 1.0 )\nv = base.dists.beta.skewness( 2.0, NaN )\nv = base.dists.beta.skewness( NaN, 2.0 )\n","base.dists.beta.stdev":"var v = base.dists.beta.stdev( 1.0, 1.0 )\nv = base.dists.beta.stdev( 4.0, 12.0 )\nv = base.dists.beta.stdev( 8.0, 2.0 )\nv = base.dists.beta.stdev( 1.0, -0.1 )\nv = base.dists.beta.stdev( -0.1, 1.0 )\nv = base.dists.beta.stdev( 2.0, NaN )\nv = base.dists.beta.stdev( NaN, 2.0 )\n","base.dists.beta.variance":"var v = base.dists.beta.variance( 1.0, 1.0 )\nv = base.dists.beta.variance( 4.0, 12.0 )\nv = base.dists.beta.variance( 8.0, 2.0 )\nv = base.dists.beta.variance( 1.0, -0.1 )\nv = base.dists.beta.variance( -0.1, 1.0 )\nv = base.dists.beta.variance( 2.0, NaN )\nv = base.dists.beta.variance( NaN, 2.0 )\n","base.dists.betaprime.BetaPrime":"var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\nbetaprime.alpha\nbetaprime.beta\nbetaprime.kurtosis\nbetaprime.mean\nbetaprime.mode\nbetaprime.skewness\nbetaprime.stdev\nbetaprime.variance\nbetaprime.cdf( 0.8 )\nbetaprime.logcdf( 0.8 )\nbetaprime.logpdf( 1.0 )\nbetaprime.pdf( 1.0 )\nbetaprime.quantile( 0.8 )\n","base.dists.betaprime.cdf":"var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.cdf.factory":"var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.betaprime.kurtosis":"var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 4.0, 12.0 )\nv = base.dists.betaprime.kurtosis( 8.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 1.0, 2.8 )\nv = base.dists.betaprime.kurtosis( 1.0, -0.1 )\nv = base.dists.betaprime.kurtosis( -0.1, 5.0 )\nv = base.dists.betaprime.kurtosis( 2.0, NaN )\nv = base.dists.betaprime.kurtosis( NaN, 6.0 )\n","base.dists.betaprime.logcdf":"var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.logcdf.factory":"var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.betaprime.logpdf":"var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.logpdf.factory":"var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.betaprime.mean":"var v = base.dists.betaprime.mean( 1.0, 2.0 )\nv = base.dists.betaprime.mean( 4.0, 12.0 )\nv = base.dists.betaprime.mean( 8.0, 2.0 )\n","base.dists.betaprime.mode":"var v = base.dists.betaprime.mode( 1.0, 2.0 )\nv = base.dists.betaprime.mode( 4.0, 12.0 )\nv = base.dists.betaprime.mode( 8.0, 2.0 )\n","base.dists.betaprime.pdf":"var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.pdf.factory":"var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.betaprime.quantile":"var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\ny = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n","base.dists.betaprime.quantile.factory":"var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\ny = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.betaprime.skewness":"var v = base.dists.betaprime.skewness( 2.0, 4.0 )\nv = base.dists.betaprime.skewness( 4.0, 12.0 )\nv = base.dists.betaprime.skewness( 8.0, 4.0 )\nv = base.dists.betaprime.skewness( 1.0, 2.8 )\nv = base.dists.betaprime.skewness( 1.0, -0.1 )\nv = base.dists.betaprime.skewness( -0.1, 4.0 )\nv = base.dists.betaprime.skewness( 2.0, NaN )\nv = base.dists.betaprime.skewness( NaN, 4.0 )\n","base.dists.betaprime.stdev":"var v = base.dists.betaprime.stdev( 1.0, 2.5 )\nv = base.dists.betaprime.stdev( 4.0, 12.0 )\nv = base.dists.betaprime.stdev( 8.0, 2.5 )\nv = base.dists.betaprime.stdev( 8.0, 1.0 )\nv = base.dists.betaprime.stdev( 1.0, -0.1 )\nv = base.dists.betaprime.stdev( -0.1, 3.0 )\nv = base.dists.betaprime.stdev( 2.0, NaN )\nv = base.dists.betaprime.stdev( NaN, 3.0 )\n","base.dists.betaprime.variance":"var v = base.dists.betaprime.variance( 1.0, 2.5 )\nv = base.dists.betaprime.variance( 4.0, 12.0 )\nv = base.dists.betaprime.variance( 8.0, 2.5 )\nv = base.dists.betaprime.variance( 8.0, 1.0 )\nv = base.dists.betaprime.variance( 1.0, -0.1 )\nv = base.dists.betaprime.variance( -0.1, 3.0 )\nv = base.dists.betaprime.variance( 2.0, NaN )\nv = base.dists.betaprime.variance( NaN, 3.0 )\n","base.dists.binomial.Binomial":"var binomial = base.dists.binomial.Binomial( 8, 0.5 );\nbinomial.n\nbinomial.p\nbinomial.kurtosis\nbinomial.mean\nbinomial.median\nbinomial.mode\nbinomial.skewness\nbinomial.stdev\nbinomial.variance\nbinomial.cdf( 2.9 )\nbinomial.logpmf( 3.0 )\nbinomial.mgf( 0.2 )\nbinomial.pmf( 3.0 )\nbinomial.quantile( 0.8 )\n","base.dists.binomial.cdf":"var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 21.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 5.0, 10, 0.4 )\ny = base.dists.binomial.cdf( 0.0, 10, 0.4 )\ny = base.dists.binomial.cdf( NaN, 20, 0.5 )\ny = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.cdf( 0.0, 20, NaN )\ny = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n","base.dists.binomial.cdf.factory":"var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.binomial.entropy":"var v = base.dists.binomial.entropy( 100, 0.1 )\nv = base.dists.binomial.entropy( 20, 0.5 )\nv = base.dists.binomial.entropy( 10.3, 0.5 )\nv = base.dists.binomial.entropy( 20, 1.1 )\nv = base.dists.binomial.entropy( 20, NaN )\n","base.dists.binomial.kurtosis":"var v = base.dists.binomial.kurtosis( 100, 0.1 )\nv = base.dists.binomial.kurtosis( 20, 0.5 )\nv = base.dists.binomial.kurtosis( 10.3, 0.5 )\nv = base.dists.binomial.kurtosis( 20, 1.1 )\nv = base.dists.binomial.kurtosis( 20, NaN )\n","base.dists.binomial.logpmf":"var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( NaN, 20, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, 20, NaN )\ny = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n","base.dists.binomial.logpmf.factory":"var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 5.0 )\n","base.dists.binomial.mean":"var v = base.dists.binomial.mean( 100, 0.1 )\nv = base.dists.binomial.mean( 20, 0.5 )\nv = base.dists.binomial.mean( 10.3, 0.5 )\nv = base.dists.binomial.mean( 20, 1.1 )\nv = base.dists.binomial.mean( 20, NaN )\n","base.dists.binomial.median":"var v = base.dists.binomial.median( 100, 0.1 )\nv = base.dists.binomial.median( 20, 0.5 )\nv = base.dists.binomial.median( 10.3, 0.5 )\nv = base.dists.binomial.median( 20, 1.1 )\nv = base.dists.binomial.median( 20, NaN )\n","base.dists.binomial.mgf":"var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\ny = base.dists.binomial.mgf( 5.0, 20, 0.2 )\ny = base.dists.binomial.mgf( 0.9, 10, 0.4 )\ny = base.dists.binomial.mgf( 0.0, 10, 0.4 )\ny = base.dists.binomial.mgf( NaN, 20, 0.5 )\ny = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.mgf( 0.0, 20, NaN )\ny = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.mgf( 2.0, 20, -1.0 )\ny = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n","base.dists.binomial.mgf.factory":"var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\nvar y = myMGF( 0.3 )\n","base.dists.binomial.mode":"var v = base.dists.binomial.mode( 100, 0.1 )\nv = base.dists.binomial.mode( 20, 0.5 )\nv = base.dists.binomial.mode( 10.3, 0.5 )\nv = base.dists.binomial.mode( 20, 1.1 )\nv = base.dists.binomial.mode( 20, NaN )\n","base.dists.binomial.pmf":"var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.pmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.pmf( NaN, 20, 0.5 )\ny = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.pmf( 0.0, 20, NaN )\ny = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n","base.dists.binomial.pmf.factory":"var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 5.0 )\n","base.dists.binomial.quantile":"var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.8, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.5, 10, 0.4 )\ny = base.dists.binomial.quantile( 0.0, 10, 0.4 )\ny = base.dists.binomial.quantile( 1.0, 10, 0.4 )\ny = base.dists.binomial.quantile( NaN, 20, 0.5 )\ny = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\ny = base.dists.binomial.quantile( 0.2, 20, NaN )\ny = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\ny = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.binomial.quantile( 0.5, 20, -1.0 )\ny = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n","base.dists.binomial.quantile.factory":"var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\nvar y = myquantile( 0.1 )\ny = myquantile( 0.9 )\n","base.dists.binomial.skewness":"var v = base.dists.binomial.skewness( 100, 0.1 )\nv = base.dists.binomial.skewness( 20, 0.5 )\nv = base.dists.binomial.skewness( 10.3, 0.5 )\nv = base.dists.binomial.skewness( 20, 1.1 )\nv = base.dists.binomial.skewness( 20, NaN )\n","base.dists.binomial.stdev":"var v = base.dists.binomial.stdev( 100, 0.1 )\nv = base.dists.binomial.stdev( 20, 0.5 )\nv = base.dists.binomial.stdev( 10.3, 0.5 )\nv = base.dists.binomial.stdev( 20, 1.1 )\nv = base.dists.binomial.stdev( 20, NaN )\n","base.dists.binomial.variance":"var v = base.dists.binomial.variance( 100, 0.1 )\nv = base.dists.binomial.variance( 20, 0.5 )\nv = base.dists.binomial.variance( 10.3, 0.5 )\nv = base.dists.binomial.variance( 20, 1.1 )\nv = base.dists.binomial.variance( 20, NaN )\n","base.dists.cauchy.Cauchy":"var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\ncauchy.x0\ncauchy.gamma\ncauchy.entropy\ncauchy.median\ncauchy.mode\ncauchy.cdf( 0.8 )\ncauchy.logcdf( 1.0 )\ncauchy.logpdf( 1.0 )\ncauchy.pdf( 1.0 )\ncauchy.quantile( 0.8 )\n","base.dists.cauchy.cdf":"var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.cdf.factory":"var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\nvar y = myCDF( 1.0 )\n","base.dists.cauchy.entropy":"var v = base.dists.cauchy.entropy( 10.0, 7.0 )\nv = base.dists.cauchy.entropy( 22.0, 0.5 )\nv = base.dists.cauchy.entropy( 10.3, -0.5 )\n","base.dists.cauchy.logcdf":"var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.logcdf.factory":"var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\nvar y = mylogCDF( 1.0 )\n","base.dists.cauchy.logpdf":"var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.logpdf.factory":"var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.cauchy.median":"var v = base.dists.cauchy.median( 10.0, 5.0 )\nv = base.dists.cauchy.median( 7.0, 0.5 )\nv = base.dists.cauchy.median( 10.3, -0.5 )\n","base.dists.cauchy.mode":"var v = base.dists.cauchy.mode( 10.0, 5.0 )\nv = base.dists.cauchy.mode( 7.0, 0.5 )\nv = base.dists.cauchy.mode( 10.3, -0.5 )\n","base.dists.cauchy.pdf":"var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.pdf.factory":"var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.cauchy.quantile":"var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\ny = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\ny = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\ny = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\ny = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cauchy.quantile.factory":"var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.chi.cdf":"var y = base.dists.chi.cdf( 2.0, 3.0 )\ny = base.dists.chi.cdf( 1.0, 0.5 )\ny = base.dists.chi.cdf( -1.0, 4.0 )\ny = base.dists.chi.cdf( NaN, 1.0 )\ny = base.dists.chi.cdf( 0.0, NaN )\ny = base.dists.chi.cdf( 2.0, -1.0 )\ny = base.dists.chi.cdf( 2.0, 0.0 )\ny = base.dists.chi.cdf( -2.0, 0.0 )\ny = base.dists.chi.cdf( 0.0, 0.0 )\n","base.dists.chi.cdf.factory":"var mycdf = base.dists.chi.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chi.Chi":"var chi = base.dists.chi.Chi( 6.0 );\nchi.k\nchi.entropy\nchi.kurtosis\nchi.mean\nchi.mode\nchi.skewness\nchi.stdev\nchi.variance\nchi.cdf( 1.0 )\nchi.logpdf( 1.5 )\nchi.pdf( 1.5 )\nchi.quantile( 0.5 )\n","base.dists.chi.entropy":"var v = base.dists.chi.entropy( 11.0 )\nv = base.dists.chi.entropy( 1.5 )\n","base.dists.chi.kurtosis":"var v = base.dists.chi.kurtosis( 9.0 )\nv = base.dists.chi.kurtosis( 1.5 )\n","base.dists.chi.logpdf":"var y = base.dists.chi.logpdf( 0.3, 4.0 )\ny = base.dists.chi.logpdf( 0.7, 0.7 )\ny = base.dists.chi.logpdf( -1.0, 0.5 )\ny = base.dists.chi.logpdf( 0.0, NaN )\ny = base.dists.chi.logpdf( NaN, 2.0 )\ny = base.dists.chi.logpdf( 2.0, -1.0 )\ny = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.logpdf.factory":"var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\nvar y = mylogPDF( 3.0 )\n","base.dists.chi.mean":"var v = base.dists.chi.mean( 11.0 )\nv = base.dists.chi.mean( 4.5 )\n","base.dists.chi.mode":"var v = base.dists.chi.mode( 11.0 )\nv = base.dists.chi.mode( 1.5 )\n","base.dists.chi.pdf":"var y = base.dists.chi.pdf( 0.3, 4.0 )\ny = base.dists.chi.pdf( 0.7, 0.7 )\ny = base.dists.chi.pdf( -1.0, 0.5 )\ny = base.dists.chi.pdf( 0.0, NaN )\ny = base.dists.chi.pdf( NaN, 2.0 )\ny = base.dists.chi.pdf( 2.0, -1.0 )\ny = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.pdf.factory":"var myPDF = base.dists.chi.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chi.quantile":"var y = base.dists.chi.quantile( 0.8, 1.0 )\ny = base.dists.chi.quantile( 0.5, 4.0 )\ny = base.dists.chi.quantile( 0.8, 0.1 )\ny = base.dists.chi.quantile( -0.2, 0.5 )\ny = base.dists.chi.quantile( 1.1, 0.5 )\ny = base.dists.chi.quantile( NaN, 1.0 )\ny = base.dists.chi.quantile( 0.0, NaN )\ny = base.dists.chi.quantile( 0.5, -1.0 )\ny = base.dists.chi.quantile( 0.3, 0.0 )\ny = base.dists.chi.quantile( 0.9, 0.0 )\n","base.dists.chi.quantile.factory":"var myquantile = base.dists.chi.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chi.skewness":"var v = base.dists.chi.skewness( 11.0 )\nv = base.dists.chi.skewness( 1.5 )\n","base.dists.chi.stdev":"var v = base.dists.chi.stdev( 11.0 )\nv = base.dists.chi.stdev( 1.5 )\n","base.dists.chi.variance":"var v = base.dists.chi.variance( 11.0 )\nv = base.dists.chi.variance( 1.5 )\n","base.dists.chisquare.cdf":"var y = base.dists.chisquare.cdf( 2.0, 3.0 )\ny = base.dists.chisquare.cdf( 1.0, 0.5 )\ny = base.dists.chisquare.cdf( -1.0, 4.0 )\ny = base.dists.chisquare.cdf( NaN, 1.0 )\ny = base.dists.chisquare.cdf( 0.0, NaN )\ny = base.dists.chisquare.cdf( 2.0, -1.0 )\ny = base.dists.chisquare.cdf( 2.0, 0.0 )\ny = base.dists.chisquare.cdf( -2.0, 0.0 )\ny = base.dists.chisquare.cdf( 0.0, 0.0 )\n","base.dists.chisquare.cdf.factory":"var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chisquare.ChiSquare":"var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\nchisquare.k\nchisquare.entropy\nchisquare.kurtosis\nchisquare.mean\nchisquare.median\nchisquare.mode\nchisquare.skewness\nchisquare.stdev\nchisquare.variance\nchisquare.cdf( 3.0 )\nchisquare.mgf( 0.2 )\nchisquare.pdf( 1.5 )\nchisquare.quantile( 0.5 )\n","base.dists.chisquare.entropy":"var v = base.dists.chisquare.entropy( 11.0 )\nv = base.dists.chisquare.entropy( 1.5 )\n","base.dists.chisquare.kurtosis":"var v = base.dists.chisquare.kurtosis( 9.0 )\nv = base.dists.chisquare.kurtosis( 1.5 )\n","base.dists.chisquare.logpdf":"var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\ny = base.dists.chisquare.logpdf( 0.7, 0.7 )\ny = base.dists.chisquare.logpdf( -1.0, 0.5 )\ny = base.dists.chisquare.logpdf( 0.0, NaN )\ny = base.dists.chisquare.logpdf( NaN, 2.0 )\ny = base.dists.chisquare.logpdf( 2.0, -1.0 )\ny = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.logpdf.factory":"var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\nvar y = myLogPDF( 3.0 )\n","base.dists.chisquare.mean":"var v = base.dists.chisquare.mean( 11.0 )\nv = base.dists.chisquare.mean( 4.5 )\n","base.dists.chisquare.median":"var k = base.dists.chisquare.median( 9.0 )\nk = base.dists.chisquare.median( 2.0 )\n","base.dists.chisquare.mgf":"var y = base.dists.chisquare.mgf( 0.4, 2 )\ny = base.dists.chisquare.mgf( -1.0, 5.0 )\ny = base.dists.chisquare.mgf( 0.0, 10.0 )\n","base.dists.chisquare.mgf.factory":"var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.chisquare.mode":"var v = base.dists.chisquare.mode( 11.0 )\nv = base.dists.chisquare.mode( 1.5 )\n","base.dists.chisquare.pdf":"var y = base.dists.chisquare.pdf( 0.3, 4.0 )\ny = base.dists.chisquare.pdf( 0.7, 0.7 )\ny = base.dists.chisquare.pdf( -1.0, 0.5 )\ny = base.dists.chisquare.pdf( 0.0, NaN )\ny = base.dists.chisquare.pdf( NaN, 2.0 )\ny = base.dists.chisquare.pdf( 2.0, -1.0 )\ny = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.pdf.factory":"var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chisquare.quantile":"var y = base.dists.chisquare.quantile( 0.8, 1.0 )\ny = base.dists.chisquare.quantile( 0.5, 4.0 )\ny = base.dists.chisquare.quantile( 0.8, 0.1 )\ny = base.dists.chisquare.quantile( -0.2, 0.5 )\ny = base.dists.chisquare.quantile( 1.1, 0.5 )\ny = base.dists.chisquare.quantile( NaN, 1.0 )\ny = base.dists.chisquare.quantile( 0.0, NaN )\ny = base.dists.chisquare.quantile( 0.5, -1.0 )\ny = base.dists.chisquare.quantile( 0.3, 0.0 )\ny = base.dists.chisquare.quantile( 0.9, 0.0 )\n","base.dists.chisquare.quantile.factory":"var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chisquare.skewness":"var v = base.dists.chisquare.skewness( 11.0 )\nv = base.dists.chisquare.skewness( 1.5 )\n","base.dists.chisquare.stdev":"var v = base.dists.chisquare.stdev( 11.0 )\nv = base.dists.chisquare.stdev( 1.5 )\n","base.dists.chisquare.variance":"var v = base.dists.chisquare.variance( 11.0 )\nv = base.dists.chisquare.variance( 1.5 )\n","base.dists.cosine.cdf":"var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.cdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.cdf.factory":"var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.9 )\n","base.dists.cosine.Cosine":"var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\ncosine.mu\ncosine.s\ncosine.kurtosis\ncosine.mean\ncosine.median\ncosine.mode\ncosine.skewness\ncosine.stdev\ncosine.variance\ncosine.cdf( 0.5 )\ncosine.logcdf( 0.5 )\ncosine.logpdf( -1.0 )\ncosine.mgf( 0.2 )\ncosine.pdf( -2.0 )\ncosine.quantile( 0.9 )\n","base.dists.cosine.kurtosis":"var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\ny = base.dists.cosine.kurtosis( 4.0, 2.0 )\ny = base.dists.cosine.kurtosis( NaN, 1.0 )\ny = base.dists.cosine.kurtosis( 0.0, NaN )\ny = base.dists.cosine.kurtosis( 0.0, 0.0 )\n","base.dists.cosine.logcdf":"var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.logcdf.factory":"var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.9 )\n","base.dists.cosine.logpdf":"var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\ny = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.logpdf.factory":"var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.cosine.mean":"var y = base.dists.cosine.mean( 0.0, 1.0 )\ny = base.dists.cosine.mean( 4.0, 2.0 )\ny = base.dists.cosine.mean( NaN, 1.0 )\ny = base.dists.cosine.mean( 0.0, NaN )\ny = base.dists.cosine.mean( 0.0, 0.0 )\n","base.dists.cosine.median":"var y = base.dists.cosine.median( 0.0, 1.0 )\ny = base.dists.cosine.median( 4.0, 2.0 )\ny = base.dists.cosine.median( NaN, 1.0 )\ny = base.dists.cosine.median( 0.0, NaN )\ny = base.dists.cosine.median( 0.0, 0.0 )\n","base.dists.cosine.mgf":"var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.mgf( 0.5, 0.0, NaN )\ny = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\ny = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n","base.dists.cosine.mgf.factory":"var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\nvar y = mymgf( 1.9 )\n","base.dists.cosine.mode":"var y = base.dists.cosine.mode( 0.0, 1.0 )\ny = base.dists.cosine.mode( 4.0, 2.0 )\ny = base.dists.cosine.mode( NaN, 1.0 )\ny = base.dists.cosine.mode( 0.0, NaN )\ny = base.dists.cosine.mode( 0.0, 0.0 )\n","base.dists.cosine.pdf":"var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\ny = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.pdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.pdf.factory":"var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\nvar y = myPDF( 2.0 )\n","base.dists.cosine.quantile":"var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cosine.quantile( 0.0, 0.0, NaN )\ny = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cosine.quantile.factory":"var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.3 )\n","base.dists.cosine.skewness":"var y = base.dists.cosine.skewness( 0.0, 1.0 )\ny = base.dists.cosine.skewness( 4.0, 2.0 )\ny = base.dists.cosine.skewness( NaN, 1.0 )\ny = base.dists.cosine.skewness( 0.0, NaN )\ny = base.dists.cosine.skewness( 0.0, 0.0 )\n","base.dists.cosine.stdev":"var y = base.dists.cosine.stdev( 0.0, 1.0 )\ny = base.dists.cosine.stdev( 4.0, 2.0 )\ny = base.dists.cosine.stdev( NaN, 1.0 )\ny = base.dists.cosine.stdev( 0.0, NaN )\ny = base.dists.cosine.stdev( 0.0, 0.0 )\n","base.dists.cosine.variance":"var y = base.dists.cosine.variance( 0.0, 1.0 )\ny = base.dists.cosine.variance( 4.0, 2.0 )\ny = base.dists.cosine.variance( NaN, 1.0 )\ny = base.dists.cosine.variance( 0.0, NaN )\ny = base.dists.cosine.variance( 0.0, 0.0 )\n","base.dists.degenerate.cdf":"var y = base.dists.degenerate.cdf( 2.0, 3.0 )\ny = base.dists.degenerate.cdf( 4.0, 3.0 )\ny = base.dists.degenerate.cdf( 3.0, 3.0 )\ny = base.dists.degenerate.cdf( NaN, 0.0 )\ny = base.dists.degenerate.cdf( 0.0, NaN )\n","base.dists.degenerate.cdf.factory":"var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 6.0 )\n","base.dists.degenerate.Degenerate":"var degenerate = base.dists.degenerate.Degenerate( 2.0 );\ndegenerate.mu\ndegenerate.entropy\ndegenerate.mean\ndegenerate.mode\ndegenerate.median\ndegenerate.stdev\ndegenerate.variance\ndegenerate.cdf( 0.5 )\ndegenerate.logcdf( 2.5 )\ndegenerate.logpdf( 0.5 )\ndegenerate.logpmf( 2.5 )\ndegenerate.mgf( 0.2 )\ndegenerate.pdf( 2.0 )\ndegenerate.pmf( 2.0 )\ndegenerate.quantile( 0.7 )\n","base.dists.degenerate.entropy":"var v = base.dists.degenerate.entropy( 20.0 )\nv = base.dists.degenerate.entropy( -10.0 )\n","base.dists.degenerate.logcdf":"var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\ny = base.dists.degenerate.logcdf( 4.0, 3.0 )\ny = base.dists.degenerate.logcdf( 3.0, 3.0 )\ny = base.dists.degenerate.logcdf( NaN, 0.0 )\ny = base.dists.degenerate.logcdf( 0.0, NaN )\n","base.dists.degenerate.logcdf.factory":"var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 6.0 )\n","base.dists.degenerate.logpdf":"var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\ny = base.dists.degenerate.logpdf( 3.0, 3.0 )\ny = base.dists.degenerate.logpdf( NaN, 0.0 )\ny = base.dists.degenerate.logpdf( 0.0, NaN )\n","base.dists.degenerate.logpdf.factory":"var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.degenerate.logpmf":"var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\ny = base.dists.degenerate.logpmf( 3.0, 3.0 )\ny = base.dists.degenerate.logpmf( NaN, 0.0 )\ny = base.dists.degenerate.logpmf( 0.0, NaN )\n","base.dists.degenerate.logpmf.factory":"var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\nvar y = mylogPMF( 10.0 )\n","base.dists.degenerate.mean":"var v = base.dists.degenerate.mean( 20.0 )\nv = base.dists.degenerate.mean( -10.0 )\n","base.dists.degenerate.median":"var v = base.dists.degenerate.median( 20.0 )\nv = base.dists.degenerate.median( -10.0 )\n","base.dists.degenerate.mgf":"var y = base.dists.degenerate.mgf( 1.0, 1.0 )\ny = base.dists.degenerate.mgf( 2.0, 3.0 )\ny = base.dists.degenerate.mgf( NaN, 0.0 )\ny = base.dists.degenerate.mgf( 0.0, NaN )\n","base.dists.degenerate.mgf.factory":"var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\nvar y = myMGF( 0.1 )\n","base.dists.degenerate.mode":"var v = base.dists.degenerate.mode( 20.0 )\nv = base.dists.degenerate.mode( -10.0 )\n","base.dists.degenerate.pdf":"var y = base.dists.degenerate.pdf( 2.0, 3.0 )\ny = base.dists.degenerate.pdf( 3.0, 3.0 )\ny = base.dists.degenerate.pdf( NaN, 0.0 )\ny = base.dists.degenerate.pdf( 0.0, NaN )\n","base.dists.degenerate.pdf.factory":"var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\nvar y = myPDF( 10.0 )\n","base.dists.degenerate.pmf":"var y = base.dists.degenerate.pmf( 2.0, 3.0 )\ny = base.dists.degenerate.pmf( 3.0, 3.0 )\ny = base.dists.degenerate.pmf( NaN, 0.0 )\ny = base.dists.degenerate.pmf( 0.0, NaN )\n","base.dists.degenerate.pmf.factory":"var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\nvar y = myPMF( 10.0 )\n","base.dists.degenerate.quantile":"var y = base.dists.degenerate.quantile( 0.5, 2.0 )\ny = base.dists.degenerate.quantile( 0.9, 4.0 )\ny = base.dists.degenerate.quantile( 1.1, 0.0 )\ny = base.dists.degenerate.quantile( -0.2, 0.0 )\ny = base.dists.degenerate.quantile( NaN, 0.0 )\ny = base.dists.degenerate.quantile( 0.0, NaN )\n","base.dists.degenerate.quantile.factory":"var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.degenerate.stdev":"var v = base.dists.degenerate.stdev( 20.0 )\nv = base.dists.degenerate.stdev( -10.0 )\n","base.dists.degenerate.variance":"var v = base.dists.degenerate.variance( 20.0 )\nv = base.dists.degenerate.variance( -10.0 )\n","base.dists.discreteUniform.cdf":"var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.cdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.cdf.factory":"var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.discreteUniform.DiscreteUniform":"var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\ndiscreteUniform.a\ndiscreteUniform.b\ndiscreteUniform.entropy\ndiscreteUniform.kurtosis\ndiscreteUniform.mean\ndiscreteUniform.median\ndiscreteUniform.skewness\ndiscreteUniform.stdev\ndiscreteUniform.variance\ndiscreteUniform.cdf( 0.8 )\ndiscreteUniform.logcdf( 0.5 )\ndiscreteUniform.logpmf( 1.0 )\ndiscreteUniform.mgf( 0.8 )\ndiscreteUniform.pmf( 0.0 )\ndiscreteUniform.quantile( 0.8 )\n","base.dists.discreteUniform.entropy":"var v = base.dists.discreteUniform.entropy( 0, 1 )\nv = base.dists.discreteUniform.entropy( 4, 12 )\nv = base.dists.discreteUniform.entropy( 2, 8 )\n","base.dists.discreteUniform.kurtosis":"var v = base.dists.discreteUniform.kurtosis( 0, 1 )\nv = base.dists.discreteUniform.kurtosis( 4, 12 )\nv = base.dists.discreteUniform.kurtosis( -4, 8 )\n","base.dists.discreteUniform.logcdf":"var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.logcdf.factory":"var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\nvar y = myLogCDF( 0.5 )\ny = myLogCDF( 8.0 )\n","base.dists.discreteUniform.logpmf":"var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.logpmf.factory":"var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\nvar y = myLogPMF( 7.0 )\ny = myLogPMF( 5.0 )\n","base.dists.discreteUniform.mean":"var v = base.dists.discreteUniform.mean( -2, 2 )\nv = base.dists.discreteUniform.mean( 4, 12 )\nv = base.dists.discreteUniform.mean( 2, 8 )\n","base.dists.discreteUniform.median":"var v = base.dists.discreteUniform.median( -2, 2 )\nv = base.dists.discreteUniform.median( 4, 12 )\nv = base.dists.discreteUniform.median( 2, 8 )\n","base.dists.discreteUniform.mgf":"var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\ny = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\ny = base.dists.discreteUniform.mgf( NaN, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n","base.dists.discreteUniform.mgf.factory":"var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.discreteUniform.pmf":"var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.pmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.pmf.factory":"var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\nvar y = myPMF( 7.0 )\ny = myPMF( 5.0 )\n","base.dists.discreteUniform.quantile":"var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\ny = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\ny = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\ny = base.dists.discreteUniform.quantile( NaN, -2, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\ny = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n","base.dists.discreteUniform.quantile.factory":"var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\nvar y = myQuantile( 0.8 )\n","base.dists.discreteUniform.skewness":"var v = base.dists.discreteUniform.skewness( -2, 2 )\nv = base.dists.discreteUniform.skewness( 4, 12 )\nv = base.dists.discreteUniform.skewness( 2, 8 )\n","base.dists.discreteUniform.stdev":"var v = base.dists.discreteUniform.stdev( 0, 1 )\nv = base.dists.discreteUniform.stdev( 4, 12 )\nv = base.dists.discreteUniform.stdev( 2, 8 )\n","base.dists.discreteUniform.variance":"var v = base.dists.discreteUniform.variance( 0, 1 )\nv = base.dists.discreteUniform.variance( 4, 12 )\nv = base.dists.discreteUniform.variance( 2, 8 )\n","base.dists.erlang.cdf":"var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 3, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\ny = base.dists.erlang.cdf( -1.0, 2, 2.0 )\ny = base.dists.erlang.cdf( PINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NaN, 0, 1.0 )\ny = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.cdf( 0.0, 0, NaN )\ny = base.dists.erlang.cdf( 2.0, -1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n","base.dists.erlang.cdf.factory":"var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\nvar y = mycdf( 6.0 )\ny = mycdf( 2.0 )\n","base.dists.erlang.entropy":"var v = base.dists.erlang.entropy( 1, 1.0 )\nv = base.dists.erlang.entropy( 4, 12.0 )\nv = base.dists.erlang.entropy( 8, 2.0 )\n","base.dists.erlang.Erlang":"var erlang = base.dists.erlang.Erlang( 6, 5.0 );\nerlang.k\nerlang.lambda\nerlang.entropy\nerlang.kurtosis\nerlang.mean\nerlang.mode\nerlang.skewness\nerlang.stdev\nerlang.variance\nerlang.cdf( 3.0 )\nerlang.logpdf( 3.0 )\nerlang.mgf( -0.5 )\nerlang.pdf( 3.0 )\nerlang.quantile( 0.8 )\n","base.dists.erlang.kurtosis":"var v = base.dists.erlang.kurtosis( 1, 1.0 )\nv = base.dists.erlang.kurtosis( 4, 12.0 )\nv = base.dists.erlang.kurtosis( 8, 2.0 )\n","base.dists.erlang.logpdf":"var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.logpdf( NaN, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, 1, NaN )\ny = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n","base.dists.erlang.logpdf.factory":"var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\ny = myLogPDF( 7.0 )\n","base.dists.erlang.mean":"var v = base.dists.erlang.mean( 1, 1.0 )\nv = base.dists.erlang.mean( 4, 12.0 )\nv = base.dists.erlang.mean( 8, 2.0 )\n","base.dists.erlang.mgf":"var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\ny = base.dists.erlang.mgf( 2.0, 2, 3.0 )\ny = base.dists.erlang.mgf( -1.0, 2, 2.0 )\ny = base.dists.erlang.mgf( NaN, 1, 1.0 )\ny = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.mgf( 0.0, 1, NaN )\ny = base.dists.erlang.mgf( 0.2, -2, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 1, 0.0 )\ny = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n","base.dists.erlang.mgf.factory":"var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\nvar y = myMGF( 0.2 )\ny = myMGF( -0.5 )\n","base.dists.erlang.mode":"var v = base.dists.erlang.mode( 1, 1.0 )\nv = base.dists.erlang.mode( 4, 12.0 )\nv = base.dists.erlang.mode( 8, 2.0 )\n","base.dists.erlang.pdf":"var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.pdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.pdf( NaN, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.pdf( 0.0, 1, NaN )\ny = base.dists.erlang.pdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n","base.dists.erlang.pdf.factory":"var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\ny = myPDF( 7.0 )\n","base.dists.erlang.quantile":"var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 4, 2.0 )\ny = base.dists.erlang.quantile( 1.1, 1, 1.0 )\ny = base.dists.erlang.quantile( -0.2, 1, 1.0 )\ny = base.dists.erlang.quantile( NaN, 1, 1.0 )\ny = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\ny = base.dists.erlang.quantile( 0.0, 1, NaN )\ny = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\ny = base.dists.erlang.quantile( 0.5, -1, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n","base.dists.erlang.quantile.factory":"var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.erlang.skewness":"var v = base.dists.erlang.skewness( 1, 1.0 )\nv = base.dists.erlang.skewness( 4, 12.0 )\nv = base.dists.erlang.skewness( 8, 2.0 )\n","base.dists.erlang.stdev":"var v = base.dists.erlang.stdev( 1, 1.0 )\nv = base.dists.erlang.stdev( 4, 12.0 )\nv = base.dists.erlang.stdev( 8, 2.0 )\n","base.dists.erlang.variance":"var v = base.dists.erlang.variance( 1, 1.0 )\nv = base.dists.erlang.variance( 4, 12.0 )\nv = base.dists.erlang.variance( 8, 2.0 )\n","base.dists.exponential.cdf":"var y = base.dists.exponential.cdf( 2.0, 0.1 )\ny = base.dists.exponential.cdf( 1.0, 2.0 )\ny = base.dists.exponential.cdf( -1.0, 4.0 )\ny = base.dists.exponential.cdf( NaN, 1.0 )\ny = base.dists.exponential.cdf( 0.0, NaN )\ny = base.dists.exponential.cdf( 2.0, -1.0 )\n","base.dists.exponential.cdf.factory":"var myCDF = base.dists.exponential.cdf.factory( 0.5 );\nvar y = myCDF( 3.0 )\n","base.dists.exponential.entropy":"var v = base.dists.exponential.entropy( 11.0 )\nv = base.dists.exponential.entropy( 4.5 )\n","base.dists.exponential.Exponential":"var exponential = base.dists.exponential.Exponential( 6.0 );\nexponential.lambda\nexponential.entropy\nexponential.kurtosis\nexponential.mean\nexponential.median\nexponential.mode\nexponential.skewness\nexponential.stdev\nexponential.variance\nexponential.cdf( 1.0 )\nexponential.logcdf( 1.0 )\nexponential.logpdf( 1.5 )\nexponential.mgf( -0.5 )\nexponential.pdf( 1.5 )\nexponential.quantile( 0.5 )\n","base.dists.exponential.kurtosis":"var v = base.dists.exponential.kurtosis( 11.0 )\nv = base.dists.exponential.kurtosis( 4.5 )\n","base.dists.exponential.logcdf":"var y = base.dists.exponential.logcdf( 2.0, 0.1 )\ny = base.dists.exponential.logcdf( 1.0, 2.0 )\ny = base.dists.exponential.logcdf( -1.0, 4.0 )\ny = base.dists.exponential.logcdf( NaN, 1.0 )\ny = base.dists.exponential.logcdf( 0.0, NaN )\ny = base.dists.exponential.logcdf( 2.0, -1.0 )\n","base.dists.exponential.logcdf.factory":"var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\nvar y = mylogCDF( 3.0 )\n","base.dists.exponential.logpdf":"var y = base.dists.exponential.logpdf( 0.3, 4.0 )\ny = base.dists.exponential.logpdf( 2.0, 0.7 )\ny = base.dists.exponential.logpdf( -1.0, 0.5 )\ny = base.dists.exponential.logpdf( 0, NaN )\ny = base.dists.exponential.logpdf( NaN, 2.0 )\ny = base.dists.exponential.logpdf( 2.0, -1.0 )\n","base.dists.exponential.logpdf.factory":"var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\nvar y = mylogpdf( 3.0 )\n","base.dists.exponential.mean":"var v = base.dists.exponential.mean( 11.0 )\nv = base.dists.exponential.mean( 4.5 )\n","base.dists.exponential.median":"var v = base.dists.exponential.median( 11.0 )\nv = base.dists.exponential.median( 4.5 )\n","base.dists.exponential.mgf":"var v = base.dists.exponential.mgf( 2.0, 3.0 )\nv = base.dists.exponential.mgf( 0.4, 1.2 )\nv = base.dists.exponential.mgf( 0.8, 1.6 )\nv = base.dists.exponential.mgf( 4.0, 3.0 )\nv = base.dists.exponential.mgf( NaN, 3.0 )\nv = base.dists.exponential.mgf( 2.0, NaN )\n","base.dists.exponential.mgf.factory":"var myMGF = base.dists.exponential.mgf.factory( 4.0 );\nvar y = myMGF( 3.0 )\ny = myMGF( 0.5 )\n","base.dists.exponential.mode":"var v = base.dists.exponential.mode( 11.0 )\nv = base.dists.exponential.mode( 4.5 )\n","base.dists.exponential.pdf":"var y = base.dists.exponential.pdf( 0.3, 4.0 )\ny = base.dists.exponential.pdf( 2.0, 0.7 )\ny = base.dists.exponential.pdf( -1.0, 0.5 )\ny = base.dists.exponential.pdf( 0, NaN )\ny = base.dists.exponential.pdf( NaN, 2.0 )\ny = base.dists.exponential.pdf( 2.0, -1.0 )\n","base.dists.exponential.pdf.factory":"var myPDF = base.dists.exponential.pdf.factory( 0.5 );\nvar y = myPDF( 3.0 )\n","base.dists.exponential.quantile":"var y = base.dists.exponential.quantile( 0.8, 1.0 )\ny = base.dists.exponential.quantile( 0.5, 4.0 )\ny = base.dists.exponential.quantile( 0.5, 0.1 )\ny = base.dists.exponential.quantile( -0.2, 0.1 )\ny = base.dists.exponential.quantile( NaN, 1.0 )\ny = base.dists.exponential.quantile( 0.0, NaN )\ny = base.dists.exponential.quantile( 0.5, -1.0 )\n","base.dists.exponential.quantile.factory":"var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.exponential.skewness":"var v = base.dists.exponential.skewness( 11.0 )\nv = base.dists.exponential.skewness( 4.5 )\n","base.dists.exponential.stdev":"var v = base.dists.exponential.stdev( 9.0 )\nv = base.dists.exponential.stdev( 1.0 )\n","base.dists.exponential.variance":"var v = base.dists.exponential.variance( 9.0 )\nv = base.dists.exponential.variance( 1.0 )\n","base.dists.f.cdf":"var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\nvar y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\nvar y = base.dists.f.cdf( PINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NaN, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 0.0, NaN, 1.0 )\nvar y = base.dists.f.cdf( 0.0, 1.0, NaN )\nvar y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\nvar y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n","base.dists.f.cdf.factory":"var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 8.0 )\n","base.dists.f.entropy":"var v = base.dists.f.entropy( 3.0, 7.0 )\nv = base.dists.f.entropy( 4.0, 12.0 )\nv = base.dists.f.entropy( 8.0, 2.0 )\n","base.dists.f.F":"var f = base.dists.f.F( 6.0, 9.0 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myPDF( 2.0 )\n","base.dists.f.quantile":"var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.f.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.f.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.f.quantile( NaN, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, NaN, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, NaN )\ny = base.dists.f.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n","base.dists.f.quantile.factory":"var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.f.skewness":"var v = base.dists.f.skewness( 3.0, 7.0 )\nv = base.dists.f.skewness( 4.0, 12.0 )\nv = base.dists.f.skewness( 8.0, 7.0 )\n","base.dists.f.stdev":"var v = base.dists.f.stdev( 3.0, 5.0 )\nv = base.dists.f.stdev( 4.0, 12.0 )\nv = base.dists.f.stdev( 8.0, 5.0 )\n","base.dists.f.variance":"var v = base.dists.f.variance( 3.0, 5.0 )\nv = base.dists.f.variance( 4.0, 12.0 )\nv = 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NaN )\n","base.dists.gamma.cdf":"var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.cdf.factory":"var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 6.0 )\ny = myCDF( 2.0 )\n","base.dists.gamma.entropy":"var v = base.dists.gamma.entropy( 1.0, 1.0 )\nv = base.dists.gamma.entropy( 4.0, 12.0 )\nv = base.dists.gamma.entropy( 8.0, 2.0 )\n","base.dists.gamma.Gamma":"var gamma = base.dists.gamma.Gamma( 6.0, 5.0 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base.dists.gamma.mgf( 0.0, 1.0, NaN )\ny = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\ny = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.mgf.factory":"var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.gamma.mode":"var v = base.dists.gamma.mode( 1.0, 1.0 )\nv = base.dists.gamma.mode( 4.0, 12.0 )\nv = base.dists.gamma.mode( 8.0, 2.0 )\n","base.dists.gamma.pdf":"var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.pdf.factory":"var myPDF = 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base.dists.gamma.stdev( 1.0, 1.0 )\nv = base.dists.gamma.stdev( 4.0, 12.0 )\nv = base.dists.gamma.stdev( 8.0, 2.0 )\n","base.dists.gamma.variance":"var v = base.dists.gamma.variance( 1.0, 1.0 )\nv = base.dists.gamma.variance( 4.0, 12.0 )\nv = base.dists.gamma.variance( 8.0, 2.0 )\n","base.dists.geometric.cdf":"var y = base.dists.geometric.cdf( 2.0, 0.5 )\ny = base.dists.geometric.cdf( 2.0, 0.1 )\ny = base.dists.geometric.cdf( -1.0, 4.0 )\ny = base.dists.geometric.cdf( NaN, 0.5 )\ny = base.dists.geometric.cdf( 0.0, NaN )\ny = base.dists.geometric.cdf( 2.0, 1.4 )\n","base.dists.geometric.cdf.factory":"var mycdf = base.dists.geometric.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.geometric.entropy":"var v = base.dists.geometric.entropy( 0.1 )\nv = base.dists.geometric.entropy( 0.5 )\n","base.dists.geometric.Geometric":"var geometric = base.dists.geometric.Geometric( 0.6 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2.0, 0.7 )\ny = base.dists.geometric.logpmf( -1.0, 0.5 )\ny = base.dists.geometric.logpmf( 0.0, NaN )\ny = base.dists.geometric.logpmf( NaN, 0.5 )\ny = base.dists.geometric.logpmf( 2.0, 1.5 )\n","base.dists.geometric.logpmf.factory":"var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.geometric.mean":"var v = base.dists.geometric.mean( 0.1 )\nv = base.dists.geometric.mean( 0.5 )\n","base.dists.geometric.median":"var v = base.dists.geometric.median( 0.1 )\nv = base.dists.geometric.median( 0.5 )\n","base.dists.geometric.mgf":"var y = base.dists.geometric.mgf( 0.2, 0.5 )\ny = base.dists.geometric.mgf( 0.4, 0.5 )\ny = base.dists.geometric.mgf( 0.8, 0.5 )\ny = base.dists.geometric.mgf( NaN, 0.0 )\ny = base.dists.geometric.mgf( 0.0, NaN )\ny = base.dists.geometric.mgf( -2.0, -1.0 )\ny = base.dists.geometric.mgf( 0.2, 2.0 )\n","base.dists.geometric.mgf.factory":"var mymgf = base.dists.geometric.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.geometric.mode":"var v = base.dists.geometric.mode( 0.1 )\nv = base.dists.geometric.mode( 0.5 )\n","base.dists.geometric.pmf":"var y = base.dists.geometric.pmf( 4.0, 0.3 )\ny = base.dists.geometric.pmf( 2.0, 0.7 )\ny = base.dists.geometric.pmf( -1.0, 0.5 )\ny = base.dists.geometric.pmf( 0.0, NaN )\ny = base.dists.geometric.pmf( NaN, 0.5 )\ny = base.dists.geometric.pmf( 2.0, 1.5 )\n","base.dists.geometric.pmf.factory":"var mypmf = base.dists.geometric.pmf.factory( 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.geometric.quantile":"var y = base.dists.geometric.quantile( 0.8, 0.4 )\ny = base.dists.geometric.quantile( 0.5, 0.4 )\ny = base.dists.geometric.quantile( 0.9, 0.1 )\ny = base.dists.geometric.quantile( -0.2, 0.1 )\ny = base.dists.geometric.quantile( NaN, 0.8 )\ny = base.dists.geometric.quantile( 0.4, NaN )\ny = base.dists.geometric.quantile( 0.5, -1.0 )\ny = base.dists.geometric.quantile( 0.5, 1.5 )\n","base.dists.geometric.quantile.factory":"var myquantile = base.dists.geometric.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.geometric.skewness":"var v = base.dists.geometric.skewness( 0.1 )\nv = base.dists.geometric.skewness( 0.5 )\n","base.dists.geometric.stdev":"var v = base.dists.geometric.stdev( 0.1 )\nv = base.dists.geometric.stdev( 0.5 )\n","base.dists.geometric.variance":"var v = base.dists.geometric.variance( 0.1 )\nv = base.dists.geometric.variance( 0.5 )\n","base.dists.gumbel.cdf":"var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.cdf.factory":"var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.gumbel.entropy":"var y = base.dists.gumbel.entropy( 0.0, 1.0 )\ny = base.dists.gumbel.entropy( 4.0, 2.0 )\ny = base.dists.gumbel.entropy( NaN, 1.0 )\ny = base.dists.gumbel.entropy( 0.0, NaN )\ny = base.dists.gumbel.entropy( 0.0, 0.0 )\n","base.dists.gumbel.Gumbel":"var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\ngumbel.mu\ngumbel.beta\ngumbel.entropy\ngumbel.kurtosis\ngumbel.mean\ngumbel.median\ngumbel.mode\ngumbel.skewness\ngumbel.stdev\ngumbel.variance\ngumbel.cdf( 0.8 )\ngumbel.logcdf( 0.8 )\ngumbel.logpdf( 1.0 )\ngumbel.mgf( 0.2 )\ngumbel.pdf( 1.0 )\ngumbel.quantile( 0.8 )\n","base.dists.gumbel.kurtosis":"var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\ny = base.dists.gumbel.kurtosis( 4.0, 2.0 )\ny = base.dists.gumbel.kurtosis( NaN, 1.0 )\ny = base.dists.gumbel.kurtosis( 0.0, NaN )\ny = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n","base.dists.gumbel.logcdf":"var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.logcdf.factory":"var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\nvar y = myLCDF( 10.0 )\ny = myLCDF( 2.0 )\n","base.dists.gumbel.logpdf":"var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.logpdf.factory":"var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\ny = mylogpdf( 12.0 )\n","base.dists.gumbel.mean":"var y = base.dists.gumbel.mean( 0.0, 1.0 )\ny = base.dists.gumbel.mean( 4.0, 2.0 )\ny = base.dists.gumbel.mean( NaN, 1.0 )\ny = base.dists.gumbel.mean( 0.0, NaN )\ny = base.dists.gumbel.mean( 0.0, 0.0 )\n","base.dists.gumbel.median":"var y = base.dists.gumbel.median( 0.0, 1.0 )\ny = base.dists.gumbel.median( 4.0, 2.0 )\ny = base.dists.gumbel.median( NaN, 1.0 )\ny = base.dists.gumbel.median( 0.0, NaN )\ny = base.dists.gumbel.median( 0.0, 0.0 )\n","base.dists.gumbel.mgf":"var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.mgf.factory":"var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\nvar y = myMGF( -1.5 )\ny = myMGF( -1.0 )\n","base.dists.gumbel.mode":"var y = base.dists.gumbel.mode( 0.0, 1.0 )\ny = base.dists.gumbel.mode( 4.0, 2.0 )\ny = base.dists.gumbel.mode( NaN, 1.0 )\ny = base.dists.gumbel.mode( 0.0, NaN )\ny = base.dists.gumbel.mode( 0.0, 0.0 )\n","base.dists.gumbel.pdf":"var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.pdf.factory":"var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 12.0 )\n","base.dists.gumbel.quantile":"var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\ny = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\ny = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n","base.dists.gumbel.quantile.factory":"var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.7 )\n","base.dists.gumbel.skewness":"var y = base.dists.gumbel.skewness( 0.0, 1.0 )\ny = base.dists.gumbel.skewness( 4.0, 2.0 )\ny = base.dists.gumbel.skewness( NaN, 1.0 )\ny = base.dists.gumbel.skewness( 0.0, NaN )\ny = base.dists.gumbel.skewness( 0.0, 0.0 )\n","base.dists.gumbel.stdev":"var y = base.dists.gumbel.stdev( 0.0, 1.0 )\ny = base.dists.gumbel.stdev( 4.0, 2.0 )\ny = base.dists.gumbel.stdev( NaN, 1.0 )\ny = base.dists.gumbel.stdev( 0.0, NaN )\ny = base.dists.gumbel.stdev( 0.0, 0.0 )\n","base.dists.gumbel.variance":"var y = base.dists.gumbel.variance( 0.0, 1.0 )\ny = base.dists.gumbel.variance( 4.0, 2.0 )\ny = base.dists.gumbel.variance( NaN, 1.0 )\ny = base.dists.gumbel.variance( 0.0, NaN )\ny = base.dists.gumbel.variance( 0.0, 0.0 )\n","base.dists.hypergeometric.cdf":"var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\ny = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.cdf.factory":"var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\nvar y = myCDF( 4.0 )\ny = myCDF( 1.0 )\n","base.dists.hypergeometric.Hypergeometric":"var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\nhypergeometric.N\nhypergeometric.K\nhypergeometric.n\nhypergeometric.kurtosis\nhypergeometric.mean\nhypergeometric.mode\nhypergeometric.skewness\nhypergeometric.stdev\nhypergeometric.variance\nhypergeometric.cdf( 2.9 )\nhypergeometric.logpmf( 10 )\nhypergeometric.pmf( 10 )\nhypergeometric.quantile( 0.8 )\n","base.dists.hypergeometric.kurtosis":"var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\nv = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\nv = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\nv = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n","base.dists.hypergeometric.logpmf":"var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.logpmf.factory":"var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\nvar y = mylogPMF( 4.0 )\ny = mylogPMF( 1.0 )\n","base.dists.hypergeometric.mean":"var v = base.dists.hypergeometric.mean( 16, 11, 4 )\nv = base.dists.hypergeometric.mean( 2, 1, 1 )\nv = base.dists.hypergeometric.mean( 10, 5, 12 )\nv = base.dists.hypergeometric.mean( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mean( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mean( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mean( NaN, 10, 4 )\nv = base.dists.hypergeometric.mean( 20, NaN, 4 )\nv = base.dists.hypergeometric.mean( 20, 10, NaN )\n","base.dists.hypergeometric.mode":"var v = base.dists.hypergeometric.mode( 16, 11, 4 )\nv = base.dists.hypergeometric.mode( 2, 1, 1 )\nv = base.dists.hypergeometric.mode( 10, 5, 12 )\nv = base.dists.hypergeometric.mode( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mode( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mode( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mode( NaN, 10, 4 )\nv = base.dists.hypergeometric.mode( 20, NaN, 4 )\nv = base.dists.hypergeometric.mode( 20, 10, NaN )\n","base.dists.hypergeometric.pmf":"var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.pmf.factory":"var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\nvar y = myPMF( 4.0 )\ny = myPMF( 1.0 )\n","base.dists.hypergeometric.quantile":"var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\ny = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\ny = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n","base.dists.hypergeometric.quantile.factory":"var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.hypergeometric.skewness":"var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\nv = base.dists.hypergeometric.skewness( 4, 2, 2 )\nv = base.dists.hypergeometric.skewness( 10, 5, 12 )\nv = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\nv = base.dists.hypergeometric.skewness( NaN, 10, 4 )\nv = base.dists.hypergeometric.skewness( 20, NaN, 4 )\nv = base.dists.hypergeometric.skewness( 20, 10, NaN )\n","base.dists.hypergeometric.stdev":"var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\nv = base.dists.hypergeometric.stdev( 2, 1, 1 )\nv = base.dists.hypergeometric.stdev( 10, 5, 12 )\nv = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\nv = base.dists.hypergeometric.stdev( NaN, 10, 4 )\nv = base.dists.hypergeometric.stdev( 20, NaN, 4 )\nv = base.dists.hypergeometric.stdev( 20, 10, NaN )\n","base.dists.hypergeometric.variance":"var v = base.dists.hypergeometric.variance( 16, 11, 4 )\nv = base.dists.hypergeometric.variance( 2, 1, 1 )\nv = base.dists.hypergeometric.variance( 10, 5, 12 )\nv = base.dists.hypergeometric.variance( 10.3, 10, 4 )\nv = base.dists.hypergeometric.variance( 10, 5.5, 4 )\nv = base.dists.hypergeometric.variance( 10, 5, 4.5 )\nv = base.dists.hypergeometric.variance( NaN, 10, 4 )\nv = base.dists.hypergeometric.variance( 20, NaN, 4 )\nv = base.dists.hypergeometric.variance( 20, 10, NaN )\n","base.dists.invgamma.cdf":"var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.cdf.factory":"var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 0.5 )\ny = myCDF( 2.0 )\n","base.dists.invgamma.entropy":"var v = base.dists.invgamma.entropy( 1.0, 1.0 )\nv = base.dists.invgamma.entropy( 4.0, 12.0 )\nv = base.dists.invgamma.entropy( 8.0, 2.0 )\n","base.dists.invgamma.InvGamma":"var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\ninvgamma.alpha\ninvgamma.beta\ninvgamma.entropy\ninvgamma.kurtosis\ninvgamma.mean\ninvgamma.mode\ninvgamma.skewness\ninvgamma.stdev\ninvgamma.variance\ninvgamma.cdf( 0.8 )\ninvgamma.pdf( 1.0 )\ninvgamma.logpdf( 1.0 )\ninvgamma.quantile( 0.8 )\n","base.dists.invgamma.kurtosis":"var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\nv = base.dists.invgamma.kurtosis( 6.0, 12.0 )\nv = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n","base.dists.invgamma.logpdf":"var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.logpdf.factory":"var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.invgamma.mean":"var v = base.dists.invgamma.mean( 4.0, 12.0 )\nv = base.dists.invgamma.mean( 8.0, 2.0 )\n","base.dists.invgamma.mode":"var v = base.dists.invgamma.mode( 1.0, 1.0 )\nv = base.dists.invgamma.mode( 4.0, 12.0 )\nv = base.dists.invgamma.mode( 8.0, 2.0 )\n","base.dists.invgamma.pdf":"var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.pdf.factory":"var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.invgamma.quantile":"var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n","base.dists.invgamma.quantile.factory":"var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.invgamma.skewness":"var v = base.dists.invgamma.skewness( 4.0, 12.0 )\nv = base.dists.invgamma.skewness( 8.0, 2.0 )\n","base.dists.invgamma.stdev":"var v = base.dists.invgamma.stdev( 5.0, 7.0 )\nv = base.dists.invgamma.stdev( 4.0, 12.0 )\nv = base.dists.invgamma.stdev( 8.0, 2.0 )\n","base.dists.invgamma.variance":"var v = base.dists.invgamma.variance( 5.0, 7.0 )\nv = base.dists.invgamma.variance( 4.0, 12.0 )\nv = base.dists.invgamma.variance( 8.0, 2.0 )\n","base.dists.kumaraswamy.cdf":"var y = 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mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.kumaraswamy.quantile":"var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.quantile.factory":"var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.3 )\n","base.dists.kumaraswamy.skewness":"var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\nv = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\nv = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n","base.dists.kumaraswamy.stdev":"var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\nv = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\nv = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n","base.dists.kumaraswamy.variance":"var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\nv = base.dists.kumaraswamy.variance( 4.0, 12.0 )\nv = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n","base.dists.laplace.cdf":"var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 2, NaN, 1.0 )\ny = base.dists.laplace.cdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.cdf.factory":"var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.laplace.entropy":"var y = base.dists.laplace.entropy( 0.0, 1.0 )\ny = base.dists.laplace.entropy( 4.0, 2.0 )\ny = base.dists.laplace.entropy( NaN, 1.0 )\ny = base.dists.laplace.entropy( 0.0, NaN )\ny = base.dists.laplace.entropy( 0.0, 0.0 )\n","base.dists.laplace.kurtosis":"var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\ny = base.dists.laplace.kurtosis( 4.0, 2.0 )\ny = base.dists.laplace.kurtosis( NaN, 1.0 )\ny = base.dists.laplace.kurtosis( 0.0, NaN )\ny = base.dists.laplace.kurtosis( 0.0, 0.0 )\n","base.dists.laplace.Laplace":"var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\nlaplace.mu\nlaplace.b\nlaplace.entropy\nlaplace.kurtosis\nlaplace.mean\nlaplace.median\nlaplace.mode\nlaplace.skewness\nlaplace.stdev\nlaplace.variance\nlaplace.cdf( 0.8 )\nlaplace.logcdf( 0.8 )\nlaplace.logpdf( 1.0 )\nlaplace.mgf( 0.2 )\nlaplace.pdf( 2.0 )\nlaplace.quantile( 0.9 )\n","base.dists.laplace.logcdf":"var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 2, NaN, 1.0 )\ny = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logcdf.factory":"var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 2.0 )\n","base.dists.laplace.logpdf":"var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logpdf.factory":"var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.laplace.mean":"var y = base.dists.laplace.mean( 0.0, 1.0 )\ny = base.dists.laplace.mean( 4.0, 2.0 )\ny = base.dists.laplace.mean( NaN, 1.0 )\ny = base.dists.laplace.mean( 0.0, NaN )\ny = base.dists.laplace.mean( 0.0, 0.0 )\n","base.dists.laplace.median":"var y = base.dists.laplace.median( 0.0, 1.0 )\ny = base.dists.laplace.median( 4.0, 2.0 )\ny = base.dists.laplace.median( NaN, 1.0 )\ny = base.dists.laplace.median( 0.0, NaN )\ny = base.dists.laplace.median( 0.0, 0.0 )\n","base.dists.laplace.mgf":"var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\ny = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, NaN )\ny = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\ny = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.mgf.factory":"var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.laplace.mode":"var y = base.dists.laplace.mode( 0.0, 1.0 )\ny = base.dists.laplace.mode( 4.0, 2.0 )\ny = base.dists.laplace.mode( NaN, 1.0 )\ny = base.dists.laplace.mode( 0.0, NaN )\ny = base.dists.laplace.mode( 0.0, 0.0 )\n","base.dists.laplace.pdf":"var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.pdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.pdf.factory":"var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.laplace.quantile":"var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\ny = base.dists.laplace.quantile( 0.0, 0.0, NaN )\ny = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n","base.dists.laplace.quantile.factory":"var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.laplace.skewness":"var y = base.dists.laplace.skewness( 0.0, 1.0 )\ny = base.dists.laplace.skewness( 4.0, 2.0 )\ny = base.dists.laplace.skewness( NaN, 1.0 )\ny = base.dists.laplace.skewness( 0.0, NaN )\ny = base.dists.laplace.skewness( 0.0, 0.0 )\n","base.dists.laplace.stdev":"var y = base.dists.laplace.stdev( 0.0, 1.0 )\ny = base.dists.laplace.stdev( 4.0, 2.0 )\ny = base.dists.laplace.stdev( NaN, 1.0 )\ny = base.dists.laplace.stdev( 0.0, NaN )\ny = base.dists.laplace.stdev( 0.0, 0.0 )\n","base.dists.laplace.variance":"var y = base.dists.laplace.variance( 0.0, 1.0 )\ny = base.dists.laplace.variance( 4.0, 2.0 )\ny = base.dists.laplace.variance( NaN, 1.0 )\ny = base.dists.laplace.variance( 0.0, NaN )\ny = base.dists.laplace.variance( 0.0, 0.0 )\n","base.dists.levy.cdf":"var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.cdf( 2, NaN, 1.0 )\ny = base.dists.levy.cdf( 2.0, 0.0, NaN )\ny = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.cdf.factory":"var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.levy.entropy":"var y = base.dists.levy.entropy( 0.0, 1.0 )\ny = base.dists.levy.entropy( 4.0, 2.0 )\ny = base.dists.levy.entropy( NaN, 1.0 )\ny = base.dists.levy.entropy( 0.0, NaN )\ny = base.dists.levy.entropy( 0.0, 0.0 )\n","base.dists.levy.Levy":"var levy = base.dists.levy.Levy( -2.0, 3.0 );\nlevy.mu\nlevy.c\nlevy.entropy\nlevy.mean\nlevy.median\nlevy.mode\nlevy.stdev\nlevy.variance\nlevy.cdf( 0.8 )\nlevy.logcdf( 0.8 )\nlevy.logpdf( 1.0 )\nlevy.pdf( 1.0 )\nlevy.quantile( 0.8 )\n","base.dists.levy.logcdf":"var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 2, NaN, 1.0 )\ny = base.dists.levy.logcdf( 2.0, 0.0, NaN )\ny = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.logcdf.factory":"var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 2.0 )\n","base.dists.levy.logpdf":"var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.levy.logpdf( 0.0, 0.0, NaN )\ny = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.logpdf.factory":"var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 11.0 )\n","base.dists.levy.mean":"var y = base.dists.levy.mean( 0.0, 1.0 )\ny = base.dists.levy.mean( 4.0, 3.0 )\ny = base.dists.levy.mean( NaN, 1.0 )\ny = base.dists.levy.mean( 0.0, NaN )\ny = base.dists.levy.mean( 0.0, 0.0 )\n","base.dists.levy.median":"var y = base.dists.levy.median( 0.0, 1.0 )\ny = base.dists.levy.median( 4.0, 3.0 )\ny = base.dists.levy.median( NaN, 1.0 )\ny = base.dists.levy.median( 0.0, NaN )\ny = base.dists.levy.median( 0.0, 0.0 )\n","base.dists.levy.mode":"var y = base.dists.levy.mode( 0.0, 1.0 )\ny = base.dists.levy.mode( 4.0, 3.0 )\ny = base.dists.levy.mode( NaN, 1.0 )\ny = base.dists.levy.mode( 0.0, NaN )\ny = base.dists.levy.mode( 0.0, 0.0 )\n","base.dists.levy.pdf":"var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.levy.pdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.levy.pdf( 0.0, 0.0, NaN )\ny = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.pdf.factory":"var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 11.0 )\n","base.dists.levy.quantile":"var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.levy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.levy.quantile( 0.0, 0.0, NaN )\ny = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.levy.quantile.factory":"var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.levy.stdev":"var y = base.dists.levy.stdev( 0.0, 1.0 )\ny = base.dists.levy.stdev( 4.0, 3.0 )\ny = base.dists.levy.stdev( NaN, 1.0 )\ny = base.dists.levy.stdev( 0.0, NaN )\ny = base.dists.levy.stdev( 0.0, 0.0 )\n","base.dists.levy.variance":"var y = base.dists.levy.variance( 0.0, 1.0 )\ny = base.dists.levy.variance( 4.0, 3.0 )\ny = base.dists.levy.variance( NaN, 1.0 )\ny = base.dists.levy.variance( 0.0, NaN )\ny = base.dists.levy.variance( 0.0, 0.0 )\n","base.dists.logistic.cdf":"var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.cdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\ny = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n","base.dists.logistic.cdf.factory":"var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.0 )\n","base.dists.logistic.entropy":"var y = base.dists.logistic.entropy( 0.0, 1.0 )\ny = base.dists.logistic.entropy( 4.0, 2.0 )\ny = base.dists.logistic.entropy( NaN, 1.0 )\ny = base.dists.logistic.entropy( 0.0, NaN )\ny = base.dists.logistic.entropy( 0.0, 0.0 )\n","base.dists.logistic.kurtosis":"var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\ny = base.dists.logistic.kurtosis( 4.0, 2.0 )\ny = base.dists.logistic.kurtosis( NaN, 1.0 )\ny = base.dists.logistic.kurtosis( 0.0, NaN )\ny = base.dists.logistic.kurtosis( 0.0, 0.0 )\n","base.dists.logistic.logcdf":"var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.logcdf( 2, NaN, 1.0 )\ny = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n","base.dists.logistic.logcdf.factory":"var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.0 )\n","base.dists.logistic.Logistic":"var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\nlogistic.mu\nlogistic.s\nlogistic.entropy\nlogistic.kurtosis\nlogistic.mean\nlogistic.median\nlogistic.mode\nlogistic.skewness\nlogistic.stdev\nlogistic.variance\nlogistic.cdf( 0.8 )\nlogistic.logcdf( 0.8 )\nlogistic.logpdf( 2.0 )\nlogistic.mgf( 0.2 )\nlogistic.pdf( 2.0 )\nlogistic.quantile( 0.9 )\n","base.dists.logistic.logpdf":"var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.logpdf.factory":"var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.logistic.mean":"var y = base.dists.logistic.mean( 0.0, 1.0 )\ny = base.dists.logistic.mean( 4.0, 2.0 )\ny = base.dists.logistic.mean( NaN, 1.0 )\ny = base.dists.logistic.mean( 0.0, NaN )\ny = base.dists.logistic.mean( 0.0, 0.0 )\n","base.dists.logistic.median":"var y = base.dists.logistic.median( 0.0, 1.0 )\ny = base.dists.logistic.median( 4.0, 2.0 )\ny = base.dists.logistic.median( NaN, 1.0 )\ny = base.dists.logistic.median( 0.0, NaN )\ny = base.dists.logistic.median( 0.0, 0.0 )\n","base.dists.logistic.mgf":"var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\ny = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\ny = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n","base.dists.logistic.mgf.factory":"var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\nvar y = mymgf( 0.5 )\ny = mymgf( 2.0 )\n","base.dists.logistic.mode":"var y = base.dists.logistic.mode( 0.0, 1.0 )\ny = base.dists.logistic.mode( 4.0, 2.0 )\ny = base.dists.logistic.mode( NaN, 1.0 )\ny = base.dists.logistic.mode( 0.0, NaN )\ny = base.dists.logistic.mode( 0.0, 0.0 )\n","base.dists.logistic.pdf":"var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.pdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.pdf.factory":"var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.logistic.quantile":"var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\ny = base.dists.logistic.quantile( 0.0, 0.0, NaN )\ny = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n","base.dists.logistic.quantile.factory":"var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.logistic.skewness":"var y = base.dists.logistic.skewness( 0.0, 1.0 )\ny = base.dists.logistic.skewness( 4.0, 2.0 )\ny = base.dists.logistic.skewness( NaN, 1.0 )\ny = base.dists.logistic.skewness( 0.0, NaN )\ny = base.dists.logistic.skewness( 0.0, 0.0 )\n","base.dists.logistic.stdev":"var y = base.dists.logistic.stdev( 0.0, 1.0 )\ny = base.dists.logistic.stdev( 4.0, 2.0 )\ny = base.dists.logistic.stdev( NaN, 1.0 )\ny = base.dists.logistic.stdev( 0.0, NaN )\ny = base.dists.logistic.stdev( 0.0, 0.0 )\n","base.dists.logistic.variance":"var y = base.dists.logistic.variance( 0.0, 1.0 )\ny = base.dists.logistic.variance( 4.0, 2.0 )\ny = base.dists.logistic.variance( NaN, 1.0 )\ny = base.dists.logistic.variance( 0.0, NaN )\ny = base.dists.logistic.variance( 0.0, 0.0 )\n","base.dists.lognormal.cdf":"var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\ny = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\ny = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.cdf.factory":"var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 4.0 )\n","base.dists.lognormal.entropy":"var y = base.dists.lognormal.entropy( 0.0, 1.0 )\ny = base.dists.lognormal.entropy( 5.0, 2.0 )\ny = base.dists.lognormal.entropy( NaN, 1.0 )\ny = base.dists.lognormal.entropy( 0.0, NaN )\ny = base.dists.lognormal.entropy( 0.0, 0.0 )\n","base.dists.lognormal.kurtosis":"var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\ny = base.dists.lognormal.kurtosis( 5.0, 2.0 )\ny = base.dists.lognormal.kurtosis( NaN, 1.0 )\ny = base.dists.lognormal.kurtosis( 0.0, NaN )\ny = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n","base.dists.lognormal.LogNormal":"var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\nlognormal.mu\nlognormal.sigma\nlognormal.entropy\nlognormal.kurtosis\nlognormal.mean\nlognormal.median\nlognormal.mode\nlognormal.skewness\nlognormal.stdev\nlognormal.variance\nlognormal.cdf( 0.8 )\nlognormal.logcdf( 0.8 )\nlognormal.logpdf( 2.0 )\nlognormal.pdf( 2.0 )\nlognormal.quantile( 0.9 )\n","base.dists.lognormal.logcdf":"var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\ny = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.lognormal.logcdf.factory":"var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.lognormal.logpdf":"var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.logpdf.factory":"var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.lognormal.mean":"var y = base.dists.lognormal.mean( 0.0, 1.0 )\ny = base.dists.lognormal.mean( 4.0, 2.0 )\ny = base.dists.lognormal.mean( NaN, 1.0 )\ny = base.dists.lognormal.mean( 0.0, NaN )\ny = base.dists.lognormal.mean( 0.0, 0.0 )\n","base.dists.lognormal.median":"var y = base.dists.lognormal.median( 0.0, 1.0 )\ny = base.dists.lognormal.median( 5.0, 2.0 )\ny = base.dists.lognormal.median( NaN, 1.0 )\ny = base.dists.lognormal.median( 0.0, NaN )\ny = base.dists.lognormal.median( 0.0, 0.0 )\n","base.dists.lognormal.mode":"var y = base.dists.lognormal.mode( 0.0, 1.0 )\ny = base.dists.lognormal.mode( 5.0, 2.0 )\ny = base.dists.lognormal.mode( NaN, 1.0 )\ny = base.dists.lognormal.mode( 0.0, NaN )\ny = base.dists.lognormal.mode( 0.0, 0.0 )\n","base.dists.lognormal.pdf":"var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.pdf.factory":"var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.lognormal.quantile":"var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\ny = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n","base.dists.lognormal.quantile.factory":"var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.lognormal.skewness":"var y = base.dists.lognormal.skewness( 0.0, 1.0 )\ny = base.dists.lognormal.skewness( 5.0, 2.0 )\ny = base.dists.lognormal.skewness( NaN, 1.0 )\ny = base.dists.lognormal.skewness( 0.0, NaN )\ny = base.dists.lognormal.skewness( 0.0, 0.0 )\n","base.dists.lognormal.stdev":"var y = base.dists.lognormal.stdev( 0.0, 1.0 )\ny = base.dists.lognormal.stdev( 4.0, 2.0 )\ny = base.dists.lognormal.stdev( NaN, 1.0 )\ny = base.dists.lognormal.stdev( 0.0, NaN )\ny = base.dists.lognormal.stdev( 0.0, 0.0 )\n","base.dists.lognormal.variance":"var y = base.dists.lognormal.variance( 0.0, 1.0 )\ny = base.dists.lognormal.variance( 4.0, 2.0 )\ny = base.dists.lognormal.variance( NaN, 1.0 )\ny = base.dists.lognormal.variance( 0.0, NaN )\ny = base.dists.lognormal.variance( 0.0, 0.0 )\n","base.dists.negativeBinomial.cdf":"var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n","base.dists.negativeBinomial.cdf.factory":"var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\nvar y = myCDF( 3.0 )\ny = myCDF( 11.0 )\n","base.dists.negativeBinomial.kurtosis":"var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\nv = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n","base.dists.negativeBinomial.logpmf":"var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.logpmf.factory":"var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\nvar y = mylogPMF( 3.0 )\ny = mylogPMF( 5.0 )\n","base.dists.negativeBinomial.mean":"var v = base.dists.negativeBinomial.mean( 100, 0.2 )\nv = base.dists.negativeBinomial.mean( 20, 0.5 )\n","base.dists.negativeBinomial.mgf":"var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\ny = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\ny = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n","base.dists.negativeBinomial.mgf.factory":"var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\nvar y = myMGF( 0.2 )\ny = myMGF( 0.4 )\n","base.dists.negativeBinomial.mode":"var v = base.dists.negativeBinomial.mode( 100, 0.2 )\nv = base.dists.negativeBinomial.mode( 20, 0.5 )\n","base.dists.negativeBinomial.NegativeBinomial":"var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\nnbinomial.r\nnbinomial.p\nnbinomial.kurtosis\nnbinomial.mean\nnbinomial.mode\nnbinomial.skewness\nnbinomial.stdev\nnbinomial.variance\nnbinomial.cdf( 2.9 )\nnbinomial.logpmf( 3.0 )\nnbinomial.mgf( 0.2 )\nnbinomial.pmf( 3.0 )\nnbinomial.quantile( 0.8 )\n","base.dists.negativeBinomial.pmf":"var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.pmf.factory":"var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\nvar y = myPMF( 3.0 )\ny = myPMF( 5.0 )\n","base.dists.negativeBinomial.quantile":"var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\ny = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\ny = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\ny = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n","base.dists.negativeBinomial.quantile.factory":"var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\nvar y = myQuantile( 0.1 )\ny = myQuantile( 0.9 )\n","base.dists.negativeBinomial.skewness":"var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\nv = base.dists.negativeBinomial.skewness( 20, 0.5 )\n","base.dists.negativeBinomial.stdev":"var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\nv = base.dists.negativeBinomial.stdev( 20, 0.5 )\n","base.dists.negativeBinomial.variance":"var v = base.dists.negativeBinomial.variance( 100, 0.2 )\nv = base.dists.negativeBinomial.variance( 20, 0.5 )\n","base.dists.normal.cdf":"var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\ny = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.cdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.cdf( 0.0, 0.0, NaN )\ny = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n","base.dists.normal.cdf.factory":"var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\n","base.dists.normal.entropy":"var y = base.dists.normal.entropy( 0.0, 1.0 )\ny = base.dists.normal.entropy( 4.0, 3.0 )\ny = base.dists.normal.entropy( NaN, 1.0 )\ny = base.dists.normal.entropy( 0.0, NaN )\ny = base.dists.normal.entropy( 0.0, 0.0 )\n","base.dists.normal.kurtosis":"var y = base.dists.normal.kurtosis( 0.0, 1.0 )\ny = base.dists.normal.kurtosis( 4.0, 3.0 )\ny = base.dists.normal.kurtosis( NaN, 1.0 )\ny = base.dists.normal.kurtosis( 0.0, NaN )\ny = base.dists.normal.kurtosis( 0.0, 0.0 )\n","base.dists.normal.logcdf":"var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logcdf.factory":"var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.normal.logpdf":"var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logpdf.factory":"var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\nvar y = myLogPDF( 10.0 )\n","base.dists.normal.mean":"var y = base.dists.normal.mean( 0.0, 1.0 )\ny = base.dists.normal.mean( 4.0, 2.0 )\ny = base.dists.normal.mean( NaN, 1.0 )\ny = base.dists.normal.mean( 0.0, NaN )\ny = base.dists.normal.mean( 0.0, 0.0 )\n","base.dists.normal.median":"var y = base.dists.normal.median( 0.0, 1.0 )\ny = base.dists.normal.median( 4.0, 2.0 )\ny = base.dists.normal.median( NaN, 1.0 )\ny = base.dists.normal.median( 0.0, NaN )\ny = base.dists.normal.median( 0.0, 0.0 )\n","base.dists.normal.mgf":"var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.mgf( NaN, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, NaN, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, NaN )\ny = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n","base.dists.normal.mgf.factory":"var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.normal.mode":"var y = base.dists.normal.mode( 0.0, 1.0 )\ny = base.dists.normal.mode( 4.0, 2.0 )\ny = base.dists.normal.mode( NaN, 1.0 )\ny = base.dists.normal.mode( 0.0, NaN )\ny = base.dists.normal.mode( 0.0, 0.0 )\n","base.dists.normal.Normal":"var normal = base.dists.normal.Normal( -2.0, 3.0 );\nnormal.mu\nnormal.sigma\nnormal.entropy\nnormal.kurtosis\nnormal.mean\nnormal.median\nnormal.mode\nnormal.skewness\nnormal.stdev\nnormal.variance\nnormal.cdf( 0.8 )\nnormal.logcdf( 0.8 )\nnormal.logpdf( 2.0 )\nnormal.mgf( 0.2 )\nnormal.pdf( 2.0 )\nnormal.quantile( 0.9 )\n","base.dists.normal.pdf":"var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.pdf( 0.0, 0.0, NaN )\ny = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.pdf.factory":"var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.normal.quantile":"var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.normal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.normal.quantile( 0.0, 0.0, NaN )\ny = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\ny = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n","base.dists.normal.quantile.factory":"var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.normal.skewness":"var y = base.dists.normal.skewness( 0.0, 1.0 )\ny = base.dists.normal.skewness( 4.0, 3.0 )\ny = base.dists.normal.skewness( NaN, 1.0 )\ny = base.dists.normal.skewness( 0.0, NaN )\ny = base.dists.normal.skewness( 0.0, 0.0 )\n","base.dists.normal.stdev":"var y = base.dists.normal.stdev( 0.0, 1.0 )\ny = base.dists.normal.stdev( 4.0, 3.0 )\ny = base.dists.normal.stdev( NaN, 1.0 )\ny = base.dists.normal.stdev( 0.0, NaN )\ny = base.dists.normal.stdev( 0.0, 0.0 )\n","base.dists.normal.variance":"var y = base.dists.normal.variance( 0.0, 1.0 )\ny = base.dists.normal.variance( 4.0, 3.0 )\ny = base.dists.normal.variance( NaN, 1.0 )\ny = base.dists.normal.variance( 0.0, NaN )\ny = base.dists.normal.variance( 0.0, 0.0 )\n","base.dists.pareto1.cdf":"var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.cdf.factory":"var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 2.5 )\n","base.dists.pareto1.entropy":"var v = base.dists.pareto1.entropy( 0.8, 1.0 )\nv = base.dists.pareto1.entropy( 4.0, 12.0 )\nv = base.dists.pareto1.entropy( 8.0, 2.0 )\n","base.dists.pareto1.kurtosis":"var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\nv = base.dists.pareto1.kurtosis( 4.5, 12.0 )\nv = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n","base.dists.pareto1.logcdf":"var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.logcdf.factory":"var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\nvar y = mylogCDF( 3.0 )\ny = mylogCDF( 2.5 )\n","base.dists.pareto1.logpdf":"var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.logpdf.factory":"var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\nvar y = mylogPDF( 0.8 )\ny = mylogPDF( 2.0 )\n","base.dists.pareto1.mean":"var v = base.dists.pareto1.mean( 0.8, 1.0 )\nv = base.dists.pareto1.mean( 4.0, 12.0 )\nv = base.dists.pareto1.mean( 8.0, 2.0 )\n","base.dists.pareto1.median":"var v = base.dists.pareto1.median( 0.8, 1.0 )\nv = base.dists.pareto1.median( 4.0, 12.0 )\nv = base.dists.pareto1.median( 8.0, 2.0 )\n","base.dists.pareto1.mode":"var v = base.dists.pareto1.mode( 0.8, 1.0 )\nv = base.dists.pareto1.mode( 4.0, 12.0 )\nv = base.dists.pareto1.mode( 8.0, 2.0 )\n","base.dists.pareto1.Pareto1":"var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\npareto1.alpha\npareto1.beta\npareto1.entropy\npareto1.kurtosis\npareto1.mean\npareto1.median\npareto1.mode\npareto1.skewness\npareto1.variance\npareto1.cdf( 7.0 )\npareto1.logcdf( 7.0 )\npareto1.logpdf( 5.0 )\npareto1.pdf( 5.0 )\npareto1.quantile( 0.8 )\n","base.dists.pareto1.pdf":"var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.pdf.factory":"var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\nvar y = myPDF( 0.8 )\ny = myPDF( 2.0 )\n","base.dists.pareto1.quantile":"var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\ny = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n","base.dists.pareto1.quantile.factory":"var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.pareto1.skewness":"var v = base.dists.pareto1.skewness( 3.5, 1.0 )\nv = base.dists.pareto1.skewness( 4.0, 12.0 )\nv = base.dists.pareto1.skewness( 8.0, 2.0 )\n","base.dists.pareto1.stdev":"var v = base.dists.pareto1.stdev( 0.8, 1.0 )\nv = base.dists.pareto1.stdev( 4.0, 12.0 )\nv = base.dists.pareto1.stdev( 8.0, 2.0 )\n","base.dists.pareto1.variance":"var v = base.dists.pareto1.variance( 0.8, 1.0 )\nv = base.dists.pareto1.variance( 4.0, 12.0 )\nv = base.dists.pareto1.variance( 8.0, 2.0 )\n","base.dists.poisson.cdf":"var y = base.dists.poisson.cdf( 2.0, 0.5 )\ny = base.dists.poisson.cdf( 2.0, 10.0 )\ny = base.dists.poisson.cdf( -1.0, 4.0 )\ny = base.dists.poisson.cdf( NaN, 1.0 )\ny = base.dists.poisson.cdf( 0.0, NaN )\ny = base.dists.poisson.cdf( 2.0, -1.0 )\ny = base.dists.poisson.cdf( -2.0, 0.0 )\ny = base.dists.poisson.cdf( 0.0, 0.0 )\ny = base.dists.poisson.cdf( 10.0, 0.0 )\n","base.dists.poisson.cdf.factory":"var mycdf = base.dists.poisson.cdf.factory( 5.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 8.0 )\n","base.dists.poisson.entropy":"var v = base.dists.poisson.entropy( 11.0 )\nv = base.dists.poisson.entropy( 4.5 )\n","base.dists.poisson.kurtosis":"var v = base.dists.poisson.kurtosis( 11.0 )\nv = base.dists.poisson.kurtosis( 4.5 )\n","base.dists.poisson.logpmf":"var y = base.dists.poisson.logpmf( 4.0, 3.0 )\ny = base.dists.poisson.logpmf( 1.0, 3.0 )\ny = base.dists.poisson.logpmf( -1.0, 2.0 )\ny = base.dists.poisson.logpmf( 0.0, NaN )\ny = base.dists.poisson.logpmf( NaN, 0.5 )\ny = base.dists.poisson.logpmf( 2.0, -0.5 )\ny = base.dists.poisson.logpmf( 2.0, 0.0 )\ny = base.dists.poisson.logpmf( 0.0, 0.0 )\n","base.dists.poisson.logpmf.factory":"var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.poisson.mean":"var v = base.dists.poisson.mean( 11.0 )\nv = base.dists.poisson.mean( 4.5 )\n","base.dists.poisson.median":"var v = base.dists.poisson.median( 11.0 )\nv = base.dists.poisson.median( 4.5 )\n","base.dists.poisson.mgf":"var y = base.dists.poisson.mgf( 1.0, 1.5 )\ny = base.dists.poisson.mgf( 0.5, 0.5 )\ny = base.dists.poisson.mgf( NaN, 0.5 )\ny = base.dists.poisson.mgf( 0.0, NaN )\ny = base.dists.poisson.mgf( -2.0, -1.0 )\n","base.dists.poisson.mgf.factory":"var myMGF = base.dists.poisson.mgf.factory( 2.0 );\nvar y = myMGF( 0.1 )\n","base.dists.poisson.mode":"var v = base.dists.poisson.mode( 11.0 )\nv = base.dists.poisson.mode( 4.5 )\n","base.dists.poisson.pmf":"var y = base.dists.poisson.pmf( 4.0, 3.0 )\ny = base.dists.poisson.pmf( 1.0, 3.0 )\ny = base.dists.poisson.pmf( -1.0, 2.0 )\ny = base.dists.poisson.pmf( 0.0, NaN )\ny = base.dists.poisson.pmf( NaN, 0.5 )\ny = base.dists.poisson.pmf( 2.0, -0.5 )\ny = base.dists.poisson.pmf( 2.0, 0.0 )\ny = base.dists.poisson.pmf( 0.0, 0.0 )\n","base.dists.poisson.pmf.factory":"var mypmf = base.dists.poisson.pmf.factory( 1.0 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.poisson.Poisson":"var poisson = base.dists.poisson.Poisson( 6.0 );\npoisson.lambda\npoisson.entropy\npoisson.kurtosis\npoisson.mean\npoisson.median\npoisson.mode\npoisson.skewness\npoisson.stdev\npoisson.variance\npoisson.cdf( 4.0 )\npoisson.logpmf( 2.0 )\npoisson.mgf( 0.5 )\npoisson.pmf( 2.0 )\npoisson.quantile( 0.5 )\n","base.dists.poisson.quantile":"var y = base.dists.poisson.quantile( 0.5, 2.0 )\ny = base.dists.poisson.quantile( 0.9, 4.0 )\ny = base.dists.poisson.quantile( 0.1, 200.0 )\ny = base.dists.poisson.quantile( 1.1, 0.0 )\ny = base.dists.poisson.quantile( -0.2, 0.0 )\ny = base.dists.poisson.quantile( NaN, 0.5 )\ny = base.dists.poisson.quantile( 0.0, NaN )\ny = base.dists.poisson.quantile( 2.0, -1.0 )\ny = base.dists.poisson.quantile( 0.1, 0.0 )\ny = base.dists.poisson.quantile( 0.9, 0.0 )\n","base.dists.poisson.quantile.factory":"var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.poisson.skewness":"var v = base.dists.poisson.skewness( 11.0 )\nv = base.dists.poisson.skewness( 4.5 )\n","base.dists.poisson.stdev":"var v = base.dists.poisson.stdev( 11.0 )\nv = base.dists.poisson.stdev( 4.5 )\n","base.dists.poisson.variance":"var v = base.dists.poisson.variance( 11.0 )\nv = base.dists.poisson.variance( 4.5 )\n","base.dists.rayleigh.cdf":"var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\ny = base.dists.rayleigh.cdf( 1.0, 2.0 )\ny = base.dists.rayleigh.cdf( -1.0, 4.0 )\ny = base.dists.rayleigh.cdf( NaN, 1.0 )\ny = base.dists.rayleigh.cdf( 0.0, NaN )\ny = base.dists.rayleigh.cdf( 2.0, -1.0 )\ny = base.dists.rayleigh.cdf( -2.0, 0.0 )\ny = base.dists.rayleigh.cdf( 0.0, 0.0 )\ny = base.dists.rayleigh.cdf( 2.0, 0.0 )\n","base.dists.rayleigh.cdf.factory":"var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 0.5 )\n","base.dists.rayleigh.entropy":"var v = base.dists.rayleigh.entropy( 11.0 )\nv = base.dists.rayleigh.entropy( 4.5 )\n","base.dists.rayleigh.kurtosis":"var v = base.dists.rayleigh.kurtosis( 11.0 )\nv = base.dists.rayleigh.kurtosis( 4.5 )\n","base.dists.rayleigh.logcdf":"var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\ny = base.dists.rayleigh.logcdf( 1.0, 2.0 )\ny = base.dists.rayleigh.logcdf( -1.0, 4.0 )\ny = base.dists.rayleigh.logcdf( NaN, 1.0 )\ny = base.dists.rayleigh.logcdf( 0.0, NaN )\ny = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n","base.dists.rayleigh.logcdf.factory":"var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\nvar y = mylogcdf( 1.0 )\ny = mylogcdf( 0.5 )\n","base.dists.rayleigh.logpdf":"var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\ny = base.dists.rayleigh.logpdf( 2.0, 0.8 )\ny = base.dists.rayleigh.logpdf( -1.0, 0.5 )\ny = base.dists.rayleigh.logpdf( 0.0, NaN )\ny = base.dists.rayleigh.logpdf( NaN, 2.0 )\ny = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n","base.dists.rayleigh.logpdf.factory":"var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\nvar y = mylogpdf( 6.0 )\ny = mylogpdf( 4.0 )\n","base.dists.rayleigh.mean":"var v = base.dists.rayleigh.mean( 11.0 )\nv = base.dists.rayleigh.mean( 4.5 )\n","base.dists.rayleigh.median":"var v = base.dists.rayleigh.median( 11.0 )\nv = base.dists.rayleigh.median( 4.5 )\n","base.dists.rayleigh.mgf":"var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\ny = base.dists.rayleigh.mgf( 1.0, 2.0 )\ny = base.dists.rayleigh.mgf( -1.0, 4.0 )\ny = base.dists.rayleigh.mgf( NaN, 1.0 )\ny = base.dists.rayleigh.mgf( 0.0, NaN )\ny = base.dists.rayleigh.mgf( 0.5, -1.0 )\n","base.dists.rayleigh.mgf.factory":"var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.rayleigh.mode":"var v = base.dists.rayleigh.mode( 11.0 )\nv = base.dists.rayleigh.mode( 4.5 )\n","base.dists.rayleigh.pdf":"var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.8 )\ny = base.dists.rayleigh.pdf( -1.0, 0.5 )\ny = base.dists.rayleigh.pdf( 0.0, NaN )\ny = base.dists.rayleigh.pdf( NaN, 2.0 )\ny = base.dists.rayleigh.pdf( 2.0, -1.0 )\ny = base.dists.rayleigh.pdf( -2.0, 0.0 )\ny = base.dists.rayleigh.pdf( 0.0, 0.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.0 )\n","base.dists.rayleigh.pdf.factory":"var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\nvar y = myPDF( 6.0 )\ny = myPDF( 4.0 )\n","base.dists.rayleigh.quantile":"var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\ny = base.dists.rayleigh.quantile( 0.5, 4.0 )\ny = base.dists.rayleigh.quantile( 1.1, 1.0 )\ny = base.dists.rayleigh.quantile( -0.2, 1.0 )\ny = base.dists.rayleigh.quantile( NaN, 1.0 )\ny = base.dists.rayleigh.quantile( 0.0, NaN )\ny = base.dists.rayleigh.quantile( 0.5, -1.0 )\n","base.dists.rayleigh.quantile.factory":"var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.rayleigh.Rayleigh":"var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\nrayleigh.sigma\nrayleigh.entropy\nrayleigh.kurtosis\nrayleigh.mean\nrayleigh.median\nrayleigh.mode\nrayleigh.skewness\nrayleigh.stdev\nrayleigh.variance\nrayleigh.cdf( 1.0 )\nrayleigh.logcdf( 1.0 )\nrayleigh.logpdf( 1.5 )\nrayleigh.mgf( -0.5 )\nrayleigh.pdf( 1.5 )\nrayleigh.quantile( 0.5 )\n","base.dists.rayleigh.skewness":"var v = base.dists.rayleigh.skewness( 11.0 )\nv = base.dists.rayleigh.skewness( 4.5 )\n","base.dists.rayleigh.stdev":"var v = base.dists.rayleigh.stdev( 9.0 )\nv = base.dists.rayleigh.stdev( 4.5 )\n","base.dists.rayleigh.variance":"var v = base.dists.rayleigh.variance( 9.0 )\nv = base.dists.rayleigh.variance( 4.5 )\n","base.dists.signrank.cdf":"var y = base.dists.signrank.cdf( 3, 7 )\ny = base.dists.signrank.cdf( 1.8, 3 )\ny = base.dists.signrank.cdf( -1.0, 40 )\ny = base.dists.signrank.cdf( NaN, 10 )\ny = base.dists.signrank.cdf( 0.0, NaN )\n","base.dists.signrank.cdf.factory":"var myCDF = base.dists.signrank.cdf.factory( 8 );\nvar y = myCDF( 5.7 )\ny = myCDF( 2.2 )\n","base.dists.signrank.pdf":"var y = base.dists.signrank.pdf( 3, 7 )\ny = base.dists.signrank.pdf( 1.8, 3 )\ny = base.dists.signrank.pdf( -1.0, 40 )\ny = base.dists.signrank.pdf( NaN, 10 )\ny = base.dists.signrank.pdf( 0.0, NaN )\n","base.dists.signrank.pdf.factory":"var myPDF = base.dists.signrank.pdf.factory( 8 );\nvar y = myPDF( 6.0 )\ny = myPDF( 2.0 )\n","base.dists.signrank.quantile":"var y = base.dists.signrank.quantile( 0.8, 5 )\ny = base.dists.signrank.quantile( 0.5, 4 )\ny = base.dists.signrank.quantile( 1.1, 5 )\ny = base.dists.signrank.quantile( -0.2, 5 )\ny = base.dists.signrank.quantile( NaN, 5 )\ny = base.dists.signrank.quantile( 0.0, NaN )\n","base.dists.signrank.quantile.factory":"var myQuantile = base.dists.signrank.quantile.factory( 8 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.studentizedRange.cdf":"var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\ny = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n","base.dists.studentizedRange.cdf.factory":"var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.studentizedRange.quantile":"var y = quantile( 0.5, 3.0, 2.0 )\ny = quantile( 0.9, 17.0, 2.0 )\ny = quantile( 0.5, 3.0, 2.0, 2 )\ny = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\ny = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n","base.dists.studentizedRange.quantile.factory":"var myQuantile = quantile.factory( 3.0, 3.0 );\nvar y = myQuantile( 0.5 )\n ~1.791\ny = myQuantile( 0.8 )\n ~3.245\n","base.dists.t.cdf":"var y = base.dists.t.cdf( 2.0, 0.1 )\ny = base.dists.t.cdf( 1.0, 2.0 )\ny = base.dists.t.cdf( -1.0, 4.0 )\ny = base.dists.t.cdf( NaN, 1.0 )\ny = base.dists.t.cdf( 0.0, NaN )\ny = base.dists.t.cdf( 2.0, -1.0 )\n","base.dists.t.cdf.factory":"var mycdf = base.dists.t.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.t.entropy":"var v = base.dists.t.entropy( 11.0 )\nv = base.dists.t.entropy( 4.5 )\n","base.dists.t.kurtosis":"var v = base.dists.t.kurtosis( 11.0 )\nv = base.dists.t.kurtosis( 4.5 )\n","base.dists.t.logcdf":"var y = base.dists.t.logcdf( 2.0, 0.1 )\ny = base.dists.t.logcdf( 1.0, 2.0 )\ny = base.dists.t.logcdf( -1.0, 4.0 )\ny = base.dists.t.logcdf( NaN, 1.0 )\ny = base.dists.t.logcdf( 0.0, NaN )\ny = base.dists.t.logcdf( 2.0, -1.0 )\n","base.dists.t.logcdf.factory":"var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.t.logpdf":"var y = base.dists.t.logpdf( 0.3, 4.0 )\ny = base.dists.t.logpdf( 2.0, 0.7 )\ny = base.dists.t.logpdf( -1.0, 0.5 )\ny = base.dists.t.logpdf( 0.0, NaN )\ny = base.dists.t.logpdf( NaN, 2.0 )\ny = base.dists.t.logpdf( 2.0, -1.0 )\n","base.dists.t.logpdf.factory":"var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\nvar y = mylogPDF( 1.0 )\n","base.dists.t.mean":"var v = base.dists.t.mean( 11.0 )\nv = base.dists.t.mean( 4.5 )\n","base.dists.t.median":"var v = base.dists.t.median( 11.0 )\nv = base.dists.t.median( 4.5 )\n","base.dists.t.mode":"var v = base.dists.t.mode( 11.0 )\nv = base.dists.t.mode( 4.5 )\n","base.dists.t.pdf":"var y = base.dists.t.pdf( 0.3, 4.0 )\ny = base.dists.t.pdf( 2.0, 0.7 )\ny = base.dists.t.pdf( -1.0, 0.5 )\ny = base.dists.t.pdf( 0.0, NaN )\ny = base.dists.t.pdf( NaN, 2.0 )\ny = base.dists.t.pdf( 2.0, -1.0 )\n","base.dists.t.pdf.factory":"var myPDF = base.dists.t.pdf.factory( 3.0 );\nvar y = myPDF( 1.0 )\n","base.dists.t.quantile":"var y = base.dists.t.quantile( 0.8, 1.0 )\ny = base.dists.t.quantile( 0.1, 1.0 )\ny = base.dists.t.quantile( 0.5, 0.1 )\ny = base.dists.t.quantile( -0.2, 0.1 )\ny = base.dists.t.quantile( NaN, 1.0 )\ny = base.dists.t.quantile( 0.0, NaN )\ny = base.dists.t.quantile( 0.5, -1.0 )\n","base.dists.t.quantile.factory":"var myQuantile = base.dists.t.quantile.factory( 4.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.t.skewness":"var v = base.dists.t.skewness( 11.0 )\nv = base.dists.t.skewness( 4.5 )\n","base.dists.t.stdev":"var v = base.dists.t.stdev( 9.0 )\nv = base.dists.t.stdev( 4.5 )\n","base.dists.t.T":"var t = base.dists.t.T( 6.0 );\nt.v\nt.entropy\nt.kurtosis\nt.mean\nt.median\nt.mode\nt.skewness\nt.stdev\nt.variance\nt.cdf( 1.0 )\nt.logcdf( 1.0 )\nt.logpdf( 1.5 )\nt.pdf( 1.5 )\nt.quantile( 0.8 )\n","base.dists.t.variance":"var v = base.dists.t.variance( 9.0 )\nv = base.dists.t.variance( 4.5 )\n","base.dists.triangular.cdf":"var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.cdf.factory":"var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.triangular.entropy":"var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n","base.dists.triangular.kurtosis":"var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n","base.dists.triangular.logcdf":"var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logcdf.factory":"var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.triangular.logpdf":"var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logpdf.factory":"var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\nvar y = mylogpdf( 2.0 )\ny = mylogpdf( 12.0 )\n","base.dists.triangular.mean":"var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n","base.dists.triangular.median":"var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.median( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n","base.dists.triangular.mgf":"var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n","base.dists.triangular.mgf.factory":"var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\nvar y = mymgf( -1.0 )\ny = mymgf( 2.0 )\n","base.dists.triangular.mode":"var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n","base.dists.triangular.pdf":"var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.pdf.factory":"var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\nvar y = mypdf( 2.0 )\ny = mypdf( 12.0 )\n","base.dists.triangular.quantile":"var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\ny = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n","base.dists.triangular.quantile.factory":"var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\n","base.dists.triangular.skewness":"var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n","base.dists.triangular.stdev":"var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n","base.dists.triangular.Triangular":"var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\ntriangular.a\ntriangular.b\ntriangular.c\ntriangular.entropy\ntriangular.kurtosis\ntriangular.mean\ntriangular.median\ntriangular.mode\ntriangular.skewness\ntriangular.stdev\ntriangular.variance\ntriangular.cdf( 0.8 )\ntriangular.logcdf( 0.8 )\ntriangular.logpdf( 0.8 )\ntriangular.mgf( 0.8 )\ntriangular.pdf( 0.8 )\ntriangular.quantile( 0.8 )\n","base.dists.triangular.variance":"var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n","base.dists.uniform.cdf":"var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.cdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.cdf.factory":"var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.uniform.entropy":"var v = base.dists.uniform.entropy( 0.0, 1.0 )\nv = base.dists.uniform.entropy( 4.0, 12.0 )\nv = base.dists.uniform.entropy( 2.0, 8.0 )\n","base.dists.uniform.kurtosis":"var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\nv = base.dists.uniform.kurtosis( 4.0, 12.0 )\nv = base.dists.uniform.kurtosis( 2.0, 8.0 )\n","base.dists.uniform.logcdf":"var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.logcdf.factory":"var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.uniform.logpdf":"var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.logpdf.factory":"var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.uniform.mean":"var v = base.dists.uniform.mean( 0.0, 1.0 )\nv = base.dists.uniform.mean( 4.0, 12.0 )\nv = base.dists.uniform.mean( 2.0, 8.0 )\n","base.dists.uniform.median":"var v = base.dists.uniform.median( 0.0, 1.0 )\nv = base.dists.uniform.median( 4.0, 12.0 )\nv = base.dists.uniform.median( 2.0, 8.0 )\n","base.dists.uniform.mgf":"var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\ny = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\ny = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n","base.dists.uniform.mgf.factory":"var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.uniform.pdf":"var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.pdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.pdf.factory":"var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.uniform.quantile":"var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\ny = base.dists.uniform.quantile( 0.0, 0.0, NaN )\ny = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n","base.dists.uniform.quantile.factory":"var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.uniform.skewness":"var v = base.dists.uniform.skewness( 0.0, 1.0 )\nv = base.dists.uniform.skewness( 4.0, 12.0 )\nv = base.dists.uniform.skewness( 2.0, 8.0 )\n","base.dists.uniform.stdev":"var v = base.dists.uniform.stdev( 0.0, 1.0 )\nv = base.dists.uniform.stdev( 4.0, 12.0 )\nv = base.dists.uniform.stdev( 2.0, 8.0 )\n","base.dists.uniform.Uniform":"var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\nuniform.a\nuniform.b\nuniform.entropy\nuniform.kurtosis\nuniform.mean\nuniform.median\nuniform.skewness\nuniform.stdev\nuniform.variance\nuniform.cdf( 0.8 )\nuniform.logcdf( 0.5 )\nuniform.logpdf( 1.0 )\nuniform.mgf( 0.8 )\nuniform.pdf( 0.8 )\nuniform.quantile( 0.8 )\n","base.dists.uniform.variance":"var v = base.dists.uniform.variance( 0.0, 1.0 )\nv = base.dists.uniform.variance( 4.0, 12.0 )\nv = base.dists.uniform.variance( 2.0, 8.0 )\n","base.dists.weibull.cdf":"var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.cdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.cdf.factory":"var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\nvar y = myCDF( 12.0 )\n","base.dists.weibull.entropy":"var v = base.dists.weibull.entropy( 1.0, 1.0 )\nv = base.dists.weibull.entropy( 4.0, 12.0 )\nv = base.dists.weibull.entropy( 8.0, 2.0 )\n","base.dists.weibull.kurtosis":"var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\nv = base.dists.weibull.kurtosis( 4.0, 12.0 )\nv = base.dists.weibull.kurtosis( 8.0, 2.0 )\n","base.dists.weibull.logcdf":"var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logcdf.factory":"var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\nvar y = mylogcdf( 12.0 )\n","base.dists.weibull.logpdf":"var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logpdf.factory":"var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\ny = mylofpdf( 7.0 )\n","base.dists.weibull.mean":"var v = base.dists.weibull.mean( 1.0, 1.0 )\nv = base.dists.weibull.mean( 4.0, 12.0 )\nv = base.dists.weibull.mean( 8.0, 2.0 )\n","base.dists.weibull.median":"var v = base.dists.weibull.median( 1.0, 1.0 )\nv = base.dists.weibull.median( 4.0, 12.0 )\nv = base.dists.weibull.median( 8.0, 2.0 )\n","base.dists.weibull.mgf":"var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\ny = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\ny = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\ny = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.mgf( 0.0, 1.0, NaN )\ny = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\ny = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n","base.dists.weibull.mgf.factory":"var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.08 )\n","base.dists.weibull.mode":"var v = base.dists.weibull.mode( 1.0, 1.0 )\nv = base.dists.weibull.mode( 4.0, 12.0 )\nv = base.dists.weibull.mode( 8.0, 2.0 )\n","base.dists.weibull.pdf":"var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.pdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.pdf.factory":"var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\nvar y = myPDF( 7.0 )\n","base.dists.weibull.quantile":"var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\ny = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\ny = base.dists.weibull.quantile( 0.0, 0.0, NaN )\ny = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n","base.dists.weibull.quantile.factory":"var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.weibull.skewness":"var v = base.dists.weibull.skewness( 1.0, 1.0 )\nv = base.dists.weibull.skewness( 4.0, 12.0 )\nv = base.dists.weibull.skewness( 8.0, 2.0 )\n","base.dists.weibull.stdev":"var v = base.dists.weibull.stdev( 1.0, 1.0 )\nv = base.dists.weibull.stdev( 4.0, 12.0 )\nv = base.dists.weibull.stdev( 8.0, 2.0 )\n","base.dists.weibull.variance":"var v = base.dists.weibull.variance( 1.0, 1.0 )\nv = base.dists.weibull.variance( 4.0, 12.0 )\nv = base.dists.weibull.variance( 8.0, 2.0 )\n","base.dists.weibull.Weibull":"var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\nweibull.k\nweibull.lambda\nweibull.entropy\nweibull.kurtosis\nweibull.mean\nweibull.median\nweibull.mode\nweibull.skewness\nweibull.stdev\nweibull.variance\nweibull.cdf( 3.0 )\nweibull.logcdf( 3.0 )\nweibull.logpdf( 1.0 )\nweibull.mgf( -0.5 )\nweibull.pdf( 3.0 )\nweibull.quantile( 0.8 )\n","base.ellipe":"var y = base.ellipe( 0.5 )\ny = base.ellipe( -1.0 )\ny = base.ellipe( 2.0 )\ny = base.ellipe( PINF )\ny = base.ellipe( NINF )\ny = base.ellipe( NaN )\n","base.ellipj":"var v = base.ellipj( 0.3, 0.5 )\nv = base.ellipj( 0.0, 0.0 )\nv = base.ellipj( Infinity, 1.0 )\nv = base.ellipj( 0.0, -2.0)\nv = base.ellipj( NaN, NaN )\n","base.ellipj.assign":"var out = new Float64Array( 4 );\nvar v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.ellipj.sn":"var v = base.ellipj.sn( 0.3, 0.5 )\n","base.ellipj.cn":"var v = base.ellipj.cn( 0.3, 0.5 )\n","base.ellipj.dn":"var v = base.ellipj.dn( 0.3, 0.5 )\n","base.ellipj.am":"var v = base.ellipj.am( 0.3, 0.5 )\n","base.ellipk":"var y = base.ellipk( 0.5 )\ny = base.ellipk( -1.0 )\ny = base.ellipk( 2.0 )\ny = base.ellipk( PINF )\ny = base.ellipk( NINF )\ny = base.ellipk( NaN )\n","base.endsWith":"var bool = base.endsWith( 'beep', 'ep', 4 )\nbool = base.endsWith( 'Beep', 'op', 4 )\nbool = base.endsWith( 'Beep', 'ee', 3 )\nbool = base.endsWith( 'Beep', 'ee', -1 )\nbool = base.endsWith( 'beep', '', 4 )\n","base.epsdiff":"var d = base.epsdiff( 12.15, 12.149999999999999 )\nd = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\nfunction scale( x, y ) { return ( x > y ) ? y : x; };\nd = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n","base.erf":"var y = base.erf( 2.0 )\ny = base.erf( -1.0 )\ny = base.erf( -0.0 )\ny = base.erf( NaN )\n","base.erfc":"var y = base.erfc( 2.0 )\ny = base.erfc( -1.0 )\ny = base.erfc( 0.0 )\ny = base.erfc( PINF )\ny = base.erfc( NINF )\ny = base.erfc( NaN )\n","base.erfcinv":"var y = base.erfcinv( 0.5 )\ny = base.erfcinv( 0.8 )\ny = base.erfcinv( 0.0 )\ny = base.erfcinv( 2.0 )\ny = base.erfcinv( NaN )\n","base.erfcx":"var y = base.erfcx( 1.0 )\ny = base.erfcx( -1.0 )\ny = base.erfcx( 0.0 )\ny = base.erfcx( NaN )\n","base.erfinv":"var y = base.erfinv( 0.5 )\ny = base.erfinv( 0.8 )\ny = base.erfinv( 0.0 )\ny = base.erfinv( -0.0 )\ny = base.erfinv( -1.0 )\ny = base.erfinv( 1.0 )\ny = base.erfinv( NaN )\n","base.eta":"var y = base.eta( 0.0 )\ny = base.eta( -1.0 )\ny = base.eta( 1.0 )\ny = base.eta( 3.14 )\ny = base.eta( NaN )\n","base.evalpoly":"var arr = [ 3.0, 2.0, 1.0 ];\nvar v = base.evalpoly( arr, 10.0 )\n","base.evalpoly.factory":"var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\nvar v = f( 10.0 )\nv = f( 5.0 )\n","base.evalrational":"var P = [ -6.0, -5.0, 4.0, 2.0 ];\nvar Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\nvar v = base.evalrational( P, Q, 6.0 )\n","base.evalrational.factory":"var P = [ 20.0, 8.0, 3.0 ];\nvar Q = [ 10.0, 9.0, 1.0 ];\nvar f = base.evalrational.factory( P, Q );\nvar v = f( 10.0 )\nv = f( 2.0 )\n","base.exp":"var y = base.exp( 4.0 )\ny = base.exp( -9.0 )\ny = base.exp( 0.0 )\ny = base.exp( NaN )\n","base.exp2":"var y = base.exp2( 3.0 )\ny = base.exp2( -9.0 )\ny = base.exp2( 0.0 )\ny = base.exp2( NaN )\n","base.exp10":"var y = base.exp10( 3.0 )\ny = base.exp10( -9.0 )\ny = base.exp10( 0.0 )\ny = base.exp10( NaN )\n","base.expit":"var y = base.expit( 0.0 )\ny = base.expit( 1.0 )\ny = base.expit( -1.0 )\ny = base.expit( Infinity )\ny = base.expit( NaN )\n","base.expm1":"var y = base.expm1( 0.2 )\ny = base.expm1( -9.0 )\ny = base.expm1( 0.0 )\ny = base.expm1( NaN )\n","base.expm1rel":"var y = base.expm1rel( 0.0 )\ny = base.expm1rel( 1.0 )\ny = base.expm1rel( -1.0 )\ny = base.expm1rel( NaN )\n","base.exponent":"var exponent = base.exponent( 3.14e-307 )\nexponent = base.exponent( -3.14 )\nexponent = base.exponent( 0.0 )\nexponent = base.exponent( NaN )\n","base.exponentf":"var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\nexponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\nexponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\nexponent = base.exponentf( 0.0 )\nexponent = base.exponentf( NaN )\n","base.factorial":"var y = base.factorial( 3.0 )\ny = base.factorial( -1.5 )\ny = base.factorial( -0.5 )\ny = base.factorial( 0.5 )\ny = base.factorial( -10.0 )\ny = base.factorial( 171.0 )\ny = base.factorial( NaN )\n","base.factorial2":"var y = base.factorial2( 3 )\ny = base.factorial2( 5 )\ny = base.factorial2( 6 )\ny = base.factorial2( 301 )\ny = base.factorial2( NaN )\n","base.factorialln":"var y = base.factorialln( 3.0 )\ny = base.factorialln( 2.4 )\ny = base.factorialln( -1.0 )\ny = base.factorialln( -1.5 )\ny = base.factorialln( NaN )\n","base.fallingFactorial":"var v = base.fallingFactorial( 0.9, 5 )\nv = base.fallingFactorial( -9.0, 3 )\nv = base.fallingFactorial( 0.0, 2 )\nv = base.fallingFactorial( 3.0, -2 )\n","base.fibonacci":"var y = base.fibonacci( 0 )\ny = base.fibonacci( 1 )\ny = base.fibonacci( 2 )\ny = base.fibonacci( 3 )\ny = base.fibonacci( 4 )\ny = base.fibonacci( 79 )\ny = base.fibonacci( NaN )\n","base.fibonacciIndex":"var n = base.fibonacciIndex( 2 )\nn = base.fibonacciIndex( 3 )\nn = base.fibonacciIndex( 5 )\nn = base.fibonacciIndex( NaN )\nn = base.fibonacciIndex( 1 )\n","base.fibpoly":"var v = base.fibpoly( 5, 2.0 )\n","base.fibpoly.factory":"var polyval = base.fibpoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.firstCodePoint":"var out = base.firstCodePoint( 'beep', 1 )\nout = base.firstCodePoint( 'Boop', 1 )\nout = base.firstCodePoint( 'foo bar', 5 )\n","base.firstCodeUnit":"var out = base.firstCodeUnit( 'beep', 1 )\nout = base.firstCodeUnit( 'Boop', 1 )\nout = base.firstCodeUnit( 'foo bar', 5 )\n","base.firstGraphemeCluster":"var out = base.firstGraphemeCluster( 'beep', 1 )\nout = base.firstGraphemeCluster( 'Boop', 1 )\nout = base.firstGraphemeCluster( 'foo bar', 5 )\n","base.flipsign":"var z = base.flipsign( -3.0, 10.0 )\nz = base.flipsign( -3.0, -1.0 )\nz = base.flipsign( 1.0, -0.0 )\nz = base.flipsign( -3.0, -0.0 )\nz = base.flipsign( -0.0, 1.0 )\nz = base.flipsign( 0.0, -1.0 )\n","base.flipsignf":"var z = base.flipsignf( -3.0, 10.0 )\nz = base.flipsignf( -3.0, -1.0 )\nz = base.flipsignf( 1.0, -0.0 )\nz = base.flipsignf( -3.0, -0.0 )\nz = base.flipsignf( -0.0, 1.0 )\nz = base.flipsignf( 0.0, -1.0 )\n","base.float32ToInt32":"var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\ny = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( NaN ) )\ny = base.float32ToInt32( FLOAT32_PINF )\ny = base.float32ToInt32( FLOAT32_NINF )\n","base.float32ToUint32":"var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\ny = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( NaN ) )\ny = base.float32ToUint32( FLOAT32_PINF )\ny = base.float32ToUint32( FLOAT32_NINF )\n","base.float64ToFloat32":"var y = base.float64ToFloat32( 1.337 )\n","base.float64ToInt32":"var y = base.float64ToInt32( 4294967295.0 )\ny = base.float64ToInt32( 3.14 )\ny = base.float64ToInt32( -3.14 )\ny = base.float64ToInt32( NaN )\ny = base.float64ToInt32( PINF )\ny = base.float64ToInt32( NINF )\n","base.float64ToInt64Bytes":"var y = base.float64ToInt64Bytes( 4294967297.0 )\n","base.float64ToInt64Bytes.assign":"var out = new Uint8Array( 16 );\nvar y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n","base.float64ToUint32":"var y = base.float64ToUint32( 4294967297.0 )\ny = base.float64ToUint32( 3.14 )\ny = base.float64ToUint32( -3.14 )\ny = base.float64ToUint32( NaN )\ny = base.float64ToUint32( PINF )\ny = base.float64ToUint32( NINF )\n","base.floor":"var y = base.floor( 3.14 )\ny = base.floor( -4.2 )\ny = base.floor( -4.6 )\ny = base.floor( 9.5 )\ny = base.floor( -0.0 )\n","base.floor2":"var y = base.floor2( 3.14 )\ny = base.floor2( -4.2 )\ny = base.floor2( -4.6 )\ny = base.floor2( 9.5 )\ny = base.floor2( 13.0 )\ny = base.floor2( -13.0 )\ny = base.floor2( -0.0 )\n","base.floor10":"var y = base.floor10( 3.14 )\ny = base.floor10( -4.2 )\ny = base.floor10( -4.6 )\ny = base.floor10( 9.5 )\ny = base.floor10( 13.0 )\ny = base.floor10( -13.0 )\ny = base.floor10( -0.0 )\n","base.floorb":"var y = base.floorb( 3.14159, -4, 10 )\ny = base.floorb( 3.14159, 0, 2 )\ny = base.floorb( 5.0, 1, 2 )\n","base.floorf":"var y = base.floorf( 3.14 )\ny = base.floorf( -4.2 )\ny = base.floorf( -4.6 )\ny = base.floorf( 9.5 )\ny = base.floorf( -0.0 )\n","base.floorn":"var y = base.floorn( 3.14159, -4 )\ny = base.floorn( 3.14159, 0 )\ny = base.floorn( 12368.0, 3 )\n","base.floorsd":"var y = base.floorsd( 3.14159, 5, 10 )\ny = base.floorsd( 3.14159, 1, 10 )\ny = base.floorsd( 12368.0, 2, 10 )\ny = base.floorsd( 0.0313, 2, 2 )\n","base.forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachChar( 'hello world!', fcn );\nn\n","base.forEachCodePoint":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePoint( 'hello world!', fcn );\nn\n","base.forEachCodePointRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePointRight( 'hello world!', fcn );\nn\n","base.forEachGraphemeCluster":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachGraphemeCluster( 'hello world!', fcn );\nn\n","base.forEachRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachRight( 'hello world!', fcn );\nn\n","base.formatInterpolate":"var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\nout = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\nout = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n","base.formatTokenize":"var out = base.formatTokenize( 'Hello %s!' )\nout = base.formatTokenize( '%s %s %d' )\nout = base.formatTokenize( 'Pi: %.2f' )\n","base.fresnel":"var y = base.fresnel( 0.0 )\ny = base.fresnel( 1.0 )\ny = base.fresnel( PINF )\ny = base.fresnel( NINF )\ny = base.fresnel( NaN )\n","base.fresnel.assign":"var out = new Float64Array( 2 );\nvar v = base.fresnel.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.fresnelc":"var y = base.fresnelc( 0.0 )\ny = base.fresnelc( 1.0 )\ny = base.fresnelc( PINF )\ny = base.fresnelc( NINF )\ny = base.fresnelc( NaN )\n","base.fresnels":"var y = base.fresnels( 0.0 )\ny = base.fresnels( 1.0 )\ny = base.fresnels( PINF )\ny = base.fresnels( NINF )\ny = base.fresnels( NaN )\n","base.frexp":"var out = base.frexp( 4.0 )\nout = base.frexp( 0.0 )\nout = base.frexp( -0.0 )\nout = base.frexp( NaN )\nout = base.frexp( PINF )\nout = base.frexp( NINF )\n","base.frexp.assign":"var out = new Float64Array( 2 );\nvar y = base.frexp.assign( 4.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.fromBinaryString":"var bstr;\nbstr = '0100000000010000000000000000000000000000000000000000000000000000';\nvar val = base.fromBinaryString( bstr )\nbstr = '0100000000001001001000011111101101010100010001000010110100011000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111100001110011001111001110000101111010111100100010100000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000001100011010011';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000001';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111111000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\n","base.fromBinaryStringf":"var bstr = '01000000100000000000000000000000';\nvar val = base.fromBinaryStringf( bstr )\nbstr = '01000000010010010000111111011011';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111011011000011101000110011';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000010110';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000001';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111110000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\n","base.fromBinaryStringUint8":"var bstr = '01010101';\nvar val = base.fromBinaryStringUint8( bstr )\nbstr = '00000000';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '00000010';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '11111111';\nval = base.fromBinaryStringUint8( bstr )\n","base.fromBinaryStringUint16":"var bstr = '0101010101010101';\nvar val = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000000';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000010';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '1111111111111111';\nval = base.fromBinaryStringUint16( bstr )\n","base.fromBinaryStringUint32":"var bstr = '01010101010101010101010101010101';\nvar val = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000010';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '11111111111111111111111111111111';\nval = base.fromBinaryStringUint32( bstr )\n","base.fromInt64Bytes":"var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\nvar y = base.fromInt64Bytes( bytes, 1, 0 )\n","base.fromWordf":"var word = 1068180177; // => 0 01111111 01010110010001011010001\nvar f32 = base.fromWordf( word ) // when printed, promoted to float64\n","base.fromWords":"var v = base.fromWords( 1774486211, 2479577218 )\nv = base.fromWords( 3221823995, 1413754136 )\nv = base.fromWords( 0, 0 )\nv = base.fromWords( 2147483648, 0 )\nv = base.fromWords( 2146959360, 0 )\nv = base.fromWords( 2146435072, 0 )\nv = base.fromWords( 4293918720, 0 )\n","base.gamma":"var y = base.gamma( 4.0 )\ny = base.gamma( -1.5 )\ny = base.gamma( -0.5 )\ny = base.gamma( 0.5 )\ny = base.gamma( 0.0 )\ny = base.gamma( -0.0 )\ny = base.gamma( NaN )\n","base.gamma1pm1":"var y = base.gamma1pm1( 0.2 )\ny = base.gamma1pm1( -6.7 )\ny = base.gamma1pm1( 0.0 )\ny = base.gamma1pm1( NaN )\n","base.gammaDeltaRatio":"var y = base.gammaDeltaRatio( 2.0, 3.0 )\ny = base.gammaDeltaRatio( 4.0, 0.5 )\ny = base.gammaDeltaRatio( 100.0, 0.0 )\ny = base.gammaDeltaRatio( NaN, 3.0 )\ny = base.gammaDeltaRatio( 5.0, NaN )\ny = base.gammaDeltaRatio( NaN, NaN )\n","base.gammainc":"var y = base.gammainc( 6.0, 2.0 )\ny = base.gammainc( 1.0, 2.0, true, true )\ny = base.gammainc( 7.0, 5.0 )\ny = base.gammainc( 7.0, 5.0, false )\ny = base.gammainc( NaN, 2.0 )\ny = base.gammainc( 6.0, NaN )\n","base.gammaincinv":"var y = base.gammaincinv( 0.5, 2.0 )\ny = base.gammaincinv( 0.1, 10.0 )\ny = base.gammaincinv( 0.75, 3.0 )\ny = base.gammaincinv( 0.75, 3.0, true )\ny = base.gammaincinv( 0.75, NaN )\ny = base.gammaincinv( NaN, 3.0 )\n","base.gammaLanczosSum":"var y = base.gammaLanczosSum( 4.0 )\ny = base.gammaLanczosSum( -1.5 )\ny = base.gammaLanczosSum( -0.5 )\ny = base.gammaLanczosSum( 0.5 )\ny = base.gammaLanczosSum( 0.0 )\ny = base.gammaLanczosSum( NaN )\n","base.gammaLanczosSumExpGScaled":"var y = base.gammaLanczosSumExpGScaled( 4.0 )\ny = base.gammaLanczosSumExpGScaled( -1.5 )\ny = base.gammaLanczosSumExpGScaled( -0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.0 )\ny = base.gammaLanczosSumExpGScaled( NaN )\n","base.gammaln":"var y = base.gammaln( 1.0 )\ny = base.gammaln( 2.0 )\ny = base.gammaln( 4.0 )\ny = base.gammaln( -0.5 )\ny = base.gammaln( 0.5 )\ny = base.gammaln( 0.0 )\ny = base.gammaln( NaN )\n","base.gammasgn":"var y = base.gammasgn( 1.0 )\ny = base.gammasgn( -2.5 )\ny = base.gammasgn( 0.0 )\ny = base.gammasgn( NaN )\n","base.gcd":"var v = base.gcd( 48, 18 )\n","base.getHighWord":"var w = base.getHighWord( 3.14e201 )\n","base.getLowWord":"var w = base.getLowWord( 3.14e201 )\n","base.hacovercos":"var y = base.hacovercos( 3.14 )\ny = base.hacovercos( -4.2 )\ny = base.hacovercos( -4.6 )\ny = base.hacovercos( 9.5 )\ny = base.hacovercos( -0.0 )\n","base.hacoversin":"var y = base.hacoversin( 3.14 )\ny = base.hacoversin( -4.2 )\ny = base.hacoversin( -4.6 )\ny = base.hacoversin( 9.5 )\ny = base.hacoversin( -0.0 )\n","base.havercos":"var y = base.havercos( 3.14 )\ny = base.havercos( -4.2 )\ny = base.havercos( -4.6 )\ny = base.havercos( 9.5 )\ny = base.havercos( -0.0 )\n","base.haversin":"var y = base.haversin( 3.14 )\ny = base.haversin( -4.2 )\ny = base.haversin( -4.6 )\ny = base.haversin( 9.5 )\ny = base.haversin( -0.0 )\n","base.headercase":"var out = base.headercase( 'Hello World!' )\nout = base.headercase( 'beep boop' )\n","base.heaviside":"var y = base.heaviside( 3.14 )\ny = base.heaviside( -3.14 )\ny = base.heaviside( 0.0 )\ny = base.heaviside( 0.0, 'half-maximum' )\ny = base.heaviside( 0.0, 'left-continuous' )\ny = base.heaviside( 0.0, 'right-continuous' )\n","base.hermitepoly":"var y = base.hermitepoly( 1, 0.5 )\ny = base.hermitepoly( -1, 0.5 )\ny = base.hermitepoly( 0, 0.5 )\ny = base.hermitepoly( 2, 0.5 )\n","base.hermitepoly.factory":"var polyval = base.hermitepoly.factory( 2 );\nvar v = polyval( 0.5 )\n","base.hypot":"var h = base.hypot( -5.0, 12.0 )\nh = base.hypot( NaN, 12.0 )\nh = base.hypot( -0.0, -0.0 )\n","base.hypotf":"var h = base.hypotf( -5.0, 12.0 )\nh = base.hypotf( NaN, 12.0 )\nh = base.hypotf( -0.0, -0.0 )\n","base.identity":"var y = base.identity( -1.0 )\ny = base.identity( 2.0 )\ny = base.identity( 0.0 )\ny = base.identity( -0.0 )\ny = base.identity( NaN )\n","base.identityf":"var y = base.identityf( -1.0 )\ny = base.identityf( 2.0 )\ny = base.identityf( 0.0 )\ny = base.identityf( -0.0 )\ny = base.identityf( NaN )\n","base.imul":"var v = base.imul( -10|0, 4|0 )\n","base.imuldw":"var v = base.imuldw( 1, 10 )\n","base.imuldw.assign":"var out = [ 0, 0 ];\nvar v = base.imuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.int2slice":"var s = base.int2slice( -1, 5, false );\ns.start\ns.stop\ns.step\n","base.int32ToUint32":"var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\ny = base.int32ToUint32( base.float64ToInt32( 3 ) )\n","base.inv":"var y = base.inv( -1.0 )\ny = base.inv( 2.0 )\ny = base.inv( 0.0 )\ny = base.inv( -0.0 )\ny = base.inv( NaN )\n","base.invcase":"var out = base.invcase( 'Hello World!' )\nout = base.invcase( 'I am A tiny LITTLE teapot' )\n","base.invf":"var y = base.invf( -1.0 )\ny = base.invf( 2.0 )\ny = base.invf( 0.0 )\ny = base.invf( -0.0 )\ny = base.invf( NaN )\n","base.isComposite":"var bool = base.isComposite( 10.0 )\nbool = base.isComposite( 11.0 )\n","base.isCoprime":"var bool = base.isCoprime( 14.0, 15.0 )\nbool = base.isCoprime( 14.0, 21.0 )\n","base.isEven":"var bool = base.isEven( 5.0 )\nbool = base.isEven( -2.0 )\nbool = base.isEven( 0.0 )\nbool = base.isEven( NaN )\n","base.isEvenInt32":"var bool = base.isEvenInt32( 5 )\nbool = base.isEvenInt32( -2 )\nbool = base.isEvenInt32( 0 )\n","base.isFinite":"var bool = base.isFinite( 5.0 )\nbool = base.isFinite( -2.0e64 )\nbool = base.isFinite( PINF )\nbool = base.isFinite( NINF )\n","base.isFinitef":"var bool = base.isFinitef( 5.0 )\nbool = base.isFinitef( -1.0e38 )\nbool = base.isFinitef( FLOAT32_PINF )\nbool = base.isFinitef( FLOAT32_NINF )\n","base.isInfinite":"var bool = base.isInfinite( PINF )\nbool = base.isInfinite( NINF )\nbool = base.isInfinite( 5.0 )\nbool = base.isInfinite( NaN )\n","base.isInfinitef":"var bool = base.isInfinitef( FLOAT32_PINF )\nbool = base.isInfinitef( FLOAT32_NINF )\nbool = base.isInfinitef( 5.0 )\nbool = base.isInfinitef( NaN )\n","base.isInteger":"var bool = base.isInteger( 1.0 )\nbool = base.isInteger( 3.14 )\n","base.isnan":"var bool = base.isnan( NaN )\nbool = base.isnan( 7.0 )\n","base.isnanf":"var bool = base.isnanf( NaN )\nbool = base.isnanf( 7.0 )\n","base.isNegativeFinite":"var bool = base.isNegativeFinite( -3.14 )\nbool = base.isNegativeFinite( -Infinity )\nbool = base.isNegativeFinite( 2.0 )\nbool = base.isNegativeFinite( NaN )\nbool = base.isNegativeFinite( -0.0 )\n","base.isNegativeInteger":"var bool = base.isNegativeInteger( -1.0 )\nbool = base.isNegativeInteger( 0.0 )\nbool = base.isNegativeInteger( 10.0 )\n","base.isNegativeZero":"var bool = base.isNegativeZero( -0.0 )\nbool = base.isNegativeZero( 0.0 )\n","base.isNegativeZerof":"var bool = base.isNegativeZerof( -0.0 )\nbool = base.isNegativeZerof( 0.0 )\n","base.isNonNegativeFinite":"var out = base.isNonNegativeFinite( 5.0 )\nout = base.isNonNegativeFinite( 3.14 )\nout = base.isNonNegativeFinite( 0.0 )\nout = base.isNonNegativeFinite( Infinity )\nout = base.isNonNegativeFinite( -3.14 )\nout = base.isNonNegativeFinite( NaN )\n","base.isNonNegativeInteger":"var bool = base.isNonNegativeInteger( 1.0 )\nbool = base.isNonNegativeInteger( 0.0 )\nbool = base.isNonNegativeInteger( -10.0 )\n","base.isNonPositiveFinite":"var bool = base.isNonPositiveFinite( -3.14 )\nvar bool = base.isNonPositiveFinite( 0.0 )\nvar bool = base.isNonPositiveFinite( -Infinity )\nvar bool = base.isNonPositiveFinite( 3.14 )\nvar bool = base.isNonPositiveFinite( NaN )\n","base.isNonPositiveInteger":"var bool = base.isNonPositiveInteger( -1.0 )\nbool = base.isNonPositiveInteger( 0.0 )\nbool = base.isNonPositiveInteger( 10.0 )\n","base.isOdd":"var bool = base.isOdd( 5.0 )\nbool = base.isOdd( -2.0 )\nbool = base.isOdd( 0.0 )\nbool = base.isOdd( NaN )\n","base.isOddInt32":"var bool = base.isOddInt32( 5 )\nbool = base.isOddInt32( -2 )\nbool = base.isOddInt32( 0 )\n","base.isPositiveFinite":"var bool = base.isPositiveFinite( 5.0 )\nbool = base.isPositiveFinite( 3.14 )\nbool = base.isPositiveFinite( 0.0 )\nbool = base.isPositiveFinite( Infinity )\nbool = base.isPositiveFinite( -3.14 )\nbool = base.isPositiveFinite( NaN )\n","base.isPositiveInteger":"var bool = base.isPositiveInteger( 1.0 )\nbool = base.isPositiveInteger( 0.0 )\nbool = base.isPositiveInteger( -10.0 )\n","base.isPositiveZero":"var bool = base.isPositiveZero( 0.0 )\nbool = base.isPositiveZero( -0.0 )\n","base.isPositiveZerof":"var bool = base.isPositiveZerof( 0.0 )\nbool = base.isPositiveZerof( -0.0 )\n","base.isPow2Uint32":"var bool = base.isPow2Uint32( 2 )\nbool = base.isPow2Uint32( 5 )\n","base.isPrime":"var bool = base.isPrime( 11.0 )\nbool = base.isPrime( 3.14 )\n","base.isProbability":"var bool = base.isProbability( 0.5 )\nbool = base.isProbability( 3.14 )\nbool = base.isProbability( NaN )\n","base.isSafeInteger":"var bool = base.isSafeInteger( 1.0 )\nbool = base.isSafeInteger( 2.0e200 )\nbool = base.isSafeInteger( 3.14 )\n","base.kebabcase":"var out = base.kebabcase( 'Hello World!' )\nout = base.kebabcase( 'I am a tiny little teapot' )\n","base.kernelBetainc":"var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\nout = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n","base.kernelBetainc.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\nvar bool = ( v === out )\n","base.kernelBetaincinv":"var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\ny = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n","base.kernelCos":"var out = base.kernelCos( 0.0, 0.0 )\nout = base.kernelCos( PI/6.0, 0.0 )\nout = base.kernelCos( 0.785, -1.144e-17 )\nout = base.kernelCos( NaN )\n","base.kernelLog1p":"var y = base.kernelLog1p( 1.0 )\ny = base.kernelLog1p( 1.4142135623730951 )\ny = base.kernelLog1p( NaN )\n","base.kernelSin":"var y = base.kernelSin( 0.0, 0.0 )\ny = base.kernelSin( PI/6.0, 0.0 )\ny = base.kernelSin( 0.619, 9.279e-18 )\ny = base.kernelSin( NaN, 0.0 )\ny = base.kernelSin( 2.0, NaN )\ny = base.kernelSin( NaN, NaN )\n","base.kernelTan":"var out = base.kernelTan( PI/4.0, 0.0, 1 )\nout = base.kernelTan( PI/4.0, 0.0, -1 )\nout = base.kernelTan( PI/6.0, 0.0, 1 )\nout = base.kernelTan( 0.664, 5.288e-17, 1 )\nout = base.kernelTan( NaN, 0.0, 1 )\nout = base.kernelTan( 3.0, NaN, 1 )\nout = base.kernelTan( 3.0, 0.0, NaN )\n","base.kroneckerDelta":"var y = base.kroneckerDelta( 3.14, 0.0 )\ny = base.kroneckerDelta( 3.14, 3.14 )\n","base.kroneckerDeltaf":"var y = base.kroneckerDeltaf( 3.14, 0.0 )\ny = base.kroneckerDeltaf( 3.14, 3.14 )\n","base.labs":"var v = base.labs( -1|0 )\nv = base.labs( 2|0 )\nv = base.labs( 0|0 )\n","base.last":"var out = base.last( 'hello', 1 )\nout = base.last( 'JavaScript', 6 )\nout = base.last( 'foo bar', 10 )\n","base.lastCodePoint":"var out = base.lastCodePoint( 'hello world', 1 )\nout = base.lastCodePoint( 'JavaScript', 6 )\nout = base.lastCodePoint( 'अनुच्छेद', 1 )\n","base.lastGraphemeCluster":"var out = base.lastGraphemeCluster( 'beep', 1 )\nout = base.lastGraphemeCluster( 'Boop', 2 )\nout = base.lastGraphemeCluster( 'JavaScript', 6 )\n","base.lcm":"var v = base.lcm( 21, 6 )\n","base.ldexp":"var x = base.ldexp( 0.5, 3 )\nx = base.ldexp( 4.0, -2 )\nx = base.ldexp( 0.0, 20 )\nx = base.ldexp( -0.0, 39 )\nx = base.ldexp( NaN, -101 )\nx = base.ldexp( PINF, 11 )\nx = base.ldexp( NINF, -118 )\n","base.leftPad":"var out = base.leftPad( 'a', 5, ' ' )\nout = base.leftPad( 'beep', 10, 'b' )\nout = base.leftPad( 'boop', 12, 'beep' )\n","base.leftTrim":"var out = base.leftTrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n","base.ln":"var y = base.ln( 4.0 )\ny = base.ln( 0.0 )\ny = base.ln( PINF )\ny = base.ln( NaN )\ny = base.ln( -4.0 )\n","base.log":"var y = base.log( 100.0, 10.0 )\ny = base.log( 16.0, 2.0 )\ny = base.log( 5.0, 1.0 )\ny = base.log( NaN, 2.0 )\ny = base.log( 1.0, NaN )\ny = base.log( -4.0, 2.0 )\ny = base.log( 4.0, -2.0 )\n","base.log1mexp":"var y = base.log1mexp( -10.0 )\ny = base.log1mexp( 0.0 )\ny = base.log1mexp( 5.0 )\ny = base.log1mexp( 10.0 )\ny = base.log1mexp( NaN )\n","base.log1p":"var y = base.log1p( 4.0 )\ny = base.log1p( -1.0 )\ny = base.log1p( 0.0 )\ny = base.log1p( -0.0 )\ny = base.log1p( -2.0 )\ny = base.log1p( NaN )\n","base.log1pexp":"var y = base.log1pexp( -10.0 )\ny = base.log1pexp( 0.0 )\ny = base.log1pexp( 5.0 )\ny = base.log1pexp( 34.0 )\ny = base.log1pexp( NaN )\n","base.log1pmx":"base.log1pmx( 1.1 )\nbase.log1pmx( 0.99 )\nbase.log1pmx( -0.99 )\nbase.log1pmx( -1.1 )\nbase.log1pmx( NaN )\n","base.log2":"var y = base.log2( 4.0 )\ny = base.log2( 8.0 )\ny = base.log2( 0.0 )\ny = base.log2( PINF )\ny = base.log2( NaN )\ny = base.log2( -4.0 )\n","base.log10":"var y = base.log10( 100.0 )\ny = base.log10( 8.0 )\ny = base.log10( 0.0 )\ny = base.log10( PINF )\ny = base.log10( NaN )\ny = base.log10( -4.0 )\n","base.logaddexp":"var v = base.logaddexp( 90.0, 90.0 )\nv = base.logaddexp( -20.0, 90.0 )\nv = base.logaddexp( 0.0, -100.0 )\nv = base.logaddexp( NaN, NaN )\n","base.logit":"var y = base.logit( 0.2 )\ny = base.logit( 0.9 )\ny = base.logit( -4.0 )\ny = base.logit( 1.5 )\ny = base.logit( NaN )\n","base.lowercase":"var out = base.lowercase( 'bEEp' )\n","base.lucas":"var y = base.lucas( 0 )\ny = base.lucas( 1 )\ny = base.lucas( 2 )\ny = base.lucas( 3 )\ny = base.lucas( 4 )\ny = base.lucas( 77 )\ny = base.lucas( NaN )\n","base.lucaspoly":"var v = base.lucaspoly( 5, 2.0 )\n","base.lucaspoly.factory":"var polyval = base.lucaspoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.max":"var v = base.max( 3.14, 4.2 )\nv = base.max( 3.14, NaN )\nv = base.max( +0.0, -0.0 )\n","base.maxabs":"var v = base.maxabs( 3.14, -4.2 )\nv = base.maxabs( 3.14, NaN )\nv = base.maxabs( +0.0, -0.0 )\n","base.maxabsn":"var v = base.maxabsn( 3.14, -4.2 )\nv = base.maxabsn( 5.9, 3.14, 4.2 )\nv = base.maxabsn( 3.14, NaN )\nv = base.maxabsn( +0.0, -0.0 )\n","base.maxn":"var v = base.maxn( 3.14, 4.2 )\nv = base.maxn( 5.9, 3.14, 4.2 )\nv = base.maxn( 3.14, NaN )\nv = base.maxn( +0.0, -0.0 )\n","base.min":"var v = base.min( 3.14, 4.2 )\nv = base.min( 3.14, NaN )\nv = base.min( +0.0, -0.0 )\n","base.minabs":"var v = base.minabs( 3.14, -4.2 )\nv = base.minabs( 3.14, NaN )\nv = base.minabs( +0.0, -0.0 )\n","base.minabsn":"var v = base.minabsn( 3.14, -4.2 )\nv = base.minabsn( 5.9, 3.14, 4.2 )\nv = base.minabsn( 3.14, NaN )\nv = base.minabsn( +0.0, -0.0 )\n","base.minmax":"var v = base.minmax( 3.14, 4.2 )\nv = base.minmax( 3.14, NaN )\nv = base.minmax( +0.0, -0.0 )\n","base.minmax.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabs":"var v = base.minmaxabs( 3.14, 4.2 )\nv = base.minmaxabs( -5.9, 3.14)\nv = base.minmaxabs( 3.14, NaN )\nv = base.minmaxabs( +0.0, -0.0 )\n","base.minmaxabs.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabsn":"var v = base.minmaxabsn( 3.14, 4.2 )\nv = base.minmaxabsn( -5.9, 3.14, 4.2 )\nv = base.minmaxabsn( 3.14, NaN )\nv = base.minmaxabsn( +0.0, -0.0 )\nv = base.minmaxabsn( 3.14 )\n","base.minmaxabsn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxn":"var v = base.minmaxn( 3.14, 4.2 )\nv = base.minmaxn( 5.9, 3.14, 4.2 )\nv = base.minmaxn( 3.14, NaN )\nv = base.minmaxn( +0.0, -0.0 )\nv = base.minmaxn( 3.14 )\n","base.minmaxn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minn":"var v = base.minn( 3.14, 4.2 )\nv = base.minn( 5.9, 3.14, 4.2 )\nv = base.minn( 3.14, NaN )\nv = base.minn( +0.0, -0.0 )\n","base.modf":"var parts = base.modf( 3.14 )\nparts = base.modf( 3.14 )\nparts = base.modf( +0.0 )\nparts = base.modf( -0.0 )\nparts = base.modf( PINF )\nparts = base.modf( NINF )\nparts = base.modf( NaN )\n","base.modf.assign":"var out = new Float64Array( 2 );\nvar parts = base.modf.assign( 3.14, out, 1, 0 )\nvar bool = ( parts === out )\n","base.mul":"var v = base.mul( -1.0, 5.0 )\nv = base.mul( 2.0, 5.0 )\nv = base.mul( 0.0, 5.0 )\nv = base.mul( -0.0, 0.0 )\nv = base.mul( NaN, NaN )\n","base.mulf":"var v = base.mulf( -1.0, 5.0 )\nv = base.mulf( 2.0, 5.0 )\nv = base.mulf( 0.0, 5.0 )\nv = base.mulf( -0.0, 0.0 )\nv = base.mulf( NaN, NaN )\n","base.ndarray":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\narr.iset( 3, 99 );\narr.get( 1, 1 )\n","base.ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","base.ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","base.ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","base.ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","base.ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","base.ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","base.ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","base.ndarray.prototype.order: string":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","base.ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","base.ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","base.ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","base.ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","base.ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","base.ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","base.ndarray.prototype.toLocaleString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toLocaleString()\n","base.ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","base.ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","base.ndarrayUnary":"var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dtype = 'float64';\nvar shape = [ 2, 2 ];\nvar sx = [ 2, 1 ];\nvar sy = [ 2, 1 ];\nvar ox = 0;\nvar oy = 0;\nvar order = 'row-major';\nvar x = ndarray( dtype, xbuf, shape, sx, ox, order );\nvar y = ndarray( dtype, ybuf, shape, sy, oy, order );\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\nx = {\n 'dtype': dtype,\n 'data': xbuf,\n 'shape': shape,\n 'strides': sx,\n 'offset': ox,\n 'order': order\n };\ny = {\n 'dtype': dtype,\n 'data': ybuf,\n 'shape': shape,\n 'strides': sy,\n 'offset': oy,\n 'order': order\n };\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\n","base.ndzeros":"var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n","base.ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar y = base.ndzerosLike( x )\n","base.negafibonacci":"var y = base.negafibonacci( 0 )\ny = base.negafibonacci( -1 )\ny = base.negafibonacci( -2 )\ny = base.negafibonacci( -3 )\ny = base.negafibonacci( -4 )\ny = base.negafibonacci( -79 )\ny = base.negafibonacci( -80 )\ny = base.negafibonacci( NaN )\n","base.negalucas":"var y = base.negalucas( 0 )\ny = base.negalucas( -1 )\ny = base.negalucas( -2 )\ny = base.negalucas( -3 )\ny = base.negalucas( -4 )\ny = base.negalucas( -77 )\ny = base.negalucas( -78 )\ny = base.negalucas( NaN )\n","base.nonfibonacci":"var v = base.nonfibonacci( 1 )\nv = base.nonfibonacci( 2 )\nv = base.nonfibonacci( 3 )\nv = base.nonfibonacci( NaN )\n","base.normalize":"var out = base.normalize( 3.14e-319 )\nvar y = out[ 0 ];\nvar exponent = out[ 1 ];\nvar bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\nout = base.normalize( 0.0 )\nout = base.normalize( PINF )\nout = base.normalize( NINF )\nout = base.normalize( NaN )\n","base.normalize.assign":"var out = new Float64Array( 2 )\nvar v = base.normalize.assign( 3.14e-319, out, 1, 0 )\nvar bool = ( v === out )\n","base.normalizef":"var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\nvar y = out[ 0 ];\nvar exp = out[ 1 ];\nvar bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\nout = base.normalizef( FLOAT32_PINF )\nout = base.normalizef( FLOAT32_NINF )\nout = base.normalizef( NaN )\n","base.normalizef.assign":"out = new Float32Array( 2 );\nvar v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\nbool = ( v === out )\n","base.normalizeMultiSlice":"var s1 = new MultiSlice( 1, 3, null );\nvar s2 = base.normalizeMultiSlice( s1, [ 5, 5, 5 ], false );\nvar v = s2.data[ 0 ];\nv.start\nv.stop\nv.step\nv = s2.data[ 1 ];\nv.start\nv.stop\nv.step\nv = s2.data[ 2 ];\nv.start\nv.stop\nv.step\n","base.normalizeSlice":"var s1 = new Slice( 1, 10, 1 );\nvar s2 = base.normalizeSlice( s1, 5, false );\ns2.start\ns2.stop\ns2.step\ns1 = new Slice( -2, null, -1 );\ns2 = base.normalizeSlice( s1, 10, false );\ns2.start\ns2.stop\ns2.step\n","base.normhermitepoly":"var y = base.normhermitepoly( 1, 0.5 )\ny = base.normhermitepoly( -1, 0.5 )\ny = base.normhermitepoly( 0, 0.5 )\ny = base.normhermitepoly( 2, 0.5 )\n","base.normhermitepoly.factory":"var f = base.normhermitepoly.factory( 2 );\nvar v = f( 0.5 )\n","base.pascalcase":"var out = base.pascalcase( 'Hello World!' )\nout = base.pascalcase( 'beep boop' )\n","base.pdiff":"var v = base.pdiff( 5.9, 3.14 )\nv = base.pdiff( 3.14, 4.2 )\nv = base.pdiff( 3.14, NaN )\nv = base.pdiff( -0.0, +0.0 )\n","base.pdifff":"var v = base.pdifff( 5.9, 3.15 )\nv = base.pdifff( 3.14, 4.2 )\nv = base.pdifff( 3.14, NaN )\nv = base.pdifff( -0.0, +0.0 )\n","base.percentEncode":"var out = base.percentEncode( '☃' )\n","base.polygamma":"var v = base.polygamma( 3, 1.2 )\nv = base.polygamma( 5, 1.2 )\nv = base.polygamma( 3, -4.9 )\nv = base.polygamma( -1, 5.3 )\nv = base.polygamma( 2, -1.0 )\n","base.pow":"var y = base.pow( 2.0, 3.0 )\ny = base.pow( 4.0, 0.5 )\ny = base.pow( 100.0, 0.0 )\ny = base.pow( PI, 5.0 )\ny = base.pow( PI, -0.2 )\ny = base.pow( NaN, 3.0 )\ny = base.pow( 5.0, NaN )\ny = base.pow( NaN, NaN )\n","base.powm1":"var y = base.powm1( 2.0, 3.0 )\ny = base.powm1( 4.0, 0.5 )\ny = base.powm1( 0.0, 100.0 )\ny = base.powm1( 100.0, 0.0 )\ny = base.powm1( 0.0, 0.0 )\ny = base.powm1( PI, 5.0 )\ny = base.powm1( NaN, 3.0 )\ny = base.powm1( 5.0, NaN )\n","base.rad2deg":"var d = base.rad2deg( PI/2.0 )\nd = base.rad2deg( -PI/4.0 )\nd = base.rad2deg( NaN )\nd = base.rad2deg( PI/6.0 )\n","base.rad2degf":"var d = base.rad2degf( 3.141592653589793 / 2.0 )\nd = base.rad2degf( -3.141592653589793 / 4.0 )\nd = base.rad2degf( NaN )\nd = base.rad2degf( 3.141592653589793 / 6.0 )\n","base.ramp":"var y = base.ramp( 3.14 )\ny = base.ramp( -3.14 )\n","base.rampf":"var y = base.rampf( 3.14 )\ny = base.rampf( -3.14 )\n","base.random.arcsine":"var r = base.random.arcsine( 2.0, 5.0 )\n","base.random.arcsine.factory":"var rand = base.random.arcsine.factory();\nvar r = rand( 0.0, 1.0 )\nr = rand( -2.0, 2.0 )\nrand = base.random.arcsine.factory( 0.0, 1.0 );\nr = rand()\nr = rand()\n","base.random.arcsine.NAME":"var str = base.random.arcsine.NAME\n","base.random.arcsine.PRNG":"var prng = base.random.arcsine.PRNG;\n","base.random.arcsine.seed":"var seed = base.random.arcsine.seed;\n","base.random.arcsine.seedLength":"var len = base.random.arcsine.seedLength;\n","base.random.arcsine.state":"var r = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nvar state = base.random.arcsine.state\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nbase.random.arcsine.state = state;\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\n","base.random.arcsine.stateLength":"var len = base.random.arcsine.stateLength;\n","base.random.arcsine.byteLength":"var sz = base.random.arcsine.byteLength;\n","base.random.arcsine.toJSON":"var o = base.random.arcsine.toJSON()\n","base.random.bernoulli":"var r = base.random.bernoulli( 0.8 );\n","base.random.bernoulli.factory":"var rand = base.random.bernoulli.factory();\nvar r = rand( 0.3 );\nr = rand( 0.59 );\nrand = base.random.bernoulli.factory( 0.3 );\nr = rand();\nr = rand();\n","base.random.bernoulli.NAME":"var str = base.random.bernoulli.NAME\n","base.random.bernoulli.PRNG":"var prng = base.random.bernoulli.PRNG;\n","base.random.bernoulli.seed":"var seed = base.random.bernoulli.seed;\n","base.random.bernoulli.seedLength":"var len = base.random.bernoulli.seedLength;\n","base.random.bernoulli.state":"var r = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nvar state = base.random.bernoulli.state\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nbase.random.bernoulli.state = state;\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\n","base.random.bernoulli.stateLength":"var len = base.random.bernoulli.stateLength;\n","base.random.bernoulli.byteLength":"var sz = base.random.bernoulli.byteLength;\n","base.random.bernoulli.toJSON":"var o = base.random.bernoulli.toJSON()\n","base.random.beta":"var r = base.random.beta( 2.0, 5.0 );\n","base.random.beta.factory":"var rand = base.random.beta.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.beta.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.beta.NAME":"var str = base.random.beta.NAME\n","base.random.beta.PRNG":"var prng = base.random.beta.PRNG;\n","base.random.beta.seed":"var seed = base.random.beta.seed;\n","base.random.beta.seedLength":"var len = base.random.beta.seedLength;\n","base.random.beta.state":"var r = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nvar state = base.random.beta.state\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nbase.random.beta.state = state;\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\n","base.random.beta.stateLength":"var len = base.random.beta.stateLength;\n","base.random.beta.byteLength":"var sz = base.random.beta.byteLength;\n","base.random.beta.toJSON":"var o = base.random.beta.toJSON()\n","base.random.betaprime":"var r = base.random.betaprime( 2.0, 5.0 );\n","base.random.betaprime.factory":"var rand = base.random.betaprime.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.betaprime.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.betaprime.NAME":"var str = base.random.betaprime.NAME\n","base.random.betaprime.PRNG":"var prng = base.random.betaprime.PRNG;\n","base.random.betaprime.seed":"var seed = base.random.betaprime.seed;\n","base.random.betaprime.seedLength":"var len = base.random.betaprime.seedLength;\n","base.random.betaprime.state":"var r = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nvar state = base.random.betaprime.state\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nbase.random.betaprime.state = state;\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\n","base.random.betaprime.stateLength":"var len = base.random.betaprime.stateLength;\n","base.random.betaprime.byteLength":"var sz = base.random.betaprime.byteLength;\n","base.random.betaprime.toJSON":"var o = base.random.betaprime.toJSON()\n","base.random.binomial":"var r = base.random.binomial( 20, 0.8 );\n","base.random.binomial.factory":"var rand = base.random.binomial.factory();\nvar r = rand( 20, 0.3 );\nr = rand( 10, 0.77 );\nrand = base.random.binomial.factory( 10, 0.8 );\nr = rand();\nr = rand();\n","base.random.binomial.NAME":"var str = base.random.binomial.NAME\n","base.random.binomial.PRNG":"var prng = base.random.binomial.PRNG;\n","base.random.binomial.seed":"var seed = base.random.binomial.seed;\n","base.random.binomial.seedLength":"var len = base.random.binomial.seedLength;\n","base.random.binomial.state":"var r = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nvar state = base.random.binomial.state\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nbase.random.binomial.state = state;\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\n","base.random.binomial.stateLength":"var len = base.random.binomial.stateLength;\n","base.random.binomial.byteLength":"var sz = base.random.binomial.byteLength;\n","base.random.binomial.toJSON":"var o = base.random.binomial.toJSON()\n","base.random.boxMuller":"var r = base.random.boxMuller();\n","base.random.boxMuller.factory":"var rand = base.random.boxMuller.factory();\nr = rand();\nr = rand();\n","base.random.boxMuller.NAME":"var str = base.random.boxMuller.NAME\n","base.random.boxMuller.PRNG":"var prng = base.random.boxMuller.PRNG;\n","base.random.boxMuller.seed":"var seed = base.random.boxMuller.seed;\n","base.random.boxMuller.seedLength":"var len = base.random.boxMuller.seedLength;\n","base.random.boxMuller.state":"var r = base.random.boxMuller()\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nvar state = base.random.boxMuller.state\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nbase.random.boxMuller.state = state;\nr = base.random.boxMuller()\nr = base.random.boxMuller()\n","base.random.boxMuller.stateLength":"var len = base.random.boxMuller.stateLength;\n","base.random.boxMuller.byteLength":"var sz = base.random.boxMuller.byteLength;\n","base.random.boxMuller.toJSON":"var o = base.random.boxMuller.toJSON()\n","base.random.cauchy":"var r = base.random.cauchy( 2.0, 5.0 );\n","base.random.cauchy.factory":"var rand = base.random.cauchy.factory();\nvar r = rand( 0.0, 1.5 );\nr = rand( -2.0, 2.0 );\nrand = base.random.cauchy.factory( 0.0, 1.5 );\nr = rand();\nr = rand();\n","base.random.cauchy.NAME":"var str = base.random.cauchy.NAME\n","base.random.cauchy.PRNG":"var prng = base.random.cauchy.PRNG;\n","base.random.cauchy.seed":"var seed = base.random.cauchy.seed;\n","base.random.cauchy.seedLength":"var len = base.random.cauchy.seedLength;\n","base.random.cauchy.state":"var r = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nvar state = base.random.cauchy.state\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nbase.random.cauchy.state = state;\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\n","base.random.cauchy.stateLength":"var len = base.random.cauchy.stateLength;\n","base.random.cauchy.byteLength":"var sz = base.random.cauchy.byteLength;\n","base.random.cauchy.toJSON":"var o = base.random.cauchy.toJSON()\n","base.random.chi":"var r = base.random.chi( 2 );\n","base.random.chi.factory":"var rand = base.random.chi.factory();\nvar r = rand( 5 );\nr = rand( 3.14 );\nrand = base.random.chi.factory( 3 );\nr = rand();\nr = rand();\n","base.random.chi.NAME":"var str = base.random.chi.NAME\n","base.random.chi.PRNG":"var prng = base.random.chi.PRNG;\n","base.random.chi.seed":"var seed = base.random.chi.seed;\n","base.random.chi.seedLength":"var len = base.random.chi.seedLength;\n","base.random.chi.state":"var r = base.random.chi( 2 )\nr = base.random.chi( 2 )\nr = base.random.chi( 2 )\nvar state = base.random.chi.state\nr = base.random.chi( 2 )\nr = base.random.chi( 2 )\nbase.random.chi.state = state;\nr = base.random.chi( 2 )\nr = base.random.chi( 2 )\n","base.random.chi.stateLength":"var len = base.random.chi.stateLength;\n","base.random.chi.byteLength":"var sz = base.random.chi.byteLength;\n","base.random.chi.toJSON":"var o = base.random.chi.toJSON()\n","base.random.chisquare":"var r = base.random.chisquare( 2 );\n","base.random.chisquare.factory":"var rand = base.random.chisquare.factory();\nvar r = rand( 5 );\nr = rand( 3.14 );\nrand = base.random.chisquare.factory( 3 );\nr = rand();\nr = rand();\n","base.random.chisquare.NAME":"var str = base.random.chisquare.NAME\n","base.random.chisquare.PRNG":"var prng = base.random.chisquare.PRNG;\n","base.random.chisquare.seed":"var seed = base.random.chisquare.seed;\n","base.random.chisquare.seedLength":"var len = base.random.chisquare.seedLength;\n","base.random.chisquare.state":"var r = base.random.chisquare( 2 )\nr = base.random.chisquare( 2 )\nr = base.random.chisquare( 2 )\nvar state = base.random.chisquare.state\nr = base.random.chisquare( 2 )\nr = base.random.chisquare( 2 )\nbase.random.chisquare.state = state;\nr = base.random.chisquare( 2 )\nr = base.random.chisquare( 2 )\n","base.random.chisquare.stateLength":"var len = base.random.chisquare.stateLength;\n","base.random.chisquare.byteLength":"var sz = base.random.chisquare.byteLength;\n","base.random.chisquare.toJSON":"var o = base.random.chisquare.toJSON()\n","base.random.cosine":"var r = base.random.cosine( 2.0, 5.0 );\n","base.random.cosine.factory":"var rand = base.random.cosine.factory();\nvar r = rand( 0.1, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.cosine.factory( 0.1, 1.5 );\nr = rand();\nr = rand();\n","base.random.cosine.NAME":"var str = base.random.cosine.NAME\n","base.random.cosine.PRNG":"var prng = base.random.cosine.PRNG;\n","base.random.cosine.seed":"var seed = base.random.cosine.seed;\n","base.random.cosine.seedLength":"var len = base.random.cosine.seedLength;\n","base.random.cosine.state":"var r = base.random.cosine( 2.0, 5.0 )\nr = base.random.cosine( 2.0, 5.0 )\nr = base.random.cosine( 2.0, 5.0 )\nvar state = base.random.cosine.state\nr = base.random.cosine( 2.0, 5.0 )\nr = base.random.cosine( 2.0, 5.0 )\nbase.random.cosine.state = state;\nr = base.random.cosine( 2.0, 5.0 )\nr = base.random.cosine( 2.0, 5.0 )\n","base.random.cosine.stateLength":"var len = base.random.cosine.stateLength;\n","base.random.cosine.byteLength":"var sz = base.random.cosine.byteLength;\n","base.random.cosine.toJSON":"var o = base.random.cosine.toJSON()\n","base.random.discreteUniform":"var r = base.random.discreteUniform( 2, 50 );\n","base.random.discreteUniform.factory":"var rand = base.random.discreteUniform.factory();\nvar r = rand( 0, 10 );\nr = rand( -20, 20 );\nrand = base.random.discreteUniform.factory( 0, 10 );\nr = rand();\nr = 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);\n","base.random.kumaraswamy.factory":"var rand = base.random.kumaraswamy.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.kumaraswamy.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.kumaraswamy.NAME":"var str = base.random.kumaraswamy.NAME\n","base.random.kumaraswamy.PRNG":"var prng = base.random.kumaraswamy.PRNG;\n","base.random.kumaraswamy.seed":"var seed = base.random.kumaraswamy.seed;\n","base.random.kumaraswamy.seedLength":"var len = base.random.kumaraswamy.seedLength;\n","base.random.kumaraswamy.state":"var r = base.random.kumaraswamy( 1.5, 1.5 )\nr = base.random.kumaraswamy( 1.5, 1.5 )\nr = base.random.kumaraswamy( 1.5, 1.5 )\nvar state = base.random.kumaraswamy.state\nr = base.random.kumaraswamy( 1.5, 1.5 )\nr = base.random.kumaraswamy( 1.5, 1.5 )\nbase.random.kumaraswamy.state = state;\nr = base.random.kumaraswamy( 1.5, 1.5 )\nr = base.random.kumaraswamy( 1.5, 1.5 )\n","base.random.kumaraswamy.stateLength":"var len = 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base.random.mt19937.MAX\n","base.random.mt19937.seed":"var seed = base.random.mt19937.seed;\n","base.random.mt19937.seedLength":"var len = base.random.mt19937.seedLength;\n","base.random.mt19937.state":"var r = base.random.mt19937()\nr = base.random.mt19937()\nr = base.random.mt19937()\nvar state = base.random.mt19937.state\nr = base.random.mt19937()\nr = base.random.mt19937()\nbase.random.mt19937.state = state;\nr = base.random.mt19937()\nr = base.random.mt19937()\n","base.random.mt19937.stateLength":"var len = base.random.mt19937.stateLength;\n","base.random.mt19937.byteLength":"var sz = base.random.mt19937.byteLength;\n","base.random.mt19937.toJSON":"var o = base.random.mt19937.toJSON()\n","base.random.negativeBinomial":"var r = base.random.negativeBinomial( 20, 0.8 );\n","base.random.negativeBinomial.factory":"var rand = base.random.negativeBinomial.factory();\nvar r = rand( 20, 0.3 );\nr = rand( 10, 0.77 );\nrand = base.random.negativeBinomial.factory( 10, 0.8 );\nr = rand();\nr = rand();\n","base.random.negativeBinomial.NAME":"var str = base.random.negativeBinomial.NAME\n","base.random.negativeBinomial.PRNG":"var prng = base.random.negativeBinomial.PRNG;\n","base.random.negativeBinomial.seed":"var seed = base.random.negativeBinomial.seed;\n","base.random.negativeBinomial.seedLength":"var len = base.random.negativeBinomial.seedLength;\n","base.random.negativeBinomial.state":"var r = base.random.negativeBinomial( 20, 0.3 )\nr = base.random.negativeBinomial( 20, 0.3 )\nr = base.random.negativeBinomial( 20, 0.3 )\nvar state = base.random.negativeBinomial.state\nr = base.random.negativeBinomial( 20, 0.3 )\nr = base.random.negativeBinomial( 20, 0.3 )\nbase.random.negativeBinomial.state = state;\nr = base.random.negativeBinomial( 20, 0.3 )\nr = base.random.negativeBinomial( 20, 0.3 )\n","base.random.negativeBinomial.stateLength":"var len = base.random.negativeBinomial.stateLength;\n","base.random.negativeBinomial.byteLength":"var sz = 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base.random.normal( 2.0, 5.0 )\n","base.random.normal.stateLength":"var len = base.random.normal.stateLength;\n","base.random.normal.byteLength":"var sz = base.random.normal.byteLength;\n","base.random.normal.toJSON":"var o = base.random.normal.toJSON()\n","base.random.pareto1":"var r = base.random.pareto1( 2.0, 5.0 );\n","base.random.pareto1.factory":"var rand = base.random.pareto1.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.pareto1.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.pareto1.NAME":"var str = base.random.pareto1.NAME\n","base.random.pareto1.PRNG":"var prng = base.random.pareto1.PRNG;\n","base.random.pareto1.seed":"var seed = base.random.pareto1.seed;\n","base.random.pareto1.seedLength":"var len = base.random.pareto1.seedLength;\n","base.random.pareto1.state":"var r = base.random.pareto1( 2.0, 5.0 )\nr = base.random.pareto1( 2.0, 5.0 )\nr = base.random.pareto1( 2.0, 5.0 )\nvar state = base.random.pareto1.state\nr = base.random.pareto1( 2.0, 5.0 )\nr = base.random.pareto1( 2.0, 5.0 )\nbase.random.pareto1.state = state;\nr = base.random.pareto1( 2.0, 5.0 )\nr = base.random.pareto1( 2.0, 5.0 )\n","base.random.pareto1.stateLength":"var len = base.random.pareto1.stateLength;\n","base.random.pareto1.byteLength":"var sz = base.random.pareto1.byteLength;\n","base.random.pareto1.toJSON":"var o = base.random.pareto1.toJSON()\n","base.random.poisson":"var r = base.random.poisson( 7.9 );\n","base.random.poisson.factory":"var rand = base.random.poisson.factory();\nvar r = rand( 4.0 );\nr = rand( 3.14 );\nrand = base.random.poisson.factory( 10.0 );\nr = rand();\nr = rand();\n","base.random.poisson.NAME":"var str = base.random.poisson.NAME\n","base.random.poisson.PRNG":"var prng = base.random.poisson.PRNG;\n","base.random.poisson.seed":"var seed = base.random.poisson.seed;\n","base.random.poisson.seedLength":"var len = base.random.poisson.seedLength;\n","base.random.poisson.state":"var r = base.random.poisson( 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base.random.randi.MAX;\n","base.random.randi.seed":"var seed = base.random.randi.seed;\n","base.random.randi.seedLength":"var len = base.random.randi.seedLength;\n","base.random.randi.state":"var r = base.random.randi()\nr = base.random.randi()\nr = base.random.randi()\nvar state = base.random.randi.state;\nr = base.random.randi()\nr = base.random.randi()\nbase.random.randi.state = state;\nr = base.random.randi()\nr = base.random.randi()\n","base.random.randi.stateLength":"var len = base.random.randi.stateLength;\n","base.random.randi.byteLength":"var sz = base.random.randi.byteLength;\n","base.random.randi.toJSON":"var o = base.random.randi.toJSON()\n","base.random.randn":"var r = base.random.randn();\n","base.random.randn.factory":"var rand = base.random.randn.factory();\nvar r = rand();\nr = rand();\nvar rand = base.random.randn.factory({ 'name': 'box-muller' });\nr = rand();\nr = rand();\n","base.random.randn.NAME":"var str = base.random.randn.NAME\n","base.random.randn.PRNG":"var 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base.random.randu.NAME\n","base.random.randu.PRNG":"var prng = base.random.randu.PRNG;\n","base.random.randu.MIN":"var v = base.random.randu.MIN;\n","base.random.randu.MAX":"var v = base.random.randu.MAX;\n","base.random.randu.seed":"var seed = base.random.randu.seed;\n","base.random.randu.seedLength":"var len = base.random.randu.seedLength;\n","base.random.randu.state":"var r = base.random.randu()\nr = base.random.randu()\nr = base.random.randu()\nvar state = base.random.randu.state;\nr = base.random.randu()\nr = base.random.randu()\nbase.random.randu.state = state;\nr = base.random.randu()\nr = base.random.randu()\n","base.random.randu.stateLength":"var len = base.random.randu.stateLength;\n","base.random.randu.byteLength":"var sz = base.random.randu.byteLength;\n","base.random.randu.toJSON":"var o = base.random.randu.toJSON()\n","base.random.rayleigh":"var r = base.random.rayleigh( 2.5 );\n","base.random.rayleigh.factory":"var rand = base.random.rayleigh.factory();\nvar r = rand( 5.0 );\nr = rand( 10.0 );\nrand = base.random.rayleigh.factory( 5.0 );\nr = rand();\nr = rand();\n","base.random.rayleigh.NAME":"var str = base.random.rayleigh.NAME\n","base.random.rayleigh.PRNG":"var prng = base.random.rayleigh.PRNG;\n","base.random.rayleigh.seed":"var seed = base.random.rayleigh.seed;\n","base.random.rayleigh.seedLength":"var len = base.random.rayleigh.seedLength;\n","base.random.rayleigh.state":"var r = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nvar state = base.random.rayleigh.state\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nbase.random.rayleigh.state = state;\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\n","base.random.rayleigh.stateLength":"var len = base.random.rayleigh.stateLength;\n","base.random.rayleigh.byteLength":"var sz = base.random.rayleigh.byteLength;\n","base.random.rayleigh.toJSON":"var o = base.random.rayleigh.toJSON()\n","base.random.t":"var r = base.random.t( 2.0 );\n","base.random.t.factory":"var rand = base.random.t.factory();\nvar r = rand( 5.0 );\nr = rand( 3.14 );\nrand = base.random.t.factory( 5.0 );\nr = rand();\nr = rand();\n","base.random.t.NAME":"var str = base.random.t.NAME\n","base.random.t.PRNG":"var prng = base.random.t.PRNG;\n","base.random.t.seed":"var seed = base.random.t.seed;\n","base.random.t.seedLength":"var len = base.random.t.seedLength;\n","base.random.t.state":"var r = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nvar state = base.random.t.state\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nbase.random.t.state = state;\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\n","base.random.t.stateLength":"var len = base.random.t.stateLength;\n","base.random.t.byteLength":"var sz = base.random.t.byteLength;\n","base.random.t.toJSON":"var o = base.random.t.toJSON()\n","base.random.triangular":"var r = base.random.triangular( 2.0, 5.0, 3.33 );\n","base.random.triangular.factory":"var rand = base.random.triangular.factory();\nvar r = rand( 0.0, 1.0, 0.5 );\nr = rand( -2.0, 2.0, 1.0 );\nrand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\nr = rand();\nr = rand();\n","base.random.triangular.NAME":"var str = base.random.triangular.NAME\n","base.random.triangular.PRNG":"var prng = base.random.triangular.PRNG;\n","base.random.triangular.seed":"var seed = base.random.triangular.seed;\n","base.random.triangular.seedLength":"var len = base.random.triangular.seedLength;\n","base.random.triangular.state":"var r = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nvar state = base.random.triangular.state\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nbase.random.triangular.state = state;\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\n","base.random.triangular.stateLength":"var len = base.random.triangular.stateLength;\n","base.random.triangular.byteLength":"var sz = base.random.triangular.byteLength;\n","base.random.triangular.toJSON":"var o = base.random.triangular.toJSON()\n","base.random.uniform":"var r = base.random.uniform( 2.0, 5.0 );\n","base.random.uniform.factory":"var rand = base.random.uniform.factory();\nvar r = rand( 0.0, 1.0 );\nr = rand( -2.0, 2.0 );\nrand = base.random.uniform.factory( 0.0, 1.0 );\nr = rand();\nr = rand();\n","base.random.uniform.NAME":"var str = base.random.uniform.NAME\n","base.random.uniform.PRNG":"var prng = base.random.uniform.PRNG;\n","base.random.uniform.seed":"var seed = base.random.uniform.seed;\n","base.random.uniform.seedLength":"var len = base.random.uniform.seedLength;\n","base.random.uniform.state":"var r = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nvar state = base.random.uniform.state\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nbase.random.uniform.state = state;\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\n","base.random.uniform.stateLength":"var len = base.random.uniform.stateLength;\n","base.random.uniform.byteLength":"var sz = base.random.uniform.byteLength;\n","base.random.uniform.toJSON":"var o = base.random.uniform.toJSON()\n","base.random.weibull":"var r = base.random.weibull( 2.0, 5.0 );\n","base.random.weibull.factory":"var rand = base.random.weibull.factory();\nvar r = rand( 0.1, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.weibull.factory( 0.1, 1.5 );\nr = rand();\nr = rand();\n","base.random.weibull.NAME":"var str = base.random.weibull.NAME\n","base.random.weibull.PRNG":"var prng = base.random.weibull.PRNG;\n","base.random.weibull.seed":"var seed = base.random.weibull.seed;\n","base.random.weibull.seedLength":"var len = base.random.weibull.seedLength;\n","base.random.weibull.state":"var r = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nvar state = base.random.weibull.state\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nbase.random.weibull.state = state;\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\n","base.random.weibull.stateLength":"var len = base.random.weibull.stateLength;\n","base.random.weibull.byteLength":"var sz = base.random.weibull.byteLength;\n","base.random.weibull.toJSON":"var o = base.random.weibull.toJSON()\n","base.rcbrt":"var y = base.rcbrt( 8.0 )\ny = base.rcbrt( 1000.0 )\ny = base.rcbrt( 0.0 )\ny = base.rcbrt( PINF )\ny = base.rcbrt( -8.0 )\ny = base.rcbrt( NaN )\n","base.rcbrtf":"var y = base.rcbrtf( 8.0 )\ny = base.rcbrtf( 1000.0 )\ny = base.rcbrtf( 0.0 )\ny = base.rcbrtf( PINF )\ny = base.rcbrtf( -8.0 )\ny = base.rcbrtf( NaN )\n","base.reldiff":"var d = base.reldiff( 2.0, 5.0 )\nd = base.reldiff( -1.0, 3.14 )\nd = base.reldiff( -2.0, 5.0, 'max-abs' )\nd = base.reldiff( -2.0, 5.0, 'max' )\nd = base.reldiff( -2.0, 5.0, 'min-abs' )\nd = base.reldiff( -2.0, 5.0, 'min' )\nd = base.reldiff( -2.0, 5.0, 'mean-abs' )\nd = base.reldiff( -2.0, 5.0, 'mean' )\nd = base.reldiff( -2.0, 5.0, 'x' )\nd = base.reldiff( 5.0, -2.0, 'x' )\nd = base.reldiff( -2.0, 5.0, 'y' )\nd = base.reldiff( 5.0, -2.0, 'y' )\nfunction scale( x, y ) {\n var s;\n\n x = base.abs( x );\n y = base.abs( y );\n\n // Maximum absolute value:\n s = (x < y ) ? y : x;\n\n // Scale in units of epsilon:\n return s * EPS;\n };\nd = base.reldiff( 12.15, 12.149999999999999, scale )\n","base.removeFirst":"var out = base.removeFirst( 'beep', 1 )\nout = base.removeFirst( 'Boop', 1 )\nout = base.removeFirst( 'foo bar', 5 )\n","base.removeFirstCodePoint":"var out = base.removeFirstCodePoint( 'beep', 1 )\nout = base.removeFirstCodePoint( 'Boop', 1 )\nout = base.removeFirstCodePoint( 'foo bar', 5 )\n","base.removeFirstGraphemeCluster":"var out = base.removeFirstGraphemeCluster( 'beep', 1 )\nout = base.removeFirstGraphemeCluster( 'Boop', 1 )\nout = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n","base.removeLast":"var out = base.removeLast( 'beep', 1 )\nout = base.removeLast( 'Boop', 1 )\nout = base.removeLast( 'foo bar', 5 )\n","base.removeLastCodePoint":"var out = base.removeLastCodePoint( 'beep', 1 )\nout = base.removeLastCodePoint( 'Boop', 1 )\nout = base.removeLastCodePoint( 'foo bar', 5 )\n","base.removeLastGraphemeCluster":"var out = base.removeLastGraphemeCluster( 'beep', 1 )\nout = base.removeLastGraphemeCluster( 'Boop', 1 )\nout = base.removeLastGraphemeCluster( 'foo bar', 5 )\n","base.rempio2":"var y = [ 0.0, 0.0 ];\nvar n = base.rempio2( 128.0, y )\nvar y1 = y[ 0 ]\nvar y2 = y[ 1 ]\n","base.repeat":"var out = base.repeat( 'a', 5 )\nout = base.repeat( '', 100 )\nout = base.repeat( 'beep', 0 )\n","base.replace":"function replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nvar out = base.replace( str, /([^\\s]+)/gi, replacer )\nout = base.replace( 'beep', /e/, 'o' )\n","base.replaceAfter":"var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\nout = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\nout = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n","base.replaceAfterLast":"var str = 'beep boop';\nvar out = base.replaceAfterLast( str, ' ', 'foo', str.length )\nout = base.replaceAfterLast( str, 'o', 'foo', str.length )\nout = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n","base.replaceBefore":"var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n","base.replaceBeforeLast":"var str = 'beep boop';\nvar out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\nout = base.replaceBeforeLast( str, 'o', 'foo', str.length )\nout = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n","base.reverse":"var out = base.reverse( 'beep' )\nout = base.reverse( 'Boop' )\nout = base.reverse( 'foo bar' )\n","base.reverseCodePoints":"var out = base.reverseCodePoints( 'beep' )\nout = base.reverseCodePoints( 'Boop' )\nout = base.reverseCodePoints( 'foo bar' )\n","base.reverseGraphemeClusters":"var out = base.reverseGraphemeClusters( 'beep' )\nout = base.reverseGraphemeClusters( 'Boop' )\nout = base.reverseGraphemeClusters( 'foo bar' )\n","base.rightPad":"var out = base.rightPad( 'a', 5, ' ' )\nout = base.rightPad( 'beep', 10, 'b' )\nout = base.rightPad( 'boop', 12, 'beep' )\n","base.rightTrim":"var out = base.rightTrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","base.risingFactorial":"var v = base.risingFactorial( 0.9, 5 )\nv = base.risingFactorial( -9.0, 3 )\nv = base.risingFactorial( 0.0, 2 )\nv = base.risingFactorial( 3.0, -2 )\n","base.rotl32":"var x = 2147483649;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotl32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.rotr32":"var x = 1;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotr32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.round":"var y = base.round( 3.14 )\ny = base.round( -4.2 )\ny = base.round( -4.6 )\ny = base.round( 9.5 )\ny = base.round( -0.0 )\n","base.round2":"var y = base.round2( 3.14 )\ny = base.round2( -4.2 )\ny = base.round2( -4.6 )\ny = base.round2( 9.5 )\ny = base.round2( 13.0 )\ny = base.round2( -13.0 )\ny = base.round2( -0.0 )\n","base.round10":"var y = base.round10( 3.14 )\ny = base.round10( -4.2 )\ny = base.round10( -4.6 )\ny = base.round10( 9.5 )\ny = base.round10( 13.0 )\ny = base.round10( -13.0 )\ny = base.round10( -0.0 )\n","base.roundb":"var y = base.roundb( 3.14159, -2, 10 )\ny = base.roundb( 3.14159, 0, 2 )\ny = base.roundb( 5.0, 1, 2 )\n","base.roundn":"var y = base.roundn( 3.14159, -2 )\ny = base.roundn( 3.14159, 0 )\ny = base.roundn( 12368.0, 3 )\n","base.roundsd":"var y = base.roundsd( 3.14159, 3 )\ny = base.roundsd( 3.14159, 1 )\ny = base.roundsd( 12368.0, 2 )\ny = base.roundsd( 0.0313, 2, 2 )\n","base.rsqrt":"var y = base.rsqrt( 4.0 )\ny = base.rsqrt( 100.0 )\ny = base.rsqrt( 0.0 )\ny = base.rsqrt( Infinity )\ny = base.rsqrt( -4.0 )\ny = base.rsqrt( NaN )\n","base.rsqrtf":"var y = base.rsqrtf( 4.0 )\ny = base.rsqrtf( 0.0 )\ny = base.rsqrtf( Infinity )\ny = base.rsqrtf( -4.0 )\ny = base.rsqrtf( NaN )\n","base.sargs2multislice":"var s = new base.sargs2multislice( 'null,null,null' );\ns.data\ns = new base.sargs2multislice( '10,Slice(0,10,1),null' );\ns.data\n","base.scalar2ndarray":"var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\nvar sh = ndarrayShape( x )\nvar v = x.get()\n","base.secd":"var y = base.secd( 1.0 )\ny = base.secd( PI )\ny = base.secd( -PI )\ny = base.secd( NaN )\n","base.seq2multislice":"var s = new base.seq2multislice( '1:10', [ 10 ], false );\ns.data\ns = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\ns.data\n","base.seq2slice":"var s = new base.seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new base.seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","base.setHighWord":"var high = 1072693248 >>> 0;\nvar y = base.setHighWord( PINF, high )\n","base.setLowWord":"var low = 5 >>> 0;\nvar x = 3.14e201;\nvar y = base.setLowWord( x, low )\nvar low = 12345678;\nvar y = base.setLowWord( PINF, low )\ny = base.setLowWord( NINF, low )\ny = base.setLowWord( NaN, low )\n","base.sici":"var y = base.sici( 3.0 )\ny = base.sici( 0.0 )\ny = base.sici( -9.0 )\ny = base.sici( NaN )\n","base.sici.assign":"var out = new Float64Array( 2 );\nvar y = base.sici.assign( 3.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.signbit":"var bool = base.signbit( 4.0 )\nbool = base.signbit( -9.14e-34 )\nbool = base.signbit( 0.0 )\nbool = base.signbit( -0.0 )\n","base.signbitf":"var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\nbool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\nbool = base.signbitf( 0.0 )\nbool = base.signbitf( -0.0 )\n","base.significandf":"var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\ns = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\ns = base.significandf( base.float64ToFloat32( -3.14 ) )\ns = base.significandf( 0.0 )\ns = base.significandf( NaN )\n","base.signum":"var sign = base.signum( -5.0 )\nsign = base.signum( 5.0 )\nsign = base.signum( -0.0 )\nsign = base.signum( 0.0 )\nsign = base.signum( NaN )\n","base.signumf":"var sign = base.signumf( -5.0 )\nsign = base.signumf( 5.0 )\nsign = base.signumf( -0.0 )\nsign = base.signumf( 0.0 )\nsign = base.signumf( NaN )\n","base.sin":"var y = base.sin( 0.0 )\ny = base.sin( PI/2.0 )\ny = base.sin( -PI/6.0 )\ny = base.sin( NaN )\n","base.sinc":"var y = base.sinc( 0.5 )\ny = base.sinc( -1.2 )\ny = base.sinc( 0.0 )\ny = base.sinc( NaN )\n","base.sincos":"var y = base.sincos( 0.0 )\ny = base.sincos( PI/2.0 )\ny = base.sincos( -PI/6.0 )\ny = base.sincos( NaN )\n","base.sincos.assign":"var out = new Float64Array( 2 );\nvar v = base.sincos.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sincospi":"var y = base.sincospi( 0.0 )\ny = base.sincospi( 0.5 )\ny = base.sincospi( 0.1 )\ny = base.sincospi( NaN )\n","base.sincospi.assign":"var out = new Float64Array( 2 );\nvar v = base.sincospi.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sinh":"var y = base.sinh( 0.0 )\ny = base.sinh( 2.0 )\ny = base.sinh( -2.0 )\ny = base.sinh( NaN )\n","base.sinpi":"var y = base.sinpi( 0.0 )\ny = base.sinpi( 0.5 )\ny = base.sinpi( 0.9 )\ny = base.sinpi( NaN )\n","base.slice2seq":"var out = base.slice2seq( new Slice( 1, 10, 1 ) )\nout = base.slice2seq( new Slice( null, 10 ) )\n","base.sliceLength":"var s = new Slice( 1, 10, 1 );\nbase.sliceLength( s )\n","base.sliceNonReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceNonReducedDimensions( s )\n","base.sliceReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceReducedDimensions( s )\n","base.sliceShape":"var s = new Slice( 1, 10, 1 );\nvar ms = new MultiSlice( s, s );\nbase.sliceShape( ms )\n","base.snakecase":"var out = base.snakecase( 'Hello World!' )\nout = base.snakecase( 'I am a tiny little teapot' )\n","base.spence":"var y = base.spence( 3.0 )\ny = base.spence( 0.0 )\ny = base.spence( -9.0 )\ny = base.spence( NaN )\n","base.sqrt":"var y = base.sqrt( 4.0 )\ny = base.sqrt( 9.0 )\ny = base.sqrt( 0.0 )\ny = base.sqrt( -4.0 )\ny = base.sqrt( NaN )\n","base.sqrt1pm1":"var y = base.sqrt1pm1( 3.0 )\ny = base.sqrt1pm1( 0.5 )\ny = base.sqrt1pm1( 0.02 )\ny = base.sqrt1pm1( -0.5 )\ny = base.sqrt1pm1( -1.1 )\ny = base.sqrt1pm1( NaN )\n","base.sqrtf":"var y = base.sqrtf( 4.0 )\ny = base.sqrtf( 9.0 )\ny = base.sqrtf( 0.0 )\ny = base.sqrtf( -4.0 )\ny = base.sqrtf( NaN )\n","base.sqrtpi":"var y = base.sqrtpi( 4.0 )\ny = base.sqrtpi( 10.0 )\ny = base.sqrtpi( 0.0 )\ny = base.sqrtpi( -4.0 )\ny = base.sqrtpi( NaN )\n","base.startcase":"var out = base.startcase( 'beep boop' )\n","base.startsWith":"var bool = base.startsWith( 'Beep', 'Be', 0 )\nbool = base.startsWith( 'Beep', 'ep', 0 )\nbool = base.startsWith( 'Beep', 'ee', 1 )\nbool = base.startsWith( 'Beep', 'ee', -3 )\nbool = base.startsWith( 'Beep', '', 0 )\n","base.stickycase":"var out = base.stickycase( 'Hello World!' )\nout = base.stickycase( 'I am a tiny little teapot' )\n","base.strided.binary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary( [ x, y, z ], shape, strides, f );\nz\n","base.strided.binary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\nz\n","base.strided.binaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n","base.strided.binarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\nvar t = {\n 'default': base.add,\n 'complex64': base.caddf,\n 'complex128': base.cadd\n };\nvar out = base.strided.binarySignatureCallbacks( t, sigs )\n","base.strided.ccopy":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy( x.length, x, 1, y, 1 )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy( 2, x, -2, y, 1 )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.ccopy( 2, x1, -2, y1, 1 )\ny0\n","base.strided.ccopy.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\nvar v = y.get( 0 )\ny = new Complex64Array( x.length );\nbase.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\nv = y.get( 0 )\nvar x0 = new Complex64Array( xbuf );\nvar y0 = new Complex64Array( x0.length );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\nv = y1.get( 0 )\n","base.strided.cmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\nvar v = y.get( 0 )\nx = new Complex64Array( xbuf );\ny = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\nv = y.get( y.length-1 )\n","base.strided.cswap":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap( x.length, x, 1, y, 1 );\nx\ny\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap( 2, x, -2, y, 1 );\nx\ny\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cswap( 2, x1, -2, y1, 1 );\nx0\ny0\n","base.strided.cswap.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\nx\ny\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nx\ny\n","base.strided.cumax":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumax( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.cumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.cumax.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumaxabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.cumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.cumaxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumin":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumin( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.cumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.cumin.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cuminabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.cuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.cuminabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs2":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs2.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dapx":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.dapx.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsum( 3, 5.0, x1, 2 )\n","base.strided.dapxsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn( 3, 5.0, x1, 2)\n","base.strided.dapxsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.dapxsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumors( 3, 5.0, x1, 2 )\n","base.strided.dapxsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dapxsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dasum":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum( x.length, x, 1 )\ns = base.strided.dasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.dasum( 3, x1, 2 )\n","base.strided.dasum.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.dasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.dasumpw( 3, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.dasumpw( 3, x1, stride )\n","base.strided.dasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.daxpy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.daxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.daxpy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.dceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcopy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dcopy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcuminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcuminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ddeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.ddeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddot":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.ddot( 3, x1, -2, y1, 1 )\n","base.strided.ddot.ndarray":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dfill":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.dfill.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dfloor":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.dfloor.ndarray":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.dinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( x.length, x, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( 2, x, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap( 2, x1, -2, y1, 1, base.identity )\ny0\n","base.strided.dmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n","base.strided.dmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\nz0\n","base.strided.dmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n","base.strided.dmax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmax( 3, x1, 2 )\n","base.strided.dmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmax.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabs( 3, x1, 2 )\n","base.strided.dmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabssorted":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabssorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabssorted( 3, x1, 2 )\n","base.strided.dmaxabssorted.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxsorted( 3, x1, 2 )\n","base.strided.dmaxsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmean":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmean( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmean( 3, x1, 2 )\n","base.strided.dmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmean.ndarray( 3, x, 2, 1 )\n","base.strided.dmeankbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeankbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeankbn( 3, x1, 2 )\n","base.strided.dmeankbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n","base.strided.dmeankbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeankbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeankbn2( 3, x1, 2 )\n","base.strided.dmeankbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanli":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanli( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanli( 3, x1, 2 )\n","base.strided.dmeanli.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanli.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanlipw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanlipw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanlipw( 3, x1, 2 )\n","base.strided.dmeanlipw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanlipw.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanors( 3, x1, 2 )\n","base.strided.dmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanpn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanpn( 3, x1, 2 )\n","base.strided.dmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanpn.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanpw( 3, x1, 2 )\n","base.strided.dmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( 3, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( 3, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( 3, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( 3, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvar":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar( 3, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar( 3, 1, x1, 2, out, 1 )\n","base.strided.dmeanvar.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvarpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( 3, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( 3, 1, x1, 2, out, 1 )\n","base.strided.dmeanvarpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanwd( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanwd( 3, x1, 2 )\n","base.strided.dmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.dmediansorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmediansorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmediansorted( 3, x1, 2 )\n","base.strided.dmediansorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmidrange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmidrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmidrange( 3, x1, 2 )\n","base.strided.dmidrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmidrange.ndarray( 3, x, 2, 1 )\n","base.strided.dmin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmin( N, x1, stride )\n","base.strided.dmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmin.ndarray( 3, x, 2, 1 )\n","base.strided.dminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminabs( 3, x1, 2 )\n","base.strided.dminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dminsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminsorted( 3, x1, 2 )\n","base.strided.dminsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmskabs":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskabs2":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskdeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskdeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskfloor":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskfloor.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.dmskmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.dmskmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\nz0\n","base.strided.dmskmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n","base.strided.dmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmax( 3, x1, 2, mask1, 2 )\n","base.strided.dmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmin( 3, x1, 2, mask1, 2 )\n","base.strided.dmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.dmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskrsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskrsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsksqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsksqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsktrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsktrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dnanasum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanasum( 4, x1, 2 )\n","base.strided.dnanasum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum.ndarray( 4, x, 2, 1 )\n","base.strided.dnanasumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanasumors( 4, x1, 2 )\n","base.strided.dnanasumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasumors.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmax":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmax( 3, x1, 2 )\n","base.strided.dnanmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmax.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmaxabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmaxabs( 3, x1, 2 )\n","base.strided.dnanmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmean":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmean( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmean( 4, x1,2 )\n","base.strided.dnanmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmean.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanors( 4, x1, 2 )\n","base.strided.dnanmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanors.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanpn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanpn( 4, x1, 2 )\n","base.strided.dnanmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanpn.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmeanpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanpw( 4, x1, 2 )\n","base.strided.dnanmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanwd( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanwd( 4, x1, 2 )\n","base.strided.dnanmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanwd.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmin":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmin( 3, x1, 2 )\n","base.strided.dnanmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmin.ndarray( 3, x, 2, 1 )\n","base.strided.dnanminabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanminabs( 3, x1, 2 )\n","base.strided.dnanminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmskmax( 3, x1, 2, mask1, 2 )\n","base.strided.dnanmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmskmin( 3, x1, 2, mask1, 2 )\n","base.strided.dnanmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.dnanmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dnannsum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x1, 2, out, 1 )\n","base.strided.dnannsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x1, 2, out, 1 )\n","base.strided.dnannsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x1, 2, out, 1 )\n","base.strided.dnannsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnanrange":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanrange( 3, x1, 2 )\n","base.strided.dnanrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanrange.ndarray( 3, x, 2, 1 )\n","base.strided.dnanstdev":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnanstdev( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdev( 3, 1, x1, 2 )\n","base.strided.dnanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnanstdev.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dnanstdevch":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevch( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevch( 4, 1, x1, 2 )\n","base.strided.dnanstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevch.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevpn( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevpn( 4, 1, x1, 2 )\n","base.strided.dnanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevpn.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanstdevtk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevtk( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevtk( 4, 1, x1, 2 )\n","base.strided.dnanstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevtk.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanstdevwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevwd( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevwd( 4, 1, x1, 2 )\n","base.strided.dnanstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevwd.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanstdevyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevyc( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevyc( 4, 1, x1, 2 )\n","base.strided.dnanstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevyc.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnansum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansum( 4, x1, 2 )\n","base.strided.dnansum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn( 4, x1, 2 )\n","base.strided.dnansumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn2( 4, x1, 2 )\n","base.strided.dnansumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumors( 4, x1, 2 )\n","base.strided.dnansumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumpw( 4, x1, 2 )\n","base.strided.dnansumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dnanvariance":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariance( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariance( 4, 1, x1, 2 )\n","base.strided.dnanvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariance.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvariancech":"var x = new Float64Array( [ 1.0, NaN, -2.0, 2.0 ] );\nbase.strided.dnanvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancech( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariancech( 4, 1, x1, 2 )\n","base.strided.dnanvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancech.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvariancepn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancepn( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariancepn( 4, 1, x1, 2 )\n","base.strided.dnanvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancepn.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvariancetk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancetk( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariancetk( 4, 1, x1, 2 )\n","base.strided.dnanvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancetk.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvariancewd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancewd( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariancewd( 4, 1, x1, 2 )\n","base.strided.dnanvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancewd.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnanvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvarianceyc( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvarianceyc( 4, 1, x1, 2 )\n","base.strided.dnanvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvarianceyc.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnrm2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnrm2( 3, x1, 2 )\n","base.strided.dnrm2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.dramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.dramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.drange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.drange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.drange( 3, x1, 2 )\n","base.strided.drange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.drange.ndarray( 3, x, 2, 1 )\n","base.strided.drev":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.drev( 3, x1, 2 )\nx0\n","base.strided.drev.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.drev.ndarray( 3, x, 2, 1 )\n","base.strided.drsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.drsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.drsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsum( 3, 5.0, x1, 2 )\n","base.strided.dsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dscal":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.dscal.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\ndot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n","base.strided.dsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dsem":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsem( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsem( 3, 1, x1, 2 )\n","base.strided.dsem.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsem.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemch( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemch( 3, 1, x1, 2 )\n","base.strided.dsemch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsempn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsempn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsempn( 3, 1, x1, 2 )\n","base.strided.dsempn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsempn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemtk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemtk( 3, 1, x1, 2 )\n","base.strided.dsemtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemwd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemwd( 3, 1, x1, 2 )\n","base.strided.dsemwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemyc( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemyc( 3, 1, x1, 2 )\n","base.strided.dsemyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmean( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmean( 3, x1, 2 )\n","base.strided.dsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmean.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanors( 3, x1, 2 )\n","base.strided.dsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanpn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanpn( 3, x1, 2 )\n","base.strided.dsmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanpw( 3, x1, 2 )\n","base.strided.dsmeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanwd( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanwd( 3, x1, 2 )\n","base.strided.dsmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.dsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmean( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnanmean( 4, x1, 2 )\n","base.strided.dsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmean.ndarray( 4, x, 2, 1 )\n","base.strided.dsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnanmeanors( 4, x1, 2 )\n","base.strided.dsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanors.ndarray( 4, x, 2, 1 )\n","base.strided.dsnanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanpn( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnanmeanpn( 4, x1, 2 )\n","base.strided.dsnanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanpn.ndarray( 4, x, 2, 1 )\n","base.strided.dsnanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanwd( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnanmeanwd( 4, x1, 2 )\n","base.strided.dsnanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanwd.ndarray( 4, x, 2, 1 )\n","base.strided.dsnannsumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors( x.length, x, 1, out, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( N, x1, 2, out, 1 )\n","base.strided.dsnannsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansum( 4, x1, 2 )\n","base.strided.dsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsnansum.ndarray( 3, x, 2, 1 )\n","base.strided.dsnansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumors( 4, x1, 2 )\n","base.strided.dsnansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumpw( 4, x1, 2 )\n","base.strided.dsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dsort2hp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2hp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2ins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2ins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2sh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2sh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsorthp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsorthp( 2, 1, x1, 2 )\nx0\n","base.strided.dsorthp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.dsortins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsortins( 2, 1, x1, 2 )\nx0\n","base.strided.dsortins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.dsortsh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortsh( N, 1, x1, 2 )\nx0\n","base.strided.dsortsh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssum( 3, x1, 2 )\n","base.strided.dssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssum.ndarray(3, x, 2, 1 )\n","base.strided.dssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumors( 3, x1, 2 )\n","base.strided.dssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumors.ndarray( 3, x, 2, 1 )\n","base.strided.dssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumpw( 3, x1, 2 )\n","base.strided.dssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdev( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdev( 3, 1, x1, 2 )\n","base.strided.dstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdev.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevch( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevch( 3, 1, x1, 2 )\n","base.strided.dstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevpn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevpn( 3, 1, x1, 2 )\n","base.strided.dstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevpn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevtk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevtk( 3, 1, x1, 2 )\n","base.strided.dstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevwd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevwd( 3, 1, x1, 2 )\n","base.strided.dstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc( x.length, 1.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevyc( 3, 1.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevyc( 3, 1.0, x1, 2 )\n","base.strided.dstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n","base.strided.dsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsum( 3, x1, 2 )\n","base.strided.dsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsum.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn( 3, x1, 2 )\n","base.strided.dsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn2( 3, x1, 2 )\n","base.strided.dsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.dsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumors( 3, x1, 2 )\n","base.strided.dsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumors.ndarray( 3, x, 2, 1 )\n","base.strided.dsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumpw( 3, x1, 2 )\n","base.strided.dsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dsvariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsvariance( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsvariance( 3, 1, x1, 2 )\n","base.strided.dsvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsvariance.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsvariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsvariancepn( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsvariancepn( 3, 1, x1, 2 )\n","base.strided.dsvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsvariancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dswap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dswap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dtrunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.dtrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtypeEnum2Str":"var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveEnum":"var out = base.strided.dtypeResolveEnum( 'float64' )\nout = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveStr":"var out = base.strided.dtypeResolveStr( 'float64' )\nout = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeStr2Enum":"var out = base.strided.dtypeStr2Enum( 'float64' )\n","base.strided.dvariance":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariance( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariance( 3, 1, x1, 2 )\n","base.strided.dvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariance.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancech":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancech( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancech( 3, 1, x1, 2 )\n","base.strided.dvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancepn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancepn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancepn( 3, 1, x1, 2 )\n","base.strided.dvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancetk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancetk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancetk( 3, 1, x1, 2 )\n","base.strided.dvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancewd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancewd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancewd( 3, 1, x1, 2 )\n","base.strided.dvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarianceyc( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarianceyc( 3, 1, x1, 2 )\n","base.strided.dvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvarm":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm( x.length, 1, 1.0/3.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarm( 3, 1, 1.0/3.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarm( 3, 1, 1.0/3.0, x1, 2 )\n","base.strided.dvarm.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nbase.strided.dvarm.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n","base.strided.dvarmpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn( x.length, 1, 1.0/3.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarmpn( 3, 1, 1.0/3.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarmpn( 3, 1, 1.0/3.0, x1, 2 )\n","base.strided.dvarmpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nbase.strided.dvarmpn.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n","base.strided.dvarmtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk( x.length, 1, 1.0/3.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarmtk( 3, 1, 1.0/3.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarmtk( 3, 1, 1.0/3.0, x1, 2 )\n","base.strided.dvarmtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nbase.strided.dvarmtk.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n","base.strided.gapx":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gapx( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gapx( 4, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.gapx.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsum( 3, 5.0, x1, 2 )\n","base.strided.gapxsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.gapxsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.gapxsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumors( 3, 5.0, x1, 2 )\n","base.strided.gapxsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.gapxsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gasum":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum( x.length, x, 1 )\ns = base.strided.gasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.gasum( 3, x1, 2 )\n","base.strided.gasum.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\ns = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.gasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.gasumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gasumpw( 3, x1, 2 )\n","base.strided.gasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.gasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.gaxpy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.gaxpy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcopy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gcopy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusum":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumors":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumpw":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gdot":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.gdot( 3, x1, -2, y1, 1 )\n","base.strided.gdot.ndarray":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nout = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.gfill":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.gfill.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gfillBy":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( x.length, x, 1, fill )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( 3, x, 2, fill )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gfillBy( 3, x1, 2, fill )\nx0\n","base.strided.gfillBy.ndarray":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n","base.strided.gnannsumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( x.length, x, 1, out, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( 4, x1, 2, out, 1 )\n","base.strided.gnannsumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.gnansum":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansum( 4, x1, 2 )\n","base.strided.gnansum.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansum.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumkbn( 4, x1, 2 )\n","base.strided.gnansumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumkbn2":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn2( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumkbn2( 4, x1, 2 )\n","base.strided.gnansumkbn2.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumors( 4, x1, 2 )\n","base.strided.gnansumors.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumpw":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumpw( 4, x1, 2 )\n","base.strided.gnansumpw.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.gnrm2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnrm2( 3, x1, 2 )\n","base.strided.gnrm2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.grev":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( x.length, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.grev( 3, x1, 2 )\nx0\n","base.strided.grev.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.grev.ndarray( 3, x, 2, 1 )\n","base.strided.gscal":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gscal( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.gscal.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gsort2hp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsort2hp( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2hp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2ins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2ins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2sh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsort2sh( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2sh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsorthp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsorthp( 2, 1, x1, 2 )\nx0\n","base.strided.gsorthp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.gsortins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsortins( 2, 1, x1, 2 )\nx0\n","base.strided.gsortins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.gsortsh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsortsh( 2, 1, x1, 2 )\nx0\n","base.strided.gsortsh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( 2, 1, x, 2, 1 )\n","base.strided.gsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsum( 3, x1, 2 )\n","base.strided.gsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsum.ndarray( 3, x, 2, 1 )\n","base.strided.gsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumkbn( 3, x1, 2 )\n","base.strided.gsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.gsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumkbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumkbn2( 3, x1, 2 )\n","base.strided.gsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.gsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumors( 3, x1, 2 )\n","base.strided.gsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumors.ndarray( 3, x, 2, 1 )\n","base.strided.gsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumpw( 3, x1, 2 )\n","base.strided.gsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumpw.ndarray( 3, x, 2, 1 )\n","base.strided.gswap":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gswap.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.mapBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\ny0\n","base.strided.mapBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n","base.strided.mapBy2":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\nz0\n","base.strided.mapBy2.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 1.0, 1.0, 2.0, 2.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n","base.strided.max":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.max( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.max( 3, x1, 2 )\n","base.strided.max.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.max.ndarray( 3, x, 2, 1 )\n","base.strided.maxabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.maxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.maxabs( 3, x1, 2 )\n","base.strided.maxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.maxabs.ndarray( 3, x, 2, 1 )\n","base.strided.maxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy( 3, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.maxBy( 3, x1, 2, accessor )\n","base.strided.maxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.maxBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.maxsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.maxsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.maxsorted( 3, x1, 2 )\n","base.strided.maxsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nbase.strided.maxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.maxViewBufferIndex":"var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n","base.strided.mean":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.mean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.mean( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.mean( 3, x1, 2 )\n","base.strided.mean.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.mean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.mean.ndarray( 3, x, 2, 1 )\n","base.strided.meankbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meankbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meankbn( 3, x1, 2 )\n","base.strided.meankbn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meankbn.ndarray( 3, x, 2, 1 )\n","base.strided.meankbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meankbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meankbn2( 3, x1, 2 )\n","base.strided.meankbn2.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meankbn2.ndarray( 3, x, 2, 1 )\n","base.strided.meanors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanors( 3, x1, 2 )\n","base.strided.meanors.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanors.ndarray( 3, x, 2, 1 )\n","base.strided.meanpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanpn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanpn( 3, x1, 2 )\n","base.strided.meanpn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meanpn.ndarray( 3, x, 2, 1 )\n","base.strided.meanpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanpw( 3, x1, 2 )\n","base.strided.meanpw.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meanpw.ndarray( 3, x, 2, 1 )\n","base.strided.meanwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanwd( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanwd( 3, x1, 2 )\n","base.strided.meanwd.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meanwd.ndarray( 3, x, 2, 1 )\n","base.strided.mediansorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.mediansorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.mediansorted( 3, x1, 2 )\n","base.strided.mediansorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nbase.strided.mediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.metaDataProps":"var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\nvar dt = [ 'float64', 'float64' ];\nvar obj = {};\nbase.strided.metaDataProps( meta, dt, obj, false );\nobj.nargs\nobj.nin\nobj.nout\nobj.types\n","base.strided.min":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.min( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.min( 3, x1, 2 )\n","base.strided.min.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.min.ndarray( 3, x, 2, 1 )\n","base.strided.minabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.minabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.minabs( 3, x1, 2 )\n","base.strided.minabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.minabs.ndarray( 3, x, 2, 1 )\n","base.strided.minBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\nbase.strided.minBy( 3, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.minBy( 3, x1, 2, accessor )\n","base.strided.minBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.minBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.minsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.minsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.minsorted( 3, x1, 2 )\n","base.strided.minsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nbase.strided.minsorted.ndarray( 3, x, 2, 1 )\n","base.strided.minViewBufferIndex":"var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n","base.strided.mskmax":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.mskmax( 3, x1, 2, mask1, 2 )\n","base.strided.mskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.mskmin":"var x = [ 1.0, -2.0, -4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.mskmin( 3, x1, 2, mask1, 2 )\n","base.strided.mskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.mskrange":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.mskrange( 3, x1, 2, mask1, 2 )\n","base.strided.mskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.mskunary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nbase.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\ny\n","base.strided.mskunary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nbase.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.mskunaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.mskunaryDtypeSignatures( dt, dt )\n","base.strided.mskunarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.mskunarySignatureCallbacks( t, sigs )\n","base.strided.nanmax":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmax( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmax( 4, x1, 2 )\n","base.strided.nanmax.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmax.ndarray( 4, x, 2, 1 )\n","base.strided.nanmaxabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmaxabs( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmaxabs( 4, x1, 2 )\n","base.strided.nanmaxabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmaxabs.ndarray( 4, x, 2, 1 )\n","base.strided.nanmaxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.nanmaxBy( 3, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmaxBy( 3, x1, 2, accessor )\n","base.strided.nanmaxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.nanmaxBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.nanmean":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanmean( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmean( 4, x1, 2 )\n","base.strided.nanmean.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmean.ndarray( 4, x, 2, 1 )\n","base.strided.nanmeanors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmeanors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmeanors( 4, x1, 2 )\n","base.strided.nanmeanors.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmeanors.ndarray( 4, x, 2, 1 )\n","base.strided.nanmeanpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanmeanpn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmeanpn( 4, x1, 2 )\n","base.strided.nanmeanpn.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmeanpn.ndarray( 4, x, 2, 1 )\n","base.strided.nanmeanwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanmeanwd( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmeanwd( 4, x1, 2 )\n","base.strided.nanmeanwd.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmeanwd.ndarray( 4, x, 2, 1 )\n","base.strided.nanmin":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmin( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmin( 4, x1, 2 )\n","base.strided.nanmin.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmin.ndarray( 4, x, 2, 1 )\n","base.strided.nanminabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanminabs( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanminabs( 4, x1, 2 )\n","base.strided.nanminabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanminabs.ndarray( 4, x, 2, 1 )\n","base.strided.nanminBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\nbase.strided.nanminBy( 4, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanminBy( 3, x1, 2, accessor )\n","base.strided.nanminBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.nanminBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.nanmskmax":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskmax( 4, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmskmax( 4, x1, 2, mask1, 2 )\n","base.strided.nanmskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0, NaN, NaN ];\nmask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmax.ndarray( 4, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskmin":"var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskmin( 4, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmskmin( 4, x1, 2, mask1, 2 )\n","base.strided.nanmskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0, NaN, NaN ];\nmask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin.ndarray( 4, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskrange":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskrange( 5, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.nanmskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskrange.ndarray( 5, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.nanrange":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanrange( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanrange( 4, x1, 2 )\n","base.strided.nanrange.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanrange.ndarray( 4, x, 2, 1 )\n","base.strided.nanrangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\nbase.strided.nanrangeBy( 4, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanrangeBy( 3, x1, 2, accessor )\n","base.strided.nanrangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.nanrangeBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.nanstdev":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdev( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0,NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdev( 4, 1, x1, 2 )\n","base.strided.nanstdev.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdev.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevch":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevch( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevch( 4, 1, x1, 2 )\n","base.strided.nanstdevch.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevch.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevpn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevpn( 4, 1, x1, 2 )\n","base.strided.nanstdevpn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevpn.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevtk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevtk( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevtk( 4, 1, x1, 2 )\n","base.strided.nanstdevtk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevtk.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevwd( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevwd( 4, 1, x1, 2 )\n","base.strided.nanstdevwd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevwd.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevyc( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevyc( 4, 1, x1, 2 )\n","base.strided.nanstdevyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevyc.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvariance":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanvariance( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariance( 4, 1, x1, 2 )\n","base.strided.nanvariance.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanvariance.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvariancech":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanvariancech( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariancech( 4, 1, x1, 2 )\n","base.strided.nanvariancech.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanvariancech.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvariancepn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.nanvariancepn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariancepn( 3, 1, x1, 2 )\n","base.strided.nanvariancepn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.nanvariancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.nanvariancetk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanvariancetk( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariancetk( 4, 1, x1, 2 )\n","base.strided.nanvariancetk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanvariancetk.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvariancewd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanvariancewd( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariancewd( 4, 1, x1, 2 )\n","base.strided.nanvariancewd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanvariancewd.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvarianceyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc( 4, 1.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.nanvarianceyc( 3, 1.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvarianceyc( 3, 1.0, x1, 2 )\n","base.strided.nanvarianceyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc.ndarray( 4, 1.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.nanvarianceyc.ndarray( 3, 1.0, x, 2, 1 )\n","base.strided.nullary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary( [ x ], shape, strides, fcn );\nx\n","base.strided.nullary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1 ];\nvar offsets = [ 0 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\nx\n","base.strided.offsetView":"var x = new Float64Array( 10 );\nvar out = base.strided.offsetView( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.quaternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\nu\n","base.strided.quaternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\nu\n","base.strided.quinary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\nv\n","base.strided.quinary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\nv\n","base.strided.range":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.range( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.range( 3, x1, 2 )\n","base.strided.range.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.range.ndarray( 3, x, 2, 1 )\n","base.strided.rangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy( 3, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.rangeBy( 3, x1, 2, accessor )\n","base.strided.rangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.rangeBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.reinterpretComplex":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex( x, 0 )\nvar bool = ( out.buffer === x.buffer )\nx = new Complex64Array( 10 );\nout = base.strided.reinterpretComplex( x, 0 )\nbool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex64":"var x = new Complex64Array( 10 );\nvar out = base.strided.reinterpretComplex64( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex128":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex128( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.sabs":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sabs2":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs2.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sapx":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.sapx.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsum( 3, 5.0, x1, 2 )\n","base.strided.sapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumors( 3, 5.0, x1, 2 )\n","base.strided.sapxsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.sapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sasum":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum( x.length, x, 1 )\ns = base.strided.sasum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.sasum( 3, x1, 2 )\n","base.strided.sasum.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.sasumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sasumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sasumpw( 3, x1, 2 )\n","base.strided.sasumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.saxpy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.saxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.saxpy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.scbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.scbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.sceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scopy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.scopy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumin( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scuminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scuminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sdeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.sdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdot( 3, x1, -2, y1, 1 )\n","base.strided.sdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsum( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n","base.strided.sdsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsmean( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsmean( 3, x1, 2 )\n","base.strided.sdsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsmean.ndarray( 3, x, 2, 1 )\n","base.strided.sdsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsmeanors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsmeanors( 3, x1, 2 )\n","base.strided.sdsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.sdsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmean( N, x1, stride )\n","base.strided.sdsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.sdsnanmeanors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnanmeanors( 3, x1, 2 )\n","base.strided.sdsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.sdsnanmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.sdsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnansum( 4, x1, 2 )\n","base.strided.sdsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n","base.strided.sdsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnansumpw( 4, x1, 2 )\n","base.strided.sdsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.sdssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdssum( 3, x1, 2 )\n","base.strided.sdssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssum.ndarray( 3, x, 2, 1 )\n","base.strided.sdssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdssumpw( 3, x1, 2 )\n","base.strided.sdssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sfill":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.sfill.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sfloor":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.sfloor.ndarray":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.sinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.smap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( x.length, x, 1, y, 1, base.identityf )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( 2, x, 2, y, -1, base.identityf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap( 2, x1, -2, y1, 1, base.identityf )\ny0\n","base.strided.smap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n","base.strided.smap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\nz0\n","base.strided.smap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n","base.strided.smax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smax( 3, x1, 2 )\n","base.strided.smax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smax.ndarray( N, x, 2, 1 )\n","base.strided.smaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabs( 3, x1, 2 )\n","base.strided.smaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.smaxabssorted":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabssorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabssorted( 3, x1, 2 )\n","base.strided.smaxabssorted.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n","base.strided.smaxsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxsorted( 3, x1, 2 )\n","base.strided.smaxsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.smean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smean( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smean( 3, x1, 2 )\n","base.strided.smean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smean.ndarray( 3, x, 2, 1 )\n","base.strided.smeankbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeankbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeankbn( 3, x1, 2 )\n","base.strided.smeankbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeankbn.ndarray( 3, x, 2, 1 )\n","base.strided.smeankbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeankbn2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeankbn2( 3, x1, 2 )\n","base.strided.smeankbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeankbn2.ndarray( 3, x, 2, 1 )\n","base.strided.smeanli":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanli( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanli( 3, x1, 2 )\n","base.strided.smeanli.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanli.ndarray( 3, x, 2, 1 )\n","base.strided.smeanlipw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanlipw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanlipw( 3, x1, 2 )\n","base.strided.smeanlipw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanlipw.ndarray( 3, x, 2, 1 )\n","base.strided.smeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanors( 3, x1, 2 )\n","base.strided.smeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanors.ndarray( 3, x, 2, 1 )\n","base.strided.smeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanpn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanpn( 3, x1, 2 )\n","base.strided.smeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanpn.ndarray( 3, x, 2, 1 )\n","base.strided.smeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanpw( 3, x1, 2 )\n","base.strided.smeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanpw.ndarray( 3, x, 2, 1 )\n","base.strided.smeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanwd( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanwd( 3, x1, 2 )\n","base.strided.smeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.smediansorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smediansorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smediansorted( 3, x1, 2 )\n","base.strided.smediansorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.smidrange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smidrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smidrange( 3, x1, 2 )\n","base.strided.smidrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smidrange.ndarray( 3, x, 2, 1 )\n","base.strided.smin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smin( 3, x1, 2 )\n","base.strided.smin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smin.ndarray( 3, x, 2, 1 )\n","base.strided.sminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminabs( 3, x1, 2 )\n","base.strided.sminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sminabs.ndarray( 3, x, 2, 1 )\n","base.strided.sminsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminsorted( 3, x1, 2 )\n","base.strided.sminsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( 3, x, 2, 1 )\n","base.strided.smskabs":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskabs2":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs2.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskcbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskcbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskfloor":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskfloor.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskmap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.smskmap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.smskmap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\nz0\n","base.strided.smskmap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n","base.strided.smskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmax( 3, x1, 2, mask1, 2 )\n","base.strided.smskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmin( 3, x1, 2, mask1, 2 )\n","base.strided.smskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskrange( 3, x1, 2, mask1, 2 )\n","base.strided.smskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskrsqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskrsqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsksqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsksqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsktrunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsktrunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.snanmax":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmax( 3, x1, 2 )\n","base.strided.snanmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmax.ndarray( 3, x, 2, 1 )\n","base.strided.snanmaxabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmaxabs( 3, x1, 2 )\n","base.strided.snanmaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmean( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmean( 4, x1, 2 )\n","base.strided.snanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snanmean.ndarray( 4, x, 2, 1 )\n","base.strided.snanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmeanors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmeanors( 4, x1, 2 )\n","base.strided.snanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanors.ndarray( 4, x, 2, 1 )\n","base.strided.snanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanpn( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmeanpn( 4, x1, 2 )\n","base.strided.snanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanpn.ndarray( 4, x, 2, 1 )\n","base.strided.snanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanwd( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmeanwd( 4, x1, 2 )\n","base.strided.snanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanwd.ndarray( 4, x, 2, 1 )\n","base.strided.snanmin":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmin( 3, x1, 2 )\n","base.strided.snanmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmin.ndarray( 3, x, 2, 1 )\n","base.strided.snanminabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanminabs( 3, x1, 2 )\n","base.strided.snanminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmskmax( 3, x1, 2, mask1, 2 )\n","base.strided.snanmskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmskmin( 3, x1, 2, mask1, 2 )\n","base.strided.snanmskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.snanmskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.snanrange":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanrange( 3, x1, 2 )\n","base.strided.snanrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanrange.ndarray( 3, x, 2, 1 )\n","base.strided.snanstdev":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdev( N, 1, x1, stride )\n","base.strided.snanstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevch":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevch( N, 1, x1, stride )\n","base.strided.snanstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevpn( N, 1, x1, stride )\n","base.strided.snanstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevtk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevtk( N, 1, x1, stride )\n","base.strided.snanstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevwd( N, 1, x1, stride )\n","base.strided.snanstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevyc( N, 1, x1, stride )\n","base.strided.snanstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansum( 4, x1, 2 )\n","base.strided.snansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansum.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumkbn( 4, x1, 2 )\n","base.strided.snansumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn2":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn2( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumkbn2( 4, x1, 2 )\n","base.strided.snansumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.snansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumors( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumors( 4, x1, stride )\n","base.strided.snansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumors.ndarray( 4, x, 2, 1 )\n","base.strided.snansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumpw( 4, x1, 2 )\n","base.strided.snansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.snanvariance":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariance( N, 1, x1, 2 )\n","base.strided.snanvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancech":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancech( N, 1, x1, 2 )\n","base.strided.snanvariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancepn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancepn( N, 1, x1, 2 )\n","base.strided.snanvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancetk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancetk( N, 1, x1, 2 )\n","base.strided.snanvariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancewd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancewd( N, 1, x1, 2 )\n","base.strided.snanvariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvarianceyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x1, 2 )\n","base.strided.snanvarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snrm2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.snrm2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snrm2( 3, x1, 2 )\n","base.strided.snrm2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.snrm2.ndarray( 3, x, 2, 1 )\n","base.strided.sramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.sramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.srange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.srange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srange( 3, x1, 2 )\n","base.strided.srange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.srange.ndarray( 3, x, 2, 1 )\n","base.strided.srev":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srev( 3, x1, 2 )\nx0\n","base.strided.srev.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.srev.ndarray( 3, x, 2, 1 )\n","base.strided.srsqrt":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.srsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.srsqrt.ndarray":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sscal":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.sscal.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.ssort2hp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2hp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2ins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2ins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2sh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2sh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssorthp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssorthp( 2, 1, x1, 2 )\nx0\n","base.strided.ssorthp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortins( 2, 1, x1, 2 )\nx0\n","base.strided.ssortins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortsh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortsh( 2, 1, x1, 2 )\nx0\n","base.strided.ssortsh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.ssqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sstdev":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdev( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdev( 3, 1, x1, 2 )\n","base.strided.sstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdev.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevch":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevch( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevch( 3, 1, x1, 2 )\n","base.strided.sstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevpn( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevpn( 3, 1, x1, 2 )\n","base.strided.sstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevpn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevtk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevtk( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevtk( 3, 1, x1, 2 )\n","base.strided.sstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevwd( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevwd( 3, 1, x1, 2 )\n","base.strided.sstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevyc( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevyc( 3, 1, x1, 2 )\n","base.strided.sstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.ssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssum( 3, x1, 2 )\n","base.strided.ssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssum.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn( 3, x1, 2 )\n","base.strided.ssumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn2( 3, x1, 2 )\n","base.strided.ssumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.ssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumors( 3, x1, 2 )\n","base.strided.ssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumors.ndarray( 3, x, 2, 1 )\n","base.strided.ssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumpw( 3, x1, 2 )\n","base.strided.ssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sswap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.sswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.sswap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.stdev":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdev( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdev( 3, 1, x1, 2 )\n","base.strided.stdev.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdev.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevch":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevch( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevch( 3, 1, x1, 2 )\n","base.strided.stdevch.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevpn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevpn( 3, 1, x1, 2 )\n","base.strided.stdevpn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevpn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevtk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevtk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevtk( 3, 1, x1, 2 )\n","base.strided.stdevtk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevwd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevwd( 3, 1, x1, 2 )\n","base.strided.stdevwd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevyc( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevyc( 3, 1, x1, 2 )\n","base.strided.stdevyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.strunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.strunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.strunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.svariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariance( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariance( 3, 1, x1, 2 )\n","base.strided.svariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariance.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancech":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancech( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancech( 3, 1, x1, 2 )\n","base.strided.svariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancepn( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancepn( 3, 1, x1, 2 )\n","base.strided.svariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancetk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancetk( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancetk( 3, 1, x1, 2 )\n","base.strided.svariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancewd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancewd( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancewd( 3, 1, x1, 2 )\n","base.strided.svariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancewd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svarianceyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svarianceyc( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svarianceyc( 3, 1, x1, 2 )\n","base.strided.svarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.ternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary( [ x, y, z, w ], shape, strides, f );\nw\n","base.strided.ternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\nw\n","base.strided.unary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nbase.strided.unary( [ x, y ], shape, strides, base.abs );\ny\n","base.strided.unary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar offsets = [ 0, 0 ];\nbase.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.unaryBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nsh = [ 2 ];\nst = [ -2, 1 ];\nbase.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\ny1\ny0\n","base.strided.unaryBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nvar o = [ 0, 0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\no = [ 1, y.length-1 ];\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\n","base.strided.unaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.unaryDtypeSignatures( dt, dt )\n","base.strided.unarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.unaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.unarySignatureCallbacks( t, sigs )\n","base.strided.variance":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variance( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variance( 3, 1, x1, 2 )\n","base.strided.variance.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variance.ndarray( 3, 1, x, 2, 1 )\n","base.strided.variancech":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variancech( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variancech( 3, 1, x1, 2 )\n","base.strided.variancech.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variancech.ndarray( 3, 1, x, 2, 1 )\n","base.strided.variancepn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variancepn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variancepn( 3, 1, x1, 2 )\n","base.strided.variancepn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.variancetk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variancetk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variancetk( 3, 1, x1, 2 )\n","base.strided.variancetk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variancetk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.variancewd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variancewd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variancewd( 3, 1, x1, 2 )\n","base.strided.variancewd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variancewd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.varianceyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc( x.length, 1.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.varianceyc( 3, 1.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.varianceyc( 3, 1.0, x1, 2 )\n","base.strided.varianceyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc.ndarray( x.length, 1.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.varianceyc.ndarray( 3, 1.0, x, 2, 1 )\n","base.strided.zmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\nvar v = y.get( 0 )\ny = new Complex128Array( x.length );\nbase.strided.zmap( 2, x, 2, y, -1, base.cidentity );\nv = y.get( 0 )\nvar x0 = new Complex128Array( xbuf );\nvar y0 = new Complex128Array( x0.length );\nvar x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\nv = y1.get( 0 )\n","base.strided.zmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\nvar v = y.get( 0 )\nx = new Complex128Array( xbuf );\ny = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\nv = y.get( y.length-1 )\n","base.str2multislice":"var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\ns.data\ns = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\ns.data\n","base.str2slice":"var s = new base.str2slice( 'Slice(1,10,1)' );\ns.start\ns.stop\ns.step\ns = new base.str2slice( 'Slice(2,5,2)' );\ns.start\ns.stop\ns.step\n","base.sub":"var v = base.sub( -1.0, 5.0 )\nv = base.sub( 2.0, 5.0 )\nv = base.sub( 0.0, 5.0 )\nv = base.sub( -0.0, 0.0 )\nv = base.sub( NaN, NaN )\n","base.subf":"var v = base.subf( -1.0, 5.0 )\nv = base.subf( 2.0, 5.0 )\nv = base.subf( 0.0, 5.0 )\nv = base.subf( -0.0, 0.0 )\nv = base.subf( NaN, NaN )\n","base.sumSeries":"function* geometricSeriesGenerator( x ) {\n var exponent = 0;\n while ( true ) {\n yield Math.pow( x, exponent );\n exponent += 1;\n }\n };\nvar gen = geometricSeriesGenerator( 0.9 );\nvar out = base.sumSeries( gen )\nfunction geometricSeriesClosure( x ) {\n var exponent = -1;\n return function() {\n exponent += 1;\n return Math.pow( x, exponent );\n };\n };\ngen = geometricSeriesClosure( 0.9 );\nout = base.sumSeries( gen )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n","base.tan":"var y = base.tan( 0.0 )\ny = base.tan( -PI/4.0 )\ny = base.tan( PI/4.0 )\ny = base.tan( NaN )\n","base.tand":"var y = base.tand( 0.0 )\ny = base.tand( 90.0 )\ny = base.tand( 60.0 )\ny = base.tand( NaN )\n","base.tanh":"var y = base.tanh( 0.0 )\nvar y = base.tanh( -0.0 )\ny = base.tanh( 2.0 )\ny = base.tanh( -2.0 )\ny = base.tanh( NaN )\n","base.toBinaryString":"var str = base.toBinaryString( 4.0 )\nstr = base.toBinaryString( PI )\nstr = base.toBinaryString( -1.0e308 )\nstr = base.toBinaryString( -3.14e-320 )\nstr = base.toBinaryString( 5.0e-324 )\nstr = base.toBinaryString( 0.0 )\nstr = base.toBinaryString( -0.0 )\nstr = base.toBinaryString( NaN )\nstr = base.toBinaryString( PINF )\nstr = base.toBinaryString( NINF )\n","base.toBinaryStringf":"var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( PI ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\nstr = base.toBinaryStringf( 0.0 )\nstr = base.toBinaryStringf( -0.0 )\nstr = base.toBinaryStringf( NaN )\nstr = base.toBinaryStringf( FLOAT32_PINF )\nstr = base.toBinaryStringf( FLOAT32_NINF )\n","base.toBinaryStringUint8":"var a = new Uint8Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint8( a[ 0 ] )\nstr = base.toBinaryStringUint8( a[ 1 ] )\nstr = base.toBinaryStringUint8( a[ 2 ] )\n","base.toBinaryStringUint16":"var a = new Uint16Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint16( a[ 0 ] )\nstr = base.toBinaryStringUint16( a[ 1 ] )\nstr = base.toBinaryStringUint16( a[ 2 ] )\n","base.toBinaryStringUint32":"var a = new Uint32Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint32( a[ 0 ] )\nstr = base.toBinaryStringUint32( a[ 1 ] )\nstr = base.toBinaryStringUint32( a[ 2 ] )\n","base.toWordf":"var f32 = base.float64ToFloat32( 1.337 )\nvar w = base.toWordf( f32 )\n","base.toWords":"var w = base.toWords( 3.14e201 )\n","base.toWords.assign":"var out = new Uint32Array( 2 );\nvar w = base.toWords.assign( 3.14e201, out, 1, 0 )\nvar bool = ( w === out )\n","base.transpose":"var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nvar y = base.transpose( x, false )\n","base.tribonacci":"var y = base.tribonacci( 0 )\ny = base.tribonacci( 1 )\ny = base.tribonacci( 2 )\ny = base.tribonacci( 3 )\ny = base.tribonacci( 4 )\ny = base.tribonacci( 64 )\ny = base.tribonacci( NaN )\n","base.trigamma":"var y = base.trigamma( -2.5 )\ny = base.trigamma( 1.0 )\ny = base.trigamma( 10.0 )\ny = base.trigamma( NaN )\ny = base.trigamma( -1.0 )\n","base.trim":"var out = base.trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","base.trunc":"var y = base.trunc( 3.14 )\ny = base.trunc( -4.2 )\ny = base.trunc( -4.6 )\ny = base.trunc( 9.5 )\ny = base.trunc( -0.0 )\n","base.trunc2":"var y = base.trunc2( 3.14 )\ny = base.trunc2( -4.2 )\ny = base.trunc2( -4.6 )\ny = base.trunc2( 9.5 )\ny = base.trunc2( 13.0 )\ny = base.trunc2( -13.0 )\ny = base.trunc2( -0.0 )\n","base.trunc10":"var y = base.trunc10( 3.14 )\ny = base.trunc10( -4.2 )\ny = base.trunc10( -4.6 )\ny = base.trunc10( 9.5 )\ny = base.trunc10( 13.0 )\ny = base.trunc10( -13.0 )\ny = base.trunc10( -0.0 )\n","base.truncateMiddle":"var str = 'beep boop';\nvar out = base.truncateMiddle( str, 5, '...' )\nout = base.truncateMiddle( str, 5, '|' )\n","base.truncb":"var y = base.truncb( 3.14159, -4, 10 )\ny = base.truncb( 3.14159, 0, 2 )\ny = base.truncb( 5.0, 1, 2 )\n","base.truncf":"var y = base.truncf( 3.14 )\ny = base.truncf( -4.2 )\ny = base.truncf( -4.6 )\ny = base.truncf( 9.5 )\ny = base.truncf( -0.0 )\n","base.truncn":"var y = base.truncn( 3.14159, -4 )\ny = base.truncn( 3.14159, 0 )\ny = base.truncn( 12368.0, 3 )\n","base.truncsd":"var y = base.truncsd( 3.14159, 5, 10 )\ny = base.truncsd( 3.14159, 1, 10 )\ny = base.truncsd( 12368.0, 2, 10 )\ny = base.truncsd( 0.0313, 2, 2 )\n","base.uint32ToInt32":"var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\ny = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n","base.umul":"var v = base.umul( 10>>>0, 4>>>0 )\n","base.umuldw":"var v = base.umuldw( 1, 10 )\n","base.umuldw.assign":"var out = [ 0, 0 ];\nvar v = base.umuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.uncapitalize":"var out = base.uncapitalize( 'Beep' )\nout = base.uncapitalize( 'bOOp' )\n","base.uppercase":"var out = base.uppercase( 'bEEp' )\n","base.vercos":"var y = base.vercos( 3.14 )\ny = base.vercos( -4.2 )\ny = base.vercos( -4.6 )\ny = base.vercos( 9.5 )\ny = base.vercos( -0.0 )\n","base.versin":"var y = base.versin( 3.14 )\ny = base.versin( -4.2 )\ny = base.versin( -4.6 )\ny = base.versin( 9.5 )\ny = base.versin( -0.0 )\n","base.wrap":"var y = base.wrap( 3.14, 0.0, 5.0 )\ny = base.wrap( -3.14, 0.0, 5.0 )\ny = base.wrap( 3.14, 0.0, 3.0 )\ny = base.wrap( -0.0, 0.0, 5.0 )\ny = base.wrap( 0.0, -3.14, -0.0 )\ny = base.wrap( NaN, 0.0, 5.0 )\n","base.xlog1py":"var out = base.xlog1py( 3.0, 2.0 )\nout = base.xlog1py( 1.5, 5.9 )\nout = base.xlog1py( 0.9, 1.0 )\nout = base.xlog1py( 1.0, 0.0 )\nout = base.xlog1py( 0.0, -2.0 )\nout = base.xlog1py( 1.5, NaN )\nout = base.xlog1py( 0.0, NaN )\nout = base.xlog1py( NaN, 2.3 )\n","base.xlogy":"var out = base.xlogy( 3.0, 2.0 )\nout = base.xlogy( 1.5, 5.9 )\nout = base.xlogy( 0.9, 1.0 )\nout = base.xlogy( 0.0, -2.0 )\nout = base.xlogy( 1.5, NaN )\nout = base.xlogy( 0.0, NaN )\nout = base.xlogy( NaN, 2.3 )\n","base.zeta":"var y = base.zeta( 1.1 )\ny = base.zeta( -4.0 )\ny = base.zeta( 70.0 )\ny = base.zeta( 0.5 )\ny = base.zeta( NaN )\ny = base.zeta( 1.0 )\n","BERNDT_CPS_WAGES_1985":"var data = BERNDT_CPS_WAGES_1985()\n","bifurcate":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar f = [ true, true, false, true ];\nvar out = bifurcate( collection, f )\nf = [ 1, 1, 0, 1 ];\nout = bifurcate( collection, f )\nf = [ true, true, false, true ];\nvar opts = { 'returns': 'indices' };\nout = bifurcate( collection, opts, f )\nopts = { 'returns': '*' };\nout = bifurcate( collection, opts, f )\n","bifurcateBy":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = bifurcateBy( collection, predicate )\nvar opts = { 'returns': 'indices' };\nout = bifurcateBy( collection, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateBy( collection, opts, predicate )\n","bifurcateByAsync":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, predicate, done )\nvar opts = { 'returns': 'indices' };\nbifurcateByAsync( arr, opts, predicate, done )\nopts = { 'returns': '*' };\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n","bifurcateByAsync.factory":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = bifurcateByAsync.factory( opts, predicate );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","bifurcateIn":"function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nfunction predicate( v ) { return v[ 0 ] === 'b'; };\nvar out = bifurcateIn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateIn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateIn( obj, opts, predicate )\n","bifurcateOwn":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = bifurcateOwn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateOwn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateOwn( obj, opts, predicate )\n","BigInt":"var v = ( BigInt ) ? BigInt( '1' ) : null\n","binomialTest":"var out = binomialTest( 682, 925 )\nout = binomialTest( [ 682, 925 - 682 ] )\nout = binomialTest( 21, 40, {\n 'p': 0.4,\n 'alternative': 'greater'\n })\n","Boolean":"var b = new Boolean( null )\nb = Boolean( null )\nb = Boolean( [] )\n","Boolean.prototype.toString":"var b = new Boolean( true )\nb.toString()\n","Boolean.prototype.valueOf":"var b = new Boolean( true )\nb.valueOf()\n","BooleanArray":"var arr = new BooleanArray()\nvar arr = new BooleanArray( 10 )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar arr2 = new BooleanArray( arr1 )\nvar len = arr2.length\nvar buf = new Uint8Array( [ 1, 0, 0, 1 ] )\nvar arr = new BooleanArray( buf )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar len = arr1.length\nvar arr2 = new BooleanArray( [ {}, null, '', 4 ] );\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new BooleanArray( buf )\nvar len = arr1.length\nvar arr2 = new BooleanArray( buf, 8 )\nlen = arr2.length\nvar arr3 = new BooleanArray( buf, 8, 20 )\nlen = arr3.length\n","BooleanArray.from":"function map( v ) { return !v };\nvar src = [ true, false ];\nvar arr = BooleanArray.from( src, map )\nvar len = arr.length\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.of":"var arr = BooleanArray.of( true, false, false, true )\nvar len = arr.length\n","BooleanArray.BYTES_PER_ELEMENT":"var nbytes = BooleanArray.BYTES_PER_ELEMENT\n","BooleanArray.name":"var str = BooleanArray.name\n","BooleanArray.prototype.buffer":"var arr = new BooleanArray( 2 )\nvar buf = arr.buffer\n","BooleanArray.prototype.byteLength":"var arr = new BooleanArray( 10 )\nvar nbytes = arr.byteLength\n","BooleanArray.prototype.byteOffset":"var arr = new BooleanArray( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new BooleanArray( buf, 64 )\noffset = arr.byteOffset\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"var arr = new BooleanArray( 10 )\narr.BYTES_PER_ELEMENT\n","BooleanArray.prototype.length":"var arr = new BooleanArray( 10 )\nvar len = arr.length\n","BooleanArray.prototype.at":"var arr = new BooleanArray( [ true, false, false, true ] )\nvar v = arr.at( 1 )\nv = arr.at( -1 )\n","BooleanArray.prototype.copyWithin":"var arr = new BooleanArray( [ true, false, false, true ] )\narr.copyWithin( 0, 2 )\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.prototype.entries":"var arr = new BooleanArray( [ true, false, true ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.every":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, true, true ] )\nvar bool = arr.every( predicate )\n","BooleanArray.prototype.fill":"var arr = new BooleanArray( 3 )\narr.fill( true );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.filter":"function predicate( v ) { return ( v === true ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.find":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.find( predicate )\n","BooleanArray.prototype.findIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findIndex( predicate )\n","BooleanArray.prototype.findLast":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.findLast( predicate )\n","BooleanArray.prototype.findLastIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findLastIndex( predicate )\n","BooleanArray.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new BooleanArray( [ true, false, false, true ] )\narr.forEach( clbk );\nstr\n","BooleanArray.prototype.get":"var arr = new BooleanArray( 10 )\narr.set( true, 0 );\nvar v = arr.get( 0 )\n","BooleanArray.prototype.includes":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar bool = arr.includes( true )\nbool = arr.includes( false, 3 )\n","BooleanArray.prototype.indexOf":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar idx = arr.indexOf( true )\nidx = arr.indexOf( false, 3 )\n","BooleanArray.prototype.join":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.join()\nstr = arr.join( '|' )\n","BooleanArray.prototype.keys":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","BooleanArray.prototype.lastIndexOf":"var arr = new BooleanArray( [ true, true, true, false, true ] )\nvar idx = arr.lastIndexOf( false )\nidx = arr.lastIndexOf( false, 2 )\n","BooleanArray.prototype.map":"function invert( v ) { return !v; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.map( invert )\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.reduce":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduce( reducer )\n","BooleanArray.prototype.reduceRight":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduceRight( reducer )\n","BooleanArray.prototype.reverse":"var arr = new BooleanArray( [ true, false, false ] )\narr.reverse();\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.set":"var arr = new BooleanArray( 2 )\narr.set( false );\nvar v = arr.get( 0 )\narr.set( true, 1 );\nv = arr.get( 1 )\n","BooleanArray.prototype.slice":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.some":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ false, true, false ] )\nvar bool = arr.some( predicate )\n","BooleanArray.prototype.sort":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\narr.sort( compare );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.subarray":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.toLocaleString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toLocaleString()\n","BooleanArray.prototype.toReversed":"var arr = new BooleanArray( [ true, false, false ] )\nvar out = arr.toReversed()\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toSorted":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.toSorted( compare );\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toString()\n","BooleanArray.prototype.values":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.values();\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.with":"var arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.with( 0, false )\nvar v = out.get( 0 )\n","broadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = broadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","broadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = broadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","Buffer":"var b = new Buffer( 4 )\nvar b1 = new Buffer( [ 1, 2, 3, 4 ] );\nvar b2 = new Buffer( b1 )\nvar b = new Buffer( [ 1, 2, 3, 4 ] )\nvar b = new Buffer( 'beep boop' )\n","buffer2json":"var buf = new allocUnsafe( 2 );\nbuf[ 0 ] = 1;\nbuf[ 1 ] = 2;\nvar json = buffer2json( buf )\n","BYTE_ORDER":"BYTE_ORDER\n","camelcase":"var out = camelcase( 'Hello World!' )\nout = camelcase( 'beep boop' )\n","capitalize":"var out = capitalize( 'beep' )\nout = capitalize( 'Boop' )\n","capitalizeKeys":"var obj = { 'aa': 1, 'bb': 2 };\nvar out = capitalizeKeys( obj )\n","CATALAN":"CATALAN\n","CBRT_EPS":"CBRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"var data = CDC_NCHS_US_BIRTHS_1969_1988()\n","CDC_NCHS_US_BIRTHS_1994_2003":"var data = CDC_NCHS_US_BIRTHS_1994_2003()\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n","chdir":"var err = chdir( '/path/to/current/working/directory' )\n","chi2gof":"var x = [ 89, 37, 30, 28, 2 ];\nvar p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nvar out = chi2gof( x, p );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.01 };\nout = chi2gof( x, p, opts );\nout.toString()\nx = [ 89, 37, 30, 28, 2 ];\np = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nopts = { 'simulate': true, 'iterations': 1000 };\nout = chi2gof( x, p, opts );\nout.toString()\nvar lambda = 3.0;\nvar rpois = base.random.poisson.factory( lambda );\nvar len = 400;\nx = [];\nfor ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\nvar freqs = new Int32Array( len );\nfor ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\nout = chi2gof( freqs, 'poisson', lambda );\nout.toString()\n","chi2test":"var x = [ [ 20, 30 ], [ 30, 20 ] ];\nvar out = chi2test( x );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.1 };\nout = chi2test( x, opts );\no = out.toJSON()\nout.toString()\nopts = { 'correct': false };\nout = chi2test( x, opts );\nout.toString()\n","circarray2iterator":"var it = circarray2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","circularArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","circularArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = circularArrayStream.factory( opts );\n","circularArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","CircularBuffer":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.length\nb.count\nb.push( 'boop' )\n","CircularBuffer.prototype.clear":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.count\nb.clear();\nb.count\n","CircularBuffer.prototype.count":"var b = CircularBuffer( 3 );\nb.count\nb.push( 'foo' );\nb.count\nb.push( 'bar' );\nb.count\n","CircularBuffer.prototype.full":"var b = CircularBuffer( 3 );\nb.full\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.full\n","CircularBuffer.prototype.iterator":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar it = b.iterator( b.length );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","CircularBuffer.prototype.length":"var b = CircularBuffer( [ 0, 0, 0 ] );\nvar len = b.length\n","CircularBuffer.prototype.push":"var b = CircularBuffer( 3 );\nb.push( 'foo' )\nb.push( 'bar' )\nb.push( 'beep' )\nb.push( 'boop' )\n","CircularBuffer.prototype.toArray":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar vals = b.toArray()\n","CircularBuffer.prototype.toJSON":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar o = b.toJSON()\n","close":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nvar fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close( fd, done ); };\n","close.sync":"var fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","CMUDICT":"var data = CMUDICT();\nvar dict = data.dict\nvar phones = data.phones\nvar symbols = data.symbols\nvar vp = data.vp\n","codePointAt":"var out = codePointAt( 'last man standing', 4 )\nout = codePointAt( 'presidential election', 8, true )\nout = codePointAt( 'अनुच्छेद', 2 )\nout = codePointAt( '🌷', 1, true )\n","commonKeys":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeys( obj1, obj2 )\n","commonKeysIn":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeysIn( obj1, obj2 )\n","complex":"var z = complex( 5.0, 3.0, 'float64' )\nz = complex( 5.0, 3.0, 'float32' )\n","Complex64":"var z = new Complex64( 5.0, 3.0 )\nz.re\nz.im\n","Complex64.name":"var str = Complex64.name\n","Complex64.BYTES_PER_ELEMENT":"var s = Complex64.BYTES_PER_ELEMENT\n","Complex64.prototype.BYTES_PER_ELEMENT":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex64.prototype.byteLength":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX64_NAN":"COMPLEX64_NAN\n","COMPLEX64_NUM_BYTES":"COMPLEX64_NUM_BYTES\n","COMPLEX64_ZERO":"COMPLEX64_ZERO\n","Complex64Array":"var arr = new Complex64Array()\nvar arr = new Complex64Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex64Array( arr1 )\nvar len = arr2.length\nvar buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex64Array( buf )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\nvar arr2 = new Complex64Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new Complex64Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex64Array( buf, 8 )\nlen = arr2.length\nvar arr3 = new Complex64Array( buf, 8, 20 )\nlen = arr3.length\n","Complex64Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.of":"var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex64( 1.0, -1.0 );\nvar z2 = new Complex64( 2.0, -2.0 );\narr = Complex64Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.BYTES_PER_ELEMENT":"var nbytes = Complex64Array.BYTES_PER_ELEMENT\n","Complex64Array.name":"var str = Complex64Array.name\n","Complex64Array.prototype.buffer":"var arr = new Complex64Array( 2 )\nvar buf = arr.buffer\n","Complex64Array.prototype.byteLength":"var arr = new Complex64Array( 10 )\nvar nbytes = arr.byteLength\n","Complex64Array.prototype.byteOffset":"var arr = new Complex64Array( 5 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new Complex64Array( buf, 64 )\noffset = arr.byteOffset\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex64Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex64Array.prototype.length":"var arr = new Complex64Array( 10 )\nvar len = arr.length\n","Complex64Array.prototype.at":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.copyWithin":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.entries":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nvar re = realf( v[ 1 ] )\nvar im = imagf( v[ 1 ] )\nv = it.next().value\nre = realf( v[ 1 ] )\nim = imagf( v[ 1 ] )\nv = it.next().value\nre = realf( v[ 1 ] )\nim = imagf( v[ 1 ] )\nvar bool = it.next().done\n","Complex64Array.prototype.every":"function predicate( v ) { return ( realf( v ) > 0.0 ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex64Array.prototype.fill":"var arr = new Complex64Array( 3 )\narr.fill( new Complex64( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.filter":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.find":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.findIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex64Array.prototype.findLast":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.findLastIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex64Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex64Array.prototype.get":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.includes":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex64( 3.0, -3.0 ) )\nbool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.indexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.join":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex64Array.prototype.keys":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex64Array.prototype.lastIndexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n","Complex64Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.reduce":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.caddf )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.reduceRight":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.caddf )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.reverse":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.set":"var arr = new Complex64Array( 2 )\narr.set( new Complex64( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\narr.set( new Complex64( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.slice":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.some":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex64Array.prototype.sort":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.subarray":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toLocaleString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex64Array.prototype.toReversed":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = out.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toSorted":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = out.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex64Array.prototype.values":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nvar re = realf( v )\nvar im = imagf( v )\nv = it.next().value\nre = realf( v )\nim = imagf( v )\nvar bool = it.next().done\n","Complex64Array.prototype.with":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex128.name":"var str = Complex128.name\n","Complex128.BYTES_PER_ELEMENT":"var s = Complex128.BYTES_PER_ELEMENT\n","Complex128.prototype.BYTES_PER_ELEMENT":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex128.prototype.byteLength":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX128_NAN":"COMPLEX128_NAN\n","COMPLEX128_NUM_BYTES":"COMPLEX128_NUM_BYTES\n","COMPLEX128_ZERO":"COMPLEX128_ZERO\n","Complex128Array":"var arr = new Complex128Array()\nvar arr = new Complex128Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex128Array( arr1 )\nvar len = arr2.length\nvar buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex128Array( buf )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\nvar arr2 = new Complex128Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 480 );\nvar arr1 = new Complex128Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex128Array( buf, 16 )\nlen = arr2.length\nvar arr3 = new Complex128Array( buf, 16, 20 )\nlen = arr3.length\n","Complex128Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.of":"var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex128( 1.0, -1.0 );\nvar z2 = new Complex128( 2.0, -2.0 );\narr = Complex128Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.BYTES_PER_ELEMENT":"var nbytes = Complex128Array.BYTES_PER_ELEMENT\n","Complex128Array.name":"var str = Complex128Array.name\n","Complex128Array.prototype.buffer":"var arr = new Complex128Array( 2 )\nvar buf = arr.buffer\n","Complex128Array.prototype.byteLength":"var arr = new Complex128Array( 10 )\nvar nbytes = arr.byteLength\n","Complex128Array.prototype.byteOffset":"var arr = new Complex128Array( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 480 );\narr = new Complex128Array( buf, 128 )\noffset = arr.byteOffset\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex128Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex128Array.prototype.length":"var arr = new Complex128Array( 10 )\nvar len = arr.length\n","Complex128Array.prototype.at":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.copyWithin":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.entries":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nvar re = real( v[ 1 ] )\nvar im = imag( v[ 1 ] )\nv = it.next().value\nre = real( v[ 1 ] )\nim = imag( v[ 1 ] )\nv = it.next().value\nre = real( v[ 1 ] )\nim = imag( v[ 1 ] )\nvar bool = it.next().done\n","Complex128Array.prototype.every":"function predicate( v ) { return ( real( v ) > 0.0 ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex128Array.prototype.fill":"var arr = new Complex128Array( 3 )\narr.fill( new Complex128( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.filter":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.find":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.findIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex128Array.prototype.findLast":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.findLastIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex128Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex128Array.prototype.get":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.includes":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex128( 3.0, -3.0 ) )\nbool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.indexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.join":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex128Array.prototype.keys":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex128Array.prototype.lastIndexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n","Complex128Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.reduce":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.cadd )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.reduceRight":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.cadd )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.reverse":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.set":"var arr = new Complex128Array( 2 )\narr.set( new Complex128( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\narr.set( new Complex128( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.slice":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.some":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex128Array.prototype.sort":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.subarray":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toLocaleString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex128Array.prototype.toReversed":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toSorted":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex128Array.prototype.values":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nvar re = real( v )\nvar im = imag( v )\nv = it.next().value\nre = real( v )\nim = imag( v )\nvar bool = it.next().done\n","Complex128Array.prototype.with":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\nvar re = real( z )\nvar im = imag( z )\n","complexarray":"var arr = complexarray()\narr = complexarray( 'complex64' )\nvar arr = complexarray( 5 )\narr = complexarray( 5, 'complex64' )\nvar arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\nvar arr2 = complexarray( arr1, 'complex64' )\nvar arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\nvar arr2 = complexarray( arr1, 'complex64' )\nvar buf = new ArrayBuffer( 64 );\nvar arr = complexarray( buf, 0, 8, 'complex64' )\n","complexarrayCtors":"var ctor = complexarrayCtors( 'complex64' )\nctor = complexarrayCtors( 'float32' )\n","complexarrayDataTypes":"var out = complexarrayDataTypes()\n","complexCtors":"var ctor = complexCtors( 'complex128' )\nctor = complexCtors( 'complex' )\n","complexDataType":"var v = new Complex128( 1.0, 2.0 );\nvar dt = complexDataType( v )\ndt = complexDataType( 'beep' )\n","complexDataTypes":"var out = complexDataTypes()\n","complexPromotionRules":"var out = complexPromotionRules( 'complex128', 'complex64' )\n","compose":"function a( x ) {\nreturn 2 * x;\n }\nfunction b( x ) {\nreturn x + 3;\n }\nfunction c( x ) {\nreturn x / 5;\n }\nvar f = compose( c, b, a );\nvar z = f( 6 )\n","composeAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x/5 );\n}\n };\nvar f = composeAsync( c, b, a );\nfunction done( error, result ) {\nif ( error ) {\n throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","configdir":"var dir = configdir()\ndir = configdir( 'appname/config' )\n","conj":"var z = new Complex128( 5.0, 3.0 );\nz.toString()\nvar v = conj( z );\nv.toString()\n","conjf":"var z = new Complex64( 5.0, 3.0 );\nz.toString()\nvar v = conjf( z );\nv.toString()\n","constantcase":"var out = constantcase( 'Hello World!' )\nout = constantcase( 'I am a tiny little teapot' )\n","constantFunction":"var fcn = constantFunction( 3.14 );\nvar v = fcn()\nv = fcn()\nv = fcn()\n","constantStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream( 'beep', opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","constantStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = constantStream.factory( opts );\n","constantStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream.objectMode( 3.14, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","constructorName":"var v = constructorName( 'a' )\nv = constructorName( {} )\nv = constructorName( true )\n","contains":"var bool = contains( 'Hello World', 'World' )\nbool = contains( 'Hello World', 'world' )\nbool = contains( [ 1, 2, 3, 4 ], 2 )\nbool = contains( [ NaN, 2, 3, 4 ], NaN )\nbool = contains( 'Hello World', 'Hello', 6 )\nbool = contains( [ true, NaN, false ], true, 1 )\n","convertArray":"var arr = [ 1.0, 2.0, 3.0, 4.0 ];\nvar out = convertArray( arr, 'float32' )\n","convertArraySame":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = new Float32Array( 0 );\nvar out = convertArraySame( x, y )\n","convertPath":"var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\nout = convertPath( '/c/foo/bar/beep.c', 'mixed' )\nout = convertPath( '/c/foo/bar/beep.c', 'posix' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n","copy":"var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nvar out = copy( value )\nvar bool = ( value[ 0 ].c === out[ 0 ].c )\nvalue = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nout = copy( value, 1 );\nbool = ( value[ 0 ] === out[ 0 ] )\nbool = ( value[ 0 ].c === out[ 0 ].c )\n","copyBuffer":"var b1 = array2buffer( [ 1, 2, 3, 4 ] );\nvar b2 = copyBuffer( b1 )\n","countBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = countBy( collection, indicator )\n","countByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n","countByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = countByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 500 ];\nf( arr, done )\n","currentYear":"var y = currentYear()\n","curry":"function add( x, y ) { return x + y; };\nvar f = curry( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curry( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curry( obj.greet, obj );\nvar str = f( 'Hello' )( 'there' )\n","curryRight":"function add( x, y ) { return x + y; };\nvar f = curryRight( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curryRight( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curryRight( obj.greet, obj );\nvar str = f( 'there' )( 'Hello' )\n","cwd":"var dir = cwd()\n","DALE_CHALL_NEW":"var list = DALE_CHALL_NEW()\n","datasets":"var out = datasets( 'MONTH_NAMES_EN' )\nvar opts = { 'data': 'cities' };\nout = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n","DataType":"var dt = new DataType( 'float64' );\ndt.byteLength\n","DataType.name":"DataType.name\n","DataType.prototype.alignment":"var dt = new DataType( 'float64' );\ndt.alignment\n","DataType.prototype.byteLength":"var dt = new DataType( 'float64' );\ndt.byteLength\n","DataType.prototype.byteOrder":"var dt = new DataType( 'float64' );\ndt.byteOrder\n","DataType.prototype.char":"var dt = new DataType( 'float64' );\ndt.char\n","DataType.prototype.description":"var dt = new DataType( 'float64' );\ndt.description\n","DataType.prototype.enum":"var dt = new DataType( 'float64' );\ndt.enum\n","DataType.prototype.value":"var dt = new DataType( 'float64' );\ndt.value\n","DataType.prototype.toJSON":"var dt = new DataType( 'float64' );\ndt.toJSON()\n","DataType.prototype.toString":"var dt = new DataType( 'float64' );\ndt.toString()\n","DataType.prototype.valueOf":"var dt = new DataType( 'float64' );\ndt.valueOf()\n","DataView":"var buf = new ArrayBuffer( 5 )\nvar dv = new DataView( buf )\n","DataView.prototype.buffer":"var buf1 = new ArrayBuffer( 5 );\nvar dv = new DataView( buf1 );\nvar buf2 = dv.buffer\nvar b = ( buf1 === buf2 )\n","DataView.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf );\ndv.byteLength\n","DataView.prototype.byteOffset":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf, 2 );\ndv.byteLength\ndv.byteOffset\n","datespace":"var stop = '2014-12-02T07:00:54.973Z';\nvar start = new Date( stop ) - 60000;\nvar arr = datespace( start, stop, 6 )\nvar opts = { 'round': 'ceil' };\narr = datespace( 1417503655000, 1417503655001, 3, opts )\n","dayOfQuarter":"var day = dayOfQuarter()\nday = dayOfQuarter( new Date() )\nday = dayOfQuarter( 12, 31, 2017 )\nday = dayOfQuarter( 'dec', 31, 2017 )\nday = dayOfQuarter( 'december', 31, 2017 )\n","dayOfYear":"var day = dayOfYear()\nday = dayOfYear( new Date() )\nday = dayOfYear( 12, 31, 2016 )\nday = dayOfYear( 'dec', 31, 2016 )\nday = dayOfYear( 'december', 31, 2016 )\n","daysInMonth":"var num = daysInMonth()\nnum = daysInMonth( 2 )\nnum = daysInMonth( 2, 2016 )\nnum = daysInMonth( 2, 2017 )\nnum = daysInMonth( 'feb', 2016 )\nnum = daysInMonth( 'february', 2016 )\n","daysInYear":"var num = daysInYear()\nnum = daysInYear( 2016 )\nnum = daysInYear( 2017 )\n","ddot":"var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = ddot( x, y )\n","debugSinkStream":"var s = debugSinkStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugSinkStream.factory( opts );\n","debugSinkStream.objectMode":"var s = debugSinkStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","debugStream":"var s = debugStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugStream.factory( opts );\n","debugStream.objectMode":"var s = debugStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","decorateAfter":"function f( v ) { return -v; };\nvar fcn = decorateAfter( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","decorateAfter.factory":"function f( v ) { return -v; };\nvar fcn = decorateAfter.factory( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","deepEqual":"var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\nbool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\nbool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n","deepGet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a.b.c' )\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n","deepGet.factory":"var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = dget( obj )\n","deepHasOwnProp":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepHasOwnProp( obj, 'a.b.c' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasOwnProp.factory":"var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = has( obj )\n","deepHasProp":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar obj = { 'a': new Foo() };\nvar bool = deepHasProp( obj, 'a.b.c' )\nbool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasProp.factory":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': new Foo() };\nvar bool = has( obj )\n","deepPluck":"var arr = [\n { 'a': { 'b': { 'c': 1 } } },\n { 'a': { 'b': { 'c': 2 } } }\n ];\nvar out = deepPluck( arr, 'a.b.c' )\narr = [\n { 'a': [ 0, 1, 2 ] },\n { 'a': [ 3, 4, 5 ] }\n ];\nout = deepPluck( arr, [ 'a', 1 ] )\n","deepSet":"var obj1 = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepSet( obj1, 'a.b.c', 'beep' )\nvar obj2 = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj2, 'a/b/c', 'beep', { 'sep': '/' } );\nobj2\nvar obj3 = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj3, 'a.e.c', 'boop', { 'create': true } );\nobj3\n","deepSet.factory":"var dset = deepSet.factory( 'a/b/c', {\n 'create': true,\n 'sep': '/'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = dset( obj, 'beep' )\nobj\n","defineMemoizedProperty":"var obj = {};\nfunction foo() {\n return 'bar';\n };\ndefineMemoizedProperty( obj, 'foo', {\n 'configurable': false,\n 'enumerable': true,\n 'writable': false,\n 'value': foo\n });\nobj.foo\n","defineProperties":"var obj = {};\ndefineProperties( obj, {\n 'foo': {\n 'value': 'bar',\n 'writable': false,\n 'configurable': false,\n 'enumerable': true\n },\n 'baz': {\n 'value': 13\n }\n });\nobj.foo\nobj.baz\n","defineProperty":"var obj = {};\ndefineProperty( obj, 'foo', {\n 'value': 'bar',\n 'enumerable': true,\n 'writable': false\n });\nobj.foo = 'boop';\nobj\n","dirname":"var dir = dirname( './foo/bar/index.js' )\n","dotcase":"var out = dotcase( 'Hello World!' )\nout = dotcase( 'beep boop' )\n","DoublyLinkedList":"var list = DoublyLinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","doUntil":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoUntil( beep, predicate )\n","doUntilAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ndoUntilAsync( fcn, predicate, done )\n","doUntilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoUntilEach( arr, logger, predicate )\n","doUntilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoUntilEachRight( arr, logger, predicate )\n","doWhile":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoWhile( beep, predicate )\n","doWhileAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ndoWhileAsync( fcn, predicate, done )\n","doWhileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoWhileEach( arr, logger, predicate )\n","doWhileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoWhileEachRight( arr, logger, predicate )\n","dswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ndswap( x, y );\nx.data\ny.data\n","E":"E\n","EMOJI":"var data = EMOJI()\n","EMOJI_CODE_PICTO":"var out = EMOJI_CODE_PICTO()\n","EMOJI_PICTO_CODE":"var out = EMOJI_PICTO_CODE()\n","emptyStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = emptyStream();\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","emptyStream.factory":"var opts = { 'objectMode': true };\nvar createStream = emptyStream.factory( opts );\n","emptyStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = emptyStream.objectMode();\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","endsWith":"var bool = endsWith( 'beep', 'ep' )\nbool = endsWith( 'Beep', 'op' )\nbool = endsWith( 'Beep', 'ee', 3 )\nbool = endsWith( 'Beep', 'ee', -1 )\nbool = endsWith( 'beep', '' )\n","enumerableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = enumerableProperties( obj )\n","enumerablePropertiesIn":"var props = enumerablePropertiesIn( [] )\n","enumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbols( obj )\n","enumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbolsIn( obj )\n","ENV":"var user = ENV.USER\n","EPS":"EPS\n","error2json":"var err = new Error( 'beep' );\nvar json = error2json( err )\n","EULERGAMMA":"EULERGAMMA\n","every":"var arr = [ 1, 1, 1, 1, 1 ];\nvar bool = every( arr )\n","everyBy":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyBy( arr, positive )\n","everyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n","everyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","everyByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyByRight( arr, positive )\n","everyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n","everyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","everyInBy":"function positive( v ) { return ( v > 0 ); };\nvar o = {a: 1, b: 2, c: 3};\nvar bool = everyInBy( o, positive )\n","everyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nvar bool = everyOwnBy( obj, positive )\n","evil":"var v = evil( '5*4*3*2*1' )\n","EXEC_PATH":"EXEC_PATH\n","exists":"function done( error, bool ) { console.log( bool ); };\nexists( './beep/boop', done );\n","exists.sync":"var bool = exists.sync( './beep/boop' )\n","expandAcronyms":"var str = 'LOL, this is fun. I am ROFL.';\nvar out = expandAcronyms( str )\nstr = 'brb, I need to check my mail. thx!';\nout = expandAcronyms( str )\n","expandContractions":"var str = 'I won\\'t be able to get y\\'all out of this one.';\nvar out = expandContractions( str )\nstr = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\nout = expandContractions( str )\n","extname":"var ext = extname( 'index.js' )\n","FancyArray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","FancyArray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","FancyArray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","FancyArray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","FancyArray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","FancyArray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","FancyArray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","FancyArray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","FancyArray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","FancyArray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","FancyArray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","FancyArray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","FancyArray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","FancyArray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","FancyArray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","FancyArray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","fastmath.abs":"var v = fastmath.abs( -1.0 )\nv = fastmath.abs( 2.0 )\nv = fastmath.abs( 0.0 )\nv = fastmath.abs( -0.0 )\nv = fastmath.abs( NaN )\n","fastmath.acosh":"var v = fastmath.acosh( 1.0 )\nv = fastmath.acosh( 2.0 )\nv = fastmath.acosh( NaN )\nv = fastmath.acosh( 1.0e308 )\n","fastmath.ampbm":"var h = fastmath.ampbm( 5.0, 12.0 )\n","fastmath.ampbm.factory":"var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n","fastmath.asinh":"var v = fastmath.asinh( 0.0 )\nv = fastmath.asinh( 2.0 )\nv = fastmath.asinh( -2.0 )\nv = fastmath.asinh( NaN )\nv = fastmath.asinh( 1.0e200 )\nv = fastmath.asinh( 1.0e-50 )\n","fastmath.atanh":"var v = fastmath.atanh( 0.0 )\nv = fastmath.atanh( 0.9 )\nv = fastmath.atanh( 1.0 )\nv = fastmath.atanh( -1.0 )\nv = fastmath.atanh( NaN )\nv = fastmath.atanh( 1.0e-17 )\n","fastmath.hypot":"var h = fastmath.hypot( -5.0, 12.0 )\nh = fastmath.hypot( 1.0e154, 1.0e154 )\nh = fastmath.hypot( 1e-200, 1.0e-200 )\n","fastmath.log2Uint32":"var v = fastmath.log2Uint32( 4 >>> 0 )\nv = fastmath.log2Uint32( 8 >>> 0 )\nv = fastmath.log2Uint32( 9 >>> 0 )\n","fastmath.max":"var v = fastmath.max( 3.14, 4.2 )\nv = fastmath.max( 3.14, NaN )\nv = fastmath.max( NaN, 3.14 )\nv = fastmath.max( -0.0, +0.0 )\nv = fastmath.max( +0.0, -0.0 )\n","fastmath.min":"var v = fastmath.min( 3.14, 4.2 )\nv = fastmath.min( 3.14, NaN )\nv = fastmath.min( NaN, 3.14 )\nv = fastmath.min( -0.0, +0.0 )\nv = fastmath.min( +0.0, -0.0 )\n","fastmath.powint":"var v = fastmath.powint( 2.0, 3 )\nv = fastmath.powint( 3.14, 0 )\nv = fastmath.powint( 2.0, -2 )\nv = fastmath.powint( 0.0, 0 )\nv = fastmath.powint( -3.14, 1 )\nv = fastmath.powint( NaN, 0 )\n","fastmath.sqrtUint32":"var v = fastmath.sqrtUint32( 9 >>> 0 )\nv = fastmath.sqrtUint32( 2 >>> 0 )\nv = fastmath.sqrtUint32( 3 >>> 0 )\nv = fastmath.sqrtUint32( 0 >>> 0 )\n","FEMALE_FIRST_NAMES_EN":"var list = FEMALE_FIRST_NAMES_EN()\n","FIFO":"var q = FIFO();\nq.push( 'foo' ).push( 'bar' );\nq.length\nq.pop()\nq.length\nq.pop()\nq.length\n","filledarray":"var arr = filledarray()\narr = filledarray( 'float32' )\nvar arr = filledarray( 1.0, 5 )\narr = filledarray( 1, 5, 'int32' )\nvar arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n","filledarrayBy":"var arr = filledarrayBy()\narr = filledarrayBy( 'float32' )\nfunction clbk() { return 1.0; };\nvar arr = filledarrayBy( 5, clbk )\narr = filledarrayBy( 5, 'int32', clbk )\nvar arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n","filterArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v !== 2 ); };\nvar bar = filterArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","find":"var data = [ 30, 20, 50, 60, 10 ];\nfunction condition( val ) { return val > 20; };\nvar vals = find( data, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nvar opts = { 'k': 2, 'returns': 'values' };\nvals = find( data, opts, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nopts = { 'k': -2, 'returns': '*' };\nvals = find( data, opts, condition )\n","firstChar":"var out = firstChar( 'beep' )\nout = firstChar( 'Boop', 1 )\nout = firstChar( 'foo bar', 5 )\n","FIVETHIRTYEIGHT_FFQ":"var data = FIVETHIRTYEIGHT_FFQ()\n","flattenArray":"var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nvar out = flattenArray( arr )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2 } )\nvar bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2, 'copy': true } )\nbool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n","flattenArray.factory":"var flatten = flattenArray.factory( [ 2, 2 ], {\n 'copy': false\n });\nvar out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\nout = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n","flattenObject":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flattenObject( obj )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'depth': 1 } )\nvar bool = ( obj.a.b === out[ 'a.b' ] )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'delimiter': '-|-' } )\nobj = { 'a': { 'b': [ 1, 2, 3 ] } };\nout = flattenObject( obj, { 'flattenArrays': true } )\n","flattenObject.factory":"var flatten = flattenObject.factory({\n 'depth': 1,\n 'copy': true,\n 'delimiter': '|'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flatten( obj )\n","flignerTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = flignerTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = flignerTest( arr, { 'groups': groups } )\n","FLOAT_WORD_ORDER":"FLOAT_WORD_ORDER\n","FLOAT16_CBRT_EPS":"FLOAT16_CBRT_EPS\n","FLOAT16_EPS":"FLOAT16_EPS\n","FLOAT16_EXPONENT_BIAS":"FLOAT16_EXPONENT_BIAS\n","FLOAT16_MAX":"FLOAT16_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"FLOAT16_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"FLOAT16_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"FLOAT16_NINF\n","FLOAT16_NUM_BYTES":"FLOAT16_NUM_BYTES\n","FLOAT16_PINF":"FLOAT16_PINF\n","FLOAT16_PRECISION":"FLOAT16_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"FLOAT16_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"FLOAT16_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"FLOAT16_SQRT_EPS\n","FLOAT32_ABS_MASK":"FLOAT32_ABS_MASK\nbase.toBinaryStringUint32( FLOAT32_ABS_MASK )\n","FLOAT32_CBRT_EPS":"FLOAT32_CBRT_EPS\n","FLOAT32_E":"FLOAT32_E\n","FLOAT32_EPS":"FLOAT32_EPS\n","FLOAT32_EXPONENT_BIAS":"FLOAT32_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"FLOAT32_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n","FLOAT32_FOURTH_PI":"FLOAT32_FOURTH_PI\n","FLOAT32_HALF_LN_TWO":"FLOAT32_HALF_LN_TWO\n","FLOAT32_HALF_PI":"FLOAT32_HALF_PI\n","FLOAT32_LN_HALF":"FLOAT32_LN_HALF\n","FLOAT32_LN_PI":"FLOAT32_LN_PI\n","FLOAT32_LN_TEN":"FLOAT32_LN_TEN\n","FLOAT32_LN_TWO":"FLOAT32_LN_TWO\n","FLOAT32_MAX":"FLOAT32_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"FLOAT32_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"FLOAT32_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"FLOAT32_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"FLOAT32_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"FLOAT32_MAX_SAFE_NTH_FACTORIAL\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"FLOAT32_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"FLOAT32_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"FLOAT32_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"FLOAT32_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"FLOAT32_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"FLOAT32_NAN\n","FLOAT32_NINF":"FLOAT32_NINF\n","FLOAT32_NUM_BYTES":"FLOAT32_NUM_BYTES\n","FLOAT32_PHI":"FLOAT32_PHI\n","FLOAT32_PI":"FLOAT32_PI\n","FLOAT32_PINF":"FLOAT32_PINF\n","FLOAT32_PRECISION":"FLOAT32_PRECISION\n","FLOAT32_SIGN_MASK":"FLOAT32_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n","FLOAT32_SIGNIFICAND_MASK":"FLOAT32_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n","FLOAT32_SMALLEST_NORMAL":"FLOAT32_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"FLOAT32_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"FLOAT32_SQRT_EPS\n","FLOAT32_SQRT_HALF":"FLOAT32_SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"FLOAT32_SQRT_HALF_PI\n","FLOAT32_SQRT_PHI":"FLOAT32_SQRT_PHI\n","FLOAT32_SQRT_PI":"FLOAT32_SQRT_PI\n","FLOAT32_SQRT_THREE":"FLOAT32_SQRT_THREE\n","FLOAT32_SQRT_TWO":"FLOAT32_SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"FLOAT32_SQRT_TWO_PI\n","FLOAT32_TWO_PI":"FLOAT32_TWO_PI\n","Float32Array":"var arr = new Float32Array()\nvar arr = new Float32Array( 5 )\nvar arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float32Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Float32Array( buf, 0, 4 )\n","Float32Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float32Array.of":"var arr = Float32Array.of( 2.0, -2.0 )\n","Float32Array.BYTES_PER_ELEMENT":"Float32Array.BYTES_PER_ELEMENT\n","Float32Array.name":"Float32Array.name\n","Float32Array.prototype.buffer":"var arr = new Float32Array( 5 );\narr.buffer\n","Float32Array.prototype.byteLength":"var arr = new Float32Array( 5 );\narr.byteLength\n","Float32Array.prototype.byteOffset":"var arr = new Float32Array( 5 );\narr.byteOffset\n","Float32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float32Array.prototype.length":"var arr = new Float32Array( 5 );\narr.length\n","Float32Array.prototype.copyWithin":"var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float32Array.prototype.entries":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.every":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float32Array.prototype.fill":"var arr = new Float32Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float32Array.prototype.filter":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float32Array.prototype.find":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float32Array.prototype.findIndex":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float32Array.prototype.forEach":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float32Array.prototype.includes":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float32Array.prototype.indexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float32Array.prototype.join":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float32Array.prototype.keys":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.lastIndexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float32Array.prototype.map":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float32Array.prototype.reduce":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float32Array.prototype.reduceRight":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float32Array.prototype.reverse":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float32Array.prototype.set":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float32Array.prototype.slice":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float32Array.prototype.some":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float32Array.prototype.sort":"var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float32Array.prototype.subarray":"var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float32Array.prototype.toLocaleString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float32Array.prototype.toString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float32Array.prototype.values":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","FLOAT64_EXPONENT_BIAS":"FLOAT64_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"FLOAT64_HIGH_WORD_ABS_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"FLOAT64_HIGH_WORD_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n","FLOAT64_HIGH_WORD_SIGN_MASK":"FLOAT64_HIGH_WORD_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n","FLOAT64_MAX":"FLOAT64_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"FLOAT64_MAX_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"FLOAT64_MAX_SAFE_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MIN_BASE2_EXPONENT":"FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE10_EXPONENT":"FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"FLOAT64_MIN_LN\n","FLOAT64_MIN_SAFE_INTEGER":"FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"FLOAT64_NUM_BYTES\n","FLOAT64_PRECISION":"FLOAT64_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"FLOAT64_SMALLEST_NORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"FLOAT64_SMALLEST_SUBNORMAL\n","Float64Array":"var arr = new Float64Array()\nvar arr = new Float64Array( 5 )\nvar arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float64Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float64Array( arr1 )\nvar buf = new ArrayBuffer( 32 );\nvar arr = new Float64Array( buf, 0, 4 )\n","Float64Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float64Array.of":"var arr = Float64Array.of( 2.0, -2.0 )\n","Float64Array.BYTES_PER_ELEMENT":"Float64Array.BYTES_PER_ELEMENT\n","Float64Array.name":"Float64Array.name\n","Float64Array.prototype.buffer":"var arr = new Float64Array( 5 );\narr.buffer\n","Float64Array.prototype.byteLength":"var arr = new Float64Array( 5 );\narr.byteLength\n","Float64Array.prototype.byteOffset":"var arr = new Float64Array( 5 );\narr.byteOffset\n","Float64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float64Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float64Array.prototype.length":"var arr = new Float64Array( 5 );\narr.length\n","Float64Array.prototype.copyWithin":"var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float64Array.prototype.entries":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.every":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float64Array.prototype.fill":"var arr = new Float64Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float64Array.prototype.filter":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float64Array.prototype.find":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float64Array.prototype.findIndex":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float64Array.prototype.forEach":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float64Array.prototype.includes":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float64Array.prototype.indexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float64Array.prototype.join":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float64Array.prototype.keys":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.lastIndexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float64Array.prototype.map":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float64Array.prototype.reduce":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float64Array.prototype.reduceRight":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float64Array.prototype.reverse":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float64Array.prototype.set":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float64Array.prototype.slice":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float64Array.prototype.some":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float64Array.prototype.sort":"var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float64Array.prototype.subarray":"var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float64Array.prototype.toLocaleString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float64Array.prototype.toString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float64Array.prototype.values":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","forEach":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEach( arr, logger )\n","forEachAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n","forEachAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nforEachChar( 'hello world!', fcn );\nn\n","forEachRight":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEachRight( arr, logger )\n","forEachRightAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n","forEachRightAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachRightAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","forIn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nfunction Foo() { return this; };\nFoo.prototype.beep = 'boop';\nvar obj = new Foo();\nforIn( obj, logger )\n","format":"var out = format( 'Hello, %s!', 'World' )\nout = format( '%s %s', 'Hello', 'World' )\nout = format( 'Pi: %.2f', PI )\n","forOwn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nforOwn( obj, logger )\n","FOURTH_PI":"FOURTH_PI\n","FOURTH_ROOT_EPS":"FOURTH_ROOT_EPS\n","FRB_SF_WAGE_RIGIDITY":"var data = FRB_SF_WAGE_RIGIDITY()\n","fromCodePoint":"var out = fromCodePoint( 9731 )\nout = fromCodePoint( [ 9731 ] )\nout = fromCodePoint( 97, 98, 99 )\nout = fromCodePoint( [ 97, 98, 99 ] )\n","Function":"var f = new Function( 'x', 'y', 'return x + y' );\nf( 1, 2 )\n","Function.prototype.apply":"var f = new Function( 'x', 'y', 'return x + y' );\nf.apply( null, [ 1, 2 ] )\n","Function.prototype.call":"var f = new Function( 'x', 'y', 'return x + y' );\nf.call( null, 1, 2 )\n","Function.prototype.bind":"var f = new Function( 'x', 'y', 'return x + y' );\nvar g = f.bind( null, 1 );\ng( 2 )\n","Function.prototype.toString":"var f = new Function( 'x', 'y', 'return x + y' );\nf.toString()\n","Function.prototype.length":"var f = new Function( 'x', 'y', 'return x + y' );\nf.length\n","Function.prototype.name":"var f = new Function( 'x', 'y', 'return x + y' );\nf.name\nvar f = new Function( 'x', 'y', 'return x + y' );\nf.name = 'add';\nf.name\n","Function.prototype.prototype":"var f = new Function( 'x', 'y', 'return x + y' );\nf.prototype\n","function2string":"function2string( base.erf )\n","functionName":"var v = functionName( String )\nv = functionName( function foo(){} )\nv = functionName( function(){} )\n","functionSequence":"function a( x ) { return 2 * x; };\nfunction b( x ) { return x + 3; };\nfunction c( x ) { return x / 5; };\nvar f = functionSequence( a, b, c );\nvar z = f( 6 )\n","functionSequenceAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x/5 );\n}\n };\nvar f = functionSequenceAsync( a, b, c );\nfunction done( error, result ) {\nif ( error ) {\n throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","GAMMA_LANCZOS_G":"GAMMA_LANCZOS_G\n","gdot":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngdot( x, y )\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngdot( x, y )\n","getegid":"var gid = getegid()\n","geteuid":"var uid = geteuid()\n","getgid":"var gid = getgid()\n","getGlobal":"var g = getGlobal()\n","getPrototypeOf":"var proto = getPrototypeOf( {} )\n","getuid":"var uid = getuid()\n","GLAISHER":"GLAISHER\n","graphemeClusters2iterator":"var it = graphemeClusters2iterator( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","graphemeClusters2iteratorRight":"var it = graphemeClusters2iteratorRight( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","group":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar groups = [ 'b', 'b', 'f', 'b' ];\nvar out = group( collection, groups )\ngroups = [ 1, 1, 2, 1 ];\nout = group( collection, groups )\ngroups = [ 'b', 'b', 'f', 'b' ];\nvar opts = { 'returns': 'indices' };\nout = group( collection, opts, groups )\nopts = { 'returns': '*' };\nout = group( collection, opts, groups )\n","groupBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = groupBy( collection, indicator )\nvar opts = { 'returns': 'indices' };\nout = groupBy( collection, opts, indicator )\nopts = { 'returns': '*' };\nout = groupBy( collection, opts, indicator )\n","groupByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, indicator, done )\nvar opts = { 'returns': 'indices' };\ngroupByAsync( arr, opts, indicator, done )\nopts = { 'returns': '*' };\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n","groupByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = groupByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","groupIn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nfunction Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nvar out = groupIn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupIn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupIn( obj, opts, indicator )\n","groupOwn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = groupOwn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupOwn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupOwn( obj, opts, indicator )\n","gswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngswap( x, y );\nx.data\ny.data\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngswap( x, y );\nx\ny\n","HALF_LN2":"HALF_LN2\n","HALF_PI":"HALF_PI\n","HARRISON_BOSTON_HOUSE_PRICES":"var data = HARRISON_BOSTON_HOUSE_PRICES()\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n","hasArrayBufferSupport":"var bool = hasArrayBufferSupport()\n","hasArrowFunctionSupport":"var bool = hasArrowFunctionSupport()\n","hasAsyncAwaitSupport":"var bool = hasAsyncAwaitSupport()\n","hasAsyncIteratorSymbolSupport":"var bool = hasAsyncIteratorSymbolSupport()\n","hasAtobSupport":"var bool = hasAtobSupport()\n","hasBigInt64ArraySupport":"var bool = hasBigInt64ArraySupport()\n","hasBigIntSupport":"var bool = hasBigIntSupport()\n","hasBigUint64ArraySupport":"var bool = hasBigUint64ArraySupport()\n","hasBtoaSupport":"var bool = hasBtoaSupport()\n","hasClassSupport":"var bool = hasClassSupport()\n","hasDataViewSupport":"var bool = hasDataViewSupport()\n","hasDefinePropertiesSupport":"var bool = hasDefinePropertiesSupport()\n","hasDefinePropertySupport":"var bool = hasDefinePropertySupport()\n","hasFloat32ArraySupport":"var bool = hasFloat32ArraySupport()\n","hasFloat64ArraySupport":"var bool = hasFloat64ArraySupport()\n","hasFunctionNameSupport":"var bool = hasFunctionNameSupport()\n","hasGeneratorSupport":"var bool = hasGeneratorSupport()\n","hasGlobalThisSupport":"var bool = hasGlobalThisSupport()\n","hasInt8ArraySupport":"var bool = hasInt8ArraySupport()\n","hasInt16ArraySupport":"var bool = hasInt16ArraySupport()\n","hasInt32ArraySupport":"var bool = hasInt32ArraySupport()\n","hasIteratorSymbolSupport":"var bool = hasIteratorSymbolSupport()\n","hasMapSupport":"var bool = hasMapSupport()\n","hasNodeBufferSupport":"var bool = hasNodeBufferSupport()\n","hasOwnProp":"var beep = { 'boop': true };\nvar bool = hasOwnProp( beep, 'boop' )\nbool = hasOwnProp( beep, 'bop' )\n","hasProp":"var beep = { 'boop': true };\nvar bool = hasProp( beep, 'boop' )\nbool = hasProp( beep, 'toString' )\nbool = hasProp( beep, 'bop' )\n","hasProxySupport":"var bool = hasProxySupport()\n","hasSetSupport":"var bool = hasSetSupport()\n","hasSharedArrayBufferSupport":"var bool = hasSharedArrayBufferSupport()\n","hasSymbolSupport":"var bool = hasSymbolSupport()\n","hasToStringTagSupport":"var bool = hasToStringTagSupport()\n","hasUint8ArraySupport":"var bool = hasUint8ArraySupport()\n","hasUint8ClampedArraySupport":"var bool = hasUint8ClampedArraySupport()\n","hasUint16ArraySupport":"var bool = hasUint16ArraySupport()\n","hasUint32ArraySupport":"var bool = hasUint32ArraySupport()\n","hasUTF16SurrogatePairAt":"var out = hasUTF16SurrogatePairAt( '🌷', 0 )\nout = hasUTF16SurrogatePairAt( '🌷', 1 )\n","hasWeakMapSupport":"var bool = hasWeakMapSupport()\n","hasWeakSetSupport":"var bool = hasWeakSetSupport()\n","hasWebAssemblySupport":"var bool = hasWebAssemblySupport()\n","headercase":"var out = headercase( 'Hello World!' )\nout = headercase( 'beep boop' )\n","HERNDON_VENUS_SEMIDIAMETERS":"var d = HERNDON_VENUS_SEMIDIAMETERS()\n","homedir":"var home = homedir()\n","HOURS_IN_DAY":"var days = 3.14;\nvar hrs = days * HOURS_IN_DAY\n","HOURS_IN_WEEK":"var wks = 3.14;\nvar hrs = wks * HOURS_IN_WEEK\n","hoursInMonth":"var num = hoursInMonth()\nnum = hoursInMonth( 2 )\nnum = hoursInMonth( 2, 2016 )\nnum = hoursInMonth( 2, 2017 )\nnum = hoursInMonth( 'feb', 2016 )\nnum = hoursInMonth( 'february', 2016 )\n","hoursInYear":"var num = hoursInYear()\nnum = hoursInYear( 2016 )\nnum = hoursInYear( 2017 )\n","httpServerFactory":"var boot = httpServerFactory()\nfunction onRequest( request, response ) {\nconsole.log( request.url );\nresponse.end( 'OK' );\n };\nboot = httpServerFactory( onRequest )\nvar opts = { 'port': 7331 };\nboot = httpServerFactory( opts )\n","identity":"var v = identity( 3.14 )\n","ifelse":"var z = ifelse( true, 1.0, -1.0 )\nz = ifelse( false, 1.0, -1.0 )\n","ifelseAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, true );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nifelseAsync( predicate, 'beep', 'boop', done )\n","ifthen":"function x() { return 1.0; };\nfunction y() { return -1.0; };\nvar z = ifthen( true, x, y )\nz = ifthen( false, x, y )\n","ifthenAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, false );\n }\n };\nfunction x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'beep' );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nifthenAsync( predicate, x, y, done )\n","imag":"var z = new Complex128( 5.0, 3.0 );\nvar im = imag( z )\n","imagf":"var z = new Complex64( 5.0, 3.0 );\nvar im = imagf( z )\n","IMG_ACANTHUS_MOLLIS":"var img = IMG_ACANTHUS_MOLLIS()\n","IMG_AIRPLANE_FROM_ABOVE":"var img = IMG_AIRPLANE_FROM_ABOVE()\n","IMG_ALLIUM_OREOPHILUM":"var img = IMG_ALLIUM_OREOPHILUM()\n","IMG_BLACK_CANYON":"var img = IMG_BLACK_CANYON()\n","IMG_DUST_BOWL_HOME":"var img = IMG_DUST_BOWL_HOME()\n","IMG_FRENCH_ALPINE_LANDSCAPE":"var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n","IMG_LOCOMOTION_HOUSE_CAT":"var img = IMG_LOCOMOTION_HOUSE_CAT()\n","IMG_LOCOMOTION_NUDE_MALE":"var img = IMG_LOCOMOTION_NUDE_MALE()\n","IMG_MARCH_PASTORAL":"var img = IMG_MARCH_PASTORAL()\n","IMG_NAGASAKI_BOATS":"var img = IMG_NAGASAKI_BOATS()\n","incrapcorr":"var accumulator = incrapcorr();\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator()\n","incrBinaryClassification":"var opts = {};\nopts.intercept = true;\nopts.lambda = 1.0e-5;\nvar acc = incrBinaryClassification( 3, opts );\nvar buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\nvar x = array( buf );\nvar coefs = acc( x, 1 )\nbuf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\nx = array( buf );\nvar yhat = acc.predict( x )\n","incrcount":"var accumulator = incrcount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrcovariance":"var accumulator = incrcovariance();\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator()\n","incrcovmat":"var accumulator = incrcovmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrcv":"var accumulator = incrcv();\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator()\n","increwmean":"var accumulator = increwmean( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","increwstdev":"var accumulator = increwstdev( 0.5 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","increwvariance":"var accumulator = increwvariance( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrgmean":"var accumulator = incrgmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrgrubbs":"var acc = incrgrubbs();\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrhmean":"var accumulator = incrhmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrkmeans":"var accumulator = incrkmeans( 5, 2 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v );\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v );\n","incrkurtosis":"var accumulator = incrkurtosis();\nvar v = accumulator( 2.0 )\nv = accumulator( 2.0 )\nv = accumulator( -4.0 )\nv = accumulator( -4.0 )\n","incrmaape":"var accumulator = incrmaape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmae":"var accumulator = incrmae();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmapcorr":"var accumulator = incrmapcorr( 3 );\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator( 3.0, -1.0 )\nar = accumulator( 5.0, -9.5 )\nar = accumulator()\n","incrmape":"var accumulator = incrmape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmax":"var accumulator = incrmax();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmaxabs":"var accumulator = incrmaxabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmcovariance":"var accumulator = incrmcovariance( 3 );\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator( 3.0, -1.0 )\nv = accumulator( 5.0, -9.5 )\nv = accumulator()\n","incrmcv":"var accumulator = incrmcv( 3 );\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator( 3.0 )\ncv = accumulator( 7.0 )\ncv = accumulator()\n","incrmda":"var accumulator = incrmda();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 4.0 )\nm = accumulator()\n","incrme":"var accumulator = incrme();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmean":"var accumulator = incrmean();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs":"var accumulator = incrmeanabs();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs2":"var accumulator = incrmeanabs2();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanstdev":"var accumulator = incrmeanstdev();\nvar ms = accumulator()\nms = accumulator( 2.0 )\nms = accumulator( -5.0 )\nms = accumulator( 3.0 )\nms = accumulator( 5.0 )\nms = accumulator()\n","incrmeanvar":"var accumulator = incrmeanvar();\nvar mv = accumulator()\nmv = accumulator( 2.0 )\nmv = accumulator( -5.0 )\nmv = accumulator( 3.0 )\nmv = accumulator( 5.0 )\nmv = accumulator()\n","incrmgmean":"var accumulator = incrmgmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmgrubbs":"var acc = incrmgrubbs( 20 );\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrmhmean":"var accumulator = incrmhmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmidrange":"var accumulator = incrmidrange();\nvar v = accumulator()\nv = accumulator( 3.14 )\nv = accumulator( -5.0 )\nv = accumulator( 10.1 )\nv = accumulator()\n","incrmin":"var accumulator = incrmin();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminabs":"var accumulator = incrminabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminmax":"var accumulator = incrminmax();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrminmaxabs":"var accumulator = incrminmaxabs();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmaape":"var accumulator = incrmmaape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmae":"var accumulator = incrmmae( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmape":"var accumulator = incrmmape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmax":"var accumulator = incrmmax( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmaxabs":"var accumulator = incrmmaxabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmda":"var accumulator = incrmmda( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 4.0, 5.0 )\nm = accumulator()\n","incrmme":"var accumulator = incrmme( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmean":"var accumulator = incrmmean( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs":"var accumulator = incrmmeanabs( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs2":"var accumulator = incrmmeanabs2( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmeanstdev":"var accumulator = incrmmeanstdev( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmeanvar":"var accumulator = incrmmeanvar( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmidrange":"var accumulator = incrmmidrange( 3 );\nvar mr = accumulator()\nmr = accumulator( 2.0 )\nmr = accumulator( -5.0 )\nmr = accumulator( 3.0 )\nmr = accumulator( 5.0 )\nmr = accumulator()\n","incrmmin":"var accumulator = incrmmin( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminabs":"var accumulator = incrmminabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminmax":"var accumulator = incrmminmax( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmminmaxabs":"var accumulator = incrmminmaxabs( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmpe":"var accumulator = incrmmpe( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmse":"var accumulator = incrmmse( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmpcorr":"var accumulator = incrmpcorr( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator( 3.0, -1.0 )\nr = accumulator( 5.0, -9.5 )\nr = accumulator()\n","incrmpcorr2":"var accumulator = incrmpcorr2( 3 );\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator( 3.0, -1.0 )\nr2 = accumulator( 5.0, -9.5 )\nr2 = accumulator()\n","incrmpcorrdist":"var accumulator = incrmpcorrdist( 3 );\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator( 3.0, -1.0 )\nd = accumulator( 5.0, -9.5 )\nd = accumulator()\n","incrmpe":"var accumulator = incrmpe();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmprod":"var accumulator = incrmprod( 3 );\nvar p = accumulator()\np = accumulator( 2.0 )\np = accumulator( -5.0 )\np = accumulator( 3.0 )\np = accumulator( 5.0 )\np = accumulator()\n","incrmrange":"var accumulator = incrmrange( 3 );\nvar r = accumulator()\nr = accumulator( 2.0 )\nr = accumulator( -5.0 )\nr = accumulator( 3.0 )\nr = accumulator( 5.0 )\nr = accumulator()\n","incrmrmse":"var accumulator = incrmrmse( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmrss":"var accumulator = incrmrss( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmse":"var accumulator = incrmse();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmstdev":"var accumulator = incrmstdev( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsum":"var accumulator = incrmsum( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsumabs":"var accumulator = incrmsumabs( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumabs2":"var accumulator = incrmsumabs2( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsummary":"var accumulator = incrmsummary( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumprod":"var accumulator = incrmsumprod( 3 );\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator( 3.0, -2.0 )\ns = accumulator( 5.0, 3.0 )\ns = accumulator()\n","incrmvariance":"var accumulator = incrmvariance( 3 );\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator( 3.0 )\ns2 = accumulator( 5.0 )\ns2 = accumulator()\n","incrmvmr":"var accumulator = incrmvmr( 3 );\nvar F = accumulator()\nF = accumulator( 2.0 )\nF = accumulator( 1.0 )\nF = accumulator( 3.0 )\nF = accumulator( 7.0 )\nF = accumulator()\n","incrnancount":"var accumulator = incrnancount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrnansum":"var accumulator = incrnansum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs":"var accumulator = incrnansumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs2":"var accumulator = incrnansumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrpcorr":"var accumulator = incrpcorr();\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator()\n","incrpcorr2":"var accumulator = incrpcorr2();\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator()\n","incrpcorrdist":"var accumulator = incrpcorrdist();\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator()\n","incrpcorrdistmat":"var accumulator = incrpcorrdistmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrpcorrmat":"var accumulator = incrpcorrmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrprod":"var accumulator = incrprod();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrrange":"var accumulator = incrrange();\nvar v = accumulator()\nv = accumulator( -2.0 )\nv = accumulator( 1.0 )\nv = accumulator( 3.0 )\nv = accumulator()\n","incrrmse":"var accumulator = incrrmse();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrrss":"var accumulator = incrrss();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrskewness":"var accumulator = incrskewness();\nvar v = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( -10.0 )\nv = accumulator()\n","incrspace":"var arr = incrspace( 0, 11, 2 )\n","incrstdev":"var accumulator = incrstdev();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsum":"var accumulator = incrsum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs":"var accumulator = incrsumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs2":"var accumulator = incrsumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsummary":"var accumulator = incrsummary();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumprod":"var accumulator = incrsumprod();\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator()\n","incrvariance":"var accumulator = incrvariance();\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator()\n","incrvmr":"var accumulator = incrvmr();\nvar D = accumulator()\nD = accumulator( 2.0 )\nD = accumulator( 1.0 )\nD = accumulator()\n","incrwmean":"var accumulator = incrwmean();\nvar mu = accumulator()\nmu = accumulator( 2.0, 1.0 )\nmu = accumulator( 2.0, 0.5 )\nmu = accumulator( 3.0, 1.5 )\nmu = accumulator()\n","ind2sub":"var d = [ 3, 3, 3 ];\nvar s = ind2sub( d, 17 )\n","ind2sub.assign":"var d = [ 3, 3, 3 ];\nvar out = [ 0, 0, 0 ];\nvar s = ind2sub.assign( d, 17, out )\nvar bool = ( s === out )\n","indexOf":"var arr = [ 4, 3, 2, 1 ];\nvar idx = indexOf( arr, 3 )\narr = [ 4, 3, 2, 1 ];\nidx = indexOf( arr, 5 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, 3 )\narr = [ 1, 2, 3, 4, 2, 5 ];\nidx = indexOf( arr, 2, 10 )\narr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\nidx = indexOf( arr, 2, -4 )\nidx = indexOf( arr, 2, -1 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, -10 )\nvar str = 'bebop';\nidx = indexOf( str, 'o' )\n","inherit":"function Foo() { return this; };\nFoo.prototype.beep = function beep() { return 'boop'; };\nfunction Bar() { Foo.call( this ); return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar v = bar.beep()\n","inheritedEnumerableProperties":"var props = inheritedEnumerableProperties( {} )\n","inheritedEnumerablePropertySymbols":"var symbols = inheritedEnumerablePropertySymbols( [] )\n","inheritedKeys":"var keys = inheritedKeys( {} )\n","inheritedNonEnumerableProperties":"var props = inheritedNonEnumerableProperties( {} )\n","inheritedNonEnumerablePropertyNames":"var keys = inheritedNonEnumerablePropertyNames( {} )\n","inheritedNonEnumerablePropertySymbols":"var symbols = inheritedNonEnumerablePropertySymbols( [] )\n","inheritedProperties":"var symbols = inheritedProperties( [] )\n","inheritedPropertyDescriptor":"var desc = inheritedPropertyDescriptor( {}, 'toString' )\n","inheritedPropertyDescriptors":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = inheritedPropertyDescriptors( obj )\n","inheritedPropertyNames":"var keys = inheritedPropertyNames( [] )\n","inheritedPropertySymbols":"var symbols = inheritedPropertySymbols( [] )\n","inheritedWritableProperties":"var props = inheritedWritableProperties( {} )\n","inheritedWritablePropertyNames":"var keys = inheritedWritablePropertyNames( {} )\n","inheritedWritablePropertySymbols":"var symbols = inheritedWritablePropertySymbols( [] )\n","inmap":"function foo( v, i ) { return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmap( arr, foo )\nvar bool = ( out === arr )\n","inmapAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n","inmapAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","inmapRight":"function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmapRight( arr, foo )\nvar bool = ( out === arr )\n","inmapRightAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n","inmapRightAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapRightAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","inspectSinkStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectSinkStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","inspectStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","instanceOf":"var bool = instanceOf( [], Array )\nbool = instanceOf( {}, Object )\nbool = instanceOf( null, Object )\n","INT8_MAX":"INT8_MAX\n","INT8_MIN":"INT8_MIN\n","INT8_NUM_BYTES":"INT8_NUM_BYTES\n","Int8Array":"var arr = new Int8Array()\nvar arr = new Int8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Int8Array( buf, 0, 4 )\n","Int8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int8Array.from( [ 1, 2 ], mapFcn )\n","Int8Array.of":"var arr = Int8Array.of( 1, 2 )\n","Int8Array.BYTES_PER_ELEMENT":"Int8Array.BYTES_PER_ELEMENT\n","Int8Array.name":"Int8Array.name\n","Int8Array.prototype.buffer":"var arr = new Int8Array( 5 );\narr.buffer\n","Int8Array.prototype.byteLength":"var arr = new Int8Array( 5 );\narr.byteLength\n","Int8Array.prototype.byteOffset":"var arr = new Int8Array( 5 );\narr.byteOffset\n","Int8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int8Array.prototype.length":"var arr = new Int8Array( 5 );\narr.length\n","Int8Array.prototype.copyWithin":"var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int8Array.prototype.entries":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.every":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int8Array.prototype.fill":"var arr = new Int8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int8Array.prototype.filter":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int8Array.prototype.find":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int8Array.prototype.findIndex":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int8Array.prototype.forEach":"var arr = new Int8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int8Array.prototype.includes":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int8Array.prototype.indexOf":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int8Array.prototype.join":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int8Array.prototype.keys":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.lastIndexOf":"var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int8Array.prototype.map":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int8Array.prototype.reduce":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int8Array.prototype.reduceRight":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int8Array.prototype.reverse":"var arr = new Int8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int8Array.prototype.set":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int8Array.prototype.slice":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int8Array.prototype.some":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int8Array.prototype.sort":"var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int8Array.prototype.subarray":"var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int8Array.prototype.toLocaleString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int8Array.prototype.toString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toString()\n","Int8Array.prototype.values":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT16_MAX":"INT16_MAX\n","INT16_MIN":"INT16_MIN\n","INT16_NUM_BYTES":"INT16_NUM_BYTES\n","Int16Array":"var arr = new Int16Array()\nvar arr = new Int16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Int16Array( buf, 0, 4 )\n","Int16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int16Array.from( [ 1, 2 ], mapFcn )\n","Int16Array.of":"var arr = Int16Array.of( 1, 2 )\n","Int16Array.BYTES_PER_ELEMENT":"Int16Array.BYTES_PER_ELEMENT\n","Int16Array.name":"Int16Array.name\n","Int16Array.prototype.buffer":"var arr = new Int16Array( 5 );\narr.buffer\n","Int16Array.prototype.byteLength":"var arr = new Int16Array( 5 );\narr.byteLength\n","Int16Array.prototype.byteOffset":"var arr = new Int16Array( 5 );\narr.byteOffset\n","Int16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int16Array.prototype.length":"var arr = new Int16Array( 5 );\narr.length\n","Int16Array.prototype.copyWithin":"var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int16Array.prototype.entries":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.every":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int16Array.prototype.fill":"var arr = new Int16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int16Array.prototype.filter":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int16Array.prototype.find":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int16Array.prototype.findIndex":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int16Array.prototype.forEach":"var arr = new Int16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int16Array.prototype.includes":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int16Array.prototype.indexOf":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int16Array.prototype.join":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int16Array.prototype.keys":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.lastIndexOf":"var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int16Array.prototype.map":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int16Array.prototype.reduce":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int16Array.prototype.reduceRight":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int16Array.prototype.reverse":"var arr = new Int16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int16Array.prototype.set":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int16Array.prototype.slice":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int16Array.prototype.some":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int16Array.prototype.sort":"var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int16Array.prototype.subarray":"var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int16Array.prototype.toLocaleString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int16Array.prototype.toString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toString()\n","Int16Array.prototype.values":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT32_MAX":"INT32_MAX\n","INT32_MIN":"INT32_MIN\n","INT32_NUM_BYTES":"INT32_NUM_BYTES\n","Int32Array":"var arr = new Int32Array()\nvar arr = new Int32Array( 5 )\nvar arr1 = new Int16Array( [ 5, 5, 5 ] );\nvar arr2 = new Int32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Int32Array( buf, 0, 4 )\n","Int32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int32Array.from( [ 1, 2 ], mapFcn )\n","Int32Array.of":"var arr = Int32Array.of( 1, 2 )\n","Int32Array.BYTES_PER_ELEMENT":"Int32Array.BYTES_PER_ELEMENT\n","Int32Array.name":"Int32Array.name\n","Int32Array.prototype.buffer":"var arr = new Int32Array( 5 );\narr.buffer\n","Int32Array.prototype.byteLength":"var arr = new Int32Array( 5 );\narr.byteLength\n","Int32Array.prototype.byteOffset":"var arr = new Int32Array( 5 );\narr.byteOffset\n","Int32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int32Array.prototype.length":"var arr = new Int32Array( 5 );\narr.length\n","Int32Array.prototype.copyWithin":"var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int32Array.prototype.entries":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.every":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int32Array.prototype.fill":"var arr = new Int32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int32Array.prototype.filter":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int32Array.prototype.find":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int32Array.prototype.findIndex":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int32Array.prototype.forEach":"var arr = new Int32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int32Array.prototype.includes":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int32Array.prototype.indexOf":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int32Array.prototype.join":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int32Array.prototype.keys":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.lastIndexOf":"var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int32Array.prototype.map":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int32Array.prototype.reduce":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int32Array.prototype.reduceRight":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int32Array.prototype.reverse":"var arr = new Int32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int32Array.prototype.set":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int32Array.prototype.slice":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int32Array.prototype.some":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int32Array.prototype.sort":"var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int32Array.prototype.subarray":"var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int32Array.prototype.toLocaleString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int32Array.prototype.toString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toString()\n","Int32Array.prototype.values":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","IS_BIG_ENDIAN":"IS_BIG_ENDIAN\n","IS_BROWSER":"IS_BROWSER\n","IS_DARWIN":"IS_DARWIN\n","IS_DOCKER":"IS_DOCKER\n","IS_ELECTRON":"IS_ELECTRON\n","IS_ELECTRON_MAIN":"IS_ELECTRON_MAIN\n","IS_ELECTRON_RENDERER":"IS_ELECTRON_RENDERER\n","IS_LITTLE_ENDIAN":"IS_LITTLE_ENDIAN\n","IS_MOBILE":"IS_MOBILE\n","IS_NODE":"IS_NODE\n","IS_TOUCH_DEVICE":"IS_TOUCH_DEVICE\n","IS_WEB_WORKER":"IS_WEB_WORKER\n","IS_WINDOWS":"IS_WINDOWS\n","isAbsoluteHttpURI":"var bool = isAbsoluteHttpURI( 'http://example.com/' )\nbool = isAbsoluteHttpURI( 'example.com' )\nbool = isAbsoluteHttpURI( 'foo@bar.com' )\n","isAbsolutePath":"var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath( '/foo/bar/baz' )\n","isAbsolutePath.posix":"var bool = isAbsolutePath.posix( '/foo/bar/baz' )\nbool = isAbsolutePath.posix( 'foo/bar/baz' )\n","isAbsolutePath.win32":"var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n","isAbsoluteURI":"var bool = isAbsoluteURI( 'http://example.com/' )\nbool = isAbsoluteURI( 'example.com' )\nbool = isAbsoluteURI( 'foo@bar.com' )\n","isAccessorArray":"var bool = isAccessorArray( new Complex64Array( 10 ) )\nbool = isAccessorArray( [] )\nbool = isAccessorArray( { 'length': 0 } )\nbool = isAccessorArray( {} )\n","isAccessorProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorProperty( obj, 'boop' )\nbool = isAccessorProperty( obj, 'beep' )\n","isAccessorPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorPropertyIn( obj, 'boop' )\nbool = isAccessorPropertyIn( obj, 'beep' )\n","isAlphagram":"var out = isAlphagram( 'beep' )\nout = isAlphagram( 'zba' )\nout = isAlphagram( '' )\n","isAlphaNumeric":"var bool = isAlphaNumeric( 'abc0123456789' )\nbool = isAlphaNumeric( 'abcdef' )\nbool = isAlphaNumeric( '0xff' )\nbool = isAlphaNumeric( '' )\n","isAnagram":"var str1 = 'I am a weakish speller';\nvar str2 = 'William Shakespeare';\nvar bool = isAnagram( str1, str2 )\nbool = isAnagram( 'bat', 'tabba' )\n","isArguments":"function foo() { return arguments; };\nvar bool = isArguments( foo() )\nbool = isArguments( [] )\n","isArray":"var bool = isArray( [] )\nbool = isArray( {} )\n","isArrayArray":"var bool = isArrayArray( [ [], [] ] )\nbool = isArrayArray( [ {}, {} ] )\nbool = isArrayArray( [] )\n","isArrayBuffer":"var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\nbool = isArrayBuffer( [] )\n","isArrayBufferView":"var bool = isArrayBufferView( new Int8Array() )\nbool = isArrayBufferView( [] )\n","isArrayLength":"var bool = isArrayLength( 5 )\nbool = isArrayLength( 2.0e200 )\nbool = isArrayLength( -3.14 )\nbool = isArrayLength( null )\n","isArrayLike":"var bool = isArrayLike( [] )\nbool = isArrayLike( { 'length': 10 } )\nbool = isArrayLike( 'beep' )\nbool = isArrayLike( null )\n","isArrayLikeObject":"var bool = isArrayLikeObject( [] )\nbool = isArrayLikeObject( { 'length': 10 } )\nbool = isArrayLikeObject( 'beep' )\n","isArrowFunction":"function beep() {};\nvar bool = isArrowFunction( beep )\nbool = isArrowFunction( {} )\n","isASCII":"var str = 'beep boop';\nvar bool = isASCII( str )\nbool = isASCII( fromCodePoint( 130 ) )\n","isBetween":"var bool = isBetween( 3.14, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.0, 4.0 )\nbool = isBetween( 4.0, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.14, 4.0 )\nbool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\nbool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n","isBetweenArray":"var arr = [ 3.0, 3.14, 4.0 ];\nvar bool = isBetweenArray( arr, 3.0, 4.0 )\nbool = isBetweenArray( arr, 3.14, 4.0 )\nbool = isBetweenArray( arr, 3.0, 3.14 )\nbool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\nbool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n","isBigInt":"var bool = isBigInt( BigInt( '1' ) )\nbool = isBigInt( Object( BigInt( '1' ) ) )\nbool = isBigInt( {} )\nbool = isBigInt( null )\nbool = isBigInt( true )\n","isBigInt64Array":"var bool = isBigInt64Array( new BigInt64Array( 10 ) )\nbool = isBigInt64Array( [] )\n","isBigUint64Array":"var bool = isBigUint64Array( new BigUint64Array( 10 ) )\nbool = isBigUint64Array( [] )\n","isBinaryString":"var bool = isBinaryString( '1000101' )\nbool = isBinaryString( 'beep' )\nbool = isBinaryString( '' )\n","isBlankString":"var bool = isBlankString( ' ' )\nbool = isBlankString( 'beep' )\nbool = isBlankString( null )\n","isBoolean":"var bool = isBoolean( false )\nbool = isBoolean( new Boolean( false ) )\n","isBoolean.isPrimitive":"var bool = isBoolean.isPrimitive( true )\nbool = isBoolean.isPrimitive( false )\nbool = isBoolean.isPrimitive( new Boolean( true ) )\n","isBoolean.isObject":"var bool = isBoolean.isObject( true )\nbool = isBoolean.isObject( new Boolean( false ) )\n","isBooleanArray":"var bool = isBooleanArray( [ true, false, true ] )\nbool = isBooleanArray( [ true, 'abc', false ] )\n","isBooleanArray.primitives":"var bool = isBooleanArray.primitives( [ true, false ] )\nbool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n","isBooleanArray.objects":"var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\nbool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n","isBoxedPrimitive":"var bool = isBoxedPrimitive( new Boolean( false ) )\nbool = isBoxedPrimitive( true )\n","isBuffer":"var bool = isBuffer( new Buffer( 'beep' ) )\nbool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\nbool = isBuffer( {} )\nbool = isBuffer( [] )\n","isCamelcase":"var bool = isCamelcase( 'helloWorld' )\nbool = isCamelcase( 'hello world' )\n","isCapitalized":"var bool = isCapitalized( 'Hello' )\nbool = isCapitalized( 'world' )\n","isCentrosymmetricMatrix":"var buf = [ 2, 1, 1, 2 ];\nvar M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isCentrosymmetricMatrix( M )\nbool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isCentrosymmetricMatrix( 3.14 )\nbool = isCentrosymmetricMatrix( {} )\n","isCircular":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircular( obj )\nbool = isCircular( {} )\nbool = isCircular( null )\n","isCircularArray":"var arr = [ 1, 2, 3 ];\narr.push( arr );\nvar bool = isCircularArray( arr )\nbool = isCircularArray( [] )\nbool = isCircularArray( null )\n","isCircularPlainObject":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircularPlainObject( obj )\nbool = isCircularPlainObject( {} )\nbool = isCircularPlainObject( null )\n","isClass":"var bool = isClass( class Person {} )\nbool = isClass( function Person() {} )\nbool = isClass( {} )\nbool = isClass( null )\nbool = isClass( true )\n","isCollection":"var bool = isCollection( [] )\nbool = isCollection( { 'length': 0 } )\nbool = isCollection( {} )\n","isComplex":"var bool = isComplex( new Complex64( 2.0, 2.0 ) )\nbool = isComplex( new Complex128( 3.0, 1.0 ) )\nbool = isComplex( 3.14 )\nbool = isComplex( {} )\n","isComplex64":"var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\nbool = isComplex64( new Complex128( 3.0, 1.0 ) )\nbool = isComplex64( 3.14 )\nbool = isComplex64( {} )\n","isComplex64Array":"var bool = isComplex64Array( new Complex64Array( 10 ) )\nbool = isComplex64Array( [] )\n","isComplex64MatrixLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64MatrixLike( M )\nbool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64MatrixLike( 3.14 )\nbool = isComplex64MatrixLike( {} )\n","isComplex64ndarrayLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64ndarrayLike( M )\nbool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64ndarrayLike( 3.14 )\nbool = isComplex64ndarrayLike( {} )\n","isComplex64VectorLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64VectorLike( M )\nbool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64VectorLike( 3.14 )\nbool = isComplex64VectorLike( {} )\n","isComplex128":"var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\nbool = isComplex128( new Complex64( 2.0, 2.0 ) )\nbool = isComplex128( 3.14 )\nbool = isComplex128( {} )\n","isComplex128Array":"var bool = isComplex128Array( new Complex128Array( 10 ) )\nbool = isComplex128Array( [] )\n","isComplex128MatrixLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128MatrixLike( M )\nbool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128MatrixLike( 3.14 )\nbool = isComplex128MatrixLike( {} )\n","isComplex128ndarrayLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128ndarrayLike( M )\nbool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128ndarrayLike( 3.14 )\nbool = isComplex128ndarrayLike( {} )\n","isComplex128VectorLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128VectorLike( M )\nbool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128VectorLike( 3.14 )\nbool = isComplex128VectorLike( {} )\n","isComplexLike":"var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\nbool = isComplexLike( new Complex128( 3.0, 1.0 ) )\nbool = isComplexLike( 3.14 )\nbool = isComplexLike( {} )\n","isComplexTypedArray":"var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n","isComplexTypedArrayLike":"var bool = isComplexTypedArrayLike( new Complex128Array() )\nbool = isComplexTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4,\n'get': function get() {},\n'set': function set() {}\n })\n","isComposite":"var bool = isComposite( 4.0 )\nbool = isComposite( new Number( 4.0 ) )\nbool = isComposite( 3.14 )\nbool = isComposite( -4.0 )\nbool = isComposite( null )\n","isComposite.isPrimitive":"var bool = isComposite.isPrimitive( 4.0 )\nbool = isComposite.isPrimitive( new Number( 4.0 ) )\n","isComposite.isObject":"var bool = isComposite.isObject( 4.0 )\nbool = isComposite.isObject( new Number( 4.0 ) )\n","isConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurableProperty( obj, 'boop' )\nbool = isConfigurableProperty( obj, 'beep' )\n","isConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurablePropertyIn( obj, 'boop' )\nbool = isConfigurablePropertyIn( obj, 'beep' )\n","isConstantcase":"var bool = isConstantcase( 'BEEP_BOOP' )\nbool = isConstantcase( 'BEEP and BOOP' )\n","isCubeNumber":"var bool = isCubeNumber( 8.0 )\nbool = isCubeNumber( new Number( 8.0 ) )\nbool = isCubeNumber( 3.14 )\nbool = isCubeNumber( -5.0 )\nbool = isCubeNumber( null )\n","isCubeNumber.isPrimitive":"var bool = isCubeNumber.isPrimitive( 8.0 )\nbool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n","isCubeNumber.isObject":"var bool = isCubeNumber.isObject( 8.0 )\nbool = isCubeNumber.isObject( new Number( 8.0 ) )\n","isCurrentYear":"var bool = isCurrentYear( new Date() )\nbool = isCurrentYear( currentYear() )\nbool = isCurrentYear( 2021 )\nbool = isCurrentYear( null )\n","isDataProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataProperty( obj, 'boop' )\nbool = isDataProperty( obj, 'beep' )\n","isDataPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataPropertyIn( obj, 'boop' )\nbool = isDataPropertyIn( obj, 'beep' )\n","isDataView":"var buf = new ArrayBuffer( 10 );\nvar bool = isDataView( new DataView( buf ) )\nbool = isDataView( [] )\n","isDateObject":"var bool = isDateObject( new Date() )\nbool = isDateObject( '2017-01-01' )\n","isDateObjectArray":"var bool = isDateObjectArray( [ new Date(), new Date() ] )\nbool = isDateObjectArray( [ {}, {} ] )\nbool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\nbool = isDateObjectArray( [] )\n","isDigitString":"var bool = isDigitString( '0123456789' )\nbool = isDigitString( 'abcdef' )\nbool = isDigitString( '0xff' )\nbool = isDigitString( '' )\n","isDomainName":"var bool = isDomainName( 'example.com' )\nbool = isDomainName( 'foo@bar.com' )\n","isDurationString":"var bool = isDurationString( '1d' )\nbool = isDurationString( '1h' )\nbool = isDurationString( 'beep' )\n","isEmailAddress":"var bool = isEmailAddress( 'beep@boop.com' )\nbool = isEmailAddress( 'beep' )\nbool = isEmailAddress( null )\n","isEmptyArray":"var bool = isEmptyArray( [] )\nbool = isEmptyArray( [ 1, 2, 3 ] )\nbool = isEmptyArray( {} )\n","isEmptyArrayLikeObject":"var bool = isEmptyArrayLikeObject( [] )\nbool = isEmptyArrayLikeObject( { 'length': 0 } )\nbool = isEmptyArrayLikeObject( '' )\n","isEmptyCollection":"var bool = isEmptyCollection( [] )\nbool = isEmptyCollection( { 'length': 0 } )\nbool = isEmptyCollection( [ 1, 2, 3 ] )\nbool = isEmptyCollection( {} )\n","isEmptyObject":"var bool = isEmptyObject( {} )\nbool = isEmptyObject( { 'beep': 'boop' } )\nbool = isEmptyObject( [] )\n","isEmptyString":"var bool = isEmptyString( '' )\nbool = isEmptyString( new String( '' ) )\nbool = isEmptyString( 'beep' )\nbool = isEmptyString( [] )\n","isEmptyString.isPrimitive":"var bool = isEmptyString.isPrimitive( '' )\nbool = isEmptyString.isPrimitive( new String( '' ) )\n","isEmptyString.isObject":"var bool = isEmptyString.isObject( new String( '' ) )\nbool = isEmptyString.isObject( '' )\n","isEnumerableProperty":"var beep = { 'boop': true };\nvar bool = isEnumerableProperty( beep, 'boop' )\nbool = isEnumerableProperty( beep, 'hasOwnProperty' )\n","isEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isEnumerablePropertyIn( obj, 'boop' )\nbool = isEnumerablePropertyIn( obj, 'beep' )\n","isEqualArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isEqualArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isEqualArray( x, y )\n","isEqualDateObject":"var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar bool = isEqualDateObject( d1, d2 )\nd1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nd2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\nbool = isEqualDateObject( d1, d2 )\n","isError":"var bool = isError( new Error( 'beep' ) )\nbool = isError( {} )\n","isEvalError":"var bool = isEvalError( new EvalError( 'beep' ) )\nbool = isEvalError( {} )\n","isEven":"var bool = isEven( 4.0 )\nbool = isEven( new Number( 4.0 ) )\nbool = isEven( 3.0 )\nbool = isEven( -3.14 )\nbool = isEven( null )\n","isEven.isPrimitive":"var bool = isEven.isPrimitive( -4.0 )\nbool = isEven.isPrimitive( new Number( -4.0 ) )\n","isEven.isObject":"var bool = isEven.isObject( 4.0 )\nbool = isEven.isObject( new Number( 4.0 ) )\n","isFalsy":"var bool = isFalsy( false )\nbool = isFalsy( '' )\nbool = isFalsy( 0 )\nbool = isFalsy( null )\nbool = isFalsy( void 0 )\nbool = isFalsy( NaN )\nbool = isFalsy( {} )\nbool = isFalsy( [] )\n","isFalsyArray":"var bool = isFalsyArray( [ null, '' ] )\nbool = isFalsyArray( [ {}, [] ] )\nbool = isFalsyArray( [] )\n","isFinite":"var bool = isFinite( 5.0 )\nbool = isFinite( new Number( 5.0 ) )\nbool = isFinite( 1.0/0.0 )\nbool = isFinite( null )\n","isFinite.isPrimitive":"var bool = isFinite.isPrimitive( -3.0 )\nbool = isFinite.isPrimitive( new Number( -3.0 ) )\n","isFinite.isObject":"var bool = isFinite.isObject( 3.0 )\nbool = isFinite.isObject( new Number( 3.0 ) )\n","isFiniteArray":"var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n","isFiniteArray.primitives":"var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\nbool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isFiniteArray.objects":"var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n","isFloat32Array":"var bool = isFloat32Array( new Float32Array( 10 ) )\nbool = isFloat32Array( [] )\n","isFloat32MatrixLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32MatrixLike( M )\nbool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32MatrixLike( 3.14 )\nbool = isFloat32MatrixLike( {} )\n","isFloat32ndarrayLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32ndarrayLike( M )\nbool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32ndarrayLike( 3.14 )\nbool = isFloat32ndarrayLike( {} )\n","isFloat32VectorLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32VectorLike( M )\nbool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32VectorLike( 3.14 )\nbool = isFloat32VectorLike( {} )\n","isFloat64Array":"var bool = isFloat64Array( new Float64Array( 10 ) )\nbool = isFloat64Array( [] )\n","isFloat64MatrixLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64MatrixLike( M )\nbool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64MatrixLike( 3.14 )\nbool = isFloat64MatrixLike( {} )\n","isFloat64ndarrayLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64ndarrayLike( M )\nbool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64ndarrayLike( 3.14 )\nbool = isFloat64ndarrayLike( {} )\n","isFloat64VectorLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64VectorLike( M )\nbool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64VectorLike( 3.14 )\nbool = isFloat64VectorLike( {} )\n","isFunction":"function beep() {};\nvar bool = isFunction( beep )\nbool = isFunction( {} )\n","isFunctionArray":"function beep() {};\nfunction boop() {};\nvar bool = isFunctionArray( [ beep, boop ] )\nbool = isFunctionArray( [ {}, beep ] )\nbool = isFunctionArray( [] )\n","isGeneratorObject":"function* generateID() {\n var idx = 0;\n while ( idx < idx+1 ) {\n yield idx;\n idx += 1;\n }\n };\nvar bool = isGeneratorObject( generateID() )\nbool = isGeneratorObject( generateID )\nbool = isGeneratorObject( {} )\nbool = isGeneratorObject( null )\n","isGeneratorObjectLike":"var obj = {\n 'next': function noop() {},\n 'return': function noop() {},\n 'throw': function noop() {}\n };\nvar bool = isGeneratorObjectLike( obj )\nbool = isGeneratorObjectLike( {} )\nbool = isGeneratorObjectLike( null )\n","isgzipBuffer":"var buf = new Uint8Array( 20 );\nbuf[ 0 ] = 31; // 0x1f => magic number\nbuf[ 1 ] = 139; // 0x8b\nbuf[ 2 ] = 8; // 0x08 => compression method\nvar bool = isgzipBuffer( buf )\nbool = isgzipBuffer( [] )\n","isHexString":"var bool = isHexString( '0123456789abcdefABCDEF' )\nbool = isHexString( '0xffffff' )\nbool = isHexString( 'x' )\nbool = isHexString( '' )\n","isInfinite":"var bool = isInfinite( 1.0/0.0 )\nbool = isInfinite( new Number( -1.0/0.0 ) )\nbool = isInfinite( 5.0 )\nbool = isInfinite( '1.0/0.0' )\n","isInfinite.isPrimitive":"var bool = isInfinite.isPrimitive( -1.0/0.0 )\nbool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isInfinite.isObject":"var bool = isInfinite.isObject( 1.0/0.0 )\nbool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n","isInheritedProperty":"var beep = { 'boop': true };\nvar bool = isInheritedProperty( beep, 'boop' )\nbool = isInheritedProperty( beep, 'toString' )\nbool = isInheritedProperty( beep, 'bop' )\n","isInt8Array":"var bool = isInt8Array( new Int8Array( 10 ) )\nbool = isInt8Array( [] )\n","isInt16Array":"var bool = isInt16Array( new Int16Array( 10 ) )\nbool = isInt16Array( [] )\n","isInt32Array":"var bool = isInt32Array( new Int32Array( 10 ) )\nbool = isInt32Array( [] )\n","isInteger":"var bool = isInteger( 5.0 )\nbool = isInteger( new Number( 5.0 ) )\nbool = isInteger( -3.14 )\nbool = isInteger( null )\n","isInteger.isPrimitive":"var bool = isInteger.isPrimitive( -3.0 )\nbool = isInteger.isPrimitive( new Number( -3.0 ) )\n","isInteger.isObject":"var bool = isInteger.isObject( 3.0 )\nbool = isInteger.isObject( new Number( 3.0 ) )\n","isIntegerArray":"var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isIntegerArray( [ -3.0, '3.0' ] )\n","isIntegerArray.primitives":"var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\nbool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isIntegerArray.objects":"var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n","isIterableLike":"var bool = isIterableLike( [ 1, 2, 3 ] )\nbool = isIterableLike( {} )\nbool = isIterableLike( null )\n","isIteratorLike":"var obj = {\n 'next': function noop() {}\n };\nvar bool = isIteratorLike( obj )\nbool = isIteratorLike( {} )\nbool = isIteratorLike( null )\n","isJSON":"var bool = isJSON( '{\"a\":5}' )\nbool = isJSON( '{a\":5}' )\n","isKebabcase":"var bool = isKebabcase( 'beep-boop' )\nbool = isKebabcase( 'BEEP_BOOP' )\n","isLeapYear":"var bool = isLeapYear( new Date() )\nbool = isLeapYear( 1996 )\nbool = isLeapYear( 2001 )\n","isLocalhost":"var bool = isLocalhost( 'localhost' )\nbool = isLocalhost( '127.0.0.1' )\nbool = isLocalhost( 'stdlib.io' )\n","isLowercase":"var bool = isLowercase( 'hello' )\nbool = isLowercase( 'World' )\n","isMatrixLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isMatrixLike( M )\nbool = isMatrixLike( [ 1, 2, 3, 4 ] )\nbool = isMatrixLike( 3.14 )\nbool = isMatrixLike( {} )\n","isMethod":"var beep = { 'boop': function beep() { return 'beep'; } };\nvar bool = isMethod( beep, 'boop' )\nbool = isMethod( beep, 'toString' )\n","isMethodIn":"var beep = { 'boop': true };\nvar bool = isMethodIn( beep, 'toString' )\nbool = isMethodIn( beep, 'boop' )\nbool = isMethodIn( beep, 'bop' )\n","isMultiSlice":"var bool = isMultiSlice( new MultiSlice() )\nbool = isMultiSlice( 3.14 )\nbool = isMultiSlice( {} )\n","isNamedTypedTupleLike":"var Point = namedtypedtuple( [ 'x', 'y' ] );\nvar p = new Point();\nvar bool = isNamedTypedTupleLike( p )\nbool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\nbool = isNamedTypedTupleLike( 3.14 )\nbool = isNamedTypedTupleLike( {} )\n","isnan":"var bool = isnan( NaN )\nbool = isnan( new Number( NaN ) )\nbool = isnan( 3.14 )\nbool = isnan( null )\n","isnan.isPrimitive":"var bool = isnan.isPrimitive( NaN )\nbool = isnan.isPrimitive( 3.14 )\nbool = isnan.isPrimitive( new Number( NaN ) )\n","isnan.isObject":"var bool = isnan.isObject( NaN )\nbool = isnan.isObject( new Number( NaN ) )\n","isNaNArray":"var bool = isNaNArray( [ NaN, NaN, NaN ] )\nbool = isNaNArray( [ NaN, 2 ] )\n","isNaNArray.primitives":"var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\nbool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n","isNaNArray.objects":"var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n","isNativeFunction":"var bool = isNativeFunction( Date )\nfunction beep() {};\nbool = isNativeFunction( beep )\nbool = isNativeFunction( {} )\n","isndarrayLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLike( M )\nbool = isndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isndarrayLike( 3.14 )\nbool = isndarrayLike( {} )\n","isndarrayLikeWithDataType":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLikeWithDataType( M, 'generic' )\nbool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\nbool = isndarrayLikeWithDataType( 3.14, 'generic' )\nbool = isndarrayLikeWithDataType( {}, 'generic' )\n","isNegativeFinite":"var bool = isNegativeFinite( -5.0 )\nbool = isNegativeFinite( new Number( -5.0 ) )\nbool = isNegativeFinite( -3.14 )\nbool = isNegativeFinite( 5.0 )\nbool = isNegativeFinite( null )\nbool = isNegativeFinite( -1.0/0.0 )\nbool = isNegativeFinite( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isPrimitive":"var bool = isNegativeFinite.isPrimitive( -3.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\nvar bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isObject":"var bool = isNegativeFinite.isObject( -3.0 )\nbool = isNegativeFinite.isObject( new Number( -3.0 ) )\nbool = isNegativeFinite.isObject( -1.0/0.0 )\nbool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n","isNegativeInteger":"var bool = isNegativeInteger( -5.0 )\nbool = isNegativeInteger( new Number( -5.0 ) )\nbool = isNegativeInteger( 5.0 )\nbool = isNegativeInteger( -3.14 )\nbool = isNegativeInteger( null )\n","isNegativeInteger.isPrimitive":"var bool = isNegativeInteger.isPrimitive( -3.0 )\nbool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n","isNegativeInteger.isObject":"var bool = isNegativeInteger.isObject( -3.0 )\nbool = isNegativeInteger.isObject( new Number( -3.0 ) )\n","isNegativeIntegerArray":"var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n","isNegativeIntegerArray.primitives":"var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeIntegerArray.objects":"var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumber":"var bool = isNegativeNumber( -5.0 )\nbool = isNegativeNumber( new Number( -5.0 ) )\nbool = isNegativeNumber( -3.14 )\nbool = isNegativeNumber( 5.0 )\nbool = isNegativeNumber( null )\n","isNegativeNumber.isPrimitive":"var bool = isNegativeNumber.isPrimitive( -3.0 )\nbool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n","isNegativeNumber.isObject":"var bool = isNegativeNumber.isObject( -3.0 )\nbool = isNegativeNumber.isObject( new Number( -3.0 ) )\n","isNegativeNumberArray":"var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n","isNegativeNumberArray.primitives":"var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumberArray.objects":"var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeZero":"var bool = isNegativeZero( -0.0 )\nbool = isNegativeZero( new Number( -0.0 ) )\nbool = isNegativeZero( -3.14 )\nbool = isNegativeZero( 0.0 )\nbool = isNegativeZero( null )\n","isNegativeZero.isPrimitive":"var bool = isNegativeZero.isPrimitive( -0.0 )\nbool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n","isNegativeZero.isObject":"var bool = isNegativeZero.isObject( -0.0 )\nbool = isNegativeZero.isObject( new Number( -0.0 ) )\n","isNodeBuiltin":"var bool = isNodeBuiltin( 'cluster' )\nbool = isNodeBuiltin( 'crypto' )\nbool = isNodeBuiltin( 'fs-extra' )\nbool = isNodeBuiltin( '' )\n","isNodeDuplexStreamLike":"var Stream = require( 'stream' ).Duplex;\ns = new Stream();\nvar bool = isNodeDuplexStreamLike( s )\nbool = isNodeDuplexStreamLike( {} )\n","isNodeReadableStreamLike":"var Stream = require( 'stream' ).Readable;\ns = new Stream();\nvar bool = isNodeReadableStreamLike( s )\nbool = isNodeReadableStreamLike( {} )\n","isNodeREPL":"var bool = isNodeREPL()\n","isNodeStreamLike":"var Stream = require( 'stream' ).Stream;\ns = new Stream();\nvar bool = isNodeStreamLike( s )\nbool = isNodeStreamLike( {} )\n","isNodeTransformStreamLike":"var Stream = require( 'stream' ).Transform;\ns = new Stream();\nvar bool = isNodeTransformStreamLike( s )\nbool = isNodeTransformStreamLike( {} )\n","isNodeWritableStreamLike":"var Stream = require( 'stream' ).Writable;\ns = new Stream();\nvar bool = isNodeWritableStreamLike( s )\nbool = isNodeWritableStreamLike( {} )\n","isNonConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurableProperty( obj, 'boop' )\nbool = isNonConfigurableProperty( obj, 'beep' )\n","isNonConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurablePropertyIn( obj, 'boop' )\nbool = isNonConfigurablePropertyIn( obj, 'beep' )\n","isNonEnumerableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerableProperty( obj, 'boop' )\nbool = isNonEnumerableProperty( obj, 'beep' )\n","isNonEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerablePropertyIn( obj, 'boop' )\nbool = isNonEnumerablePropertyIn( obj, 'beep' )\n","isNonNegativeFinite":"var bool = isNonNegativeFinite( 5.0 )\nbool = isNonNegativeFinite( new Number( 5.0 ) )\nbool = isNonNegativeFinite( 3.14 )\nbool = isNonNegativeFinite( -5.0 )\nbool = isNonNegativeFinite( null )\nbool = isNonNegativeFinite( PINF )\n","isNonNegativeFinite.isPrimitive":"var bool = isNonNegativeFinite.isPrimitive( 3.0 )\nbool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeFinite.isObject":"var bool = isNonNegativeFinite.isObject( 3.0 )\nbool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n","isNonNegativeInteger":"var bool = isNonNegativeInteger( 5.0 )\nbool = isNonNegativeInteger( new Number( 5.0 ) )\nbool = isNonNegativeInteger( 3.14 )\nbool = isNonNegativeInteger( -5.0 )\nbool = isNonNegativeInteger( null )\n","isNonNegativeInteger.isPrimitive":"var bool = isNonNegativeInteger.isPrimitive( 3.0 )\nbool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeInteger.isObject":"var bool = isNonNegativeInteger.isObject( 3.0 )\nbool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n","isNonNegativeIntegerArray":"var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n","isNonNegativeIntegerArray.primitives":"var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeIntegerArray.objects":"var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumber":"var bool = isNonNegativeNumber( 5.0 )\nbool = isNonNegativeNumber( new Number( 5.0 ) )\nbool = isNonNegativeNumber( 3.14 )\nbool = isNonNegativeNumber( -5.0 )\nbool = isNonNegativeNumber( null )\n","isNonNegativeNumber.isPrimitive":"var bool = isNonNegativeNumber.isPrimitive( 3.0 )\nbool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeNumber.isObject":"var bool = isNonNegativeNumber.isObject( 3.0 )\nbool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n","isNonNegativeNumberArray":"var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n","isNonNegativeNumberArray.primitives":"var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumberArray.objects":"var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonPositiveFinite":"var bool = isNonPositiveFinite( -5.0 )\nbool = isNonPositiveFinite( new Number( -5.0 ) )\nbool = isNonPositiveFinite( -3.14 )\nbool = isNonPositiveFinite( 5.0 )\nbool = isNonPositiveFinite( null )\n","isNonPositiveFinite.isPrimitive":"var bool = isNonPositiveFinite.isPrimitive( -3.0 )\nbool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveFinite.isObject":"var bool = isNonPositiveFinite.isObject( -3.0 )\nbool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n","isNonPositiveInteger":"var bool = isNonPositiveInteger( -5.0 )\nbool = isNonPositiveInteger( new Number( -5.0 ) )\nbool = isNonPositiveInteger( 5.0 )\nbool = isNonPositiveInteger( -3.14 )\nbool = isNonPositiveInteger( null )\n","isNonPositiveInteger.isPrimitive":"var bool = isNonPositiveInteger.isPrimitive( -3.0 )\nbool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveInteger.isObject":"var bool = isNonPositiveInteger.isObject( -3.0 )\nbool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n","isNonPositiveIntegerArray":"var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n","isNonPositiveIntegerArray.primitives":"var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveIntegerArray.objects":"var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumber":"var bool = isNonPositiveNumber( -5.0 )\nbool = isNonPositiveNumber( new Number( -5.0 ) )\nbool = isNonPositiveNumber( -3.14 )\nbool = isNonPositiveNumber( 5.0 )\nbool = isNonPositiveNumber( null )\n","isNonPositiveNumber.isPrimitive":"var bool = isNonPositiveNumber.isPrimitive( -3.0 )\nbool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveNumber.isObject":"var bool = isNonPositiveNumber.isObject( -3.0 )\nbool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n","isNonPositiveNumberArray":"var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n","isNonPositiveNumberArray.primitives":"var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumberArray.objects":"var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonSymmetricMatrix":"var buf = [ 1, 2, 3, 4 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isNonSymmetricMatrix( M )\nbool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isNonSymmetricMatrix( 3.14 )\nbool = isNonSymmetricMatrix( {} )\n","isNull":"var bool = isNull( null )\nbool = isNull( true )\n","isNullArray":"var bool = isNullArray( [ null, null, null ] )\nbool = isNullArray( [ NaN, 2, null ] )\n","isNumber":"var bool = isNumber( 3.14 )\nbool = isNumber( new Number( 3.14 ) )\nbool = isNumber( NaN )\nbool = isNumber( null )\n","isNumber.isPrimitive":"var bool = isNumber.isPrimitive( 3.14 )\nbool = isNumber.isPrimitive( NaN )\nbool = isNumber.isPrimitive( new Number( 3.14 ) )\n","isNumber.isObject":"var bool = isNumber.isObject( 3.14 )\nbool = isNumber.isObject( new Number( 3.14 ) )\n","isNumberArray":"var bool = isNumberArray( [ 1, 2, 3 ] )\nbool = isNumberArray( [ '1', 2, 3 ] )\n","isNumberArray.primitives":"var arr = [ 1, 2, 3 ];\nvar bool = isNumberArray.primitives( arr )\narr = [ 1, new Number( 2 ) ];\nbool = isNumberArray.primitives( arr )\n","isNumberArray.objects":"var arr = [ new Number( 1 ), new Number( 2 ) ];\nvar bool = isNumberArray.objects( arr )\narr = [ new Number( 1 ), 2 ];\nbool = isNumberArray.objects( arr )\n","isNumericArray":"var bool = isNumericArray( new Int8Array( 10 ) )\nbool = isNumericArray( [ 1, 2, 3 ] )\nbool = isNumericArray( [ '1', '2', '3' ] )\n","isObject":"var bool = isObject( {} )\nbool = isObject( true )\n","isObjectArray":"var bool = isObjectArray( [ {}, new Number(3.0) ] )\nbool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isObjectArray( [ {}, '3.0' ] )\n","isObjectLike":"var bool = isObjectLike( {} )\nbool = isObjectLike( [] )\nbool = isObjectLike( null )\n","isOdd":"var bool = isOdd( 5.0 )\nbool = isOdd( new Number( 5.0 ) )\nbool = isOdd( 4.0 )\nbool = isOdd( new Number( 4.0 ) )\nbool = isOdd( -3.14 )\nbool = isOdd( null )\n","isOdd.isPrimitive":"var bool = isOdd.isPrimitive( -5.0 )\nbool = isOdd.isPrimitive( new Number( -5.0 ) )\n","isOdd.isObject":"var bool = isOdd.isObject( 5.0 )\nbool = isOdd.isObject( new Number( 5.0 ) )\n","isoWeeksInYear":"var num = isoWeeksInYear()\nnum = isoWeeksInYear( 2015 )\nnum = isoWeeksInYear( 2017 )\n","isPascalcase":"var bool = isPascalcase( 'HelloWorld' )\nbool = isPascalcase( 'hello-world' )\n","isPersymmetricMatrix":"var buf = [ 1, 2, 3, 1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isPersymmetricMatrix( M )\nbool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isPersymmetricMatrix( 3.14 )\nbool = isPersymmetricMatrix( {} )\n","isPlainObject":"var bool = isPlainObject( {} )\nbool = isPlainObject( null )\n","isPlainObjectArray":"var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isPlainObjectArray( [ {}, new Number(3.0) ] )\nbool = isPlainObjectArray( [ {}, '3.0' ] )\n","isPositiveFinite":"var bool = isPositiveFinite( 5.0 )\nbool = isPositiveFinite( new Number( 5.0 ) )\nbool = isPositiveFinite( 3.14 )\nbool = isPositiveFinite( -5.0 )\nvar bool = isPositiveFinite( 1.0/0.0 )\nbool = isPositiveFinite( new Number( 1.0/0.0 ) )\nbool = isPositiveFinite( null )\n","isPositiveFinite.isPrimitive":"var bool = isPositiveFinite.isPrimitive( 3.0 )\nvar bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\nbool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n","isPositiveFinite.isObject":"var bool = isPositiveFinite.isObject( 3.0 )\nbool = isPositiveFinite.isObject( new Number( 3.0 ) )\nbool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n","isPositiveInteger":"var bool = isPositiveInteger( 5.0 )\nbool = isPositiveInteger( new Number( 5.0 ) )\nbool = isPositiveInteger( 3.14 )\nbool = isPositiveInteger( -5.0 )\nbool = isPositiveInteger( null )\n","isPositiveInteger.isPrimitive":"var bool = isPositiveInteger.isPrimitive( 3.0 )\nbool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n","isPositiveInteger.isObject":"var bool = isPositiveInteger.isObject( 3.0 )\nbool = isPositiveInteger.isObject( new Number( 3.0 ) )\n","isPositiveIntegerArray":"var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n","isPositiveIntegerArray.primitives":"var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveIntegerArray.objects":"var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveNumber":"var bool = isPositiveNumber( 5.0 )\nbool = isPositiveNumber( new Number( 5.0 ) )\nbool = isPositiveNumber( 3.14 )\nbool = isPositiveNumber( -5.0 )\nbool = isPositiveNumber( null )\n","isPositiveNumber.isPrimitive":"var bool = isPositiveNumber.isPrimitive( 3.0 )\nbool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n","isPositiveNumber.isObject":"var bool = isPositiveNumber.isObject( 3.0 )\nbool = isPositiveNumber.isObject( new Number( 3.0 ) )\n","isPositiveNumberArray":"var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n","isPositiveNumberArray.primitives":"var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveNumberArray.objects":"var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveZero":"var bool = isPositiveZero( 0.0 )\nbool = isPositiveZero( new Number( 0.0 ) )\nbool = isPositiveZero( -3.14 )\nbool = isPositiveZero( -0.0 )\nbool = isPositiveZero( null )\n","isPositiveZero.isPrimitive":"var bool = isPositiveZero.isPrimitive( 0.0 )\nbool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n","isPositiveZero.isObject":"var bool = isPositiveZero.isObject( 0.0 )\nbool = isPositiveZero.isObject( new Number( 0.0 ) )\n","isPrime":"var bool = isPrime( 5.0 )\nbool = isPrime( new Number( 5.0 ) )\nbool = isPrime( 3.14 )\nbool = isPrime( -5.0 )\nbool = isPrime( null )\n","isPrime.isPrimitive":"var bool = isPrime.isPrimitive( 5.0 )\nbool = isPrime.isPrimitive( new Number( 5.0 ) )\n","isPrime.isObject":"var bool = isPrime.isObject( 5.0 )\nbool = isPrime.isObject( new Number( 5.0 ) )\n","isPrimitive":"var bool = isPrimitive( true )\nbool = isPrimitive( {} )\n","isPrimitiveArray":"var bool = isPrimitiveArray( [ '3', 2, null ] )\nbool = isPrimitiveArray( [ {}, 2, 1 ] )\nbool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n","isPRNGLike":"var bool = isPRNGLike( base.random.randu )\nbool = isPRNGLike( [ 1, 2, 3, 4 ] )\nbool = isPRNGLike( 3.14 )\nbool = isPRNGLike( {} )\n","isProbability":"var bool = isProbability( 0.5 )\nbool = isProbability( new Number( 0.5 ) )\nbool = isProbability( 3.14 )\nbool = isProbability( -5.0 )\nbool = isProbability( null )\n","isProbability.isPrimitive":"var bool = isProbability.isPrimitive( 0.3 )\nbool = isProbability.isPrimitive( new Number( 0.3 ) )\n","isProbability.isObject":"var bool = isProbability.isObject( 0.77 )\nbool = isProbability.isObject( new Number( 0.77 ) )\n","isProbabilityArray":"var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\nbool = isProbabilityArray( [ 0.8, 1.2 ] )\nbool = isProbabilityArray( [ 0.8, '0.2' ] )\n","isProbabilityArray.primitives":"var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\nbool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n","isProbabilityArray.objects":"var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\nbool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n","isPropertyKey":"var out = isPropertyKey( 'foo' )\nout = isPropertyKey( 1 )\nout = isPropertyKey( true )\n","isPrototypeOf":"function Foo() { return this; };\nfunction Bar() { return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar bool = isPrototypeOf( bar, Foo.prototype )\n","isRaggedNestedArray":"var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\nbool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nbool = isRaggedNestedArray( 'beep' )\n","isRangeError":"var bool = isRangeError( new RangeError( 'beep' ) )\nbool = isRangeError( {} )\n","isReadableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadableProperty( obj, 'boop' )\nbool = isReadableProperty( obj, 'beep' )\n","isReadablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadablePropertyIn( obj, 'boop' )\nbool = isReadablePropertyIn( obj, 'beep' )\n","isReadOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyProperty( obj, 'boop' )\nbool = isReadOnlyProperty( obj, 'beep' )\n","isReadOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyPropertyIn( obj, 'boop' )\nbool = isReadOnlyPropertyIn( obj, 'beep' )\n","isReadWriteProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWriteProperty( obj, 'boop' )\nbool = isReadWriteProperty( obj, 'beep' )\n","isReadWritePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWritePropertyIn( obj, 'boop' )\nbool = isReadWritePropertyIn( obj, 'beep' )\n","isReferenceError":"var bool = isReferenceError( new ReferenceError( 'beep' ) )\nbool = isReferenceError( {} )\n","isRegExp":"var bool = isRegExp( /\\.+/ )\nbool = isRegExp( {} )\n","isRegExpString":"var bool = isRegExpString( '/beep/' )\nbool = isRegExpString( 'beep' )\nbool = isRegExpString( '' )\nbool = isRegExpString( null )\n","isRelativePath":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( './foo/bar/baz' )\n","isRelativePath.posix":"var bool = isRelativePath.posix( './foo/bar/baz' )\nbool = isRelativePath.posix( '/foo/../bar/baz' )\n","isRelativePath.win32":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n","isRelativeURI":"var bool = isRelativeURI( '/images/example.png' )\nbool = isRelativeURI( 'http://www.example.com' )\nbool = isRelativeURI( null )\n","isSafeInteger":"var bool = isSafeInteger( 5.0 )\nbool = isSafeInteger( new Number( 5.0 ) )\nbool = isSafeInteger( 2.0e200 )\nbool = isSafeInteger( -3.14 )\nbool = isSafeInteger( null )\n","isSafeInteger.isPrimitive":"var bool = isSafeInteger.isPrimitive( -3.0 )\nbool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n","isSafeInteger.isObject":"var bool = isSafeInteger.isObject( 3.0 )\nbool = isSafeInteger.isObject( new Number( 3.0 ) )\n","isSafeIntegerArray":"var arr = [ -3.0, new Number(0.0), 2.0 ];\nvar bool = isSafeIntegerArray( arr )\narr = [ -3.0, '3.0' ];\nbool = isSafeIntegerArray( arr )\n","isSafeIntegerArray.primitives":"var arr = [ -1.0, 10.0 ];\nvar bool = isSafeIntegerArray.primitives( arr )\narr = [ -1.0, 0.0, 5.0 ];\nbool = isSafeIntegerArray.primitives( arr )\narr = [ -3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.primitives( arr )\n","isSafeIntegerArray.objects":"var arr = [ new Number(1.0), new Number(3.0) ];\nvar bool = isSafeIntegerArray.objects( arr )\narr = [ -1.0, 0.0, 3.0 ];\nbool = isSafeIntegerArray.objects( arr )\narr = [ 3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.objects( arr )\n","isSameArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArray( x, y )\n","isSameArrayLike":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArrayLike( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArrayLike( x, y )\n","isSameComplex64":"var x = new Complex64( 1.0, 2.0 );\nvar y = new Complex64( 1.0, 2.0 );\nvar bool = isSameComplex64( x, y )\nx = new Complex64( NaN, NaN );\ny = new Complex64( NaN, NaN );\nbool = isSameComplex64( x, y )\n","isSameComplex64Array":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex64Array( x, y )\nx = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex64Array( x, y )\n","isSameComplex128":"var x = new Complex128( 1.0, 2.0 );\nvar y = new Complex128( 1.0, 2.0 );\nvar bool = isSameComplex128( x, y )\nx = new Complex128( NaN, NaN );\ny = new Complex128( NaN, NaN );\nbool = isSameComplex128( x, y )\n","isSameComplex128Array":"var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex128Array( x, y )\nx = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex128Array( x, y )\n","isSameFloat32Array":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat32Array( x, y )\nx = new Float32Array( [ NaN, NaN, NaN ] );\ny = new Float32Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat32Array( x, y )\n","isSameFloat64Array":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat64Array( x, y )\nx = new Float64Array( [ NaN, NaN, NaN ] );\ny = new Float64Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat64Array( x, y )\n","isSameNativeClass":"var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\nbool = isSameNativeClass( 'beep', 'boop' )\nbool = isSameNativeClass( {}, [] )\n","isSameType":"var bool = isSameType( true, true )\nbool = isSameType( {}, [] )\nbool = isSameType( 3.12, -3.12 )\nbool = isSameType( 0.0, '0.0' )\n","isSameValue":"var bool = isSameValue( true, true )\nbool = isSameValue( {}, {} )\nbool = isSameValue( -0.0, -0.0 )\nbool = isSameValue( -0.0, 0.0 )\nbool = isSameValue( NaN, NaN )\n","isSameValueZero":"var bool = isSameValueZero( true, true )\nbool = isSameValueZero( {}, {} )\nbool = isSameValueZero( -0.0, -0.0 )\nbool = isSameValueZero( -0.0, 0.0 )\nbool = isSameValueZero( NaN, NaN )\n","isSemVer":"var bool = isSemVer( '1.0.0' )\nbool = isSemVer( '1.0.0-alpha.1' )\nbool = isSemVer( '0.1' )\nbool = isSemVer( null )\n","isSharedArrayBuffer":"var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\nbool = isSharedArrayBuffer( [] )\n","isSkewCentrosymmetricMatrix":"var buf = [ 2, 1, -1, -2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewCentrosymmetricMatrix( M )\nbool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewCentrosymmetricMatrix( 3.14 )\nbool = isSkewCentrosymmetricMatrix( {} )\n","isSkewPersymmetricMatrix":"var buf = [ 1, 0, 0, -1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewPersymmetricMatrix( M )\nbool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewPersymmetricMatrix( 3.14 )\nbool = isSkewPersymmetricMatrix( {} )\n","isSkewSymmetricMatrix":"var buf = [ 0, -1, 1, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewSymmetricMatrix( M )\nbool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewSymmetricMatrix( 3.14 )\nbool = isSkewSymmetricMatrix( {} )\n","isSlice":"var bool = isSlice( new Slice( 10 ) )\nbool = isSlice( 3.14 )\nbool = isSlice( {} )\n","isSnakecase":"var bool = isSnakecase( 'hello_world' )\nbool = isSnakecase( 'Hello World' )\n","isSquareMatrix":"var buf = [ 0, 0, 0, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSquareMatrix( M )\nbool = isSquareMatrix( [ 1, 2, 3, 4 ] )\nbool = isSquareMatrix( 3.14 )\nbool = isSquareMatrix( {} )\n","isSquareNumber":"var bool = isSquareNumber( 4.0 )\nbool = isSquareNumber( new Number( 4.0 ) )\nbool = isSquareNumber( 3.14 )\nbool = isSquareNumber( -5.0 )\nbool = isSquareNumber( null )\n","isSquareNumber.isPrimitive":"var bool = isSquareNumber.isPrimitive( 4.0 )\nbool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n","isSquareNumber.isObject":"var bool = isSquareNumber.isObject( 4.0 )\nbool = isSquareNumber.isObject( new Number( 4.0 ) )\n","isSquareTriangularNumber":"var bool = isSquareTriangularNumber( 36.0 )\nbool = isSquareTriangularNumber( new Number( 36.0 ) )\nbool = isSquareTriangularNumber( 3.14 )\nbool = isSquareTriangularNumber( -5.0 )\nbool = isSquareTriangularNumber( null )\n","isSquareTriangularNumber.isPrimitive":"var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\nbool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isSquareTriangularNumber.isObject":"var bool = isSquareTriangularNumber.isObject( 36.0 )\nbool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n","isStartcase":"var bool = isStartcase( 'Beep Boop' )\nbool = isStartcase( 'Beep and Boop' )\n","isStrictEqual":"var bool = isStrictEqual( true, true )\nbool = isStrictEqual( {}, {} )\nbool = isStrictEqual( -0.0, -0.0 )\nbool = isStrictEqual( -0.0, 0.0 )\nbool = isStrictEqual( NaN, NaN )\n","isString":"var bool = isString( 'beep' )\nbool = isString( new String( 'beep' ) )\nbool = isString( 5 )\n","isString.isPrimitive":"var bool = isString.isPrimitive( 'beep' )\nbool = isString.isPrimitive( new String( 'beep' ) )\n","isString.isObject":"var bool = isString.isObject( new String( 'beep' ) )\nbool = isString.isObject( 'beep' )\n","isStringArray":"var bool = isStringArray( [ 'abc', 'def' ] )\nbool = isStringArray( [ 'abc', 123 ] )\n","isStringArray.primitives":"var arr = [ 'abc', 'def' ];\nvar bool = isStringArray.primitives( arr )\narr = [ 'abc', new String( 'def' ) ];\nbool = isStringArray.primitives( arr )\n","isStringArray.objects":"var arr = [ new String( 'ab' ), new String( 'cd' ) ];\nvar bool = isStringArray.objects( arr )\narr = [ new String( 'abc' ), 'def' ];\nbool = isStringArray.objects( arr )\n","isStruct":"var schema = [ { 'name': 'foo', 'type': 'float64' } ];\nvar S = structFactory( schema );\nvar bool = isStruct( new S() )\nbool = isStruct( [ 1, 2, 3, 4 ] )\nbool = isStruct( 3.14 )\nbool = isStruct( {} )\n","isStructConstructorLike":"var schema = [ { 'name': 'foo', 'type': 'float64' } ];\nvar S = structFactory( schema );\nvar bool = isStructConstructorLike( S )\nbool = isStructConstructorLike( [ 1, 2, 3, 4 ] )\nbool = isStructConstructorLike( 3.14 )\nbool = isStructConstructorLike( {} )\n","isSymbol":"var bool = isSymbol( Symbol( 'beep' ) )\nbool = isSymbol( Object( Symbol( 'beep' ) ) )\nbool = isSymbol( {} )\nbool = isSymbol( null )\nbool = isSymbol( true )\n","isSymbolArray":"var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\nbool = isSymbolArray( Symbol( 'beep' ) )\nbool = isSymbolArray( [] )\nbool = isSymbolArray( {} )\nbool = isSymbolArray( null )\nbool = isSymbolArray( true )\n","isSymbolArray.primitives":"var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.primitives( [] )\nbool = isSymbolArray.primitives( {} )\nbool = isSymbolArray.primitives( null )\nbool = isSymbolArray.primitives( true )\n","isSymbolArray.objects":"var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.objects( [] )\nbool = isSymbolArray.objects( {} )\nbool = isSymbolArray.objects( null )\nbool = isSymbolArray.objects( true )\n","isSymmetricMatrix":"var buf = [ 0, 1, 1, 2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSymmetricMatrix( M )\nbool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSymmetricMatrix( 3.14 )\nbool = isSymmetricMatrix( {} )\n","isSyntaxError":"var bool = isSyntaxError( new SyntaxError( 'beep' ) )\nbool = isSyntaxError( {} )\n","isTriangularNumber":"var bool = isTriangularNumber( 36.0 )\nbool = isTriangularNumber( new Number( 36.0 ) )\nbool = isTriangularNumber( 3.14 )\nbool = isTriangularNumber( -5.0 )\nbool = isTriangularNumber( null )\n","isTriangularNumber.isPrimitive":"var bool = isTriangularNumber.isPrimitive( 36.0 )\nbool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isTriangularNumber.isObject":"var bool = isTriangularNumber.isObject( 36.0 )\nbool = isTriangularNumber.isObject( new Number( 36.0 ) )\n","isTruthy":"var bool = isTruthy( true )\nbool = isTruthy( {} )\nbool = isTruthy( [] )\nbool = isTruthy( false )\nbool = isTruthy( '' )\nbool = isTruthy( 0 )\nbool = isTruthy( null )\nbool = isTruthy( void 0 )\nbool = isTruthy( NaN )\n","isTruthyArray":"var bool = isTruthyArray( [ {}, [] ] )\nbool = isTruthyArray( [ null, '' ] )\nbool = isTruthyArray( [] )\n","isTypedArray":"var bool = isTypedArray( new Int8Array( 10 ) )\n","isTypedArrayLength":"var bool = isTypedArrayLength( 5 )\nbool = isTypedArrayLength( 2.0e200 )\nbool = isTypedArrayLength( -3.14 )\nbool = isTypedArrayLength( null )\n","isTypedArrayLike":"var bool = isTypedArrayLike( new Int16Array() )\nbool = isTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4\n })\n","isTypeError":"var bool = isTypeError( new TypeError( 'beep' ) )\nbool = isTypeError( {} )\n","isUint8Array":"var bool = isUint8Array( new Uint8Array( 10 ) )\nbool = isUint8Array( [] )\n","isUint8ClampedArray":"var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\nbool = isUint8ClampedArray( [] )\n","isUint16Array":"var bool = isUint16Array( new Uint16Array( 10 ) )\nbool = isUint16Array( [] )\n","isUint32Array":"var bool = isUint32Array( new Uint32Array( 10 ) )\nbool = isUint32Array( [] )\n","isUNCPath":"var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\nbool = isUNCPath( '/foo/bar/baz' )\n","isUndefined":"var bool = isUndefined( void 0 )\nbool = isUndefined( null )\n","isUndefinedOrNull":"var bool = isUndefinedOrNull( void 0 )\nbool = isUndefinedOrNull( null )\nbool = isUndefinedOrNull( false )\n","isUnityProbabilityArray":"var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\nbool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\nbool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\nbool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n","isUppercase":"var bool = isUppercase( 'HELLO' )\nbool = isUppercase( 'World' )\n","isURI":"var bool = isURI( 'http://google.com' )\nbool = isURI( 'http://localhost/' )\nbool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\nbool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\nbool = isURI( '' )\nbool = isURI( 'foo@bar' )\nbool = isURI( '://foo/' )\nbool = isURI( 'http://' )\nbool = isURI( 'http:////foo.html' )\nbool = isURI( 'http://example.w3.org/%a' )\n","isURIError":"var bool = isURIError( new URIError( 'beep' ) )\nbool = isURIError( {} )\n","isVectorLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isVectorLike( M )\nbool = isVectorLike( [ 1, 2, 3, 4 ] )\nbool = isVectorLike( 3.14 )\nbool = isVectorLike( {} )\n","isWebAssemblyMemory":"var bool = isWebAssemblyMemory( {} )\n","isWellFormedString":"var bool = isWellFormedString( '' )\nbool = isWellFormedString( new String( '' ) )\nbool = isWellFormedString( '\\uDBFF' )\nbool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\nbool = isWellFormedString( [] )\nbool = isWellFormedString( '-5' )\nbool = isWellFormedString( null )\n","isWellFormedString.isPrimitive":"var bool = isWellFormedString.isPrimitive( '' )\nbool = isWellFormedString.isPrimitive( new String( '' ) )\n","isWellFormedString.isObject":"var bool = isWellFormedString.isObject( '' )\nbool = isWellFormedString.isObject( new String( '' ) )\n","isWhitespace":"var bool = isWhitespace( ' ' )\nbool = isWhitespace( 'abcdef' )\nbool = isWhitespace( '' )\n","isWritableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritableProperty( obj, 'boop' )\nbool = isWritableProperty( obj, 'beep' )\n","isWritablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritablePropertyIn( obj, 'boop' )\nbool = isWritablePropertyIn( obj, 'beep' )\n","isWriteOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyProperty( obj, 'boop' )\nbool = isWriteOnlyProperty( obj, 'beep' )\n","isWriteOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyPropertyIn( obj, 'boop' )\nbool = isWriteOnlyPropertyIn( obj, 'beep' )\n","iterAbs":"var it = iterAbs( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAbs2":"var it = iterAbs2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAcos":"var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcosh":"var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcot":"var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoth":"var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcovercos":"var it = iterAcovercos( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoversin":"var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAdd":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterAdd( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterAdvance":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar it = iterAdvance( arr, 4 );\nvar v = it.next().value\nvar bool = it.next().done\n","iterAhavercos":"var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAhaversin":"var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAny":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterAny( arr )\n","iterAnyBy":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v === 1 ); };\nvar bool = iterAnyBy( arr, fcn )\n","iterAsin":"var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAsinh":"var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan":"var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan2":"var x = random.iterators.uniform( -2.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterAtan2( y, x );\nvar r = it.next().value\nr = it.next().value\n","iterAtanh":"var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterator2array":"var opts = { 'iter': 10 };\nvar arr = iterator2array( random.iterators.randu( opts ) )\n","iterator2arrayview":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayview( it, out, 5, 15 )\n","iterator2arrayviewRight":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayviewRight( it, out, 5, 15 )\n","iteratorStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream( it );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","iteratorStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = iteratorStream.factory( opts );\n","iteratorStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream.objectMode( it );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","IteratorSymbol":"var s = IteratorSymbol\n","iterAvercos":"var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAversin":"var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterawgn":"var src = iterSineWave();\nvar it = iterawgn( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawln":"var src = iterSineWave();\nvar it = iterawln( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawun":"var src = iterSineWave();\nvar it = iterawun( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterBartlettHannPulse":"var it = iterBartlettHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBartlettPulse":"var it = iterBartlettPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBesselj0":"var it = iterBesselj0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBesselj1":"var it = iterBesselj1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely0":"var it = iterBessely0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely1":"var it = iterBessely1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBeta":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBeta( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBetaln":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBetaln( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBinet":"var it = iterBinet( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCbrt":"var it = iterCbrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil":"var it = iterCeil( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil2":"var it = iterCeil2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil10":"var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterCompositesSeq":"var it = iterCompositesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterConcat":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = array2iterator( [ 3, 4 ] );\nvar it = iterConcat( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterConstant":"var it = iterConstant( 3.14 );\nvar v = it.next().value\nv = it.next().value\n","iterContinuedFraction":"var terms = array2iterator( [ 3, 4, 12, 4 ] );\nvar v = iterContinuedFraction( terms )\n","iterContinuedFractionSeq":"var it = iterContinuedFractionSeq( 3.245 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\nit = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n","iterCos":"var it = iterCos( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCosh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterCosh( r );\nvar v = it.next().value\nv = it.next().value\n","iterCosineWave":"var it = iterCosineWave();\nvar v = it.next().value\nv = it.next().value\n","iterCosm1":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCosm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterCospi":"var it = iterCospi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCounter":"var it = iterCounter( random.iterators.randu() );\nvar v = it.next().value\nv = it.next().value\n","iterCovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterCoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterCubesSeq":"var it = iterCubesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","itercugmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercugmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercuhmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercuhmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumax( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumaxabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumean( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs2( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumidrange( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumin( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuminabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuprod( arr );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itercurange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercurange( arr );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\nr = it.next().value\n","itercusum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusum( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs2( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterDatespace":"var t1 = new Date();\nvar it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\nvar v = it.next().value\nv = it.next().value\n","iterDedupe":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nvar it = iterDedupe( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDedupeBy":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nfunction fcn( v ) { return v; };\nvar it = iterDedupeBy( arr, fcn );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDeg2rad":"var r = random.iterators.uniform( -360.0, 360.0 );\nvar it = iterDeg2rad( r );\nvar v = it.next().value\nv = it.next().value\n","iterDigamma":"var r = random.iterators.uniform( 0.01, 5.0 );\nvar it = iterDigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterDiracComb":"var it = iterDiracComb();\nvar v = it.next().value\nv = it.next().value\n","iterDiracDelta":"var it = iterDiracDelta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterDivide":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterDivide( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterDoUntilEach":"function predicate( v ) { return v !== v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterDoUntilEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterDoWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterDoWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterEllipe":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipe( r );\nvar v = it.next().value\nv = it.next().value\n","iterEllipk":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipk( r );\nvar v = it.next().value\nv = it.next().value\n","iterEmpty":"var it = iterEmpty();\nvar bool = it.next().done\n","iterErf":"var it = iterErf( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfc":"var it = iterErfc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfcinv":"var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterErfinv":"var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterEta":"var it = iterEta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterEvenIntegersSeq":"var it = iterEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterEvery":"var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\nvar bool = iterEvery( arr )\n","iterEveryBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterEveryBy( arr, fcn )\n","iterExp":"var it = iterExp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterExp2":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp2( r );\nvar v = it.next().value\nv = it.next().value\n","iterExp10":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp10( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterExpit( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterExpm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1rel":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExpm1rel( r );\nvar v = it.next().value\nv = it.next().value\n","iterFactorial":"var it = iterFactorial( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialln":"var it = iterFactorialln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialsSeq":"var it = iterFactorialsSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFibonacciSeq":"var it = iterFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterFifthPowersSeq":"var it = iterFifthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFill":"var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterFilter":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilter( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFilterMap":"function f( v ) { if ( v > 2 ) { return v * 10 }; };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilterMap( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFirst":"var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\nvar v = iterFirst( arr )\n","iterFlatTopPulse":"var it = iterFlatTopPulse();\nvar v = it.next().value\nv = it.next().value\n","iterFloor":"var it = iterFloor( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFloor2":"var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFloor10":"var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFlow":"var o = {};\no.head = iterHead;\no.some = iterSome;\nvar fiter = iterFlow( o )\n","iterForEach":"function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterForEach( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterFourthPowersSeq":"var it = iterFourthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFresnelc":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnelc( r );\nvar v = it.next().value\nv = it.next().value\n","iterFresnels":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnels( r );\nvar v = it.next().value\nv = it.next().value\n","iterGamma":"var it = iterGamma( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterGamma1pm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterGamma1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterGammaln":"var it = iterGammaln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterHacovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHacoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHannPulse":"var it = iterHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterHavercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHavercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHaversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHaversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHead":"var it = iterHead( random.iterators.randu(), 5 );\nvar r = it.next().value\nr = it.next().value\n","iterIncrspace":"var it = iterIncrspace( 0, 101, 2 );\nvar v = it.next().value\nv = it.next().value\n","iterIntegersSeq":"var it = iterIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterIntersection":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterIntersection( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterIntersectionByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nfunction f( v ) { return v.toString(); };\nvar it = iterIntersectionByHash( it1, it2, f );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterInv":"var it = iterInv( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLanczosPulse":"var it = iterLanczosPulse();\nvar v = it.next().value\nv = it.next().value\n","iterLast":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar v = iterLast( arr )\n","iterLength":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar len = iterLength( arr )\n","iterLinspace":"var it = iterLinspace( 0, 99, 100 );\nvar v = it.next().value\nv = it.next().value\n","iterLn":"var it = iterLn( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog":"var x = random.iterators.uniform( 0.0, 100.0 );\nvar y = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterLog( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterLog1mexp":"var it = iterLog1mexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1p":"var it = iterLog1p( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1pexp":"var it = iterLog1pexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog2":"var it = iterLog2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog10":"var it = iterLog10( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLogit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterLogit( r );\nvar v = it.next().value\nv = it.next().value\n","iterLogspace":"var it = iterLogspace( 0, 3, 4 );\nvar v = it.next().value\nv = it.next().value\n","iterLucasSeq":"var it = iterLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterMap":"function f( v ) { return v * 10.0; };\nvar it = iterMap( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterMapN":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nfunction fcn( x, y ) { return x + y; };\nvar it = iterMapN( it1, it2, fcn );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermax":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermax( arr )\n","itermaxabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermaxabs( arr )\n","itermean":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = itermean( arr )\n","itermeanabs":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs( arr )\n","itermeanabs2":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs2( arr )\n","itermidrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = itermidrange( arr )\n","itermin":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermin( arr )\n","iterminabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = iterminabs( arr )\n","itermmax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmax( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmaxabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmean( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs2( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmidrange( arr, 3 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itermmin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmin( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermminabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","iterMod":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterMod( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermprod( arr, 3 );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itermrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermrange( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermsum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsum( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs2( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterMultiply":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterMultiply( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterNegaFibonacciSeq":"var it = iterNegaFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegaLucasSeq":"var it = iterNegaLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeEvenIntegersSeq":"var it = iterNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeIntegersSeq":"var it = iterNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeOddIntegersSeq":"var it = iterNegativeOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNone":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterNone( arr )\n","iterNoneBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v <= 0 ); };\nvar bool = iterNoneBy( arr, fcn )\n","iterNonFibonacciSeq":"var it = iterNonFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeEvenIntegersSeq":"var it = iterNonNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeIntegersSeq":"var it = iterNonNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveEvenIntegersSeq":"var it = iterNonPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveIntegersSeq":"var it = iterNonPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonSquaresSeq":"var it = iterNonSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterNth":"var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\nvar v = iterNth( arr, 3 )\n","iterOddIntegersSeq":"var it = iterOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterPeriodicSinc":"var it = iterPeriodicSinc( 7 );\nvar v = it.next().value\nv = it.next().value\n","iterPipeline":"var it1 = iterThunk( iterHead, 100 );\nfunction f( r ) { return ( r > 0.95 ); };\nvar it2 = iterThunk( iterSomeBy, 5, f );\nvar p = iterPipeline( it1, it2 );\nvar bool = p( random.iterators.randu() )\n","iterPop":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPop( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterPositiveEvenIntegersSeq":"var it = iterPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveIntegersSeq":"var it = iterPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveOddIntegersSeq":"var it = iterPositiveOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPow":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterPow( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterPrimesSeq":"var it = iterPrimesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterprod":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = iterprod( arr )\n","iterPulse":"var it = iterPulse();\nvar v = it.next().value\nv = it.next().value\n","iterPush":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPush( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterRad2deg":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterRad2deg( r );\nvar v = it.next().value\nv = it.next().value\n","iterRamp":"var it = iterRamp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = iterrange( arr )\n","iterReject":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterReject( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterReplicate":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nvar it2 = iterReplicate( it1, 2 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterReplicateBy":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nfunction f( v, i ) { return i + 1; };\nvar it2 = iterReplicateBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterRound":"var it = iterRound( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterRound2":"var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRound10":"var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRsqrt":"var it = iterRsqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSawtoothWave":"var it = iterSawtoothWave();\nvar v = it.next().value\nv = it.next().value\n","iterShift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterShift( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterSignum":"var it = iterSignum( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSin":"var it = iterSin( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSinc":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinc( r );\nvar v = it.next().value\nv = it.next().value\n","iterSineWave":"var it = iterSineWave();\nvar v = it.next().value\nv = it.next().value\n","iterSinh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinh( r );\nvar v = it.next().value\nv = it.next().value\n","iterSinpi":"var it = iterSinpi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSlice":"var it = iterSlice( random.iterators.randu(), 5, 10 );\nvar r = it.next().value\nr = it.next().value\n","iterSome":"var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = iterSome( arr, 3 )\n","iterSomeBy":"var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterSomeBy( arr, 3, fcn )\n","iterSpence":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSpence( r );\nvar v = it.next().value\nv = it.next().value\n","iterSqrt":"var it = iterSqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSqrt1pm1":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSqrt1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterSquaredTriangularSeq":"var it = iterSquaredTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquaresSeq":"var it = iterSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquareWave":"var it = iterSquareWave();\nvar v = it.next().value\nv = it.next().value\n","iterstdev":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar m = iterstdev( arr )\n","iterStep":"var it = iterStep( 0, 2, 10 );\nvar v = it.next().value\nv = it.next().value\n","iterStrided":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nvar it = iterStrided( arr, 2, 1 );\nvar r = it.next().value\nr = it.next().value\n","iterStridedBy":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nfunction stride( v, i ) { return (i % 10)+1; };\nvar it = iterStridedBy( arr, stride );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterSubtract":"var it1 = array2iterator( [ 1.0, 5.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterSubtract( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itersum":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = itersum( arr )\n","itersumabs":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs( arr )\n","itersumabs2":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs2( arr )\n","iterTan":"var r = random.iterators.uniform( -1.57, 1.57 );\nvar it = iterTan( r );\nvar v = it.next().value\nv = it.next().value\n","iterTanh":"var r = random.iterators.uniform( -4.0, 4.0 );\nvar it = iterTanh( r );\nvar v = it.next().value\nv = it.next().value\n","iterThunk":"var fcn = iterThunk( iterSome, 3 );\nvar arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = fcn( arr )\n","iterTriangleWave":"var it = iterTriangleWave();\nvar v = it.next().value\nv = it.next().value\n","iterTriangularSeq":"var it = iterTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterTribonnaciSeq":"var it = iterTribonnaciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterTrigamma":"var r = random.iterators.uniform( 0.01, 50.0 );\nvar it = iterTrigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterTrunc":"var it = iterTrunc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc2":"var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc10":"var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterUnion":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterUnion( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterUnique":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = iterUnique( it1 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueBy":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( a, b ) { return ( a !== b ); };\nvar it2 = iterUniqueBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( v ) { return v.toString(); };\nvar it2 = iterUniqueByHash( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUnitspace":"var it = iterUnitspace( 0, 99 );\nvar v = it.next().value\nv = it.next().value\n","iterUnshift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterUnshift( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUntilEach":"function predicate( v ) { return v !== v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterUntilEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","itervariance":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar s2 = itervariance( arr )\n","iterVercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterVersin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVersin( r );\nvar v = it.next().value\nv = it.next().value\n","iterWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterZeta":"var r = random.iterators.uniform( 1.1, 50.0 );\nvar it = iterZeta( r );\nvar v = it.next().value\nv = it.next().value\n","joinStream":"var s = joinStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = joinStream.factory( opts );\nvar s = createStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.objectMode":"var s = joinStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","kde2d":"var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\nvar y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\nvar out = kde2d( x, y )\n","kebabcase":"var out = kebabcase( 'Hello World!' )\nout = kebabcase( 'I am a tiny little teapot' )\n","keyBy":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyBy( arr, toKey )\n","keyByRight":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyByRight( arr, toKey )\n","keysIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = keysIn( obj )\n","kruskalTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = kruskalTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = kruskalTest( arr, { 'groups': groups } )\n","kstest":"var rnorm = base.random.normal.factory({ 'seed': 4839 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\nvar out = kstest( x, 'normal', 0.0, 1.0 )\nout = kstest( x, 'normal', 3.0, 1.0 )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0 )\nout.print()\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\nx = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\nout = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n","last":"var out = last( 'beep' )\nout = last( 'Boop', 2 )\nout = last( 'foo bar', 3 )\n","leveneTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = leveneTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = leveneTest( arr, { 'groups': groups } )\n","LinkedList":"var list = LinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","linspace":"var arr = linspace( 0.0, 100.0, 6 )\narr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\narr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n","linspace.assign":"var arr = [ 0, 0, 0, 0, 0, 0 ];\nvar out = linspace.assign( 0, 100, arr )\nvar bool = ( arr === out )\narr = [ 0, 0, 0, 0, 0 ];\nout = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n","LIU_NEGATIVE_OPINION_WORDS_EN":"var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n","LIU_POSITIVE_OPINION_WORDS_EN":"var list = LIU_POSITIVE_OPINION_WORDS_EN()\n","LN_HALF":"LN_HALF\n","LN_PI":"LN_PI\n","LN_SQRT_TWO_PI":"LN_SQRT_TWO_PI\n","LN_TWO_PI":"LN_TWO_PI\n","LN2":"LN2\n","LN10":"LN10\n","LOG2E":"LOG2E\n","LOG10E":"LOG10E\n","logspace":"var arr = logspace( 0, 2, 6 )\n","lowercase":"var out = lowercase( 'bEEp' )\n","lowercaseKeys":"var obj = { 'A': 1, 'B': 2 };\nvar out = lowercaseKeys( obj )\n","lowess":"var x = new Float64Array( 100 );\nvar y = new Float64Array( x.length );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = i;\n y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n }\nvar out = lowess( x, y );\nvar yhat = out.y;\nvar h = Plot( [ x, x ], [ y, yhat ] );\nh.lineStyle = [ 'none', '-' ];\nh.symbols = [ 'closed-circle', 'none' ];\nh.view( 'window' );\n","lpad":"var out = lpad( 'a', 5 )\nout = lpad( 'beep', 10, 'b' )\nout = lpad( 'boop', 12, 'beep' )\n","ltrim":"var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n","ltrimN":"var out = ltrimN( ' abc ', 2 )\nvar out = ltrimN( '!!!abc!!!', 2, '!' )\n","MALE_FIRST_NAMES_EN":"var list = MALE_FIRST_NAMES_EN()\n","map":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = map( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = map( arr, f );\nvar v = out.get( 1, 1 )\n","map.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","map2":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2( x, y, f );\nvar v = out.get( 1, 1 )\n","map2.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map2d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\nvar out = map2d( arr, f );\nout[ 0 ]\nout[ 1 ]\n","map2Right":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2Right( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2Right( x, y, f );\nvar v = out.get( 1, 1 )\n","map2Right.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2Right.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2Right.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map3d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\nvar out = map3d( arr, f );\nout[ 0 ][ 0 ]\nout[ 1 ][ 0 ]\n","map4d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\nvar out = map4d( arr, f );\nout[ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ]\n","map5d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\nvar out = map5d( arr, f );\nout[ 0 ][ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ][ 0 ]\n","mapArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nfunction clbk( v ) { return v * 2; };\nvar bar = mapArguments( foo, clbk );\nvar out = bar( 1, 2, 3 )\n","mapFun":"function fcn( i ) { return i; };\nvar arr = mapFun( fcn, 5 )\n","mapFunAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nmapFunAsync( fcn, 10, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nvar opts = { 'limit': 2 };\nmapFunAsync( fcn, 10, opts, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nvar opts = { 'series': true };\nmapFunAsync( fcn, 10, opts, done )\n","mapFunAsync.factory":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nvar opts = { 'series': true };\nvar f = mapFunAsync.factory( opts, fcn );\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nf( 10, done )\n","mapKeys":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapKeys( obj, transform )\n","mapKeysAsync":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapKeysAsync( obj, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n","mapKeysAsync.factory":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapKeysAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","mapReduce":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduce( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduce( arr, 0.0, f1, f2 )\n","mapReduceRight":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduceRight( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduceRight( arr, 0.0, f1, f2 )\n","mapRight":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = mapRight( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapRight( arr, f );\nvar v = out.get( 1, 1 )\n","mapRight.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmapRight.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmapRight.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","mapValues":"function transform( value, key ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapValues( obj, transform )\n","mapValuesAsync":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapValuesAsync( obj, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n","mapValuesAsync.factory":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapValuesAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","maskArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = maskArguments( foo, [ 1, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","MAX_ARRAY_LENGTH":"MAX_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"MAX_TYPED_ARRAY_LENGTH\n","maybeBroadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","maybeBroadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = maybeBroadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","memoize":"function factorial( n ) {\n var prod;\n var i;\n prod = 1;\n for ( i = n; i > 1; i-- ) {\n prod *= i;\n }\n return prod;\n };\nvar memoized = memoize( factorial );\nvar v = memoized( 5 )\nv = memoized( 5 )\n","merge":"var target = { 'a': 'beep' };\nvar source = { 'a': 'boop', 'b': 'bap' };\nvar out = merge( target, source )\nvar bool = ( out === target )\n","merge.factory":"var opts = {\n 'level': 100,\n 'copy': true,\n 'override': true,\n 'extend': true\n };\nvar merge = merge.factory( opts )\nmerge = merge.factory( { 'level': 2 } );\nvar target = {\n '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n };\nvar source = {\n '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n };\nvar out = merge( target, source )\nmerge = merge.factory( { 'copy': false } );\ntarget = {};\nsource = { 'a': [ 1, 2, 3 ] };\nout = merge( target, source );\nvar bool = ( out.a === source.a )\nmerge = merge.factory( { 'override': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'a': null, 'c': 'bop' };\nout = merge( target, source )\nfunction strategy( a, b, key ) {\n // a => target value\n // b => source value\n // key => object key\n if ( key === 'a' ) {\n return b;\n }\n if ( key === 'b' ) {\n return a;\n }\n return 'bebop';\n };\nmerge = merge.factory( { 'override': strategy } );\ntarget = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\nsource = { 'a': null, 'b': {}, 'c': 'bop' };\nout = merge( target, source )\nmerge = merge.factory( { 'extend': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'b': 'hello', 'c': 'world' };\nout = merge( target, source )\n","MILLISECONDS_IN_DAY":"var days = 3.14;\nvar ms = days * MILLISECONDS_IN_DAY\n","MILLISECONDS_IN_HOUR":"var hrs = 3.14;\nvar ms = hrs * MILLISECONDS_IN_HOUR\n","MILLISECONDS_IN_MINUTE":"var mins = 3.14;\nvar ms = mins * MILLISECONDS_IN_MINUTE\n","MILLISECONDS_IN_SECOND":"var secs = 3.14;\nvar ms = secs * MILLISECONDS_IN_SECOND\n","MILLISECONDS_IN_WEEK":"var weeks = 3.14;\nvar ms = weeks * MILLISECONDS_IN_WEEK\n","MINARD_NAPOLEONS_MARCH":"var data = MINARD_NAPOLEONS_MARCH();\nvar army = data.army\nvar cities = data.cities\nvar labels = data.labels\nvar rivers = data.rivers\nvar t = data.temperature\n","MINUTES_IN_DAY":"var days = 3.14;\nvar mins = days * MINUTES_IN_DAY\n","MINUTES_IN_HOUR":"var hrs = 3.14;\nvar mins = hrs * MINUTES_IN_HOUR\n","MINUTES_IN_WEEK":"var wks = 3.14;\nvar mins = wks * MINUTES_IN_WEEK\n","minutesInMonth":"var num = minutesInMonth()\nnum = minutesInMonth( 2 )\nnum = minutesInMonth( 2, 2016 )\nnum = minutesInMonth( 2, 2017 )\nnum = minutesInMonth( 'feb', 2016 )\nnum = minutesInMonth( 'february', 2016 )\n","minutesInYear":"var num = minutesInYear()\nnum = minutesInYear( 2016 )\nnum = minutesInYear( 2017 )\n","MOBY_DICK":"var data = MOBY_DICK()\n","MONTH_NAMES_EN":"var list = MONTH_NAMES_EN()\n","MONTHS_IN_YEAR":"var yrs = 3.14;\nvar mons = yrs * MONTHS_IN_YEAR\n","moveProperty":"var obj1 = { 'a': 'b' };\nvar obj2 = {};\nvar bool = moveProperty( obj1, 'a', obj2 )\nbool = moveProperty( obj1, 'c', obj2 )\n","MultiSlice":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\n","MultiSlice.prototype.ndims":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.ndims\n","MultiSlice.prototype.data":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.data\n","MultiSlice.prototype.toString":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.toString()\n","MultiSlice.prototype.toJSON":"var s = new Slice( 2, 10, 1 );\nvar ms = new MultiSlice( 2, s );\nms.toJSON()\n","namedtypedtuple":"var opts = {};\nopts.name = 'Point';\nvar factory = namedtypedtuple( [ 'x', 'y' ], opts );\nvar tuple = factory();\n","NAN":"NAN\n","naryFunction":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = naryFunction( foo, 2 );\nvar out = bar( 1, 2, 3 )\n","nativeClass":"var str = nativeClass( 'a' )\nstr = nativeClass( 5 )\nfunction Beep(){};\nstr = nativeClass( new Beep() )\n","ndarray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","ndarray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","ndarray2array":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2array( arr )\n","ndarray2fancy":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar arr = ndarray2fancy( x );\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray2fancy.factory":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar f = ndarray2fancy.factory();\nvar y = f( x );\n","ndarray2fancy.idx":"var opts = { 'dtype': 'int32' };\nvar buf = new Int32Array( [ 1, 2, 3, 4 ] );\nvar arr = array( buf, opts );\nvar idx = ndarray2fancy.idx( arr );\n","ndarray2json":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2json( arr )\n","ndarrayCastingModes":"var out = ndarrayCastingModes()\n","ndarrayDataBuffer":"var opts = { 'dtype': 'float64' };\nvar out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataType":"var opts = { 'dtype': 'float64' };\nvar dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataTypes":"var out = ndarrayDataTypes()\nout = ndarrayDataTypes( 'floating_point' )\nout = ndarrayDataTypes( 'floating_point_and_generic' )\n","ndarrayDataTypes.binary":"var dt = ndarrayDataTypes.binary\n","ndarrayDataTypes.boolean":"var dt = ndarrayDataTypes.boolean\n","ndarrayDataTypes.complex32":"var dt = ndarrayDataTypes.complex32\n","ndarrayDataTypes.complex64":"var dt = ndarrayDataTypes.complex64\n","ndarrayDataTypes.complex128":"var dt = ndarrayDataTypes.complex128\n","ndarrayDataTypes.float16":"var dt = ndarrayDataTypes.float16\n","ndarrayDataTypes.float32":"var dt = ndarrayDataTypes.float32\n","ndarrayDataTypes.float64":"var dt = ndarrayDataTypes.float64\n","ndarrayDataTypes.generic":"var dt = ndarrayDataTypes.generic\n","ndarrayDataTypes.int8":"var dt = ndarrayDataTypes.int8\n","ndarrayDataTypes.int16":"var dt = ndarrayDataTypes.int16\n","ndarrayDataTypes.int32":"var dt = ndarrayDataTypes.int32\n","ndarrayDataTypes.uint8":"var dt = ndarrayDataTypes.uint8\n","ndarrayDataTypes.uint8c":"var dt = ndarrayDataTypes.uint8c\n","ndarrayDataTypes.uint16":"var dt = ndarrayDataTypes.uint16\n","ndarrayDataTypes.uint32":"var dt = ndarrayDataTypes.uint32\n","ndarrayDispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\nvar xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\nf( x, y );\nybuf\n","ndarrayFlag":"var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n","ndarrayFlags":"var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayIndexModes":"var out = ndarrayIndexModes()\n","ndarraylike2ndarray":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarraylike2ndarray( arr )\n","ndarrayMinDataType":"var dt = ndarrayMinDataType( 3.141592653589793 )\ndt = ndarrayMinDataType( 3 )\ndt = ndarrayMinDataType( -3 )\ndt = ndarrayMinDataType( '-3' )\n","ndarrayMostlySafeCasts":"var out = ndarrayMostlySafeCasts( 'float32' )\n","ndarrayNextDataType":"var out = ndarrayNextDataType( 'float32' )\n","ndarrayOffset":"var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayOrder":"var opts = { 'order': 'row-major' };\nvar dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayOrders":"var out = ndarrayOrders()\n","ndarrayPromotionRules":"var out = ndarrayPromotionRules( 'float32', 'int32' )\n","ndarraySafeCasts":"var out = ndarraySafeCasts( 'float32' )\n","ndarraySameKindCasts":"var out = ndarraySameKindCasts( 'float32' )\n","ndarrayShape":"var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayStride":"var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n","ndarrayStrides":"var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n","ndat":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nndat( x, 0, 1 )\nndat( x, 1, 0 )\n","ndempty":"var arr = ndempty( [ 2, 2 ] )\n","ndemptyLike":"var x = ndzeros( [ 2, 2 ] )\nvar y = ndemptyLike( x )\n","ndfill":"var opts = { 'dtype': 'float64' };\nvar x = ndzeros( [ 2, 2 ], opts );\nx.get( 0, 0 )\nndfill( x, 10.0 );\nx.get( 0, 0 )\n","ndfillBy":"var opts = { 'dtype': 'float64' };\nvar x = ndzeros( [ 2, 2 ], opts );\nx.get( 0, 0 )\nfunction fcn() { return 10.0; };\nndfillBy( x, fcn );\nx.get( 0, 0 )\nx.get( 0, 1 )\nx.get( 1, 0 )\nx.get( 1, 1 )\n","ndfilter":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v > 2.0; };\nvar y = ndfilter( x, f )\n","ndfilterMap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\nvar y = ndfilterMap( x, f )\n","ndforEach":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\nndforEach( x, f );\n","ndims":"var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n","ndindex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\n","ndindex.free":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.free( idx.id )\n","ndindex.get":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.get( idx.id )\n","ndindex.cartesianIndex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = ndindex.cartesianIndex( x );\n","ndindex.linearIndex":"var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\nvar idx = ndindex.linearIndex( x );\n","ndindex.prototype.data":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.data\n","ndindex.prototype.dtype":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.dtype\n","ndindex.prototype.id":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.id\n","ndindex.prototype.isCached":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.isCached\n","ndindex.prototype.kind":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x, { 'kind': 'cartesian' } );\nidx.kind\n","ndindex.prototype.type":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.type\n","ndindex.prototype.toString":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toString()\n","ndindex.prototype.toJSON":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toJSON()\n","nditer2arrayEach":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditer2arrayEach( nditerRows( x ) );\nvar v = it.next().value\nv = it.next().value\n","nditerColumnEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumnEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerColumns":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumns( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerEntries( x );\nvar v = it.next().value\nv = it.next().value\n","nditerIndices":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerIndices( x.shape );\nvar v = it.next().value\nv = it.next().value\n","nditerInterleaveSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerInterleaveSubarrays( [ x, x ], 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrices":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrices( x );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrixEntries":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrixEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRowEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRowEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRows":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRows( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerSelectDimension":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSelectDimension( x, 0 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerStacks":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerStacks( x, [ 1, 2 ] );\nvar v = it.next().value;\nndarray2array( v )\n","nditerSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSubarrays( x, 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerValues":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerValues( x );\nvar v = it.next().value\nv = it.next().value\n","ndmap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v*10.0; };\nvar y = ndmap( x, f )\n","ndreject":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v <= 2.0; };\nvar y = ndreject( x, f );\nndarray2array( y )\n","ndslice":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar s = new MultiSlice( null, 1 )\nvar y = ndslice( x, s )\ny.shape\nndarray2array( y )\n","ndsliceAssign":"var y = ndzeros( [ 2, 2 ] )\nvar x = scalar2ndarray( 3.0 )\nvar s = new MultiSlice( null, 1 )\nvar out = ndsliceAssign( x, y, s )\nvar bool = ( out === y )\nndarray2array( y )\n","ndsliceDimension":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimension( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionFrom( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceFrom( x, 0, 1 )\ny.shape\nndarray2array( y )\n","ndsliceTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndzeros":"var arr = ndzeros( [ 2, 2 ] )\n","ndzerosLike":"var x = ndzeros( [ 2, 2 ] )\nvar y = ndzerosLike( x )\n","nextGraphemeClusterBreak":"var out = nextGraphemeClusterBreak( 'last man standing', 4 )\nout = nextGraphemeClusterBreak( 'presidential election', 8 )\nout = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\nout = nextGraphemeClusterBreak( '🌷' )\n","nextTick":"function f() { console.log( 'beep' ); };\nnextTick( f )\n","NIGHTINGALES_ROSE":"var data = NIGHTINGALES_ROSE()\n","NINF":"NINF\n","NODE_VERSION":"NODE_VERSION\n","none":"var arr = [ 0, 0, 0, 0, 0 ];\nvar bool = none( arr )\n","noneBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = noneBy( arr, negative )\n","noneByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n","noneByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","noneByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ -1, -2, -3, -4 ];\nvar bool = noneByRight( arr, positive )\n","noneByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n","noneByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","noneInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 4 };\nvar bool = noneInBy( obj, negative )\n","nonEnumerableProperties":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar props = nonEnumerableProperties( obj )\n","nonEnumerablePropertiesIn":"var props = nonEnumerablePropertiesIn( [] )\n","nonEnumerablePropertyNames":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNames( obj )\n","nonEnumerablePropertyNamesIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNamesIn( obj )\n","nonEnumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbols( obj )\n","nonEnumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbolsIn( obj )\n","noneOwnBy":"function isUnderage( v ) { return ( v < 18 ); };\nvar obj = { 'a': 11, 'b': 12, 'c': 22 };\nvar bool = noneOwnBy( obj, isUnderage )\n","nonIndexKeys":"function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = nonIndexKeys( obj )\n","noop":"noop();\n","now":"var ts = now()\n","NUM_CPUS":"NUM_CPUS\n","num2words":"var out = num2words( 123 )\nout = num2words( 16.31 )\nout = num2words( 123, { 'lang': 'de' } )\n","Number":"var v = new Number( 5 )\n","numel":"var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n","numelDimension":"var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n","numGraphemeClusters":"var out = numGraphemeClusters( 'beep' )\nout = numGraphemeClusters( '🌷' )\n","Object":"var o = new Object( null )\no = new Object( 5.0 )\no = new Object( 'beep' )\n","Object.assign":"var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n","Object.create":"var o = Object.create( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperties":"var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperty":"var o = Object.defineProperty( {}, 'a', {\n","Object.entries":"var o = Object.entries( { 'a': 1, 'b': 2 } )\n","Object.freeze":"var o = Object.freeze( { 'a': 1 } )\n","Object.getOwnPropertyDescriptor":"var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n","Object.getOwnPropertyDescriptors":"var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertyNames":"var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertySymbols":"var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n","Object.getPrototypeOf":"var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n","Object.hasOwn":"var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n","Object.is":"var o = Object.is( 1, 1 )\nvar o = Object.is( 1, '1' )\n","Object.isExtensible":"var o = Object.isExtensible( { 'a': 1 } )\n","Object.isFrozen":"var o = Object.isFrozen( { 'a': 1 } )\nvar o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n","Object.isSealed":"var o = Object.isSealed( { 'a': 1 } )\nvar o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n","Object.keys":"var o = Object.keys( { 'a': 1, 'b': 2 } )\n","Object.preventExtensions":"var o = Object.preventExtensions( { 'a': 1 } )\no.b = 2;\no\n","Object.seal":"var o = Object.seal( { 'a': 1 } )\no.b = 2;\no\ndelete o.a;\no\n","Object.setPrototypeOf":"var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\no.b\n","Object.values":"var o = Object.values( { 'a': 1, 'b': 2 } )\n","Object.prototype.toLocaleString":"var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.toString":"var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.valueOf":"var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.hasOwnProperty":"var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n","Object.prototype.isPrototypeOf":"var p = { 'a': 1 };\nvar o = { '__proto__': p };\nvar b = o.isPrototypeOf( p );\n","Object.prototype.propertyIsEnumerable":"var o = { 'a': 1, 'b': 2 };\nvar bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n","Object.prototype.constructor":"var o = new Object( null );\nvar ctr = o.constructor;\n","objectEntries":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar entries = objectEntries( obj )\n","objectEntriesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar entries = objectEntriesIn( obj )\n","objectFromEntries":"var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\nvar obj = objectFromEntries( entries )\n","objectInverse":"var obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverse( obj )\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverse( obj )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverse( obj, { 'duplicates': false } )\n","objectInverseBy":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverseBy( obj, transform )\nfunction transform( key, value ) { return value; };\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverseBy( obj, transform )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverseBy( obj, { 'duplicates': false }, transform )\n","objectKeys":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = objectKeys( obj )\n","objectValues":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar vals = objectValues( obj )\n","objectValuesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar values = objectValuesIn( obj )\n","omit":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omit( obj1, 'b' )\n","omitBy":"function predicate( key, value ) { return ( value > 1 ); };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omitBy( obj1, predicate )\n","open":"function onOpen( error, fd ) {\n if ( error ) {\n console.error( error.message );\n } else {\n close.sync( fd );\n }\n };\nopen( './beep/boop.txt', onOpen );\n","open.sync":"var fd = open.sync( './beep/boop.txt' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","openURL":"var out = openURL( 'https://google.com' );\n","ordinalize":"var out = ordinalize( '1' )\nout = ordinalize( 2, { 'suffixOnly': true } )\nout = ordinalize( '3', { 'lang': 'es' } )\n","PACE_BOSTON_HOUSE_PRICES":"var data = PACE_BOSTON_HOUSE_PRICES()\n","pad":"var out = pad( 'a', 5 )\nout = pad( 'a', 10, { 'lpad': 'b' } )\nout = pad( 'a', 12, { 'rpad': 'b' } )\nvar opts = { 'lpad': 'a', 'rpad': 'c' };\nout = pad( 'b', 11, opts )\nopts.centerRight = false;\nout = pad( 'b', 10, opts )\nopts.centerRight = true;\nout = pad( 'b', 10, opts )\nopts = { 'lpad': 'boop', 'rpad': 'woot' };\nout = pad( 'beep', 10, opts )\nout = pad( 'beep', 2 )\nopts = { 'lpad': 'b' };\nout = pad( 'beep', 2, opts )\nopts = { 'lpad': '@', 'rpad': '!' };\nout = pad( 'beep', 2, opts )\nout = pad( 'abcdef', 3, opts )\nopts.centerRight = true;\nout = pad( 'abcdef', 3, opts )\n","padjust":"var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\nvar out = padjust( pvalues, 'bh' )\nout = padjust( pvalues, 'bonferroni' )\nout = padjust( pvalues, 'by' )\nout = padjust( pvalues, 'holm' )\nout = padjust( pvalues, 'hommel' )\n","papply":"function add( x, y ) { return x + y; };\nvar add2 = papply( add, 2 );\nvar sum = add2( 3 )\n","papplyRight":"function say( text, name ) { return text + ', ' + name + '.'; };\nvar toGrace = papplyRight( say, 'Grace Hopper' );\nvar str = toGrace( 'Hello' )\nstr = toGrace( 'Thank you' )\n","parseJSON":"var obj = parseJSON( '{\"beep\":\"boop\"}' )\nfunction reviver( key, value ) {\n if ( key === '' ) { return value; }\n if ( key === 'beep' ) { return value; }\n };\nvar str = '{\"beep\":\"boop\",\"a\":\"b\"}';\nvar out = parseJSON( str, reviver )\n","pascalcase":"var out = pascalcase( 'Hello World!' )\nout = pascalcase( 'beep boop' )\n","PATH_DELIMITER":"PATH_DELIMITER\nvar path = '/usr/bin:/bin:/usr/sbin';\nvar parts = path.split( PATH_DELIMITER )\npath = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\nparts = path.split( PATH_DELIMITER )\n","PATH_DELIMITER_POSIX":"PATH_DELIMITER_POSIX\nvar PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\nvar paths = PATH.split( PATH_DELIMITER_POSIX )\n","PATH_DELIMITER_WIN32":"PATH_DELIMITER_WIN32\nvar PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\nvar paths = PATH.split( PATH_DELIMITER_WIN32 )\n","PATH_SEP":"PATH_SEP\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\nparts = 'foo/bar/baz'.split( PATH_SEP )\n","PATH_SEP_POSIX":"PATH_SEP_POSIX\nvar parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n","PATH_SEP_WIN32":"PATH_SEP_WIN32\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n","pcorrtest":"var rho = 0.5;\nvar x = new Array( 300 );\nvar y = new Array( 300 );\nfor ( var i = 0; i < 300; i++ ) {\nx[ i ] = base.random.normal( 0.0, 1.0 );\ny[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\nbase.sqrt( 1.0 - (rho*rho) ) );\n }\nvar out = pcorrtest( x, y )\nvar table = out.print()\n","percentEncode":"var out = percentEncode( '☃' )\n","PHI":"PHI\n","PI":"PI\n","PI_SQUARED":"PI_SQUARED\n","pick":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pick( obj1, 'b' )\n","pickArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = pickArguments( foo, [ 0, 2 ] );\nvar out = bar( 1, 2, 3 )\n","pickBy":"function predicate( key, value ) {\n return ( value > 1 );\n };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pickBy( obj1, predicate )\n","PINF":"PINF\n","pkg2alias":"var v = pkg2alias( '@stdlib/math/base/special/sin' )\nv = pkg2alias( '@stdlib/math-base-special-sin' )\n","pkg2related":"var v = pkg2related( '@stdlib/math/base/special/sin' )\nv = pkg2related( '@stdlib/math-base-special-sin' )\n","pkg2standalone":"var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n","PLATFORM":"PLATFORM\n","plot":"var plot = plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n","Plot":"var plot = Plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n","pluck":"var arr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nvar out = pluck( arr, 'a' )\narr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nout = pluck( arr, 'a', { 'copy': false } )\nvar bool = ( arr[ 0 ] === out[ 0 ] )\n","pop":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = pop( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = pop( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = pop( arr )\n","porterStemmer":"var out = porterStemmer( 'walking' )\nout = porterStemmer( 'walked' )\nout = porterStemmer( 'walks' )\nout = porterStemmer( '' )\n","prepend":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = prepend( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = prepend( arr, [ 3.0, 4.0 ] )\narr = { 'length': 1, '0': 1.0 };\narr = prepend( arr, [ 2.0, 3.0 ] )\n","prevGraphemeClusterBreak":"var out = prevGraphemeClusterBreak( 'last man standing', 4 )\nout = prevGraphemeClusterBreak( 'presidential election', 8 )\nout = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\nout = prevGraphemeClusterBreak( '🌷', 1 )\n","PRIMES_100K":"var list = PRIMES_100K()\n","properties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = properties( obj )\n","propertiesIn":"var props = propertiesIn( [] )\n","propertyDescriptor":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptor( obj, 'a' )\n","propertyDescriptorIn":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptorIn( obj, 'a' )\n","propertyDescriptors":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptors( obj )\n","propertyDescriptorsIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = propertyDescriptorsIn( obj )\n","propertyNames":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNames( obj )\n","propertyNamesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNamesIn( obj )\n","propertySymbols":"var s = propertySymbols( {} )\n","propertySymbolsIn":"var s = propertySymbolsIn( [] )\n","Proxy":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = new Proxy( {}, h );\np.a = 3.14;\np.a\n","Proxy.revocable":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = Proxy.revocable( {}, h );\np.proxy.a = 3.14;\np.proxy.a\np.revoke();\n","push":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = push( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = push( arr, 3.0, 4.0 )\narr = { 'length': 0 };\narr = push( arr, 1.0, 2.0 )\n","quarterOfYear":"var q = quarterOfYear( new Date() )\nq = quarterOfYear( 4 )\nq = quarterOfYear( 'June' )\nq = quarterOfYear( 'April' )\nq = quarterOfYear( 'apr' )\n","random.array.arcsine":"var out = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.arcsine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.arcsine.factory":"var fcn = random.array.arcsine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.arcsine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.arcsine.PRNG":"var prng = random.array.arcsine.PRNG;\n","random.array.arcsine.seed":"var seed = random.array.arcsine.seed;\n","random.array.arcsine.seedLength":"var len = random.array.arcsine.seedLength;\n","random.array.arcsine.state":"var out = random.array.arcsine( 3, 2.0, 5.0 )\nvar state = random.array.arcsine.state\nout = random.array.arcsine( 3, 2.0, 5.0 )\nout = random.array.arcsine( 3, 2.0, 5.0 )\nrandom.array.arcsine.state = state;\nout = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.stateLength":"var len = random.array.arcsine.stateLength;\n","random.array.arcsine.byteLength":"var sz = random.array.arcsine.byteLength;\n","random.array.bernoulli":"var out = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.bernoulli.assign( 0.5, x )\nvar bool = ( out === x )\n","random.array.bernoulli.factory":"var fcn = random.array.bernoulli.factory();\nvar out = fcn( 3, 0.5 )\nfcn = random.array.bernoulli.factory( 0.5 );\nout = fcn( 3 )\n","random.array.bernoulli.PRNG":"var prng = random.array.bernoulli.PRNG;\n","random.array.bernoulli.seed":"var seed = random.array.bernoulli.seed;\n","random.array.bernoulli.seedLength":"var len = random.array.bernoulli.seedLength;\n","random.array.bernoulli.state":"var out = random.array.bernoulli( 3, 0.5 )\nvar state = random.array.bernoulli.state\nout = random.array.bernoulli( 3, 0.5 )\nout = random.array.bernoulli( 3, 0.5 )\nrandom.array.bernoulli.state = state;\nout = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.stateLength":"var len = random.array.bernoulli.stateLength;\n","random.array.bernoulli.byteLength":"var sz = random.array.bernoulli.byteLength;\n","random.array.beta":"var out = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.beta.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.beta.factory":"var fcn = random.array.beta.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.beta.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.beta.PRNG":"var prng = random.array.beta.PRNG;\n","random.array.beta.seed":"var seed = random.array.beta.seed;\n","random.array.beta.seedLength":"var len = random.array.beta.seedLength;\n","random.array.beta.state":"var out = random.array.beta( 3, 2.0, 5.0 )\nvar state = random.array.beta.state\nout = random.array.beta( 3, 2.0, 5.0 )\nout = random.array.beta( 3, 2.0, 5.0 )\nrandom.array.beta.state = state;\nout = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.stateLength":"var len = random.array.beta.stateLength;\n","random.array.beta.byteLength":"var sz = random.array.beta.byteLength;\n","random.array.betaprime":"var out = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.betaprime.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.betaprime.factory":"var fcn = random.array.betaprime.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.betaprime.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.betaprime.PRNG":"var prng = random.array.betaprime.PRNG;\n","random.array.betaprime.seed":"var seed = random.array.betaprime.seed;\n","random.array.betaprime.seedLength":"var len = random.array.betaprime.seedLength;\n","random.array.betaprime.state":"var out = random.array.betaprime( 3, 2.0, 5.0 )\nvar state = random.array.betaprime.state\nout = random.array.betaprime( 3, 2.0, 5.0 )\nout = random.array.betaprime( 3, 2.0, 5.0 )\nrandom.array.betaprime.state = state;\nout = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.stateLength":"var len = random.array.betaprime.stateLength;\n","random.array.betaprime.byteLength":"var sz = random.array.betaprime.byteLength;\n","random.array.binomial":"var out = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.binomial.assign( 17, 0.5, x )\nvar bool = ( out === x )\n","random.array.binomial.factory":"var fcn = random.array.binomial.factory();\nvar out = fcn( 3, 17, 0.5 )\nfcn = random.array.binomial.factory( 17, 0.5 );\nout = fcn( 3 )\n","random.array.binomial.PRNG":"var prng = random.array.binomial.PRNG;\n","random.array.binomial.seed":"var seed = random.array.binomial.seed;\n","random.array.binomial.seedLength":"var len = random.array.binomial.seedLength;\n","random.array.binomial.state":"var out = random.array.binomial( 3, 17, 0.5 )\nvar state = random.array.binomial.state\nout = random.array.binomial( 3, 17, 0.5 )\nout = random.array.binomial( 3, 17, 0.5 )\nrandom.array.binomial.state = state;\nout = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.stateLength":"var len = random.array.binomial.stateLength;\n","random.array.binomial.byteLength":"var sz = random.array.binomial.byteLength;\n","random.array.cauchy":"var out = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cauchy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cauchy.factory":"var fcn = random.array.cauchy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cauchy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cauchy.PRNG":"var prng = random.array.cauchy.PRNG;\n","random.array.cauchy.seed":"var seed = random.array.cauchy.seed;\n","random.array.cauchy.seedLength":"var len = random.array.cauchy.seedLength;\n","random.array.cauchy.state":"var out = random.array.cauchy( 3, 2.0, 5.0 )\nvar state = random.array.cauchy.state\nout = random.array.cauchy( 3, 2.0, 5.0 )\nout = random.array.cauchy( 3, 2.0, 5.0 )\nrandom.array.cauchy.state = state;\nout = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.stateLength":"var len = random.array.cauchy.stateLength;\n","random.array.cauchy.byteLength":"var sz = random.array.cauchy.byteLength;\n","random.array.chi":"var out = random.array.chi( 3, 2.0 )\n","random.array.chi.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chi.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chi.factory":"var fcn = random.array.chi.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chi.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chi.PRNG":"var prng = random.array.chi.PRNG;\n","random.array.chi.seed":"var seed = random.array.chi.seed;\n","random.array.chi.seedLength":"var len = random.array.chi.seedLength;\n","random.array.chi.state":"var out = random.array.chi( 3, 2.0 )\nvar state = random.array.chi.state\nout = random.array.chi( 3, 2.0 )\nout = random.array.chi( 3, 2.0 )\nrandom.array.chi.state = state;\nout = random.array.chi( 3, 2.0 )\n","random.array.chi.stateLength":"var len = random.array.chi.stateLength;\n","random.array.chi.byteLength":"var sz = random.array.chi.byteLength;\n","random.array.chisquare":"var out = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chisquare.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chisquare.factory":"var fcn = random.array.chisquare.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chisquare.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chisquare.PRNG":"var prng = random.array.chisquare.PRNG;\n","random.array.chisquare.seed":"var seed = random.array.chisquare.seed;\n","random.array.chisquare.seedLength":"var len = random.array.chisquare.seedLength;\n","random.array.chisquare.state":"var out = random.array.chisquare( 3, 2.0 )\nvar state = random.array.chisquare.state\nout = random.array.chisquare( 3, 2.0 )\nout = random.array.chisquare( 3, 2.0 )\nrandom.array.chisquare.state = state;\nout = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.stateLength":"var len = random.array.chisquare.stateLength;\n","random.array.chisquare.byteLength":"var sz = random.array.chisquare.byteLength;\n","random.array.cosine":"var out = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cosine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cosine.factory":"var fcn = random.array.cosine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cosine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cosine.PRNG":"var prng = random.array.cosine.PRNG;\n","random.array.cosine.seed":"var seed = random.array.cosine.seed;\n","random.array.cosine.seedLength":"var len = random.array.cosine.seedLength;\n","random.array.cosine.state":"var out = random.array.cosine( 3, 2.0, 5.0 )\nvar state = random.array.cosine.state\nout = random.array.cosine( 3, 2.0, 5.0 )\nout = random.array.cosine( 3, 2.0, 5.0 )\nrandom.array.cosine.state = state;\nout = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.stateLength":"var len = random.array.cosine.stateLength;\n","random.array.cosine.byteLength":"var sz = random.array.cosine.byteLength;\n","random.array.discreteUniform":"var out = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.discreteUniform.assign( -10, 10, x )\nvar bool = ( out === x )\n","random.array.discreteUniform.factory":"var fcn = random.array.discreteUniform.factory();\nvar out = fcn( 3, -10, 10 )\nfcn = random.array.discreteUniform.factory( -10, 10 );\nout = fcn( 3 )\n","random.array.discreteUniform.PRNG":"var prng = random.array.discreteUniform.PRNG;\n","random.array.discreteUniform.seed":"var seed = random.array.discreteUniform.seed;\n","random.array.discreteUniform.seedLength":"var len = random.array.discreteUniform.seedLength;\n","random.array.discreteUniform.state":"var out = random.array.discreteUniform( 3, -10, 10 )\nvar state = random.array.discreteUniform.state\nout = random.array.discreteUniform( 3, -10, 10 )\nout = random.array.discreteUniform( 3, -10, 10 )\nrandom.array.discreteUniform.state = state;\nout = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.stateLength":"var len = random.array.discreteUniform.stateLength;\n","random.array.discreteUniform.byteLength":"var sz = random.array.discreteUniform.byteLength;\n","random.array.erlang":"var out = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.erlang.assign( 2, 5.0, x )\nvar bool = ( out === x )\n","random.array.erlang.factory":"var fcn = random.array.erlang.factory();\nvar out = fcn( 3, 2, 5.0 )\nfcn = random.array.erlang.factory( 2, 5.0 );\nout = fcn( 3 )\n","random.array.erlang.PRNG":"var prng = random.array.erlang.PRNG;\n","random.array.erlang.seed":"var seed = random.array.erlang.seed;\n","random.array.erlang.seedLength":"var len = random.array.erlang.seedLength;\n","random.array.erlang.state":"var out = random.array.erlang( 3, 2, 5.0 )\nvar state = random.array.erlang.state\nout = random.array.erlang( 3, 2, 5.0 )\nout = random.array.erlang( 3, 2, 5.0 )\nrandom.array.erlang.state = state;\nout = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.stateLength":"var len = random.array.erlang.stateLength;\n","random.array.erlang.byteLength":"var sz = random.array.erlang.byteLength;\n","random.array.exponential":"var out = random.array.exponential( 3, 2.0 )\n","random.array.exponential.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.exponential.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.exponential.factory":"var fcn = random.array.exponential.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.exponential.factory( 2.0 );\nout = fcn( 3 )\n","random.array.exponential.PRNG":"var prng = random.array.exponential.PRNG;\n","random.array.exponential.seed":"var seed = random.array.exponential.seed;\n","random.array.exponential.seedLength":"var len = random.array.exponential.seedLength;\n","random.array.exponential.state":"var out = random.array.exponential( 3, 2.0 )\nvar state = random.array.exponential.state\nout = random.array.exponential( 3, 2.0 )\nout = random.array.exponential( 3, 2.0 )\nrandom.array.exponential.state = state;\nout = random.array.exponential( 3, 2.0 )\n","random.array.exponential.stateLength":"var len = random.array.exponential.stateLength;\n","random.array.exponential.byteLength":"var sz = random.array.exponential.byteLength;\n","random.array.f":"var out = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.f.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.f.factory":"var fcn = random.array.f.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.f.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.f.PRNG":"var prng = random.array.f.PRNG;\n","random.array.f.seed":"var seed = random.array.f.seed;\n","random.array.f.seedLength":"var len = random.array.f.seedLength;\n","random.array.f.state":"var out = random.array.f( 3, 2.0, 5.0 )\nvar state = random.array.f.state\nout = random.array.f( 3, 2.0, 5.0 )\nout = random.array.f( 3, 2.0, 5.0 )\nrandom.array.f.state = state;\nout = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.stateLength":"var len = random.array.f.stateLength;\n","random.array.f.byteLength":"var sz = random.array.f.byteLength;\n","random.array.frechet":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.frechet.factory":"var fcn = random.array.frechet.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.frechet.PRNG":"var prng = random.array.frechet.PRNG;\n","random.array.frechet.seed":"var seed = random.array.frechet.seed;\n","random.array.frechet.seedLength":"var len = random.array.frechet.seedLength;\n","random.array.frechet.state":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.frechet.state\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nrandom.array.frechet.state = state;\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.stateLength":"var len = random.array.frechet.stateLength;\n","random.array.frechet.byteLength":"var sz = random.array.frechet.byteLength;\n","random.array.gamma":"var out = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gamma.factory":"var fcn = random.array.gamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gamma.PRNG":"var prng = random.array.gamma.PRNG;\n","random.array.gamma.seed":"var seed = random.array.gamma.seed;\n","random.array.gamma.seedLength":"var len = random.array.gamma.seedLength;\n","random.array.gamma.state":"var out = random.array.gamma( 3, 2.0, 5.0 )\nvar state = random.array.gamma.state\nout = random.array.gamma( 3, 2.0, 5.0 )\nout = random.array.gamma( 3, 2.0, 5.0 )\nrandom.array.gamma.state = state;\nout = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.stateLength":"var len = random.array.gamma.stateLength;\n","random.array.gamma.byteLength":"var sz = random.array.gamma.byteLength;\n","random.array.geometric":"var out = random.array.geometric( 3, 0.01 )\n","random.array.geometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.geometric.assign( 0.01, x )\nvar bool = ( out === x )\n","random.array.geometric.factory":"var fcn = random.array.geometric.factory();\nvar out = fcn( 3, 0.01 )\nfcn = random.array.geometric.factory( 0.01 );\nout = fcn( 3 )\n","random.array.geometric.PRNG":"var prng = random.array.geometric.PRNG;\n","random.array.geometric.seed":"var seed = random.array.geometric.seed;\n","random.array.geometric.seedLength":"var len = random.array.geometric.seedLength;\n","random.array.geometric.state":"var out = random.array.geometric( 3, 0.01 )\nvar state = random.array.geometric.state\nout = random.array.geometric( 3, 0.01 )\nout = random.array.geometric( 3, 0.01 )\nrandom.array.geometric.state = state;\nout = random.array.geometric( 3, 0.01 )\n","random.array.geometric.stateLength":"var len = random.array.geometric.stateLength;\n","random.array.geometric.byteLength":"var sz = random.array.geometric.byteLength;\n","random.array.gumbel":"var out = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gumbel.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gumbel.factory":"var fcn = random.array.gumbel.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gumbel.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gumbel.PRNG":"var prng = random.array.gumbel.PRNG;\n","random.array.gumbel.seed":"var seed = random.array.gumbel.seed;\n","random.array.gumbel.seedLength":"var len = random.array.gumbel.seedLength;\n","random.array.gumbel.state":"var out = random.array.gumbel( 3, 2.0, 5.0 )\nvar state = random.array.gumbel.state\nout = random.array.gumbel( 3, 2.0, 5.0 )\nout = random.array.gumbel( 3, 2.0, 5.0 )\nrandom.array.gumbel.state = state;\nout = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.stateLength":"var len = random.array.gumbel.stateLength;\n","random.array.gumbel.byteLength":"var sz = random.array.gumbel.byteLength;\n","random.array.hypergeometric":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.hypergeometric.assign( 20, 10, 7, x )\nvar bool = ( out === x )\n","random.array.hypergeometric.factory":"var fcn = random.array.hypergeometric.factory();\nvar out = fcn( 3, 20, 10, 7 )\nfcn = random.array.hypergeometric.factory( 20, 10, 7 );\nout = fcn( 3 )\n","random.array.hypergeometric.PRNG":"var prng = random.array.hypergeometric.PRNG;\n","random.array.hypergeometric.seed":"var seed = random.array.hypergeometric.seed;\n","random.array.hypergeometric.seedLength":"var len = random.array.hypergeometric.seedLength;\n","random.array.hypergeometric.state":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\nvar state = random.array.hypergeometric.state\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nrandom.array.hypergeometric.state = state;\nout = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.stateLength":"var len = random.array.hypergeometric.stateLength;\n","random.array.hypergeometric.byteLength":"var sz = random.array.hypergeometric.byteLength;\n","random.array.invgamma":"var out = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.invgamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.invgamma.factory":"var fcn = random.array.invgamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.invgamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.invgamma.PRNG":"var prng = random.array.invgamma.PRNG;\n","random.array.invgamma.seed":"var seed = random.array.invgamma.seed;\n","random.array.invgamma.seedLength":"var len = random.array.invgamma.seedLength;\n","random.array.invgamma.state":"var out = random.array.invgamma( 3, 2.0, 5.0 )\nvar state = random.array.invgamma.state\nout = random.array.invgamma( 3, 2.0, 5.0 )\nout = random.array.invgamma( 3, 2.0, 5.0 )\nrandom.array.invgamma.state = state;\nout = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.stateLength":"var len = random.array.invgamma.stateLength;\n","random.array.invgamma.byteLength":"var sz = random.array.invgamma.byteLength;\n","random.array.kumaraswamy":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.kumaraswamy.factory":"var fcn = random.array.kumaraswamy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.kumaraswamy.PRNG":"var prng = random.array.kumaraswamy.PRNG;\n","random.array.kumaraswamy.seed":"var seed = random.array.kumaraswamy.seed;\n","random.array.kumaraswamy.seedLength":"var len = random.array.kumaraswamy.seedLength;\n","random.array.kumaraswamy.state":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\nvar state = random.array.kumaraswamy.state\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nrandom.array.kumaraswamy.state = state;\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.stateLength":"var len = random.array.kumaraswamy.stateLength;\n","random.array.kumaraswamy.byteLength":"var sz = random.array.kumaraswamy.byteLength;\n","random.array.laplace":"var out = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.laplace.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.laplace.factory":"var fcn = random.array.laplace.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.laplace.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.laplace.PRNG":"var prng = random.array.laplace.PRNG;\n","random.array.laplace.seed":"var seed = random.array.laplace.seed;\n","random.array.laplace.seedLength":"var len = random.array.laplace.seedLength;\n","random.array.laplace.state":"var out = random.array.laplace( 3, 2.0, 5.0 )\nvar state = random.array.laplace.state\nout = random.array.laplace( 3, 2.0, 5.0 )\nout = random.array.laplace( 3, 2.0, 5.0 )\nrandom.array.laplace.state = state;\nout = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.stateLength":"var len = random.array.laplace.stateLength;\n","random.array.laplace.byteLength":"var sz = random.array.laplace.byteLength;\n","random.array.levy":"var out = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.levy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.levy.factory":"var fcn = random.array.levy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.levy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.levy.PRNG":"var prng = random.array.levy.PRNG;\n","random.array.levy.seed":"var seed = random.array.levy.seed;\n","random.array.levy.seedLength":"var len = random.array.levy.seedLength;\n","random.array.levy.state":"var out = random.array.levy( 3, 2.0, 5.0 )\nvar state = random.array.levy.state\nout = random.array.levy( 3, 2.0, 5.0 )\nout = random.array.levy( 3, 2.0, 5.0 )\nrandom.array.levy.state = state;\nout = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.stateLength":"var len = random.array.levy.stateLength;\n","random.array.levy.byteLength":"var sz = random.array.levy.byteLength;\n","random.array.logistic":"var out = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.logistic.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.logistic.factory":"var fcn = random.array.logistic.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.logistic.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.logistic.PRNG":"var prng = random.array.logistic.PRNG;\n","random.array.logistic.seed":"var seed = random.array.logistic.seed;\n","random.array.logistic.seedLength":"var len = random.array.logistic.seedLength;\n","random.array.logistic.state":"var out = random.array.logistic( 3, 2.0, 5.0 )\nvar state = random.array.logistic.state\nout = random.array.logistic( 3, 2.0, 5.0 )\nout = random.array.logistic( 3, 2.0, 5.0 )\nrandom.array.logistic.state = state;\nout = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.stateLength":"var len = random.array.logistic.stateLength;\n","random.array.logistic.byteLength":"var sz = random.array.logistic.byteLength;\n","random.array.lognormal":"var out = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.lognormal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.lognormal.factory":"var fcn = random.array.lognormal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.lognormal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.lognormal.PRNG":"var prng = random.array.lognormal.PRNG;\n","random.array.lognormal.seed":"var seed = random.array.lognormal.seed;\n","random.array.lognormal.seedLength":"var len = random.array.lognormal.seedLength;\n","random.array.lognormal.state":"var out = random.array.lognormal( 3, 2.0, 5.0 )\nvar state = random.array.lognormal.state\nout = random.array.lognormal( 3, 2.0, 5.0 )\nout = random.array.lognormal( 3, 2.0, 5.0 )\nrandom.array.lognormal.state = state;\nout = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.stateLength":"var len = random.array.lognormal.stateLength;\n","random.array.lognormal.byteLength":"var sz = random.array.lognormal.byteLength;\n","random.array.minstd":"var out = random.array.minstd( 3 )\n","random.array.minstd.normalized":"var out = random.array.minstd.normalized( 3 )\n","random.array.minstd.factory":"var fcn = random.array.minstd.factory();\nvar out = fcn( 3 )\n","random.array.minstd.PRNG":"var prng = random.array.minstd.PRNG;\n","random.array.minstd.seed":"var seed = random.array.minstd.seed;\n","random.array.minstd.seedLength":"var len = random.array.minstd.seedLength;\n","random.array.minstd.state":"var out = random.array.minstd( 3 )\nvar state = random.array.minstd.state;\nout = random.array.minstd( 3 )\nout = random.array.minstd( 3 )\nrandom.array.minstd.state = state;\nout = random.array.minstd( 3 )\n","random.array.minstd.stateLength":"var len = random.array.minstd.stateLength;\n","random.array.minstd.byteLength":"var sz = random.array.minstd.byteLength;\n","random.array.minstdShuffle":"var out = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.normalized":"var out = random.array.minstdShuffle.normalized( 3 )\n","random.array.minstdShuffle.factory":"var fcn = random.array.minstdShuffle.factory();\nvar out = fcn( 3 )\n","random.array.minstdShuffle.PRNG":"var prng = random.array.minstdShuffle.PRNG;\n","random.array.minstdShuffle.seed":"var seed = random.array.minstdShuffle.seed;\n","random.array.minstdShuffle.seedLength":"var len = random.array.minstdShuffle.seedLength;\n","random.array.minstdShuffle.state":"var out = random.array.minstdShuffle( 3 )\nvar state = random.array.minstdShuffle.state;\nout = random.array.minstdShuffle( 3 )\nout = random.array.minstdShuffle( 3 )\nrandom.array.minstdShuffle.state = state;\nout = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.stateLength":"var len = random.array.minstdShuffle.stateLength;\n","random.array.minstdShuffle.byteLength":"var sz = random.array.minstdShuffle.byteLength;\n","random.array.mt19937":"var out = random.array.mt19937( 3 )\n","random.array.mt19937.normalized":"var out = random.array.mt19937.normalized( 3 )\n","random.array.mt19937.factory":"var fcn = random.array.mt19937.factory();\nvar out = fcn( 3 )\n","random.array.mt19937.PRNG":"var prng = random.array.mt19937.PRNG;\n","random.array.mt19937.seed":"var seed = random.array.mt19937.seed;\n","random.array.mt19937.seedLength":"var len = random.array.mt19937.seedLength;\n","random.array.mt19937.state":"var out = random.array.mt19937( 3 )\nvar state = random.array.mt19937.state;\nout = random.array.mt19937( 3 )\nout = random.array.mt19937( 3 )\nrandom.array.mt19937.state = state;\nout = random.array.mt19937( 3 )\n","random.array.mt19937.stateLength":"var len = random.array.mt19937.stateLength;\n","random.array.mt19937.byteLength":"var sz = random.array.mt19937.byteLength;\n","random.array.negativeBinomial":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.negativeBinomial.assign( 10, 0.5, x )\nvar bool = ( out === x )\n","random.array.negativeBinomial.factory":"var fcn = random.array.negativeBinomial.factory();\nvar out = fcn( 3, 10, 0.5 )\nfcn = random.array.negativeBinomial.factory( 10, 0.5 );\nout = fcn( 3 )\n","random.array.negativeBinomial.PRNG":"var prng = random.array.negativeBinomial.PRNG;\n","random.array.negativeBinomial.seed":"var seed = random.array.negativeBinomial.seed;\n","random.array.negativeBinomial.seedLength":"var len = random.array.negativeBinomial.seedLength;\n","random.array.negativeBinomial.state":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\nvar state = random.array.negativeBinomial.state\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nrandom.array.negativeBinomial.state = state;\nout = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.stateLength":"var len = random.array.negativeBinomial.stateLength;\n","random.array.negativeBinomial.byteLength":"var sz = random.array.negativeBinomial.byteLength;\n","random.array.normal":"var out = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.normal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.normal.factory":"var fcn = random.array.normal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.normal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.normal.PRNG":"var prng = random.array.normal.PRNG;\n","random.array.normal.seed":"var seed = random.array.normal.seed;\n","random.array.normal.seedLength":"var len = random.array.normal.seedLength;\n","random.array.normal.state":"var out = random.array.normal( 3, 2.0, 5.0 )\nvar state = random.array.normal.state\nout = random.array.normal( 3, 2.0, 5.0 )\nout = random.array.normal( 3, 2.0, 5.0 )\nrandom.array.normal.state = state;\nout = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.stateLength":"var len = random.array.normal.stateLength;\n","random.array.normal.byteLength":"var sz = random.array.normal.byteLength;\n","random.array.pareto1":"var out = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.pareto1.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.pareto1.factory":"var fcn = random.array.pareto1.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.pareto1.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.pareto1.PRNG":"var prng = random.array.pareto1.PRNG;\n","random.array.pareto1.seed":"var seed = random.array.pareto1.seed;\n","random.array.pareto1.seedLength":"var len = random.array.pareto1.seedLength;\n","random.array.pareto1.state":"var out = random.array.pareto1( 3, 2.0, 5.0 )\nvar state = random.array.pareto1.state\nout = random.array.pareto1( 3, 2.0, 5.0 )\nout = random.array.pareto1( 3, 2.0, 5.0 )\nrandom.array.pareto1.state = state;\nout = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.stateLength":"var len = random.array.pareto1.stateLength;\n","random.array.pareto1.byteLength":"var sz = random.array.pareto1.byteLength;\n","random.array.poisson":"var out = random.array.poisson( 3, 2.0 )\n","random.array.poisson.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.poisson.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.poisson.factory":"var fcn = random.array.poisson.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.poisson.factory( 2.0 );\nout = fcn( 3 )\n","random.array.poisson.PRNG":"var prng = random.array.poisson.PRNG;\n","random.array.poisson.seed":"var seed = random.array.poisson.seed;\n","random.array.poisson.seedLength":"var len = random.array.poisson.seedLength;\n","random.array.poisson.state":"var out = random.array.poisson( 3, 2.0 )\nvar state = random.array.poisson.state\nout = random.array.poisson( 3, 2.0 )\nout = random.array.poisson( 3, 2.0 )\nrandom.array.poisson.state = state;\nout = random.array.poisson( 3, 2.0 )\n","random.array.poisson.stateLength":"var len = random.array.poisson.stateLength;\n","random.array.poisson.byteLength":"var sz = random.array.poisson.byteLength;\n","random.array.randu":"var out = random.array.randu( 3 )\n","random.array.randu.factory":"var fcn = random.array.randu.factory();\nvar out = fcn( 3 )\n","random.array.randu.PRNG":"var prng = random.array.randu.PRNG;\n","random.array.randu.seed":"var seed = random.array.randu.seed;\n","random.array.randu.seedLength":"var len = random.array.randu.seedLength;\n","random.array.randu.state":"var out = random.array.randu( 3 )\nvar state = random.array.randu.state;\nout = random.array.randu( 3 )\nout = random.array.randu( 3 )\nrandom.array.randu.state = state;\nout = random.array.randu( 3 )\n","random.array.randu.stateLength":"var len = random.array.randu.stateLength;\n","random.array.randu.byteLength":"var sz = random.array.randu.byteLength;\n","random.array.rayleigh":"var out = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.rayleigh.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.rayleigh.factory":"var fcn = random.array.rayleigh.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.rayleigh.factory( 2.0 );\nout = fcn( 3 )\n","random.array.rayleigh.PRNG":"var prng = random.array.rayleigh.PRNG;\n","random.array.rayleigh.seed":"var seed = random.array.rayleigh.seed;\n","random.array.rayleigh.seedLength":"var len = random.array.rayleigh.seedLength;\n","random.array.rayleigh.state":"var out = random.array.rayleigh( 3, 2.0 )\nvar state = random.array.rayleigh.state\nout = random.array.rayleigh( 3, 2.0 )\nout = random.array.rayleigh( 3, 2.0 )\nrandom.array.rayleigh.state = state;\nout = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.stateLength":"var len = random.array.rayleigh.stateLength;\n","random.array.rayleigh.byteLength":"var sz = random.array.rayleigh.byteLength;\n","random.array.t":"var out = random.array.t( 3, 2.0 )\n","random.array.t.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.t.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.t.factory":"var fcn = random.array.t.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.t.factory( 2.0 );\nout = fcn( 3 )\n","random.array.t.PRNG":"var prng = random.array.t.PRNG;\n","random.array.t.seed":"var seed = random.array.t.seed;\n","random.array.t.seedLength":"var len = random.array.t.seedLength;\n","random.array.t.state":"var out = random.array.t( 3, 2.0 )\nvar state = random.array.t.state\nout = random.array.t( 3, 2.0 )\nout = random.array.t( 3, 2.0 )\nrandom.array.t.state = state;\nout = random.array.t( 3, 2.0 )\n","random.array.t.stateLength":"var len = random.array.t.stateLength;\n","random.array.t.byteLength":"var sz = random.array.t.byteLength;\n","random.array.triangular":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.triangular.factory":"var fcn = random.array.triangular.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.triangular.PRNG":"var prng = random.array.triangular.PRNG;\n","random.array.triangular.seed":"var seed = random.array.triangular.seed;\n","random.array.triangular.seedLength":"var len = random.array.triangular.seedLength;\n","random.array.triangular.state":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.triangular.state\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nrandom.array.triangular.state = state;\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.stateLength":"var len = random.array.triangular.stateLength;\n","random.array.triangular.byteLength":"var sz = random.array.triangular.byteLength;\n","random.array.uniform":"var out = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.uniform.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.uniform.factory":"var fcn = random.array.uniform.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.uniform.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.uniform.PRNG":"var prng = random.array.uniform.PRNG;\n","random.array.uniform.seed":"var seed = random.array.uniform.seed;\n","random.array.uniform.seedLength":"var len = random.array.uniform.seedLength;\n","random.array.uniform.state":"var out = random.array.uniform( 3, 2.0, 5.0 )\nvar state = random.array.uniform.state\nout = random.array.uniform( 3, 2.0, 5.0 )\nout = random.array.uniform( 3, 2.0, 5.0 )\nrandom.array.uniform.state = state;\nout = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.stateLength":"var len = random.array.uniform.stateLength;\n","random.array.uniform.byteLength":"var sz = random.array.uniform.byteLength;\n","random.array.weibull":"var out = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.weibull.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.weibull.factory":"var fcn = random.array.weibull.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.weibull.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.weibull.PRNG":"var prng = random.array.weibull.PRNG;\n","random.array.weibull.seed":"var seed = random.array.weibull.seed;\n","random.array.weibull.seedLength":"var len = random.array.weibull.seedLength;\n","random.array.weibull.state":"var out = random.array.weibull( 3, 2.0, 5.0 )\nvar state = random.array.weibull.state\nout = random.array.weibull( 3, 2.0, 5.0 )\nout = random.array.weibull( 3, 2.0, 5.0 )\nrandom.array.weibull.state = state;\nout = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.stateLength":"var len = random.array.weibull.stateLength;\n","random.array.weibull.byteLength":"var sz = random.array.weibull.byteLength;\n","random.iterators.arcsine":"var it = random.iterators.arcsine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.bernoulli":"var it = random.iterators.bernoulli( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.beta":"var it = random.iterators.beta( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.betaprime":"var it = random.iterators.betaprime( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.binomial":"var it = random.iterators.binomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.boxMuller":"var it = random.iterators.boxMuller();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cauchy":"var it = random.iterators.cauchy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chi":"var it = random.iterators.chi( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chisquare":"var it = random.iterators.chisquare( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cosine":"var it = random.iterators.cosine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.discreteUniform":"var it = random.iterators.discreteUniform( 0, 3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.erlang":"var it = random.iterators.erlang( 1, 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.exponential":"var it = random.iterators.exponential( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.f":"var it = random.iterators.f( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.frechet":"var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gamma":"var it = random.iterators.gamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.geometric":"var it = random.iterators.geometric( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gumbel":"var it = random.iterators.gumbel( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.hypergeometric":"var it = random.iterators.hypergeometric( 20, 10, 7 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.improvedZiggurat":"var it = random.iterators.improvedZiggurat();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.invgamma":"var it = random.iterators.invgamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.kumaraswamy":"var it = random.iterators.kumaraswamy( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.laplace":"var it = random.iterators.laplace( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.levy":"var it = random.iterators.levy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.logistic":"var it = random.iterators.logistic( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.lognormal":"var it = random.iterators.lognormal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstd":"var it = random.iterators.minstd();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstdShuffle":"var it = random.iterators.minstdShuffle();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.mt19937":"var it = random.iterators.mt19937();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.negativeBinomial":"var it = random.iterators.negativeBinomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.normal":"var it = random.iterators.normal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.pareto1":"var it = random.iterators.pareto1( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.poisson":"var it = random.iterators.poisson( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randi":"var it = random.iterators.randi();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randn":"var it = random.iterators.randn();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randu":"var it = random.iterators.randu();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.rayleigh":"var it = random.iterators.rayleigh( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.t":"var it = random.iterators.t( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.triangular":"var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.uniform":"var it = random.iterators.uniform( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.weibull":"var it = random.iterators.weibull( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.streams.arcsine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.arcsine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.arcsine.factory( opts );\n","random.streams.arcsine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.bernoulli":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.bernoulli.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.bernoulli.factory( opts );\n","random.streams.bernoulli.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.beta":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.beta.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.beta.factory( opts );\n","random.streams.beta.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.betaprime":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.betaprime.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.betaprime.factory( opts );\n","random.streams.betaprime.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.binomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial( 20, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.binomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.binomial.factory( opts );\n","random.streams.binomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial.objectMode( 20, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.boxMuller":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.boxMuller.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.boxMuller.factory( opts );\n","random.streams.boxMuller.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cauchy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cauchy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cauchy.factory( opts );\n","random.streams.cauchy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chi.factory( opts );\n","random.streams.chi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chisquare":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chisquare.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chisquare.factory( opts );\n","random.streams.chisquare.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cosine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cosine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cosine.factory( opts );\n","random.streams.cosine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.discreteUniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform( 2, 5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.discreteUniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.discreteUniform.factory( opts );\n","random.streams.discreteUniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform.objectMode( 2, 5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.erlang":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang( 2, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.erlang.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.erlang.factory( opts );\n","random.streams.erlang.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang.objectMode( 2, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.exponential":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.exponential.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.exponential.factory( opts );\n","random.streams.exponential.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.f":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.f.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.f.factory( opts );\n","random.streams.f.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.frechet":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.frechet.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.frechet.factory( opts );\n","random.streams.frechet.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gamma.factory( opts );\n","random.streams.gamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.geometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.geometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.geometric.factory( opts );\n","random.streams.geometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gumbel":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gumbel.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gumbel.factory( opts );\n","random.streams.gumbel.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.hypergeometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric( 5, 3, 2, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.hypergeometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.hypergeometric.factory( opts );\n","random.streams.hypergeometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.improvedZiggurat.factory( opts );\n","random.streams.improvedZiggurat.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.invgamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.invgamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.invgamma.factory( opts );\n","random.streams.invgamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.kumaraswamy.factory( opts );\n","random.streams.kumaraswamy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.laplace":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.laplace.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.laplace.factory( opts );\n","random.streams.laplace.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.levy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.levy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.levy.factory( opts );\n","random.streams.levy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.logistic":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.logistic.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.logistic.factory( opts );\n","random.streams.logistic.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.lognormal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.lognormal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.lognormal.factory( opts );\n","random.streams.lognormal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstd":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstd.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstd.factory( opts );\n","random.streams.minstd.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstdShuffle.factory( opts );\n","random.streams.minstdShuffle.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.mt19937":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.mt19937.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.mt19937.factory( opts );\n","random.streams.mt19937.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial( 20.0, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.negativeBinomial.factory( opts );\n","random.streams.negativeBinomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.normal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.normal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.normal.factory( opts );\n","random.streams.normal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.pareto1":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.pareto1.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.pareto1.factory( opts );\n","random.streams.pareto1.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.poisson":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.poisson.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.poisson.factory( opts );\n","random.streams.poisson.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randi.factory( opts );\n","random.streams.randi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randn":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randn.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randn.factory( opts );\n","random.streams.randn.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randu":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randu.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randu.factory( opts );\n","random.streams.randu.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.rayleigh":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.rayleigh.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.rayleigh.factory( opts );\n","random.streams.rayleigh.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.t":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.t.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.t.factory( opts );\n","random.streams.t.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.triangular":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.triangular.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.triangular.factory( opts );\n","random.streams.triangular.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.uniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.uniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.uniform.factory( opts );\n","random.streams.uniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.weibull":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.weibull.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.weibull.factory( opts );\n","random.streams.weibull.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.strided.arcsine":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n","random.strided.arcsine.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.bernoulli":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n","random.strided.bernoulli.factory":"var fcn = random.strided.bernoulli.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.PRNG":"var prng = random.strided.bernoulli.PRNG;\n","random.strided.bernoulli.seed":"var seed = random.strided.bernoulli.seed;\n","random.strided.bernoulli.seedLength":"var len = random.strided.bernoulli.seedLength;\n","random.strided.bernoulli.state":"var out = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nvar state = random.strided.bernoulli.state\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nrandom.strided.bernoulli.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.stateLength":"var len = random.strided.bernoulli.stateLength;\n","random.strided.bernoulli.byteLength":"var sz = random.strided.bernoulli.byteLength;\n","random.strided.beta":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta( 3, a, -2, b, 1, out, 1 )\n","random.strided.beta.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.betaprime":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n","random.strided.betaprime.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.chi":"var out = azeros( 5, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chi.factory":"var fcn = random.strided.chi.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.PRNG":"var prng = random.strided.chi.PRNG;\n","random.strided.chi.seed":"var seed = random.strided.chi.seed;\n","random.strided.chi.seedLength":"var len = random.strided.chi.seedLength;\n","random.strided.chi.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chi.state\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chi.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.stateLength":"var len = random.strided.chi.stateLength;\n","random.strided.chi.byteLength":"var sz = random.strided.chi.byteLength;\n","random.strided.chisquare":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chisquare.factory":"var fcn = random.strided.chisquare.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.PRNG":"var prng = random.strided.chisquare.PRNG;\n","random.strided.chisquare.seed":"var seed = random.strided.chisquare.seed;\n","random.strided.chisquare.seedLength":"var len = random.strided.chisquare.seedLength;\n","random.strided.chisquare.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chisquare.state\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chisquare.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.stateLength":"var len = random.strided.chisquare.stateLength;\n","random.strided.chisquare.byteLength":"var sz = random.strided.chisquare.byteLength;\n","random.strided.cosine":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n","random.strided.cosine.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n","random.strided.discreteUniform":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.discreteUniform.ndarray":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.exponential":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.exponential.factory":"var fcn = random.strided.exponential.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.PRNG":"var prng = random.strided.exponential.PRNG;\n","random.strided.exponential.seed":"var seed = random.strided.exponential.seed;\n","random.strided.exponential.seedLength":"var len = random.strided.exponential.seedLength;\n","random.strided.exponential.state":"var out = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.exponential.state\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.exponential.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.stateLength":"var len = random.strided.exponential.stateLength;\n","random.strided.exponential.byteLength":"var sz = random.strided.exponential.byteLength;\n","random.strided.gamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.gamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.geometric":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n","random.strided.geometric.factory":"var fcn = random.strided.geometric.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.PRNG":"var prng = random.strided.geometric.PRNG;\n","random.strided.geometric.seed":"var seed = random.strided.geometric.seed;\n","random.strided.geometric.seedLength":"var len = random.strided.geometric.seedLength;\n","random.strided.geometric.state":"var out = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nvar state = random.strided.geometric.state\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nrandom.strided.geometric.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.stateLength":"var len = random.strided.geometric.stateLength;\n","random.strided.geometric.byteLength":"var sz = random.strided.geometric.byteLength;\n","random.strided.invgamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.invgamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.lognormal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.lognormal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.minstd":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd( out.length, out, 1 )\n","random.strided.minstd.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.ndarray( out.length, out, 1, 0 )\n","random.strided.minstd.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized( out.length, out, 1 )\n","random.strided.minstd.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle( out.length, out, 1 )\n","random.strided.minstdShuffle.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized( out.length, out, 1 )\n","random.strided.minstdShuffle.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937( out.length, out, 1 )\n","random.strided.mt19937.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized( out.length, out, 1 )\n","random.strided.mt19937.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.normal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.normal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.poisson":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.poisson.factory":"var fcn = random.strided.poisson.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.PRNG":"var prng = random.strided.poisson.PRNG;\n","random.strided.poisson.seed":"var seed = random.strided.poisson.seed;\n","random.strided.poisson.seedLength":"var len = random.strided.poisson.seedLength;\n","random.strided.poisson.state":"var out = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.poisson.state\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.poisson.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.stateLength":"var len = random.strided.poisson.stateLength;\n","random.strided.poisson.byteLength":"var sz = random.strided.poisson.byteLength;\n","random.strided.randu":"var out = azeros( 5, 'generic' );\nrandom.strided.randu( out.length, out, 1 )\n","random.strided.randu.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.randu.ndarray( out.length, out, 1, 0 )\n","random.strided.rayleigh":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.rayleigh.factory":"var fcn = random.strided.rayleigh.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.PRNG":"var prng = random.strided.rayleigh.PRNG;\n","random.strided.rayleigh.seed":"var seed = random.strided.rayleigh.seed;\n","random.strided.rayleigh.seedLength":"var len = random.strided.rayleigh.seedLength;\n","random.strided.rayleigh.state":"var out = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.rayleigh.state\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.rayleigh.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.stateLength":"var len = random.strided.rayleigh.stateLength;\n","random.strided.rayleigh.byteLength":"var sz = random.strided.rayleigh.byteLength;\n","random.strided.t":"var out = azeros( 5, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.t.factory":"var fcn = random.strided.t.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.PRNG":"var prng = random.strided.t.PRNG;\n","random.strided.t.seed":"var seed = random.strided.t.seed;\n","random.strided.t.seedLength":"var len = random.strided.t.seedLength;\n","random.strided.t.state":"var out = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.t.state\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.t.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.stateLength":"var len = random.strided.t.stateLength;\n","random.strided.t.byteLength":"var sz = random.strided.t.byteLength;\n","random.strided.uniform":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.uniform.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.weibull":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull( 3, a, -2, b, 1, out, 1 )\n","random.strided.weibull.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","ranks":"var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\nvar out = ranks( arr )\narr = [ 2, 2, 1, 4, 3 ];\nout = ranks( arr )\narr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\nout = ranks( arr )\n","readDir":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadDir( './beep/boop', onRead );\n","readDir.sync":"var out = readDir.sync( './beep/boop' );\n","readFile":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadFile( './beep/boop.js', onRead );\n","readFile.sync":"var out = readFile.sync( './beep/boop.js' );\n","readFileList":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nvar filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nreadFileList( filepaths, onRead );\n","readFileList.sync":"var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nvar out = readFileList.sync( filepaths );\n","readJSON":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadJSON( './beep/boop.json', onRead );\n","readJSON.sync":"var out = readJSON.sync( './beep/boop.json' );\n","readWASM":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadWASM( './beep/boop.wasm', onRead );\n","readWASM.sync":"var out = readWASM.sync( './beep/boop.wasm' );\n","real":"var z = new Complex128( 5.0, 3.0 );\nvar re = real( z )\n","realarray":"var arr = realarray()\narr = realarray( 'float32' )\nvar arr = realarray( 5 )\narr = realarray( 5, 'int32' )\nvar arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = realarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = realarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = realarray( buf, 0, 4, 'float32' )\n","realarrayCtors":"var ctor = realarrayCtors( 'float64' )\nctor = realarrayCtors( 'float' )\n","realarrayDataTypes":"var out = realarrayDataTypes()\n","realf":"var z = new Complex64( 5.0, 3.0 );\nvar re = realf( z )\n","realmax":"var m = realmax( 'float16' )\nm = realmax( 'float32' )\n","realmin":"var m = realmin( 'float16' )\nm = realmin( 'float32' )\n","reBasename":"var RE = reBasename()\nvar RE_POSIX = reBasename( 'posix' );\nvar RE_WIN32 = reBasename( 'win32' );\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reBasename.REGEXP":"var RE = reBasename.REGEXP\n","reBasename.REGEXP_POSIX":"var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reBasename.REGEXP_WIN32":"var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reBasenamePosix":"var RE_BASENAME_POSIX = reBasenamePosix();\nvar base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n","reBasenamePosix.REGEXP":"var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n","reBasenameWindows":"var RE_BASENAME_WINDOWS = reBasenameWindows();\nvar base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n","reBasenameWindows.REGEXP":"var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n","reColorHexadecimal":"var RE = reColorHexadecimal();\nvar bool = RE.test( 'ffffff' )\nbool = RE.test( '000' )\nbool = RE.test( 'beep' )\n","reColorHexadecimal.REGEXP":"var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP.test( '000' )\nbool = reColorHexadecimal.REGEXP.test( 'beep' )\n","reColorHexadecimal.REGEXP_SHORTHAND":"var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n","reColorHexadecimal.REGEXP_EITHER":"var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n","reDecimalNumber":"var RE = reDecimalNumber();\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\nbool = RE.test( '0.0' )\nbool = RE.test( '.0' )\nbool = RE.test( '0' )\nbool = RE.test( 'beep' )\nvar re = reDecimalNumber({ 'flags': 'g' });\nvar str = '1.234 5.6, 7.8';\nvar out = str.match( re )\n","reDecimalNumber.REGEXP":"var RE = reDecimalNumber.REGEXP;\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\n","reDecimalNumber.REGEXP_CAPTURE":"var RE = reDecimalNumber.REGEXP_CAPTURE;\nvar str = '1.02';\nvar out = replace( str, RE, '$1 x $1' )\n","reDirname":"var RE = reDirname()\nvar RE_POSIX = reDirname( 'posix' );\nvar dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reDirname( 'win32' );\ndir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reDirname.REGEXP":"var RE = reDirname.REGEXP\n","reDirname.REGEXP_POSIX":"var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirname.REGEXP_WIN32":"var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reDirnamePosix":"var RE = reDirnamePosix();\nvar dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\ndir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\ndir = RE.exec( 'foo/file.pdf' )[ 1 ]\ndir = RE.exec( '/foo/bar/file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '.' )[ 1 ]\ndir = RE.exec( './' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnamePosix.REGEXP":"var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirnameWindows":"var RE = reDirnameWindows();\nvar dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\ndir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\ndir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\ndir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnameWindows.REGEXP":"var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n","reduce":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduce( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduce( arr, 0.0, f )\n","reduce2d":"var f = naryFunction( base.add, 2 );\nvar arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\nvar out = reduce2d( arr, [ 0, 0 ], f )\n","reduceAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n","reduceAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 2000, 1500, 1000 ];\nf( arr, acc, done )\n","reduceRight":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduceRight( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduceRight( arr, 0.0, f )\n","reduceRightAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n","reduceRightAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceRightAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 1000, 1500, 2000 ];\nf( arr, acc, done )\n","reDurationString":"var RE = reDurationString();\nvar parts = RE.exec( '3d2ms' )\nparts = RE.exec( '4h3m20s' )\n","reDurationString.REGEXP":"var bool = reDurationString.REGEXP.test( '3d2ms' )\nbool = reDurationString.REGEXP.test( 'foo' )\n","reEOL":"var RE_EOL = reEOL();\nvar bool = RE_EOL.test( '\\n' )\nbool = RE_EOL.test( '\\r\\n' )\nbool = RE_EOL.test( '\\\\r\\\\n' )\n","reEOL.REGEXP":"var bool = reEOL.REGEXP.test( 'abc' )\n","reEOL.REGEXP_CAPTURE":"var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n","reExtendedLengthPath":"var RE = reExtendedLengthPath();\nvar path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\nvar bool = RE.test( path )\npath = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\nbool = RE.test( path )\npath = 'C:\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '/c/foo/bar';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\n","reExtendedLengthPath.REGEXP":"var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n","reExtname":"var RE = reExtname()\nvar RE_POSIX = reExtname( 'posix' );\nvar ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reExtname( 'win32' );\next = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reExtname.REGEXP":"var RE = reExtname.REGEXP\n","reExtname.REGEXP_POSIX":"var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtname.REGEXP_WIN32":"var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reExtnamePosix":"var RE = reExtnamePosix();\nvar ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\next = RE.exec( './foo/bar/.gitignore' )[ 1 ]\next = RE.exec( 'foo/file.pdf' )[ 1 ]\next = RE.exec( '/foo/bar/file' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '.' )[ 1 ]\next = RE.exec( './' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnamePosix.REGEXP":"var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtnameWindows":"var RE = reExtnameWindows();\nvar ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\next = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\next = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\next = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\next = RE.exec( 'beep\\\\boop.' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnameWindows.REGEXP":"var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reFilename":"var RE = reFilename()\nvar RE_POSIX = reFilename( 'posix' );\nvar parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\nvar RE_WIN32 = reFilename( 'win32' );\nparts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reFilename.REGEXP":"var RE = reFilename.REGEXP\n","reFilename.REGEXP_POSIX":"var f = '/foo/bar/index.js';\nvar parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n","reFilename.REGEXP_WIN32":"var f = 'C:\\\\foo\\\\bar\\\\index.js';\nvar parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n","reFilenamePosix":"var RE = reFilenamePosix();\nvar parts = RE.exec( '/foo/bar/index.js' ).slice()\nparts = RE.exec( './foo/bar/.gitignore' ).slice()\nparts = RE.exec( 'foo/file.pdf' ).slice()\nparts = RE.exec( '/foo/bar/file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenamePosix.REGEXP":"var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n","reFilenameWindows":"var RE = reFilenameWindows();\nvar parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\nparts = RE.exec( 'foo\\\\file.pdf' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenameWindows.REGEXP":"var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n","reFromString":"var re = reFromString( '/beep/' )\nre = reFromString( '/beep' )\n","reFunctionName":"var RE_FUNCTION_NAME = reFunctionName();\nfunction beep() { return 'boop'; };\nvar name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\nname = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n","reFunctionName.REGEXP":"var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n","regexp2json":"var json = regexp2json( /ab+c/ )\n","reim":"var z = new Complex128( 5.0, 3.0 );\nvar out = reim( z )\n","reimf":"var z = new Complex64( 5.0, 3.0 );\nvar out = reimf( z )\n","rejectArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v === 2 ); };\nvar bar = rejectArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","removeFirst":"var out = removeFirst( 'beep' )\nout = removeFirst( 'Boop' )\nout = removeFirst( 'foo bar', 4 )\n","removeLast":"var out = removeLast( 'beep' )\nout = removeLast( 'Boop' )\nout = removeLast( 'foo bar', 4 )\n","removePunctuation":"var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\nvar out = removePunctuation( str )\nstr = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\nout = removePunctuation( str )\n","removeUTF8BOM":"var out = removeUTF8BOM( '\\ufeffbeep' )\n","removeWords":"var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\nout = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n","rename":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nrename( './beep/boop.txt', './beep/foo.txt', done );\n","rename.sync":"var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n","reNativeFunction":"var RE = reNativeFunction();\nvar bool = RE.test( Date.toString() )\nbool = RE.test( (function noop() {}).toString() )\n","reNativeFunction.REGEXP":"var bool = reNativeFunction.REGEXP.test( Date.toString() )\nbool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n","reorderArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reorderArguments( foo, [ 2, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","repeat":"var out = repeat( 'a', 5 )\nout = repeat( '', 100 )\nout = repeat( 'beep', 0 )\n","replace":"var out = replace( 'beep', 'e', 'o' )\nfunction replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nout = replace( str, /([^\\s]+)/gi, replacer )\nout = replace( 'beep', /e/, 'o' )\n","replaceBefore":"var str = 'beep boop';\nvar out = replaceBefore( str, ' ', 'foo' )\nout = replaceBefore( str, 'o', 'foo' )\n","reRegExp":"var RE = reRegExp();\nvar bool = RE.test( '/^beep$/' )\nbool = RE.test( '/boop' )\nbool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\nbool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n","reRegExp.REGEXP":"var bool = reRegExp.REGEXP.test( '/^beep$/' )\nbool = reRegExp.REGEXP.test( '/boop' )\n","rescape":"var str = rescape( '[A-Z]*' )\n","reSemVer":"var RE_SEMVER = reSemVer()\nvar bool = RE_SEMVER.test( '1.0.0' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1' )\nbool = RE_SEMVER.test( 'abc' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n","reSemVer.REGEXP":"var bool = reSemVer.REGEXP.test( '1.0.0' )\nbool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n","resolveParentPath":"function onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n };\nresolveParentPath( 'package.json', onPath );\n","resolveParentPath.sync":"var out = resolveParentPath.sync( 'package.json' );\n","resolveParentPathBy":"function predicate( path, next ) {\n setTimeout( onTimeout, path );\n function onTimeout() {\n console.log( path );\n next( null, false );\n }\n };\nfunction onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n };\nresolveParentPathBy( 'package.json', predicate, onPath );\n","resolveParentPathBy.sync":"function predicate() { return false; };\nvar out = resolveParentPathBy.sync( 'package.json', predicate );\n","reUncPath":"var RE = reUncPath();\nvar path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = 'beep boop \\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server';\nbool = RE.test( path )\npath = '\\\\';\nbool = RE.test( path )\npath = '';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\nbool = RE.test( path )\npath = '//server/share';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\npath = 'foo/bar';\nbool = RE.test( path )\npath = './foo/bar';\nbool = RE.test( path )\npath = '/foo/../bar';\nbool = RE.test( path )\n","reUncPath.REGEXP":"var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = reUncPath.REGEXP.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = reUncPath.REGEXP.test( path )\n","reUtf16SurrogatePair":"var RE = reUtf16SurrogatePair();\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16SurrogatePair.REGEXP":"var RE = reUtf16SurrogatePair.REGEXP;\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16UnpairedSurrogate":"var RE = reUtf16UnpairedSurrogate();\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reUtf16UnpairedSurrogate.REGEXP":"var RE = reUtf16UnpairedSurrogate.REGEXP;\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reverseArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reverseArguments( foo );\nvar out = bar( 1, 2, 3 )\n","reverseString":"var out = reverseString( 'foo' )\nout = reverseString( 'abcdef' )\n","reviveBasePRNG":"var str = JSON.stringify( base.random.mt19937 );\nvar r = parseJSON( str, reviveBasePRNG )\n","reviveBuffer":"var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\nvar buf = parseJSON( str, reviveBuffer )\n","reviveComplex":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex )\n","reviveComplex64":"var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex64 )\n","reviveComplex128":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex128 )\n","reviveError":"var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\nvar err = JSON.parse( str, reviveError )\n","reviveRegExp":"var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\nvar v = parseJSON( str, reviveRegExp )\n","reviveTypedArray":"var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\nvar arr = parseJSON( str, reviveTypedArray )\n","reWhitespace":"var RE = reWhitespace();\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP":"var RE = reWhitespace.REGEXP;\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP_CAPTURE":"var RE = reWhitespace.REGEXP_CAPTURE;\nvar str = 'Duplicate capture';\nvar out = replace( str, RE, '$1$1' )\n","rpad":"var out = rpad( 'a', 5 )\nout = rpad( 'beep', 10, 'p' )\nout = rpad( 'beep', 12, 'boop' )\n","rtrim":"var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","rtrimN":"var out = rtrimN( ' abc ', 2 )\nvar out = rtrimN( '!!!abc!!!', 2, '!' )\n","safeintmax":"var m = safeintmax( 'float16' )\nm = safeintmax( 'float32' )\n","safeintmin":"var m = safeintmin( 'float16' )\nm = safeintmin( 'float32' )\n","sample":"var out = sample( 'abc' )\nout = sample( [ 3, 6, 9 ] )\nvar bool = ( out.length === 3 )\nout = sample( [ 3, null, NaN, 'abc', function(){} ] )\nout = sample( [ 3, 6, 9 ], { 'size': 10 } )\nout = sample( [ 0, 1 ], { 'size': 20 } )\nout = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\nout = sample( [ 0, 1 ], { 'replace': false } )\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\nout = sample( x, { 'probs': probs } )\nout = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n","sample.factory":"var mysample = sample.factory({ 'seed': 232 } );\nvar out = mysample( 'abcdefg' )\nvar pool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\nout = mysample()\nout = mysample()\nvar opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\npool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, opts );\nout = mysample()\nout = mysample()\nout = mysample()\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'size': 10 })\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'replace': false })\nout = mysample()\n","SAVOY_STOPWORDS_FIN":"var list = SAVOY_STOPWORDS_FIN()\n","SAVOY_STOPWORDS_FR":"var list = SAVOY_STOPWORDS_FR()\n","SAVOY_STOPWORDS_GER":"var list = SAVOY_STOPWORDS_GER()\n","SAVOY_STOPWORDS_IT":"var list = SAVOY_STOPWORDS_IT()\n","SAVOY_STOPWORDS_POR":"var list = SAVOY_STOPWORDS_POR()\n","SAVOY_STOPWORDS_SP":"var list = SAVOY_STOPWORDS_SP()\n","SAVOY_STOPWORDS_SWE":"var list = SAVOY_STOPWORDS_SWE()\n","scalar2array":"var x = scalar2array( 1.0 )\n","scalar2ndarray":"var x = scalar2ndarray( 1.0 )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","sdot":"var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = sdot( x, y )\nz.get()\n","SECONDS_IN_DAY":"var days = 3.14;\nvar secs = days * SECONDS_IN_DAY\n","SECONDS_IN_HOUR":"var hrs = 3.14;\nvar secs = hrs * SECONDS_IN_HOUR\n","SECONDS_IN_MINUTE":"var mins = 3.14;\nvar secs = mins * SECONDS_IN_MINUTE\n","SECONDS_IN_WEEK":"var wks = 3.14;\nvar secs = wks * SECONDS_IN_WEEK\n","secondsInMonth":"var num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n","secondsInYear":"var num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n","sentencize":"var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\nout = sentencize( 'Hello World! How are you?' )\n","seq2slice":"var s = new seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","setConfigurableReadOnly":"var obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setConfigurableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setConfigurableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setConfigurableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setMemoizedConfigurableReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedConfigurableReadOnly( obj, 'foo', foo );\nobj.foo\n","setMemoizedReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedReadOnly( obj, 'foo', foo );\nobj.foo\n","setNonEnumerableProperty":"var obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n","setNonEnumerableReadOnly":"var obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setNonEnumerableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setNonEnumerableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setNonEnumerableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setReadOnly":"var obj = {};\nsetReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","SharedArrayBuffer":"var buf = new SharedArrayBuffer( 5 )\n","SharedArrayBuffer.length":"SharedArrayBuffer.length\n","SharedArrayBuffer.prototype.byteLength":"var buf = new SharedArrayBuffer( 5 );\nbuf.byteLength\n","SharedArrayBuffer.prototype.slice":"var b1 = new SharedArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","shift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = shift( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = shift( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = shift( arr )\n","shuffle":"var data = [ 1, 2, 3 ];\nvar out = shuffle( data )\nout = shuffle( data, { 'copy': 'none' } );\nvar bool = ( data === out )\n","shuffle.factory":"var myshuffle = shuffle.factory();\nmyshuffle = shuffle.factory({ 'seed': 239 });\nvar arr = [ 0, 1, 2, 3, 4 ];\nvar out = myshuffle( arr )\nmyshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\narr = [ 1, 2, 3, 4, 5, 6 ];\nout = myshuffle( arr );\nvar bool = ( arr === out )\narr = [ 1, 2, 3, 4 ];\nout = myshuffle( arr, { 'copy': 'shallow' } );\nbool = ( arr === out )\n","sizeOf":"var s = sizeOf( 'int8' )\ns = sizeOf( 'uint32' )\n","Slice":"var s = new Slice();\ns = new Slice( 10 );\nvar s = new Slice( 2, 10 );\ns = new Slice( 2, 10, 1 );\n","Slice.prototype.start":"var s = new Slice( 10 );\ns.start\ns = new Slice( 2, 10 );\ns.start\n","Slice.prototype.stop":"var s = new Slice( 10 );\ns.stop\ns = new Slice( 2, 10 );\ns.stop\n","Slice.prototype.step":"var s = new Slice( 10 );\ns.step\ns = new Slice( 2, 10 );\ns.step\ns = new Slice( 2, 10, 1 );\ns.step\n","Slice.prototype.toString":"var s = new Slice( 10 );\ns.toString()\ns = new Slice( 2, 10, 1 );\ns.toString()\n","Slice.prototype.toJSON":"var s = new Slice( 10 );\ns.toJSON()\ns = new Slice( 2, 10, 1 );\ns.toJSON()\n","snakecase":"var out = snakecase( 'Hello World!' )\nout = snakecase( 'I am a tiny little teapot' )\n","some":"var arr = [ 0, 0, 1, 2, 3 ];\nvar bool = some( arr, 3 )\n","someBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, -3, 4, -1 ];\nvar bool = someBy( arr, 2, negative )\n","someByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n","someByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, 2, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, 2, done )\n","someByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, -2, 3, 4 ];\nvar bool = someByRight( arr, 2, negative )\n","someByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n","someByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, 2, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, 2, done )\n","someInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\nvar bool = someInBy( obj, 2, negative )\n","someOwnBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\nvar bool = someOwnBy( obj, 2, negative )\n","SOTU":"var out = SOTU()\nvar opts = { 'name': 'Barack Obama' };\nout = SOTU( opts )\nopts = { 'party': [ 'Democratic', 'Federalist' ] };\nout = SOTU( opts )\nopts = { 'year': [ 2008, 2009, 2011 ] };\nout = SOTU( opts )\nopts = { 'range': [ 2008, 2016 ] }\nout = SOTU( opts )\n","SPACHE_REVISED":"var list = SPACHE_REVISED()\n","SPAM_ASSASSIN":"var data = SPAM_ASSASSIN()\n","SparklineBase":"var sparkline = new SparklineBase()\nvar data = [ 1, 2, 3 ];\nsparkline = new SparklineBase( data )\n","sparsearray2iterator":"var it = sparsearray2iterator( [ 1, , 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","sparsearray2iteratorRight":"var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\nvar v = it.next().value\nv = it.next().value\n","splitStream":"var s = splitStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = splitStream.factory( opts );\nvar s = createStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.objectMode":"var s = splitStream.objectMode();\ns.write( 'a\\nb\\c' );\ns.end();\n","SQRT_EPS":"SQRT_EPS\n","SQRT_HALF":"SQRT_HALF\n","SQRT_HALF_PI":"SQRT_HALF_PI\n","SQRT_PHI":"SQRT_PHI\n","SQRT_PI":"SQRT_PI\n","SQRT_THREE":"SQRT_THREE\n","SQRT_TWO":"SQRT_TWO\n","SQRT_TWO_PI":"SQRT_TWO_PI\n","SSA_US_BIRTHS_2000_2014":"var data = SSA_US_BIRTHS_2000_2014()\n","sswap":"var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\nsswap( x, y );\nx.data\ny.data\n","Stack":"var s = Stack();\ns.push( 'foo' ).push( 'bar' );\ns.length\ns.pop()\ns.length\ns.pop()\ns.length\n","standalone2pkg":"var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n","STANDARD_CARD_DECK":"var list = STANDARD_CARD_DECK()\n","startcase":"var out = startcase( 'beep boop' )\n","startsWith":"var bool = startsWith( 'Beep', 'Be' )\nbool = startsWith( 'Beep', 'ep' )\nbool = startsWith( 'Beep', 'ee', 1 )\nbool = startsWith( 'Beep', 'ee', -3 )\nbool = startsWith( 'Beep', '' )\n","STOPWORDS_EN":"var list = STOPWORDS_EN()\n","strided.abs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( 2, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2By":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.abs2By.ndarray":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -1.0, -2.0, -3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.absBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.absBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.absBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acosBy":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acosBy.ndarray":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 0.707, 0.866, -0.707 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoshBy":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoshBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoshBy.ndarray":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 1.5, 2.0, 2.5 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acotBy":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acotBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acotBy.ndarray":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -2.5, -1.5, -0.5, 0.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acothBy":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acothBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acothBy.ndarray":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -5.0, -4.0, -3.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acovercosBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acovercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acovercosBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.add":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.add.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.addBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.addBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.addBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ahavercosBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahavercosBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ahaversinBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahaversinBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinhBy":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinhBy.ndarray":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.0, 2.0, -2.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanBy":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -1.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanhBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanhBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.avercosBy":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.avercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.avercosBy.ndarray":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -1.57, -0.5, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.aversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.aversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.aversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.binetBy":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.binetBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.binetBy.ndarray":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 2.0, 3.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.cbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.cbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cbrtBy":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cbrtBy.ndarray":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 9.0, -27.0, 81.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cosBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cosBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.deg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.deg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.dataTypes":"var out = strided.dataTypes()\n","strided.dcbrtBy":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy( x.length, x, 1, y, 1, clbk )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.dcbrtBy.ndarray":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.dispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1 );\ny\nf = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\ny\n","strided.dispatchBy":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\ny\nf = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\ny\n","strided.floor":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.floor.ndarray":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.inv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.inv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.mul":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.mul.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.mulBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.mulBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.rsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.rsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sinBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sinBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.sqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sqrtBy":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sqrtBy.ndarray":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 122.0, 50.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sub":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.sub.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.subBy":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.subBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.subBy.ndarray":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 11.0, 12.0, 13.0, 14.0 ];\ny = [ 8.0, 7.0, 6.0, 5.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.trunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.trunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","stridedarray2iterator":"var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\nvar v = it.next().value\nv = it.next().value\n","stridedArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","stridedArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = stridedArrayStream.factory( opts );\n","stridedArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","string2buffer":"var b = string2buffer( 'beep boop' )\nb = string2buffer( '7468697320697320612074c3a97374', 'hex' );\nb.toString()\n","sub2ind":"var d = [ 3, 3, 3 ];\nvar idx = sub2ind( d, 1, 2, 2 )\n","substringAfter":"var out = substringAfter( 'Hello World!', 'World' )\nout = substringAfter( 'Hello World!', 'Hello ' )\nout = substringAfter( 'Hello World!', 'l', 5 )\n","substringAfterLast":"var out = substringAfterLast( 'beep boop beep baz', 'beep' )\nout = substringAfterLast( 'Hello World!', 'Hello ' )\nout = substringAfterLast( 'Hello World!', 'o', 5 )\n","substringBefore":"var str = 'beep boop';\nvar out = substringBefore( str, ' ' )\nout = substringBefore( str, 'o' )\n","substringBeforeLast":"var str = 'Beep Boop Beep';\nvar out = substringBeforeLast( str, 'Beep' )\nout = substringBeforeLast( str, 'Boop' )\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n","Symbol":"var s = ( Symbol ) ? Symbol( 'beep' ) : null\n","tabulate":"var collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulate( collection )\n","tabulateBy":"function indicator( value ) { return value[ 0 ]; };\nvar collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulateBy( collection, indicator )\n","tabulateByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n","tabulateByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = tabulateByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 750 ];\nf( arr, done )\n","thunk":"var fcn = thunk( base.add, 2, 3 );\nvar v = fcn()\nv = fcn()\n","tic":"var t = tic()\n","timeit":"var code = 'var x = Math.pow( Math.random(), 3 );';\ncode += 'if ( x !== x ) {';\ncode += 'throw new Error( \\'Something went wrong.\\' );';\ncode += '}';\nfunction done( error, results ) {\n if ( error ) {\n throw error;\n }\n console.dir( results );\n };\ntimeit( code, done )\n","tmpdir":"var dir = tmpdir()\n","toc":"var start = tic();\nvar delta = toc( start )\n","tokenize":"var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\nout = tokenize( 'Hello World!', true )\n","transformStream":"var s = transformStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = transformStream.factory( opts );\nfunction fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar s = createStream( fcn );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.objectMode":"var s = transformStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","transformStream.ctor":"function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar opts = { 'highWaterMark': 64, 'transform': fcn };\nvar customStream = transformStream.ctor( opts );\nvar s = customStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","trim":"var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","truncate":"var str = 'beep boop';\nvar out = truncate( str, 5 )\nout = truncate( str, 5, '|' )\n","truncateMiddle":"var str = 'beep boop';\nvar out = truncateMiddle( str, 5 )\nout = truncateMiddle( str, 5, '|' )\n","trycatch":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n };\nvar z = trycatch( x, -1.0 )\n","trycatchAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n // process error...\n }\n console.log( result );\n };\ntrycatchAsync( x, 'boop', done )\n","tryFunction":"function fcn() { throw new Error( 'beep boop' ); };\nvar f = tryFunction( fcn );\nvar out = f();\nout.message\n","tryRequire":"var out = tryRequire( '_unknown_module_id_' )\n","trythen":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n };\nfunction y() {\n return -1.0;\n };\nvar z = trythen( x, y )\n","trythenAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ntrythenAsync( x, y, done )\n","ttest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ttest( x )\nrnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\nx = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n y[ i ] = rnorm();\n }\nout = ttest( x, y )\nvar table = out.print()\nvar arr = [ 2, 4, 3, 1, 0 ];\nout = ttest( arr, { 'alpha': 0.01 } );\ntable = out.print()\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest( arr, { 'alternative': 'greater' } );\ntable = out.print()\n","ttest2":"var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\nvar y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\nvar out = ttest2( x, y )\nvar table = out.print()\nout = ttest2( x, y, { 'alpha': 0.1 } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'greater' } );\ntable = out.print()\nx = [ 2, 3, 1, 4 ];\ny = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\nout = ttest2( x, y, { 'variance': 'equal' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 3.0 );\n }\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 1.0, 3.0 );\n }\nout = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n","TWO_PI":"TWO_PI\n","typedarray":"var arr = typedarray()\narr = typedarray( 'float32' )\nvar arr = typedarray( 5 )\narr = typedarray( 5, 'int32' )\nvar arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = typedarray( buf, 0, 4, 'float32' )\n","typedarray2json":"var arr = new Float64Array( 2 );\narr[ 0 ] = 5.0;\narr[ 1 ] = 3.0;\nvar json = typedarray2json( arr )\n","typedarrayCtors":"var ctor = typedarrayCtors( 'float64' )\nctor = typedarrayCtors( 'float' )\n","typedarrayDataTypes":"var out = typedarrayDataTypes()\n","typedarraypool":"var arr = typedarraypool()\narr = typedarraypool( 'float32' )\nvar arr = typedarraypool( 5 )\narr = typedarraypool( 5, 'int32' )\nvar arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool( arr1, 'float32' )\n","typedarraypool.malloc":"var arr = typedarraypool.malloc()\narr = typedarraypool.malloc( 'float32' )\nvar arr = typedarraypool.malloc( 5 )\narr = typedarraypool.malloc( 5, 'int32' )\nvar arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\n","typedarraypool.calloc":"var arr = typedarraypool.calloc()\narr = typedarraypool.calloc( 'float32' )\nvar arr = typedarraypool.calloc( 5 )\narr = typedarraypool.calloc( 5, 'int32' )\n","typedarraypool.free":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\n","typedarraypool.clear":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\ntypedarraypool.clear();\n","typedarraypool.highWaterMark":"typedarraypool.highWaterMark\n","typedarraypool.nbytes":"var arr = typedarraypool( 5 )\ntypedarraypool.nbytes\n","typedarraypool.factory":"var pool = typedarraypool.factory();\nvar arr1 = pool( 3, 'float64' )\n","typemax":"var m = typemax( 'int8' )\nm = typemax( 'uint32' )\n","typemin":"var m = typemin( 'int8' )\nm = typemin( 'uint32' )\n","typeOf":"var t = typeOf( 'a' )\nt = typeOf( 5 )\nt = typeOf( NaN )\nt = typeOf( true )\nt = typeOf( false )\nt = typeOf( null )\nt = typeOf( undefined )\nt = typeOf( [] )\nt = typeOf( {} )\nt = typeOf( function noop() {} )\nt = typeOf( Symbol( 'beep' ) )\nt = typeOf( /.+/ )\nt = typeOf( new String( 'beep' ) )\nt = typeOf( new Number( 5 ) )\nt = typeOf( new Boolean( false ) )\nt = typeOf( new Array() )\nt = typeOf( new Object() )\nt = typeOf( new Int8Array( 10 ) )\nt = typeOf( new Uint8Array( 10 ) )\nt = typeOf( new Uint8ClampedArray( 10 ) )\nt = typeOf( new Int16Array( 10 ) )\nt = typeOf( new Uint16Array( 10 ) )\nt = typeOf( new Int32Array( 10 ) )\nt = typeOf( new Uint32Array( 10 ) )\nt = typeOf( new Float32Array( 10 ) )\nt = typeOf( new Float64Array( 10 ) )\nt = typeOf( new ArrayBuffer( 10 ) )\nt = typeOf( new Date() )\nt = typeOf( new RegExp( '.+' ) )\nt = typeOf( new Map() )\nt = typeOf( new Set() )\nt = typeOf( new WeakMap() )\nt = typeOf( new WeakSet() )\nt = typeOf( new Error( 'beep' ) )\nt = typeOf( new TypeError( 'beep' ) )\nt = typeOf( new SyntaxError( 'beep' ) )\nt = typeOf( new ReferenceError( 'beep' ) )\nt = typeOf( new URIError( 'beep' ) )\nt = typeOf( new RangeError( 'beep' ) )\nt = typeOf( new EvalError( 'beep' ) )\nt = typeOf( Math )\nt = typeOf( JSON )\nfunction beep() { return arguments; };\nt = typeOf( beep() )\nt = typeOf( new Buffer( 10 ) )\nfunction Person() { return this };\nt = typeOf( new Person() )\nvar Foo = function () { return this; };\nt = typeOf( new Foo() )\n","UINT8_MAX":"UINT8_MAX\n","UINT8_NUM_BYTES":"UINT8_NUM_BYTES\n","Uint8Array":"var arr = new Uint8Array()\nvar arr = new Uint8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8Array( buf, 0, 4 )\n","Uint8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n","Uint8Array.of":"var arr = Uint8Array.of( 1, 2 )\n","Uint8Array.BYTES_PER_ELEMENT":"Uint8Array.BYTES_PER_ELEMENT\n","Uint8Array.name":"Uint8Array.name\n","Uint8Array.prototype.buffer":"var arr = new Uint8Array( 5 );\narr.buffer\n","Uint8Array.prototype.byteLength":"var arr = new Uint8Array( 5 );\narr.byteLength\n","Uint8Array.prototype.byteOffset":"var arr = new Uint8Array( 5 );\narr.byteOffset\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8Array.prototype.length":"var arr = new Uint8Array( 5 );\narr.length\n","Uint8Array.prototype.copyWithin":"var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8Array.prototype.entries":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.every":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8Array.prototype.fill":"var arr = new Uint8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8Array.prototype.filter":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8Array.prototype.find":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8Array.prototype.findIndex":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8Array.prototype.forEach":"var arr = new Uint8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8Array.prototype.includes":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8Array.prototype.indexOf":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8Array.prototype.join":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8Array.prototype.keys":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.lastIndexOf":"var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8Array.prototype.map":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8Array.prototype.reduce":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8Array.prototype.reduceRight":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8Array.prototype.reverse":"var arr = new Uint8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8Array.prototype.set":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8Array.prototype.slice":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8Array.prototype.some":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8Array.prototype.sort":"var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8Array.prototype.subarray":"var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8Array.prototype.toLocaleString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8Array.prototype.toString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint8Array.prototype.values":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray":"var arr = new Uint8ClampedArray()\nvar arr = new Uint8ClampedArray( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8ClampedArray( buf, 0, 4 )\n","Uint8ClampedArray.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n","Uint8ClampedArray.of":"var arr = Uint8ClampedArray.of( 1, 2 )\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"Uint8ClampedArray.BYTES_PER_ELEMENT\n","Uint8ClampedArray.name":"Uint8ClampedArray.name\n","Uint8ClampedArray.prototype.buffer":"var arr = new Uint8ClampedArray( 5 );\narr.buffer\n","Uint8ClampedArray.prototype.byteLength":"var arr = new Uint8ClampedArray( 5 );\narr.byteLength\n","Uint8ClampedArray.prototype.byteOffset":"var arr = new Uint8ClampedArray( 5 );\narr.byteOffset\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8ClampedArray( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8ClampedArray.prototype.length":"var arr = new Uint8ClampedArray( 5 );\narr.length\n","Uint8ClampedArray.prototype.copyWithin":"var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8ClampedArray.prototype.entries":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.every":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8ClampedArray.prototype.fill":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8ClampedArray.prototype.filter":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8ClampedArray.prototype.find":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8ClampedArray.prototype.findIndex":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8ClampedArray.prototype.forEach":"var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8ClampedArray.prototype.includes":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8ClampedArray.prototype.indexOf":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8ClampedArray.prototype.join":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8ClampedArray.prototype.keys":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.lastIndexOf":"var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8ClampedArray.prototype.map":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8ClampedArray.prototype.reduce":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8ClampedArray.prototype.reduceRight":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8ClampedArray.prototype.reverse":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8ClampedArray.prototype.set":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8ClampedArray.prototype.slice":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8ClampedArray.prototype.some":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8ClampedArray.prototype.sort":"var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8ClampedArray.prototype.subarray":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8ClampedArray.prototype.toLocaleString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8ClampedArray.prototype.toString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toString()\n","Uint8ClampedArray.prototype.values":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT16_MAX":"UINT16_MAX\n","UINT16_NUM_BYTES":"UINT16_NUM_BYTES\n","Uint16Array":"var arr = new Uint16Array()\nvar arr = new Uint16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Uint16Array( buf, 0, 4 )\n","Uint16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n","Uint16Array.of":"var arr = Uint16Array.of( 1, 2 )\n","Uint16Array.BYTES_PER_ELEMENT":"Uint16Array.BYTES_PER_ELEMENT\n","Uint16Array.name":"Uint16Array.name\n","Uint16Array.prototype.buffer":"var arr = new Uint16Array( 5 );\narr.buffer\n","Uint16Array.prototype.byteLength":"var arr = new Uint16Array( 5 );\narr.byteLength\n","Uint16Array.prototype.byteOffset":"var arr = new Uint16Array( 5 );\narr.byteOffset\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint16Array.prototype.length":"var arr = new Uint16Array( 5 );\narr.length\n","Uint16Array.prototype.copyWithin":"var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint16Array.prototype.entries":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.every":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint16Array.prototype.fill":"var arr = new Uint16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint16Array.prototype.filter":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint16Array.prototype.find":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint16Array.prototype.findIndex":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint16Array.prototype.forEach":"var arr = new Uint16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint16Array.prototype.includes":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint16Array.prototype.indexOf":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint16Array.prototype.join":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint16Array.prototype.keys":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.lastIndexOf":"var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint16Array.prototype.map":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint16Array.prototype.reduce":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint16Array.prototype.reduceRight":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint16Array.prototype.reverse":"var arr = new Uint16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint16Array.prototype.set":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint16Array.prototype.slice":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint16Array.prototype.some":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint16Array.prototype.sort":"var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint16Array.prototype.subarray":"var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint16Array.prototype.toLocaleString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint16Array.prototype.toString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint16Array.prototype.values":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT32_MAX":"UINT32_MAX\n","UINT32_NUM_BYTES":"UINT32_NUM_BYTES\n","Uint32Array":"var arr = new Uint32Array()\nvar arr = new Uint32Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Uint32Array( buf, 0, 4 )\n","Uint32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n","Uint32Array.of":"var arr = Uint32Array.of( 1, 2 )\n","Uint32Array.BYTES_PER_ELEMENT":"Uint32Array.BYTES_PER_ELEMENT\n","Uint32Array.name":"Uint32Array.name\n","Uint32Array.prototype.buffer":"var arr = new Uint32Array( 5 );\narr.buffer\n","Uint32Array.prototype.byteLength":"var arr = new Uint32Array( 5 );\narr.byteLength\n","Uint32Array.prototype.byteOffset":"var arr = new Uint32Array( 5 );\narr.byteOffset\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint32Array.prototype.length":"var arr = new Uint32Array( 5 );\narr.length\n","Uint32Array.prototype.copyWithin":"var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint32Array.prototype.entries":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.every":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint32Array.prototype.fill":"var arr = new Uint32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint32Array.prototype.filter":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint32Array.prototype.find":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint32Array.prototype.findIndex":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint32Array.prototype.forEach":"var arr = new Uint32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint32Array.prototype.includes":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint32Array.prototype.indexOf":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint32Array.prototype.join":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint32Array.prototype.keys":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.lastIndexOf":"var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint32Array.prototype.map":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint32Array.prototype.reduce":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint32Array.prototype.reduceRight":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint32Array.prototype.reverse":"var arr = new Uint32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint32Array.prototype.set":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint32Array.prototype.slice":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint32Array.prototype.some":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint32Array.prototype.sort":"var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint32Array.prototype.subarray":"var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint32Array.prototype.toLocaleString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint32Array.prototype.toString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint32Array.prototype.values":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","umask":"var mask = umask()\nmask = umask( { 'symbolic': true } )\n","uncapitalize":"var out = uncapitalize( 'Beep' )\nout = uncapitalize( 'bOOp' )\n","uncapitalizeKeys":"var obj = { 'AA': 1, 'BB': 2 };\nvar out = uncapitalizeKeys( obj )\n","uncurry":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n };\nvar fcn = uncurry( addX );\nvar sum = fcn( 2, 3 )\nfunction add( x ) {\n return function add( y ) {\n return x + y;\n };\n };\nfcn = uncurry( add, 2 );\nsum = fcn( 9 )\nfunction addX( x ) {\n this.x = x;\n return addY;\n };\nfunction addY( y ) {\n return this.x + y;\n };\nfcn = uncurry( addX, {} );\nsum = fcn( 2, 3 )\n","uncurryRight":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n };\nvar fcn = uncurryRight( addX );\nvar sum = fcn( 3, 2 )\nfunction add( y ) {\n return function add( x ) {\n return x + y;\n };\n };\nfcn = uncurryRight( add, 2 );\nsum = fcn( 9 )\nfunction addY( y ) {\n this.y = y;\n return addX;\n };\nfunction addX( x ) {\n return x + this.y;\n };\nfcn = uncurryRight( addY, {} );\nsum = fcn( 3, 2 )\n","UNICODE_MAX":"UNICODE_MAX\n","UNICODE_MAX_BMP":"UNICODE_MAX_BMP\n","UnicodeColumnChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeColumnChartSparkline( data );\nchart.render()\n","UnicodeLineChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeLineChartSparkline( data );\nchart.render()\n","UnicodeSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeSparkline( data );\nchart.render()\nchart.type = 'line';\nchart.render()\n","UnicodeTristateChartSparkline":"var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\nvar chart = new UnicodeTristateChartSparkline( data );\nchart.render()\n","UnicodeUpDownChartSparkline":"var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\nvar chart = new UnicodeUpDownChartSparkline( data );\nchart.render()\n","UnicodeWinLossChartSparkline":"var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\nvar chart = new UnicodeWinLossChartSparkline( data );\nchart.render()\n","unlink":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nunlink( './beep/boop.txt', done );\n","unlink.sync":"var out = unlink.sync( './beep/boop.txt' );\n","unshift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = unshift( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = unshift( arr, 3.0, 4.0 )\narr = { 'length': 1, '0': 1.0 };\narr = unshift( arr, 2.0, 3.0 )\n","until":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nuntil( predicate, beep )\n","untilAsync":"function predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nuntilAsync( predicate, fcn, done )\n","untilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nuntilEach( arr, predicate, logger )\n","untilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nuntilEachRight( arr, predicate, logger )\n","unzip":"var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nvar out = unzip( arr )\narr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nout = unzip( arr, [ 0, 2 ] )\n","uppercase":"var out = uppercase( 'bEEp' )\n","uppercaseKeys":"var obj = { 'a': 1, 'b': 2 };\nvar out = uppercaseKeys( obj )\n","US_STATES_ABBR":"var list = US_STATES_ABBR()\n","US_STATES_CAPITALS":"var list = US_STATES_CAPITALS()\n","US_STATES_CAPITALS_NAMES":"var out = US_STATES_CAPITALS_NAMES()\n","US_STATES_NAMES":"var list = US_STATES_NAMES()\n","US_STATES_NAMES_CAPITALS":"var out = US_STATES_NAMES_CAPITALS()\n","utf16ToUTF8Array":"var str = '☃';\nvar out = utf16ToUTF8Array( str )\n","vartest":"var x = [ 610, 610, 550, 590, 565, 570 ];\nvar y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\nvar out = vartest( x, y )\nvar table = out.print()\n","waterfall":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nwaterfall( fcns, done );\n","waterfall.factory":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nvar waterfall = waterfall.factory( fcns, done );\nwaterfall();\nwaterfall();\nwaterfall();\n","WebAssemblyMemory":"var mem = new WebAssemblyMemory( { 'initial': 0 } )\n","WebAssemblyMemory.prototype.buffer":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.buffer\n","WebAssemblyMemory.prototype.grow":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.grow( 1 )\n","whileAsync":"function predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nwhileAsync( predicate, fcn, done )\n","whileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nwhileEach( arr, predicate, logger )\n","whileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nwhileEachRight( arr, predicate, logger )\n","whilst":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nwhilst( predicate, beep )\n","wilcoxon":"var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\nvar out = wilcoxon( x )\nrunif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\nvar x = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = runif();\n y[ i ] = runif();\n }\nout = wilcoxon( x, y )\nvar table = out.print()\nout = wilcoxon( arr, { 'alpha': 0.01 });\ntable = out.print()\nout = wilcoxon( arr, { 'mu': 10 })\nout = wilcoxon( arr, { 'alternative': 'less' });\ntable = out.print()\nout = wilcoxon( arr, { 'alternative': 'greater' });\ntable = out.print()\n","writableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = writableProperties( obj )\n","writablePropertiesIn":"var props = writablePropertiesIn( [] )\n","writablePropertyNames":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNames( obj )\n","writablePropertyNamesIn":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNamesIn( obj )\n","writablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbols( obj )\n","writablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbolsIn( obj )\n","writeFile":"function onWrite( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nwriteFile( './beep/boop.txt', 'beep boop', onWrite );\n","writeFile.sync":"var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n","zip":"var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\nvar opts = { 'trunc': false };\nout = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n","ztest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ztest( x, 2.0 )\narr = [ 2, 4, 3, 1, 0 ];\nout = ztest( arr, 2.0, { 'alpha': 0.01 } );\ntable = out.print()\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'alternative': 'less' } )\nout = ztest( arr, 1.0, { 'alternative': 'greater' } )\n","ztest2":"var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\nvar y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\nvar out = ztest2( x, y, 2.0, 2.0 )\nvar table = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 1.0 );\n }\ny = new Array( 100 );\n for ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 0.0, 2.0 );\n }\nout = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n"} +{"abs":"var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\nvar x = array( arr );\nvar y = abs( x )\n","abs.assign":"var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\nvar x = array( arr );\nvar sh = ndarrayShape( x );\nvar y = ndzeros( sh );\nvar out = abs.assign( x, y )\nvar bool = ( out === y )\n","acartesianPower":"var x = [ 1, 2 ];\nvar out = acartesianPower( x, 2 )\n","acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = acartesianProduct( x1, x2 )\n","acartesianSquare":"var out = acartesianSquare( [ 1, 2 ] )\n","acronym":"var out = acronym( 'the quick brown fox' )\nout = acronym( 'Hard-boiled eggs' )\n","aempty":"var arr = aempty( 2 )\narr = aempty( 2, 'float32' )\n","aemptyLike":"var x = new Float64Array( 2 );\nvar arr = aemptyLike( x )\narr = aemptyLike( x, 'float32' )\n","AFINN_96":"var list = AFINN_96()\n","AFINN_111":"var list = AFINN_111()\n","afull":"var arr = afull( 2, 1.0 )\narr = afull( 2, 1.0, 'float32' )\n","afullLike":"var x = new Float64Array( 2 );\nvar y = afullLike( x, 1.0 )\ny = afullLike( x, 1.0, 'float32' )\n","alias2pkg":"var v = alias2pkg( 'base.sin' )\n","alias2related":"var v = alias2related( 'base.sin' )\n","alias2standalone":"var v = alias2standalone( 'base.sin' )\n","aliases":"var o = aliases()\no = aliases( '@stdlib/math/base/special' )\n","allocUnsafe":"var buf = allocUnsafe( 100 )\n","amskfilter":"var x = [ 1, 2, 3, 4 ];\nvar y = amskfilter( x, [ 0, 1, 0, 1 ] )\n","amskput":"var x = [ 1, 2, 3, 4 ];\nvar out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","amskreject":"var x = [ 1, 2, 3, 4 ];\nvar y = amskreject( x, [ 0, 1, 0, 1 ] )\n","anans":"var arr = anans( 2 )\narr = anans( 2, 'float32' )\n","anansLike":"var x = new Float64Array( 2 );\nvar y = anansLike( x )\ny = anansLike( x, 'float32' )\n","anova1":"var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nvar f = [\n 'control', 'treatA', 'treatB', 'treatC', 'control',\n 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ];\nvar out = anova1( x, f )\n","ANSCOMBES_QUARTET":"var d = ANSCOMBES_QUARTET()\n","any":"var arr = [ 0, 0, 0, 0, 1 ];\nvar bool = any( arr )\n","anyBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4, -1 ];\nvar bool = anyBy( arr, negative )\n","anyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n","anyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","anyByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, 2, 3, 4 ];\nvar bool = anyByRight( arr, negative )\n","anyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n","anyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","anyInBy":"function isNegative(value) { return value < 0 }\nvar obj = { a: 1, b: -2, c: 3, d: 4 }\nvar result = anyInBy(obj, isNegative)\n","anyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': -1, 'b': 2, 'c': -3 };\nvar bool = anyOwnBy( obj, positive )\n","aones":"var arr = aones( 2 )\narr = aones( 2, 'float32' )\n","aonesLike":"var x = new Float64Array( 2 );\nvar y = aonesLike( x )\ny = aonesLike( x, 'float32' )\n","aoneTo":"var arr = aoneTo( 2 )\narr = aoneTo( 2, 'float32' )\n","aoneToLike":"var arr = aoneToLike( [ 0, 0 ] )\narr = aoneToLike( [ 0, 0 ], 'float32' )\n","APERY":"APERY\n","aplace":"var x = [ 1, 2, 3, 4 ];\nvar out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","append":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = append( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = append( arr, [ 3.0, 4.0 ] )\narr = { 'length': 0 };\narr = append( arr, [ 1.0, 2.0 ] )\n","aput":"var x = [ 1, 2, 3, 4 ];\nvar out = aput( x, [ 1, 3 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","ARCH":"ARCH\n","argumentFunction":"var argn = argumentFunction( 1 );\nvar v = argn( 3.14, -3.14, 0.0 )\nv = argn( -1.0, -0.0, 1.0 )\nv = argn( 'beep', 'boop', 'bop' )\nv = argn( 'beep' )\n","ARGV":"var execPath = ARGV[ 0 ]\n","array":"var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","array2buffer":"var buf = array2buffer( [ 1, 2, 3, 4 ] )\n","array2fancy":"var y = array2fancy( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.factory":"var f = array2fancy.factory();\nvar y = f( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.idx":"var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n","array2iterator":"var it = array2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","array2iteratorRight":"var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","ArrayBuffer":"var buf = new ArrayBuffer( 5 )\n","ArrayBuffer.length":"ArrayBuffer.length\n","ArrayBuffer.isView":"var arr = new Float64Array( 10 );\nArrayBuffer.isView( arr )\n","ArrayBuffer.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nbuf.byteLength\n","ArrayBuffer.prototype.slice":"var b1 = new ArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","arraybuffer2buffer":"var ab = new ArrayBuffer( 10 )\nvar buf = arraybuffer2buffer( ab )\nvar len = buf.length\nbuf = arraybuffer2buffer( ab, 2, 6 )\nlen = buf.length\n","arrayCtors":"var ctor = arrayCtors( 'float64' )\nctor = arrayCtors( 'float' )\n","arrayDataType":"var arr = new Float64Array( 10 );\nvar dt = arrayDataType( arr )\ndt = arrayDataType( 'beep' )\n","arrayDataTypes":"var out = arrayDataTypes()\nout = arrayDataTypes( 'floating_point' )\nout = arrayDataTypes( 'floating_point_and_generic' )\n","ArrayIndex":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n","ArrayIndex.free":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.free( idx.id )\n","ArrayIndex.get":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.get( idx.id )\n","ArrayIndex.prototype.data":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.data\n","ArrayIndex.prototype.dtype":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.dtype\n","ArrayIndex.prototype.id":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.id\n","ArrayIndex.prototype.isCached":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.isCached\n","ArrayIndex.prototype.type":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.type\n","ArrayIndex.prototype.toString":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toString()\n","ArrayIndex.prototype.toJSON":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toJSON()\n","arrayMinDataType":"var dt = arrayMinDataType( 3.141592653589793 )\ndt = arrayMinDataType( 3 )\ndt = arrayMinDataType( -3 )\ndt = arrayMinDataType( '-3' )\n","arrayMostlySafeCasts":"var out = arrayMostlySafeCasts( 'float32' )\n","arrayNextDataType":"var out = arrayNextDataType( 'float32' )\n","arrayPromotionRules":"var out = arrayPromotionRules( 'float32', 'int32' )\n","arraySafeCasts":"var out = arraySafeCasts( 'float32' )\n","arraySameKindCasts":"var out = arraySameKindCasts( 'float32' )\n","arrayShape":"var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n","arrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = arrayStream( [ 1, 2, 3 ] );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","arrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = arrayStream.factory( opts );\n","arrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = arrayStream.objectMode( [ 1, 2, 3 ] );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","arrayview2iterator":"var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","arrayview2iteratorRight":"var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","aslice":"var out = aslice( [ 1, 2, 3, 4 ] )\nout = aslice( [ 1, 2, 3, 4 ], 1 )\nout = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n","AsyncIteratorSymbol":"var s = AsyncIteratorSymbol\n","atake":"var x = [ 1, 2, 3, 4 ];\nvar y = atake( x, [ 1, 3 ] )\n","azeros":"var arr = azeros( 2 )\narr = azeros( 2, 'float32' )\n","azerosLike":"var x = new Float64Array( 2 );\nvar y = azerosLike( x )\ny = azerosLike( x, 'float32' )\n","azeroTo":"var arr = azeroTo( 2 )\narr = azeroTo( 2, 'float32' )\n","azeroToLike":"var arr = azeroToLike( [ 0, 0 ] )\narr = azeroToLike( [ 0, 0 ], 'float32' )\n","bartlettTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = bartlettTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = bartlettTest( arr, { 'groups': groups } )\n","base.abs":"var y = base.abs( -1.0 )\ny = base.abs( 2.0 )\ny = base.abs( 0.0 )\ny = base.abs( -0.0 )\ny = base.abs( NaN )\n","base.abs2":"var y = base.abs2( -1.0 )\ny = base.abs2( 2.0 )\ny = base.abs2( 0.0 )\ny = base.abs2( -0.0 )\ny = base.abs2( NaN )\n","base.abs2f":"var y = base.abs2f( -1.0 )\ny = base.abs2f( 2.0 )\ny = base.abs2f( 0.0 )\ny = base.abs2f( -0.0 )\ny = base.abs2f( NaN )\n","base.absdiff":"var d = base.absdiff( 2.0, 5.0 )\nd = base.absdiff( -1.0, 3.14 )\nd = base.absdiff( 10.1, -2.05 )\nd = base.absdiff( -0.0, 0.0 )\nd = base.absdiff( NaN, 5.0 )\nd = base.absdiff( PINF, NINF )\nd = base.absdiff( PINF, PINF )\n","base.absf":"var y = base.absf( -1.0 )\ny = base.absf( 2.0 )\ny = base.absf( 0.0 )\ny = base.absf( -0.0 )\ny = base.absf( NaN )\n","base.acartesianPower":"var x = [ 1, 2 ];\nvar out = base.acartesianPower( x, 2 )\n","base.acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = base.acartesianProduct( x1, x2 )\n","base.acartesianSquare":"var x = [ 1, 2 ];\nvar out = base.acartesianSquare( x )\n","base.acos":"var y = base.acos( 1.0 )\ny = base.acos( 0.707 )\ny = base.acos( NaN )\n","base.acosd":"var y = base.acosd( 0.0 )\ny = base.acosd( PI/6.0 )\ny = base.acosd( NaN )\n","base.acosdf":"var y = base.acosdf( 0.0 )\ny = base.acosdf( FLOAT32_PI / 6.0 )\ny = base.acosdf( NaN )\n","base.acosf":"var y = base.acosf( 1.0 )\ny = base.acosf( 0.707 )\ny = base.acosf( NaN )\n","base.acosh":"var y = base.acosh( 1.0 )\ny = base.acosh( 2.0 )\ny = base.acosh( NaN )\n","base.acot":"var y = base.acot( 2.0 )\ny = base.acot( 0.0 )\ny = base.acot( 0.5 )\ny = base.acot( 1.0 )\ny = base.acot( NaN )\n","base.acotd":"var y = base.acotd( 0.0 )\ny = base.acotd( PI/6.0 )\ny = base.acotd( NaN )\n","base.acotdf":"var y = base.acotdf( 0.0 )\ny = base.acotdf( FLOAT32_PI/6.0 )\ny = base.acotdf( NaN )\n","base.acotf":"var y = base.acotf( 2.0 )\ny = base.acotf( 0.0 )\ny = base.acotf( 0.5 )\ny = base.acotf( 1.0 )\ny = base.acotf( NaN )\n","base.acoth":"var y = base.acoth( 2.0 )\ny = base.acoth( 0.0 )\ny = base.acoth( 0.5 )\ny = base.acoth( 1.0 )\ny = base.acoth( NaN )\n","base.acovercos":"var y = base.acovercos( 1.5 )\ny = base.acovercos( -0.0 )\n","base.acoversin":"var y = base.acoversin( 1.5 )\ny = base.acoversin( 0.0 )\n","base.acsc":"var y = base.acsc( 1.0 )\ny = base.acsc( PI )\ny = base.acsc( -PI )\ny = base.acsc( NaN )\n","base.acscd":"var y = base.acscd( 0.0 )\ny = base.acscd( PI/6.0 )\ny = base.acscd( 1 )\ny = base.acscd( NaN )\n","base.acscdf":"var y = base.acscdf( 0.0 )\ny = base.acscdf( 3.1415927410125732 / 6.0 )\ny = base.acscdf( 1.0 )\ny = base.acscdf( NaN )\n","base.acscf":"var y = base.acscf( 1.0 )\ny = base.acscf( 3.141592653589793 )\ny = base.acscf( -3.141592653589793 )\ny = base.acscf( NaN )\n","base.acsch":"var y = base.acsch( 0.0 )\ny = base.acsch( -1.0 )\ny = base.acsch( NaN )\n","base.add":"var v = base.add( -1.0, 5.0 )\nv = base.add( 2.0, 5.0 )\nv = base.add( 0.0, 5.0 )\nv = base.add( -0.0, 0.0 )\nv = base.add( NaN, NaN )\n","base.add3":"var v = base.add3( -1.0, 5.0, 2.0 )\nv = base.add3( 2.0, 5.0, 2.0 )\nv = base.add3( 0.0, 5.0, 2.0 )\nv = base.add3( -0.0, 0.0, -0.0 )\nv = base.add3( NaN, NaN, NaN )\n","base.add4":"var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\nv = base.add4( 2.0, 5.0, 2.0, -3.0 )\nv = base.add4( 0.0, 5.0, 2.0, -3.0 )\nv = base.add4( -0.0, 0.0, -0.0, -0.0 )\nv = base.add4( NaN, NaN, NaN, NaN )\n","base.add5":"var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\nv = base.add5( NaN, NaN, NaN, NaN, NaN )\n","base.addf":"var v = base.addf( -1.0, 5.0 )\nv = base.addf( 2.0, 5.0 )\nv = base.addf( 0.0, 5.0 )\nv = base.addf( -0.0, 0.0 )\nv = base.addf( NaN, NaN )\n","base.afilled":"var out = base.afilled( 0.0, 3 )\n","base.afilled2d":"var out = base.afilled2d( 0.0, [ 1, 3 ] )\n","base.afilled2dBy":"function clbk() { return 1.0; };\nvar out = base.afilled2dBy( [ 1, 3 ], clbk )\n","base.afilled3d":"var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n","base.afilled3dBy":"function clbk() { return 1.0; };\nvar out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n","base.afilled4d":"var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n","base.afilled4dBy":"function clbk() { return 1.0; };\nvar out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n","base.afilled5d":"var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n","base.afilled5dBy":"function clbk() { return 1.0; };\nvar out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n","base.afilledBy":"function clbk() { return 1.0; };\nvar out = base.afilledBy( 3, clbk )\n","base.afillednd":"var out = base.afillednd( 0.0, [ 1, 3 ] )\n","base.afilledndBy":"function clbk() { return 1.0; };\nvar out = base.afilledndBy( [ 1, 3 ], clbk )\n","base.afilter":"function f( v ) { return ( v > 0 ); };\nvar x = [ 1, -2, -3, 4 ];\nvar out = base.afilter( x, f )\n","base.afirst":"var out = base.afirst( [ 1, 2, 3 ] )\n","base.aflatten":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten( x, [ 2, 2 ], false )\nout = base.aflatten( x, [ 2, 2 ], true )\n","base.aflatten.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2d":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2d( x, [ 2, 2 ], false )\nout = base.aflatten2d( x, [ 2, 2 ], true )\n","base.aflatten2d.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\nout = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n","base.aflatten2dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten3d":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3d( x, [ 2, 1, 2 ], false )\nout = base.aflatten3d( x, [ 2, 1, 2 ], true )\n","base.aflatten3d.assign":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten3dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\nout = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n","base.aflatten3dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten4d":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\nout = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n","base.aflatten4d.assign":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten4dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\nout = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n","base.aflatten4dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten5d":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\nout = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n","base.aflatten5d.assign":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten5dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\nout = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n","base.aflatten5dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflattenBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\nout = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n","base.aflattenBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.afliplr2d":"var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.afliplr3d":"var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.afliplr4d":"var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.afliplr5d":"var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.aflipud2d":"var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.aflipud3d":"var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.aflipud4d":"var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.aflipud5d":"var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.ahavercos":"var y = base.ahavercos( 0.5 )\ny = base.ahavercos( 0.0 )\n","base.ahaversin":"var y = base.ahaversin( 0.5 )\ny = base.ahaversin( 0.0 )\n","base.altcase":"var out = base.altcase( 'Hello World!' )\nout = base.altcase( 'I am a tiny little teapot' )\n","base.aones":"var out = base.aones( 3 )\n","base.aones2d":"var out = base.aones2d( [ 1, 3 ] )\n","base.aones3d":"var out = base.aones3d( [ 1, 1, 3 ] )\n","base.aones4d":"var out = base.aones4d( [ 1, 1, 1, 3 ] )\n","base.aones5d":"var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n","base.aonesnd":"var out = base.aonesnd( [ 1, 3 ] )\n","base.aoneTo":"var arr = base.aoneTo( 6 )\n","base.aoneTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.aoneTo.assign( out, -1, out.length-1 );\nout\n","base.args2multislice":"var args = [ null, null, null ];\nvar s = new base.args2multislice( args );\ns.data\nargs = [ 10, new Slice( 0, 10, 1 ), null ];\ns = new base.args2multislice( args );\ns.data\n","base.asec":"var y = base.asec( 1.0 )\ny = base.asec( 2.0 )\ny = base.asec( NaN )\n","base.asecd":"var y = base.asecd( 0.0 )\ny = base.asecd( 2 )\ny = base.asecd( NaN )\n","base.asecdf":"var y = base.asecdf( 2.0 )\ny = base.asecdf( 0.0 )\ny = base.asecdf( NaN )\n","base.asecf":"var y = base.asecf( 1.0 )\ny = base.asecf( 2.0 )\ny = base.asecf( NaN )\n","base.asech":"var y = base.asech( 1.0 )\ny = base.asech( 0.5 )\ny = base.asech( NaN )\n","base.asin":"var y = base.asin( 0.0 )\ny = base.asin( -PI/6.0 )\ny = base.asin( NaN )\n","base.asind":"var y = base.asind( 0.0 )\ny = base.asind( PI / 6.0 )\ny = base.asind( NaN )\n","base.asindf":"var y = base.asindf( 0.0 )\ny = base.asindf( 3.1415927410125732 / 6.0 )\ny = base.asindf( NaN )\n","base.asinf":"var y = base.asinf( 0.0 )\ny = base.asinf( -3.14/6.0 )\ny = base.asinf( NaN )\n","base.asinh":"var y = base.asinh( 0.0 )\ny = base.asinh( 2.0 )\ny = base.asinh( -2.0 )\ny = base.asinh( NaN )\ny = base.asinh( NINF )\ny = base.asinh( PINF )\n","base.atan":"var y = base.atan( 0.0 )\ny = base.atan( -PI/2.0 )\ny = base.atan( PI/2.0 )\ny = base.atan( NaN )\n","base.atan2":"var v = base.atan2( 2.0, 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)\n","base.azerosnd":"var out = base.azerosnd( [ 1, 3 ] )\n","base.azeroTo":"var arr = base.azeroTo( 6 )\n","base.azeroTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.azeroTo.assign( out, -1, out.length-1 );\nout\n","base.bernoulli":"var y = base.bernoulli( 0 )\ny = base.bernoulli( 1 )\ny = base.bernoulli( 2 )\ny = base.bernoulli( 3 )\ny = base.bernoulli( 4 )\ny = base.bernoulli( 5 )\ny = base.bernoulli( 20 )\ny = base.bernoulli( 260 )\ny = base.bernoulli( 262 )\ny = base.bernoulli( NaN )\n","base.besselj0":"var y = base.besselj0( 0.0 )\ny = base.besselj0( 1.0 )\ny = base.besselj0( PINF )\ny = base.besselj0( NINF )\ny = base.besselj0( NaN )\n","base.besselj1":"var y = base.besselj1( 0.0 )\ny = base.besselj1( 1.0 )\ny = base.besselj1( PINF )\ny = base.besselj1( NINF )\ny = base.besselj1( NaN )\n","base.bessely0":"var y = base.bessely0( 0.0 )\ny = base.bessely0( 1.0 )\ny = base.bessely0( -1.0 )\ny = base.bessely0( PINF )\ny = base.bessely0( NINF )\ny = base.bessely0( NaN )\n","base.bessely1":"var y = base.bessely1( 0.0 )\ny = base.bessely1( 1.0 )\ny = base.bessely1( -1.0 )\ny = base.bessely1( PINF )\ny = base.bessely1( NINF )\ny = base.bessely1( NaN )\n","base.beta":"var v = base.beta( 0.0, 0.5 )\nv = base.beta( 1.0, 1.0 )\nv = base.beta( -1.0, 2.0 )\nv = base.beta( 5.0, 0.2 )\nv = base.beta( 4.0, 1.0 )\nv = base.beta( NaN, 2.0 )\n","base.betainc":"var y = base.betainc( 0.5, 2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, 2.0, false )\ny = base.betainc( 0.2, 1.0, 2.0 )\ny = base.betainc( 0.2, 1.0, 2.0, true, true )\ny = base.betainc( NaN, 1.0, 1.0 )\ny = base.betainc( 0.8, NaN, 1.0 )\ny = base.betainc( 0.8, 1.0, NaN )\ny = base.betainc( 1.5, 1.0, 1.0 )\ny = base.betainc( -0.5, 1.0, 1.0 )\ny = base.betainc( 0.5, -2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, -2.0 )\n","base.betaincinv":"var y = base.betaincinv( 0.2, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0, true )\ny = base.betaincinv( 0.4, 1.0, 6.0 )\ny = base.betaincinv( 0.8, 1.0, 6.0 )\ny = base.betaincinv( NaN, 1.0, 1.0 )\ny = base.betaincinv( 0.5, NaN, 1.0 )\ny = base.betaincinv( 0.5, 1.0, NaN )\ny = base.betaincinv( 1.2, 1.0, 1.0 )\ny = base.betaincinv( -0.5, 1.0, 1.0 )\ny = base.betaincinv( 0.5, -2.0, 2.0 )\ny = base.betaincinv( 0.5, 0.0, 2.0 )\ny = base.betaincinv( 0.5, 2.0, -2.0 )\ny = base.betaincinv( 0.5, 2.0, 0.0 )\n","base.betaln":"var v = base.betaln( 0.0, 0.0 )\nv = base.betaln( 1.0, 1.0 )\nv = base.betaln( -1.0, 2.0 )\nv = base.betaln( 5.0, 0.2 )\nv = base.betaln( 4.0, 1.0 )\nv = base.betaln( NaN, 2.0 )\n","base.binet":"var y = base.binet( 0.0 )\ny = base.binet( 1.0 )\ny = base.binet( 2.0 )\ny = base.binet( 3.0 )\ny = base.binet( 4.0 )\ny = base.binet( 5.0 )\ny = base.binet( NaN )\n","base.binomcoef":"var v = base.binomcoef( 8, 2 )\nv = base.binomcoef( 0, 0 )\nv = base.binomcoef( -4, 2 )\nv = base.binomcoef( 5, 3 )\nv = base.binomcoef( NaN, 3 )\nv = base.binomcoef( 5, NaN )\nv = base.binomcoef( NaN, NaN )\n","base.binomcoefln":"var v = base.binomcoefln( 8, 2 )\nv = base.binomcoefln( 0, 0 )\nv = base.binomcoefln( -4, 2 )\nv = base.binomcoefln( 88, 3 )\nv = base.binomcoefln( NaN, 3 )\nv = base.binomcoefln( 5, NaN )\nv = base.binomcoefln( NaN, NaN )\n","base.boxcox":"var v = base.boxcox( 1.0, 2.5 )\nv = base.boxcox( 4.0, 2.5 )\nv = base.boxcox( 10.0, 2.5 )\nv = base.boxcox( 2.0, 0.0 )\nv = base.boxcox( -1.0, 2.5 )\nv = base.boxcox( 0.0, -1.0 )\n","base.boxcox1p":"var v = base.boxcox1p( 1.0, 2.5 )\nv = base.boxcox1p( 4.0, 2.5 )\nv = base.boxcox1p( 10.0, 2.5 )\nv = base.boxcox1p( 2.0, 0.0 )\nv = base.boxcox1p( -1.0, 2.5 )\nv = base.boxcox1p( 0.0, -1.0 )\nv = base.boxcox1p( -1.0, -1.0 )\n","base.boxcox1pinv":"var v = base.boxcox1pinv( 1.0, 2.5 )\nv = base.boxcox1pinv( 4.0, 2.5 )\nv = base.boxcox1pinv( 10.0, 2.5 )\nv = base.boxcox1pinv( 2.0, 0.0 )\nv = base.boxcox1pinv( -1.0, 2.5 )\nv = base.boxcox1pinv( 0.0, -1.0 )\nv = base.boxcox1pinv( 1.0, NaN )\nv = base.boxcox1pinv( NaN, 3.1 )\n","base.boxcoxinv":"var v = base.boxcoxinv( 1.0, 2.5 )\nv = base.boxcoxinv( 4.0, 2.5 )\nv = base.boxcoxinv( 10.0, 2.5 )\nv = base.boxcoxinv( 2.0, 0.0 )\nv = base.boxcoxinv( -1.0, 2.5 )\nv = base.boxcoxinv( 0.0, -1.0 )\nv = base.boxcoxinv( 1.0, NaN )\nv = base.boxcoxinv( NaN, 3.1 )\n","base.cabs":"var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n","base.cabs2":"var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n","base.cabs2f":"var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n","base.cabsf":"var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n","base.cadd":"var z = new Complex128( 5.0, 3.0 )\nvar out = base.cadd( z, z )\nvar re = real( out )\nvar im = imag( out )\n","base.cadd.assign":"var out = new Float64Array( 2 );\nbase.cadd.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.cadd.strided":"var z1 = new Float64Array( [ 5.0, 3.0 ] );\nvar z2 = new Float64Array( [ -2.0, 1.0 ] );\nvar out = new Float64Array( 2 );\nbase.cadd.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.caddf":"var z = new Complex64( 5.0, 3.0 )\nvar out = base.caddf( z, z )\nvar re = realf( out )\nvar im = imagf( out )\n","base.caddf.assign":"var out = new Float32Array( 2 );\nbase.caddf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.caddf.strided":"var z1 = new Float32Array( [ 5.0, 3.0 ] );\nvar z2 = new Float32Array( [ -2.0, 1.0 ] );\nvar out = new Float32Array( 2 );\nbase.caddf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.camelcase":"var out = base.camelcase( 'Hello World!' )\nout = base.camelcase( 'beep boop' )\n","base.capitalize":"var out = base.capitalize( 'beep' )\nout = base.capitalize( 'Boop' )\n","base.cbrt":"var y = base.cbrt( 64.0 )\ny = base.cbrt( 27.0 )\ny = base.cbrt( 0.0 )\ny = base.cbrt( -0.0 )\ny = base.cbrt( -9.0 )\ny = base.cbrt( NaN )\n","base.cbrtf":"var y = base.cbrtf( 64.0 )\ny = base.cbrtf( 27.0 )\ny = base.cbrtf( 0.0 )\ny = base.cbrtf( -0.0 )\ny = base.cbrtf( -9.0 )\ny = base.cbrtf( NaN )\n","base.cceil":"var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n","base.cceilf":"var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n","base.cceiln":"var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n","base.ccis":"var y = base.ccis( new Complex128( 0.0, 0.0 ) )\ny = base.ccis( new Complex128( 1.0, 0.0 ) )\n","base.cdiv":"var z1 = new Complex128( -13.0, -1.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar y = base.cdiv( z1, z2 )\nvar re = real( y )\nvar im = imag( y )\n","base.cdiv.assign":"var out = new Float64Array( 2 );\nbase.cdiv.assign( -13.0, -1.0, -2.0, 1.0, out, 1, 0 )\n","base.cdiv.strided":"var z1 = new Float64Array( [ -13.0, -1.0 ] );\nvar z2 = new Float64Array( [ -2.0, 1.0 ] );\nvar out = new Float64Array( 2 );\nbase.cdiv.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.ceil":"var y = base.ceil( 3.14 )\ny = base.ceil( -4.2 )\ny = base.ceil( -4.6 )\ny = base.ceil( 9.5 )\ny = base.ceil( -0.0 )\n","base.ceil2":"var y = base.ceil2( 3.14 )\ny = base.ceil2( -4.2 )\ny = base.ceil2( -4.6 )\ny = base.ceil2( 9.5 )\ny = base.ceil2( 13.0 )\ny = base.ceil2( -13.0 )\ny = base.ceil2( -0.0 )\n","base.ceil10":"var y = base.ceil10( 3.14 )\ny = base.ceil10( -4.2 )\ny = base.ceil10( -4.6 )\ny = base.ceil10( 9.5 )\ny = base.ceil10( 13.0 )\ny = base.ceil10( -13.0 )\ny = base.ceil10( -0.0 )\n","base.ceilb":"var y = base.ceilb( 3.14159, -4, 10 )\ny = base.ceilb( 3.14159, 0, 2 )\ny = base.ceilb( 5.0, 1, 2 )\n","base.ceilf":"var y = base.ceilf( 3.14 )\ny = base.ceilf( -4.2 )\ny = base.ceilf( -4.6 )\ny = base.ceilf( 9.5 )\ny = base.ceilf( -0.0 )\n","base.ceiln":"var y = base.ceiln( 3.14159, -2 )\ny = base.ceiln( 3.14159, 0 )\ny = base.ceiln( 12368.0, 3 )\n","base.ceilsd":"var y = base.ceilsd( 3.14159, 5, 10 )\ny = base.ceilsd( 3.14159, 1, 10 )\ny = base.ceilsd( 12368.0, 2, 10 )\ny = base.ceilsd( 0.0313, 2, 2 )\n","base.cexp":"var y = base.cexp( new Complex128( 0.0, 0.0 ) )\ny = base.cexp( new Complex128( 0.0, 1.0 ) )\n","base.cflipsign":"var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\n","base.cflipsignf":"var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\n","base.cfloor":"var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\n","base.cfloorn":"var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\n","base.cidentity":"var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\nvar re = real( v )\nvar img = imag( v )\n","base.cidentityf":"var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\nvar re = realf( v )\nvar img = imagf( v )\n","base.cinv":"var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n","base.cinvf":"var v = base.cinvf( new Complex64( 2.0, 4.0 ) )\n","base.clamp":"var y = base.clamp( 3.14, 0.0, 5.0 )\ny = base.clamp( -3.14, 0.0, 5.0 )\ny = base.clamp( 3.14, 0.0, 3.0 )\ny = base.clamp( -0.0, 0.0, 5.0 )\ny = base.clamp( 0.0, -3.14, -0.0 )\ny = base.clamp( NaN, 0.0, 5.0 )\n","base.clampf":"var y = base.clampf( 3.14, 0.0, 5.0 )\ny = base.clampf( -3.14, 0.0, 5.0 )\ny = base.clampf( 3.14, 0.0, 3.0 )\ny = base.clampf( -0.0, 0.0, 5.0 )\ny = base.clampf( 0.0, -3.14, -0.0 )\ny = base.clampf( NaN, 0.0, 5.0 )\n","base.cmul":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.cmul( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.cmul.assign":"var out = new Float64Array( 2 );\nbase.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.cmul.strided":"var z1 = new Float64Array( [ 5.0, 3.0 ] );\nvar z2 = new Float64Array( [ -2.0, 1.0 ] );\nvar out = new Float64Array( 2 );\nbase.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.cmulf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.cmulf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.cmulf.assign":"var out = new Float32Array( 2 );\nbase.cmulf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.cmulf.strided":"var z1 = new Float32Array( [ 5.0, 3.0 ] );\nvar z2 = new Float32Array( [ -2.0, 1.0 ] );\nvar out = new Float32Array( 2 );\nbase.cmulf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.cneg":"var z = new Complex128( -4.2, 5.5 )\nvar v = base.cneg( z )\nvar re = real( v )\nvar im = imag( v )\n","base.cnegf":"var z = new Complex64( -4.0, 5.0 )\nvar v = base.cnegf( z )\nvar re = realf( v )\nvar im = imagf( v )\n","base.codePointAt":"var out = base.codePointAt( 'last man standing', 4, false )\nout = base.codePointAt( 'presidential election', 8, true )\nout = base.codePointAt( 'अनुच्छेद', 2, false )\nout = base.codePointAt( '🌷', 1, true )\n","base.constantcase":"var out = base.constantcase( 'Hello World!' )\nout = base.constantcase( 'I am a tiny little teapot' )\n","base.continuedFraction":"function closure() {\nvar i = 0;\nreturn function() {\n i += 1;\n return [ i, i ];\n};\n };\nvar gen = closure();\nvar out = base.continuedFraction( gen )\nfunction* generator() {\n var i = 0;\n while ( true ) {\n i += 1;\n yield [ i, i ];\n }\n };\ngen = generator();\nout = base.continuedFraction( gen )\nout = base.continuedFraction( generator(), { 'keep': true } )\nout = base.continuedFraction( generator(), { 'maxIter': 10 } )\nout = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n","base.copysign":"var z = base.copysign( -3.14, 10.0 )\nz = base.copysign( 3.14, -1.0 )\nz = base.copysign( 1.0, -0.0 )\nz = base.copysign( -3.14, -0.0 )\nz = base.copysign( -0.0, 1.0 )\n","base.copysignf":"var z = base.copysignf( -3.0, 10.0 )\nz = base.copysignf( 3.0, -1.0 )\nz = base.copysignf( 1.0, -0.0 )\nz = base.copysignf( -3.0, -0.0 )\nz = base.copysignf( -0.0, 1.0 )\n","base.cos":"var y = base.cos( 0.0 )\ny = base.cos( PI/4.0 )\ny = base.cos( -PI/6.0 )\ny = base.cos( NaN )\n","base.cosd":"var y = base.cosd( 0.0 )\ny = base.cosd( 90.0 )\ny = base.cosd( 60.0 )\ny = base.cosd( NaN )\n","base.cosh":"var y = base.cosh( 0.0 )\ny = base.cosh( 2.0 )\ny = base.cosh( -2.0 )\ny = base.cosh( NaN )\n","base.cosm1":"var y = base.cosm1( 0.0 )\ny = base.cosm1( PI/4.0 )\ny = base.cosm1( -PI/6.0 )\ny = base.cosm1( NaN )\n","base.cospi":"var y = base.cospi( 0.0 )\ny = base.cospi( 0.5 )\ny = base.cospi( 0.1 )\ny = 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base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.pdf.factory":"var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.arcsine.quantile":"var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\ny = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n","base.dists.arcsine.quantile.factory":"var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.arcsine.skewness":"var v = base.dists.arcsine.skewness( 0.0, 1.0 )\nv = base.dists.arcsine.skewness( 4.0, 12.0 )\nv = base.dists.arcsine.skewness( 2.0, 8.0 )\n","base.dists.arcsine.stdev":"var v = base.dists.arcsine.stdev( 0.0, 1.0 )\nv = base.dists.arcsine.stdev( 4.0, 12.0 )\nv = base.dists.arcsine.stdev( 2.0, 8.0 )\n","base.dists.arcsine.variance":"var v = base.dists.arcsine.variance( 0.0, 1.0 )\nv = base.dists.arcsine.variance( 4.0, 12.0 )\nv = base.dists.arcsine.variance( 2.0, 8.0 )\n","base.dists.bernoulli.Bernoulli":"var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\nbernoulli.p\nbernoulli.entropy\nbernoulli.kurtosis\nbernoulli.mean\nbernoulli.median\nbernoulli.skewness\nbernoulli.stdev\nbernoulli.variance\nbernoulli.cdf( 0.5 )\nbernoulli.mgf( 3.0 )\nbernoulli.pmf( 0.0 )\nbernoulli.quantile( 0.7 )\n","base.dists.bernoulli.cdf":"var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\ny = base.dists.bernoulli.cdf( 0.8, 0.1 )\ny = base.dists.bernoulli.cdf( -1.0, 0.4 )\ny = base.dists.bernoulli.cdf( 1.5, 0.4 )\ny = base.dists.bernoulli.cdf( NaN, 0.5 )\ny = base.dists.bernoulli.cdf( 0.0, NaN )\ny = base.dists.bernoulli.cdf( 2.0, 1.4 )\n","base.dists.bernoulli.cdf.factory":"var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 0.7 )\n","base.dists.bernoulli.entropy":"var v = base.dists.bernoulli.entropy( 0.1 )\nv = base.dists.bernoulli.entropy( 0.5 )\n","base.dists.bernoulli.kurtosis":"var v = base.dists.bernoulli.kurtosis( 0.1 )\nv = base.dists.bernoulli.kurtosis( 0.5 )\n","base.dists.bernoulli.mean":"var v = base.dists.bernoulli.mean( 0.1 )\nv = base.dists.bernoulli.mean( 0.5 )\n","base.dists.bernoulli.median":"var v = base.dists.bernoulli.median( 0.1 )\nv = base.dists.bernoulli.median( 0.8 )\n","base.dists.bernoulli.mgf":"var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\ny = base.dists.bernoulli.mgf( 0.4, 0.5 )\ny = base.dists.bernoulli.mgf( NaN, 0.0 )\ny = base.dists.bernoulli.mgf( 0.0, NaN )\ny = base.dists.bernoulli.mgf( -2.0, -1.0 )\ny = base.dists.bernoulli.mgf( 0.2, 2.0 )\n","base.dists.bernoulli.mgf.factory":"var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.bernoulli.mode":"var v = base.dists.bernoulli.mode( 0.1 )\nv = base.dists.bernoulli.mode( 0.8 )\n","base.dists.bernoulli.pmf":"var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\ny = base.dists.bernoulli.pmf( 0.0, 0.7 )\ny = base.dists.bernoulli.pmf( -1.0, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, NaN )\ny = base.dists.bernoulli.pmf( NaN, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, 1.5 )\n","base.dists.bernoulli.pmf.factory":"var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\nvar y = mypmf( 1.0 )\ny = mypmf( 0.0 )\n","base.dists.bernoulli.quantile":"var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\ny = base.dists.bernoulli.quantile( 0.5, 0.4 )\ny = base.dists.bernoulli.quantile( 0.9, 0.1 )\ny = base.dists.bernoulli.quantile( -0.2, 0.1 )\ny = base.dists.bernoulli.quantile( NaN, 0.8 )\ny = base.dists.bernoulli.quantile( 0.4, NaN )\ny = base.dists.bernoulli.quantile( 0.5, -1.0 )\ny = base.dists.bernoulli.quantile( 0.5, 1.5 )\n","base.dists.bernoulli.quantile.factory":"var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.bernoulli.skewness":"var v = base.dists.bernoulli.skewness( 0.1 )\nv = base.dists.bernoulli.skewness( 0.5 )\n","base.dists.bernoulli.stdev":"var v = base.dists.bernoulli.stdev( 0.1 )\nv = base.dists.bernoulli.stdev( 0.5 )\n","base.dists.bernoulli.variance":"var v = base.dists.bernoulli.variance( 0.1 )\nv = base.dists.bernoulli.variance( 0.5 )\n","base.dists.beta.Beta":"var beta = base.dists.beta.Beta( 1.0, 1.0 );\nbeta.alpha\nbeta.beta\nbeta.entropy\nbeta.kurtosis\nbeta.mean\nbeta.median\nbeta.mode\nbeta.skewness\nbeta.stdev\nbeta.variance\nbeta.cdf( 0.8 )\nbeta.logcdf( 0.8 )\nbeta.logpdf( 1.0 )\nbeta.mgf( 3.14 )\nbeta.pdf( 1.0 )\nbeta.quantile( 0.8 )\n","base.dists.beta.cdf":"var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.cdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.cdf( 0.0, 1.0, NaN )\n","base.dists.beta.cdf.factory":"var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.beta.entropy":"var v = base.dists.beta.entropy( 1.0, 1.0 )\nv = base.dists.beta.entropy( 4.0, 12.0 )\nv = base.dists.beta.entropy( 8.0, 2.0 )\nv = base.dists.beta.entropy( 1.0, -0.1 )\nv = base.dists.beta.entropy( -0.1, 1.0 )\nv = base.dists.beta.entropy( 2.0, NaN )\nv = base.dists.beta.entropy( NaN, 2.0 )\n","base.dists.beta.kurtosis":"var v = base.dists.beta.kurtosis( 1.0, 1.0 )\nv = base.dists.beta.kurtosis( 4.0, 12.0 )\nv = base.dists.beta.kurtosis( 8.0, 2.0 )\nv = base.dists.beta.kurtosis( 1.0, -0.1 )\nv = base.dists.beta.kurtosis( -0.1, 1.0 )\nv = base.dists.beta.kurtosis( 2.0, NaN )\nv = base.dists.beta.kurtosis( NaN, 2.0 )\n","base.dists.beta.logcdf":"var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n","base.dists.beta.logcdf.factory":"var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.beta.logpdf":"var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n","base.dists.beta.logpdf.factory":"var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.beta.mean":"var v = base.dists.beta.mean( 1.0, 1.0 )\nv = base.dists.beta.mean( 4.0, 12.0 )\nv = base.dists.beta.mean( 8.0, 2.0 )\n","base.dists.beta.median":"var v = base.dists.beta.median( 1.0, 1.0 )\nv = base.dists.beta.median( 4.0, 12.0 )\nv = base.dists.beta.median( 8.0, 2.0 )\nv = base.dists.beta.median( 1.0, -0.1 )\nv = base.dists.beta.median( -0.1, 1.0 )\nv = base.dists.beta.median( 2.0, NaN )\nv = base.dists.beta.median( NaN, 2.0 )\n","base.dists.beta.mgf":"var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\ny = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\ny = base.dists.beta.mgf( NaN, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.0, NaN, 1.0 )\ny = base.dists.beta.mgf( 0.0, 1.0, NaN )\ny = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n","base.dists.beta.mgf.factory":"var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.3 )\n","base.dists.beta.mode":"var v = base.dists.beta.mode( 4.0, 12.0 )\nv = base.dists.beta.mode( 8.0, 2.0 )\nv = base.dists.beta.mode( 1.0, 1.0 )\n","base.dists.beta.pdf":"var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 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= base.dists.beta.skewness( 1.0, 1.0 )\nv = base.dists.beta.skewness( 4.0, 12.0 )\nv = base.dists.beta.skewness( 8.0, 2.0 )\nv = base.dists.beta.skewness( 1.0, -0.1 )\nv = base.dists.beta.skewness( -0.1, 1.0 )\nv = base.dists.beta.skewness( 2.0, NaN )\nv = base.dists.beta.skewness( NaN, 2.0 )\n","base.dists.beta.stdev":"var v = base.dists.beta.stdev( 1.0, 1.0 )\nv = base.dists.beta.stdev( 4.0, 12.0 )\nv = base.dists.beta.stdev( 8.0, 2.0 )\nv = base.dists.beta.stdev( 1.0, -0.1 )\nv = base.dists.beta.stdev( -0.1, 1.0 )\nv = base.dists.beta.stdev( 2.0, NaN )\nv = base.dists.beta.stdev( NaN, 2.0 )\n","base.dists.beta.variance":"var v = base.dists.beta.variance( 1.0, 1.0 )\nv = base.dists.beta.variance( 4.0, 12.0 )\nv = base.dists.beta.variance( 8.0, 2.0 )\nv = base.dists.beta.variance( 1.0, -0.1 )\nv = base.dists.beta.variance( -0.1, 1.0 )\nv = base.dists.beta.variance( 2.0, NaN )\nv = base.dists.beta.variance( NaN, 2.0 )\n","base.dists.betaprime.BetaPrime":"var betaprime = 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base.dists.betaprime.kurtosis( 2.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 4.0, 12.0 )\nv = base.dists.betaprime.kurtosis( 8.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 1.0, 2.8 )\nv = base.dists.betaprime.kurtosis( 1.0, -0.1 )\nv = base.dists.betaprime.kurtosis( -0.1, 5.0 )\nv = base.dists.betaprime.kurtosis( 2.0, NaN )\nv = base.dists.betaprime.kurtosis( NaN, 6.0 )\n","base.dists.betaprime.logcdf":"var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.logcdf.factory":"var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.betaprime.logpdf":"var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.logpdf.factory":"var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.betaprime.mean":"var v = base.dists.betaprime.mean( 1.0, 2.0 )\nv = base.dists.betaprime.mean( 4.0, 12.0 )\nv = base.dists.betaprime.mean( 8.0, 2.0 )\n","base.dists.betaprime.mode":"var v = base.dists.betaprime.mode( 1.0, 2.0 )\nv = base.dists.betaprime.mode( 4.0, 12.0 )\nv = base.dists.betaprime.mode( 8.0, 2.0 )\n","base.dists.betaprime.pdf":"var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.pdf.factory":"var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.betaprime.quantile":"var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\ny = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n","base.dists.betaprime.quantile.factory":"var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\ny = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.betaprime.skewness":"var v = base.dists.betaprime.skewness( 2.0, 4.0 )\nv = base.dists.betaprime.skewness( 4.0, 12.0 )\nv = base.dists.betaprime.skewness( 8.0, 4.0 )\nv = base.dists.betaprime.skewness( 1.0, 2.8 )\nv = base.dists.betaprime.skewness( 1.0, -0.1 )\nv = base.dists.betaprime.skewness( -0.1, 4.0 )\nv = base.dists.betaprime.skewness( 2.0, NaN )\nv = base.dists.betaprime.skewness( NaN, 4.0 )\n","base.dists.betaprime.stdev":"var v = base.dists.betaprime.stdev( 1.0, 2.5 )\nv = base.dists.betaprime.stdev( 4.0, 12.0 )\nv = base.dists.betaprime.stdev( 8.0, 2.5 )\nv = base.dists.betaprime.stdev( 8.0, 1.0 )\nv = base.dists.betaprime.stdev( 1.0, -0.1 )\nv = base.dists.betaprime.stdev( -0.1, 3.0 )\nv = base.dists.betaprime.stdev( 2.0, NaN )\nv = base.dists.betaprime.stdev( NaN, 3.0 )\n","base.dists.betaprime.variance":"var v = base.dists.betaprime.variance( 1.0, 2.5 )\nv = base.dists.betaprime.variance( 4.0, 12.0 )\nv = base.dists.betaprime.variance( 8.0, 2.5 )\nv = base.dists.betaprime.variance( 8.0, 1.0 )\nv = base.dists.betaprime.variance( 1.0, -0.1 )\nv = base.dists.betaprime.variance( -0.1, 3.0 )\nv = base.dists.betaprime.variance( 2.0, NaN )\nv = base.dists.betaprime.variance( NaN, 3.0 )\n","base.dists.binomial.Binomial":"var binomial = base.dists.binomial.Binomial( 8, 0.5 );\nbinomial.n\nbinomial.p\nbinomial.kurtosis\nbinomial.mean\nbinomial.median\nbinomial.mode\nbinomial.skewness\nbinomial.stdev\nbinomial.variance\nbinomial.cdf( 2.9 )\nbinomial.logpmf( 3.0 )\nbinomial.mgf( 0.2 )\nbinomial.pmf( 3.0 )\nbinomial.quantile( 0.8 )\n","base.dists.binomial.cdf":"var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 21.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 5.0, 10, 0.4 )\ny = base.dists.binomial.cdf( 0.0, 10, 0.4 )\ny = base.dists.binomial.cdf( NaN, 20, 0.5 )\ny = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.cdf( 0.0, 20, NaN )\ny = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n","base.dists.binomial.cdf.factory":"var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.binomial.entropy":"var v = base.dists.binomial.entropy( 100, 0.1 )\nv = base.dists.binomial.entropy( 20, 0.5 )\nv = base.dists.binomial.entropy( 10.3, 0.5 )\nv = base.dists.binomial.entropy( 20, 1.1 )\nv = base.dists.binomial.entropy( 20, NaN )\n","base.dists.binomial.kurtosis":"var v = base.dists.binomial.kurtosis( 100, 0.1 )\nv = base.dists.binomial.kurtosis( 20, 0.5 )\nv = base.dists.binomial.kurtosis( 10.3, 0.5 )\nv = base.dists.binomial.kurtosis( 20, 1.1 )\nv = base.dists.binomial.kurtosis( 20, NaN )\n","base.dists.binomial.logpmf":"var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( NaN, 20, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, 20, NaN )\ny = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n","base.dists.binomial.logpmf.factory":"var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 5.0 )\n","base.dists.binomial.mean":"var v = base.dists.binomial.mean( 100, 0.1 )\nv = base.dists.binomial.mean( 20, 0.5 )\nv = base.dists.binomial.mean( 10.3, 0.5 )\nv = base.dists.binomial.mean( 20, 1.1 )\nv = base.dists.binomial.mean( 20, NaN )\n","base.dists.binomial.median":"var v = base.dists.binomial.median( 100, 0.1 )\nv = base.dists.binomial.median( 20, 0.5 )\nv = base.dists.binomial.median( 10.3, 0.5 )\nv = base.dists.binomial.median( 20, 1.1 )\nv = base.dists.binomial.median( 20, NaN )\n","base.dists.binomial.mgf":"var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\ny = base.dists.binomial.mgf( 5.0, 20, 0.2 )\ny = base.dists.binomial.mgf( 0.9, 10, 0.4 )\ny = base.dists.binomial.mgf( 0.0, 10, 0.4 )\ny = base.dists.binomial.mgf( NaN, 20, 0.5 )\ny = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.mgf( 0.0, 20, NaN )\ny = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.mgf( 2.0, 20, -1.0 )\ny = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n","base.dists.binomial.mgf.factory":"var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\nvar y = myMGF( 0.3 )\n","base.dists.binomial.mode":"var v = base.dists.binomial.mode( 100, 0.1 )\nv = base.dists.binomial.mode( 20, 0.5 )\nv = base.dists.binomial.mode( 10.3, 0.5 )\nv = base.dists.binomial.mode( 20, 1.1 )\nv = base.dists.binomial.mode( 20, NaN )\n","base.dists.binomial.pmf":"var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.pmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.pmf( NaN, 20, 0.5 )\ny = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.pmf( 0.0, 20, NaN )\ny = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n","base.dists.binomial.pmf.factory":"var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 5.0 )\n","base.dists.binomial.quantile":"var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.8, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.5, 10, 0.4 )\ny = base.dists.binomial.quantile( 0.0, 10, 0.4 )\ny = base.dists.binomial.quantile( 1.0, 10, 0.4 )\ny = base.dists.binomial.quantile( NaN, 20, 0.5 )\ny = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\ny = base.dists.binomial.quantile( 0.2, 20, NaN )\ny = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\ny = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.binomial.quantile( 0.5, 20, -1.0 )\ny = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n","base.dists.binomial.quantile.factory":"var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\nvar y = myquantile( 0.1 )\ny = myquantile( 0.9 )\n","base.dists.binomial.skewness":"var v = base.dists.binomial.skewness( 100, 0.1 )\nv = base.dists.binomial.skewness( 20, 0.5 )\nv = base.dists.binomial.skewness( 10.3, 0.5 )\nv = base.dists.binomial.skewness( 20, 1.1 )\nv = base.dists.binomial.skewness( 20, NaN )\n","base.dists.binomial.stdev":"var v = base.dists.binomial.stdev( 100, 0.1 )\nv = base.dists.binomial.stdev( 20, 0.5 )\nv = base.dists.binomial.stdev( 10.3, 0.5 )\nv = base.dists.binomial.stdev( 20, 1.1 )\nv = base.dists.binomial.stdev( 20, NaN )\n","base.dists.binomial.variance":"var v = base.dists.binomial.variance( 100, 0.1 )\nv = base.dists.binomial.variance( 20, 0.5 )\nv = base.dists.binomial.variance( 10.3, 0.5 )\nv = base.dists.binomial.variance( 20, 1.1 )\nv = base.dists.binomial.variance( 20, NaN )\n","base.dists.cauchy.Cauchy":"var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\ncauchy.x0\ncauchy.gamma\ncauchy.entropy\ncauchy.median\ncauchy.mode\ncauchy.cdf( 0.8 )\ncauchy.logcdf( 1.0 )\ncauchy.logpdf( 1.0 )\ncauchy.pdf( 1.0 )\ncauchy.quantile( 0.8 )\n","base.dists.cauchy.cdf":"var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.cdf.factory":"var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\nvar y = myCDF( 1.0 )\n","base.dists.cauchy.entropy":"var v = base.dists.cauchy.entropy( 10.0, 7.0 )\nv = base.dists.cauchy.entropy( 22.0, 0.5 )\nv = base.dists.cauchy.entropy( 10.3, -0.5 )\n","base.dists.cauchy.logcdf":"var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.logcdf.factory":"var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\nvar y = mylogCDF( 1.0 )\n","base.dists.cauchy.logpdf":"var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.logpdf.factory":"var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.cauchy.median":"var v = base.dists.cauchy.median( 10.0, 5.0 )\nv = base.dists.cauchy.median( 7.0, 0.5 )\nv = base.dists.cauchy.median( 10.3, -0.5 )\n","base.dists.cauchy.mode":"var v = base.dists.cauchy.mode( 10.0, 5.0 )\nv = base.dists.cauchy.mode( 7.0, 0.5 )\nv = base.dists.cauchy.mode( 10.3, -0.5 )\n","base.dists.cauchy.pdf":"var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.pdf.factory":"var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.cauchy.quantile":"var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\ny = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\ny = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\ny = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\ny = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cauchy.quantile.factory":"var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.chi.cdf":"var y = base.dists.chi.cdf( 2.0, 3.0 )\ny = base.dists.chi.cdf( 1.0, 0.5 )\ny = base.dists.chi.cdf( -1.0, 4.0 )\ny = base.dists.chi.cdf( NaN, 1.0 )\ny = base.dists.chi.cdf( 0.0, NaN )\ny = base.dists.chi.cdf( 2.0, -1.0 )\ny = base.dists.chi.cdf( 2.0, 0.0 )\ny = base.dists.chi.cdf( -2.0, 0.0 )\ny = base.dists.chi.cdf( 0.0, 0.0 )\n","base.dists.chi.cdf.factory":"var mycdf = base.dists.chi.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chi.Chi":"var chi = base.dists.chi.Chi( 6.0 );\nchi.k\nchi.entropy\nchi.kurtosis\nchi.mean\nchi.mode\nchi.skewness\nchi.stdev\nchi.variance\nchi.cdf( 1.0 )\nchi.logpdf( 1.5 )\nchi.pdf( 1.5 )\nchi.quantile( 0.5 )\n","base.dists.chi.entropy":"var v = base.dists.chi.entropy( 11.0 )\nv = base.dists.chi.entropy( 1.5 )\n","base.dists.chi.kurtosis":"var v = base.dists.chi.kurtosis( 9.0 )\nv = base.dists.chi.kurtosis( 1.5 )\n","base.dists.chi.logpdf":"var y = base.dists.chi.logpdf( 0.3, 4.0 )\ny = base.dists.chi.logpdf( 0.7, 0.7 )\ny = base.dists.chi.logpdf( -1.0, 0.5 )\ny = base.dists.chi.logpdf( 0.0, NaN )\ny = base.dists.chi.logpdf( NaN, 2.0 )\ny = base.dists.chi.logpdf( 2.0, -1.0 )\ny = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.logpdf.factory":"var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\nvar y = mylogPDF( 3.0 )\n","base.dists.chi.mean":"var v = base.dists.chi.mean( 11.0 )\nv = base.dists.chi.mean( 4.5 )\n","base.dists.chi.mode":"var v = base.dists.chi.mode( 11.0 )\nv = base.dists.chi.mode( 1.5 )\n","base.dists.chi.pdf":"var y = base.dists.chi.pdf( 0.3, 4.0 )\ny = base.dists.chi.pdf( 0.7, 0.7 )\ny = base.dists.chi.pdf( -1.0, 0.5 )\ny = base.dists.chi.pdf( 0.0, NaN )\ny = base.dists.chi.pdf( NaN, 2.0 )\ny = base.dists.chi.pdf( 2.0, -1.0 )\ny = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.pdf.factory":"var myPDF = base.dists.chi.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chi.quantile":"var y = base.dists.chi.quantile( 0.8, 1.0 )\ny = base.dists.chi.quantile( 0.5, 4.0 )\ny = base.dists.chi.quantile( 0.8, 0.1 )\ny = base.dists.chi.quantile( -0.2, 0.5 )\ny = base.dists.chi.quantile( 1.1, 0.5 )\ny = base.dists.chi.quantile( NaN, 1.0 )\ny = base.dists.chi.quantile( 0.0, NaN )\ny = base.dists.chi.quantile( 0.5, -1.0 )\ny = base.dists.chi.quantile( 0.3, 0.0 )\ny = base.dists.chi.quantile( 0.9, 0.0 )\n","base.dists.chi.quantile.factory":"var myquantile = base.dists.chi.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chi.skewness":"var v = base.dists.chi.skewness( 11.0 )\nv = base.dists.chi.skewness( 1.5 )\n","base.dists.chi.stdev":"var v = base.dists.chi.stdev( 11.0 )\nv = base.dists.chi.stdev( 1.5 )\n","base.dists.chi.variance":"var v = base.dists.chi.variance( 11.0 )\nv = base.dists.chi.variance( 1.5 )\n","base.dists.chisquare.cdf":"var y = base.dists.chisquare.cdf( 2.0, 3.0 )\ny = base.dists.chisquare.cdf( 1.0, 0.5 )\ny = base.dists.chisquare.cdf( -1.0, 4.0 )\ny = base.dists.chisquare.cdf( NaN, 1.0 )\ny = base.dists.chisquare.cdf( 0.0, NaN )\ny = base.dists.chisquare.cdf( 2.0, -1.0 )\ny = base.dists.chisquare.cdf( 2.0, 0.0 )\ny = base.dists.chisquare.cdf( -2.0, 0.0 )\ny = base.dists.chisquare.cdf( 0.0, 0.0 )\n","base.dists.chisquare.cdf.factory":"var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chisquare.ChiSquare":"var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\nchisquare.k\nchisquare.entropy\nchisquare.kurtosis\nchisquare.mean\nchisquare.median\nchisquare.mode\nchisquare.skewness\nchisquare.stdev\nchisquare.variance\nchisquare.cdf( 3.0 )\nchisquare.mgf( 0.2 )\nchisquare.pdf( 1.5 )\nchisquare.quantile( 0.5 )\n","base.dists.chisquare.entropy":"var v = base.dists.chisquare.entropy( 11.0 )\nv = base.dists.chisquare.entropy( 1.5 )\n","base.dists.chisquare.kurtosis":"var v = base.dists.chisquare.kurtosis( 9.0 )\nv = base.dists.chisquare.kurtosis( 1.5 )\n","base.dists.chisquare.logpdf":"var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\ny = base.dists.chisquare.logpdf( 0.7, 0.7 )\ny = base.dists.chisquare.logpdf( -1.0, 0.5 )\ny = base.dists.chisquare.logpdf( 0.0, NaN )\ny = base.dists.chisquare.logpdf( NaN, 2.0 )\ny = base.dists.chisquare.logpdf( 2.0, -1.0 )\ny = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.logpdf.factory":"var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\nvar y = myLogPDF( 3.0 )\n","base.dists.chisquare.mean":"var v = base.dists.chisquare.mean( 11.0 )\nv = base.dists.chisquare.mean( 4.5 )\n","base.dists.chisquare.median":"var k = base.dists.chisquare.median( 9.0 )\nk = base.dists.chisquare.median( 2.0 )\n","base.dists.chisquare.mgf":"var y = base.dists.chisquare.mgf( 0.4, 2 )\ny = base.dists.chisquare.mgf( -1.0, 5.0 )\ny = base.dists.chisquare.mgf( 0.0, 10.0 )\n","base.dists.chisquare.mgf.factory":"var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.chisquare.mode":"var v = base.dists.chisquare.mode( 11.0 )\nv = base.dists.chisquare.mode( 1.5 )\n","base.dists.chisquare.pdf":"var y = base.dists.chisquare.pdf( 0.3, 4.0 )\ny = base.dists.chisquare.pdf( 0.7, 0.7 )\ny = base.dists.chisquare.pdf( -1.0, 0.5 )\ny = base.dists.chisquare.pdf( 0.0, NaN )\ny = base.dists.chisquare.pdf( NaN, 2.0 )\ny = base.dists.chisquare.pdf( 2.0, -1.0 )\ny = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.pdf.factory":"var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chisquare.quantile":"var y = base.dists.chisquare.quantile( 0.8, 1.0 )\ny = base.dists.chisquare.quantile( 0.5, 4.0 )\ny = base.dists.chisquare.quantile( 0.8, 0.1 )\ny = base.dists.chisquare.quantile( -0.2, 0.5 )\ny = base.dists.chisquare.quantile( 1.1, 0.5 )\ny = base.dists.chisquare.quantile( NaN, 1.0 )\ny = base.dists.chisquare.quantile( 0.0, NaN )\ny = base.dists.chisquare.quantile( 0.5, -1.0 )\ny = base.dists.chisquare.quantile( 0.3, 0.0 )\ny = base.dists.chisquare.quantile( 0.9, 0.0 )\n","base.dists.chisquare.quantile.factory":"var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chisquare.skewness":"var v = base.dists.chisquare.skewness( 11.0 )\nv = base.dists.chisquare.skewness( 1.5 )\n","base.dists.chisquare.stdev":"var v = base.dists.chisquare.stdev( 11.0 )\nv = base.dists.chisquare.stdev( 1.5 )\n","base.dists.chisquare.variance":"var v = base.dists.chisquare.variance( 11.0 )\nv = base.dists.chisquare.variance( 1.5 )\n","base.dists.cosine.cdf":"var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.cdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.cdf.factory":"var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.9 )\n","base.dists.cosine.Cosine":"var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\ncosine.mu\ncosine.s\ncosine.kurtosis\ncosine.mean\ncosine.median\ncosine.mode\ncosine.skewness\ncosine.stdev\ncosine.variance\ncosine.cdf( 0.5 )\ncosine.logcdf( 0.5 )\ncosine.logpdf( -1.0 )\ncosine.mgf( 0.2 )\ncosine.pdf( -2.0 )\ncosine.quantile( 0.9 )\n","base.dists.cosine.kurtosis":"var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\ny = base.dists.cosine.kurtosis( 4.0, 2.0 )\ny = base.dists.cosine.kurtosis( NaN, 1.0 )\ny = base.dists.cosine.kurtosis( 0.0, NaN )\ny = base.dists.cosine.kurtosis( 0.0, 0.0 )\n","base.dists.cosine.logcdf":"var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.logcdf.factory":"var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.9 )\n","base.dists.cosine.logpdf":"var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\ny = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.logpdf.factory":"var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.cosine.mean":"var y = base.dists.cosine.mean( 0.0, 1.0 )\ny = base.dists.cosine.mean( 4.0, 2.0 )\ny = base.dists.cosine.mean( NaN, 1.0 )\ny = base.dists.cosine.mean( 0.0, NaN )\ny = base.dists.cosine.mean( 0.0, 0.0 )\n","base.dists.cosine.median":"var y = base.dists.cosine.median( 0.0, 1.0 )\ny = base.dists.cosine.median( 4.0, 2.0 )\ny = base.dists.cosine.median( NaN, 1.0 )\ny = base.dists.cosine.median( 0.0, NaN )\ny = base.dists.cosine.median( 0.0, 0.0 )\n","base.dists.cosine.mgf":"var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.mgf( 0.5, 0.0, NaN )\ny = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\ny = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n","base.dists.cosine.mgf.factory":"var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\nvar y = mymgf( 1.9 )\n","base.dists.cosine.mode":"var y = base.dists.cosine.mode( 0.0, 1.0 )\ny = base.dists.cosine.mode( 4.0, 2.0 )\ny = base.dists.cosine.mode( NaN, 1.0 )\ny = base.dists.cosine.mode( 0.0, NaN )\ny = base.dists.cosine.mode( 0.0, 0.0 )\n","base.dists.cosine.pdf":"var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\ny = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.pdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.pdf.factory":"var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\nvar y = myPDF( 2.0 )\n","base.dists.cosine.quantile":"var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cosine.quantile( 0.0, 0.0, NaN )\ny = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cosine.quantile.factory":"var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.3 )\n","base.dists.cosine.skewness":"var y = base.dists.cosine.skewness( 0.0, 1.0 )\ny = base.dists.cosine.skewness( 4.0, 2.0 )\ny = base.dists.cosine.skewness( NaN, 1.0 )\ny = base.dists.cosine.skewness( 0.0, NaN )\ny = base.dists.cosine.skewness( 0.0, 0.0 )\n","base.dists.cosine.stdev":"var y = base.dists.cosine.stdev( 0.0, 1.0 )\ny = base.dists.cosine.stdev( 4.0, 2.0 )\ny = base.dists.cosine.stdev( NaN, 1.0 )\ny = base.dists.cosine.stdev( 0.0, NaN )\ny = base.dists.cosine.stdev( 0.0, 0.0 )\n","base.dists.cosine.variance":"var y = base.dists.cosine.variance( 0.0, 1.0 )\ny = base.dists.cosine.variance( 4.0, 2.0 )\ny = base.dists.cosine.variance( NaN, 1.0 )\ny = base.dists.cosine.variance( 0.0, NaN )\ny = base.dists.cosine.variance( 0.0, 0.0 )\n","base.dists.degenerate.cdf":"var y = base.dists.degenerate.cdf( 2.0, 3.0 )\ny = base.dists.degenerate.cdf( 4.0, 3.0 )\ny = base.dists.degenerate.cdf( 3.0, 3.0 )\ny = base.dists.degenerate.cdf( NaN, 0.0 )\ny = base.dists.degenerate.cdf( 0.0, NaN )\n","base.dists.degenerate.cdf.factory":"var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 6.0 )\n","base.dists.degenerate.Degenerate":"var degenerate = base.dists.degenerate.Degenerate( 2.0 );\ndegenerate.mu\ndegenerate.entropy\ndegenerate.mean\ndegenerate.mode\ndegenerate.median\ndegenerate.stdev\ndegenerate.variance\ndegenerate.cdf( 0.5 )\ndegenerate.logcdf( 2.5 )\ndegenerate.logpdf( 0.5 )\ndegenerate.logpmf( 2.5 )\ndegenerate.mgf( 0.2 )\ndegenerate.pdf( 2.0 )\ndegenerate.pmf( 2.0 )\ndegenerate.quantile( 0.7 )\n","base.dists.degenerate.entropy":"var v = base.dists.degenerate.entropy( 20.0 )\nv = base.dists.degenerate.entropy( -10.0 )\n","base.dists.degenerate.logcdf":"var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\ny = base.dists.degenerate.logcdf( 4.0, 3.0 )\ny = base.dists.degenerate.logcdf( 3.0, 3.0 )\ny = base.dists.degenerate.logcdf( NaN, 0.0 )\ny = base.dists.degenerate.logcdf( 0.0, NaN )\n","base.dists.degenerate.logcdf.factory":"var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 6.0 )\n","base.dists.degenerate.logpdf":"var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\ny = base.dists.degenerate.logpdf( 3.0, 3.0 )\ny = base.dists.degenerate.logpdf( NaN, 0.0 )\ny = base.dists.degenerate.logpdf( 0.0, NaN )\n","base.dists.degenerate.logpdf.factory":"var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.degenerate.logpmf":"var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\ny = base.dists.degenerate.logpmf( 3.0, 3.0 )\ny = base.dists.degenerate.logpmf( NaN, 0.0 )\ny = base.dists.degenerate.logpmf( 0.0, NaN )\n","base.dists.degenerate.logpmf.factory":"var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\nvar y = mylogPMF( 10.0 )\n","base.dists.degenerate.mean":"var v = base.dists.degenerate.mean( 20.0 )\nv = base.dists.degenerate.mean( -10.0 )\n","base.dists.degenerate.median":"var v = base.dists.degenerate.median( 20.0 )\nv = base.dists.degenerate.median( -10.0 )\n","base.dists.degenerate.mgf":"var y = base.dists.degenerate.mgf( 1.0, 1.0 )\ny = base.dists.degenerate.mgf( 2.0, 3.0 )\ny = base.dists.degenerate.mgf( NaN, 0.0 )\ny = base.dists.degenerate.mgf( 0.0, NaN )\n","base.dists.degenerate.mgf.factory":"var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\nvar y = myMGF( 0.1 )\n","base.dists.degenerate.mode":"var v = base.dists.degenerate.mode( 20.0 )\nv = base.dists.degenerate.mode( -10.0 )\n","base.dists.degenerate.pdf":"var y = base.dists.degenerate.pdf( 2.0, 3.0 )\ny = base.dists.degenerate.pdf( 3.0, 3.0 )\ny = base.dists.degenerate.pdf( NaN, 0.0 )\ny = base.dists.degenerate.pdf( 0.0, NaN )\n","base.dists.degenerate.pdf.factory":"var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\nvar y = myPDF( 10.0 )\n","base.dists.degenerate.pmf":"var y = base.dists.degenerate.pmf( 2.0, 3.0 )\ny = base.dists.degenerate.pmf( 3.0, 3.0 )\ny = base.dists.degenerate.pmf( NaN, 0.0 )\ny = base.dists.degenerate.pmf( 0.0, NaN )\n","base.dists.degenerate.pmf.factory":"var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\nvar y = myPMF( 10.0 )\n","base.dists.degenerate.quantile":"var y = base.dists.degenerate.quantile( 0.5, 2.0 )\ny = base.dists.degenerate.quantile( 0.9, 4.0 )\ny = base.dists.degenerate.quantile( 1.1, 0.0 )\ny = base.dists.degenerate.quantile( -0.2, 0.0 )\ny = base.dists.degenerate.quantile( NaN, 0.0 )\ny = base.dists.degenerate.quantile( 0.0, NaN )\n","base.dists.degenerate.quantile.factory":"var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.degenerate.stdev":"var v = base.dists.degenerate.stdev( 20.0 )\nv = base.dists.degenerate.stdev( -10.0 )\n","base.dists.degenerate.variance":"var v = base.dists.degenerate.variance( 20.0 )\nv = base.dists.degenerate.variance( -10.0 )\n","base.dists.discreteUniform.cdf":"var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.cdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.cdf.factory":"var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.discreteUniform.DiscreteUniform":"var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\ndiscreteUniform.a\ndiscreteUniform.b\ndiscreteUniform.entropy\ndiscreteUniform.kurtosis\ndiscreteUniform.mean\ndiscreteUniform.median\ndiscreteUniform.skewness\ndiscreteUniform.stdev\ndiscreteUniform.variance\ndiscreteUniform.cdf( 0.8 )\ndiscreteUniform.logcdf( 0.5 )\ndiscreteUniform.logpmf( 1.0 )\ndiscreteUniform.mgf( 0.8 )\ndiscreteUniform.pmf( 0.0 )\ndiscreteUniform.quantile( 0.8 )\n","base.dists.discreteUniform.entropy":"var v = base.dists.discreteUniform.entropy( 0, 1 )\nv = base.dists.discreteUniform.entropy( 4, 12 )\nv = base.dists.discreteUniform.entropy( 2, 8 )\n","base.dists.discreteUniform.kurtosis":"var v = base.dists.discreteUniform.kurtosis( 0, 1 )\nv = base.dists.discreteUniform.kurtosis( 4, 12 )\nv = base.dists.discreteUniform.kurtosis( -4, 8 )\n","base.dists.discreteUniform.logcdf":"var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.logcdf.factory":"var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\nvar y = myLogCDF( 0.5 )\ny = myLogCDF( 8.0 )\n","base.dists.discreteUniform.logpmf":"var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.logpmf.factory":"var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\nvar y = myLogPMF( 7.0 )\ny = myLogPMF( 5.0 )\n","base.dists.discreteUniform.mean":"var v = base.dists.discreteUniform.mean( -2, 2 )\nv = base.dists.discreteUniform.mean( 4, 12 )\nv = base.dists.discreteUniform.mean( 2, 8 )\n","base.dists.discreteUniform.median":"var v = base.dists.discreteUniform.median( -2, 2 )\nv = base.dists.discreteUniform.median( 4, 12 )\nv = base.dists.discreteUniform.median( 2, 8 )\n","base.dists.discreteUniform.mgf":"var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\ny = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\ny = base.dists.discreteUniform.mgf( NaN, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n","base.dists.discreteUniform.mgf.factory":"var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.discreteUniform.pmf":"var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.pmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.pmf.factory":"var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\nvar y = myPMF( 7.0 )\ny = myPMF( 5.0 )\n","base.dists.discreteUniform.quantile":"var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\ny = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\ny = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\ny = base.dists.discreteUniform.quantile( NaN, -2, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\ny = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n","base.dists.discreteUniform.quantile.factory":"var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\nvar y = myQuantile( 0.8 )\n","base.dists.discreteUniform.skewness":"var v = base.dists.discreteUniform.skewness( -2, 2 )\nv = base.dists.discreteUniform.skewness( 4, 12 )\nv = base.dists.discreteUniform.skewness( 2, 8 )\n","base.dists.discreteUniform.stdev":"var v = base.dists.discreteUniform.stdev( 0, 1 )\nv = base.dists.discreteUniform.stdev( 4, 12 )\nv = base.dists.discreteUniform.stdev( 2, 8 )\n","base.dists.discreteUniform.variance":"var v = base.dists.discreteUniform.variance( 0, 1 )\nv = base.dists.discreteUniform.variance( 4, 12 )\nv = base.dists.discreteUniform.variance( 2, 8 )\n","base.dists.erlang.cdf":"var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 3, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\ny = base.dists.erlang.cdf( -1.0, 2, 2.0 )\ny = base.dists.erlang.cdf( PINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NaN, 0, 1.0 )\ny = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.cdf( 0.0, 0, NaN )\ny = base.dists.erlang.cdf( 2.0, -1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n","base.dists.erlang.cdf.factory":"var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\nvar y = mycdf( 6.0 )\ny = mycdf( 2.0 )\n","base.dists.erlang.entropy":"var v = base.dists.erlang.entropy( 1, 1.0 )\nv = base.dists.erlang.entropy( 4, 12.0 )\nv = base.dists.erlang.entropy( 8, 2.0 )\n","base.dists.erlang.Erlang":"var erlang = base.dists.erlang.Erlang( 6, 5.0 );\nerlang.k\nerlang.lambda\nerlang.entropy\nerlang.kurtosis\nerlang.mean\nerlang.mode\nerlang.skewness\nerlang.stdev\nerlang.variance\nerlang.cdf( 3.0 )\nerlang.logpdf( 3.0 )\nerlang.mgf( -0.5 )\nerlang.pdf( 3.0 )\nerlang.quantile( 0.8 )\n","base.dists.erlang.kurtosis":"var v = base.dists.erlang.kurtosis( 1, 1.0 )\nv = base.dists.erlang.kurtosis( 4, 12.0 )\nv = base.dists.erlang.kurtosis( 8, 2.0 )\n","base.dists.erlang.logpdf":"var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.logpdf( NaN, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, 1, NaN )\ny = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n","base.dists.erlang.logpdf.factory":"var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\ny = myLogPDF( 7.0 )\n","base.dists.erlang.mean":"var v = base.dists.erlang.mean( 1, 1.0 )\nv = base.dists.erlang.mean( 4, 12.0 )\nv = base.dists.erlang.mean( 8, 2.0 )\n","base.dists.erlang.mgf":"var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\ny = base.dists.erlang.mgf( 2.0, 2, 3.0 )\ny = base.dists.erlang.mgf( -1.0, 2, 2.0 )\ny = base.dists.erlang.mgf( NaN, 1, 1.0 )\ny = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.mgf( 0.0, 1, NaN )\ny = base.dists.erlang.mgf( 0.2, -2, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 1, 0.0 )\ny = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n","base.dists.erlang.mgf.factory":"var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\nvar y = myMGF( 0.2 )\ny = myMGF( -0.5 )\n","base.dists.erlang.mode":"var v = base.dists.erlang.mode( 1, 1.0 )\nv = base.dists.erlang.mode( 4, 12.0 )\nv = base.dists.erlang.mode( 8, 2.0 )\n","base.dists.erlang.pdf":"var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.pdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.pdf( NaN, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.pdf( 0.0, 1, NaN )\ny = base.dists.erlang.pdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n","base.dists.erlang.pdf.factory":"var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\ny = myPDF( 7.0 )\n","base.dists.erlang.quantile":"var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 4, 2.0 )\ny = base.dists.erlang.quantile( 1.1, 1, 1.0 )\ny = base.dists.erlang.quantile( -0.2, 1, 1.0 )\ny = base.dists.erlang.quantile( NaN, 1, 1.0 )\ny = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\ny = base.dists.erlang.quantile( 0.0, 1, NaN )\ny = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\ny = base.dists.erlang.quantile( 0.5, -1, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n","base.dists.erlang.quantile.factory":"var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.erlang.skewness":"var v = base.dists.erlang.skewness( 1, 1.0 )\nv = base.dists.erlang.skewness( 4, 12.0 )\nv = base.dists.erlang.skewness( 8, 2.0 )\n","base.dists.erlang.stdev":"var v = base.dists.erlang.stdev( 1, 1.0 )\nv = base.dists.erlang.stdev( 4, 12.0 )\nv = base.dists.erlang.stdev( 8, 2.0 )\n","base.dists.erlang.variance":"var v = base.dists.erlang.variance( 1, 1.0 )\nv = base.dists.erlang.variance( 4, 12.0 )\nv = base.dists.erlang.variance( 8, 2.0 )\n","base.dists.exponential.cdf":"var y = base.dists.exponential.cdf( 2.0, 0.1 )\ny = base.dists.exponential.cdf( 1.0, 2.0 )\ny = base.dists.exponential.cdf( -1.0, 4.0 )\ny = base.dists.exponential.cdf( NaN, 1.0 )\ny = base.dists.exponential.cdf( 0.0, NaN )\ny = base.dists.exponential.cdf( 2.0, -1.0 )\n","base.dists.exponential.cdf.factory":"var myCDF = base.dists.exponential.cdf.factory( 0.5 );\nvar y = myCDF( 3.0 )\n","base.dists.exponential.entropy":"var v = base.dists.exponential.entropy( 11.0 )\nv = base.dists.exponential.entropy( 4.5 )\n","base.dists.exponential.Exponential":"var exponential = base.dists.exponential.Exponential( 6.0 );\nexponential.lambda\nexponential.entropy\nexponential.kurtosis\nexponential.mean\nexponential.median\nexponential.mode\nexponential.skewness\nexponential.stdev\nexponential.variance\nexponential.cdf( 1.0 )\nexponential.logcdf( 1.0 )\nexponential.logpdf( 1.5 )\nexponential.mgf( -0.5 )\nexponential.pdf( 1.5 )\nexponential.quantile( 0.5 )\n","base.dists.exponential.kurtosis":"var v = base.dists.exponential.kurtosis( 11.0 )\nv = base.dists.exponential.kurtosis( 4.5 )\n","base.dists.exponential.logcdf":"var y = base.dists.exponential.logcdf( 2.0, 0.1 )\ny = base.dists.exponential.logcdf( 1.0, 2.0 )\ny = base.dists.exponential.logcdf( -1.0, 4.0 )\ny = base.dists.exponential.logcdf( NaN, 1.0 )\ny = base.dists.exponential.logcdf( 0.0, NaN )\ny = base.dists.exponential.logcdf( 2.0, -1.0 )\n","base.dists.exponential.logcdf.factory":"var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\nvar y = mylogCDF( 3.0 )\n","base.dists.exponential.logpdf":"var y = base.dists.exponential.logpdf( 0.3, 4.0 )\ny = base.dists.exponential.logpdf( 2.0, 0.7 )\ny = base.dists.exponential.logpdf( -1.0, 0.5 )\ny = base.dists.exponential.logpdf( 0, NaN )\ny = base.dists.exponential.logpdf( NaN, 2.0 )\ny = base.dists.exponential.logpdf( 2.0, -1.0 )\n","base.dists.exponential.logpdf.factory":"var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\nvar y = mylogpdf( 3.0 )\n","base.dists.exponential.mean":"var v = base.dists.exponential.mean( 11.0 )\nv = base.dists.exponential.mean( 4.5 )\n","base.dists.exponential.median":"var v = base.dists.exponential.median( 11.0 )\nv = base.dists.exponential.median( 4.5 )\n","base.dists.exponential.mgf":"var v = base.dists.exponential.mgf( 2.0, 3.0 )\nv = base.dists.exponential.mgf( 0.4, 1.2 )\nv = base.dists.exponential.mgf( 0.8, 1.6 )\nv = base.dists.exponential.mgf( 4.0, 3.0 )\nv = base.dists.exponential.mgf( NaN, 3.0 )\nv = base.dists.exponential.mgf( 2.0, NaN )\n","base.dists.exponential.mgf.factory":"var myMGF = base.dists.exponential.mgf.factory( 4.0 );\nvar y = myMGF( 3.0 )\ny = myMGF( 0.5 )\n","base.dists.exponential.mode":"var v = base.dists.exponential.mode( 11.0 )\nv = base.dists.exponential.mode( 4.5 )\n","base.dists.exponential.pdf":"var y = base.dists.exponential.pdf( 0.3, 4.0 )\ny = base.dists.exponential.pdf( 2.0, 0.7 )\ny = 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);\nvar y = myPDF( 7.0 )\ny = myPDF( 2.0 )\n","base.dists.f.quantile":"var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.f.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.f.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.f.quantile( NaN, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, NaN, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, NaN )\ny = base.dists.f.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n","base.dists.f.quantile.factory":"var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.f.skewness":"var v = base.dists.f.skewness( 3.0, 7.0 )\nv = base.dists.f.skewness( 4.0, 12.0 )\nv = base.dists.f.skewness( 8.0, 7.0 )\n","base.dists.f.stdev":"var v = base.dists.f.stdev( 3.0, 5.0 )\nv = base.dists.f.stdev( 4.0, 12.0 )\nv = base.dists.f.stdev( 8.0, 5.0 )\n","base.dists.f.variance":"var v = base.dists.f.variance( 3.0, 5.0 )\nv = 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)\n","base.dists.frechet.Frechet":"var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\nfrechet.alpha\nfrechet.s\nfrechet.m\nfrechet.entropy\nfrechet.kurtosis\nfrechet.mean\nfrechet.median\nfrechet.mode\nfrechet.skewness\nfrechet.stdev\nfrechet.variance\nfrechet.cdf( 0.8 )\nfrechet.logcdf( 0.8 )\nfrechet.logpdf( 0.8 )\nfrechet.pdf( 0.8 )\nfrechet.quantile( 0.8 )\n","base.dists.frechet.kurtosis":"var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\nvar y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\ny = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\ny = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n","base.dists.frechet.logcdf":"var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 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4.0, 2.0, 1.0 )\ny = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mean( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mean( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mean( 1.0, 1.0, NaN )\n","base.dists.frechet.median":"var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.median( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.median( NaN, 1.0, 0.0 )\ny = base.dists.frechet.median( 1.0, NaN, 0.0 )\ny = base.dists.frechet.median( 1.0, 1.0, NaN )\n","base.dists.frechet.mode":"var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mode( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mode( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mode( 1.0, 1.0, NaN )\n","base.dists.frechet.pdf":"var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.pdf.factory":"var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.frechet.quantile":"var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\ny = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\ny = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\ny = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\ny = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.quantile.factory":"var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.2 )\n","base.dists.frechet.skewness":"var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\ny = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\ny = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n","base.dists.frechet.stdev":"var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\ny = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\ny = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n","base.dists.frechet.variance":"var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.variance( NaN, 1.0, 0.0 )\ny = base.dists.frechet.variance( 1.0, NaN, 0.0 )\ny = base.dists.frechet.variance( 1.0, 1.0, NaN )\n","base.dists.gamma.cdf":"var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.cdf.factory":"var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 6.0 )\ny = myCDF( 2.0 )\n","base.dists.gamma.entropy":"var v = base.dists.gamma.entropy( 1.0, 1.0 )\nv = base.dists.gamma.entropy( 4.0, 12.0 )\nv = base.dists.gamma.entropy( 8.0, 2.0 )\n","base.dists.gamma.Gamma":"var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\ngamma.alpha\ngamma.beta\ngamma.entropy\ngamma.kurtosis\ngamma.mean\ngamma.mode\ngamma.skewness\ngamma.stdev\ngamma.variance\ngamma.cdf( 0.8 )\ngamma.logcdf( 0.8 )\ngamma.logpdf( 1.0 )\ngamma.mgf( -0.5 )\ngamma.pdf( 1.0 )\ngamma.quantile( 0.8 )\n","base.dists.gamma.kurtosis":"var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\nv = base.dists.gamma.kurtosis( 4.0, 12.0 )\nv = base.dists.gamma.kurtosis( 8.0, 2.0 )\n","base.dists.gamma.logcdf":"var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.logcdf.factory":"var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\nvar y = mylogCDF( 2.0 )\n","base.dists.gamma.logpdf":"var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.logpdf.factory":"var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.gamma.mean":"var v = base.dists.gamma.mean( 1.0, 1.0 )\nv = base.dists.gamma.mean( 4.0, 12.0 )\nv = base.dists.gamma.mean( 8.0, 2.0 )\n","base.dists.gamma.mgf":"var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\ny = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\ny = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.mgf( 0.0, 1.0, NaN )\ny = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\ny = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.mgf.factory":"var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.gamma.mode":"var v = base.dists.gamma.mode( 1.0, 1.0 )\nv = base.dists.gamma.mode( 4.0, 12.0 )\nv = base.dists.gamma.mode( 8.0, 2.0 )\n","base.dists.gamma.pdf":"var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.pdf.factory":"var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.gamma.quantile":"var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\ny = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\ny = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n","base.dists.gamma.quantile.factory":"var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.gamma.skewness":"var v = base.dists.gamma.skewness( 1.0, 1.0 )\nv = base.dists.gamma.skewness( 4.0, 12.0 )\nv = base.dists.gamma.skewness( 8.0, 2.0 )\n","base.dists.gamma.stdev":"var v = base.dists.gamma.stdev( 1.0, 1.0 )\nv = base.dists.gamma.stdev( 4.0, 12.0 )\nv = base.dists.gamma.stdev( 8.0, 2.0 )\n","base.dists.gamma.variance":"var v = base.dists.gamma.variance( 1.0, 1.0 )\nv = base.dists.gamma.variance( 4.0, 12.0 )\nv = base.dists.gamma.variance( 8.0, 2.0 )\n","base.dists.geometric.cdf":"var y = base.dists.geometric.cdf( 2.0, 0.5 )\ny = base.dists.geometric.cdf( 2.0, 0.1 )\ny = base.dists.geometric.cdf( -1.0, 4.0 )\ny = base.dists.geometric.cdf( NaN, 0.5 )\ny = base.dists.geometric.cdf( 0.0, NaN )\ny = base.dists.geometric.cdf( 2.0, 1.4 )\n","base.dists.geometric.cdf.factory":"var mycdf = base.dists.geometric.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.geometric.entropy":"var v = base.dists.geometric.entropy( 0.1 )\nv = base.dists.geometric.entropy( 0.5 )\n","base.dists.geometric.Geometric":"var geometric = base.dists.geometric.Geometric( 0.6 );\ngeometric.p\ngeometric.entropy\ngeometric.kurtosis\ngeometric.mean\ngeometric.median\ngeometric.mode\ngeometric.skewness\ngeometric.stdev\ngeometric.variance\ngeometric.cdf( 3.0 )\ngeometric.logcdf( 3.0 )\ngeometric.logpmf( 4.0 )\ngeometric.mgf( 0.5 )\ngeometric.pmf( 2.0 )\ngeometric.quantile( 0.7 )\n","base.dists.geometric.kurtosis":"var v = base.dists.geometric.kurtosis( 0.1 )\nv = base.dists.geometric.kurtosis( 0.5 )\n","base.dists.geometric.logcdf":"var y = base.dists.geometric.logcdf( 2.0, 0.5 )\ny = base.dists.geometric.logcdf( 2.0, 0.1 )\ny = base.dists.geometric.logcdf( -1.0, 4.0 )\ny = base.dists.geometric.logcdf( NaN, 0.5 )\ny = base.dists.geometric.logcdf( 0.0, NaN )\ny = base.dists.geometric.logcdf( 2.0, 1.4 )\n","base.dists.geometric.logcdf.factory":"var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.geometric.logpmf":"var y = base.dists.geometric.logpmf( 4.0, 0.3 )\ny = base.dists.geometric.logpmf( 2.0, 0.7 )\ny = base.dists.geometric.logpmf( -1.0, 0.5 )\ny = base.dists.geometric.logpmf( 0.0, NaN )\ny = base.dists.geometric.logpmf( NaN, 0.5 )\ny = base.dists.geometric.logpmf( 2.0, 1.5 )\n","base.dists.geometric.logpmf.factory":"var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.geometric.mean":"var v = base.dists.geometric.mean( 0.1 )\nv = base.dists.geometric.mean( 0.5 )\n","base.dists.geometric.median":"var v = base.dists.geometric.median( 0.1 )\nv = base.dists.geometric.median( 0.5 )\n","base.dists.geometric.mgf":"var y = base.dists.geometric.mgf( 0.2, 0.5 )\ny = base.dists.geometric.mgf( 0.4, 0.5 )\ny = base.dists.geometric.mgf( 0.8, 0.5 )\ny = base.dists.geometric.mgf( NaN, 0.0 )\ny = base.dists.geometric.mgf( 0.0, NaN )\ny = base.dists.geometric.mgf( -2.0, -1.0 )\ny = base.dists.geometric.mgf( 0.2, 2.0 )\n","base.dists.geometric.mgf.factory":"var mymgf = base.dists.geometric.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.geometric.mode":"var v = base.dists.geometric.mode( 0.1 )\nv = base.dists.geometric.mode( 0.5 )\n","base.dists.geometric.pmf":"var y = base.dists.geometric.pmf( 4.0, 0.3 )\ny = base.dists.geometric.pmf( 2.0, 0.7 )\ny = base.dists.geometric.pmf( -1.0, 0.5 )\ny = base.dists.geometric.pmf( 0.0, NaN )\ny = base.dists.geometric.pmf( NaN, 0.5 )\ny = base.dists.geometric.pmf( 2.0, 1.5 )\n","base.dists.geometric.pmf.factory":"var mypmf = base.dists.geometric.pmf.factory( 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.geometric.quantile":"var y = base.dists.geometric.quantile( 0.8, 0.4 )\ny = base.dists.geometric.quantile( 0.5, 0.4 )\ny = base.dists.geometric.quantile( 0.9, 0.1 )\ny = base.dists.geometric.quantile( -0.2, 0.1 )\ny = base.dists.geometric.quantile( NaN, 0.8 )\ny = base.dists.geometric.quantile( 0.4, NaN )\ny = base.dists.geometric.quantile( 0.5, -1.0 )\ny = base.dists.geometric.quantile( 0.5, 1.5 )\n","base.dists.geometric.quantile.factory":"var myquantile = base.dists.geometric.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.geometric.skewness":"var v = base.dists.geometric.skewness( 0.1 )\nv = base.dists.geometric.skewness( 0.5 )\n","base.dists.geometric.stdev":"var v = base.dists.geometric.stdev( 0.1 )\nv = base.dists.geometric.stdev( 0.5 )\n","base.dists.geometric.variance":"var v = base.dists.geometric.variance( 0.1 )\nv = base.dists.geometric.variance( 0.5 )\n","base.dists.gumbel.cdf":"var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.cdf.factory":"var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.gumbel.entropy":"var y = base.dists.gumbel.entropy( 0.0, 1.0 )\ny = base.dists.gumbel.entropy( 4.0, 2.0 )\ny = base.dists.gumbel.entropy( NaN, 1.0 )\ny = base.dists.gumbel.entropy( 0.0, NaN )\ny = base.dists.gumbel.entropy( 0.0, 0.0 )\n","base.dists.gumbel.Gumbel":"var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\ngumbel.mu\ngumbel.beta\ngumbel.entropy\ngumbel.kurtosis\ngumbel.mean\ngumbel.median\ngumbel.mode\ngumbel.skewness\ngumbel.stdev\ngumbel.variance\ngumbel.cdf( 0.8 )\ngumbel.logcdf( 0.8 )\ngumbel.logpdf( 1.0 )\ngumbel.mgf( 0.2 )\ngumbel.pdf( 1.0 )\ngumbel.quantile( 0.8 )\n","base.dists.gumbel.kurtosis":"var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\ny = base.dists.gumbel.kurtosis( 4.0, 2.0 )\ny = base.dists.gumbel.kurtosis( NaN, 1.0 )\ny = base.dists.gumbel.kurtosis( 0.0, NaN )\ny = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n","base.dists.gumbel.logcdf":"var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.logcdf.factory":"var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\nvar y = myLCDF( 10.0 )\ny = myLCDF( 2.0 )\n","base.dists.gumbel.logpdf":"var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.logpdf.factory":"var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\ny = mylogpdf( 12.0 )\n","base.dists.gumbel.mean":"var y = base.dists.gumbel.mean( 0.0, 1.0 )\ny = base.dists.gumbel.mean( 4.0, 2.0 )\ny = base.dists.gumbel.mean( NaN, 1.0 )\ny = base.dists.gumbel.mean( 0.0, NaN )\ny = base.dists.gumbel.mean( 0.0, 0.0 )\n","base.dists.gumbel.median":"var y = base.dists.gumbel.median( 0.0, 1.0 )\ny = base.dists.gumbel.median( 4.0, 2.0 )\ny = base.dists.gumbel.median( NaN, 1.0 )\ny = base.dists.gumbel.median( 0.0, NaN )\ny = base.dists.gumbel.median( 0.0, 0.0 )\n","base.dists.gumbel.mgf":"var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.mgf.factory":"var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\nvar y = myMGF( -1.5 )\ny = myMGF( -1.0 )\n","base.dists.gumbel.mode":"var y = base.dists.gumbel.mode( 0.0, 1.0 )\ny = base.dists.gumbel.mode( 4.0, 2.0 )\ny = base.dists.gumbel.mode( NaN, 1.0 )\ny = base.dists.gumbel.mode( 0.0, NaN )\ny = base.dists.gumbel.mode( 0.0, 0.0 )\n","base.dists.gumbel.pdf":"var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.pdf.factory":"var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 12.0 )\n","base.dists.gumbel.quantile":"var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\ny = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\ny = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n","base.dists.gumbel.quantile.factory":"var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.7 )\n","base.dists.gumbel.skewness":"var y = base.dists.gumbel.skewness( 0.0, 1.0 )\ny = base.dists.gumbel.skewness( 4.0, 2.0 )\ny = base.dists.gumbel.skewness( NaN, 1.0 )\ny = base.dists.gumbel.skewness( 0.0, NaN )\ny = base.dists.gumbel.skewness( 0.0, 0.0 )\n","base.dists.gumbel.stdev":"var y = base.dists.gumbel.stdev( 0.0, 1.0 )\ny = base.dists.gumbel.stdev( 4.0, 2.0 )\ny = base.dists.gumbel.stdev( NaN, 1.0 )\ny = base.dists.gumbel.stdev( 0.0, NaN )\ny = base.dists.gumbel.stdev( 0.0, 0.0 )\n","base.dists.gumbel.variance":"var y = base.dists.gumbel.variance( 0.0, 1.0 )\ny = base.dists.gumbel.variance( 4.0, 2.0 )\ny = base.dists.gumbel.variance( NaN, 1.0 )\ny = base.dists.gumbel.variance( 0.0, NaN )\ny = base.dists.gumbel.variance( 0.0, 0.0 )\n","base.dists.hypergeometric.cdf":"var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\ny = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.cdf.factory":"var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\nvar y = myCDF( 4.0 )\ny = myCDF( 1.0 )\n","base.dists.hypergeometric.Hypergeometric":"var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\nhypergeometric.N\nhypergeometric.K\nhypergeometric.n\nhypergeometric.kurtosis\nhypergeometric.mean\nhypergeometric.mode\nhypergeometric.skewness\nhypergeometric.stdev\nhypergeometric.variance\nhypergeometric.cdf( 2.9 )\nhypergeometric.logpmf( 10 )\nhypergeometric.pmf( 10 )\nhypergeometric.quantile( 0.8 )\n","base.dists.hypergeometric.kurtosis":"var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\nv = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\nv = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\nv = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n","base.dists.hypergeometric.logpmf":"var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.logpmf.factory":"var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\nvar y = mylogPMF( 4.0 )\ny = mylogPMF( 1.0 )\n","base.dists.hypergeometric.mean":"var v = base.dists.hypergeometric.mean( 16, 11, 4 )\nv = base.dists.hypergeometric.mean( 2, 1, 1 )\nv = base.dists.hypergeometric.mean( 10, 5, 12 )\nv = base.dists.hypergeometric.mean( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mean( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mean( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mean( NaN, 10, 4 )\nv = base.dists.hypergeometric.mean( 20, NaN, 4 )\nv = base.dists.hypergeometric.mean( 20, 10, NaN )\n","base.dists.hypergeometric.mode":"var v = base.dists.hypergeometric.mode( 16, 11, 4 )\nv = base.dists.hypergeometric.mode( 2, 1, 1 )\nv = base.dists.hypergeometric.mode( 10, 5, 12 )\nv = base.dists.hypergeometric.mode( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mode( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mode( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mode( NaN, 10, 4 )\nv = base.dists.hypergeometric.mode( 20, NaN, 4 )\nv = base.dists.hypergeometric.mode( 20, 10, NaN )\n","base.dists.hypergeometric.pmf":"var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.pmf.factory":"var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\nvar y = myPMF( 4.0 )\ny = myPMF( 1.0 )\n","base.dists.hypergeometric.quantile":"var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\ny = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\ny = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n","base.dists.hypergeometric.quantile.factory":"var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.hypergeometric.skewness":"var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\nv = base.dists.hypergeometric.skewness( 4, 2, 2 )\nv = base.dists.hypergeometric.skewness( 10, 5, 12 )\nv = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\nv = base.dists.hypergeometric.skewness( NaN, 10, 4 )\nv = base.dists.hypergeometric.skewness( 20, NaN, 4 )\nv = base.dists.hypergeometric.skewness( 20, 10, NaN )\n","base.dists.hypergeometric.stdev":"var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\nv = base.dists.hypergeometric.stdev( 2, 1, 1 )\nv = base.dists.hypergeometric.stdev( 10, 5, 12 )\nv = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\nv = base.dists.hypergeometric.stdev( NaN, 10, 4 )\nv = base.dists.hypergeometric.stdev( 20, NaN, 4 )\nv = base.dists.hypergeometric.stdev( 20, 10, NaN )\n","base.dists.hypergeometric.variance":"var v = base.dists.hypergeometric.variance( 16, 11, 4 )\nv = base.dists.hypergeometric.variance( 2, 1, 1 )\nv = base.dists.hypergeometric.variance( 10, 5, 12 )\nv = base.dists.hypergeometric.variance( 10.3, 10, 4 )\nv = base.dists.hypergeometric.variance( 10, 5.5, 4 )\nv = base.dists.hypergeometric.variance( 10, 5, 4.5 )\nv = base.dists.hypergeometric.variance( NaN, 10, 4 )\nv = base.dists.hypergeometric.variance( 20, NaN, 4 )\nv = base.dists.hypergeometric.variance( 20, 10, NaN )\n","base.dists.invgamma.cdf":"var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.cdf.factory":"var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 0.5 )\ny = myCDF( 2.0 )\n","base.dists.invgamma.entropy":"var v = base.dists.invgamma.entropy( 1.0, 1.0 )\nv = base.dists.invgamma.entropy( 4.0, 12.0 )\nv = base.dists.invgamma.entropy( 8.0, 2.0 )\n","base.dists.invgamma.InvGamma":"var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\ninvgamma.alpha\ninvgamma.beta\ninvgamma.entropy\ninvgamma.kurtosis\ninvgamma.mean\ninvgamma.mode\ninvgamma.skewness\ninvgamma.stdev\ninvgamma.variance\ninvgamma.cdf( 0.8 )\ninvgamma.pdf( 1.0 )\ninvgamma.logpdf( 1.0 )\ninvgamma.quantile( 0.8 )\n","base.dists.invgamma.kurtosis":"var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\nv = base.dists.invgamma.kurtosis( 6.0, 12.0 )\nv = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n","base.dists.invgamma.logpdf":"var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.logpdf.factory":"var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.invgamma.mean":"var v = base.dists.invgamma.mean( 4.0, 12.0 )\nv = base.dists.invgamma.mean( 8.0, 2.0 )\n","base.dists.invgamma.mode":"var v = base.dists.invgamma.mode( 1.0, 1.0 )\nv = base.dists.invgamma.mode( 4.0, 12.0 )\nv = base.dists.invgamma.mode( 8.0, 2.0 )\n","base.dists.invgamma.pdf":"var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.pdf.factory":"var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.invgamma.quantile":"var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n","base.dists.invgamma.quantile.factory":"var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.invgamma.skewness":"var v = base.dists.invgamma.skewness( 4.0, 12.0 )\nv = base.dists.invgamma.skewness( 8.0, 2.0 )\n","base.dists.invgamma.stdev":"var v = base.dists.invgamma.stdev( 5.0, 7.0 )\nv = base.dists.invgamma.stdev( 4.0, 12.0 )\nv = base.dists.invgamma.stdev( 8.0, 2.0 )\n","base.dists.invgamma.variance":"var v = base.dists.invgamma.variance( 5.0, 7.0 )\nv = base.dists.invgamma.variance( 4.0, 12.0 )\nv = base.dists.invgamma.variance( 8.0, 2.0 )\n","base.dists.kumaraswamy.cdf":"var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.cdf.factory":"var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.kumaraswamy.Kumaraswamy":"var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\nkumaraswamy.a\nkumaraswamy.b\nkumaraswamy.kurtosis\nkumaraswamy.mean\nkumaraswamy.mode\nkumaraswamy.skewness\nkumaraswamy.stdev\nkumaraswamy.variance\nkumaraswamy.cdf( 0.8 )\nkumaraswamy.pdf( 1.0 )\nkumaraswamy.quantile( 0.8 )\n","base.dists.kumaraswamy.kurtosis":"var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\nv = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\nv = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n","base.dists.kumaraswamy.logcdf":"var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logcdf.factory":"var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.kumaraswamy.logpdf":"var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logpdf.factory":"var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.kumaraswamy.mean":"var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mean( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n","base.dists.kumaraswamy.median":"var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\nv = base.dists.kumaraswamy.median( 4.0, 12.0 )\nv = base.dists.kumaraswamy.median( 16.0, 8.0 )\n","base.dists.kumaraswamy.mode":"var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mode( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n","base.dists.kumaraswamy.pdf":"var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.pdf.factory":"var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.kumaraswamy.quantile":"var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.quantile.factory":"var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.3 )\n","base.dists.kumaraswamy.skewness":"var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\nv = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\nv = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n","base.dists.kumaraswamy.stdev":"var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\nv = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\nv = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n","base.dists.kumaraswamy.variance":"var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\nv = base.dists.kumaraswamy.variance( 4.0, 12.0 )\nv = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n","base.dists.laplace.cdf":"var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 2, NaN, 1.0 )\ny = base.dists.laplace.cdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.cdf.factory":"var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.laplace.entropy":"var y = base.dists.laplace.entropy( 0.0, 1.0 )\ny = base.dists.laplace.entropy( 4.0, 2.0 )\ny = base.dists.laplace.entropy( NaN, 1.0 )\ny = base.dists.laplace.entropy( 0.0, NaN )\ny = base.dists.laplace.entropy( 0.0, 0.0 )\n","base.dists.laplace.kurtosis":"var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\ny = base.dists.laplace.kurtosis( 4.0, 2.0 )\ny = base.dists.laplace.kurtosis( NaN, 1.0 )\ny = base.dists.laplace.kurtosis( 0.0, NaN )\ny = base.dists.laplace.kurtosis( 0.0, 0.0 )\n","base.dists.laplace.Laplace":"var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\nlaplace.mu\nlaplace.b\nlaplace.entropy\nlaplace.kurtosis\nlaplace.mean\nlaplace.median\nlaplace.mode\nlaplace.skewness\nlaplace.stdev\nlaplace.variance\nlaplace.cdf( 0.8 )\nlaplace.logcdf( 0.8 )\nlaplace.logpdf( 1.0 )\nlaplace.mgf( 0.2 )\nlaplace.pdf( 2.0 )\nlaplace.quantile( 0.9 )\n","base.dists.laplace.logcdf":"var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 2, NaN, 1.0 )\ny = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logcdf.factory":"var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 2.0 )\n","base.dists.laplace.logpdf":"var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logpdf.factory":"var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.laplace.mean":"var y = base.dists.laplace.mean( 0.0, 1.0 )\ny = base.dists.laplace.mean( 4.0, 2.0 )\ny = base.dists.laplace.mean( NaN, 1.0 )\ny = base.dists.laplace.mean( 0.0, NaN )\ny = base.dists.laplace.mean( 0.0, 0.0 )\n","base.dists.laplace.median":"var y = base.dists.laplace.median( 0.0, 1.0 )\ny = base.dists.laplace.median( 4.0, 2.0 )\ny = base.dists.laplace.median( NaN, 1.0 )\ny = base.dists.laplace.median( 0.0, NaN )\ny = base.dists.laplace.median( 0.0, 0.0 )\n","base.dists.laplace.mgf":"var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\ny = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, NaN )\ny = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\ny = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.mgf.factory":"var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.laplace.mode":"var y = base.dists.laplace.mode( 0.0, 1.0 )\ny = base.dists.laplace.mode( 4.0, 2.0 )\ny = base.dists.laplace.mode( NaN, 1.0 )\ny = base.dists.laplace.mode( 0.0, NaN )\ny = base.dists.laplace.mode( 0.0, 0.0 )\n","base.dists.laplace.pdf":"var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.pdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.pdf.factory":"var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.laplace.quantile":"var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\ny = base.dists.laplace.quantile( 0.0, 0.0, NaN )\ny = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n","base.dists.laplace.quantile.factory":"var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.laplace.skewness":"var y = base.dists.laplace.skewness( 0.0, 1.0 )\ny = base.dists.laplace.skewness( 4.0, 2.0 )\ny = base.dists.laplace.skewness( NaN, 1.0 )\ny = base.dists.laplace.skewness( 0.0, NaN )\ny = base.dists.laplace.skewness( 0.0, 0.0 )\n","base.dists.laplace.stdev":"var y = base.dists.laplace.stdev( 0.0, 1.0 )\ny = base.dists.laplace.stdev( 4.0, 2.0 )\ny = base.dists.laplace.stdev( NaN, 1.0 )\ny = base.dists.laplace.stdev( 0.0, NaN )\ny = base.dists.laplace.stdev( 0.0, 0.0 )\n","base.dists.laplace.variance":"var y = base.dists.laplace.variance( 0.0, 1.0 )\ny = base.dists.laplace.variance( 4.0, 2.0 )\ny = base.dists.laplace.variance( NaN, 1.0 )\ny = base.dists.laplace.variance( 0.0, NaN )\ny = base.dists.laplace.variance( 0.0, 0.0 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NaN )\ny = base.dists.logistic.kurtosis( 0.0, 0.0 )\n","base.dists.logistic.logcdf":"var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.logcdf( 2, NaN, 1.0 )\ny = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n","base.dists.logistic.logcdf.factory":"var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.0 )\n","base.dists.logistic.Logistic":"var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\nlogistic.mu\nlogistic.s\nlogistic.entropy\nlogistic.kurtosis\nlogistic.mean\nlogistic.median\nlogistic.mode\nlogistic.skewness\nlogistic.stdev\nlogistic.variance\nlogistic.cdf( 0.8 )\nlogistic.logcdf( 0.8 )\nlogistic.logpdf( 2.0 )\nlogistic.mgf( 0.2 )\nlogistic.pdf( 2.0 )\nlogistic.quantile( 0.9 )\n","base.dists.logistic.logpdf":"var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.logpdf.factory":"var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.logistic.mean":"var y = base.dists.logistic.mean( 0.0, 1.0 )\ny = base.dists.logistic.mean( 4.0, 2.0 )\ny = base.dists.logistic.mean( NaN, 1.0 )\ny = base.dists.logistic.mean( 0.0, NaN )\ny = base.dists.logistic.mean( 0.0, 0.0 )\n","base.dists.logistic.median":"var y = base.dists.logistic.median( 0.0, 1.0 )\ny = base.dists.logistic.median( 4.0, 2.0 )\ny = base.dists.logistic.median( NaN, 1.0 )\ny = base.dists.logistic.median( 0.0, NaN )\ny = base.dists.logistic.median( 0.0, 0.0 )\n","base.dists.logistic.mgf":"var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 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base.dists.logistic.skewness( 0.0, NaN )\ny = base.dists.logistic.skewness( 0.0, 0.0 )\n","base.dists.logistic.stdev":"var y = base.dists.logistic.stdev( 0.0, 1.0 )\ny = base.dists.logistic.stdev( 4.0, 2.0 )\ny = base.dists.logistic.stdev( NaN, 1.0 )\ny = base.dists.logistic.stdev( 0.0, NaN )\ny = base.dists.logistic.stdev( 0.0, 0.0 )\n","base.dists.logistic.variance":"var y = base.dists.logistic.variance( 0.0, 1.0 )\ny = base.dists.logistic.variance( 4.0, 2.0 )\ny = base.dists.logistic.variance( NaN, 1.0 )\ny = base.dists.logistic.variance( 0.0, NaN )\ny = base.dists.logistic.variance( 0.0, 0.0 )\n","base.dists.lognormal.cdf":"var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\ny = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\ny = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.cdf.factory":"var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 4.0 )\n","base.dists.lognormal.entropy":"var y = base.dists.lognormal.entropy( 0.0, 1.0 )\ny = base.dists.lognormal.entropy( 5.0, 2.0 )\ny = base.dists.lognormal.entropy( NaN, 1.0 )\ny = base.dists.lognormal.entropy( 0.0, NaN )\ny = base.dists.lognormal.entropy( 0.0, 0.0 )\n","base.dists.lognormal.kurtosis":"var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\ny = base.dists.lognormal.kurtosis( 5.0, 2.0 )\ny = base.dists.lognormal.kurtosis( NaN, 1.0 )\ny = base.dists.lognormal.kurtosis( 0.0, NaN )\ny = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n","base.dists.lognormal.LogNormal":"var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\nlognormal.mu\nlognormal.sigma\nlognormal.entropy\nlognormal.kurtosis\nlognormal.mean\nlognormal.median\nlognormal.mode\nlognormal.skewness\nlognormal.stdev\nlognormal.variance\nlognormal.cdf( 0.8 )\nlognormal.logcdf( 0.8 )\nlognormal.logpdf( 2.0 )\nlognormal.pdf( 2.0 )\nlognormal.quantile( 0.9 )\n","base.dists.lognormal.logcdf":"var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\ny = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.lognormal.logcdf.factory":"var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.lognormal.logpdf":"var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.logpdf.factory":"var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.lognormal.mean":"var y = base.dists.lognormal.mean( 0.0, 1.0 )\ny = base.dists.lognormal.mean( 4.0, 2.0 )\ny = base.dists.lognormal.mean( NaN, 1.0 )\ny = base.dists.lognormal.mean( 0.0, NaN )\ny = base.dists.lognormal.mean( 0.0, 0.0 )\n","base.dists.lognormal.median":"var y = base.dists.lognormal.median( 0.0, 1.0 )\ny = base.dists.lognormal.median( 5.0, 2.0 )\ny = base.dists.lognormal.median( NaN, 1.0 )\ny = base.dists.lognormal.median( 0.0, NaN )\ny = base.dists.lognormal.median( 0.0, 0.0 )\n","base.dists.lognormal.mode":"var y = base.dists.lognormal.mode( 0.0, 1.0 )\ny = base.dists.lognormal.mode( 5.0, 2.0 )\ny = base.dists.lognormal.mode( NaN, 1.0 )\ny = base.dists.lognormal.mode( 0.0, NaN )\ny = base.dists.lognormal.mode( 0.0, 0.0 )\n","base.dists.lognormal.pdf":"var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.pdf.factory":"var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.lognormal.quantile":"var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\ny = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n","base.dists.lognormal.quantile.factory":"var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.lognormal.skewness":"var y = base.dists.lognormal.skewness( 0.0, 1.0 )\ny = base.dists.lognormal.skewness( 5.0, 2.0 )\ny = base.dists.lognormal.skewness( NaN, 1.0 )\ny = base.dists.lognormal.skewness( 0.0, NaN )\ny = base.dists.lognormal.skewness( 0.0, 0.0 )\n","base.dists.lognormal.stdev":"var y = base.dists.lognormal.stdev( 0.0, 1.0 )\ny = base.dists.lognormal.stdev( 4.0, 2.0 )\ny = base.dists.lognormal.stdev( NaN, 1.0 )\ny = base.dists.lognormal.stdev( 0.0, NaN )\ny = base.dists.lognormal.stdev( 0.0, 0.0 )\n","base.dists.lognormal.variance":"var y = base.dists.lognormal.variance( 0.0, 1.0 )\ny = base.dists.lognormal.variance( 4.0, 2.0 )\ny = base.dists.lognormal.variance( NaN, 1.0 )\ny = base.dists.lognormal.variance( 0.0, NaN )\ny = base.dists.lognormal.variance( 0.0, 0.0 )\n","base.dists.negativeBinomial.cdf":"var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n","base.dists.negativeBinomial.cdf.factory":"var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\nvar y = myCDF( 3.0 )\ny = myCDF( 11.0 )\n","base.dists.negativeBinomial.kurtosis":"var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\nv = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n","base.dists.negativeBinomial.logpmf":"var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.logpmf.factory":"var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\nvar y = mylogPMF( 3.0 )\ny = mylogPMF( 5.0 )\n","base.dists.negativeBinomial.mean":"var v = base.dists.negativeBinomial.mean( 100, 0.2 )\nv = base.dists.negativeBinomial.mean( 20, 0.5 )\n","base.dists.negativeBinomial.mgf":"var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\ny = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\ny = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n","base.dists.negativeBinomial.mgf.factory":"var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\nvar y = myMGF( 0.2 )\ny = myMGF( 0.4 )\n","base.dists.negativeBinomial.mode":"var v = base.dists.negativeBinomial.mode( 100, 0.2 )\nv = base.dists.negativeBinomial.mode( 20, 0.5 )\n","base.dists.negativeBinomial.NegativeBinomial":"var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\nnbinomial.r\nnbinomial.p\nnbinomial.kurtosis\nnbinomial.mean\nnbinomial.mode\nnbinomial.skewness\nnbinomial.stdev\nnbinomial.variance\nnbinomial.cdf( 2.9 )\nnbinomial.logpmf( 3.0 )\nnbinomial.mgf( 0.2 )\nnbinomial.pmf( 3.0 )\nnbinomial.quantile( 0.8 )\n","base.dists.negativeBinomial.pmf":"var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.pmf.factory":"var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\nvar y = myPMF( 3.0 )\ny = myPMF( 5.0 )\n","base.dists.negativeBinomial.quantile":"var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\ny = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\ny = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\ny = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n","base.dists.negativeBinomial.quantile.factory":"var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\nvar y = myQuantile( 0.1 )\ny = myQuantile( 0.9 )\n","base.dists.negativeBinomial.skewness":"var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\nv = base.dists.negativeBinomial.skewness( 20, 0.5 )\n","base.dists.negativeBinomial.stdev":"var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\nv = base.dists.negativeBinomial.stdev( 20, 0.5 )\n","base.dists.negativeBinomial.variance":"var v = base.dists.negativeBinomial.variance( 100, 0.2 )\nv = base.dists.negativeBinomial.variance( 20, 0.5 )\n","base.dists.normal.cdf":"var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\ny = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.cdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.cdf( 0.0, 0.0, NaN )\ny = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n","base.dists.normal.cdf.factory":"var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\n","base.dists.normal.entropy":"var y = base.dists.normal.entropy( 0.0, 1.0 )\ny = base.dists.normal.entropy( 4.0, 3.0 )\ny = base.dists.normal.entropy( NaN, 1.0 )\ny = base.dists.normal.entropy( 0.0, NaN )\ny = base.dists.normal.entropy( 0.0, 0.0 )\n","base.dists.normal.kurtosis":"var y = base.dists.normal.kurtosis( 0.0, 1.0 )\ny = base.dists.normal.kurtosis( 4.0, 3.0 )\ny = base.dists.normal.kurtosis( NaN, 1.0 )\ny = base.dists.normal.kurtosis( 0.0, NaN )\ny = base.dists.normal.kurtosis( 0.0, 0.0 )\n","base.dists.normal.logcdf":"var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logcdf.factory":"var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.normal.logpdf":"var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logpdf.factory":"var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\nvar y = myLogPDF( 10.0 )\n","base.dists.normal.mean":"var y = base.dists.normal.mean( 0.0, 1.0 )\ny = base.dists.normal.mean( 4.0, 2.0 )\ny = base.dists.normal.mean( NaN, 1.0 )\ny = base.dists.normal.mean( 0.0, NaN )\ny = base.dists.normal.mean( 0.0, 0.0 )\n","base.dists.normal.median":"var y = base.dists.normal.median( 0.0, 1.0 )\ny = base.dists.normal.median( 4.0, 2.0 )\ny = base.dists.normal.median( NaN, 1.0 )\ny = base.dists.normal.median( 0.0, NaN )\ny = base.dists.normal.median( 0.0, 0.0 )\n","base.dists.normal.mgf":"var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.mgf( NaN, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, NaN, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, NaN )\ny = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n","base.dists.normal.mgf.factory":"var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.normal.mode":"var y = base.dists.normal.mode( 0.0, 1.0 )\ny = base.dists.normal.mode( 4.0, 2.0 )\ny = base.dists.normal.mode( NaN, 1.0 )\ny = base.dists.normal.mode( 0.0, NaN )\ny = base.dists.normal.mode( 0.0, 0.0 )\n","base.dists.normal.Normal":"var normal = base.dists.normal.Normal( -2.0, 3.0 );\nnormal.mu\nnormal.sigma\nnormal.entropy\nnormal.kurtosis\nnormal.mean\nnormal.median\nnormal.mode\nnormal.skewness\nnormal.stdev\nnormal.variance\nnormal.cdf( 0.8 )\nnormal.logcdf( 0.8 )\nnormal.logpdf( 2.0 )\nnormal.mgf( 0.2 )\nnormal.pdf( 2.0 )\nnormal.quantile( 0.9 )\n","base.dists.normal.pdf":"var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.pdf( 0.0, 0.0, NaN )\ny = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.pdf.factory":"var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.normal.quantile":"var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.normal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.normal.quantile( 0.0, 0.0, NaN )\ny = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\ny = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n","base.dists.normal.quantile.factory":"var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.normal.skewness":"var y = base.dists.normal.skewness( 0.0, 1.0 )\ny = base.dists.normal.skewness( 4.0, 3.0 )\ny = base.dists.normal.skewness( NaN, 1.0 )\ny = base.dists.normal.skewness( 0.0, NaN )\ny = base.dists.normal.skewness( 0.0, 0.0 )\n","base.dists.normal.stdev":"var y = base.dists.normal.stdev( 0.0, 1.0 )\ny = base.dists.normal.stdev( 4.0, 3.0 )\ny = base.dists.normal.stdev( NaN, 1.0 )\ny = base.dists.normal.stdev( 0.0, NaN )\ny = base.dists.normal.stdev( 0.0, 0.0 )\n","base.dists.normal.variance":"var y = base.dists.normal.variance( 0.0, 1.0 )\ny = base.dists.normal.variance( 4.0, 3.0 )\ny = base.dists.normal.variance( NaN, 1.0 )\ny = base.dists.normal.variance( 0.0, NaN )\ny = base.dists.normal.variance( 0.0, 0.0 )\n","base.dists.pareto1.cdf":"var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.cdf.factory":"var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 2.5 )\n","base.dists.pareto1.entropy":"var v = base.dists.pareto1.entropy( 0.8, 1.0 )\nv = base.dists.pareto1.entropy( 4.0, 12.0 )\nv = base.dists.pareto1.entropy( 8.0, 2.0 )\n","base.dists.pareto1.kurtosis":"var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\nv = base.dists.pareto1.kurtosis( 4.5, 12.0 )\nv = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n","base.dists.pareto1.logcdf":"var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.logcdf.factory":"var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\nvar y = mylogCDF( 3.0 )\ny = mylogCDF( 2.5 )\n","base.dists.pareto1.logpdf":"var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.logpdf.factory":"var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\nvar y = mylogPDF( 0.8 )\ny = mylogPDF( 2.0 )\n","base.dists.pareto1.mean":"var v = base.dists.pareto1.mean( 0.8, 1.0 )\nv = base.dists.pareto1.mean( 4.0, 12.0 )\nv = base.dists.pareto1.mean( 8.0, 2.0 )\n","base.dists.pareto1.median":"var v = base.dists.pareto1.median( 0.8, 1.0 )\nv = base.dists.pareto1.median( 4.0, 12.0 )\nv = base.dists.pareto1.median( 8.0, 2.0 )\n","base.dists.pareto1.mode":"var v = base.dists.pareto1.mode( 0.8, 1.0 )\nv = base.dists.pareto1.mode( 4.0, 12.0 )\nv = base.dists.pareto1.mode( 8.0, 2.0 )\n","base.dists.pareto1.Pareto1":"var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\npareto1.alpha\npareto1.beta\npareto1.entropy\npareto1.kurtosis\npareto1.mean\npareto1.median\npareto1.mode\npareto1.skewness\npareto1.variance\npareto1.cdf( 7.0 )\npareto1.logcdf( 7.0 )\npareto1.logpdf( 5.0 )\npareto1.pdf( 5.0 )\npareto1.quantile( 0.8 )\n","base.dists.pareto1.pdf":"var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.pdf.factory":"var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\nvar y = myPDF( 0.8 )\ny = myPDF( 2.0 )\n","base.dists.pareto1.quantile":"var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\ny = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n","base.dists.pareto1.quantile.factory":"var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.pareto1.skewness":"var v = base.dists.pareto1.skewness( 3.5, 1.0 )\nv = base.dists.pareto1.skewness( 4.0, 12.0 )\nv = base.dists.pareto1.skewness( 8.0, 2.0 )\n","base.dists.pareto1.stdev":"var v = base.dists.pareto1.stdev( 0.8, 1.0 )\nv = base.dists.pareto1.stdev( 4.0, 12.0 )\nv = base.dists.pareto1.stdev( 8.0, 2.0 )\n","base.dists.pareto1.variance":"var v = base.dists.pareto1.variance( 0.8, 1.0 )\nv = base.dists.pareto1.variance( 4.0, 12.0 )\nv = base.dists.pareto1.variance( 8.0, 2.0 )\n","base.dists.poisson.cdf":"var y = base.dists.poisson.cdf( 2.0, 0.5 )\ny = base.dists.poisson.cdf( 2.0, 10.0 )\ny = base.dists.poisson.cdf( -1.0, 4.0 )\ny = base.dists.poisson.cdf( NaN, 1.0 )\ny = base.dists.poisson.cdf( 0.0, NaN )\ny = base.dists.poisson.cdf( 2.0, -1.0 )\ny = base.dists.poisson.cdf( -2.0, 0.0 )\ny = base.dists.poisson.cdf( 0.0, 0.0 )\ny = base.dists.poisson.cdf( 10.0, 0.0 )\n","base.dists.poisson.cdf.factory":"var mycdf = base.dists.poisson.cdf.factory( 5.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 8.0 )\n","base.dists.poisson.entropy":"var v = base.dists.poisson.entropy( 11.0 )\nv = base.dists.poisson.entropy( 4.5 )\n","base.dists.poisson.kurtosis":"var v = base.dists.poisson.kurtosis( 11.0 )\nv = base.dists.poisson.kurtosis( 4.5 )\n","base.dists.poisson.logpmf":"var y = base.dists.poisson.logpmf( 4.0, 3.0 )\ny = base.dists.poisson.logpmf( 1.0, 3.0 )\ny = base.dists.poisson.logpmf( -1.0, 2.0 )\ny = base.dists.poisson.logpmf( 0.0, NaN )\ny = base.dists.poisson.logpmf( NaN, 0.5 )\ny = base.dists.poisson.logpmf( 2.0, -0.5 )\ny = base.dists.poisson.logpmf( 2.0, 0.0 )\ny = base.dists.poisson.logpmf( 0.0, 0.0 )\n","base.dists.poisson.logpmf.factory":"var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.poisson.mean":"var v = base.dists.poisson.mean( 11.0 )\nv = base.dists.poisson.mean( 4.5 )\n","base.dists.poisson.median":"var v = base.dists.poisson.median( 11.0 )\nv = base.dists.poisson.median( 4.5 )\n","base.dists.poisson.mgf":"var y = base.dists.poisson.mgf( 1.0, 1.5 )\ny = base.dists.poisson.mgf( 0.5, 0.5 )\ny = base.dists.poisson.mgf( NaN, 0.5 )\ny = base.dists.poisson.mgf( 0.0, NaN )\ny = base.dists.poisson.mgf( -2.0, -1.0 )\n","base.dists.poisson.mgf.factory":"var myMGF = base.dists.poisson.mgf.factory( 2.0 );\nvar y = myMGF( 0.1 )\n","base.dists.poisson.mode":"var v = base.dists.poisson.mode( 11.0 )\nv = base.dists.poisson.mode( 4.5 )\n","base.dists.poisson.pmf":"var y = base.dists.poisson.pmf( 4.0, 3.0 )\ny = base.dists.poisson.pmf( 1.0, 3.0 )\ny = base.dists.poisson.pmf( -1.0, 2.0 )\ny = base.dists.poisson.pmf( 0.0, NaN )\ny = base.dists.poisson.pmf( NaN, 0.5 )\ny = base.dists.poisson.pmf( 2.0, -0.5 )\ny = base.dists.poisson.pmf( 2.0, 0.0 )\ny = base.dists.poisson.pmf( 0.0, 0.0 )\n","base.dists.poisson.pmf.factory":"var mypmf = base.dists.poisson.pmf.factory( 1.0 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.poisson.Poisson":"var poisson = base.dists.poisson.Poisson( 6.0 );\npoisson.lambda\npoisson.entropy\npoisson.kurtosis\npoisson.mean\npoisson.median\npoisson.mode\npoisson.skewness\npoisson.stdev\npoisson.variance\npoisson.cdf( 4.0 )\npoisson.logpmf( 2.0 )\npoisson.mgf( 0.5 )\npoisson.pmf( 2.0 )\npoisson.quantile( 0.5 )\n","base.dists.poisson.quantile":"var y = base.dists.poisson.quantile( 0.5, 2.0 )\ny = base.dists.poisson.quantile( 0.9, 4.0 )\ny = base.dists.poisson.quantile( 0.1, 200.0 )\ny = base.dists.poisson.quantile( 1.1, 0.0 )\ny = base.dists.poisson.quantile( -0.2, 0.0 )\ny = base.dists.poisson.quantile( NaN, 0.5 )\ny = base.dists.poisson.quantile( 0.0, NaN )\ny = base.dists.poisson.quantile( 2.0, -1.0 )\ny = base.dists.poisson.quantile( 0.1, 0.0 )\ny = base.dists.poisson.quantile( 0.9, 0.0 )\n","base.dists.poisson.quantile.factory":"var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.poisson.skewness":"var v = base.dists.poisson.skewness( 11.0 )\nv = base.dists.poisson.skewness( 4.5 )\n","base.dists.poisson.stdev":"var v = base.dists.poisson.stdev( 11.0 )\nv = base.dists.poisson.stdev( 4.5 )\n","base.dists.poisson.variance":"var v = base.dists.poisson.variance( 11.0 )\nv = base.dists.poisson.variance( 4.5 )\n","base.dists.rayleigh.cdf":"var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\ny = base.dists.rayleigh.cdf( 1.0, 2.0 )\ny = base.dists.rayleigh.cdf( -1.0, 4.0 )\ny = base.dists.rayleigh.cdf( NaN, 1.0 )\ny = base.dists.rayleigh.cdf( 0.0, NaN )\ny = base.dists.rayleigh.cdf( 2.0, -1.0 )\ny = base.dists.rayleigh.cdf( -2.0, 0.0 )\ny = base.dists.rayleigh.cdf( 0.0, 0.0 )\ny = base.dists.rayleigh.cdf( 2.0, 0.0 )\n","base.dists.rayleigh.cdf.factory":"var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 0.5 )\n","base.dists.rayleigh.entropy":"var v = base.dists.rayleigh.entropy( 11.0 )\nv = base.dists.rayleigh.entropy( 4.5 )\n","base.dists.rayleigh.kurtosis":"var v = base.dists.rayleigh.kurtosis( 11.0 )\nv = base.dists.rayleigh.kurtosis( 4.5 )\n","base.dists.rayleigh.logcdf":"var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\ny = base.dists.rayleigh.logcdf( 1.0, 2.0 )\ny = base.dists.rayleigh.logcdf( -1.0, 4.0 )\ny = base.dists.rayleigh.logcdf( NaN, 1.0 )\ny = base.dists.rayleigh.logcdf( 0.0, NaN )\ny = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n","base.dists.rayleigh.logcdf.factory":"var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\nvar y = mylogcdf( 1.0 )\ny = mylogcdf( 0.5 )\n","base.dists.rayleigh.logpdf":"var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\ny = base.dists.rayleigh.logpdf( 2.0, 0.8 )\ny = base.dists.rayleigh.logpdf( -1.0, 0.5 )\ny = base.dists.rayleigh.logpdf( 0.0, NaN )\ny = base.dists.rayleigh.logpdf( NaN, 2.0 )\ny = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n","base.dists.rayleigh.logpdf.factory":"var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\nvar y = mylogpdf( 6.0 )\ny = mylogpdf( 4.0 )\n","base.dists.rayleigh.mean":"var v = base.dists.rayleigh.mean( 11.0 )\nv = base.dists.rayleigh.mean( 4.5 )\n","base.dists.rayleigh.median":"var v = base.dists.rayleigh.median( 11.0 )\nv = base.dists.rayleigh.median( 4.5 )\n","base.dists.rayleigh.mgf":"var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\ny = base.dists.rayleigh.mgf( 1.0, 2.0 )\ny = base.dists.rayleigh.mgf( -1.0, 4.0 )\ny = base.dists.rayleigh.mgf( NaN, 1.0 )\ny = base.dists.rayleigh.mgf( 0.0, NaN )\ny = base.dists.rayleigh.mgf( 0.5, -1.0 )\n","base.dists.rayleigh.mgf.factory":"var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.rayleigh.mode":"var v = base.dists.rayleigh.mode( 11.0 )\nv = base.dists.rayleigh.mode( 4.5 )\n","base.dists.rayleigh.pdf":"var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.8 )\ny = base.dists.rayleigh.pdf( -1.0, 0.5 )\ny = base.dists.rayleigh.pdf( 0.0, NaN )\ny = base.dists.rayleigh.pdf( NaN, 2.0 )\ny = base.dists.rayleigh.pdf( 2.0, -1.0 )\ny = base.dists.rayleigh.pdf( -2.0, 0.0 )\ny = base.dists.rayleigh.pdf( 0.0, 0.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.0 )\n","base.dists.rayleigh.pdf.factory":"var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\nvar y = myPDF( 6.0 )\ny = myPDF( 4.0 )\n","base.dists.rayleigh.quantile":"var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\ny = base.dists.rayleigh.quantile( 0.5, 4.0 )\ny = base.dists.rayleigh.quantile( 1.1, 1.0 )\ny = base.dists.rayleigh.quantile( -0.2, 1.0 )\ny = base.dists.rayleigh.quantile( NaN, 1.0 )\ny = base.dists.rayleigh.quantile( 0.0, NaN )\ny = base.dists.rayleigh.quantile( 0.5, -1.0 )\n","base.dists.rayleigh.quantile.factory":"var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.rayleigh.Rayleigh":"var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\nrayleigh.sigma\nrayleigh.entropy\nrayleigh.kurtosis\nrayleigh.mean\nrayleigh.median\nrayleigh.mode\nrayleigh.skewness\nrayleigh.stdev\nrayleigh.variance\nrayleigh.cdf( 1.0 )\nrayleigh.logcdf( 1.0 )\nrayleigh.logpdf( 1.5 )\nrayleigh.mgf( -0.5 )\nrayleigh.pdf( 1.5 )\nrayleigh.quantile( 0.5 )\n","base.dists.rayleigh.skewness":"var v = base.dists.rayleigh.skewness( 11.0 )\nv = base.dists.rayleigh.skewness( 4.5 )\n","base.dists.rayleigh.stdev":"var v = base.dists.rayleigh.stdev( 9.0 )\nv = base.dists.rayleigh.stdev( 4.5 )\n","base.dists.rayleigh.variance":"var v = base.dists.rayleigh.variance( 9.0 )\nv = base.dists.rayleigh.variance( 4.5 )\n","base.dists.signrank.cdf":"var y = base.dists.signrank.cdf( 3, 7 )\ny = base.dists.signrank.cdf( 1.8, 3 )\ny = base.dists.signrank.cdf( -1.0, 40 )\ny = base.dists.signrank.cdf( NaN, 10 )\ny = base.dists.signrank.cdf( 0.0, NaN )\n","base.dists.signrank.cdf.factory":"var myCDF = base.dists.signrank.cdf.factory( 8 );\nvar y = myCDF( 5.7 )\ny = myCDF( 2.2 )\n","base.dists.signrank.pdf":"var y = base.dists.signrank.pdf( 3, 7 )\ny = base.dists.signrank.pdf( 1.8, 3 )\ny = base.dists.signrank.pdf( -1.0, 40 )\ny = base.dists.signrank.pdf( NaN, 10 )\ny = base.dists.signrank.pdf( 0.0, NaN )\n","base.dists.signrank.pdf.factory":"var myPDF = base.dists.signrank.pdf.factory( 8 );\nvar y = myPDF( 6.0 )\ny = myPDF( 2.0 )\n","base.dists.signrank.quantile":"var y = base.dists.signrank.quantile( 0.8, 5 )\ny = base.dists.signrank.quantile( 0.5, 4 )\ny = base.dists.signrank.quantile( 1.1, 5 )\ny = base.dists.signrank.quantile( -0.2, 5 )\ny = base.dists.signrank.quantile( NaN, 5 )\ny = base.dists.signrank.quantile( 0.0, NaN )\n","base.dists.signrank.quantile.factory":"var myQuantile = base.dists.signrank.quantile.factory( 8 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.studentizedRange.cdf":"var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\ny = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n","base.dists.studentizedRange.cdf.factory":"var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.studentizedRange.quantile":"var y = quantile( 0.5, 3.0, 2.0 )\ny = quantile( 0.9, 17.0, 2.0 )\ny = quantile( 0.5, 3.0, 2.0, 2 )\ny = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\ny = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n","base.dists.studentizedRange.quantile.factory":"var myQuantile = quantile.factory( 3.0, 3.0 );\nvar y = myQuantile( 0.5 )\n ~1.791\ny = myQuantile( 0.8 )\n ~3.245\n","base.dists.t.cdf":"var y = base.dists.t.cdf( 2.0, 0.1 )\ny = base.dists.t.cdf( 1.0, 2.0 )\ny = base.dists.t.cdf( -1.0, 4.0 )\ny = base.dists.t.cdf( NaN, 1.0 )\ny = base.dists.t.cdf( 0.0, NaN )\ny = base.dists.t.cdf( 2.0, -1.0 )\n","base.dists.t.cdf.factory":"var mycdf = base.dists.t.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.t.entropy":"var v = base.dists.t.entropy( 11.0 )\nv = base.dists.t.entropy( 4.5 )\n","base.dists.t.kurtosis":"var v = base.dists.t.kurtosis( 11.0 )\nv = base.dists.t.kurtosis( 4.5 )\n","base.dists.t.logcdf":"var y = base.dists.t.logcdf( 2.0, 0.1 )\ny = base.dists.t.logcdf( 1.0, 2.0 )\ny = base.dists.t.logcdf( -1.0, 4.0 )\ny = base.dists.t.logcdf( NaN, 1.0 )\ny = base.dists.t.logcdf( 0.0, NaN )\ny = base.dists.t.logcdf( 2.0, -1.0 )\n","base.dists.t.logcdf.factory":"var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.t.logpdf":"var y = base.dists.t.logpdf( 0.3, 4.0 )\ny = base.dists.t.logpdf( 2.0, 0.7 )\ny = base.dists.t.logpdf( -1.0, 0.5 )\ny = base.dists.t.logpdf( 0.0, NaN )\ny = base.dists.t.logpdf( NaN, 2.0 )\ny = base.dists.t.logpdf( 2.0, -1.0 )\n","base.dists.t.logpdf.factory":"var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\nvar y = mylogPDF( 1.0 )\n","base.dists.t.mean":"var v = base.dists.t.mean( 11.0 )\nv = base.dists.t.mean( 4.5 )\n","base.dists.t.median":"var v = base.dists.t.median( 11.0 )\nv = base.dists.t.median( 4.5 )\n","base.dists.t.mode":"var v = base.dists.t.mode( 11.0 )\nv = base.dists.t.mode( 4.5 )\n","base.dists.t.pdf":"var y = base.dists.t.pdf( 0.3, 4.0 )\ny = base.dists.t.pdf( 2.0, 0.7 )\ny = base.dists.t.pdf( -1.0, 0.5 )\ny = base.dists.t.pdf( 0.0, NaN )\ny = base.dists.t.pdf( NaN, 2.0 )\ny = base.dists.t.pdf( 2.0, -1.0 )\n","base.dists.t.pdf.factory":"var myPDF = base.dists.t.pdf.factory( 3.0 );\nvar y = myPDF( 1.0 )\n","base.dists.t.quantile":"var y = base.dists.t.quantile( 0.8, 1.0 )\ny = base.dists.t.quantile( 0.1, 1.0 )\ny = base.dists.t.quantile( 0.5, 0.1 )\ny = 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0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logcdf.factory":"var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.triangular.logpdf":"var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logpdf.factory":"var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\nvar y = mylogpdf( 2.0 )\ny = mylogpdf( 12.0 )\n","base.dists.triangular.mean":"var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n","base.dists.triangular.median":"var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.median( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n","base.dists.triangular.mgf":"var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n","base.dists.triangular.mgf.factory":"var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\nvar y = mymgf( -1.0 )\ny = mymgf( 2.0 )\n","base.dists.triangular.mode":"var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n","base.dists.triangular.pdf":"var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.pdf.factory":"var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\nvar y = mypdf( 2.0 )\ny = mypdf( 12.0 )\n","base.dists.triangular.quantile":"var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\ny = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n","base.dists.triangular.quantile.factory":"var myquantile = base.dists.triangular.quantile.factory( 2.0, 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base.dists.triangular.variance( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n","base.dists.uniform.cdf":"var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.cdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.cdf.factory":"var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.uniform.entropy":"var v = base.dists.uniform.entropy( 0.0, 1.0 )\nv = base.dists.uniform.entropy( 4.0, 12.0 )\nv = base.dists.uniform.entropy( 2.0, 8.0 )\n","base.dists.uniform.kurtosis":"var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\nv = base.dists.uniform.kurtosis( 4.0, 12.0 )\nv = base.dists.uniform.kurtosis( 2.0, 8.0 )\n","base.dists.uniform.logcdf":"var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.logcdf.factory":"var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.uniform.logpdf":"var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.logpdf.factory":"var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.uniform.mean":"var v = base.dists.uniform.mean( 0.0, 1.0 )\nv = base.dists.uniform.mean( 4.0, 12.0 )\nv = base.dists.uniform.mean( 2.0, 8.0 )\n","base.dists.uniform.median":"var v = base.dists.uniform.median( 0.0, 1.0 )\nv = base.dists.uniform.median( 4.0, 12.0 )\nv = base.dists.uniform.median( 2.0, 8.0 )\n","base.dists.uniform.mgf":"var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\ny = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\ny = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n","base.dists.uniform.mgf.factory":"var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.uniform.pdf":"var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.pdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.pdf.factory":"var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.uniform.quantile":"var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\ny = base.dists.uniform.quantile( 0.0, 0.0, NaN )\ny = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n","base.dists.uniform.quantile.factory":"var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.uniform.skewness":"var v = base.dists.uniform.skewness( 0.0, 1.0 )\nv = base.dists.uniform.skewness( 4.0, 12.0 )\nv = base.dists.uniform.skewness( 2.0, 8.0 )\n","base.dists.uniform.stdev":"var v = base.dists.uniform.stdev( 0.0, 1.0 )\nv = base.dists.uniform.stdev( 4.0, 12.0 )\nv = base.dists.uniform.stdev( 2.0, 8.0 )\n","base.dists.uniform.Uniform":"var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\nuniform.a\nuniform.b\nuniform.entropy\nuniform.kurtosis\nuniform.mean\nuniform.median\nuniform.skewness\nuniform.stdev\nuniform.variance\nuniform.cdf( 0.8 )\nuniform.logcdf( 0.5 )\nuniform.logpdf( 1.0 )\nuniform.mgf( 0.8 )\nuniform.pdf( 0.8 )\nuniform.quantile( 0.8 )\n","base.dists.uniform.variance":"var v = base.dists.uniform.variance( 0.0, 1.0 )\nv = base.dists.uniform.variance( 4.0, 12.0 )\nv = base.dists.uniform.variance( 2.0, 8.0 )\n","base.dists.weibull.cdf":"var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.cdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.cdf.factory":"var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\nvar y = myCDF( 12.0 )\n","base.dists.weibull.entropy":"var v = base.dists.weibull.entropy( 1.0, 1.0 )\nv = base.dists.weibull.entropy( 4.0, 12.0 )\nv = base.dists.weibull.entropy( 8.0, 2.0 )\n","base.dists.weibull.kurtosis":"var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\nv = base.dists.weibull.kurtosis( 4.0, 12.0 )\nv = base.dists.weibull.kurtosis( 8.0, 2.0 )\n","base.dists.weibull.logcdf":"var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logcdf.factory":"var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\nvar y = mylogcdf( 12.0 )\n","base.dists.weibull.logpdf":"var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logpdf.factory":"var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\ny = mylofpdf( 7.0 )\n","base.dists.weibull.mean":"var v = base.dists.weibull.mean( 1.0, 1.0 )\nv = base.dists.weibull.mean( 4.0, 12.0 )\nv = base.dists.weibull.mean( 8.0, 2.0 )\n","base.dists.weibull.median":"var v = base.dists.weibull.median( 1.0, 1.0 )\nv = base.dists.weibull.median( 4.0, 12.0 )\nv = base.dists.weibull.median( 8.0, 2.0 )\n","base.dists.weibull.mgf":"var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\ny = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\ny = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\ny = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.mgf( 0.0, 1.0, NaN )\ny = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\ny = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n","base.dists.weibull.mgf.factory":"var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.08 )\n","base.dists.weibull.mode":"var v = base.dists.weibull.mode( 1.0, 1.0 )\nv = base.dists.weibull.mode( 4.0, 12.0 )\nv = base.dists.weibull.mode( 8.0, 2.0 )\n","base.dists.weibull.pdf":"var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.pdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.pdf.factory":"var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\nvar y = myPDF( 7.0 )\n","base.dists.weibull.quantile":"var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\ny = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\ny = base.dists.weibull.quantile( 0.0, 0.0, NaN )\ny = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n","base.dists.weibull.quantile.factory":"var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.weibull.skewness":"var v = base.dists.weibull.skewness( 1.0, 1.0 )\nv = base.dists.weibull.skewness( 4.0, 12.0 )\nv = base.dists.weibull.skewness( 8.0, 2.0 )\n","base.dists.weibull.stdev":"var v = base.dists.weibull.stdev( 1.0, 1.0 )\nv = base.dists.weibull.stdev( 4.0, 12.0 )\nv = base.dists.weibull.stdev( 8.0, 2.0 )\n","base.dists.weibull.variance":"var v = base.dists.weibull.variance( 1.0, 1.0 )\nv = base.dists.weibull.variance( 4.0, 12.0 )\nv = base.dists.weibull.variance( 8.0, 2.0 )\n","base.dists.weibull.Weibull":"var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\nweibull.k\nweibull.lambda\nweibull.entropy\nweibull.kurtosis\nweibull.mean\nweibull.median\nweibull.mode\nweibull.skewness\nweibull.stdev\nweibull.variance\nweibull.cdf( 3.0 )\nweibull.logcdf( 3.0 )\nweibull.logpdf( 1.0 )\nweibull.mgf( -0.5 )\nweibull.pdf( 3.0 )\nweibull.quantile( 0.8 )\n","base.ellipe":"var y = base.ellipe( 0.5 )\ny = base.ellipe( -1.0 )\ny = base.ellipe( 2.0 )\ny = base.ellipe( PINF )\ny = base.ellipe( NINF )\ny = base.ellipe( NaN )\n","base.ellipj":"var v = base.ellipj( 0.3, 0.5 )\nv = base.ellipj( 0.0, 0.0 )\nv = base.ellipj( Infinity, 1.0 )\nv = base.ellipj( 0.0, -2.0)\nv = base.ellipj( NaN, NaN )\n","base.ellipj.assign":"var out = new Float64Array( 4 );\nvar v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.ellipj.sn":"var v = base.ellipj.sn( 0.3, 0.5 )\n","base.ellipj.cn":"var v = base.ellipj.cn( 0.3, 0.5 )\n","base.ellipj.dn":"var v = base.ellipj.dn( 0.3, 0.5 )\n","base.ellipj.am":"var v = base.ellipj.am( 0.3, 0.5 )\n","base.ellipk":"var y = base.ellipk( 0.5 )\ny = base.ellipk( -1.0 )\ny = base.ellipk( 2.0 )\ny = base.ellipk( PINF )\ny = base.ellipk( NINF )\ny = base.ellipk( NaN )\n","base.endsWith":"var bool = base.endsWith( 'beep', 'ep', 4 )\nbool = base.endsWith( 'Beep', 'op', 4 )\nbool = base.endsWith( 'Beep', 'ee', 3 )\nbool = base.endsWith( 'Beep', 'ee', -1 )\nbool = base.endsWith( 'beep', '', 4 )\n","base.epsdiff":"var d = base.epsdiff( 12.15, 12.149999999999999 )\nd = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\nfunction scale( x, y ) { return ( x > y ) ? y : x; };\nd = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n","base.erf":"var y = base.erf( 2.0 )\ny = base.erf( -1.0 )\ny = base.erf( -0.0 )\ny = base.erf( NaN )\n","base.erfc":"var y = base.erfc( 2.0 )\ny = base.erfc( -1.0 )\ny = base.erfc( 0.0 )\ny = base.erfc( PINF )\ny = base.erfc( NINF )\ny = base.erfc( NaN )\n","base.erfcinv":"var y = base.erfcinv( 0.5 )\ny = base.erfcinv( 0.8 )\ny = base.erfcinv( 0.0 )\ny = base.erfcinv( 2.0 )\ny = base.erfcinv( NaN )\n","base.erfcx":"var y = base.erfcx( 1.0 )\ny = base.erfcx( -1.0 )\ny = base.erfcx( 0.0 )\ny = base.erfcx( NaN )\n","base.erfinv":"var y = base.erfinv( 0.5 )\ny = base.erfinv( 0.8 )\ny = base.erfinv( 0.0 )\ny = base.erfinv( -0.0 )\ny = base.erfinv( -1.0 )\ny = base.erfinv( 1.0 )\ny = base.erfinv( NaN )\n","base.eta":"var y = base.eta( 0.0 )\ny = base.eta( -1.0 )\ny = base.eta( 1.0 )\ny = base.eta( 3.14 )\ny = base.eta( NaN )\n","base.evalpoly":"var arr = [ 3.0, 2.0, 1.0 ];\nvar v = base.evalpoly( arr, 10.0 )\n","base.evalpoly.factory":"var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\nvar v = f( 10.0 )\nv = f( 5.0 )\n","base.evalrational":"var P = [ -6.0, -5.0, 4.0, 2.0 ];\nvar Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\nvar v = base.evalrational( P, Q, 6.0 )\n","base.evalrational.factory":"var P = [ 20.0, 8.0, 3.0 ];\nvar Q = [ 10.0, 9.0, 1.0 ];\nvar f = base.evalrational.factory( P, Q );\nvar v = f( 10.0 )\nv = f( 2.0 )\n","base.exp":"var y = base.exp( 4.0 )\ny = base.exp( -9.0 )\ny = base.exp( 0.0 )\ny = base.exp( NaN )\n","base.exp2":"var y = base.exp2( 3.0 )\ny = base.exp2( -9.0 )\ny = base.exp2( 0.0 )\ny = base.exp2( NaN )\n","base.exp10":"var y = base.exp10( 3.0 )\ny = base.exp10( -9.0 )\ny = base.exp10( 0.0 )\ny = base.exp10( NaN )\n","base.expit":"var y = base.expit( 0.0 )\ny = base.expit( 1.0 )\ny = base.expit( -1.0 )\ny = base.expit( Infinity )\ny = base.expit( NaN )\n","base.expm1":"var y = base.expm1( 0.2 )\ny = base.expm1( -9.0 )\ny = base.expm1( 0.0 )\ny = base.expm1( NaN )\n","base.expm1rel":"var y = base.expm1rel( 0.0 )\ny = base.expm1rel( 1.0 )\ny = base.expm1rel( -1.0 )\ny = base.expm1rel( NaN )\n","base.exponent":"var exponent = base.exponent( 3.14e-307 )\nexponent = base.exponent( -3.14 )\nexponent = base.exponent( 0.0 )\nexponent = base.exponent( NaN )\n","base.exponentf":"var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\nexponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\nexponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\nexponent = base.exponentf( 0.0 )\nexponent = base.exponentf( NaN )\n","base.factorial":"var y = base.factorial( 3.0 )\ny = base.factorial( -1.5 )\ny = base.factorial( -0.5 )\ny = base.factorial( 0.5 )\ny = base.factorial( -10.0 )\ny = base.factorial( 171.0 )\ny = base.factorial( NaN )\n","base.factorial2":"var y = base.factorial2( 3 )\ny = base.factorial2( 5 )\ny = base.factorial2( 6 )\ny = base.factorial2( 301 )\ny = base.factorial2( NaN )\n","base.factorialln":"var y = base.factorialln( 3.0 )\ny = base.factorialln( 2.4 )\ny = base.factorialln( -1.0 )\ny = base.factorialln( -1.5 )\ny = base.factorialln( NaN )\n","base.fallingFactorial":"var v = base.fallingFactorial( 0.9, 5 )\nv = base.fallingFactorial( -9.0, 3 )\nv = base.fallingFactorial( 0.0, 2 )\nv = base.fallingFactorial( 3.0, -2 )\n","base.fibonacci":"var y = base.fibonacci( 0 )\ny = base.fibonacci( 1 )\ny = base.fibonacci( 2 )\ny = base.fibonacci( 3 )\ny = base.fibonacci( 4 )\ny = base.fibonacci( 79 )\ny = base.fibonacci( NaN )\n","base.fibonacciIndex":"var n = base.fibonacciIndex( 2 )\nn = base.fibonacciIndex( 3 )\nn = base.fibonacciIndex( 5 )\nn = base.fibonacciIndex( NaN )\nn = base.fibonacciIndex( 1 )\n","base.fibpoly":"var v = base.fibpoly( 5, 2.0 )\n","base.fibpoly.factory":"var polyval = base.fibpoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.firstCodePoint":"var out = base.firstCodePoint( 'beep', 1 )\nout = base.firstCodePoint( 'Boop', 1 )\nout = base.firstCodePoint( 'foo bar', 5 )\n","base.firstCodeUnit":"var out = base.firstCodeUnit( 'beep', 1 )\nout = base.firstCodeUnit( 'Boop', 1 )\nout = base.firstCodeUnit( 'foo bar', 5 )\n","base.firstGraphemeCluster":"var out = base.firstGraphemeCluster( 'beep', 1 )\nout = base.firstGraphemeCluster( 'Boop', 1 )\nout = base.firstGraphemeCluster( 'foo bar', 5 )\n","base.flipsign":"var z = base.flipsign( -3.0, 10.0 )\nz = base.flipsign( -3.0, -1.0 )\nz = base.flipsign( 1.0, -0.0 )\nz = base.flipsign( -3.0, -0.0 )\nz = base.flipsign( -0.0, 1.0 )\nz = base.flipsign( 0.0, -1.0 )\n","base.flipsignf":"var z = base.flipsignf( -3.0, 10.0 )\nz = base.flipsignf( -3.0, -1.0 )\nz = base.flipsignf( 1.0, -0.0 )\nz = base.flipsignf( -3.0, -0.0 )\nz = base.flipsignf( -0.0, 1.0 )\nz = base.flipsignf( 0.0, -1.0 )\n","base.float32ToInt32":"var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\ny = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( NaN ) )\ny = base.float32ToInt32( FLOAT32_PINF )\ny = base.float32ToInt32( FLOAT32_NINF )\n","base.float32ToUint32":"var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\ny = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( NaN ) )\ny = base.float32ToUint32( FLOAT32_PINF )\ny = base.float32ToUint32( FLOAT32_NINF )\n","base.float64ToFloat32":"var y = base.float64ToFloat32( 1.337 )\n","base.float64ToInt32":"var y = base.float64ToInt32( 4294967295.0 )\ny = base.float64ToInt32( 3.14 )\ny = base.float64ToInt32( -3.14 )\ny = base.float64ToInt32( NaN )\ny = base.float64ToInt32( PINF )\ny = base.float64ToInt32( NINF )\n","base.float64ToInt64Bytes":"var y = base.float64ToInt64Bytes( 4294967297.0 )\n","base.float64ToInt64Bytes.assign":"var out = new Uint8Array( 16 );\nvar y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n","base.float64ToUint32":"var y = base.float64ToUint32( 4294967297.0 )\ny = base.float64ToUint32( 3.14 )\ny = base.float64ToUint32( -3.14 )\ny = base.float64ToUint32( NaN )\ny = base.float64ToUint32( PINF )\ny = base.float64ToUint32( NINF )\n","base.floor":"var y = base.floor( 3.14 )\ny = base.floor( -4.2 )\ny = base.floor( -4.6 )\ny = base.floor( 9.5 )\ny = base.floor( -0.0 )\n","base.floor2":"var y = base.floor2( 3.14 )\ny = base.floor2( -4.2 )\ny = base.floor2( -4.6 )\ny = base.floor2( 9.5 )\ny = base.floor2( 13.0 )\ny = base.floor2( -13.0 )\ny = base.floor2( -0.0 )\n","base.floor10":"var y = base.floor10( 3.14 )\ny = base.floor10( -4.2 )\ny = base.floor10( -4.6 )\ny = base.floor10( 9.5 )\ny = base.floor10( 13.0 )\ny = base.floor10( -13.0 )\ny = base.floor10( -0.0 )\n","base.floorb":"var y = base.floorb( 3.14159, -4, 10 )\ny = base.floorb( 3.14159, 0, 2 )\ny = base.floorb( 5.0, 1, 2 )\n","base.floorf":"var y = base.floorf( 3.14 )\ny = base.floorf( -4.2 )\ny = base.floorf( -4.6 )\ny = base.floorf( 9.5 )\ny = base.floorf( -0.0 )\n","base.floorn":"var y = base.floorn( 3.14159, -4 )\ny = base.floorn( 3.14159, 0 )\ny = base.floorn( 12368.0, 3 )\n","base.floorsd":"var y = base.floorsd( 3.14159, 5, 10 )\ny = base.floorsd( 3.14159, 1, 10 )\ny = base.floorsd( 12368.0, 2, 10 )\ny = base.floorsd( 0.0313, 2, 2 )\n","base.forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachChar( 'hello world!', fcn );\nn\n","base.forEachCodePoint":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePoint( 'hello world!', fcn );\nn\n","base.forEachCodePointRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePointRight( 'hello world!', fcn );\nn\n","base.forEachGraphemeCluster":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachGraphemeCluster( 'hello world!', fcn );\nn\n","base.forEachRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachRight( 'hello world!', fcn );\nn\n","base.formatInterpolate":"var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\nout = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\nout = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n","base.formatTokenize":"var out = base.formatTokenize( 'Hello %s!' )\nout = base.formatTokenize( '%s %s %d' )\nout = base.formatTokenize( 'Pi: %.2f' )\n","base.fresnel":"var y = base.fresnel( 0.0 )\ny = base.fresnel( 1.0 )\ny = base.fresnel( PINF )\ny = base.fresnel( NINF )\ny = base.fresnel( NaN )\n","base.fresnel.assign":"var out = new Float64Array( 2 );\nvar v = base.fresnel.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.fresnelc":"var y = base.fresnelc( 0.0 )\ny = base.fresnelc( 1.0 )\ny = base.fresnelc( PINF )\ny = base.fresnelc( NINF )\ny = base.fresnelc( NaN )\n","base.fresnels":"var y = base.fresnels( 0.0 )\ny = base.fresnels( 1.0 )\ny = base.fresnels( PINF )\ny = base.fresnels( NINF )\ny = base.fresnels( NaN )\n","base.frexp":"var out = base.frexp( 4.0 )\nout = base.frexp( 0.0 )\nout = base.frexp( -0.0 )\nout = base.frexp( NaN )\nout = base.frexp( PINF )\nout = base.frexp( NINF )\n","base.frexp.assign":"var out = new Float64Array( 2 );\nvar y = base.frexp.assign( 4.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.fromBinaryString":"var bstr;\nbstr = '0100000000010000000000000000000000000000000000000000000000000000';\nvar val = base.fromBinaryString( bstr )\nbstr = '0100000000001001001000011111101101010100010001000010110100011000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111100001110011001111001110000101111010111100100010100000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000001100011010011';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000001';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111111000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\n","base.fromBinaryStringf":"var bstr = '01000000100000000000000000000000';\nvar val = base.fromBinaryStringf( bstr )\nbstr = '01000000010010010000111111011011';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111011011000011101000110011';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000010110';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000001';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111110000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\n","base.fromBinaryStringUint8":"var bstr = '01010101';\nvar val = base.fromBinaryStringUint8( bstr )\nbstr = '00000000';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '00000010';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '11111111';\nval = base.fromBinaryStringUint8( bstr )\n","base.fromBinaryStringUint16":"var bstr = '0101010101010101';\nvar val = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000000';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000010';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '1111111111111111';\nval = base.fromBinaryStringUint16( bstr )\n","base.fromBinaryStringUint32":"var bstr = '01010101010101010101010101010101';\nvar val = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000010';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '11111111111111111111111111111111';\nval = base.fromBinaryStringUint32( bstr )\n","base.fromInt64Bytes":"var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\nvar y = base.fromInt64Bytes( bytes, 1, 0 )\n","base.fromWordf":"var word = 1068180177; // => 0 01111111 01010110010001011010001\nvar f32 = base.fromWordf( word ) // when printed, promoted to float64\n","base.fromWords":"var v = base.fromWords( 1774486211, 2479577218 )\nv = base.fromWords( 3221823995, 1413754136 )\nv = base.fromWords( 0, 0 )\nv = base.fromWords( 2147483648, 0 )\nv = base.fromWords( 2146959360, 0 )\nv = base.fromWords( 2146435072, 0 )\nv = base.fromWords( 4293918720, 0 )\n","base.gamma":"var y = base.gamma( 4.0 )\ny = base.gamma( -1.5 )\ny = base.gamma( -0.5 )\ny = base.gamma( 0.5 )\ny = base.gamma( 0.0 )\ny = base.gamma( -0.0 )\ny = base.gamma( NaN )\n","base.gamma1pm1":"var y = base.gamma1pm1( 0.2 )\ny = base.gamma1pm1( -6.7 )\ny = base.gamma1pm1( 0.0 )\ny = base.gamma1pm1( NaN )\n","base.gammaDeltaRatio":"var y = base.gammaDeltaRatio( 2.0, 3.0 )\ny = base.gammaDeltaRatio( 4.0, 0.5 )\ny = base.gammaDeltaRatio( 100.0, 0.0 )\ny = base.gammaDeltaRatio( NaN, 3.0 )\ny = base.gammaDeltaRatio( 5.0, NaN )\ny = base.gammaDeltaRatio( NaN, NaN )\n","base.gammainc":"var y = base.gammainc( 6.0, 2.0 )\ny = base.gammainc( 1.0, 2.0, true, true )\ny = base.gammainc( 7.0, 5.0 )\ny = base.gammainc( 7.0, 5.0, false )\ny = base.gammainc( NaN, 2.0 )\ny = base.gammainc( 6.0, NaN )\n","base.gammaincinv":"var y = base.gammaincinv( 0.5, 2.0 )\ny = base.gammaincinv( 0.1, 10.0 )\ny = base.gammaincinv( 0.75, 3.0 )\ny = base.gammaincinv( 0.75, 3.0, true )\ny = base.gammaincinv( 0.75, NaN )\ny = base.gammaincinv( NaN, 3.0 )\n","base.gammaLanczosSum":"var y = base.gammaLanczosSum( 4.0 )\ny = base.gammaLanczosSum( -1.5 )\ny = base.gammaLanczosSum( -0.5 )\ny = base.gammaLanczosSum( 0.5 )\ny = base.gammaLanczosSum( 0.0 )\ny = base.gammaLanczosSum( NaN )\n","base.gammaLanczosSumExpGScaled":"var y = base.gammaLanczosSumExpGScaled( 4.0 )\ny = base.gammaLanczosSumExpGScaled( -1.5 )\ny = base.gammaLanczosSumExpGScaled( -0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.0 )\ny = base.gammaLanczosSumExpGScaled( NaN )\n","base.gammaln":"var y = base.gammaln( 1.0 )\ny = base.gammaln( 2.0 )\ny = base.gammaln( 4.0 )\ny = base.gammaln( -0.5 )\ny = base.gammaln( 0.5 )\ny = base.gammaln( 0.0 )\ny = base.gammaln( NaN )\n","base.gammasgn":"var y = base.gammasgn( 1.0 )\ny = base.gammasgn( -2.5 )\ny = base.gammasgn( 0.0 )\ny = base.gammasgn( NaN )\n","base.gcd":"var v = base.gcd( 48, 18 )\n","base.getHighWord":"var w = base.getHighWord( 3.14e201 )\n","base.getLowWord":"var w = base.getLowWord( 3.14e201 )\n","base.hacovercos":"var y = base.hacovercos( 3.14 )\ny = base.hacovercos( -4.2 )\ny = base.hacovercos( -4.6 )\ny = base.hacovercos( 9.5 )\ny = base.hacovercos( -0.0 )\n","base.hacoversin":"var y = base.hacoversin( 3.14 )\ny = base.hacoversin( -4.2 )\ny = base.hacoversin( -4.6 )\ny = base.hacoversin( 9.5 )\ny = base.hacoversin( -0.0 )\n","base.havercos":"var y = base.havercos( 3.14 )\ny = base.havercos( -4.2 )\ny = base.havercos( -4.6 )\ny = base.havercos( 9.5 )\ny = base.havercos( -0.0 )\n","base.haversin":"var y = base.haversin( 3.14 )\ny = base.haversin( -4.2 )\ny = base.haversin( -4.6 )\ny = base.haversin( 9.5 )\ny = base.haversin( -0.0 )\n","base.headercase":"var out = base.headercase( 'Hello World!' )\nout = base.headercase( 'beep boop' )\n","base.heaviside":"var y = base.heaviside( 3.14 )\ny = base.heaviside( -3.14 )\ny = base.heaviside( 0.0 )\ny = base.heaviside( 0.0, 'half-maximum' )\ny = base.heaviside( 0.0, 'left-continuous' )\ny = base.heaviside( 0.0, 'right-continuous' )\n","base.hermitepoly":"var y = base.hermitepoly( 1, 0.5 )\ny = base.hermitepoly( -1, 0.5 )\ny = base.hermitepoly( 0, 0.5 )\ny = base.hermitepoly( 2, 0.5 )\n","base.hermitepoly.factory":"var polyval = base.hermitepoly.factory( 2 );\nvar v = polyval( 0.5 )\n","base.hypot":"var h = base.hypot( -5.0, 12.0 )\nh = base.hypot( NaN, 12.0 )\nh = base.hypot( -0.0, -0.0 )\n","base.hypotf":"var h = base.hypotf( -5.0, 12.0 )\nh = base.hypotf( NaN, 12.0 )\nh = base.hypotf( -0.0, -0.0 )\n","base.identity":"var y = base.identity( -1.0 )\ny = base.identity( 2.0 )\ny = base.identity( 0.0 )\ny = base.identity( -0.0 )\ny = base.identity( NaN )\n","base.identityf":"var y = base.identityf( -1.0 )\ny = base.identityf( 2.0 )\ny = base.identityf( 0.0 )\ny = base.identityf( -0.0 )\ny = base.identityf( NaN )\n","base.imul":"var v = base.imul( -10|0, 4|0 )\n","base.imuldw":"var v = base.imuldw( 1, 10 )\n","base.imuldw.assign":"var out = [ 0, 0 ];\nvar v = base.imuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.int2slice":"var s = base.int2slice( -1, 5, false );\ns.start\ns.stop\ns.step\n","base.int32ToUint32":"var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\ny = base.int32ToUint32( base.float64ToInt32( 3 ) )\n","base.inv":"var y = base.inv( -1.0 )\ny = base.inv( 2.0 )\ny = base.inv( 0.0 )\ny = base.inv( -0.0 )\ny = base.inv( NaN )\n","base.invcase":"var out = base.invcase( 'Hello World!' )\nout = base.invcase( 'I am A tiny LITTLE teapot' )\n","base.invf":"var y = base.invf( -1.0 )\ny = base.invf( 2.0 )\ny = base.invf( 0.0 )\ny = base.invf( -0.0 )\ny = base.invf( NaN )\n","base.isComposite":"var bool = base.isComposite( 10.0 )\nbool = base.isComposite( 11.0 )\n","base.isCoprime":"var bool = base.isCoprime( 14.0, 15.0 )\nbool = base.isCoprime( 14.0, 21.0 )\n","base.isEven":"var bool = base.isEven( 5.0 )\nbool = base.isEven( -2.0 )\nbool = base.isEven( 0.0 )\nbool = base.isEven( NaN )\n","base.isEvenInt32":"var bool = base.isEvenInt32( 5 )\nbool = base.isEvenInt32( -2 )\nbool = base.isEvenInt32( 0 )\n","base.isFinite":"var bool = base.isFinite( 5.0 )\nbool = base.isFinite( -2.0e64 )\nbool = base.isFinite( PINF )\nbool = base.isFinite( NINF )\n","base.isFinitef":"var bool = base.isFinitef( 5.0 )\nbool = base.isFinitef( -1.0e38 )\nbool = base.isFinitef( FLOAT32_PINF )\nbool = base.isFinitef( FLOAT32_NINF )\n","base.isInfinite":"var bool = base.isInfinite( PINF )\nbool = base.isInfinite( NINF )\nbool = base.isInfinite( 5.0 )\nbool = base.isInfinite( NaN )\n","base.isInfinitef":"var bool = base.isInfinitef( FLOAT32_PINF )\nbool = base.isInfinitef( FLOAT32_NINF )\nbool = base.isInfinitef( 5.0 )\nbool = base.isInfinitef( NaN )\n","base.isInteger":"var bool = base.isInteger( 1.0 )\nbool = base.isInteger( 3.14 )\n","base.isnan":"var bool = base.isnan( NaN )\nbool = base.isnan( 7.0 )\n","base.isnanf":"var bool = base.isnanf( NaN )\nbool = base.isnanf( 7.0 )\n","base.isNegativeFinite":"var bool = base.isNegativeFinite( -3.14 )\nbool = base.isNegativeFinite( -Infinity )\nbool = base.isNegativeFinite( 2.0 )\nbool = base.isNegativeFinite( NaN )\nbool = base.isNegativeFinite( -0.0 )\n","base.isNegativeInteger":"var bool = base.isNegativeInteger( -1.0 )\nbool = base.isNegativeInteger( 0.0 )\nbool = base.isNegativeInteger( 10.0 )\n","base.isNegativeZero":"var bool = base.isNegativeZero( -0.0 )\nbool = base.isNegativeZero( 0.0 )\n","base.isNegativeZerof":"var bool = base.isNegativeZerof( -0.0 )\nbool = base.isNegativeZerof( 0.0 )\n","base.isNonNegativeFinite":"var out = base.isNonNegativeFinite( 5.0 )\nout = base.isNonNegativeFinite( 3.14 )\nout = base.isNonNegativeFinite( 0.0 )\nout = base.isNonNegativeFinite( Infinity )\nout = base.isNonNegativeFinite( -3.14 )\nout = base.isNonNegativeFinite( NaN )\n","base.isNonNegativeInteger":"var bool = base.isNonNegativeInteger( 1.0 )\nbool = base.isNonNegativeInteger( 0.0 )\nbool = base.isNonNegativeInteger( -10.0 )\n","base.isNonPositiveFinite":"var bool = base.isNonPositiveFinite( -3.14 )\nvar bool = base.isNonPositiveFinite( 0.0 )\nvar bool = base.isNonPositiveFinite( -Infinity )\nvar bool = base.isNonPositiveFinite( 3.14 )\nvar bool = base.isNonPositiveFinite( NaN )\n","base.isNonPositiveInteger":"var bool = base.isNonPositiveInteger( -1.0 )\nbool = base.isNonPositiveInteger( 0.0 )\nbool = base.isNonPositiveInteger( 10.0 )\n","base.isOdd":"var bool = base.isOdd( 5.0 )\nbool = base.isOdd( -2.0 )\nbool = base.isOdd( 0.0 )\nbool = base.isOdd( NaN )\n","base.isOddInt32":"var bool = base.isOddInt32( 5 )\nbool = base.isOddInt32( -2 )\nbool = base.isOddInt32( 0 )\n","base.isPositiveFinite":"var bool = base.isPositiveFinite( 5.0 )\nbool = base.isPositiveFinite( 3.14 )\nbool = base.isPositiveFinite( 0.0 )\nbool = base.isPositiveFinite( Infinity )\nbool = base.isPositiveFinite( -3.14 )\nbool = base.isPositiveFinite( NaN )\n","base.isPositiveInteger":"var bool = base.isPositiveInteger( 1.0 )\nbool = base.isPositiveInteger( 0.0 )\nbool = base.isPositiveInteger( -10.0 )\n","base.isPositiveZero":"var bool = base.isPositiveZero( 0.0 )\nbool = base.isPositiveZero( -0.0 )\n","base.isPositiveZerof":"var bool = base.isPositiveZerof( 0.0 )\nbool = base.isPositiveZerof( -0.0 )\n","base.isPow2Uint32":"var bool = base.isPow2Uint32( 2 )\nbool = base.isPow2Uint32( 5 )\n","base.isPrime":"var bool = base.isPrime( 11.0 )\nbool = base.isPrime( 3.14 )\n","base.isProbability":"var bool = base.isProbability( 0.5 )\nbool = base.isProbability( 3.14 )\nbool = base.isProbability( NaN )\n","base.isSafeInteger":"var bool = base.isSafeInteger( 1.0 )\nbool = base.isSafeInteger( 2.0e200 )\nbool = base.isSafeInteger( 3.14 )\n","base.kebabcase":"var out = base.kebabcase( 'Hello World!' )\nout = base.kebabcase( 'I am a tiny little teapot' )\n","base.kernelBetainc":"var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\nout = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n","base.kernelBetainc.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\nvar bool = ( v === out )\n","base.kernelBetaincinv":"var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\ny = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n","base.kernelCos":"var out = base.kernelCos( 0.0, 0.0 )\nout = base.kernelCos( PI/6.0, 0.0 )\nout = base.kernelCos( 0.785, -1.144e-17 )\nout = base.kernelCos( NaN )\n","base.kernelLog1p":"var y = base.kernelLog1p( 1.0 )\ny = base.kernelLog1p( 1.4142135623730951 )\ny = base.kernelLog1p( NaN )\n","base.kernelSin":"var y = base.kernelSin( 0.0, 0.0 )\ny = base.kernelSin( PI/6.0, 0.0 )\ny = base.kernelSin( 0.619, 9.279e-18 )\ny = base.kernelSin( NaN, 0.0 )\ny = base.kernelSin( 2.0, NaN )\ny = base.kernelSin( NaN, NaN )\n","base.kernelTan":"var out = base.kernelTan( PI/4.0, 0.0, 1 )\nout = base.kernelTan( PI/4.0, 0.0, -1 )\nout = base.kernelTan( PI/6.0, 0.0, 1 )\nout = base.kernelTan( 0.664, 5.288e-17, 1 )\nout = base.kernelTan( NaN, 0.0, 1 )\nout = base.kernelTan( 3.0, NaN, 1 )\nout = base.kernelTan( 3.0, 0.0, NaN )\n","base.kroneckerDelta":"var y = base.kroneckerDelta( 3.14, 0.0 )\ny = base.kroneckerDelta( 3.14, 3.14 )\n","base.kroneckerDeltaf":"var y = base.kroneckerDeltaf( 3.14, 0.0 )\ny = base.kroneckerDeltaf( 3.14, 3.14 )\n","base.labs":"var v = base.labs( -1|0 )\nv = base.labs( 2|0 )\nv = base.labs( 0|0 )\n","base.last":"var out = base.last( 'hello', 1 )\nout = base.last( 'JavaScript', 6 )\nout = base.last( 'foo bar', 10 )\n","base.lastCodePoint":"var out = base.lastCodePoint( 'hello world', 1 )\nout = base.lastCodePoint( 'JavaScript', 6 )\nout = base.lastCodePoint( 'अनुच्छेद', 1 )\n","base.lastGraphemeCluster":"var out = base.lastGraphemeCluster( 'beep', 1 )\nout = base.lastGraphemeCluster( 'Boop', 2 )\nout = base.lastGraphemeCluster( 'JavaScript', 6 )\n","base.lcm":"var v = base.lcm( 21, 6 )\n","base.ldexp":"var x = base.ldexp( 0.5, 3 )\nx = base.ldexp( 4.0, -2 )\nx = base.ldexp( 0.0, 20 )\nx = base.ldexp( -0.0, 39 )\nx = base.ldexp( NaN, -101 )\nx = base.ldexp( PINF, 11 )\nx = base.ldexp( NINF, -118 )\n","base.leftPad":"var out = base.leftPad( 'a', 5, ' ' )\nout = base.leftPad( 'beep', 10, 'b' )\nout = base.leftPad( 'boop', 12, 'beep' )\n","base.leftTrim":"var out = base.leftTrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n","base.ln":"var y = base.ln( 4.0 )\ny = base.ln( 0.0 )\ny = base.ln( PINF )\ny = base.ln( NaN )\ny = base.ln( -4.0 )\n","base.log":"var y = base.log( 100.0, 10.0 )\ny = base.log( 16.0, 2.0 )\ny = base.log( 5.0, 1.0 )\ny = base.log( NaN, 2.0 )\ny = base.log( 1.0, NaN )\ny = base.log( -4.0, 2.0 )\ny = base.log( 4.0, -2.0 )\n","base.log1mexp":"var y = base.log1mexp( -10.0 )\ny = base.log1mexp( 0.0 )\ny = base.log1mexp( 5.0 )\ny = base.log1mexp( 10.0 )\ny = base.log1mexp( NaN )\n","base.log1p":"var y = base.log1p( 4.0 )\ny = base.log1p( -1.0 )\ny = base.log1p( 0.0 )\ny = base.log1p( -0.0 )\ny = base.log1p( -2.0 )\ny = base.log1p( NaN )\n","base.log1pexp":"var y = base.log1pexp( -10.0 )\ny = base.log1pexp( 0.0 )\ny = base.log1pexp( 5.0 )\ny = base.log1pexp( 34.0 )\ny = base.log1pexp( NaN )\n","base.log1pmx":"base.log1pmx( 1.1 )\nbase.log1pmx( 0.99 )\nbase.log1pmx( -0.99 )\nbase.log1pmx( -1.1 )\nbase.log1pmx( NaN )\n","base.log2":"var y = base.log2( 4.0 )\ny = base.log2( 8.0 )\ny = base.log2( 0.0 )\ny = base.log2( PINF )\ny = base.log2( NaN )\ny = base.log2( -4.0 )\n","base.log10":"var y = base.log10( 100.0 )\ny = base.log10( 8.0 )\ny = base.log10( 0.0 )\ny = base.log10( PINF )\ny = base.log10( NaN )\ny = base.log10( -4.0 )\n","base.logaddexp":"var v = base.logaddexp( 90.0, 90.0 )\nv = base.logaddexp( -20.0, 90.0 )\nv = base.logaddexp( 0.0, -100.0 )\nv = base.logaddexp( NaN, NaN )\n","base.logit":"var y = base.logit( 0.2 )\ny = base.logit( 0.9 )\ny = base.logit( -4.0 )\ny = base.logit( 1.5 )\ny = base.logit( NaN )\n","base.lowercase":"var out = base.lowercase( 'bEEp' )\n","base.lucas":"var y = base.lucas( 0 )\ny = base.lucas( 1 )\ny = base.lucas( 2 )\ny = base.lucas( 3 )\ny = base.lucas( 4 )\ny = base.lucas( 77 )\ny = base.lucas( NaN )\n","base.lucaspoly":"var v = base.lucaspoly( 5, 2.0 )\n","base.lucaspoly.factory":"var polyval = base.lucaspoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.max":"var v = base.max( 3.14, 4.2 )\nv = base.max( 3.14, NaN )\nv = base.max( +0.0, -0.0 )\n","base.maxabs":"var v = base.maxabs( 3.14, -4.2 )\nv = base.maxabs( 3.14, NaN )\nv = base.maxabs( +0.0, -0.0 )\n","base.maxabsn":"var v = base.maxabsn( 3.14, -4.2 )\nv = base.maxabsn( 5.9, 3.14, 4.2 )\nv = base.maxabsn( 3.14, NaN )\nv = base.maxabsn( +0.0, -0.0 )\n","base.maxn":"var v = base.maxn( 3.14, 4.2 )\nv = base.maxn( 5.9, 3.14, 4.2 )\nv = base.maxn( 3.14, NaN )\nv = base.maxn( +0.0, -0.0 )\n","base.min":"var v = base.min( 3.14, 4.2 )\nv = base.min( 3.14, NaN )\nv = base.min( +0.0, -0.0 )\n","base.minabs":"var v = base.minabs( 3.14, -4.2 )\nv = base.minabs( 3.14, NaN )\nv = base.minabs( +0.0, -0.0 )\n","base.minabsn":"var v = base.minabsn( 3.14, -4.2 )\nv = base.minabsn( 5.9, 3.14, 4.2 )\nv = base.minabsn( 3.14, NaN )\nv = base.minabsn( +0.0, -0.0 )\n","base.minmax":"var v = base.minmax( 3.14, 4.2 )\nv = base.minmax( 3.14, NaN )\nv = base.minmax( +0.0, -0.0 )\n","base.minmax.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabs":"var v = base.minmaxabs( 3.14, 4.2 )\nv = base.minmaxabs( -5.9, 3.14)\nv = base.minmaxabs( 3.14, NaN )\nv = base.minmaxabs( +0.0, -0.0 )\n","base.minmaxabs.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabsn":"var v = base.minmaxabsn( 3.14, 4.2 )\nv = base.minmaxabsn( -5.9, 3.14, 4.2 )\nv = base.minmaxabsn( 3.14, NaN )\nv = base.minmaxabsn( +0.0, -0.0 )\nv = base.minmaxabsn( 3.14 )\n","base.minmaxabsn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxn":"var v = base.minmaxn( 3.14, 4.2 )\nv = base.minmaxn( 5.9, 3.14, 4.2 )\nv = base.minmaxn( 3.14, NaN )\nv = base.minmaxn( +0.0, -0.0 )\nv = base.minmaxn( 3.14 )\n","base.minmaxn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minn":"var v = base.minn( 3.14, 4.2 )\nv = base.minn( 5.9, 3.14, 4.2 )\nv = base.minn( 3.14, NaN )\nv = base.minn( +0.0, -0.0 )\n","base.modf":"var parts = base.modf( 3.14 )\nparts = base.modf( 3.14 )\nparts = base.modf( +0.0 )\nparts = base.modf( -0.0 )\nparts = base.modf( PINF )\nparts = base.modf( NINF )\nparts = base.modf( NaN )\n","base.modf.assign":"var out = new Float64Array( 2 );\nvar parts = base.modf.assign( 3.14, out, 1, 0 )\nvar bool = ( parts === out )\n","base.mul":"var v = base.mul( -1.0, 5.0 )\nv = base.mul( 2.0, 5.0 )\nv = base.mul( 0.0, 5.0 )\nv = base.mul( -0.0, 0.0 )\nv = base.mul( NaN, NaN )\n","base.mulf":"var v = base.mulf( -1.0, 5.0 )\nv = base.mulf( 2.0, 5.0 )\nv = base.mulf( 0.0, 5.0 )\nv = base.mulf( -0.0, 0.0 )\nv = base.mulf( NaN, NaN )\n","base.ndarray":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\narr.iset( 3, 99 );\narr.get( 1, 1 )\n","base.ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","base.ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","base.ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","base.ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","base.ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","base.ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","base.ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","base.ndarray.prototype.order: string":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","base.ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","base.ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","base.ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","base.ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","base.ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","base.ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","base.ndarray.prototype.toLocaleString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toLocaleString()\n","base.ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","base.ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","base.ndarrayUnary":"var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dtype = 'float64';\nvar shape = [ 2, 2 ];\nvar sx = [ 2, 1 ];\nvar sy = [ 2, 1 ];\nvar ox = 0;\nvar oy = 0;\nvar order = 'row-major';\nvar x = ndarray( dtype, xbuf, shape, sx, ox, order );\nvar y = ndarray( dtype, ybuf, shape, sy, oy, order );\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\nx = {\n 'dtype': dtype,\n 'data': xbuf,\n 'shape': shape,\n 'strides': sx,\n 'offset': ox,\n 'order': order\n };\ny = {\n 'dtype': dtype,\n 'data': ybuf,\n 'shape': shape,\n 'strides': sy,\n 'offset': oy,\n 'order': order\n };\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\n","base.ndzeros":"var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n","base.ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar y = base.ndzerosLike( x )\n","base.negafibonacci":"var y = base.negafibonacci( 0 )\ny = base.negafibonacci( -1 )\ny = base.negafibonacci( -2 )\ny = base.negafibonacci( -3 )\ny = base.negafibonacci( -4 )\ny = base.negafibonacci( -79 )\ny = base.negafibonacci( -80 )\ny = base.negafibonacci( NaN )\n","base.negalucas":"var y = base.negalucas( 0 )\ny = base.negalucas( -1 )\ny = base.negalucas( -2 )\ny = base.negalucas( -3 )\ny = base.negalucas( -4 )\ny = base.negalucas( -77 )\ny = base.negalucas( -78 )\ny = base.negalucas( NaN )\n","base.nonfibonacci":"var v = base.nonfibonacci( 1 )\nv = base.nonfibonacci( 2 )\nv = base.nonfibonacci( 3 )\nv = base.nonfibonacci( NaN )\n","base.normalize":"var out = base.normalize( 3.14e-319 )\nvar y = out[ 0 ];\nvar exponent = out[ 1 ];\nvar bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\nout = base.normalize( 0.0 )\nout = base.normalize( PINF )\nout = base.normalize( NINF )\nout = base.normalize( NaN )\n","base.normalize.assign":"var out = new Float64Array( 2 )\nvar v = base.normalize.assign( 3.14e-319, out, 1, 0 )\nvar bool = ( v === out )\n","base.normalizef":"var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\nvar y = out[ 0 ];\nvar exp = out[ 1 ];\nvar bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\nout = base.normalizef( FLOAT32_PINF )\nout = base.normalizef( FLOAT32_NINF )\nout = base.normalizef( NaN )\n","base.normalizef.assign":"out = new Float32Array( 2 );\nvar v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\nbool = ( v === out )\n","base.normalizeMultiSlice":"var s1 = new MultiSlice( 1, 3, null );\nvar s2 = base.normalizeMultiSlice( s1, [ 5, 5, 5 ], false );\nvar v = s2.data[ 0 ];\nv.start\nv.stop\nv.step\nv = s2.data[ 1 ];\nv.start\nv.stop\nv.step\nv = s2.data[ 2 ];\nv.start\nv.stop\nv.step\n","base.normalizeSlice":"var s1 = new Slice( 1, 10, 1 );\nvar s2 = base.normalizeSlice( s1, 5, false );\ns2.start\ns2.stop\ns2.step\ns1 = new Slice( -2, null, -1 );\ns2 = base.normalizeSlice( s1, 10, false );\ns2.start\ns2.stop\ns2.step\n","base.normhermitepoly":"var y = base.normhermitepoly( 1, 0.5 )\ny = base.normhermitepoly( -1, 0.5 )\ny = base.normhermitepoly( 0, 0.5 )\ny = base.normhermitepoly( 2, 0.5 )\n","base.normhermitepoly.factory":"var f = base.normhermitepoly.factory( 2 );\nvar v = f( 0.5 )\n","base.pascalcase":"var out = base.pascalcase( 'Hello World!' )\nout = base.pascalcase( 'beep boop' )\n","base.pdiff":"var v = base.pdiff( 5.9, 3.14 )\nv = base.pdiff( 3.14, 4.2 )\nv = base.pdiff( 3.14, NaN )\nv = base.pdiff( -0.0, +0.0 )\n","base.pdifff":"var v = base.pdifff( 5.9, 3.15 )\nv = base.pdifff( 3.14, 4.2 )\nv = base.pdifff( 3.14, NaN )\nv = base.pdifff( -0.0, +0.0 )\n","base.percentEncode":"var out = base.percentEncode( '☃' )\n","base.polygamma":"var v = base.polygamma( 3, 1.2 )\nv = base.polygamma( 5, 1.2 )\nv = base.polygamma( 3, -4.9 )\nv = base.polygamma( -1, 5.3 )\nv = base.polygamma( 2, -1.0 )\n","base.pow":"var y = base.pow( 2.0, 3.0 )\ny = base.pow( 4.0, 0.5 )\ny = base.pow( 100.0, 0.0 )\ny = base.pow( PI, 5.0 )\ny = base.pow( PI, -0.2 )\ny = base.pow( NaN, 3.0 )\ny = base.pow( 5.0, NaN )\ny = base.pow( NaN, NaN )\n","base.powm1":"var y = base.powm1( 2.0, 3.0 )\ny = base.powm1( 4.0, 0.5 )\ny = base.powm1( 0.0, 100.0 )\ny = base.powm1( 100.0, 0.0 )\ny = base.powm1( 0.0, 0.0 )\ny = base.powm1( PI, 5.0 )\ny = base.powm1( NaN, 3.0 )\ny = base.powm1( 5.0, NaN )\n","base.rad2deg":"var d = base.rad2deg( PI/2.0 )\nd = base.rad2deg( -PI/4.0 )\nd = base.rad2deg( NaN )\nd = base.rad2deg( PI/6.0 )\n","base.rad2degf":"var d = base.rad2degf( 3.141592653589793 / 2.0 )\nd = base.rad2degf( -3.141592653589793 / 4.0 )\nd = base.rad2degf( NaN )\nd = base.rad2degf( 3.141592653589793 / 6.0 )\n","base.ramp":"var y = base.ramp( 3.14 )\ny = base.ramp( -3.14 )\n","base.rampf":"var y = base.rampf( 3.14 )\ny = base.rampf( -3.14 )\n","base.random.arcsine":"var r = base.random.arcsine( 2.0, 5.0 )\n","base.random.arcsine.factory":"var rand = base.random.arcsine.factory();\nvar r = rand( 0.0, 1.0 )\nr = rand( -2.0, 2.0 )\nrand = base.random.arcsine.factory( 0.0, 1.0 );\nr = rand()\nr = rand()\n","base.random.arcsine.NAME":"var str = base.random.arcsine.NAME\n","base.random.arcsine.PRNG":"var prng = base.random.arcsine.PRNG;\n","base.random.arcsine.seed":"var seed = base.random.arcsine.seed;\n","base.random.arcsine.seedLength":"var len = base.random.arcsine.seedLength;\n","base.random.arcsine.state":"var r = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nvar state = base.random.arcsine.state\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nbase.random.arcsine.state = state;\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\n","base.random.arcsine.stateLength":"var len = base.random.arcsine.stateLength;\n","base.random.arcsine.byteLength":"var sz = base.random.arcsine.byteLength;\n","base.random.arcsine.toJSON":"var o = base.random.arcsine.toJSON()\n","base.random.bernoulli":"var r = base.random.bernoulli( 0.8 );\n","base.random.bernoulli.factory":"var rand = base.random.bernoulli.factory();\nvar r = rand( 0.3 );\nr = rand( 0.59 );\nrand = base.random.bernoulli.factory( 0.3 );\nr = rand();\nr = rand();\n","base.random.bernoulli.NAME":"var str = base.random.bernoulli.NAME\n","base.random.bernoulli.PRNG":"var prng = base.random.bernoulli.PRNG;\n","base.random.bernoulli.seed":"var seed = base.random.bernoulli.seed;\n","base.random.bernoulli.seedLength":"var len = base.random.bernoulli.seedLength;\n","base.random.bernoulli.state":"var r = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nvar state = base.random.bernoulli.state\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nbase.random.bernoulli.state = state;\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\n","base.random.bernoulli.stateLength":"var len = base.random.bernoulli.stateLength;\n","base.random.bernoulli.byteLength":"var sz = base.random.bernoulli.byteLength;\n","base.random.bernoulli.toJSON":"var o = base.random.bernoulli.toJSON()\n","base.random.beta":"var r = base.random.beta( 2.0, 5.0 );\n","base.random.beta.factory":"var rand = base.random.beta.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.beta.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.beta.NAME":"var str = base.random.beta.NAME\n","base.random.beta.PRNG":"var prng = base.random.beta.PRNG;\n","base.random.beta.seed":"var seed = base.random.beta.seed;\n","base.random.beta.seedLength":"var len = base.random.beta.seedLength;\n","base.random.beta.state":"var r = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nvar state = base.random.beta.state\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nbase.random.beta.state = state;\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\n","base.random.beta.stateLength":"var len = base.random.beta.stateLength;\n","base.random.beta.byteLength":"var sz = base.random.beta.byteLength;\n","base.random.beta.toJSON":"var o = base.random.beta.toJSON()\n","base.random.betaprime":"var r = base.random.betaprime( 2.0, 5.0 );\n","base.random.betaprime.factory":"var rand = base.random.betaprime.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.betaprime.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.betaprime.NAME":"var str = base.random.betaprime.NAME\n","base.random.betaprime.PRNG":"var prng = base.random.betaprime.PRNG;\n","base.random.betaprime.seed":"var seed = base.random.betaprime.seed;\n","base.random.betaprime.seedLength":"var len = base.random.betaprime.seedLength;\n","base.random.betaprime.state":"var r = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nvar state = base.random.betaprime.state\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nbase.random.betaprime.state = state;\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\n","base.random.betaprime.stateLength":"var len = base.random.betaprime.stateLength;\n","base.random.betaprime.byteLength":"var sz = base.random.betaprime.byteLength;\n","base.random.betaprime.toJSON":"var o = base.random.betaprime.toJSON()\n","base.random.binomial":"var r = base.random.binomial( 20, 0.8 );\n","base.random.binomial.factory":"var rand = base.random.binomial.factory();\nvar r = rand( 20, 0.3 );\nr = rand( 10, 0.77 );\nrand = base.random.binomial.factory( 10, 0.8 );\nr = rand();\nr = rand();\n","base.random.binomial.NAME":"var str = base.random.binomial.NAME\n","base.random.binomial.PRNG":"var prng = base.random.binomial.PRNG;\n","base.random.binomial.seed":"var seed = base.random.binomial.seed;\n","base.random.binomial.seedLength":"var len = base.random.binomial.seedLength;\n","base.random.binomial.state":"var r = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nvar state = base.random.binomial.state\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nbase.random.binomial.state = state;\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\n","base.random.binomial.stateLength":"var len = base.random.binomial.stateLength;\n","base.random.binomial.byteLength":"var sz = base.random.binomial.byteLength;\n","base.random.binomial.toJSON":"var o = base.random.binomial.toJSON()\n","base.random.boxMuller":"var r = base.random.boxMuller();\n","base.random.boxMuller.factory":"var rand = base.random.boxMuller.factory();\nr = rand();\nr = rand();\n","base.random.boxMuller.NAME":"var str = base.random.boxMuller.NAME\n","base.random.boxMuller.PRNG":"var prng = base.random.boxMuller.PRNG;\n","base.random.boxMuller.seed":"var seed = base.random.boxMuller.seed;\n","base.random.boxMuller.seedLength":"var len = base.random.boxMuller.seedLength;\n","base.random.boxMuller.state":"var r = base.random.boxMuller()\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nvar state = base.random.boxMuller.state\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nbase.random.boxMuller.state = state;\nr = base.random.boxMuller()\nr = base.random.boxMuller()\n","base.random.boxMuller.stateLength":"var len = base.random.boxMuller.stateLength;\n","base.random.boxMuller.byteLength":"var sz = base.random.boxMuller.byteLength;\n","base.random.boxMuller.toJSON":"var o = base.random.boxMuller.toJSON()\n","base.random.cauchy":"var r = base.random.cauchy( 2.0, 5.0 );\n","base.random.cauchy.factory":"var rand = base.random.cauchy.factory();\nvar r = rand( 0.0, 1.5 );\nr = rand( -2.0, 2.0 );\nrand = base.random.cauchy.factory( 0.0, 1.5 );\nr = rand();\nr = rand();\n","base.random.cauchy.NAME":"var str = base.random.cauchy.NAME\n","base.random.cauchy.PRNG":"var prng = base.random.cauchy.PRNG;\n","base.random.cauchy.seed":"var seed = base.random.cauchy.seed;\n","base.random.cauchy.seedLength":"var len = base.random.cauchy.seedLength;\n","base.random.cauchy.state":"var r = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nvar state = base.random.cauchy.state\nr = 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);\n","base.random.kumaraswamy.factory":"var rand = base.random.kumaraswamy.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.kumaraswamy.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.kumaraswamy.NAME":"var str = base.random.kumaraswamy.NAME\n","base.random.kumaraswamy.PRNG":"var prng = base.random.kumaraswamy.PRNG;\n","base.random.kumaraswamy.seed":"var seed = base.random.kumaraswamy.seed;\n","base.random.kumaraswamy.seedLength":"var len = base.random.kumaraswamy.seedLength;\n","base.random.kumaraswamy.state":"var r = base.random.kumaraswamy( 1.5, 1.5 )\nr = base.random.kumaraswamy( 1.5, 1.5 )\nr = base.random.kumaraswamy( 1.5, 1.5 )\nvar state = base.random.kumaraswamy.state\nr = base.random.kumaraswamy( 1.5, 1.5 )\nr = base.random.kumaraswamy( 1.5, 1.5 )\nbase.random.kumaraswamy.state = state;\nr = base.random.kumaraswamy( 1.5, 1.5 )\nr = base.random.kumaraswamy( 1.5, 1.5 )\n","base.random.kumaraswamy.stateLength":"var len = 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base.random.randi.MAX;\n","base.random.randi.seed":"var seed = base.random.randi.seed;\n","base.random.randi.seedLength":"var len = base.random.randi.seedLength;\n","base.random.randi.state":"var r = base.random.randi()\nr = base.random.randi()\nr = base.random.randi()\nvar state = base.random.randi.state;\nr = base.random.randi()\nr = base.random.randi()\nbase.random.randi.state = state;\nr = base.random.randi()\nr = base.random.randi()\n","base.random.randi.stateLength":"var len = base.random.randi.stateLength;\n","base.random.randi.byteLength":"var sz = base.random.randi.byteLength;\n","base.random.randi.toJSON":"var o = base.random.randi.toJSON()\n","base.random.randn":"var r = base.random.randn();\n","base.random.randn.factory":"var rand = base.random.randn.factory();\nvar r = rand();\nr = rand();\nvar rand = base.random.randn.factory({ 'name': 'box-muller' });\nr = rand();\nr = rand();\n","base.random.randn.NAME":"var str = base.random.randn.NAME\n","base.random.randn.PRNG":"var 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5.0 );\nr = rand( 10.0 );\nrand = base.random.rayleigh.factory( 5.0 );\nr = rand();\nr = rand();\n","base.random.rayleigh.NAME":"var str = base.random.rayleigh.NAME\n","base.random.rayleigh.PRNG":"var prng = base.random.rayleigh.PRNG;\n","base.random.rayleigh.seed":"var seed = base.random.rayleigh.seed;\n","base.random.rayleigh.seedLength":"var len = base.random.rayleigh.seedLength;\n","base.random.rayleigh.state":"var r = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nvar state = base.random.rayleigh.state\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nbase.random.rayleigh.state = state;\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\n","base.random.rayleigh.stateLength":"var len = base.random.rayleigh.stateLength;\n","base.random.rayleigh.byteLength":"var sz = base.random.rayleigh.byteLength;\n","base.random.rayleigh.toJSON":"var o = base.random.rayleigh.toJSON()\n","base.random.t":"var r = base.random.t( 2.0 );\n","base.random.t.factory":"var rand = base.random.t.factory();\nvar r = rand( 5.0 );\nr = rand( 3.14 );\nrand = base.random.t.factory( 5.0 );\nr = rand();\nr = rand();\n","base.random.t.NAME":"var str = base.random.t.NAME\n","base.random.t.PRNG":"var prng = base.random.t.PRNG;\n","base.random.t.seed":"var seed = base.random.t.seed;\n","base.random.t.seedLength":"var len = base.random.t.seedLength;\n","base.random.t.state":"var r = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nvar state = base.random.t.state\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nbase.random.t.state = state;\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\n","base.random.t.stateLength":"var len = base.random.t.stateLength;\n","base.random.t.byteLength":"var sz = base.random.t.byteLength;\n","base.random.t.toJSON":"var o = base.random.t.toJSON()\n","base.random.triangular":"var r = base.random.triangular( 2.0, 5.0, 3.33 );\n","base.random.triangular.factory":"var rand = base.random.triangular.factory();\nvar r = rand( 0.0, 1.0, 0.5 );\nr = rand( -2.0, 2.0, 1.0 );\nrand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\nr = rand();\nr = rand();\n","base.random.triangular.NAME":"var str = base.random.triangular.NAME\n","base.random.triangular.PRNG":"var prng = base.random.triangular.PRNG;\n","base.random.triangular.seed":"var seed = base.random.triangular.seed;\n","base.random.triangular.seedLength":"var len = base.random.triangular.seedLength;\n","base.random.triangular.state":"var r = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nvar state = base.random.triangular.state\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nbase.random.triangular.state = state;\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\n","base.random.triangular.stateLength":"var len = base.random.triangular.stateLength;\n","base.random.triangular.byteLength":"var sz = base.random.triangular.byteLength;\n","base.random.triangular.toJSON":"var o = base.random.triangular.toJSON()\n","base.random.uniform":"var r = base.random.uniform( 2.0, 5.0 );\n","base.random.uniform.factory":"var rand = base.random.uniform.factory();\nvar r = rand( 0.0, 1.0 );\nr = rand( -2.0, 2.0 );\nrand = base.random.uniform.factory( 0.0, 1.0 );\nr = rand();\nr = rand();\n","base.random.uniform.NAME":"var str = base.random.uniform.NAME\n","base.random.uniform.PRNG":"var prng = base.random.uniform.PRNG;\n","base.random.uniform.seed":"var seed = base.random.uniform.seed;\n","base.random.uniform.seedLength":"var len = base.random.uniform.seedLength;\n","base.random.uniform.state":"var r = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nvar state = base.random.uniform.state\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nbase.random.uniform.state = state;\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\n","base.random.uniform.stateLength":"var len = base.random.uniform.stateLength;\n","base.random.uniform.byteLength":"var sz = base.random.uniform.byteLength;\n","base.random.uniform.toJSON":"var o = base.random.uniform.toJSON()\n","base.random.weibull":"var r = base.random.weibull( 2.0, 5.0 );\n","base.random.weibull.factory":"var rand = base.random.weibull.factory();\nvar r = rand( 0.1, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.weibull.factory( 0.1, 1.5 );\nr = rand();\nr = rand();\n","base.random.weibull.NAME":"var str = base.random.weibull.NAME\n","base.random.weibull.PRNG":"var prng = base.random.weibull.PRNG;\n","base.random.weibull.seed":"var seed = base.random.weibull.seed;\n","base.random.weibull.seedLength":"var len = base.random.weibull.seedLength;\n","base.random.weibull.state":"var r = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nvar state = base.random.weibull.state\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nbase.random.weibull.state = state;\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\n","base.random.weibull.stateLength":"var len = base.random.weibull.stateLength;\n","base.random.weibull.byteLength":"var sz = base.random.weibull.byteLength;\n","base.random.weibull.toJSON":"var o = base.random.weibull.toJSON()\n","base.rcbrt":"var y = base.rcbrt( 8.0 )\ny = base.rcbrt( 1000.0 )\ny = base.rcbrt( 0.0 )\ny = base.rcbrt( PINF )\ny = base.rcbrt( -8.0 )\ny = base.rcbrt( NaN )\n","base.rcbrtf":"var y = base.rcbrtf( 8.0 )\ny = base.rcbrtf( 1000.0 )\ny = base.rcbrtf( 0.0 )\ny = base.rcbrtf( PINF )\ny = base.rcbrtf( -8.0 )\ny = base.rcbrtf( NaN )\n","base.reldiff":"var d = base.reldiff( 2.0, 5.0 )\nd = base.reldiff( -1.0, 3.14 )\nd = base.reldiff( -2.0, 5.0, 'max-abs' )\nd = base.reldiff( -2.0, 5.0, 'max' )\nd = base.reldiff( -2.0, 5.0, 'min-abs' )\nd = base.reldiff( -2.0, 5.0, 'min' )\nd = base.reldiff( -2.0, 5.0, 'mean-abs' )\nd = base.reldiff( -2.0, 5.0, 'mean' )\nd = base.reldiff( -2.0, 5.0, 'x' )\nd = base.reldiff( 5.0, -2.0, 'x' )\nd = base.reldiff( -2.0, 5.0, 'y' )\nd = base.reldiff( 5.0, -2.0, 'y' )\nfunction scale( x, y ) {\n var s;\n\n x = base.abs( x );\n y = base.abs( y );\n\n // Maximum absolute value:\n s = (x < y ) ? y : x;\n\n // Scale in units of epsilon:\n return s * EPS;\n };\nd = base.reldiff( 12.15, 12.149999999999999, scale )\n","base.removeFirst":"var out = base.removeFirst( 'beep', 1 )\nout = base.removeFirst( 'Boop', 1 )\nout = base.removeFirst( 'foo bar', 5 )\n","base.removeFirstCodePoint":"var out = base.removeFirstCodePoint( 'beep', 1 )\nout = base.removeFirstCodePoint( 'Boop', 1 )\nout = base.removeFirstCodePoint( 'foo bar', 5 )\n","base.removeFirstGraphemeCluster":"var out = base.removeFirstGraphemeCluster( 'beep', 1 )\nout = base.removeFirstGraphemeCluster( 'Boop', 1 )\nout = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n","base.removeLast":"var out = base.removeLast( 'beep', 1 )\nout = base.removeLast( 'Boop', 1 )\nout = base.removeLast( 'foo bar', 5 )\n","base.removeLastCodePoint":"var out = base.removeLastCodePoint( 'beep', 1 )\nout = base.removeLastCodePoint( 'Boop', 1 )\nout = base.removeLastCodePoint( 'foo bar', 5 )\n","base.removeLastGraphemeCluster":"var out = base.removeLastGraphemeCluster( 'beep', 1 )\nout = base.removeLastGraphemeCluster( 'Boop', 1 )\nout = base.removeLastGraphemeCluster( 'foo bar', 5 )\n","base.rempio2":"var y = [ 0.0, 0.0 ];\nvar n = base.rempio2( 128.0, y )\nvar y1 = y[ 0 ]\nvar y2 = y[ 1 ]\n","base.repeat":"var out = base.repeat( 'a', 5 )\nout = base.repeat( '', 100 )\nout = base.repeat( 'beep', 0 )\n","base.replace":"function replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nvar out = base.replace( str, /([^\\s]+)/gi, replacer )\nout = base.replace( 'beep', /e/, 'o' )\n","base.replaceAfter":"var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\nout = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\nout = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n","base.replaceAfterLast":"var str = 'beep boop';\nvar out = base.replaceAfterLast( str, ' ', 'foo', str.length )\nout = base.replaceAfterLast( str, 'o', 'foo', str.length )\nout = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n","base.replaceBefore":"var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n","base.replaceBeforeLast":"var str = 'beep boop';\nvar out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\nout = base.replaceBeforeLast( str, 'o', 'foo', str.length )\nout = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n","base.reverse":"var out = base.reverse( 'beep' )\nout = base.reverse( 'Boop' )\nout = base.reverse( 'foo bar' )\n","base.reverseCodePoints":"var out = base.reverseCodePoints( 'beep' )\nout = base.reverseCodePoints( 'Boop' )\nout = base.reverseCodePoints( 'foo bar' )\n","base.reverseGraphemeClusters":"var out = base.reverseGraphemeClusters( 'beep' )\nout = base.reverseGraphemeClusters( 'Boop' )\nout = base.reverseGraphemeClusters( 'foo bar' )\n","base.rightPad":"var out = base.rightPad( 'a', 5, ' ' )\nout = base.rightPad( 'beep', 10, 'b' )\nout = base.rightPad( 'boop', 12, 'beep' )\n","base.rightTrim":"var out = base.rightTrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","base.risingFactorial":"var v = base.risingFactorial( 0.9, 5 )\nv = base.risingFactorial( -9.0, 3 )\nv = base.risingFactorial( 0.0, 2 )\nv = base.risingFactorial( 3.0, -2 )\n","base.rotl32":"var x = 2147483649;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotl32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.rotr32":"var x = 1;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotr32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.round":"var y = base.round( 3.14 )\ny = base.round( -4.2 )\ny = base.round( -4.6 )\ny = base.round( 9.5 )\ny = base.round( -0.0 )\n","base.round2":"var y = base.round2( 3.14 )\ny = base.round2( -4.2 )\ny = base.round2( -4.6 )\ny = base.round2( 9.5 )\ny = base.round2( 13.0 )\ny = base.round2( -13.0 )\ny = base.round2( -0.0 )\n","base.round10":"var y = base.round10( 3.14 )\ny = base.round10( -4.2 )\ny = base.round10( -4.6 )\ny = base.round10( 9.5 )\ny = base.round10( 13.0 )\ny = base.round10( -13.0 )\ny = base.round10( -0.0 )\n","base.roundb":"var y = base.roundb( 3.14159, -2, 10 )\ny = base.roundb( 3.14159, 0, 2 )\ny = base.roundb( 5.0, 1, 2 )\n","base.roundn":"var y = base.roundn( 3.14159, -2 )\ny = base.roundn( 3.14159, 0 )\ny = base.roundn( 12368.0, 3 )\n","base.roundsd":"var y = base.roundsd( 3.14159, 3 )\ny = base.roundsd( 3.14159, 1 )\ny = base.roundsd( 12368.0, 2 )\ny = base.roundsd( 0.0313, 2, 2 )\n","base.rsqrt":"var y = base.rsqrt( 4.0 )\ny = base.rsqrt( 100.0 )\ny = base.rsqrt( 0.0 )\ny = base.rsqrt( Infinity )\ny = base.rsqrt( -4.0 )\ny = base.rsqrt( NaN )\n","base.rsqrtf":"var y = base.rsqrtf( 4.0 )\ny = base.rsqrtf( 0.0 )\ny = base.rsqrtf( Infinity )\ny = base.rsqrtf( -4.0 )\ny = base.rsqrtf( NaN )\n","base.sargs2multislice":"var s = new base.sargs2multislice( 'null,null,null' );\ns.data\ns = new base.sargs2multislice( '10,Slice(0,10,1),null' );\ns.data\n","base.scalar2ndarray":"var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\nvar sh = ndarrayShape( x )\nvar v = x.get()\n","base.secd":"var y = base.secd( 1.0 )\ny = base.secd( PI )\ny = base.secd( -PI )\ny = base.secd( NaN )\n","base.seq2multislice":"var s = new base.seq2multislice( '1:10', [ 10 ], false );\ns.data\ns = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\ns.data\n","base.seq2slice":"var s = new base.seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new base.seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","base.setHighWord":"var high = 1072693248 >>> 0;\nvar y = base.setHighWord( PINF, high )\n","base.setLowWord":"var low = 5 >>> 0;\nvar x = 3.14e201;\nvar y = base.setLowWord( x, low )\nvar low = 12345678;\nvar y = base.setLowWord( PINF, low )\ny = base.setLowWord( NINF, low )\ny = base.setLowWord( NaN, low )\n","base.sici":"var y = base.sici( 3.0 )\ny = base.sici( 0.0 )\ny = base.sici( -9.0 )\ny = base.sici( NaN )\n","base.sici.assign":"var out = new Float64Array( 2 );\nvar y = base.sici.assign( 3.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.signbit":"var bool = base.signbit( 4.0 )\nbool = base.signbit( -9.14e-34 )\nbool = base.signbit( 0.0 )\nbool = base.signbit( -0.0 )\n","base.signbitf":"var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\nbool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\nbool = base.signbitf( 0.0 )\nbool = base.signbitf( -0.0 )\n","base.significandf":"var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\ns = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\ns = base.significandf( base.float64ToFloat32( -3.14 ) )\ns = base.significandf( 0.0 )\ns = base.significandf( NaN )\n","base.signum":"var sign = base.signum( -5.0 )\nsign = base.signum( 5.0 )\nsign = base.signum( -0.0 )\nsign = base.signum( 0.0 )\nsign = base.signum( NaN )\n","base.signumf":"var sign = base.signumf( -5.0 )\nsign = base.signumf( 5.0 )\nsign = base.signumf( -0.0 )\nsign = base.signumf( 0.0 )\nsign = base.signumf( NaN )\n","base.sin":"var y = base.sin( 0.0 )\ny = base.sin( PI/2.0 )\ny = base.sin( -PI/6.0 )\ny = base.sin( NaN )\n","base.sinc":"var y = base.sinc( 0.5 )\ny = base.sinc( -1.2 )\ny = base.sinc( 0.0 )\ny = base.sinc( NaN )\n","base.sincos":"var y = base.sincos( 0.0 )\ny = base.sincos( PI/2.0 )\ny = base.sincos( -PI/6.0 )\ny = base.sincos( NaN )\n","base.sincos.assign":"var out = new Float64Array( 2 );\nvar v = base.sincos.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sincospi":"var y = base.sincospi( 0.0 )\ny = base.sincospi( 0.5 )\ny = base.sincospi( 0.1 )\ny = base.sincospi( NaN )\n","base.sincospi.assign":"var out = new Float64Array( 2 );\nvar v = base.sincospi.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sinh":"var y = base.sinh( 0.0 )\ny = base.sinh( 2.0 )\ny = base.sinh( -2.0 )\ny = base.sinh( NaN )\n","base.sinpi":"var y = base.sinpi( 0.0 )\ny = base.sinpi( 0.5 )\ny = base.sinpi( 0.9 )\ny = base.sinpi( NaN )\n","base.slice2seq":"var out = base.slice2seq( new Slice( 1, 10, 1 ) )\nout = base.slice2seq( new Slice( null, 10 ) )\n","base.sliceLength":"var s = new Slice( 1, 10, 1 );\nbase.sliceLength( s )\n","base.sliceNonReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceNonReducedDimensions( s )\n","base.sliceReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceReducedDimensions( s )\n","base.sliceShape":"var s = new Slice( 1, 10, 1 );\nvar ms = new MultiSlice( s, s );\nbase.sliceShape( ms )\n","base.snakecase":"var out = base.snakecase( 'Hello World!' )\nout = base.snakecase( 'I am a tiny little teapot' )\n","base.spence":"var y = base.spence( 3.0 )\ny = base.spence( 0.0 )\ny = base.spence( -9.0 )\ny = base.spence( NaN )\n","base.sqrt":"var y = base.sqrt( 4.0 )\ny = base.sqrt( 9.0 )\ny = base.sqrt( 0.0 )\ny = base.sqrt( -4.0 )\ny = base.sqrt( NaN )\n","base.sqrt1pm1":"var y = base.sqrt1pm1( 3.0 )\ny = base.sqrt1pm1( 0.5 )\ny = base.sqrt1pm1( 0.02 )\ny = base.sqrt1pm1( -0.5 )\ny = base.sqrt1pm1( -1.1 )\ny = base.sqrt1pm1( NaN )\n","base.sqrtf":"var y = base.sqrtf( 4.0 )\ny = base.sqrtf( 9.0 )\ny = base.sqrtf( 0.0 )\ny = base.sqrtf( -4.0 )\ny = base.sqrtf( NaN )\n","base.sqrtpi":"var y = base.sqrtpi( 4.0 )\ny = base.sqrtpi( 10.0 )\ny = base.sqrtpi( 0.0 )\ny = base.sqrtpi( -4.0 )\ny = base.sqrtpi( NaN )\n","base.startcase":"var out = base.startcase( 'beep boop' )\n","base.startsWith":"var bool = base.startsWith( 'Beep', 'Be', 0 )\nbool = base.startsWith( 'Beep', 'ep', 0 )\nbool = base.startsWith( 'Beep', 'ee', 1 )\nbool = base.startsWith( 'Beep', 'ee', -3 )\nbool = base.startsWith( 'Beep', '', 0 )\n","base.stickycase":"var out = base.stickycase( 'Hello World!' )\nout = base.stickycase( 'I am a tiny little teapot' )\n","base.strided.binary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary( [ x, y, z ], shape, strides, f );\nz\n","base.strided.binary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\nz\n","base.strided.binaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n","base.strided.binarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\nvar t = {\n 'default': base.add,\n 'complex64': base.caddf,\n 'complex128': base.cadd\n };\nvar out = base.strided.binarySignatureCallbacks( t, sigs )\n","base.strided.ccopy":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy( x.length, x, 1, y, 1 )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy( 2, x, -2, y, 1 )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.ccopy( 2, x1, -2, y1, 1 )\ny0\n","base.strided.ccopy.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\nvar v = y.get( 0 )\ny = new Complex64Array( x.length );\nbase.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\nv = y.get( 0 )\nvar x0 = new Complex64Array( xbuf );\nvar y0 = new Complex64Array( x0.length );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\nv = y1.get( 0 )\n","base.strided.cmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\nvar v = y.get( 0 )\nx = new Complex64Array( xbuf );\ny = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\nv = y.get( y.length-1 )\n","base.strided.cswap":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap( x.length, x, 1, y, 1 );\nx\ny\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap( 2, x, -2, y, 1 );\nx\ny\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cswap( 2, x1, -2, y1, 1 );\nx0\ny0\n","base.strided.cswap.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\nx\ny\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nx\ny\n","base.strided.cumax":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumax( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.cumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.cumax.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumaxabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.cumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.cumaxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumin":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumin( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.cumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.cumin.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cuminabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.cuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.cuminabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs2":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs2.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dapx":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.dapx.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsum( 3, 5.0, x1, 2 )\n","base.strided.dapxsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn( 3, 5.0, x1, 2)\n","base.strided.dapxsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.dapxsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumors( 3, 5.0, x1, 2 )\n","base.strided.dapxsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dapxsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dasum":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum( x.length, x, 1 )\ns = base.strided.dasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.dasum( 3, x1, 2 )\n","base.strided.dasum.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.dasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.dasumpw( 3, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.dasumpw( 3, x1, stride )\n","base.strided.dasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.daxpy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.daxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.daxpy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.dceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcopy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dcopy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcuminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcuminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ddeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.ddeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddot":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.ddot( 3, x1, -2, y1, 1 )\n","base.strided.ddot.ndarray":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dfill":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.dfill.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dfloor":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.dfloor.ndarray":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.dinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( x.length, x, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( 2, x, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap( 2, x1, -2, y1, 1, base.identity )\ny0\n","base.strided.dmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n","base.strided.dmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\nz0\n","base.strided.dmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n","base.strided.dmax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmax( 3, x1, 2 )\n","base.strided.dmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmax.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabs( 3, x1, 2 )\n","base.strided.dmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabssorted":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabssorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabssorted( 3, x1, 2 )\n","base.strided.dmaxabssorted.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxsorted( 3, x1, 2 )\n","base.strided.dmaxsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmean":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmean( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmean( 3, x1, 2 )\n","base.strided.dmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmean.ndarray( 3, x, 2, 1 )\n","base.strided.dmeankbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeankbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeankbn( 3, x1, 2 )\n","base.strided.dmeankbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n","base.strided.dmeankbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeankbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeankbn2( 3, x1, 2 )\n","base.strided.dmeankbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanli":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanli( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanli( 3, x1, 2 )\n","base.strided.dmeanli.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanli.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanlipw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanlipw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanlipw( 3, x1, 2 )\n","base.strided.dmeanlipw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanlipw.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanors( 3, x1, 2 )\n","base.strided.dmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanpn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanpn( 3, x1, 2 )\n","base.strided.dmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanpn.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanpw( 3, x1, 2 )\n","base.strided.dmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( 3, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( 3, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( 3, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( 3, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvar":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar( 3, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar( 3, 1, x1, 2, out, 1 )\n","base.strided.dmeanvar.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvarpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( 3, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( 3, 1, x1, 2, out, 1 )\n","base.strided.dmeanvarpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanwd( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanwd( 3, x1, 2 )\n","base.strided.dmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.dmediansorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmediansorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmediansorted( 3, x1, 2 )\n","base.strided.dmediansorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmidrange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmidrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmidrange( 3, x1, 2 )\n","base.strided.dmidrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmidrange.ndarray( 3, x, 2, 1 )\n","base.strided.dmin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmin( N, x1, stride )\n","base.strided.dmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmin.ndarray( 3, x, 2, 1 )\n","base.strided.dminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminabs( 3, x1, 2 )\n","base.strided.dminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dminsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminsorted( 3, x1, 2 )\n","base.strided.dminsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmskabs":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskabs2":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskdeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskdeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskfloor":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskfloor.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.dmskmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.dmskmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\nz0\n","base.strided.dmskmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n","base.strided.dmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmax( 3, x1, 2, mask1, 2 )\n","base.strided.dmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmin( 3, x1, 2, mask1, 2 )\n","base.strided.dmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.dmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskrsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskrsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsksqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsksqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsktrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsktrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dnanasum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanasum( 4, x1, 2 )\n","base.strided.dnanasum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum.ndarray( 4, x, 2, 1 )\n","base.strided.dnanasumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanasumors( 4, x1, 2 )\n","base.strided.dnanasumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasumors.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmax":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmax( 3, x1, 2 )\n","base.strided.dnanmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmax.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmaxabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmaxabs( 3, x1, 2 )\n","base.strided.dnanmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmean":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmean( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmean( 4, x1,2 )\n","base.strided.dnanmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmean.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanors( 4, x1, 2 )\n","base.strided.dnanmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanors.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanpn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanpn( 4, x1, 2 )\n","base.strided.dnanmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanpn.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmeanpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanpw( 4, x1, 2 )\n","base.strided.dnanmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanwd( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanwd( 4, x1, 2 )\n","base.strided.dnanmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanwd.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmin":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmin( 3, x1, 2 )\n","base.strided.dnanmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmin.ndarray( 3, x, 2, 1 )\n","base.strided.dnanminabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanminabs( 3, x1, 2 )\n","base.strided.dnanminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmskmax( 3, x1, 2, mask1, 2 )\n","base.strided.dnanmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmskmin( 3, x1, 2, mask1, 2 )\n","base.strided.dnanmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.dnanmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dnannsum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x1, 2, out, 1 )\n","base.strided.dnannsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x1, 2, out, 1 )\n","base.strided.dnannsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x1, 2, out, 1 )\n","base.strided.dnannsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnanrange":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanrange( 3, x1, 2 )\n","base.strided.dnanrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanrange.ndarray( 3, x, 2, 1 )\n","base.strided.dnanstdev":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnanstdev( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdev( 3, 1, x1, 2 )\n","base.strided.dnanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnanstdev.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dnanstdevch":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevch( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevch( 4, 1, x1, 2 )\n","base.strided.dnanstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevch.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevpn( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevpn( 4, 1, x1, 2 )\n","base.strided.dnanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevpn.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanstdevtk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevtk( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevtk( 4, 1, x1, 2 )\n","base.strided.dnanstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevtk.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanstdevwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevwd( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevwd( 4, 1, x1, 2 )\n","base.strided.dnanstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevwd.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanstdevyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevyc( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevyc( 4, 1, x1, 2 )\n","base.strided.dnanstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevyc.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnansum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansum( 4, x1, 2 )\n","base.strided.dnansum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn( 4, x1, 2 )\n","base.strided.dnansumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn2( 4, x1, 2 )\n","base.strided.dnansumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumors( 4, x1, 2 )\n","base.strided.dnansumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumpw( 4, x1, 2 )\n","base.strided.dnansumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dnanvariance":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariance( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariance( 4, 1, x1, 2 )\n","base.strided.dnanvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariance.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvariancech":"var x = new Float64Array( [ 1.0, NaN, -2.0, 2.0 ] );\nbase.strided.dnanvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancech( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariancech( 4, 1, x1, 2 )\n","base.strided.dnanvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancech.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvariancepn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancepn( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariancepn( 4, 1, x1, 2 )\n","base.strided.dnanvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancepn.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvariancetk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancetk( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariancetk( 4, 1, x1, 2 )\n","base.strided.dnanvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancetk.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvariancewd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancewd( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariancewd( 4, 1, x1, 2 )\n","base.strided.dnanvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancewd.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnanvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvarianceyc( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvarianceyc( 4, 1, x1, 2 )\n","base.strided.dnanvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvarianceyc.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnrm2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnrm2( 3, x1, 2 )\n","base.strided.dnrm2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.dramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.dramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.drange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.drange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.drange( 3, x1, 2 )\n","base.strided.drange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.drange.ndarray( 3, x, 2, 1 )\n","base.strided.drev":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.drev( 3, x1, 2 )\nx0\n","base.strided.drev.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.drev.ndarray( 3, x, 2, 1 )\n","base.strided.drsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.drsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.drsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsum( 3, 5.0, x1, 2 )\n","base.strided.dsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dscal":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.dscal.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\ndot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n","base.strided.dsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dsem":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsem( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsem( 3, 1, x1, 2 )\n","base.strided.dsem.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsem.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemch( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemch( 3, 1, x1, 2 )\n","base.strided.dsemch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsempn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsempn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsempn( 3, 1, x1, 2 )\n","base.strided.dsempn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsempn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemtk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemtk( 3, 1, x1, 2 )\n","base.strided.dsemtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemwd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemwd( 3, 1, x1, 2 )\n","base.strided.dsemwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemyc( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemyc( 3, 1, x1, 2 )\n","base.strided.dsemyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmean( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmean( 3, x1, 2 )\n","base.strided.dsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmean.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanors( 3, x1, 2 )\n","base.strided.dsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanpn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanpn( 3, x1, 2 )\n","base.strided.dsmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanpw( 3, x1, 2 )\n","base.strided.dsmeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanwd( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanwd( 3, x1, 2 )\n","base.strided.dsmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.dsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmean( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnanmean( 4, x1, 2 )\n","base.strided.dsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmean.ndarray( 4, x, 2, 1 )\n","base.strided.dsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnanmeanors( 4, x1, 2 )\n","base.strided.dsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanors.ndarray( 4, x, 2, 1 )\n","base.strided.dsnanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanpn( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnanmeanpn( 4, x1, 2 )\n","base.strided.dsnanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanpn.ndarray( 4, x, 2, 1 )\n","base.strided.dsnanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanwd( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnanmeanwd( 4, x1, 2 )\n","base.strided.dsnanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanwd.ndarray( 4, x, 2, 1 )\n","base.strided.dsnannsumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors( x.length, x, 1, out, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( N, x1, 2, out, 1 )\n","base.strided.dsnannsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansum( 4, x1, 2 )\n","base.strided.dsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsnansum.ndarray( 3, x, 2, 1 )\n","base.strided.dsnansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumors( 4, x1, 2 )\n","base.strided.dsnansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumpw( 4, x1, 2 )\n","base.strided.dsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dsort2hp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2hp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2ins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2ins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2sh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2sh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsorthp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsorthp( 2, 1, x1, 2 )\nx0\n","base.strided.dsorthp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.dsortins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsortins( 2, 1, x1, 2 )\nx0\n","base.strided.dsortins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.dsortsh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortsh( N, 1, x1, 2 )\nx0\n","base.strided.dsortsh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssum( 3, x1, 2 )\n","base.strided.dssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssum.ndarray(3, x, 2, 1 )\n","base.strided.dssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumors( 3, x1, 2 )\n","base.strided.dssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumors.ndarray( 3, x, 2, 1 )\n","base.strided.dssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumpw( 3, x1, 2 )\n","base.strided.dssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdev( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdev( 3, 1, x1, 2 )\n","base.strided.dstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdev.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevch( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevch( 3, 1, x1, 2 )\n","base.strided.dstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevpn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevpn( 3, 1, x1, 2 )\n","base.strided.dstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevpn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevtk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevtk( 3, 1, x1, 2 )\n","base.strided.dstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevwd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevwd( 3, 1, x1, 2 )\n","base.strided.dstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc( x.length, 1.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevyc( 3, 1.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevyc( 3, 1.0, x1, 2 )\n","base.strided.dstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n","base.strided.dsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsum( 3, x1, 2 )\n","base.strided.dsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsum.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn( 3, x1, 2 )\n","base.strided.dsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn2( 3, x1, 2 )\n","base.strided.dsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.dsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumors( 3, x1, 2 )\n","base.strided.dsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumors.ndarray( 3, x, 2, 1 )\n","base.strided.dsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumpw( 3, x1, 2 )\n","base.strided.dsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dsvariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsvariance( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsvariance( 3, 1, x1, 2 )\n","base.strided.dsvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsvariance.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsvariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsvariancepn( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsvariancepn( 3, 1, x1, 2 )\n","base.strided.dsvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsvariancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dswap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dswap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dtrunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.dtrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtypeEnum2Str":"var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveEnum":"var out = base.strided.dtypeResolveEnum( 'float64' )\nout = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveStr":"var out = base.strided.dtypeResolveStr( 'float64' )\nout = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeStr2Enum":"var out = base.strided.dtypeStr2Enum( 'float64' )\n","base.strided.dvariance":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariance( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariance( 3, 1, x1, 2 )\n","base.strided.dvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariance.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancech":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancech( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancech( 3, 1, x1, 2 )\n","base.strided.dvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancepn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancepn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancepn( 3, 1, x1, 2 )\n","base.strided.dvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancetk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancetk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancetk( 3, 1, x1, 2 )\n","base.strided.dvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancewd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancewd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancewd( 3, 1, x1, 2 )\n","base.strided.dvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarianceyc( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarianceyc( 3, 1, x1, 2 )\n","base.strided.dvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvarm":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm( x.length, 1, 1.0/3.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarm( 3, 1, 1.0/3.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarm( 3, 1, 1.0/3.0, x1, 2 )\n","base.strided.dvarm.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nbase.strided.dvarm.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n","base.strided.dvarmpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn( x.length, 1, 1.0/3.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarmpn( 3, 1, 1.0/3.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarmpn( 3, 1, 1.0/3.0, x1, 2 )\n","base.strided.dvarmpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nbase.strided.dvarmpn.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n","base.strided.dvarmtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk( x.length, 1, 1.0/3.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarmtk( 3, 1, 1.0/3.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarmtk( 3, 1, 1.0/3.0, x1, 2 )\n","base.strided.dvarmtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nbase.strided.dvarmtk.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n","base.strided.gapx":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gapx( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gapx( 4, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.gapx.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsum( 3, 5.0, x1, 2 )\n","base.strided.gapxsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.gapxsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.gapxsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumors( 3, 5.0, x1, 2 )\n","base.strided.gapxsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.gapxsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gasum":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum( x.length, x, 1 )\ns = base.strided.gasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.gasum( 3, x1, 2 )\n","base.strided.gasum.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\ns = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.gasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.gasumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gasumpw( 3, x1, 2 )\n","base.strided.gasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.gasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.gaxpy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.gaxpy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcopy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gcopy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusum":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumors":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumpw":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gdot":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.gdot( 3, x1, -2, y1, 1 )\n","base.strided.gdot.ndarray":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nout = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.gfill":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.gfill.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gfillBy":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( x.length, x, 1, fill )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( 3, x, 2, fill )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gfillBy( 3, x1, 2, fill )\nx0\n","base.strided.gfillBy.ndarray":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n","base.strided.gnannsumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( x.length, x, 1, out, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( 4, x1, 2, out, 1 )\n","base.strided.gnannsumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.gnansum":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansum( 4, x1, 2 )\n","base.strided.gnansum.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansum.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumkbn( 4, x1, 2 )\n","base.strided.gnansumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumkbn2":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn2( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumkbn2( 4, x1, 2 )\n","base.strided.gnansumkbn2.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumors( 4, x1, 2 )\n","base.strided.gnansumors.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumpw":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumpw( 4, x1, 2 )\n","base.strided.gnansumpw.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.gnrm2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnrm2( 3, x1, 2 )\n","base.strided.gnrm2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.grev":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( x.length, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.grev( 3, x1, 2 )\nx0\n","base.strided.grev.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.grev.ndarray( 3, x, 2, 1 )\n","base.strided.gscal":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gscal( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.gscal.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gsort2hp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsort2hp( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2hp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2ins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2ins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2sh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsort2sh( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2sh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsorthp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsorthp( 2, 1, x1, 2 )\nx0\n","base.strided.gsorthp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.gsortins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsortins( 2, 1, x1, 2 )\nx0\n","base.strided.gsortins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.gsortsh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsortsh( 2, 1, x1, 2 )\nx0\n","base.strided.gsortsh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( 2, 1, x, 2, 1 )\n","base.strided.gsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsum( 3, x1, 2 )\n","base.strided.gsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsum.ndarray( 3, x, 2, 1 )\n","base.strided.gsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumkbn( 3, x1, 2 )\n","base.strided.gsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.gsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumkbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumkbn2( 3, x1, 2 )\n","base.strided.gsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.gsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumors( 3, x1, 2 )\n","base.strided.gsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumors.ndarray( 3, x, 2, 1 )\n","base.strided.gsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumpw( 3, x1, 2 )\n","base.strided.gsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumpw.ndarray( 3, x, 2, 1 )\n","base.strided.gswap":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gswap.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.mapBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\ny0\n","base.strided.mapBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n","base.strided.mapBy2":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\nz0\n","base.strided.mapBy2.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 1.0, 1.0, 2.0, 2.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n","base.strided.max":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.max( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.max( 3, x1, 2 )\n","base.strided.max.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.max.ndarray( 3, x, 2, 1 )\n","base.strided.maxabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.maxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.maxabs( 3, x1, 2 )\n","base.strided.maxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.maxabs.ndarray( 3, x, 2, 1 )\n","base.strided.maxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy( 3, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.maxBy( 3, x1, 2, accessor )\n","base.strided.maxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.maxBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.maxsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.maxsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.maxsorted( 3, x1, 2 )\n","base.strided.maxsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nbase.strided.maxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.maxViewBufferIndex":"var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n","base.strided.mean":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.mean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.mean( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.mean( 3, x1, 2 )\n","base.strided.mean.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.mean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.mean.ndarray( 3, x, 2, 1 )\n","base.strided.meankbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meankbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meankbn( 3, x1, 2 )\n","base.strided.meankbn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meankbn.ndarray( 3, x, 2, 1 )\n","base.strided.meankbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meankbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meankbn2( 3, x1, 2 )\n","base.strided.meankbn2.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meankbn2.ndarray( 3, x, 2, 1 )\n","base.strided.meanors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanors( 3, x1, 2 )\n","base.strided.meanors.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanors.ndarray( 3, x, 2, 1 )\n","base.strided.meanpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanpn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanpn( 3, x1, 2 )\n","base.strided.meanpn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meanpn.ndarray( 3, x, 2, 1 )\n","base.strided.meanpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanpw( 3, x1, 2 )\n","base.strided.meanpw.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meanpw.ndarray( 3, x, 2, 1 )\n","base.strided.meanwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanwd( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanwd( 3, x1, 2 )\n","base.strided.meanwd.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meanwd.ndarray( 3, x, 2, 1 )\n","base.strided.mediansorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.mediansorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.mediansorted( 3, x1, 2 )\n","base.strided.mediansorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nbase.strided.mediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.metaDataProps":"var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\nvar dt = [ 'float64', 'float64' ];\nvar obj = {};\nbase.strided.metaDataProps( meta, dt, obj, false );\nobj.nargs\nobj.nin\nobj.nout\nobj.types\n","base.strided.min":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.min( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.min( 3, x1, 2 )\n","base.strided.min.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.min.ndarray( 3, x, 2, 1 )\n","base.strided.minabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.minabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.minabs( 3, x1, 2 )\n","base.strided.minabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.minabs.ndarray( 3, x, 2, 1 )\n","base.strided.minBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\nbase.strided.minBy( 3, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.minBy( 3, x1, 2, accessor )\n","base.strided.minBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.minBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.minsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.minsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.minsorted( 3, x1, 2 )\n","base.strided.minsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nbase.strided.minsorted.ndarray( 3, x, 2, 1 )\n","base.strided.minViewBufferIndex":"var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n","base.strided.mskmax":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.mskmax( 3, x1, 2, mask1, 2 )\n","base.strided.mskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.mskmin":"var x = [ 1.0, -2.0, -4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.mskmin( 3, x1, 2, mask1, 2 )\n","base.strided.mskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.mskrange":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.mskrange( 3, x1, 2, mask1, 2 )\n","base.strided.mskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.mskunary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nbase.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\ny\n","base.strided.mskunary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nbase.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.mskunaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.mskunaryDtypeSignatures( dt, dt )\n","base.strided.mskunarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.mskunarySignatureCallbacks( t, sigs )\n","base.strided.nanmax":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmax( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmax( 4, x1, 2 )\n","base.strided.nanmax.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmax.ndarray( 4, x, 2, 1 )\n","base.strided.nanmaxabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmaxabs( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmaxabs( 4, x1, 2 )\n","base.strided.nanmaxabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmaxabs.ndarray( 4, x, 2, 1 )\n","base.strided.nanmaxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.nanmaxBy( 3, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmaxBy( 3, x1, 2, accessor )\n","base.strided.nanmaxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.nanmaxBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.nanmean":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanmean( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmean( 4, x1, 2 )\n","base.strided.nanmean.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmean.ndarray( 4, x, 2, 1 )\n","base.strided.nanmeanors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmeanors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmeanors( 4, x1, 2 )\n","base.strided.nanmeanors.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmeanors.ndarray( 4, x, 2, 1 )\n","base.strided.nanmeanpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanmeanpn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmeanpn( 4, x1, 2 )\n","base.strided.nanmeanpn.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmeanpn.ndarray( 4, x, 2, 1 )\n","base.strided.nanmeanwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanmeanwd( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmeanwd( 4, x1, 2 )\n","base.strided.nanmeanwd.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmeanwd.ndarray( 4, x, 2, 1 )\n","base.strided.nanmin":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmin( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, 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];\nbase.strided.nanminBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\nbase.strided.nanminBy( 4, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanminBy( 3, x1, 2, accessor )\n","base.strided.nanminBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.nanminBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.nanmskmax":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskmax( 4, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmskmax( 4, x1, 2, mask1, 2 )\n","base.strided.nanmskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0, NaN, NaN ];\nmask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmax.ndarray( 4, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskmin":"var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskmin( 4, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmskmin( 4, x1, 2, mask1, 2 )\n","base.strided.nanmskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0, NaN, NaN ];\nmask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin.ndarray( 4, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskrange":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskrange( 5, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.nanmskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskrange.ndarray( 5, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.nanrange":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanrange( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanrange( 4, x1, 2 )\n","base.strided.nanrange.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanrange.ndarray( 4, x, 2, 1 )\n","base.strided.nanrangeBy":"function accessor( v ) { 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x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdev( 4, 1, x1, 2 )\n","base.strided.nanstdev.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdev.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevch":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevch( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevch( 4, 1, x1, 2 )\n","base.strided.nanstdevch.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevch.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevpn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevpn( 4, 1, x1, 2 )\n","base.strided.nanstdevpn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevpn.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevtk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevtk( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevtk( 4, 1, x1, 2 )\n","base.strided.nanstdevtk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevtk.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevwd( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevwd( 4, 1, x1, 2 )\n","base.strided.nanstdevwd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevwd.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevyc( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevyc( 4, 1, x1, 2 )\n","base.strided.nanstdevyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevyc.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvariance":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanvariance( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariance( 4, 1, x1, 2 )\n","base.strided.nanvariance.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanvariance.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvariancech":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanvariancech( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariancech( 4, 1, x1, 2 )\n","base.strided.nanvariancech.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanvariancech.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvariancepn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.nanvariancepn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariancepn( 3, 1, x1, 2 )\n","base.strided.nanvariancepn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.nanvariancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.nanvariancetk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanvariancetk( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariancetk( 4, 1, x1, 2 )\n","base.strided.nanvariancetk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanvariancetk.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvariancewd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanvariancewd( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariancewd( 4, 1, x1, 2 )\n","base.strided.nanvariancewd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanvariancewd.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvarianceyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc( 4, 1.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.nanvarianceyc( 3, 1.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvarianceyc( 3, 1.0, x1, 2 )\n","base.strided.nanvarianceyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc.ndarray( 4, 1.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.nanvarianceyc.ndarray( 3, 1.0, x, 2, 1 )\n","base.strided.nullary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary( [ x ], shape, strides, fcn );\nx\n","base.strided.nullary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1 ];\nvar offsets = [ 0 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\nx\n","base.strided.offsetView":"var x = new Float64Array( 10 );\nvar out = base.strided.offsetView( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.quaternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\nu\n","base.strided.quaternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\nu\n","base.strided.quinary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\nv\n","base.strided.quinary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\nv\n","base.strided.range":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.range( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.range( 3, x1, 2 )\n","base.strided.range.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.range.ndarray( 3, x, 2, 1 )\n","base.strided.rangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy( 3, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.rangeBy( 3, x1, 2, accessor )\n","base.strided.rangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.rangeBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.reinterpretComplex":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex( x, 0 )\nvar bool = ( out.buffer === x.buffer )\nx = new Complex64Array( 10 );\nout = base.strided.reinterpretComplex( x, 0 )\nbool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex64":"var x = new Complex64Array( 10 );\nvar out = base.strided.reinterpretComplex64( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex128":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex128( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.sabs":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sabs2":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs2.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sapx":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.sapx.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsum( 3, 5.0, x1, 2 )\n","base.strided.sapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumors( 3, 5.0, x1, 2 )\n","base.strided.sapxsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.sapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sasum":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum( x.length, x, 1 )\ns = base.strided.sasum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.sasum( 3, x1, 2 )\n","base.strided.sasum.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.sasumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sasumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sasumpw( 3, x1, 2 )\n","base.strided.sasumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.saxpy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.saxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.saxpy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.scbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.scbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.sceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scopy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.scopy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumin( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scuminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scuminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sdeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.sdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdot( 3, x1, -2, y1, 1 )\n","base.strided.sdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsum( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n","base.strided.sdsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsmean( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsmean( 3, x1, 2 )\n","base.strided.sdsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsmean.ndarray( 3, x, 2, 1 )\n","base.strided.sdsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsmeanors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsmeanors( 3, x1, 2 )\n","base.strided.sdsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.sdsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmean( N, x1, stride )\n","base.strided.sdsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.sdsnanmeanors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnanmeanors( 3, x1, 2 )\n","base.strided.sdsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.sdsnanmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.sdsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnansum( 4, x1, 2 )\n","base.strided.sdsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n","base.strided.sdsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnansumpw( 4, x1, 2 )\n","base.strided.sdsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.sdssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdssum( 3, x1, 2 )\n","base.strided.sdssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssum.ndarray( 3, x, 2, 1 )\n","base.strided.sdssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdssumpw( 3, x1, 2 )\n","base.strided.sdssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sfill":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.sfill.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sfloor":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.sfloor.ndarray":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.sinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.smap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( x.length, x, 1, y, 1, base.identityf )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( 2, x, 2, y, -1, base.identityf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap( 2, x1, -2, y1, 1, base.identityf )\ny0\n","base.strided.smap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n","base.strided.smap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\nz0\n","base.strided.smap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n","base.strided.smax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smax( 3, x1, 2 )\n","base.strided.smax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smax.ndarray( N, x, 2, 1 )\n","base.strided.smaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabs( 3, x1, 2 )\n","base.strided.smaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.smaxabssorted":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabssorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabssorted( 3, x1, 2 )\n","base.strided.smaxabssorted.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n","base.strided.smaxsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxsorted( 3, x1, 2 )\n","base.strided.smaxsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.smean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smean( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smean( 3, x1, 2 )\n","base.strided.smean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smean.ndarray( 3, x, 2, 1 )\n","base.strided.smeankbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeankbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeankbn( 3, x1, 2 )\n","base.strided.smeankbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeankbn.ndarray( 3, x, 2, 1 )\n","base.strided.smeankbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeankbn2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeankbn2( 3, x1, 2 )\n","base.strided.smeankbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeankbn2.ndarray( 3, x, 2, 1 )\n","base.strided.smeanli":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanli( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanli( 3, x1, 2 )\n","base.strided.smeanli.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanli.ndarray( 3, x, 2, 1 )\n","base.strided.smeanlipw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanlipw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanlipw( 3, x1, 2 )\n","base.strided.smeanlipw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanlipw.ndarray( 3, x, 2, 1 )\n","base.strided.smeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanors( 3, x1, 2 )\n","base.strided.smeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanors.ndarray( 3, x, 2, 1 )\n","base.strided.smeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanpn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanpn( 3, x1, 2 )\n","base.strided.smeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanpn.ndarray( 3, x, 2, 1 )\n","base.strided.smeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanpw( 3, x1, 2 )\n","base.strided.smeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanpw.ndarray( 3, x, 2, 1 )\n","base.strided.smeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanwd( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanwd( 3, x1, 2 )\n","base.strided.smeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.smediansorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smediansorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smediansorted( 3, x1, 2 )\n","base.strided.smediansorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.smidrange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smidrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smidrange( 3, x1, 2 )\n","base.strided.smidrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smidrange.ndarray( 3, x, 2, 1 )\n","base.strided.smin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smin( 3, x1, 2 )\n","base.strided.smin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smin.ndarray( 3, x, 2, 1 )\n","base.strided.sminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminabs( 3, x1, 2 )\n","base.strided.sminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sminabs.ndarray( 3, x, 2, 1 )\n","base.strided.sminsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminsorted( 3, x1, 2 )\n","base.strided.sminsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( 3, x, 2, 1 )\n","base.strided.smskabs":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskabs2":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs2.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskcbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskcbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskfloor":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskfloor.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskmap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.smskmap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.smskmap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\nz0\n","base.strided.smskmap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n","base.strided.smskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmax( 3, x1, 2, mask1, 2 )\n","base.strided.smskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmin( 3, x1, 2, mask1, 2 )\n","base.strided.smskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskrange( 3, x1, 2, mask1, 2 )\n","base.strided.smskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskrsqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskrsqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsksqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsksqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsktrunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsktrunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.snanmax":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmax( 3, x1, 2 )\n","base.strided.snanmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmax.ndarray( 3, x, 2, 1 )\n","base.strided.snanmaxabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmaxabs( 3, x1, 2 )\n","base.strided.snanmaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmean( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmean( 4, x1, 2 )\n","base.strided.snanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snanmean.ndarray( 4, x, 2, 1 )\n","base.strided.snanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmeanors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmeanors( 4, x1, 2 )\n","base.strided.snanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanors.ndarray( 4, x, 2, 1 )\n","base.strided.snanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanpn( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmeanpn( 4, x1, 2 )\n","base.strided.snanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanpn.ndarray( 4, x, 2, 1 )\n","base.strided.snanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanwd( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmeanwd( 4, x1, 2 )\n","base.strided.snanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanwd.ndarray( 4, x, 2, 1 )\n","base.strided.snanmin":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmin( 3, x1, 2 )\n","base.strided.snanmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmin.ndarray( 3, x, 2, 1 )\n","base.strided.snanminabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanminabs( 3, x1, 2 )\n","base.strided.snanminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmskmax( 3, x1, 2, mask1, 2 )\n","base.strided.snanmskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmskmin( 3, x1, 2, mask1, 2 )\n","base.strided.snanmskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.snanmskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.snanrange":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanrange( 3, x1, 2 )\n","base.strided.snanrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanrange.ndarray( 3, x, 2, 1 )\n","base.strided.snanstdev":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdev( N, 1, x1, stride )\n","base.strided.snanstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevch":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevch( N, 1, x1, stride )\n","base.strided.snanstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevpn( N, 1, x1, stride )\n","base.strided.snanstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevtk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevtk( N, 1, x1, stride )\n","base.strided.snanstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevwd( N, 1, x1, stride )\n","base.strided.snanstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevyc( N, 1, x1, stride )\n","base.strided.snanstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansum( 4, x1, 2 )\n","base.strided.snansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansum.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumkbn( 4, x1, 2 )\n","base.strided.snansumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn2":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn2( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumkbn2( 4, x1, 2 )\n","base.strided.snansumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.snansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumors( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumors( 4, x1, stride )\n","base.strided.snansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumors.ndarray( 4, x, 2, 1 )\n","base.strided.snansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumpw( 4, x1, 2 )\n","base.strided.snansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.snanvariance":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariance( N, 1, x1, 2 )\n","base.strided.snanvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancech":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancech( N, 1, x1, 2 )\n","base.strided.snanvariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancepn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancepn( N, 1, x1, 2 )\n","base.strided.snanvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancetk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancetk( N, 1, x1, 2 )\n","base.strided.snanvariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancewd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancewd( N, 1, x1, 2 )\n","base.strided.snanvariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvarianceyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x1, 2 )\n","base.strided.snanvarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snrm2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.snrm2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snrm2( 3, x1, 2 )\n","base.strided.snrm2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.snrm2.ndarray( 3, x, 2, 1 )\n","base.strided.sramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.sramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.srange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.srange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srange( 3, x1, 2 )\n","base.strided.srange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.srange.ndarray( 3, x, 2, 1 )\n","base.strided.srev":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srev( 3, x1, 2 )\nx0\n","base.strided.srev.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.srev.ndarray( 3, x, 2, 1 )\n","base.strided.srsqrt":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.srsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.srsqrt.ndarray":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sscal":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.sscal.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.ssort2hp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2hp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2ins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2ins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2sh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2sh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssorthp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssorthp( 2, 1, x1, 2 )\nx0\n","base.strided.ssorthp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortins( 2, 1, x1, 2 )\nx0\n","base.strided.ssortins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortsh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortsh( 2, 1, x1, 2 )\nx0\n","base.strided.ssortsh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.ssqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sstdev":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdev( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdev( 3, 1, x1, 2 )\n","base.strided.sstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdev.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevch":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevch( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevch( 3, 1, x1, 2 )\n","base.strided.sstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevpn( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevpn( 3, 1, x1, 2 )\n","base.strided.sstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevpn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevtk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevtk( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevtk( 3, 1, x1, 2 )\n","base.strided.sstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevwd( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevwd( 3, 1, x1, 2 )\n","base.strided.sstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevyc( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevyc( 3, 1, x1, 2 )\n","base.strided.sstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.ssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssum( 3, x1, 2 )\n","base.strided.ssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssum.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn( 3, x1, 2 )\n","base.strided.ssumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn2( 3, x1, 2 )\n","base.strided.ssumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.ssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumors( 3, x1, 2 )\n","base.strided.ssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumors.ndarray( 3, x, 2, 1 )\n","base.strided.ssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumpw( 3, x1, 2 )\n","base.strided.ssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sswap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.sswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.sswap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.stdev":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdev( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdev( 3, 1, x1, 2 )\n","base.strided.stdev.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdev.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevch":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevch( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevch( 3, 1, x1, 2 )\n","base.strided.stdevch.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevpn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevpn( 3, 1, x1, 2 )\n","base.strided.stdevpn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevpn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevtk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevtk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevtk( 3, 1, x1, 2 )\n","base.strided.stdevtk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevwd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevwd( 3, 1, x1, 2 )\n","base.strided.stdevwd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevyc( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevyc( 3, 1, x1, 2 )\n","base.strided.stdevyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.strunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.strunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.strunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.svariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariance( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariance( 3, 1, x1, 2 )\n","base.strided.svariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariance.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancech":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancech( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancech( 3, 1, x1, 2 )\n","base.strided.svariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancepn( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancepn( 3, 1, x1, 2 )\n","base.strided.svariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancetk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancetk( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancetk( 3, 1, x1, 2 )\n","base.strided.svariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancewd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancewd( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancewd( 3, 1, x1, 2 )\n","base.strided.svariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancewd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svarianceyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svarianceyc( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svarianceyc( 3, 1, x1, 2 )\n","base.strided.svarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.ternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary( [ x, y, z, w ], shape, strides, f );\nw\n","base.strided.ternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\nw\n","base.strided.unary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nbase.strided.unary( [ x, y ], shape, strides, base.abs );\ny\n","base.strided.unary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar offsets = [ 0, 0 ];\nbase.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.unaryBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nsh = [ 2 ];\nst = [ -2, 1 ];\nbase.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\ny1\ny0\n","base.strided.unaryBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nvar o = [ 0, 0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\no = [ 1, y.length-1 ];\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\n","base.strided.unaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.unaryDtypeSignatures( dt, dt )\n","base.strided.unarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.unaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.unarySignatureCallbacks( t, sigs )\n","base.strided.variance":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variance( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variance( 3, 1, x1, 2 )\n","base.strided.variance.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variance.ndarray( 3, 1, x, 2, 1 )\n","base.strided.variancech":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variancech( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variancech( 3, 1, x1, 2 )\n","base.strided.variancech.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variancech.ndarray( 3, 1, x, 2, 1 )\n","base.strided.variancepn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variancepn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variancepn( 3, 1, x1, 2 )\n","base.strided.variancepn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.variancetk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variancetk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variancetk( 3, 1, x1, 2 )\n","base.strided.variancetk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variancetk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.variancewd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variancewd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variancewd( 3, 1, x1, 2 )\n","base.strided.variancewd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variancewd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.varianceyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc( x.length, 1.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.varianceyc( 3, 1.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.varianceyc( 3, 1.0, x1, 2 )\n","base.strided.varianceyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc.ndarray( x.length, 1.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.varianceyc.ndarray( 3, 1.0, x, 2, 1 )\n","base.strided.zmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\nvar v = y.get( 0 )\ny = new Complex128Array( x.length );\nbase.strided.zmap( 2, x, 2, y, -1, base.cidentity );\nv = y.get( 0 )\nvar x0 = new Complex128Array( xbuf );\nvar y0 = new Complex128Array( x0.length );\nvar x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\nv = y1.get( 0 )\n","base.strided.zmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\nvar v = y.get( 0 )\nx = new Complex128Array( xbuf );\ny = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\nv = y.get( y.length-1 )\n","base.str2multislice":"var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\ns.data\ns = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\ns.data\n","base.str2slice":"var s = new base.str2slice( 'Slice(1,10,1)' );\ns.start\ns.stop\ns.step\ns = new base.str2slice( 'Slice(2,5,2)' );\ns.start\ns.stop\ns.step\n","base.sub":"var v = base.sub( -1.0, 5.0 )\nv = base.sub( 2.0, 5.0 )\nv = base.sub( 0.0, 5.0 )\nv = base.sub( -0.0, 0.0 )\nv = base.sub( NaN, NaN )\n","base.subf":"var v = base.subf( -1.0, 5.0 )\nv = base.subf( 2.0, 5.0 )\nv = base.subf( 0.0, 5.0 )\nv = base.subf( -0.0, 0.0 )\nv = base.subf( NaN, NaN )\n","base.sumSeries":"function* geometricSeriesGenerator( x ) {\n var exponent = 0;\n while ( true ) {\n yield Math.pow( x, exponent );\n exponent += 1;\n }\n };\nvar gen = geometricSeriesGenerator( 0.9 );\nvar out = base.sumSeries( gen )\nfunction geometricSeriesClosure( x ) {\n var exponent = -1;\n return function() {\n exponent += 1;\n return Math.pow( x, exponent );\n };\n };\ngen = geometricSeriesClosure( 0.9 );\nout = base.sumSeries( gen )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n","base.tan":"var y = base.tan( 0.0 )\ny = base.tan( -PI/4.0 )\ny = base.tan( PI/4.0 )\ny = base.tan( NaN )\n","base.tand":"var y = base.tand( 0.0 )\ny = base.tand( 90.0 )\ny = base.tand( 60.0 )\ny = base.tand( NaN )\n","base.tanh":"var y = base.tanh( 0.0 )\nvar y = base.tanh( -0.0 )\ny = base.tanh( 2.0 )\ny = base.tanh( -2.0 )\ny = base.tanh( NaN )\n","base.toBinaryString":"var str = base.toBinaryString( 4.0 )\nstr = base.toBinaryString( PI )\nstr = base.toBinaryString( -1.0e308 )\nstr = base.toBinaryString( -3.14e-320 )\nstr = base.toBinaryString( 5.0e-324 )\nstr = base.toBinaryString( 0.0 )\nstr = base.toBinaryString( -0.0 )\nstr = base.toBinaryString( NaN )\nstr = base.toBinaryString( PINF )\nstr = base.toBinaryString( NINF )\n","base.toBinaryStringf":"var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( PI ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\nstr = base.toBinaryStringf( 0.0 )\nstr = base.toBinaryStringf( -0.0 )\nstr = base.toBinaryStringf( NaN )\nstr = base.toBinaryStringf( FLOAT32_PINF )\nstr = base.toBinaryStringf( FLOAT32_NINF )\n","base.toBinaryStringUint8":"var a = new Uint8Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint8( a[ 0 ] )\nstr = base.toBinaryStringUint8( a[ 1 ] )\nstr = base.toBinaryStringUint8( a[ 2 ] )\n","base.toBinaryStringUint16":"var a = new Uint16Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint16( a[ 0 ] )\nstr = base.toBinaryStringUint16( a[ 1 ] )\nstr = base.toBinaryStringUint16( a[ 2 ] )\n","base.toBinaryStringUint32":"var a = new Uint32Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint32( a[ 0 ] )\nstr = base.toBinaryStringUint32( a[ 1 ] )\nstr = base.toBinaryStringUint32( a[ 2 ] )\n","base.toWordf":"var f32 = base.float64ToFloat32( 1.337 )\nvar w = base.toWordf( f32 )\n","base.toWords":"var w = base.toWords( 3.14e201 )\n","base.toWords.assign":"var out = new Uint32Array( 2 );\nvar w = base.toWords.assign( 3.14e201, out, 1, 0 )\nvar bool = ( w === out )\n","base.transpose":"var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nvar y = base.transpose( x, false )\n","base.tribonacci":"var y = base.tribonacci( 0 )\ny = base.tribonacci( 1 )\ny = base.tribonacci( 2 )\ny = base.tribonacci( 3 )\ny = base.tribonacci( 4 )\ny = base.tribonacci( 64 )\ny = base.tribonacci( NaN )\n","base.trigamma":"var y = base.trigamma( -2.5 )\ny = base.trigamma( 1.0 )\ny = base.trigamma( 10.0 )\ny = base.trigamma( NaN )\ny = base.trigamma( -1.0 )\n","base.trim":"var out = base.trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","base.trunc":"var y = base.trunc( 3.14 )\ny = base.trunc( -4.2 )\ny = base.trunc( -4.6 )\ny = base.trunc( 9.5 )\ny = base.trunc( -0.0 )\n","base.trunc2":"var y = base.trunc2( 3.14 )\ny = base.trunc2( -4.2 )\ny = base.trunc2( -4.6 )\ny = base.trunc2( 9.5 )\ny = base.trunc2( 13.0 )\ny = base.trunc2( -13.0 )\ny = base.trunc2( -0.0 )\n","base.trunc10":"var y = base.trunc10( 3.14 )\ny = base.trunc10( -4.2 )\ny = base.trunc10( -4.6 )\ny = base.trunc10( 9.5 )\ny = base.trunc10( 13.0 )\ny = base.trunc10( -13.0 )\ny = base.trunc10( -0.0 )\n","base.truncateMiddle":"var str = 'beep boop';\nvar out = base.truncateMiddle( str, 5, '...' )\nout = base.truncateMiddle( str, 5, '|' )\n","base.truncb":"var y = base.truncb( 3.14159, -4, 10 )\ny = base.truncb( 3.14159, 0, 2 )\ny = base.truncb( 5.0, 1, 2 )\n","base.truncf":"var y = base.truncf( 3.14 )\ny = base.truncf( -4.2 )\ny = base.truncf( -4.6 )\ny = base.truncf( 9.5 )\ny = base.truncf( -0.0 )\n","base.truncn":"var y = base.truncn( 3.14159, -4 )\ny = base.truncn( 3.14159, 0 )\ny = base.truncn( 12368.0, 3 )\n","base.truncsd":"var y = base.truncsd( 3.14159, 5, 10 )\ny = base.truncsd( 3.14159, 1, 10 )\ny = base.truncsd( 12368.0, 2, 10 )\ny = base.truncsd( 0.0313, 2, 2 )\n","base.uint32ToInt32":"var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\ny = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n","base.umul":"var v = base.umul( 10>>>0, 4>>>0 )\n","base.umuldw":"var v = base.umuldw( 1, 10 )\n","base.umuldw.assign":"var out = [ 0, 0 ];\nvar v = base.umuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.uncapitalize":"var out = base.uncapitalize( 'Beep' )\nout = base.uncapitalize( 'bOOp' )\n","base.uppercase":"var out = base.uppercase( 'bEEp' )\n","base.vercos":"var y = base.vercos( 3.14 )\ny = base.vercos( -4.2 )\ny = base.vercos( -4.6 )\ny = base.vercos( 9.5 )\ny = base.vercos( -0.0 )\n","base.versin":"var y = base.versin( 3.14 )\ny = base.versin( -4.2 )\ny = base.versin( -4.6 )\ny = base.versin( 9.5 )\ny = base.versin( -0.0 )\n","base.wrap":"var y = base.wrap( 3.14, 0.0, 5.0 )\ny = base.wrap( -3.14, 0.0, 5.0 )\ny = base.wrap( 3.14, 0.0, 3.0 )\ny = base.wrap( -0.0, 0.0, 5.0 )\ny = base.wrap( 0.0, -3.14, -0.0 )\ny = base.wrap( NaN, 0.0, 5.0 )\n","base.xlog1py":"var out = base.xlog1py( 3.0, 2.0 )\nout = base.xlog1py( 1.5, 5.9 )\nout = base.xlog1py( 0.9, 1.0 )\nout = base.xlog1py( 1.0, 0.0 )\nout = base.xlog1py( 0.0, -2.0 )\nout = base.xlog1py( 1.5, NaN )\nout = base.xlog1py( 0.0, NaN )\nout = base.xlog1py( NaN, 2.3 )\n","base.xlogy":"var out = base.xlogy( 3.0, 2.0 )\nout = base.xlogy( 1.5, 5.9 )\nout = base.xlogy( 0.9, 1.0 )\nout = base.xlogy( 0.0, -2.0 )\nout = base.xlogy( 1.5, NaN )\nout = base.xlogy( 0.0, NaN )\nout = base.xlogy( NaN, 2.3 )\n","base.zeta":"var y = base.zeta( 1.1 )\ny = base.zeta( -4.0 )\ny = base.zeta( 70.0 )\ny = base.zeta( 0.5 )\ny = base.zeta( NaN )\ny = base.zeta( 1.0 )\n","BERNDT_CPS_WAGES_1985":"var data = BERNDT_CPS_WAGES_1985()\n","bifurcate":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar f = [ true, true, false, true ];\nvar out = bifurcate( collection, f )\nf = [ 1, 1, 0, 1 ];\nout = bifurcate( collection, f )\nf = [ true, true, false, true ];\nvar opts = { 'returns': 'indices' };\nout = bifurcate( collection, opts, f )\nopts = { 'returns': '*' };\nout = bifurcate( collection, opts, f )\n","bifurcateBy":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = bifurcateBy( collection, predicate )\nvar opts = { 'returns': 'indices' };\nout = bifurcateBy( collection, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateBy( collection, opts, predicate )\n","bifurcateByAsync":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, predicate, done )\nvar opts = { 'returns': 'indices' };\nbifurcateByAsync( arr, opts, predicate, done )\nopts = { 'returns': '*' };\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n","bifurcateByAsync.factory":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = bifurcateByAsync.factory( opts, predicate );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","bifurcateIn":"function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nfunction predicate( v ) { return v[ 0 ] === 'b'; };\nvar out = bifurcateIn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateIn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateIn( obj, opts, predicate )\n","bifurcateOwn":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = bifurcateOwn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateOwn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateOwn( obj, opts, predicate )\n","BigInt":"var v = ( BigInt ) ? BigInt( '1' ) : null\n","binomialTest":"var out = binomialTest( 682, 925 )\nout = binomialTest( [ 682, 925 - 682 ] )\nout = binomialTest( 21, 40, {\n 'p': 0.4,\n 'alternative': 'greater'\n })\n","Boolean":"var b = new Boolean( null )\nb = Boolean( null )\nb = Boolean( [] )\n","Boolean.prototype.toString":"var b = new Boolean( true )\nb.toString()\n","Boolean.prototype.valueOf":"var b = new Boolean( true )\nb.valueOf()\n","BooleanArray":"var arr = new BooleanArray()\nvar arr = new BooleanArray( 10 )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar arr2 = new BooleanArray( arr1 )\nvar len = arr2.length\nvar buf = new Uint8Array( [ 1, 0, 0, 1 ] )\nvar arr = new BooleanArray( buf )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar len = arr1.length\nvar arr2 = new BooleanArray( [ {}, null, '', 4 ] );\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new BooleanArray( buf )\nvar len = arr1.length\nvar arr2 = new BooleanArray( buf, 8 )\nlen = arr2.length\nvar arr3 = new BooleanArray( buf, 8, 20 )\nlen = arr3.length\n","BooleanArray.from":"function map( v ) { return !v };\nvar src = [ true, false ];\nvar arr = BooleanArray.from( src, map )\nvar len = arr.length\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.of":"var arr = BooleanArray.of( true, false, false, true )\nvar len = arr.length\n","BooleanArray.BYTES_PER_ELEMENT":"var nbytes = BooleanArray.BYTES_PER_ELEMENT\n","BooleanArray.name":"var str = BooleanArray.name\n","BooleanArray.prototype.buffer":"var arr = new BooleanArray( 2 )\nvar buf = arr.buffer\n","BooleanArray.prototype.byteLength":"var arr = new BooleanArray( 10 )\nvar nbytes = arr.byteLength\n","BooleanArray.prototype.byteOffset":"var arr = new BooleanArray( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new BooleanArray( buf, 64 )\noffset = arr.byteOffset\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"var arr = new BooleanArray( 10 )\narr.BYTES_PER_ELEMENT\n","BooleanArray.prototype.length":"var arr = new BooleanArray( 10 )\nvar len = arr.length\n","BooleanArray.prototype.at":"var arr = new BooleanArray( [ true, false, false, true ] )\nvar v = arr.at( 1 )\nv = arr.at( -1 )\n","BooleanArray.prototype.copyWithin":"var arr = new BooleanArray( [ true, false, false, true ] )\narr.copyWithin( 0, 2 )\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.prototype.entries":"var arr = new BooleanArray( [ true, false, true ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.every":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, true, true ] )\nvar bool = arr.every( predicate )\n","BooleanArray.prototype.fill":"var arr = new BooleanArray( 3 )\narr.fill( true );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.filter":"function predicate( v ) { return ( v === true ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.find":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.find( predicate )\n","BooleanArray.prototype.findIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findIndex( predicate )\n","BooleanArray.prototype.findLast":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.findLast( predicate )\n","BooleanArray.prototype.findLastIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findLastIndex( predicate )\n","BooleanArray.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new BooleanArray( [ true, false, false, true ] )\narr.forEach( clbk );\nstr\n","BooleanArray.prototype.get":"var arr = new BooleanArray( 10 )\narr.set( true, 0 );\nvar v = arr.get( 0 )\n","BooleanArray.prototype.includes":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar bool = arr.includes( true )\nbool = arr.includes( false, 3 )\n","BooleanArray.prototype.indexOf":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar idx = arr.indexOf( true )\nidx = arr.indexOf( false, 3 )\n","BooleanArray.prototype.join":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.join()\nstr = arr.join( '|' )\n","BooleanArray.prototype.keys":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","BooleanArray.prototype.lastIndexOf":"var arr = new BooleanArray( [ true, true, true, false, true ] )\nvar idx = arr.lastIndexOf( false )\nidx = arr.lastIndexOf( false, 2 )\n","BooleanArray.prototype.map":"function invert( v ) { return !v; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.map( invert )\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.reduce":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduce( reducer )\n","BooleanArray.prototype.reduceRight":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduceRight( reducer )\n","BooleanArray.prototype.reverse":"var arr = new BooleanArray( [ true, false, false ] )\narr.reverse();\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.set":"var arr = new BooleanArray( 2 )\narr.set( false );\nvar v = arr.get( 0 )\narr.set( true, 1 );\nv = arr.get( 1 )\n","BooleanArray.prototype.slice":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.some":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ false, true, false ] )\nvar bool = arr.some( predicate )\n","BooleanArray.prototype.sort":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\narr.sort( compare );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.subarray":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.toLocaleString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toLocaleString()\n","BooleanArray.prototype.toReversed":"var arr = new BooleanArray( [ true, false, false ] )\nvar out = arr.toReversed()\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toSorted":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.toSorted( compare );\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toString()\n","BooleanArray.prototype.values":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.values();\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.with":"var arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.with( 0, false )\nvar v = out.get( 0 )\n","broadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = broadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","broadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = broadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","Buffer":"var b = new Buffer( 4 )\nvar b1 = new Buffer( [ 1, 2, 3, 4 ] );\nvar b2 = new Buffer( b1 )\nvar b = new Buffer( [ 1, 2, 3, 4 ] )\nvar b = new Buffer( 'beep boop' )\n","buffer2json":"var buf = new allocUnsafe( 2 );\nbuf[ 0 ] = 1;\nbuf[ 1 ] = 2;\nvar json = buffer2json( buf )\n","BYTE_ORDER":"BYTE_ORDER\n","camelcase":"var out = camelcase( 'Hello World!' )\nout = camelcase( 'beep boop' )\n","capitalize":"var out = capitalize( 'beep' )\nout = capitalize( 'Boop' )\n","capitalizeKeys":"var obj = { 'aa': 1, 'bb': 2 };\nvar out = capitalizeKeys( obj )\n","CATALAN":"CATALAN\n","CBRT_EPS":"CBRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"var data = CDC_NCHS_US_BIRTHS_1969_1988()\n","CDC_NCHS_US_BIRTHS_1994_2003":"var data = CDC_NCHS_US_BIRTHS_1994_2003()\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n","chdir":"var err = chdir( '/path/to/current/working/directory' )\n","chi2gof":"var x = [ 89, 37, 30, 28, 2 ];\nvar p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nvar out = chi2gof( x, p );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.01 };\nout = chi2gof( x, p, opts );\nout.toString()\nx = [ 89, 37, 30, 28, 2 ];\np = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nopts = { 'simulate': true, 'iterations': 1000 };\nout = chi2gof( x, p, opts );\nout.toString()\nvar lambda = 3.0;\nvar rpois = base.random.poisson.factory( lambda );\nvar len = 400;\nx = [];\nfor ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\nvar freqs = new Int32Array( len );\nfor ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\nout = chi2gof( freqs, 'poisson', lambda );\nout.toString()\n","chi2test":"var x = [ [ 20, 30 ], [ 30, 20 ] ];\nvar out = chi2test( x );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.1 };\nout = chi2test( x, opts );\no = out.toJSON()\nout.toString()\nopts = { 'correct': false };\nout = chi2test( x, opts );\nout.toString()\n","circarray2iterator":"var it = circarray2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","circularArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","circularArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = circularArrayStream.factory( opts );\n","circularArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","CircularBuffer":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.length\nb.count\nb.push( 'boop' )\n","CircularBuffer.prototype.clear":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.count\nb.clear();\nb.count\n","CircularBuffer.prototype.count":"var b = CircularBuffer( 3 );\nb.count\nb.push( 'foo' );\nb.count\nb.push( 'bar' );\nb.count\n","CircularBuffer.prototype.full":"var b = CircularBuffer( 3 );\nb.full\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.full\n","CircularBuffer.prototype.iterator":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar it = b.iterator( b.length );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","CircularBuffer.prototype.length":"var b = CircularBuffer( [ 0, 0, 0 ] );\nvar len = b.length\n","CircularBuffer.prototype.push":"var b = CircularBuffer( 3 );\nb.push( 'foo' )\nb.push( 'bar' )\nb.push( 'beep' )\nb.push( 'boop' )\n","CircularBuffer.prototype.toArray":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar vals = b.toArray()\n","CircularBuffer.prototype.toJSON":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar o = b.toJSON()\n","close":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nvar fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close( fd, done ); };\n","close.sync":"var fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","CMUDICT":"var data = CMUDICT();\nvar dict = data.dict\nvar phones = data.phones\nvar symbols = data.symbols\nvar vp = data.vp\n","codePointAt":"var out = codePointAt( 'last man standing', 4 )\nout = codePointAt( 'presidential election', 8, true )\nout = codePointAt( 'अनुच्छेद', 2 )\nout = codePointAt( '🌷', 1, true )\n","commonKeys":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeys( obj1, obj2 )\n","commonKeysIn":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeysIn( obj1, obj2 )\n","complex":"var z = complex( 5.0, 3.0, 'float64' )\nz = complex( 5.0, 3.0, 'float32' )\n","Complex64":"var z = new Complex64( 5.0, 3.0 )\nz.re\nz.im\n","Complex64.name":"var str = Complex64.name\n","Complex64.BYTES_PER_ELEMENT":"var s = Complex64.BYTES_PER_ELEMENT\n","Complex64.prototype.BYTES_PER_ELEMENT":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex64.prototype.byteLength":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX64_NAN":"COMPLEX64_NAN\n","COMPLEX64_NUM_BYTES":"COMPLEX64_NUM_BYTES\n","COMPLEX64_ZERO":"COMPLEX64_ZERO\n","Complex64Array":"var arr = new Complex64Array()\nvar arr = new Complex64Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex64Array( arr1 )\nvar len = arr2.length\nvar buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex64Array( buf )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\nvar arr2 = new Complex64Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new Complex64Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex64Array( buf, 8 )\nlen = arr2.length\nvar arr3 = new Complex64Array( buf, 8, 20 )\nlen = arr3.length\n","Complex64Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.of":"var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex64( 1.0, -1.0 );\nvar z2 = new Complex64( 2.0, -2.0 );\narr = Complex64Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.BYTES_PER_ELEMENT":"var nbytes = Complex64Array.BYTES_PER_ELEMENT\n","Complex64Array.name":"var str = Complex64Array.name\n","Complex64Array.prototype.buffer":"var arr = new Complex64Array( 2 )\nvar buf = arr.buffer\n","Complex64Array.prototype.byteLength":"var arr = new Complex64Array( 10 )\nvar nbytes = arr.byteLength\n","Complex64Array.prototype.byteOffset":"var arr = new Complex64Array( 5 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new Complex64Array( buf, 64 )\noffset = arr.byteOffset\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex64Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex64Array.prototype.length":"var arr = new Complex64Array( 10 )\nvar len = arr.length\n","Complex64Array.prototype.at":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.copyWithin":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.entries":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nvar re = realf( v[ 1 ] )\nvar im = imagf( v[ 1 ] )\nv = it.next().value\nre = realf( v[ 1 ] )\nim = imagf( v[ 1 ] )\nv = it.next().value\nre = realf( v[ 1 ] )\nim = imagf( v[ 1 ] )\nvar bool = it.next().done\n","Complex64Array.prototype.every":"function predicate( v ) { return ( realf( v ) > 0.0 ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex64Array.prototype.fill":"var arr = new Complex64Array( 3 )\narr.fill( new Complex64( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.filter":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.find":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.findIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex64Array.prototype.findLast":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.findLastIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex64Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex64Array.prototype.get":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.includes":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex64( 3.0, -3.0 ) )\nbool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.indexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.join":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex64Array.prototype.keys":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex64Array.prototype.lastIndexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n","Complex64Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.reduce":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.caddf )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.reduceRight":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.caddf )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.reverse":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.set":"var arr = new Complex64Array( 2 )\narr.set( new Complex64( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\narr.set( new Complex64( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.slice":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.some":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex64Array.prototype.sort":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.subarray":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toLocaleString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex64Array.prototype.toReversed":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = out.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toSorted":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = out.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex64Array.prototype.values":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nvar re = realf( v )\nvar im = imagf( v )\nv = it.next().value\nre = realf( v )\nim = imagf( v )\nvar bool = it.next().done\n","Complex64Array.prototype.with":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex128.name":"var str = Complex128.name\n","Complex128.BYTES_PER_ELEMENT":"var s = Complex128.BYTES_PER_ELEMENT\n","Complex128.prototype.BYTES_PER_ELEMENT":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex128.prototype.byteLength":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX128_NAN":"COMPLEX128_NAN\n","COMPLEX128_NUM_BYTES":"COMPLEX128_NUM_BYTES\n","COMPLEX128_ZERO":"COMPLEX128_ZERO\n","Complex128Array":"var arr = new Complex128Array()\nvar arr = new Complex128Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex128Array( arr1 )\nvar len = arr2.length\nvar buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex128Array( buf )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\nvar arr2 = new Complex128Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 480 );\nvar arr1 = new Complex128Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex128Array( buf, 16 )\nlen = arr2.length\nvar arr3 = new Complex128Array( buf, 16, 20 )\nlen = arr3.length\n","Complex128Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\n","Complex128Array.of":"var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex128( 1.0, -1.0 );\nvar z2 = new Complex128( 2.0, -2.0 );\narr = Complex128Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\n","Complex128Array.BYTES_PER_ELEMENT":"var nbytes = Complex128Array.BYTES_PER_ELEMENT\n","Complex128Array.name":"var str = Complex128Array.name\n","Complex128Array.prototype.buffer":"var arr = new Complex128Array( 2 )\nvar buf = arr.buffer\n","Complex128Array.prototype.byteLength":"var arr = new Complex128Array( 10 )\nvar nbytes = arr.byteLength\n","Complex128Array.prototype.byteOffset":"var arr = new Complex128Array( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 480 );\narr = new Complex128Array( buf, 128 )\noffset = arr.byteOffset\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex128Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex128Array.prototype.length":"var arr = new Complex128Array( 10 )\nvar len = arr.length\n","Complex128Array.prototype.at":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\n","Complex128Array.prototype.copyWithin":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\n","Complex128Array.prototype.entries":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","Complex128Array.prototype.every":"function predicate( v ) { return ( real( v ) > 0.0 ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex128Array.prototype.fill":"var arr = new Complex128Array( 3 )\narr.fill( new Complex128( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n","Complex128Array.prototype.filter":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\n","Complex128Array.prototype.find":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\n","Complex128Array.prototype.findIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex128Array.prototype.findLast":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\n","Complex128Array.prototype.findLastIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex128Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex128Array.prototype.get":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\n","Complex128Array.prototype.includes":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex128( 3.0, -3.0 ) )\nbool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.indexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.join":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex128Array.prototype.keys":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex128Array.prototype.lastIndexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n","Complex128Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nz = out.get( 1 )\n","Complex128Array.prototype.reduce":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.cadd )\n","Complex128Array.prototype.reduceRight":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.cadd )\n","Complex128Array.prototype.reverse":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n","Complex128Array.prototype.set":"var arr = new Complex128Array( 2 )\narr.set( new Complex128( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\narr.set( new Complex128( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\n","Complex128Array.prototype.slice":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nz = out.get( 1 )\n","Complex128Array.prototype.some":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex128Array.prototype.sort":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n","Complex128Array.prototype.subarray":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toLocaleString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex128Array.prototype.toReversed":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toSorted":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex128Array.prototype.values":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nvar re = real( v )\nvar im = imag( v )\nv = it.next().value\nre = real( v )\nim = imag( v )\nvar bool = it.next().done\n","Complex128Array.prototype.with":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\nvar re = real( z )\nvar im = imag( z )\n","complexarray":"var arr = complexarray()\narr = complexarray( 'complex64' )\nvar arr = complexarray( 5 )\narr = complexarray( 5, 'complex64' )\nvar arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\nvar arr2 = complexarray( arr1, 'complex64' )\nvar arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\nvar arr2 = complexarray( arr1, 'complex64' )\nvar buf = new ArrayBuffer( 64 );\nvar arr = complexarray( buf, 0, 8, 'complex64' )\n","complexarrayCtors":"var ctor = complexarrayCtors( 'complex64' )\nctor = complexarrayCtors( 'float32' )\n","complexarrayDataTypes":"var out = complexarrayDataTypes()\n","complexCtors":"var ctor = complexCtors( 'complex128' )\nctor = complexCtors( 'complex' )\n","complexDataType":"var v = new Complex128( 1.0, 2.0 );\nvar dt = complexDataType( v )\ndt = complexDataType( 'beep' )\n","complexDataTypes":"var out = complexDataTypes()\n","complexPromotionRules":"var out = complexPromotionRules( 'complex128', 'complex64' )\n","compose":"function a( x ) {\nreturn 2 * x;\n }\nfunction b( x ) {\nreturn x + 3;\n }\nfunction c( x ) {\nreturn x / 5;\n }\nvar f = compose( c, b, a );\nvar z = f( 6 )\n","composeAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x/5 );\n}\n };\nvar f = composeAsync( c, b, a );\nfunction done( error, result ) {\nif ( error ) {\n throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","configdir":"var dir = configdir()\ndir = configdir( 'appname/config' )\n","conj":"var z = new Complex128( 5.0, 3.0 );\nz.toString()\nvar v = conj( z );\nv.toString()\n","conjf":"var z = new Complex64( 5.0, 3.0 );\nz.toString()\nvar v = conjf( z );\nv.toString()\n","constantcase":"var out = constantcase( 'Hello World!' )\nout = constantcase( 'I am a tiny little teapot' )\n","constantFunction":"var fcn = constantFunction( 3.14 );\nvar v = fcn()\nv = fcn()\nv = fcn()\n","constantStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream( 'beep', opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","constantStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = constantStream.factory( opts );\n","constantStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream.objectMode( 3.14, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","constructorName":"var v = constructorName( 'a' )\nv = constructorName( {} )\nv = constructorName( true )\n","contains":"var bool = contains( 'Hello World', 'World' )\nbool = contains( 'Hello World', 'world' )\nbool = contains( [ 1, 2, 3, 4 ], 2 )\nbool = contains( [ NaN, 2, 3, 4 ], NaN )\nbool = contains( 'Hello World', 'Hello', 6 )\nbool = contains( [ true, NaN, false ], true, 1 )\n","convertArray":"var arr = [ 1.0, 2.0, 3.0, 4.0 ];\nvar out = convertArray( arr, 'float32' )\n","convertArraySame":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = new Float32Array( 0 );\nvar out = convertArraySame( x, y )\n","convertPath":"var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\nout = convertPath( '/c/foo/bar/beep.c', 'mixed' )\nout = convertPath( '/c/foo/bar/beep.c', 'posix' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n","copy":"var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nvar out = copy( value )\nvar bool = ( value[ 0 ].c === out[ 0 ].c )\nvalue = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nout = copy( value, 1 );\nbool = ( value[ 0 ] === out[ 0 ] )\nbool = ( value[ 0 ].c === out[ 0 ].c )\n","copyBuffer":"var b1 = array2buffer( [ 1, 2, 3, 4 ] );\nvar b2 = copyBuffer( b1 )\n","countBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = countBy( collection, indicator )\n","countByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n","countByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = countByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 500 ];\nf( arr, done )\n","currentYear":"var y = currentYear()\n","curry":"function add( x, y ) { return x + y; };\nvar f = curry( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curry( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curry( obj.greet, obj );\nvar str = f( 'Hello' )( 'there' )\n","curryRight":"function add( x, y ) { return x + y; };\nvar f = curryRight( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curryRight( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curryRight( obj.greet, obj );\nvar str = f( 'there' )( 'Hello' )\n","cwd":"var dir = cwd()\n","DALE_CHALL_NEW":"var list = DALE_CHALL_NEW()\n","datasets":"var out = datasets( 'MONTH_NAMES_EN' )\nvar opts = { 'data': 'cities' };\nout = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n","DataType":"var dt = new DataType( 'float64' );\ndt.byteLength\n","DataType.name":"DataType.name\n","DataType.prototype.alignment":"var dt = new DataType( 'float64' );\ndt.alignment\n","DataType.prototype.byteLength":"var dt = new DataType( 'float64' );\ndt.byteLength\n","DataType.prototype.byteOrder":"var dt = new DataType( 'float64' );\ndt.byteOrder\n","DataType.prototype.char":"var dt = new DataType( 'float64' );\ndt.char\n","DataType.prototype.description":"var dt = new DataType( 'float64' );\ndt.description\n","DataType.prototype.enum":"var dt = new DataType( 'float64' );\ndt.enum\n","DataType.prototype.value":"var dt = new DataType( 'float64' );\ndt.value\n","DataType.prototype.toJSON":"var dt = new DataType( 'float64' );\ndt.toJSON()\n","DataType.prototype.toString":"var dt = new DataType( 'float64' );\ndt.toString()\n","DataType.prototype.valueOf":"var dt = new DataType( 'float64' );\ndt.valueOf()\n","DataView":"var buf = new ArrayBuffer( 5 )\nvar dv = new DataView( buf )\n","DataView.prototype.buffer":"var buf1 = new ArrayBuffer( 5 );\nvar dv = new DataView( buf1 );\nvar buf2 = dv.buffer\nvar b = ( buf1 === buf2 )\n","DataView.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf );\ndv.byteLength\n","DataView.prototype.byteOffset":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf, 2 );\ndv.byteLength\ndv.byteOffset\n","datespace":"var stop = '2014-12-02T07:00:54.973Z';\nvar start = new Date( stop ) - 60000;\nvar arr = datespace( start, stop, 6 )\nvar opts = { 'round': 'ceil' };\narr = datespace( 1417503655000, 1417503655001, 3, opts )\n","dayOfQuarter":"var day = dayOfQuarter()\nday = dayOfQuarter( new Date() )\nday = dayOfQuarter( 12, 31, 2017 )\nday = dayOfQuarter( 'dec', 31, 2017 )\nday = dayOfQuarter( 'december', 31, 2017 )\n","dayOfYear":"var day = dayOfYear()\nday = dayOfYear( new Date() )\nday = dayOfYear( 12, 31, 2016 )\nday = dayOfYear( 'dec', 31, 2016 )\nday = dayOfYear( 'december', 31, 2016 )\n","daysInMonth":"var num = daysInMonth()\nnum = daysInMonth( 2 )\nnum = daysInMonth( 2, 2016 )\nnum = daysInMonth( 2, 2017 )\nnum = daysInMonth( 'feb', 2016 )\nnum = daysInMonth( 'february', 2016 )\n","daysInYear":"var num = daysInYear()\nnum = daysInYear( 2016 )\nnum = daysInYear( 2017 )\n","ddot":"var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = ddot( x, y )\n","debugSinkStream":"var s = debugSinkStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugSinkStream.factory( opts );\n","debugSinkStream.objectMode":"var s = debugSinkStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","debugStream":"var s = debugStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugStream.factory( opts );\n","debugStream.objectMode":"var s = debugStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","decorateAfter":"function f( v ) { return -v; };\nvar fcn = decorateAfter( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","decorateAfter.factory":"function f( v ) { return -v; };\nvar fcn = decorateAfter.factory( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","deepEqual":"var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\nbool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\nbool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n","deepGet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a.b.c' )\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n","deepGet.factory":"var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = dget( obj )\n","deepHasOwnProp":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepHasOwnProp( obj, 'a.b.c' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasOwnProp.factory":"var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = has( obj )\n","deepHasProp":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar obj = { 'a': new Foo() };\nvar bool = deepHasProp( obj, 'a.b.c' )\nbool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasProp.factory":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': new Foo() };\nvar bool = has( obj )\n","deepPluck":"var arr = [\n { 'a': { 'b': { 'c': 1 } } },\n { 'a': { 'b': { 'c': 2 } } }\n ];\nvar out = deepPluck( arr, 'a.b.c' )\narr = [\n { 'a': [ 0, 1, 2 ] },\n { 'a': [ 3, 4, 5 ] }\n ];\nout = deepPluck( arr, [ 'a', 1 ] )\n","deepSet":"var obj1 = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepSet( obj1, 'a.b.c', 'beep' )\nvar obj2 = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj2, 'a/b/c', 'beep', { 'sep': '/' } );\nobj2\nvar obj3 = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj3, 'a.e.c', 'boop', { 'create': true } );\nobj3\n","deepSet.factory":"var dset = deepSet.factory( 'a/b/c', {\n 'create': true,\n 'sep': '/'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = dset( obj, 'beep' )\nobj\n","defineMemoizedProperty":"var obj = {};\nfunction foo() {\n return 'bar';\n };\ndefineMemoizedProperty( obj, 'foo', {\n 'configurable': false,\n 'enumerable': true,\n 'writable': false,\n 'value': foo\n });\nobj.foo\n","defineProperties":"var obj = {};\ndefineProperties( obj, {\n 'foo': {\n 'value': 'bar',\n 'writable': false,\n 'configurable': false,\n 'enumerable': true\n },\n 'baz': {\n 'value': 13\n }\n });\nobj.foo\nobj.baz\n","defineProperty":"var obj = {};\ndefineProperty( obj, 'foo', {\n 'value': 'bar',\n 'enumerable': true,\n 'writable': false\n });\nobj.foo = 'boop';\nobj\n","dirname":"var dir = dirname( './foo/bar/index.js' )\n","dotcase":"var out = dotcase( 'Hello World!' )\nout = dotcase( 'beep boop' )\n","DoublyLinkedList":"var list = DoublyLinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","doUntil":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoUntil( beep, predicate )\n","doUntilAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ndoUntilAsync( fcn, predicate, done )\n","doUntilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoUntilEach( arr, logger, predicate )\n","doUntilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoUntilEachRight( arr, logger, predicate )\n","doWhile":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoWhile( beep, predicate )\n","doWhileAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ndoWhileAsync( fcn, predicate, done )\n","doWhileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoWhileEach( arr, logger, predicate )\n","doWhileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoWhileEachRight( arr, logger, predicate )\n","dswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ndswap( x, y );\nx.data\ny.data\n","E":"E\n","EMOJI":"var data = EMOJI()\n","EMOJI_CODE_PICTO":"var out = EMOJI_CODE_PICTO()\n","EMOJI_PICTO_CODE":"var out = EMOJI_PICTO_CODE()\n","emptyStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = emptyStream();\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","emptyStream.factory":"var opts = { 'objectMode': true };\nvar createStream = emptyStream.factory( opts );\n","emptyStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = emptyStream.objectMode();\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","endsWith":"var bool = endsWith( 'beep', 'ep' )\nbool = endsWith( 'Beep', 'op' )\nbool = endsWith( 'Beep', 'ee', 3 )\nbool = endsWith( 'Beep', 'ee', -1 )\nbool = endsWith( 'beep', '' )\n","enumerableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = enumerableProperties( obj )\n","enumerablePropertiesIn":"var props = enumerablePropertiesIn( [] )\n","enumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbols( obj )\n","enumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbolsIn( obj )\n","ENV":"var user = ENV.USER\n","EPS":"EPS\n","error2json":"var err = new Error( 'beep' );\nvar json = error2json( err )\n","EULERGAMMA":"EULERGAMMA\n","every":"var arr = [ 1, 1, 1, 1, 1 ];\nvar bool = every( arr )\n","everyBy":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyBy( arr, positive )\n","everyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n","everyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","everyByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyByRight( arr, positive )\n","everyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n","everyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","everyInBy":"function positive( v ) { return ( v > 0 ); };\nvar o = {a: 1, b: 2, c: 3};\nvar bool = everyInBy( o, positive )\n","everyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nvar bool = everyOwnBy( obj, positive )\n","evil":"var v = evil( '5*4*3*2*1' )\n","EXEC_PATH":"EXEC_PATH\n","exists":"function done( error, bool ) { console.log( bool ); };\nexists( './beep/boop', done );\n","exists.sync":"var bool = exists.sync( './beep/boop' )\n","expandAcronyms":"var str = 'LOL, this is fun. I am ROFL.';\nvar out = expandAcronyms( str )\nstr = 'brb, I need to check my mail. thx!';\nout = expandAcronyms( str )\n","expandContractions":"var str = 'I won\\'t be able to get y\\'all out of this one.';\nvar out = expandContractions( str )\nstr = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\nout = expandContractions( str )\n","extname":"var ext = extname( 'index.js' )\n","FancyArray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","FancyArray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","FancyArray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","FancyArray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","FancyArray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","FancyArray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","FancyArray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","FancyArray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","FancyArray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","FancyArray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","FancyArray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","FancyArray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","FancyArray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","FancyArray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","FancyArray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","FancyArray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","fastmath.abs":"var v = fastmath.abs( -1.0 )\nv = fastmath.abs( 2.0 )\nv = fastmath.abs( 0.0 )\nv = fastmath.abs( -0.0 )\nv = fastmath.abs( NaN )\n","fastmath.acosh":"var v = fastmath.acosh( 1.0 )\nv = fastmath.acosh( 2.0 )\nv = fastmath.acosh( NaN )\nv = fastmath.acosh( 1.0e308 )\n","fastmath.ampbm":"var h = fastmath.ampbm( 5.0, 12.0 )\n","fastmath.ampbm.factory":"var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n","fastmath.asinh":"var v = fastmath.asinh( 0.0 )\nv = fastmath.asinh( 2.0 )\nv = fastmath.asinh( -2.0 )\nv = fastmath.asinh( NaN )\nv = fastmath.asinh( 1.0e200 )\nv = fastmath.asinh( 1.0e-50 )\n","fastmath.atanh":"var v = fastmath.atanh( 0.0 )\nv = fastmath.atanh( 0.9 )\nv = fastmath.atanh( 1.0 )\nv = fastmath.atanh( -1.0 )\nv = fastmath.atanh( NaN )\nv = fastmath.atanh( 1.0e-17 )\n","fastmath.hypot":"var h = fastmath.hypot( -5.0, 12.0 )\nh = fastmath.hypot( 1.0e154, 1.0e154 )\nh = fastmath.hypot( 1e-200, 1.0e-200 )\n","fastmath.log2Uint32":"var v = fastmath.log2Uint32( 4 >>> 0 )\nv = fastmath.log2Uint32( 8 >>> 0 )\nv = fastmath.log2Uint32( 9 >>> 0 )\n","fastmath.max":"var v = fastmath.max( 3.14, 4.2 )\nv = fastmath.max( 3.14, NaN )\nv = fastmath.max( NaN, 3.14 )\nv = fastmath.max( -0.0, +0.0 )\nv = fastmath.max( +0.0, -0.0 )\n","fastmath.min":"var v = fastmath.min( 3.14, 4.2 )\nv = fastmath.min( 3.14, NaN )\nv = fastmath.min( NaN, 3.14 )\nv = fastmath.min( -0.0, +0.0 )\nv = fastmath.min( +0.0, -0.0 )\n","fastmath.powint":"var v = fastmath.powint( 2.0, 3 )\nv = fastmath.powint( 3.14, 0 )\nv = fastmath.powint( 2.0, -2 )\nv = fastmath.powint( 0.0, 0 )\nv = fastmath.powint( -3.14, 1 )\nv = fastmath.powint( NaN, 0 )\n","fastmath.sqrtUint32":"var v = fastmath.sqrtUint32( 9 >>> 0 )\nv = fastmath.sqrtUint32( 2 >>> 0 )\nv = fastmath.sqrtUint32( 3 >>> 0 )\nv = fastmath.sqrtUint32( 0 >>> 0 )\n","FEMALE_FIRST_NAMES_EN":"var list = FEMALE_FIRST_NAMES_EN()\n","FIFO":"var q = FIFO();\nq.push( 'foo' ).push( 'bar' );\nq.length\nq.pop()\nq.length\nq.pop()\nq.length\n","filledarray":"var arr = filledarray()\narr = filledarray( 'float32' )\nvar arr = filledarray( 1.0, 5 )\narr = filledarray( 1, 5, 'int32' )\nvar arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n","filledarrayBy":"var arr = filledarrayBy()\narr = filledarrayBy( 'float32' )\nfunction clbk() { return 1.0; };\nvar arr = filledarrayBy( 5, clbk )\narr = filledarrayBy( 5, 'int32', clbk )\nvar arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n","filterArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v !== 2 ); };\nvar bar = filterArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","find":"var data = [ 30, 20, 50, 60, 10 ];\nfunction condition( val ) { return val > 20; };\nvar vals = find( data, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nvar opts = { 'k': 2, 'returns': 'values' };\nvals = find( data, opts, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nopts = { 'k': -2, 'returns': '*' };\nvals = find( data, opts, condition )\n","firstChar":"var out = firstChar( 'beep' )\nout = firstChar( 'Boop', 1 )\nout = firstChar( 'foo bar', 5 )\n","FIVETHIRTYEIGHT_FFQ":"var data = FIVETHIRTYEIGHT_FFQ()\n","flattenArray":"var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nvar out = flattenArray( arr )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2 } )\nvar bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2, 'copy': true } )\nbool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n","flattenArray.factory":"var flatten = flattenArray.factory( [ 2, 2 ], {\n 'copy': false\n });\nvar out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\nout = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n","flattenObject":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flattenObject( obj )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'depth': 1 } )\nvar bool = ( obj.a.b === out[ 'a.b' ] )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'delimiter': '-|-' } )\nobj = { 'a': { 'b': [ 1, 2, 3 ] } };\nout = flattenObject( obj, { 'flattenArrays': true } )\n","flattenObject.factory":"var flatten = flattenObject.factory({\n 'depth': 1,\n 'copy': true,\n 'delimiter': '|'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flatten( obj )\n","flignerTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = flignerTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = flignerTest( arr, { 'groups': groups } )\n","FLOAT_WORD_ORDER":"FLOAT_WORD_ORDER\n","FLOAT16_CBRT_EPS":"FLOAT16_CBRT_EPS\n","FLOAT16_EPS":"FLOAT16_EPS\n","FLOAT16_EXPONENT_BIAS":"FLOAT16_EXPONENT_BIAS\n","FLOAT16_MAX":"FLOAT16_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"FLOAT16_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"FLOAT16_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"FLOAT16_NINF\n","FLOAT16_NUM_BYTES":"FLOAT16_NUM_BYTES\n","FLOAT16_PINF":"FLOAT16_PINF\n","FLOAT16_PRECISION":"FLOAT16_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"FLOAT16_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"FLOAT16_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"FLOAT16_SQRT_EPS\n","FLOAT32_ABS_MASK":"FLOAT32_ABS_MASK\nbase.toBinaryStringUint32( FLOAT32_ABS_MASK )\n","FLOAT32_CBRT_EPS":"FLOAT32_CBRT_EPS\n","FLOAT32_E":"FLOAT32_E\n","FLOAT32_EPS":"FLOAT32_EPS\n","FLOAT32_EXPONENT_BIAS":"FLOAT32_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"FLOAT32_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n","FLOAT32_FOURTH_PI":"FLOAT32_FOURTH_PI\n","FLOAT32_HALF_LN_TWO":"FLOAT32_HALF_LN_TWO\n","FLOAT32_HALF_PI":"FLOAT32_HALF_PI\n","FLOAT32_LN_HALF":"FLOAT32_LN_HALF\n","FLOAT32_LN_PI":"FLOAT32_LN_PI\n","FLOAT32_LN_TEN":"FLOAT32_LN_TEN\n","FLOAT32_LN_TWO":"FLOAT32_LN_TWO\n","FLOAT32_MAX":"FLOAT32_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"FLOAT32_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"FLOAT32_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"FLOAT32_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"FLOAT32_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"FLOAT32_MAX_SAFE_NTH_FACTORIAL\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"FLOAT32_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"FLOAT32_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"FLOAT32_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"FLOAT32_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"FLOAT32_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"FLOAT32_NAN\n","FLOAT32_NINF":"FLOAT32_NINF\n","FLOAT32_NUM_BYTES":"FLOAT32_NUM_BYTES\n","FLOAT32_PHI":"FLOAT32_PHI\n","FLOAT32_PI":"FLOAT32_PI\n","FLOAT32_PINF":"FLOAT32_PINF\n","FLOAT32_PRECISION":"FLOAT32_PRECISION\n","FLOAT32_SIGN_MASK":"FLOAT32_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n","FLOAT32_SIGNIFICAND_MASK":"FLOAT32_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n","FLOAT32_SMALLEST_NORMAL":"FLOAT32_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"FLOAT32_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"FLOAT32_SQRT_EPS\n","FLOAT32_SQRT_HALF":"FLOAT32_SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"FLOAT32_SQRT_HALF_PI\n","FLOAT32_SQRT_PHI":"FLOAT32_SQRT_PHI\n","FLOAT32_SQRT_PI":"FLOAT32_SQRT_PI\n","FLOAT32_SQRT_THREE":"FLOAT32_SQRT_THREE\n","FLOAT32_SQRT_TWO":"FLOAT32_SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"FLOAT32_SQRT_TWO_PI\n","FLOAT32_TWO_PI":"FLOAT32_TWO_PI\n","Float32Array":"var arr = new Float32Array()\nvar arr = new Float32Array( 5 )\nvar arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float32Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Float32Array( buf, 0, 4 )\n","Float32Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float32Array.of":"var arr = Float32Array.of( 2.0, -2.0 )\n","Float32Array.BYTES_PER_ELEMENT":"Float32Array.BYTES_PER_ELEMENT\n","Float32Array.name":"Float32Array.name\n","Float32Array.prototype.buffer":"var arr = new Float32Array( 5 );\narr.buffer\n","Float32Array.prototype.byteLength":"var arr = new Float32Array( 5 );\narr.byteLength\n","Float32Array.prototype.byteOffset":"var arr = new Float32Array( 5 );\narr.byteOffset\n","Float32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float32Array.prototype.length":"var arr = new Float32Array( 5 );\narr.length\n","Float32Array.prototype.copyWithin":"var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float32Array.prototype.entries":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.every":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float32Array.prototype.fill":"var arr = new Float32Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float32Array.prototype.filter":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float32Array.prototype.find":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float32Array.prototype.findIndex":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float32Array.prototype.forEach":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float32Array.prototype.includes":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float32Array.prototype.indexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float32Array.prototype.join":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float32Array.prototype.keys":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.lastIndexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float32Array.prototype.map":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float32Array.prototype.reduce":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float32Array.prototype.reduceRight":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float32Array.prototype.reverse":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float32Array.prototype.set":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float32Array.prototype.slice":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float32Array.prototype.some":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float32Array.prototype.sort":"var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float32Array.prototype.subarray":"var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float32Array.prototype.toLocaleString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float32Array.prototype.toString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float32Array.prototype.values":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","FLOAT64_EXPONENT_BIAS":"FLOAT64_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"FLOAT64_HIGH_WORD_ABS_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"FLOAT64_HIGH_WORD_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n","FLOAT64_HIGH_WORD_SIGN_MASK":"FLOAT64_HIGH_WORD_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n","FLOAT64_MAX":"FLOAT64_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"FLOAT64_MAX_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"FLOAT64_MAX_SAFE_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MIN_BASE2_EXPONENT":"FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE10_EXPONENT":"FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"FLOAT64_MIN_LN\n","FLOAT64_MIN_SAFE_INTEGER":"FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"FLOAT64_NUM_BYTES\n","FLOAT64_PRECISION":"FLOAT64_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"FLOAT64_SMALLEST_NORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"FLOAT64_SMALLEST_SUBNORMAL\n","Float64Array":"var arr = new Float64Array()\nvar arr = new Float64Array( 5 )\nvar arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float64Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float64Array( arr1 )\nvar buf = new ArrayBuffer( 32 );\nvar arr = new Float64Array( buf, 0, 4 )\n","Float64Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float64Array.of":"var arr = Float64Array.of( 2.0, -2.0 )\n","Float64Array.BYTES_PER_ELEMENT":"Float64Array.BYTES_PER_ELEMENT\n","Float64Array.name":"Float64Array.name\n","Float64Array.prototype.buffer":"var arr = new Float64Array( 5 );\narr.buffer\n","Float64Array.prototype.byteLength":"var arr = new Float64Array( 5 );\narr.byteLength\n","Float64Array.prototype.byteOffset":"var arr = new Float64Array( 5 );\narr.byteOffset\n","Float64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float64Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float64Array.prototype.length":"var arr = new Float64Array( 5 );\narr.length\n","Float64Array.prototype.copyWithin":"var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float64Array.prototype.entries":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.every":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float64Array.prototype.fill":"var arr = new Float64Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float64Array.prototype.filter":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float64Array.prototype.find":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float64Array.prototype.findIndex":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float64Array.prototype.forEach":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float64Array.prototype.includes":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float64Array.prototype.indexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float64Array.prototype.join":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float64Array.prototype.keys":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.lastIndexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float64Array.prototype.map":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float64Array.prototype.reduce":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float64Array.prototype.reduceRight":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float64Array.prototype.reverse":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float64Array.prototype.set":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float64Array.prototype.slice":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float64Array.prototype.some":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float64Array.prototype.sort":"var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float64Array.prototype.subarray":"var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float64Array.prototype.toLocaleString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float64Array.prototype.toString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float64Array.prototype.values":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","forEach":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEach( arr, logger )\n","forEachAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n","forEachAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nforEachChar( 'hello world!', fcn );\nn\n","forEachRight":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEachRight( arr, logger )\n","forEachRightAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n","forEachRightAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachRightAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","forIn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nfunction Foo() { return this; };\nFoo.prototype.beep = 'boop';\nvar obj = new Foo();\nforIn( obj, logger )\n","format":"var out = format( 'Hello, %s!', 'World' )\nout = format( '%s %s', 'Hello', 'World' )\nout = format( 'Pi: %.2f', PI )\n","forOwn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nforOwn( obj, logger )\n","FOURTH_PI":"FOURTH_PI\n","FOURTH_ROOT_EPS":"FOURTH_ROOT_EPS\n","FRB_SF_WAGE_RIGIDITY":"var data = FRB_SF_WAGE_RIGIDITY()\n","fromCodePoint":"var out = fromCodePoint( 9731 )\nout = fromCodePoint( [ 9731 ] )\nout = fromCodePoint( 97, 98, 99 )\nout = fromCodePoint( [ 97, 98, 99 ] )\n","Function":"var f = new Function( 'x', 'y', 'return x + y' );\nf( 1, 2 )\n","Function.prototype.apply":"var f = new Function( 'x', 'y', 'return x + y' );\nf.apply( null, [ 1, 2 ] )\n","Function.prototype.call":"var f = new Function( 'x', 'y', 'return x + y' );\nf.call( null, 1, 2 )\n","Function.prototype.bind":"var f = new Function( 'x', 'y', 'return x + y' );\nvar g = f.bind( null, 1 );\ng( 2 )\n","Function.prototype.toString":"var f = new Function( 'x', 'y', 'return x + y' );\nf.toString()\n","Function.prototype.length":"var f = new Function( 'x', 'y', 'return x + y' );\nf.length\n","Function.prototype.name":"var f = new Function( 'x', 'y', 'return x + y' );\nf.name\nvar f = new Function( 'x', 'y', 'return x + y' );\nf.name = 'add';\nf.name\n","Function.prototype.prototype":"var f = new Function( 'x', 'y', 'return x + y' );\nf.prototype\n","function2string":"function2string( base.erf )\n","functionName":"var v = functionName( String )\nv = functionName( function foo(){} )\nv = functionName( function(){} )\n","functionSequence":"function a( x ) { return 2 * x; };\nfunction b( x ) { return x + 3; };\nfunction c( x ) { return x / 5; };\nvar f = functionSequence( a, b, c );\nvar z = f( 6 )\n","functionSequenceAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x/5 );\n}\n };\nvar f = functionSequenceAsync( a, b, c );\nfunction done( error, result ) {\nif ( error ) {\n throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","GAMMA_LANCZOS_G":"GAMMA_LANCZOS_G\n","gdot":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngdot( x, y )\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngdot( x, y )\n","getegid":"var gid = getegid()\n","geteuid":"var uid = geteuid()\n","getgid":"var gid = getgid()\n","getGlobal":"var g = getGlobal()\n","getPrototypeOf":"var proto = getPrototypeOf( {} )\n","getuid":"var uid = getuid()\n","GLAISHER":"GLAISHER\n","graphemeClusters2iterator":"var it = graphemeClusters2iterator( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","graphemeClusters2iteratorRight":"var it = graphemeClusters2iteratorRight( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","group":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar groups = [ 'b', 'b', 'f', 'b' ];\nvar out = group( collection, groups )\ngroups = [ 1, 1, 2, 1 ];\nout = group( collection, groups )\ngroups = [ 'b', 'b', 'f', 'b' ];\nvar opts = { 'returns': 'indices' };\nout = group( collection, opts, groups )\nopts = { 'returns': '*' };\nout = group( collection, opts, groups )\n","groupBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = groupBy( collection, indicator )\nvar opts = { 'returns': 'indices' };\nout = groupBy( collection, opts, indicator )\nopts = { 'returns': '*' };\nout = groupBy( collection, opts, indicator )\n","groupByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, indicator, done )\nvar opts = { 'returns': 'indices' };\ngroupByAsync( arr, opts, indicator, done )\nopts = { 'returns': '*' };\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n","groupByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = groupByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","groupIn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nfunction Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nvar out = groupIn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupIn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupIn( obj, opts, indicator )\n","groupOwn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = groupOwn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupOwn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupOwn( obj, opts, indicator )\n","gswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngswap( x, y );\nx.data\ny.data\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngswap( x, y );\nx\ny\n","HALF_LN2":"HALF_LN2\n","HALF_PI":"HALF_PI\n","HARRISON_BOSTON_HOUSE_PRICES":"var data = HARRISON_BOSTON_HOUSE_PRICES()\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n","hasArrayBufferSupport":"var bool = hasArrayBufferSupport()\n","hasArrowFunctionSupport":"var bool = hasArrowFunctionSupport()\n","hasAsyncAwaitSupport":"var bool = hasAsyncAwaitSupport()\n","hasAsyncIteratorSymbolSupport":"var bool = hasAsyncIteratorSymbolSupport()\n","hasAtobSupport":"var bool = hasAtobSupport()\n","hasBigInt64ArraySupport":"var bool = hasBigInt64ArraySupport()\n","hasBigIntSupport":"var bool = hasBigIntSupport()\n","hasBigUint64ArraySupport":"var bool = hasBigUint64ArraySupport()\n","hasBtoaSupport":"var bool = hasBtoaSupport()\n","hasClassSupport":"var bool = hasClassSupport()\n","hasDataViewSupport":"var bool = hasDataViewSupport()\n","hasDefinePropertiesSupport":"var bool = hasDefinePropertiesSupport()\n","hasDefinePropertySupport":"var bool = hasDefinePropertySupport()\n","hasFloat32ArraySupport":"var bool = hasFloat32ArraySupport()\n","hasFloat64ArraySupport":"var bool = hasFloat64ArraySupport()\n","hasFunctionNameSupport":"var bool = hasFunctionNameSupport()\n","hasGeneratorSupport":"var bool = hasGeneratorSupport()\n","hasGlobalThisSupport":"var bool = hasGlobalThisSupport()\n","hasInt8ArraySupport":"var bool = hasInt8ArraySupport()\n","hasInt16ArraySupport":"var bool = hasInt16ArraySupport()\n","hasInt32ArraySupport":"var bool = hasInt32ArraySupport()\n","hasIteratorSymbolSupport":"var bool = hasIteratorSymbolSupport()\n","hasMapSupport":"var bool = hasMapSupport()\n","hasNodeBufferSupport":"var bool = hasNodeBufferSupport()\n","hasOwnProp":"var beep = { 'boop': true };\nvar bool = hasOwnProp( beep, 'boop' )\nbool = hasOwnProp( beep, 'bop' )\n","hasProp":"var beep = { 'boop': true };\nvar bool = hasProp( beep, 'boop' )\nbool = hasProp( beep, 'toString' )\nbool = hasProp( beep, 'bop' )\n","hasProxySupport":"var bool = hasProxySupport()\n","hasSetSupport":"var bool = hasSetSupport()\n","hasSharedArrayBufferSupport":"var bool = hasSharedArrayBufferSupport()\n","hasSymbolSupport":"var bool = hasSymbolSupport()\n","hasToStringTagSupport":"var bool = hasToStringTagSupport()\n","hasUint8ArraySupport":"var bool = hasUint8ArraySupport()\n","hasUint8ClampedArraySupport":"var bool = hasUint8ClampedArraySupport()\n","hasUint16ArraySupport":"var bool = hasUint16ArraySupport()\n","hasUint32ArraySupport":"var bool = hasUint32ArraySupport()\n","hasUTF16SurrogatePairAt":"var out = hasUTF16SurrogatePairAt( '🌷', 0 )\nout = hasUTF16SurrogatePairAt( '🌷', 1 )\n","hasWeakMapSupport":"var bool = hasWeakMapSupport()\n","hasWeakSetSupport":"var bool = hasWeakSetSupport()\n","hasWebAssemblySupport":"var bool = hasWebAssemblySupport()\n","headercase":"var out = headercase( 'Hello World!' )\nout = headercase( 'beep boop' )\n","HERNDON_VENUS_SEMIDIAMETERS":"var d = HERNDON_VENUS_SEMIDIAMETERS()\n","homedir":"var home = homedir()\n","HOURS_IN_DAY":"var days = 3.14;\nvar hrs = days * HOURS_IN_DAY\n","HOURS_IN_WEEK":"var wks = 3.14;\nvar hrs = wks * HOURS_IN_WEEK\n","hoursInMonth":"var num = hoursInMonth()\nnum = hoursInMonth( 2 )\nnum = hoursInMonth( 2, 2016 )\nnum = hoursInMonth( 2, 2017 )\nnum = hoursInMonth( 'feb', 2016 )\nnum = hoursInMonth( 'february', 2016 )\n","hoursInYear":"var num = hoursInYear()\nnum = hoursInYear( 2016 )\nnum = hoursInYear( 2017 )\n","httpServerFactory":"var boot = httpServerFactory()\nfunction onRequest( request, response ) {\nconsole.log( request.url );\nresponse.end( 'OK' );\n };\nboot = httpServerFactory( onRequest )\nvar opts = { 'port': 7331 };\nboot = httpServerFactory( opts )\n","identity":"var v = identity( 3.14 )\n","ifelse":"var z = ifelse( true, 1.0, -1.0 )\nz = ifelse( false, 1.0, -1.0 )\n","ifelseAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, true );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nifelseAsync( predicate, 'beep', 'boop', done )\n","ifthen":"function x() { return 1.0; };\nfunction y() { return -1.0; };\nvar z = ifthen( true, x, y )\nz = ifthen( false, x, y )\n","ifthenAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, false );\n }\n };\nfunction x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'beep' );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nifthenAsync( predicate, x, y, done )\n","imag":"var z = new Complex128( 5.0, 3.0 );\nvar im = imag( z )\n","imagf":"var z = new Complex64( 5.0, 3.0 );\nvar im = imagf( z )\n","IMG_ACANTHUS_MOLLIS":"var img = IMG_ACANTHUS_MOLLIS()\n","IMG_AIRPLANE_FROM_ABOVE":"var img = IMG_AIRPLANE_FROM_ABOVE()\n","IMG_ALLIUM_OREOPHILUM":"var img = IMG_ALLIUM_OREOPHILUM()\n","IMG_BLACK_CANYON":"var img = IMG_BLACK_CANYON()\n","IMG_DUST_BOWL_HOME":"var img = IMG_DUST_BOWL_HOME()\n","IMG_FRENCH_ALPINE_LANDSCAPE":"var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n","IMG_LOCOMOTION_HOUSE_CAT":"var img = IMG_LOCOMOTION_HOUSE_CAT()\n","IMG_LOCOMOTION_NUDE_MALE":"var img = IMG_LOCOMOTION_NUDE_MALE()\n","IMG_MARCH_PASTORAL":"var img = IMG_MARCH_PASTORAL()\n","IMG_NAGASAKI_BOATS":"var img = IMG_NAGASAKI_BOATS()\n","incrapcorr":"var accumulator = incrapcorr();\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator()\n","incrBinaryClassification":"var opts = {};\nopts.intercept = true;\nopts.lambda = 1.0e-5;\nvar acc = incrBinaryClassification( 3, opts );\nvar buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\nvar x = array( buf );\nvar coefs = acc( x, 1 )\nbuf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\nx = array( buf );\nvar yhat = acc.predict( x )\n","incrcount":"var accumulator = incrcount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrcovariance":"var accumulator = incrcovariance();\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator()\n","incrcovmat":"var accumulator = incrcovmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrcv":"var accumulator = incrcv();\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator()\n","increwmean":"var accumulator = increwmean( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","increwstdev":"var accumulator = increwstdev( 0.5 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","increwvariance":"var accumulator = increwvariance( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrgmean":"var accumulator = incrgmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrgrubbs":"var acc = incrgrubbs();\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrhmean":"var accumulator = incrhmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrkmeans":"var accumulator = incrkmeans( 5, 2 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v );\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v );\n","incrkurtosis":"var accumulator = incrkurtosis();\nvar v = accumulator( 2.0 )\nv = accumulator( 2.0 )\nv = accumulator( -4.0 )\nv = accumulator( -4.0 )\n","incrmaape":"var accumulator = incrmaape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmae":"var accumulator = incrmae();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmapcorr":"var accumulator = incrmapcorr( 3 );\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator( 3.0, -1.0 )\nar = accumulator( 5.0, -9.5 )\nar = accumulator()\n","incrmape":"var accumulator = incrmape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmax":"var accumulator = incrmax();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmaxabs":"var accumulator = incrmaxabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmcovariance":"var accumulator = incrmcovariance( 3 );\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator( 3.0, -1.0 )\nv = accumulator( 5.0, -9.5 )\nv = accumulator()\n","incrmcv":"var accumulator = incrmcv( 3 );\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator( 3.0 )\ncv = accumulator( 7.0 )\ncv = accumulator()\n","incrmda":"var accumulator = incrmda();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 4.0 )\nm = accumulator()\n","incrme":"var accumulator = incrme();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmean":"var accumulator = incrmean();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs":"var accumulator = incrmeanabs();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs2":"var accumulator = incrmeanabs2();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanstdev":"var accumulator = incrmeanstdev();\nvar ms = accumulator()\nms = accumulator( 2.0 )\nms = accumulator( -5.0 )\nms = accumulator( 3.0 )\nms = accumulator( 5.0 )\nms = accumulator()\n","incrmeanvar":"var accumulator = incrmeanvar();\nvar mv = accumulator()\nmv = accumulator( 2.0 )\nmv = accumulator( -5.0 )\nmv = accumulator( 3.0 )\nmv = accumulator( 5.0 )\nmv = accumulator()\n","incrmgmean":"var accumulator = incrmgmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmgrubbs":"var acc = incrmgrubbs( 20 );\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrmhmean":"var accumulator = incrmhmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmidrange":"var accumulator = incrmidrange();\nvar v = accumulator()\nv = accumulator( 3.14 )\nv = accumulator( -5.0 )\nv = accumulator( 10.1 )\nv = accumulator()\n","incrmin":"var accumulator = incrmin();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminabs":"var accumulator = incrminabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminmax":"var accumulator = incrminmax();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrminmaxabs":"var accumulator = incrminmaxabs();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmaape":"var accumulator = incrmmaape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmae":"var accumulator = incrmmae( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmape":"var accumulator = incrmmape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmax":"var accumulator = incrmmax( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmaxabs":"var accumulator = incrmmaxabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmda":"var accumulator = incrmmda( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 4.0, 5.0 )\nm = accumulator()\n","incrmme":"var accumulator = incrmme( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmean":"var accumulator = incrmmean( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs":"var accumulator = incrmmeanabs( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs2":"var accumulator = incrmmeanabs2( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmeanstdev":"var accumulator = incrmmeanstdev( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmeanvar":"var accumulator = incrmmeanvar( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmidrange":"var accumulator = incrmmidrange( 3 );\nvar mr = accumulator()\nmr = accumulator( 2.0 )\nmr = accumulator( -5.0 )\nmr = accumulator( 3.0 )\nmr = accumulator( 5.0 )\nmr = accumulator()\n","incrmmin":"var accumulator = incrmmin( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminabs":"var accumulator = incrmminabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminmax":"var accumulator = incrmminmax( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmminmaxabs":"var accumulator = incrmminmaxabs( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmpe":"var accumulator = incrmmpe( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmse":"var accumulator = incrmmse( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmpcorr":"var accumulator = incrmpcorr( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator( 3.0, -1.0 )\nr = accumulator( 5.0, -9.5 )\nr = accumulator()\n","incrmpcorr2":"var accumulator = incrmpcorr2( 3 );\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator( 3.0, -1.0 )\nr2 = accumulator( 5.0, -9.5 )\nr2 = accumulator()\n","incrmpcorrdist":"var accumulator = incrmpcorrdist( 3 );\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator( 3.0, -1.0 )\nd = accumulator( 5.0, -9.5 )\nd = accumulator()\n","incrmpe":"var accumulator = incrmpe();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmprod":"var accumulator = incrmprod( 3 );\nvar p = accumulator()\np = accumulator( 2.0 )\np = accumulator( -5.0 )\np = accumulator( 3.0 )\np = accumulator( 5.0 )\np = accumulator()\n","incrmrange":"var accumulator = incrmrange( 3 );\nvar r = accumulator()\nr = accumulator( 2.0 )\nr = accumulator( -5.0 )\nr = accumulator( 3.0 )\nr = accumulator( 5.0 )\nr = accumulator()\n","incrmrmse":"var accumulator = incrmrmse( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmrss":"var accumulator = incrmrss( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmse":"var accumulator = incrmse();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmstdev":"var accumulator = incrmstdev( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsum":"var accumulator = incrmsum( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsumabs":"var accumulator = incrmsumabs( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumabs2":"var accumulator = incrmsumabs2( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsummary":"var accumulator = incrmsummary( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumprod":"var accumulator = incrmsumprod( 3 );\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator( 3.0, -2.0 )\ns = accumulator( 5.0, 3.0 )\ns = accumulator()\n","incrmvariance":"var accumulator = incrmvariance( 3 );\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator( 3.0 )\ns2 = accumulator( 5.0 )\ns2 = accumulator()\n","incrmvmr":"var accumulator = incrmvmr( 3 );\nvar F = accumulator()\nF = accumulator( 2.0 )\nF = accumulator( 1.0 )\nF = accumulator( 3.0 )\nF = accumulator( 7.0 )\nF = accumulator()\n","incrnancount":"var accumulator = incrnancount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrnansum":"var accumulator = incrnansum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs":"var accumulator = incrnansumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs2":"var accumulator = incrnansumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrpcorr":"var accumulator = incrpcorr();\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator()\n","incrpcorr2":"var accumulator = incrpcorr2();\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator()\n","incrpcorrdist":"var accumulator = incrpcorrdist();\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator()\n","incrpcorrdistmat":"var accumulator = incrpcorrdistmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrpcorrmat":"var accumulator = incrpcorrmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrprod":"var accumulator = incrprod();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrrange":"var accumulator = incrrange();\nvar v = accumulator()\nv = accumulator( -2.0 )\nv = accumulator( 1.0 )\nv = accumulator( 3.0 )\nv = accumulator()\n","incrrmse":"var accumulator = incrrmse();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrrss":"var accumulator = incrrss();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrskewness":"var accumulator = incrskewness();\nvar v = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( -10.0 )\nv = accumulator()\n","incrspace":"var arr = incrspace( 0, 11, 2 )\n","incrstdev":"var accumulator = incrstdev();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsum":"var accumulator = incrsum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs":"var accumulator = incrsumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs2":"var accumulator = incrsumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsummary":"var accumulator = incrsummary();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumprod":"var accumulator = incrsumprod();\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator()\n","incrvariance":"var accumulator = incrvariance();\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator()\n","incrvmr":"var accumulator = incrvmr();\nvar D = accumulator()\nD = accumulator( 2.0 )\nD = accumulator( 1.0 )\nD = accumulator()\n","incrwmean":"var accumulator = incrwmean();\nvar mu = accumulator()\nmu = accumulator( 2.0, 1.0 )\nmu = accumulator( 2.0, 0.5 )\nmu = accumulator( 3.0, 1.5 )\nmu = accumulator()\n","ind2sub":"var d = [ 3, 3, 3 ];\nvar s = ind2sub( d, 17 )\n","ind2sub.assign":"var d = [ 3, 3, 3 ];\nvar out = [ 0, 0, 0 ];\nvar s = ind2sub.assign( d, 17, out )\nvar bool = ( s === out )\n","indexOf":"var arr = [ 4, 3, 2, 1 ];\nvar idx = indexOf( arr, 3 )\narr = [ 4, 3, 2, 1 ];\nidx = indexOf( arr, 5 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, 3 )\narr = [ 1, 2, 3, 4, 2, 5 ];\nidx = indexOf( arr, 2, 10 )\narr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\nidx = indexOf( arr, 2, -4 )\nidx = indexOf( arr, 2, -1 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, -10 )\nvar str = 'bebop';\nidx = indexOf( str, 'o' )\n","inherit":"function Foo() { return this; };\nFoo.prototype.beep = function beep() { return 'boop'; };\nfunction Bar() { Foo.call( this ); return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar v = bar.beep()\n","inheritedEnumerableProperties":"var props = inheritedEnumerableProperties( {} )\n","inheritedEnumerablePropertySymbols":"var symbols = inheritedEnumerablePropertySymbols( [] )\n","inheritedKeys":"var keys = inheritedKeys( {} )\n","inheritedNonEnumerableProperties":"var props = inheritedNonEnumerableProperties( {} )\n","inheritedNonEnumerablePropertyNames":"var keys = inheritedNonEnumerablePropertyNames( {} )\n","inheritedNonEnumerablePropertySymbols":"var symbols = inheritedNonEnumerablePropertySymbols( [] )\n","inheritedProperties":"var symbols = inheritedProperties( [] )\n","inheritedPropertyDescriptor":"var desc = inheritedPropertyDescriptor( {}, 'toString' )\n","inheritedPropertyDescriptors":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = inheritedPropertyDescriptors( obj )\n","inheritedPropertyNames":"var keys = inheritedPropertyNames( [] )\n","inheritedPropertySymbols":"var symbols = inheritedPropertySymbols( [] )\n","inheritedWritableProperties":"var props = inheritedWritableProperties( {} )\n","inheritedWritablePropertyNames":"var keys = inheritedWritablePropertyNames( {} )\n","inheritedWritablePropertySymbols":"var symbols = inheritedWritablePropertySymbols( [] )\n","inmap":"function foo( v, i ) { return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmap( arr, foo )\nvar bool = ( out === arr )\n","inmapAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n","inmapAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","inmapRight":"function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmapRight( arr, foo )\nvar bool = ( out === arr )\n","inmapRightAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n","inmapRightAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapRightAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","inspectSinkStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectSinkStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","inspectStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","instanceOf":"var bool = instanceOf( [], Array )\nbool = instanceOf( {}, Object )\nbool = instanceOf( null, Object )\n","INT8_MAX":"INT8_MAX\n","INT8_MIN":"INT8_MIN\n","INT8_NUM_BYTES":"INT8_NUM_BYTES\n","Int8Array":"var arr = new Int8Array()\nvar arr = new Int8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Int8Array( buf, 0, 4 )\n","Int8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int8Array.from( [ 1, 2 ], mapFcn )\n","Int8Array.of":"var arr = Int8Array.of( 1, 2 )\n","Int8Array.BYTES_PER_ELEMENT":"Int8Array.BYTES_PER_ELEMENT\n","Int8Array.name":"Int8Array.name\n","Int8Array.prototype.buffer":"var arr = new Int8Array( 5 );\narr.buffer\n","Int8Array.prototype.byteLength":"var arr = new Int8Array( 5 );\narr.byteLength\n","Int8Array.prototype.byteOffset":"var arr = new Int8Array( 5 );\narr.byteOffset\n","Int8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int8Array.prototype.length":"var arr = new Int8Array( 5 );\narr.length\n","Int8Array.prototype.copyWithin":"var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int8Array.prototype.entries":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.every":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int8Array.prototype.fill":"var arr = new Int8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int8Array.prototype.filter":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int8Array.prototype.find":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int8Array.prototype.findIndex":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int8Array.prototype.forEach":"var arr = new Int8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int8Array.prototype.includes":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int8Array.prototype.indexOf":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int8Array.prototype.join":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int8Array.prototype.keys":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.lastIndexOf":"var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int8Array.prototype.map":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int8Array.prototype.reduce":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int8Array.prototype.reduceRight":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int8Array.prototype.reverse":"var arr = new Int8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int8Array.prototype.set":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int8Array.prototype.slice":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int8Array.prototype.some":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int8Array.prototype.sort":"var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int8Array.prototype.subarray":"var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int8Array.prototype.toLocaleString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int8Array.prototype.toString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toString()\n","Int8Array.prototype.values":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT16_MAX":"INT16_MAX\n","INT16_MIN":"INT16_MIN\n","INT16_NUM_BYTES":"INT16_NUM_BYTES\n","Int16Array":"var arr = new Int16Array()\nvar arr = new Int16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Int16Array( buf, 0, 4 )\n","Int16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int16Array.from( [ 1, 2 ], mapFcn )\n","Int16Array.of":"var arr = Int16Array.of( 1, 2 )\n","Int16Array.BYTES_PER_ELEMENT":"Int16Array.BYTES_PER_ELEMENT\n","Int16Array.name":"Int16Array.name\n","Int16Array.prototype.buffer":"var arr = new Int16Array( 5 );\narr.buffer\n","Int16Array.prototype.byteLength":"var arr = new Int16Array( 5 );\narr.byteLength\n","Int16Array.prototype.byteOffset":"var arr = new Int16Array( 5 );\narr.byteOffset\n","Int16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int16Array.prototype.length":"var arr = new Int16Array( 5 );\narr.length\n","Int16Array.prototype.copyWithin":"var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int16Array.prototype.entries":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.every":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int16Array.prototype.fill":"var arr = new Int16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int16Array.prototype.filter":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int16Array.prototype.find":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int16Array.prototype.findIndex":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int16Array.prototype.forEach":"var arr = new Int16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int16Array.prototype.includes":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int16Array.prototype.indexOf":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int16Array.prototype.join":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int16Array.prototype.keys":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.lastIndexOf":"var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int16Array.prototype.map":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int16Array.prototype.reduce":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int16Array.prototype.reduceRight":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int16Array.prototype.reverse":"var arr = new Int16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int16Array.prototype.set":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int16Array.prototype.slice":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int16Array.prototype.some":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int16Array.prototype.sort":"var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int16Array.prototype.subarray":"var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int16Array.prototype.toLocaleString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int16Array.prototype.toString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toString()\n","Int16Array.prototype.values":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT32_MAX":"INT32_MAX\n","INT32_MIN":"INT32_MIN\n","INT32_NUM_BYTES":"INT32_NUM_BYTES\n","Int32Array":"var arr = new Int32Array()\nvar arr = new Int32Array( 5 )\nvar arr1 = new Int16Array( [ 5, 5, 5 ] );\nvar arr2 = new Int32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Int32Array( buf, 0, 4 )\n","Int32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int32Array.from( [ 1, 2 ], mapFcn )\n","Int32Array.of":"var arr = Int32Array.of( 1, 2 )\n","Int32Array.BYTES_PER_ELEMENT":"Int32Array.BYTES_PER_ELEMENT\n","Int32Array.name":"Int32Array.name\n","Int32Array.prototype.buffer":"var arr = new Int32Array( 5 );\narr.buffer\n","Int32Array.prototype.byteLength":"var arr = new Int32Array( 5 );\narr.byteLength\n","Int32Array.prototype.byteOffset":"var arr = new Int32Array( 5 );\narr.byteOffset\n","Int32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int32Array.prototype.length":"var arr = new Int32Array( 5 );\narr.length\n","Int32Array.prototype.copyWithin":"var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int32Array.prototype.entries":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.every":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int32Array.prototype.fill":"var arr = new Int32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int32Array.prototype.filter":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int32Array.prototype.find":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int32Array.prototype.findIndex":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int32Array.prototype.forEach":"var arr = new Int32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int32Array.prototype.includes":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int32Array.prototype.indexOf":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int32Array.prototype.join":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int32Array.prototype.keys":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.lastIndexOf":"var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int32Array.prototype.map":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int32Array.prototype.reduce":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int32Array.prototype.reduceRight":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int32Array.prototype.reverse":"var arr = new Int32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int32Array.prototype.set":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int32Array.prototype.slice":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int32Array.prototype.some":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int32Array.prototype.sort":"var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int32Array.prototype.subarray":"var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int32Array.prototype.toLocaleString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int32Array.prototype.toString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toString()\n","Int32Array.prototype.values":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","IS_BIG_ENDIAN":"IS_BIG_ENDIAN\n","IS_BROWSER":"IS_BROWSER\n","IS_DARWIN":"IS_DARWIN\n","IS_DOCKER":"IS_DOCKER\n","IS_ELECTRON":"IS_ELECTRON\n","IS_ELECTRON_MAIN":"IS_ELECTRON_MAIN\n","IS_ELECTRON_RENDERER":"IS_ELECTRON_RENDERER\n","IS_LITTLE_ENDIAN":"IS_LITTLE_ENDIAN\n","IS_MOBILE":"IS_MOBILE\n","IS_NODE":"IS_NODE\n","IS_TOUCH_DEVICE":"IS_TOUCH_DEVICE\n","IS_WEB_WORKER":"IS_WEB_WORKER\n","IS_WINDOWS":"IS_WINDOWS\n","isAbsoluteHttpURI":"var bool = isAbsoluteHttpURI( 'http://example.com/' )\nbool = isAbsoluteHttpURI( 'example.com' )\nbool = isAbsoluteHttpURI( 'foo@bar.com' )\n","isAbsolutePath":"var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath( '/foo/bar/baz' )\n","isAbsolutePath.posix":"var bool = isAbsolutePath.posix( '/foo/bar/baz' )\nbool = isAbsolutePath.posix( 'foo/bar/baz' )\n","isAbsolutePath.win32":"var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n","isAbsoluteURI":"var bool = isAbsoluteURI( 'http://example.com/' )\nbool = isAbsoluteURI( 'example.com' )\nbool = isAbsoluteURI( 'foo@bar.com' )\n","isAccessorArray":"var bool = isAccessorArray( new Complex64Array( 10 ) )\nbool = isAccessorArray( [] )\nbool = isAccessorArray( { 'length': 0 } )\nbool = isAccessorArray( {} )\n","isAccessorProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorProperty( obj, 'boop' )\nbool = isAccessorProperty( obj, 'beep' )\n","isAccessorPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorPropertyIn( obj, 'boop' )\nbool = isAccessorPropertyIn( obj, 'beep' )\n","isAlphagram":"var out = isAlphagram( 'beep' )\nout = isAlphagram( 'zba' )\nout = isAlphagram( '' )\n","isAlphaNumeric":"var bool = isAlphaNumeric( 'abc0123456789' )\nbool = isAlphaNumeric( 'abcdef' )\nbool = isAlphaNumeric( '0xff' )\nbool = isAlphaNumeric( '' )\n","isAnagram":"var str1 = 'I am a weakish speller';\nvar str2 = 'William Shakespeare';\nvar bool = isAnagram( str1, str2 )\nbool = isAnagram( 'bat', 'tabba' )\n","isArguments":"function foo() { return arguments; };\nvar bool = isArguments( foo() )\nbool = isArguments( [] )\n","isArray":"var bool = isArray( [] )\nbool = isArray( {} )\n","isArrayArray":"var bool = isArrayArray( [ [], [] ] )\nbool = isArrayArray( [ {}, {} ] )\nbool = isArrayArray( [] )\n","isArrayBuffer":"var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\nbool = isArrayBuffer( [] )\n","isArrayBufferView":"var bool = isArrayBufferView( new Int8Array() )\nbool = isArrayBufferView( [] )\n","isArrayLength":"var bool = isArrayLength( 5 )\nbool = isArrayLength( 2.0e200 )\nbool = isArrayLength( -3.14 )\nbool = isArrayLength( null )\n","isArrayLike":"var bool = isArrayLike( [] )\nbool = isArrayLike( { 'length': 10 } )\nbool = isArrayLike( 'beep' )\nbool = isArrayLike( null )\n","isArrayLikeObject":"var bool = isArrayLikeObject( [] )\nbool = isArrayLikeObject( { 'length': 10 } )\nbool = isArrayLikeObject( 'beep' )\n","isArrowFunction":"function beep() {};\nvar bool = isArrowFunction( beep )\nbool = isArrowFunction( {} )\n","isASCII":"var str = 'beep boop';\nvar bool = isASCII( str )\nbool = isASCII( fromCodePoint( 130 ) )\n","isBetween":"var bool = isBetween( 3.14, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.0, 4.0 )\nbool = isBetween( 4.0, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.14, 4.0 )\nbool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\nbool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n","isBetweenArray":"var arr = [ 3.0, 3.14, 4.0 ];\nvar bool = isBetweenArray( arr, 3.0, 4.0 )\nbool = isBetweenArray( arr, 3.14, 4.0 )\nbool = isBetweenArray( arr, 3.0, 3.14 )\nbool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\nbool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n","isBigInt":"var bool = isBigInt( BigInt( '1' ) )\nbool = isBigInt( Object( BigInt( '1' ) ) )\nbool = isBigInt( {} )\nbool = isBigInt( null )\nbool = isBigInt( true )\n","isBigInt64Array":"var bool = isBigInt64Array( new BigInt64Array( 10 ) )\nbool = isBigInt64Array( [] )\n","isBigUint64Array":"var bool = isBigUint64Array( new BigUint64Array( 10 ) )\nbool = isBigUint64Array( [] )\n","isBinaryString":"var bool = isBinaryString( '1000101' )\nbool = isBinaryString( 'beep' )\nbool = isBinaryString( '' )\n","isBlankString":"var bool = isBlankString( ' ' )\nbool = isBlankString( 'beep' )\nbool = isBlankString( null )\n","isBoolean":"var bool = isBoolean( false )\nbool = isBoolean( new Boolean( false ) )\n","isBoolean.isPrimitive":"var bool = isBoolean.isPrimitive( true )\nbool = isBoolean.isPrimitive( false )\nbool = isBoolean.isPrimitive( new Boolean( true ) )\n","isBoolean.isObject":"var bool = isBoolean.isObject( true )\nbool = isBoolean.isObject( new Boolean( false ) )\n","isBooleanArray":"var bool = isBooleanArray( [ true, false, true ] )\nbool = isBooleanArray( [ true, 'abc', false ] )\n","isBooleanArray.primitives":"var bool = isBooleanArray.primitives( [ true, false ] )\nbool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n","isBooleanArray.objects":"var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\nbool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n","isBoxedPrimitive":"var bool = isBoxedPrimitive( new Boolean( false ) )\nbool = isBoxedPrimitive( true )\n","isBuffer":"var bool = isBuffer( new Buffer( 'beep' ) )\nbool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\nbool = isBuffer( {} )\nbool = isBuffer( [] )\n","isCamelcase":"var bool = isCamelcase( 'helloWorld' )\nbool = isCamelcase( 'hello world' )\n","isCapitalized":"var bool = isCapitalized( 'Hello' )\nbool = isCapitalized( 'world' )\n","isCentrosymmetricMatrix":"var buf = [ 2, 1, 1, 2 ];\nvar M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isCentrosymmetricMatrix( M )\nbool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isCentrosymmetricMatrix( 3.14 )\nbool = isCentrosymmetricMatrix( {} )\n","isCircular":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircular( obj )\nbool = isCircular( {} )\nbool = isCircular( null )\n","isCircularArray":"var arr = [ 1, 2, 3 ];\narr.push( arr );\nvar bool = isCircularArray( arr )\nbool = isCircularArray( [] )\nbool = isCircularArray( null )\n","isCircularPlainObject":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircularPlainObject( obj )\nbool = isCircularPlainObject( {} )\nbool = isCircularPlainObject( null )\n","isClass":"var bool = isClass( class Person {} )\nbool = isClass( function Person() {} )\nbool = isClass( {} )\nbool = isClass( null )\nbool = isClass( true )\n","isCollection":"var bool = isCollection( [] )\nbool = isCollection( { 'length': 0 } )\nbool = isCollection( {} )\n","isComplex":"var bool = isComplex( new Complex64( 2.0, 2.0 ) )\nbool = isComplex( new Complex128( 3.0, 1.0 ) )\nbool = isComplex( 3.14 )\nbool = isComplex( {} )\n","isComplex64":"var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\nbool = isComplex64( new Complex128( 3.0, 1.0 ) )\nbool = isComplex64( 3.14 )\nbool = isComplex64( {} )\n","isComplex64Array":"var bool = isComplex64Array( new Complex64Array( 10 ) )\nbool = isComplex64Array( [] )\n","isComplex64MatrixLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64MatrixLike( M )\nbool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64MatrixLike( 3.14 )\nbool = isComplex64MatrixLike( {} )\n","isComplex64ndarrayLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64ndarrayLike( M )\nbool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64ndarrayLike( 3.14 )\nbool = isComplex64ndarrayLike( {} )\n","isComplex64VectorLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64VectorLike( M )\nbool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64VectorLike( 3.14 )\nbool = isComplex64VectorLike( {} )\n","isComplex128":"var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\nbool = isComplex128( new Complex64( 2.0, 2.0 ) )\nbool = isComplex128( 3.14 )\nbool = isComplex128( {} )\n","isComplex128Array":"var bool = isComplex128Array( new Complex128Array( 10 ) )\nbool = isComplex128Array( [] )\n","isComplex128MatrixLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128MatrixLike( M )\nbool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128MatrixLike( 3.14 )\nbool = isComplex128MatrixLike( {} )\n","isComplex128ndarrayLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128ndarrayLike( M )\nbool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128ndarrayLike( 3.14 )\nbool = isComplex128ndarrayLike( {} )\n","isComplex128VectorLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128VectorLike( M )\nbool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128VectorLike( 3.14 )\nbool = isComplex128VectorLike( {} )\n","isComplexLike":"var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\nbool = isComplexLike( new Complex128( 3.0, 1.0 ) )\nbool = isComplexLike( 3.14 )\nbool = isComplexLike( {} )\n","isComplexTypedArray":"var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n","isComplexTypedArrayLike":"var bool = isComplexTypedArrayLike( new Complex128Array() )\nbool = isComplexTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4,\n'get': function get() {},\n'set': function set() {}\n })\n","isComposite":"var bool = isComposite( 4.0 )\nbool = isComposite( new Number( 4.0 ) )\nbool = isComposite( 3.14 )\nbool = isComposite( -4.0 )\nbool = isComposite( null )\n","isComposite.isPrimitive":"var bool = isComposite.isPrimitive( 4.0 )\nbool = isComposite.isPrimitive( new Number( 4.0 ) )\n","isComposite.isObject":"var bool = isComposite.isObject( 4.0 )\nbool = isComposite.isObject( new Number( 4.0 ) )\n","isConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurableProperty( obj, 'boop' )\nbool = isConfigurableProperty( obj, 'beep' )\n","isConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurablePropertyIn( obj, 'boop' )\nbool = isConfigurablePropertyIn( obj, 'beep' )\n","isConstantcase":"var bool = isConstantcase( 'BEEP_BOOP' )\nbool = isConstantcase( 'BEEP and BOOP' )\n","isCubeNumber":"var bool = isCubeNumber( 8.0 )\nbool = isCubeNumber( new Number( 8.0 ) )\nbool = isCubeNumber( 3.14 )\nbool = isCubeNumber( -5.0 )\nbool = isCubeNumber( null )\n","isCubeNumber.isPrimitive":"var bool = isCubeNumber.isPrimitive( 8.0 )\nbool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n","isCubeNumber.isObject":"var bool = isCubeNumber.isObject( 8.0 )\nbool = isCubeNumber.isObject( new Number( 8.0 ) )\n","isCurrentYear":"var bool = isCurrentYear( new Date() )\nbool = isCurrentYear( currentYear() )\nbool = isCurrentYear( 2021 )\nbool = isCurrentYear( null )\n","isDataProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataProperty( obj, 'boop' )\nbool = isDataProperty( obj, 'beep' )\n","isDataPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataPropertyIn( obj, 'boop' )\nbool = isDataPropertyIn( obj, 'beep' )\n","isDataView":"var buf = new ArrayBuffer( 10 );\nvar bool = isDataView( new DataView( buf ) )\nbool = isDataView( [] )\n","isDateObject":"var bool = isDateObject( new Date() )\nbool = isDateObject( '2017-01-01' )\n","isDateObjectArray":"var bool = isDateObjectArray( [ new Date(), new Date() ] )\nbool = isDateObjectArray( [ {}, {} ] )\nbool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\nbool = isDateObjectArray( [] )\n","isDigitString":"var bool = isDigitString( '0123456789' )\nbool = isDigitString( 'abcdef' )\nbool = isDigitString( '0xff' )\nbool = isDigitString( '' )\n","isDomainName":"var bool = isDomainName( 'example.com' )\nbool = isDomainName( 'foo@bar.com' )\n","isDurationString":"var bool = isDurationString( '1d' )\nbool = isDurationString( '1h' )\nbool = isDurationString( 'beep' )\n","isEmailAddress":"var bool = isEmailAddress( 'beep@boop.com' )\nbool = isEmailAddress( 'beep' )\nbool = isEmailAddress( null )\n","isEmptyArray":"var bool = isEmptyArray( [] )\nbool = isEmptyArray( [ 1, 2, 3 ] )\nbool = isEmptyArray( {} )\n","isEmptyArrayLikeObject":"var bool = isEmptyArrayLikeObject( [] )\nbool = isEmptyArrayLikeObject( { 'length': 0 } )\nbool = isEmptyArrayLikeObject( '' )\n","isEmptyCollection":"var bool = isEmptyCollection( [] )\nbool = isEmptyCollection( { 'length': 0 } )\nbool = isEmptyCollection( [ 1, 2, 3 ] )\nbool = isEmptyCollection( {} )\n","isEmptyObject":"var bool = isEmptyObject( {} )\nbool = isEmptyObject( { 'beep': 'boop' } )\nbool = isEmptyObject( [] )\n","isEmptyString":"var bool = isEmptyString( '' )\nbool = isEmptyString( new String( '' ) )\nbool = isEmptyString( 'beep' )\nbool = isEmptyString( [] )\n","isEmptyString.isPrimitive":"var bool = isEmptyString.isPrimitive( '' )\nbool = isEmptyString.isPrimitive( new String( '' ) )\n","isEmptyString.isObject":"var bool = isEmptyString.isObject( new String( '' ) )\nbool = isEmptyString.isObject( '' )\n","isEnumerableProperty":"var beep = { 'boop': true };\nvar bool = isEnumerableProperty( beep, 'boop' )\nbool = isEnumerableProperty( beep, 'hasOwnProperty' )\n","isEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isEnumerablePropertyIn( obj, 'boop' )\nbool = isEnumerablePropertyIn( obj, 'beep' )\n","isEqualArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isEqualArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isEqualArray( x, y )\n","isEqualDateObject":"var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar bool = isEqualDateObject( d1, d2 )\nd1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nd2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\nbool = isEqualDateObject( d1, d2 )\n","isError":"var bool = isError( new Error( 'beep' ) )\nbool = isError( {} )\n","isEvalError":"var bool = isEvalError( new EvalError( 'beep' ) )\nbool = isEvalError( {} )\n","isEven":"var bool = isEven( 4.0 )\nbool = isEven( new Number( 4.0 ) )\nbool = isEven( 3.0 )\nbool = isEven( -3.14 )\nbool = isEven( null )\n","isEven.isPrimitive":"var bool = isEven.isPrimitive( -4.0 )\nbool = isEven.isPrimitive( new Number( -4.0 ) )\n","isEven.isObject":"var bool = isEven.isObject( 4.0 )\nbool = isEven.isObject( new Number( 4.0 ) )\n","isFalsy":"var bool = isFalsy( false )\nbool = isFalsy( '' )\nbool = isFalsy( 0 )\nbool = isFalsy( null )\nbool = isFalsy( void 0 )\nbool = isFalsy( NaN )\nbool = isFalsy( {} )\nbool = isFalsy( [] )\n","isFalsyArray":"var bool = isFalsyArray( [ null, '' ] )\nbool = isFalsyArray( [ {}, [] ] )\nbool = isFalsyArray( [] )\n","isFinite":"var bool = isFinite( 5.0 )\nbool = isFinite( new Number( 5.0 ) )\nbool = isFinite( 1.0/0.0 )\nbool = isFinite( null )\n","isFinite.isPrimitive":"var bool = isFinite.isPrimitive( -3.0 )\nbool = isFinite.isPrimitive( new Number( -3.0 ) )\n","isFinite.isObject":"var bool = isFinite.isObject( 3.0 )\nbool = isFinite.isObject( new Number( 3.0 ) )\n","isFiniteArray":"var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n","isFiniteArray.primitives":"var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\nbool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isFiniteArray.objects":"var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n","isFloat32Array":"var bool = isFloat32Array( new Float32Array( 10 ) )\nbool = isFloat32Array( [] )\n","isFloat32MatrixLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32MatrixLike( M )\nbool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32MatrixLike( 3.14 )\nbool = isFloat32MatrixLike( {} )\n","isFloat32ndarrayLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32ndarrayLike( M )\nbool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32ndarrayLike( 3.14 )\nbool = isFloat32ndarrayLike( {} )\n","isFloat32VectorLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32VectorLike( M )\nbool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32VectorLike( 3.14 )\nbool = isFloat32VectorLike( {} )\n","isFloat64Array":"var bool = isFloat64Array( new Float64Array( 10 ) )\nbool = isFloat64Array( [] )\n","isFloat64MatrixLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64MatrixLike( M )\nbool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64MatrixLike( 3.14 )\nbool = isFloat64MatrixLike( {} )\n","isFloat64ndarrayLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64ndarrayLike( M )\nbool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64ndarrayLike( 3.14 )\nbool = isFloat64ndarrayLike( {} )\n","isFloat64VectorLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64VectorLike( M )\nbool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64VectorLike( 3.14 )\nbool = isFloat64VectorLike( {} )\n","isFunction":"function beep() {};\nvar bool = isFunction( beep )\nbool = isFunction( {} )\n","isFunctionArray":"function beep() {};\nfunction boop() {};\nvar bool = isFunctionArray( [ beep, boop ] )\nbool = isFunctionArray( [ {}, beep ] )\nbool = isFunctionArray( [] )\n","isGeneratorObject":"function* generateID() {\n var idx = 0;\n while ( idx < idx+1 ) {\n yield idx;\n idx += 1;\n }\n };\nvar bool = isGeneratorObject( generateID() )\nbool = isGeneratorObject( generateID )\nbool = isGeneratorObject( {} )\nbool = isGeneratorObject( null )\n","isGeneratorObjectLike":"var obj = {\n 'next': function noop() {},\n 'return': function noop() {},\n 'throw': function noop() {}\n };\nvar bool = isGeneratorObjectLike( obj )\nbool = isGeneratorObjectLike( {} )\nbool = isGeneratorObjectLike( null )\n","isgzipBuffer":"var buf = new Uint8Array( 20 );\nbuf[ 0 ] = 31; // 0x1f => magic number\nbuf[ 1 ] = 139; // 0x8b\nbuf[ 2 ] = 8; // 0x08 => compression method\nvar bool = isgzipBuffer( buf )\nbool = isgzipBuffer( [] )\n","isHexString":"var bool = isHexString( '0123456789abcdefABCDEF' )\nbool = isHexString( '0xffffff' )\nbool = isHexString( 'x' )\nbool = isHexString( '' )\n","isInfinite":"var bool = isInfinite( 1.0/0.0 )\nbool = isInfinite( new Number( -1.0/0.0 ) )\nbool = isInfinite( 5.0 )\nbool = isInfinite( '1.0/0.0' )\n","isInfinite.isPrimitive":"var bool = isInfinite.isPrimitive( -1.0/0.0 )\nbool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isInfinite.isObject":"var bool = isInfinite.isObject( 1.0/0.0 )\nbool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n","isInheritedProperty":"var beep = { 'boop': true };\nvar bool = isInheritedProperty( beep, 'boop' )\nbool = isInheritedProperty( beep, 'toString' )\nbool = isInheritedProperty( beep, 'bop' )\n","isInt8Array":"var bool = isInt8Array( new Int8Array( 10 ) )\nbool = isInt8Array( [] )\n","isInt16Array":"var bool = isInt16Array( new Int16Array( 10 ) )\nbool = isInt16Array( [] )\n","isInt32Array":"var bool = isInt32Array( new Int32Array( 10 ) )\nbool = isInt32Array( [] )\n","isInteger":"var bool = isInteger( 5.0 )\nbool = isInteger( new Number( 5.0 ) )\nbool = isInteger( -3.14 )\nbool = isInteger( null )\n","isInteger.isPrimitive":"var bool = isInteger.isPrimitive( -3.0 )\nbool = isInteger.isPrimitive( new Number( -3.0 ) )\n","isInteger.isObject":"var bool = isInteger.isObject( 3.0 )\nbool = isInteger.isObject( new Number( 3.0 ) )\n","isIntegerArray":"var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isIntegerArray( [ -3.0, '3.0' ] )\n","isIntegerArray.primitives":"var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\nbool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isIntegerArray.objects":"var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n","isIterableLike":"var bool = isIterableLike( [ 1, 2, 3 ] )\nbool = isIterableLike( {} )\nbool = isIterableLike( null )\n","isIteratorLike":"var obj = {\n 'next': function noop() {}\n };\nvar bool = isIteratorLike( obj )\nbool = isIteratorLike( {} )\nbool = isIteratorLike( null )\n","isJSON":"var bool = isJSON( '{\"a\":5}' )\nbool = isJSON( '{a\":5}' )\n","isKebabcase":"var bool = isKebabcase( 'beep-boop' )\nbool = isKebabcase( 'BEEP_BOOP' )\n","isLeapYear":"var bool = isLeapYear( new Date() )\nbool = isLeapYear( 1996 )\nbool = isLeapYear( 2001 )\n","isLocalhost":"var bool = isLocalhost( 'localhost' )\nbool = isLocalhost( '127.0.0.1' )\nbool = isLocalhost( 'stdlib.io' )\n","isLowercase":"var bool = isLowercase( 'hello' )\nbool = isLowercase( 'World' )\n","isMatrixLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isMatrixLike( M )\nbool = isMatrixLike( [ 1, 2, 3, 4 ] )\nbool = isMatrixLike( 3.14 )\nbool = isMatrixLike( {} )\n","isMethod":"var beep = { 'boop': function beep() { return 'beep'; } };\nvar bool = isMethod( beep, 'boop' )\nbool = isMethod( beep, 'toString' )\n","isMethodIn":"var beep = { 'boop': true };\nvar bool = isMethodIn( beep, 'toString' )\nbool = isMethodIn( beep, 'boop' )\nbool = isMethodIn( beep, 'bop' )\n","isMultiSlice":"var bool = isMultiSlice( new MultiSlice() )\nbool = isMultiSlice( 3.14 )\nbool = isMultiSlice( {} )\n","isNamedTypedTupleLike":"var Point = namedtypedtuple( [ 'x', 'y' ] );\nvar p = new Point();\nvar bool = isNamedTypedTupleLike( p )\nbool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\nbool = isNamedTypedTupleLike( 3.14 )\nbool = isNamedTypedTupleLike( {} )\n","isnan":"var bool = isnan( NaN )\nbool = isnan( new Number( NaN ) )\nbool = isnan( 3.14 )\nbool = isnan( null )\n","isnan.isPrimitive":"var bool = isnan.isPrimitive( NaN )\nbool = isnan.isPrimitive( 3.14 )\nbool = isnan.isPrimitive( new Number( NaN ) )\n","isnan.isObject":"var bool = isnan.isObject( NaN )\nbool = isnan.isObject( new Number( NaN ) )\n","isNaNArray":"var bool = isNaNArray( [ NaN, NaN, NaN ] )\nbool = isNaNArray( [ NaN, 2 ] )\n","isNaNArray.primitives":"var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\nbool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n","isNaNArray.objects":"var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n","isNativeFunction":"var bool = isNativeFunction( Date )\nfunction beep() {};\nbool = isNativeFunction( beep )\nbool = isNativeFunction( {} )\n","isndarrayLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLike( M )\nbool = isndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isndarrayLike( 3.14 )\nbool = isndarrayLike( {} )\n","isndarrayLikeWithDataType":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLikeWithDataType( M, 'generic' )\nbool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\nbool = isndarrayLikeWithDataType( 3.14, 'generic' )\nbool = isndarrayLikeWithDataType( {}, 'generic' )\n","isNegativeFinite":"var bool = isNegativeFinite( -5.0 )\nbool = isNegativeFinite( new Number( -5.0 ) )\nbool = isNegativeFinite( -3.14 )\nbool = isNegativeFinite( 5.0 )\nbool = isNegativeFinite( null )\nbool = isNegativeFinite( -1.0/0.0 )\nbool = isNegativeFinite( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isPrimitive":"var bool = isNegativeFinite.isPrimitive( -3.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\nvar bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isObject":"var bool = isNegativeFinite.isObject( -3.0 )\nbool = isNegativeFinite.isObject( new Number( -3.0 ) )\nbool = isNegativeFinite.isObject( -1.0/0.0 )\nbool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n","isNegativeInteger":"var bool = isNegativeInteger( -5.0 )\nbool = isNegativeInteger( new Number( -5.0 ) )\nbool = isNegativeInteger( 5.0 )\nbool = isNegativeInteger( -3.14 )\nbool = isNegativeInteger( null )\n","isNegativeInteger.isPrimitive":"var bool = isNegativeInteger.isPrimitive( -3.0 )\nbool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n","isNegativeInteger.isObject":"var bool = isNegativeInteger.isObject( -3.0 )\nbool = isNegativeInteger.isObject( new Number( -3.0 ) )\n","isNegativeIntegerArray":"var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n","isNegativeIntegerArray.primitives":"var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeIntegerArray.objects":"var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumber":"var bool = isNegativeNumber( -5.0 )\nbool = isNegativeNumber( new Number( -5.0 ) )\nbool = isNegativeNumber( -3.14 )\nbool = isNegativeNumber( 5.0 )\nbool = isNegativeNumber( null )\n","isNegativeNumber.isPrimitive":"var bool = isNegativeNumber.isPrimitive( -3.0 )\nbool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n","isNegativeNumber.isObject":"var bool = isNegativeNumber.isObject( -3.0 )\nbool = isNegativeNumber.isObject( new Number( -3.0 ) )\n","isNegativeNumberArray":"var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n","isNegativeNumberArray.primitives":"var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumberArray.objects":"var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeZero":"var bool = isNegativeZero( -0.0 )\nbool = isNegativeZero( new Number( -0.0 ) )\nbool = isNegativeZero( -3.14 )\nbool = isNegativeZero( 0.0 )\nbool = isNegativeZero( null )\n","isNegativeZero.isPrimitive":"var bool = isNegativeZero.isPrimitive( -0.0 )\nbool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n","isNegativeZero.isObject":"var bool = isNegativeZero.isObject( -0.0 )\nbool = isNegativeZero.isObject( new Number( -0.0 ) )\n","isNodeBuiltin":"var bool = isNodeBuiltin( 'cluster' )\nbool = isNodeBuiltin( 'crypto' )\nbool = isNodeBuiltin( 'fs-extra' )\nbool = isNodeBuiltin( '' )\n","isNodeDuplexStreamLike":"var Stream = require( 'stream' ).Duplex;\ns = new Stream();\nvar bool = isNodeDuplexStreamLike( s )\nbool = isNodeDuplexStreamLike( {} )\n","isNodeReadableStreamLike":"var Stream = require( 'stream' ).Readable;\ns = new Stream();\nvar bool = isNodeReadableStreamLike( s )\nbool = isNodeReadableStreamLike( {} )\n","isNodeREPL":"var bool = isNodeREPL()\n","isNodeStreamLike":"var Stream = require( 'stream' ).Stream;\ns = new Stream();\nvar bool = isNodeStreamLike( s )\nbool = isNodeStreamLike( {} )\n","isNodeTransformStreamLike":"var Stream = require( 'stream' ).Transform;\ns = new Stream();\nvar bool = isNodeTransformStreamLike( s )\nbool = isNodeTransformStreamLike( {} )\n","isNodeWritableStreamLike":"var Stream = require( 'stream' ).Writable;\ns = new Stream();\nvar bool = isNodeWritableStreamLike( s )\nbool = isNodeWritableStreamLike( {} )\n","isNonConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurableProperty( obj, 'boop' )\nbool = isNonConfigurableProperty( obj, 'beep' )\n","isNonConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurablePropertyIn( obj, 'boop' )\nbool = isNonConfigurablePropertyIn( obj, 'beep' )\n","isNonEnumerableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerableProperty( obj, 'boop' )\nbool = isNonEnumerableProperty( obj, 'beep' )\n","isNonEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerablePropertyIn( obj, 'boop' )\nbool = isNonEnumerablePropertyIn( obj, 'beep' )\n","isNonNegativeFinite":"var bool = isNonNegativeFinite( 5.0 )\nbool = isNonNegativeFinite( new Number( 5.0 ) )\nbool = isNonNegativeFinite( 3.14 )\nbool = isNonNegativeFinite( -5.0 )\nbool = isNonNegativeFinite( null )\nbool = isNonNegativeFinite( PINF )\n","isNonNegativeFinite.isPrimitive":"var bool = isNonNegativeFinite.isPrimitive( 3.0 )\nbool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeFinite.isObject":"var bool = isNonNegativeFinite.isObject( 3.0 )\nbool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n","isNonNegativeInteger":"var bool = isNonNegativeInteger( 5.0 )\nbool = isNonNegativeInteger( new Number( 5.0 ) )\nbool = isNonNegativeInteger( 3.14 )\nbool = isNonNegativeInteger( -5.0 )\nbool = isNonNegativeInteger( null )\n","isNonNegativeInteger.isPrimitive":"var bool = isNonNegativeInteger.isPrimitive( 3.0 )\nbool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeInteger.isObject":"var bool = isNonNegativeInteger.isObject( 3.0 )\nbool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n","isNonNegativeIntegerArray":"var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n","isNonNegativeIntegerArray.primitives":"var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeIntegerArray.objects":"var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumber":"var bool = isNonNegativeNumber( 5.0 )\nbool = isNonNegativeNumber( new Number( 5.0 ) )\nbool = isNonNegativeNumber( 3.14 )\nbool = isNonNegativeNumber( -5.0 )\nbool = isNonNegativeNumber( null )\n","isNonNegativeNumber.isPrimitive":"var bool = isNonNegativeNumber.isPrimitive( 3.0 )\nbool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeNumber.isObject":"var bool = isNonNegativeNumber.isObject( 3.0 )\nbool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n","isNonNegativeNumberArray":"var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n","isNonNegativeNumberArray.primitives":"var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumberArray.objects":"var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonPositiveFinite":"var bool = isNonPositiveFinite( -5.0 )\nbool = isNonPositiveFinite( new Number( -5.0 ) )\nbool = isNonPositiveFinite( -3.14 )\nbool = isNonPositiveFinite( 5.0 )\nbool = isNonPositiveFinite( null )\n","isNonPositiveFinite.isPrimitive":"var bool = isNonPositiveFinite.isPrimitive( -3.0 )\nbool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveFinite.isObject":"var bool = isNonPositiveFinite.isObject( -3.0 )\nbool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n","isNonPositiveInteger":"var bool = isNonPositiveInteger( -5.0 )\nbool = isNonPositiveInteger( new Number( -5.0 ) )\nbool = isNonPositiveInteger( 5.0 )\nbool = isNonPositiveInteger( -3.14 )\nbool = isNonPositiveInteger( null )\n","isNonPositiveInteger.isPrimitive":"var bool = isNonPositiveInteger.isPrimitive( -3.0 )\nbool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveInteger.isObject":"var bool = isNonPositiveInteger.isObject( -3.0 )\nbool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n","isNonPositiveIntegerArray":"var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n","isNonPositiveIntegerArray.primitives":"var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveIntegerArray.objects":"var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumber":"var bool = isNonPositiveNumber( -5.0 )\nbool = isNonPositiveNumber( new Number( -5.0 ) )\nbool = isNonPositiveNumber( -3.14 )\nbool = isNonPositiveNumber( 5.0 )\nbool = isNonPositiveNumber( null )\n","isNonPositiveNumber.isPrimitive":"var bool = isNonPositiveNumber.isPrimitive( -3.0 )\nbool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveNumber.isObject":"var bool = isNonPositiveNumber.isObject( -3.0 )\nbool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n","isNonPositiveNumberArray":"var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n","isNonPositiveNumberArray.primitives":"var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumberArray.objects":"var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonSymmetricMatrix":"var buf = [ 1, 2, 3, 4 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isNonSymmetricMatrix( M )\nbool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isNonSymmetricMatrix( 3.14 )\nbool = isNonSymmetricMatrix( {} )\n","isNull":"var bool = isNull( null )\nbool = isNull( true )\n","isNullArray":"var bool = isNullArray( [ null, null, null ] )\nbool = isNullArray( [ NaN, 2, null ] )\n","isNumber":"var bool = isNumber( 3.14 )\nbool = isNumber( new Number( 3.14 ) )\nbool = isNumber( NaN )\nbool = isNumber( null )\n","isNumber.isPrimitive":"var bool = isNumber.isPrimitive( 3.14 )\nbool = isNumber.isPrimitive( NaN )\nbool = isNumber.isPrimitive( new Number( 3.14 ) )\n","isNumber.isObject":"var bool = isNumber.isObject( 3.14 )\nbool = isNumber.isObject( new Number( 3.14 ) )\n","isNumberArray":"var bool = isNumberArray( [ 1, 2, 3 ] )\nbool = isNumberArray( [ '1', 2, 3 ] )\n","isNumberArray.primitives":"var arr = [ 1, 2, 3 ];\nvar bool = isNumberArray.primitives( arr )\narr = [ 1, new Number( 2 ) ];\nbool = isNumberArray.primitives( arr )\n","isNumberArray.objects":"var arr = [ new Number( 1 ), new Number( 2 ) ];\nvar bool = isNumberArray.objects( arr )\narr = [ new Number( 1 ), 2 ];\nbool = isNumberArray.objects( arr )\n","isNumericArray":"var bool = isNumericArray( new Int8Array( 10 ) )\nbool = isNumericArray( [ 1, 2, 3 ] )\nbool = isNumericArray( [ '1', '2', '3' ] )\n","isObject":"var bool = isObject( {} )\nbool = isObject( true )\n","isObjectArray":"var bool = isObjectArray( [ {}, new Number(3.0) ] )\nbool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isObjectArray( [ {}, '3.0' ] )\n","isObjectLike":"var bool = isObjectLike( {} )\nbool = isObjectLike( [] )\nbool = isObjectLike( null )\n","isOdd":"var bool = isOdd( 5.0 )\nbool = isOdd( new Number( 5.0 ) )\nbool = isOdd( 4.0 )\nbool = isOdd( new Number( 4.0 ) )\nbool = isOdd( -3.14 )\nbool = isOdd( null )\n","isOdd.isPrimitive":"var bool = isOdd.isPrimitive( -5.0 )\nbool = isOdd.isPrimitive( new Number( -5.0 ) )\n","isOdd.isObject":"var bool = isOdd.isObject( 5.0 )\nbool = isOdd.isObject( new Number( 5.0 ) )\n","isoWeeksInYear":"var num = isoWeeksInYear()\nnum = isoWeeksInYear( 2015 )\nnum = isoWeeksInYear( 2017 )\n","isPascalcase":"var bool = isPascalcase( 'HelloWorld' )\nbool = isPascalcase( 'hello-world' )\n","isPersymmetricMatrix":"var buf = [ 1, 2, 3, 1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isPersymmetricMatrix( M )\nbool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isPersymmetricMatrix( 3.14 )\nbool = isPersymmetricMatrix( {} )\n","isPlainObject":"var bool = isPlainObject( {} )\nbool = isPlainObject( null )\n","isPlainObjectArray":"var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isPlainObjectArray( [ {}, new Number(3.0) ] )\nbool = isPlainObjectArray( [ {}, '3.0' ] )\n","isPositiveFinite":"var bool = isPositiveFinite( 5.0 )\nbool = isPositiveFinite( new Number( 5.0 ) )\nbool = isPositiveFinite( 3.14 )\nbool = isPositiveFinite( -5.0 )\nvar bool = isPositiveFinite( 1.0/0.0 )\nbool = isPositiveFinite( new Number( 1.0/0.0 ) )\nbool = isPositiveFinite( null )\n","isPositiveFinite.isPrimitive":"var bool = isPositiveFinite.isPrimitive( 3.0 )\nvar bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\nbool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n","isPositiveFinite.isObject":"var bool = isPositiveFinite.isObject( 3.0 )\nbool = isPositiveFinite.isObject( new Number( 3.0 ) )\nbool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n","isPositiveInteger":"var bool = isPositiveInteger( 5.0 )\nbool = isPositiveInteger( new Number( 5.0 ) )\nbool = isPositiveInteger( 3.14 )\nbool = isPositiveInteger( -5.0 )\nbool = isPositiveInteger( null )\n","isPositiveInteger.isPrimitive":"var bool = isPositiveInteger.isPrimitive( 3.0 )\nbool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n","isPositiveInteger.isObject":"var bool = isPositiveInteger.isObject( 3.0 )\nbool = isPositiveInteger.isObject( new Number( 3.0 ) )\n","isPositiveIntegerArray":"var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n","isPositiveIntegerArray.primitives":"var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveIntegerArray.objects":"var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveNumber":"var bool = isPositiveNumber( 5.0 )\nbool = isPositiveNumber( new Number( 5.0 ) )\nbool = isPositiveNumber( 3.14 )\nbool = isPositiveNumber( -5.0 )\nbool = isPositiveNumber( null )\n","isPositiveNumber.isPrimitive":"var bool = isPositiveNumber.isPrimitive( 3.0 )\nbool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n","isPositiveNumber.isObject":"var bool = isPositiveNumber.isObject( 3.0 )\nbool = isPositiveNumber.isObject( new Number( 3.0 ) )\n","isPositiveNumberArray":"var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n","isPositiveNumberArray.primitives":"var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveNumberArray.objects":"var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveZero":"var bool = isPositiveZero( 0.0 )\nbool = isPositiveZero( new Number( 0.0 ) )\nbool = isPositiveZero( -3.14 )\nbool = isPositiveZero( -0.0 )\nbool = isPositiveZero( null )\n","isPositiveZero.isPrimitive":"var bool = isPositiveZero.isPrimitive( 0.0 )\nbool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n","isPositiveZero.isObject":"var bool = isPositiveZero.isObject( 0.0 )\nbool = isPositiveZero.isObject( new Number( 0.0 ) )\n","isPrime":"var bool = isPrime( 5.0 )\nbool = isPrime( new Number( 5.0 ) )\nbool = isPrime( 3.14 )\nbool = isPrime( -5.0 )\nbool = isPrime( null )\n","isPrime.isPrimitive":"var bool = isPrime.isPrimitive( 5.0 )\nbool = isPrime.isPrimitive( new Number( 5.0 ) )\n","isPrime.isObject":"var bool = isPrime.isObject( 5.0 )\nbool = isPrime.isObject( new Number( 5.0 ) )\n","isPrimitive":"var bool = isPrimitive( true )\nbool = isPrimitive( {} )\n","isPrimitiveArray":"var bool = isPrimitiveArray( [ '3', 2, null ] )\nbool = isPrimitiveArray( [ {}, 2, 1 ] )\nbool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n","isPRNGLike":"var bool = isPRNGLike( base.random.randu )\nbool = isPRNGLike( [ 1, 2, 3, 4 ] )\nbool = isPRNGLike( 3.14 )\nbool = isPRNGLike( {} )\n","isProbability":"var bool = isProbability( 0.5 )\nbool = isProbability( new Number( 0.5 ) )\nbool = isProbability( 3.14 )\nbool = isProbability( -5.0 )\nbool = isProbability( null )\n","isProbability.isPrimitive":"var bool = isProbability.isPrimitive( 0.3 )\nbool = isProbability.isPrimitive( new Number( 0.3 ) )\n","isProbability.isObject":"var bool = isProbability.isObject( 0.77 )\nbool = isProbability.isObject( new Number( 0.77 ) )\n","isProbabilityArray":"var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\nbool = isProbabilityArray( [ 0.8, 1.2 ] )\nbool = isProbabilityArray( [ 0.8, '0.2' ] )\n","isProbabilityArray.primitives":"var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\nbool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n","isProbabilityArray.objects":"var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\nbool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n","isPropertyKey":"var out = isPropertyKey( 'foo' )\nout = isPropertyKey( 1 )\nout = isPropertyKey( true )\n","isPrototypeOf":"function Foo() { return this; };\nfunction Bar() { return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar bool = isPrototypeOf( bar, Foo.prototype )\n","isRaggedNestedArray":"var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\nbool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nbool = isRaggedNestedArray( 'beep' )\n","isRangeError":"var bool = isRangeError( new RangeError( 'beep' ) )\nbool = isRangeError( {} )\n","isReadableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadableProperty( obj, 'boop' )\nbool = isReadableProperty( obj, 'beep' )\n","isReadablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadablePropertyIn( obj, 'boop' )\nbool = isReadablePropertyIn( obj, 'beep' )\n","isReadOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyProperty( obj, 'boop' )\nbool = isReadOnlyProperty( obj, 'beep' )\n","isReadOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyPropertyIn( obj, 'boop' )\nbool = isReadOnlyPropertyIn( obj, 'beep' )\n","isReadWriteProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWriteProperty( obj, 'boop' )\nbool = isReadWriteProperty( obj, 'beep' )\n","isReadWritePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWritePropertyIn( obj, 'boop' )\nbool = isReadWritePropertyIn( obj, 'beep' )\n","isReferenceError":"var bool = isReferenceError( new ReferenceError( 'beep' ) )\nbool = isReferenceError( {} )\n","isRegExp":"var bool = isRegExp( /\\.+/ )\nbool = isRegExp( {} )\n","isRegExpString":"var bool = isRegExpString( '/beep/' )\nbool = isRegExpString( 'beep' )\nbool = isRegExpString( '' )\nbool = isRegExpString( null )\n","isRelativePath":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( './foo/bar/baz' )\n","isRelativePath.posix":"var bool = isRelativePath.posix( './foo/bar/baz' )\nbool = isRelativePath.posix( '/foo/../bar/baz' )\n","isRelativePath.win32":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n","isRelativeURI":"var bool = isRelativeURI( '/images/example.png' )\nbool = isRelativeURI( 'http://www.example.com' )\nbool = isRelativeURI( null )\n","isSafeInteger":"var bool = isSafeInteger( 5.0 )\nbool = isSafeInteger( new Number( 5.0 ) )\nbool = isSafeInteger( 2.0e200 )\nbool = isSafeInteger( -3.14 )\nbool = isSafeInteger( null )\n","isSafeInteger.isPrimitive":"var bool = isSafeInteger.isPrimitive( -3.0 )\nbool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n","isSafeInteger.isObject":"var bool = isSafeInteger.isObject( 3.0 )\nbool = isSafeInteger.isObject( new Number( 3.0 ) )\n","isSafeIntegerArray":"var arr = [ -3.0, new Number(0.0), 2.0 ];\nvar bool = isSafeIntegerArray( arr )\narr = [ -3.0, '3.0' ];\nbool = isSafeIntegerArray( arr )\n","isSafeIntegerArray.primitives":"var arr = [ -1.0, 10.0 ];\nvar bool = isSafeIntegerArray.primitives( arr )\narr = [ -1.0, 0.0, 5.0 ];\nbool = isSafeIntegerArray.primitives( arr )\narr = [ -3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.primitives( arr )\n","isSafeIntegerArray.objects":"var arr = [ new Number(1.0), new Number(3.0) ];\nvar bool = isSafeIntegerArray.objects( arr )\narr = [ -1.0, 0.0, 3.0 ];\nbool = isSafeIntegerArray.objects( arr )\narr = [ 3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.objects( arr )\n","isSameArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArray( x, y )\n","isSameArrayLike":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArrayLike( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArrayLike( x, y )\n","isSameComplex64":"var x = new Complex64( 1.0, 2.0 );\nvar y = new Complex64( 1.0, 2.0 );\nvar bool = isSameComplex64( x, y )\nx = new Complex64( NaN, NaN );\ny = new Complex64( NaN, NaN );\nbool = isSameComplex64( x, y )\n","isSameComplex64Array":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex64Array( x, y )\nx = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex64Array( x, y )\n","isSameComplex128":"var x = new Complex128( 1.0, 2.0 );\nvar y = new Complex128( 1.0, 2.0 );\nvar bool = isSameComplex128( x, y )\nx = new Complex128( NaN, NaN );\ny = new Complex128( NaN, NaN );\nbool = isSameComplex128( x, y )\n","isSameComplex128Array":"var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex128Array( x, y )\nx = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex128Array( x, y )\n","isSameFloat32Array":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat32Array( x, y )\nx = new Float32Array( [ NaN, NaN, NaN ] );\ny = new Float32Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat32Array( x, y )\n","isSameFloat64Array":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat64Array( x, y )\nx = new Float64Array( [ NaN, NaN, NaN ] );\ny = new Float64Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat64Array( x, y )\n","isSameNativeClass":"var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\nbool = isSameNativeClass( 'beep', 'boop' )\nbool = isSameNativeClass( {}, [] )\n","isSameType":"var bool = isSameType( true, true )\nbool = isSameType( {}, [] )\nbool = isSameType( 3.12, -3.12 )\nbool = isSameType( 0.0, '0.0' )\n","isSameValue":"var bool = isSameValue( true, true )\nbool = isSameValue( {}, {} )\nbool = isSameValue( -0.0, -0.0 )\nbool = isSameValue( -0.0, 0.0 )\nbool = isSameValue( NaN, NaN )\n","isSameValueZero":"var bool = isSameValueZero( true, true )\nbool = isSameValueZero( {}, {} )\nbool = isSameValueZero( -0.0, -0.0 )\nbool = isSameValueZero( -0.0, 0.0 )\nbool = isSameValueZero( NaN, NaN )\n","isSemVer":"var bool = isSemVer( '1.0.0' )\nbool = isSemVer( '1.0.0-alpha.1' )\nbool = isSemVer( '0.1' )\nbool = isSemVer( null )\n","isSharedArrayBuffer":"var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\nbool = isSharedArrayBuffer( [] )\n","isSkewCentrosymmetricMatrix":"var buf = [ 2, 1, -1, -2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewCentrosymmetricMatrix( M )\nbool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewCentrosymmetricMatrix( 3.14 )\nbool = isSkewCentrosymmetricMatrix( {} )\n","isSkewPersymmetricMatrix":"var buf = [ 1, 0, 0, -1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewPersymmetricMatrix( M )\nbool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewPersymmetricMatrix( 3.14 )\nbool = isSkewPersymmetricMatrix( {} )\n","isSkewSymmetricMatrix":"var buf = [ 0, -1, 1, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewSymmetricMatrix( M )\nbool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewSymmetricMatrix( 3.14 )\nbool = isSkewSymmetricMatrix( {} )\n","isSlice":"var bool = isSlice( new Slice( 10 ) )\nbool = isSlice( 3.14 )\nbool = isSlice( {} )\n","isSnakecase":"var bool = isSnakecase( 'hello_world' )\nbool = isSnakecase( 'Hello World' )\n","isSquareMatrix":"var buf = [ 0, 0, 0, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSquareMatrix( M )\nbool = isSquareMatrix( [ 1, 2, 3, 4 ] )\nbool = isSquareMatrix( 3.14 )\nbool = isSquareMatrix( {} )\n","isSquareNumber":"var bool = isSquareNumber( 4.0 )\nbool = isSquareNumber( new Number( 4.0 ) )\nbool = isSquareNumber( 3.14 )\nbool = isSquareNumber( -5.0 )\nbool = isSquareNumber( null )\n","isSquareNumber.isPrimitive":"var bool = isSquareNumber.isPrimitive( 4.0 )\nbool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n","isSquareNumber.isObject":"var bool = isSquareNumber.isObject( 4.0 )\nbool = isSquareNumber.isObject( new Number( 4.0 ) )\n","isSquareTriangularNumber":"var bool = isSquareTriangularNumber( 36.0 )\nbool = isSquareTriangularNumber( new Number( 36.0 ) )\nbool = isSquareTriangularNumber( 3.14 )\nbool = isSquareTriangularNumber( -5.0 )\nbool = isSquareTriangularNumber( null )\n","isSquareTriangularNumber.isPrimitive":"var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\nbool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isSquareTriangularNumber.isObject":"var bool = isSquareTriangularNumber.isObject( 36.0 )\nbool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n","isStartcase":"var bool = isStartcase( 'Beep Boop' )\nbool = isStartcase( 'Beep and Boop' )\n","isStrictEqual":"var bool = isStrictEqual( true, true )\nbool = isStrictEqual( {}, {} )\nbool = isStrictEqual( -0.0, -0.0 )\nbool = isStrictEqual( -0.0, 0.0 )\nbool = isStrictEqual( NaN, NaN )\n","isString":"var bool = isString( 'beep' )\nbool = isString( new String( 'beep' ) )\nbool = isString( 5 )\n","isString.isPrimitive":"var bool = isString.isPrimitive( 'beep' )\nbool = isString.isPrimitive( new String( 'beep' ) )\n","isString.isObject":"var bool = isString.isObject( new String( 'beep' ) )\nbool = isString.isObject( 'beep' )\n","isStringArray":"var bool = isStringArray( [ 'abc', 'def' ] )\nbool = isStringArray( [ 'abc', 123 ] )\n","isStringArray.primitives":"var arr = [ 'abc', 'def' ];\nvar bool = isStringArray.primitives( arr )\narr = [ 'abc', new String( 'def' ) ];\nbool = isStringArray.primitives( arr )\n","isStringArray.objects":"var arr = [ new String( 'ab' ), new String( 'cd' ) ];\nvar bool = isStringArray.objects( arr )\narr = [ new String( 'abc' ), 'def' ];\nbool = isStringArray.objects( arr )\n","isStruct":"var schema = [ { 'name': 'foo', 'type': 'float64' } ];\nvar S = structFactory( schema );\nvar bool = isStruct( new S() )\nbool = isStruct( [ 1, 2, 3, 4 ] )\nbool = isStruct( 3.14 )\nbool = isStruct( {} )\n","isStructConstructorLike":"var schema = [ { 'name': 'foo', 'type': 'float64' } ];\nvar S = structFactory( schema );\nvar bool = isStructConstructorLike( S )\nbool = isStructConstructorLike( [ 1, 2, 3, 4 ] )\nbool = isStructConstructorLike( 3.14 )\nbool = isStructConstructorLike( {} )\n","isSymbol":"var bool = isSymbol( Symbol( 'beep' ) )\nbool = isSymbol( Object( Symbol( 'beep' ) ) )\nbool = isSymbol( {} )\nbool = isSymbol( null )\nbool = isSymbol( true )\n","isSymbolArray":"var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\nbool = isSymbolArray( Symbol( 'beep' ) )\nbool = isSymbolArray( [] )\nbool = isSymbolArray( {} )\nbool = isSymbolArray( null )\nbool = isSymbolArray( true )\n","isSymbolArray.primitives":"var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.primitives( [] )\nbool = isSymbolArray.primitives( {} )\nbool = isSymbolArray.primitives( null )\nbool = isSymbolArray.primitives( true )\n","isSymbolArray.objects":"var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.objects( [] )\nbool = isSymbolArray.objects( {} )\nbool = isSymbolArray.objects( null )\nbool = isSymbolArray.objects( true )\n","isSymmetricMatrix":"var buf = [ 0, 1, 1, 2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSymmetricMatrix( M )\nbool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSymmetricMatrix( 3.14 )\nbool = isSymmetricMatrix( {} )\n","isSyntaxError":"var bool = isSyntaxError( new SyntaxError( 'beep' ) )\nbool = isSyntaxError( {} )\n","isTriangularNumber":"var bool = isTriangularNumber( 36.0 )\nbool = isTriangularNumber( new Number( 36.0 ) )\nbool = isTriangularNumber( 3.14 )\nbool = isTriangularNumber( -5.0 )\nbool = isTriangularNumber( null )\n","isTriangularNumber.isPrimitive":"var bool = isTriangularNumber.isPrimitive( 36.0 )\nbool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isTriangularNumber.isObject":"var bool = isTriangularNumber.isObject( 36.0 )\nbool = isTriangularNumber.isObject( new Number( 36.0 ) )\n","isTruthy":"var bool = isTruthy( true )\nbool = isTruthy( {} )\nbool = isTruthy( [] )\nbool = isTruthy( false )\nbool = isTruthy( '' )\nbool = isTruthy( 0 )\nbool = isTruthy( null )\nbool = isTruthy( void 0 )\nbool = isTruthy( NaN )\n","isTruthyArray":"var bool = isTruthyArray( [ {}, [] ] )\nbool = isTruthyArray( [ null, '' ] )\nbool = isTruthyArray( [] )\n","isTypedArray":"var bool = isTypedArray( new Int8Array( 10 ) )\n","isTypedArrayLength":"var bool = isTypedArrayLength( 5 )\nbool = isTypedArrayLength( 2.0e200 )\nbool = isTypedArrayLength( -3.14 )\nbool = isTypedArrayLength( null )\n","isTypedArrayLike":"var bool = isTypedArrayLike( new Int16Array() )\nbool = isTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4\n })\n","isTypeError":"var bool = isTypeError( new TypeError( 'beep' ) )\nbool = isTypeError( {} )\n","isUint8Array":"var bool = isUint8Array( new Uint8Array( 10 ) )\nbool = isUint8Array( [] )\n","isUint8ClampedArray":"var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\nbool = isUint8ClampedArray( [] )\n","isUint16Array":"var bool = isUint16Array( new Uint16Array( 10 ) )\nbool = isUint16Array( [] )\n","isUint32Array":"var bool = isUint32Array( new Uint32Array( 10 ) )\nbool = isUint32Array( [] )\n","isUNCPath":"var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\nbool = isUNCPath( '/foo/bar/baz' )\n","isUndefined":"var bool = isUndefined( void 0 )\nbool = isUndefined( null )\n","isUndefinedOrNull":"var bool = isUndefinedOrNull( void 0 )\nbool = isUndefinedOrNull( null )\nbool = isUndefinedOrNull( false )\n","isUnityProbabilityArray":"var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\nbool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\nbool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\nbool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n","isUppercase":"var bool = isUppercase( 'HELLO' )\nbool = isUppercase( 'World' )\n","isURI":"var bool = isURI( 'http://google.com' )\nbool = isURI( 'http://localhost/' )\nbool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\nbool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\nbool = isURI( '' )\nbool = isURI( 'foo@bar' )\nbool = isURI( '://foo/' )\nbool = isURI( 'http://' )\nbool = isURI( 'http:////foo.html' )\nbool = isURI( 'http://example.w3.org/%a' )\n","isURIError":"var bool = isURIError( new URIError( 'beep' ) )\nbool = isURIError( {} )\n","isVectorLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isVectorLike( M )\nbool = isVectorLike( [ 1, 2, 3, 4 ] )\nbool = isVectorLike( 3.14 )\nbool = isVectorLike( {} )\n","isWebAssemblyMemory":"var bool = isWebAssemblyMemory( {} )\n","isWellFormedString":"var bool = isWellFormedString( '' )\nbool = isWellFormedString( new String( '' ) )\nbool = isWellFormedString( '\\uDBFF' )\nbool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\nbool = isWellFormedString( [] )\nbool = isWellFormedString( '-5' )\nbool = isWellFormedString( null )\n","isWellFormedString.isPrimitive":"var bool = isWellFormedString.isPrimitive( '' )\nbool = isWellFormedString.isPrimitive( new String( '' ) )\n","isWellFormedString.isObject":"var bool = isWellFormedString.isObject( '' )\nbool = isWellFormedString.isObject( new String( '' ) )\n","isWhitespace":"var bool = isWhitespace( ' ' )\nbool = isWhitespace( 'abcdef' )\nbool = isWhitespace( '' )\n","isWritableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritableProperty( obj, 'boop' )\nbool = isWritableProperty( obj, 'beep' )\n","isWritablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritablePropertyIn( obj, 'boop' )\nbool = isWritablePropertyIn( obj, 'beep' )\n","isWriteOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyProperty( obj, 'boop' )\nbool = isWriteOnlyProperty( obj, 'beep' )\n","isWriteOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyPropertyIn( obj, 'boop' )\nbool = isWriteOnlyPropertyIn( obj, 'beep' )\n","iterAbs":"var it = iterAbs( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAbs2":"var it = iterAbs2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAcos":"var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcosh":"var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcot":"var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoth":"var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcovercos":"var it = iterAcovercos( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoversin":"var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAdd":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterAdd( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterAdvance":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar it = iterAdvance( arr, 4 );\nvar v = it.next().value\nvar bool = it.next().done\n","iterAhavercos":"var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAhaversin":"var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAny":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterAny( arr )\n","iterAnyBy":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v === 1 ); };\nvar bool = iterAnyBy( arr, fcn )\n","iterAsin":"var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAsinh":"var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan":"var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan2":"var x = random.iterators.uniform( -2.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterAtan2( y, x );\nvar r = it.next().value\nr = it.next().value\n","iterAtanh":"var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterator2array":"var opts = { 'iter': 10 };\nvar arr = iterator2array( random.iterators.randu( opts ) )\n","iterator2arrayview":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayview( it, out, 5, 15 )\n","iterator2arrayviewRight":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayviewRight( it, out, 5, 15 )\n","iteratorStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream( it );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","iteratorStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = iteratorStream.factory( opts );\n","iteratorStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream.objectMode( it );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","IteratorSymbol":"var s = IteratorSymbol\n","iterAvercos":"var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAversin":"var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterawgn":"var src = iterSineWave();\nvar it = iterawgn( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawln":"var src = iterSineWave();\nvar it = iterawln( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawun":"var src = iterSineWave();\nvar it = iterawun( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterBartlettHannPulse":"var it = iterBartlettHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBartlettPulse":"var it = iterBartlettPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBesselj0":"var it = iterBesselj0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBesselj1":"var it = iterBesselj1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely0":"var it = iterBessely0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely1":"var it = iterBessely1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBeta":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBeta( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBetaln":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBetaln( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBinet":"var it = iterBinet( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCbrt":"var it = iterCbrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil":"var it = iterCeil( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil2":"var it = iterCeil2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil10":"var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterCompositesSeq":"var it = iterCompositesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterConcat":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = array2iterator( [ 3, 4 ] );\nvar it = iterConcat( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterConstant":"var it = iterConstant( 3.14 );\nvar v = it.next().value\nv = it.next().value\n","iterContinuedFraction":"var terms = array2iterator( [ 3, 4, 12, 4 ] );\nvar v = iterContinuedFraction( terms )\n","iterContinuedFractionSeq":"var it = iterContinuedFractionSeq( 3.245 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\nit = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n","iterCos":"var it = iterCos( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCosh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterCosh( r );\nvar v = it.next().value\nv = it.next().value\n","iterCosineWave":"var it = iterCosineWave();\nvar v = it.next().value\nv = it.next().value\n","iterCosm1":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCosm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterCospi":"var it = iterCospi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCounter":"var it = iterCounter( random.iterators.randu() );\nvar v = it.next().value\nv = it.next().value\n","iterCovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterCoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterCubesSeq":"var it = iterCubesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","itercugmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercugmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercuhmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercuhmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumax( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumaxabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumean( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs2( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumidrange( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumin( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuminabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuprod( arr );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itercurange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercurange( arr );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\nr = it.next().value\n","itercusum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusum( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs2( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterDatespace":"var t1 = new Date();\nvar it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\nvar v = it.next().value\nv = it.next().value\n","iterDedupe":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nvar it = iterDedupe( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDedupeBy":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nfunction fcn( v ) { return v; };\nvar it = iterDedupeBy( arr, fcn );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDeg2rad":"var r = random.iterators.uniform( -360.0, 360.0 );\nvar it = iterDeg2rad( r );\nvar v = it.next().value\nv = it.next().value\n","iterDigamma":"var r = random.iterators.uniform( 0.01, 5.0 );\nvar it = iterDigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterDiracComb":"var it = iterDiracComb();\nvar v = it.next().value\nv = it.next().value\n","iterDiracDelta":"var it = iterDiracDelta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterDivide":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterDivide( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterDoUntilEach":"function predicate( v ) { return v !== v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterDoUntilEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterDoWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterDoWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterEllipe":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipe( r );\nvar v = it.next().value\nv = it.next().value\n","iterEllipk":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipk( r );\nvar v = it.next().value\nv = it.next().value\n","iterEmpty":"var it = iterEmpty();\nvar bool = it.next().done\n","iterErf":"var it = iterErf( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfc":"var it = iterErfc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfcinv":"var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterErfinv":"var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterEta":"var it = iterEta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterEvenIntegersSeq":"var it = iterEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterEvery":"var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\nvar bool = iterEvery( arr )\n","iterEveryBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterEveryBy( arr, fcn )\n","iterExp":"var it = iterExp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterExp2":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp2( r );\nvar v = it.next().value\nv = it.next().value\n","iterExp10":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp10( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterExpit( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterExpm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1rel":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExpm1rel( r );\nvar v = it.next().value\nv = it.next().value\n","iterFactorial":"var it = iterFactorial( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialln":"var it = iterFactorialln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialsSeq":"var it = iterFactorialsSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFibonacciSeq":"var it = iterFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterFifthPowersSeq":"var it = iterFifthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFill":"var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterFilter":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilter( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFilterMap":"function f( v ) { if ( v > 2 ) { return v * 10 }; };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilterMap( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFirst":"var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\nvar v = iterFirst( arr )\n","iterFlatTopPulse":"var it = iterFlatTopPulse();\nvar v = it.next().value\nv = it.next().value\n","iterFloor":"var it = iterFloor( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFloor2":"var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFloor10":"var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFlow":"var o = {};\no.head = iterHead;\no.some = iterSome;\nvar fiter = iterFlow( o )\n","iterForEach":"function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterForEach( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterFourthPowersSeq":"var it = iterFourthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFresnelc":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnelc( r );\nvar v = it.next().value\nv = it.next().value\n","iterFresnels":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnels( r );\nvar v = it.next().value\nv = it.next().value\n","iterGamma":"var it = iterGamma( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterGamma1pm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterGamma1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterGammaln":"var it = iterGammaln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterHacovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHacoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHannPulse":"var it = iterHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterHavercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHavercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHaversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHaversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHead":"var it = iterHead( random.iterators.randu(), 5 );\nvar r = it.next().value\nr = it.next().value\n","iterIncrspace":"var it = iterIncrspace( 0, 101, 2 );\nvar v = it.next().value\nv = it.next().value\n","iterIntegersSeq":"var it = iterIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterIntersection":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterIntersection( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterIntersectionByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nfunction f( v ) { return v.toString(); };\nvar it = iterIntersectionByHash( it1, it2, f );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterInv":"var it = iterInv( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLanczosPulse":"var it = iterLanczosPulse();\nvar v = it.next().value\nv = it.next().value\n","iterLast":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar v = iterLast( arr )\n","iterLength":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar len = iterLength( arr )\n","iterLinspace":"var it = iterLinspace( 0, 99, 100 );\nvar v = it.next().value\nv = it.next().value\n","iterLn":"var it = iterLn( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog":"var x = random.iterators.uniform( 0.0, 100.0 );\nvar y = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterLog( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterLog1mexp":"var it = iterLog1mexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1p":"var it = iterLog1p( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1pexp":"var it = iterLog1pexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog2":"var it = iterLog2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog10":"var it = iterLog10( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLogit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterLogit( r );\nvar v = it.next().value\nv = it.next().value\n","iterLogspace":"var it = iterLogspace( 0, 3, 4 );\nvar v = it.next().value\nv = it.next().value\n","iterLucasSeq":"var it = iterLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterMap":"function f( v ) { return v * 10.0; };\nvar it = iterMap( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterMapN":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nfunction fcn( x, y ) { return x + y; };\nvar it = iterMapN( it1, it2, fcn );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermax":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermax( arr )\n","itermaxabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermaxabs( arr )\n","itermean":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = itermean( arr )\n","itermeanabs":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs( arr )\n","itermeanabs2":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs2( arr )\n","itermidrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = itermidrange( arr )\n","itermin":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermin( arr )\n","iterminabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = iterminabs( arr )\n","itermmax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmax( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmaxabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmean( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs2( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmidrange( arr, 3 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itermmin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmin( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermminabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","iterMod":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterMod( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermprod( arr, 3 );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itermrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermrange( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermsum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsum( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs2( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterMultiply":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterMultiply( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterNegaFibonacciSeq":"var it = iterNegaFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegaLucasSeq":"var it = iterNegaLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeEvenIntegersSeq":"var it = iterNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeIntegersSeq":"var it = iterNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeOddIntegersSeq":"var it = iterNegativeOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNone":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterNone( arr )\n","iterNoneBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v <= 0 ); };\nvar bool = iterNoneBy( arr, fcn )\n","iterNonFibonacciSeq":"var it = iterNonFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeEvenIntegersSeq":"var it = iterNonNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeIntegersSeq":"var it = iterNonNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveEvenIntegersSeq":"var it = iterNonPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveIntegersSeq":"var it = iterNonPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonSquaresSeq":"var it = iterNonSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterNth":"var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\nvar v = iterNth( arr, 3 )\n","iterOddIntegersSeq":"var it = iterOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterPeriodicSinc":"var it = iterPeriodicSinc( 7 );\nvar v = it.next().value\nv = it.next().value\n","iterPipeline":"var it1 = iterThunk( iterHead, 100 );\nfunction f( r ) { return ( r > 0.95 ); };\nvar it2 = iterThunk( iterSomeBy, 5, f );\nvar p = iterPipeline( it1, it2 );\nvar bool = p( random.iterators.randu() )\n","iterPop":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPop( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterPositiveEvenIntegersSeq":"var it = iterPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveIntegersSeq":"var it = iterPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveOddIntegersSeq":"var it = iterPositiveOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPow":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterPow( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterPrimesSeq":"var it = iterPrimesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterprod":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = iterprod( arr )\n","iterPulse":"var it = iterPulse();\nvar v = it.next().value\nv = it.next().value\n","iterPush":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPush( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterRad2deg":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterRad2deg( r );\nvar v = it.next().value\nv = it.next().value\n","iterRamp":"var it = iterRamp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = iterrange( arr )\n","iterReject":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterReject( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterReplicate":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nvar it2 = iterReplicate( it1, 2 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterReplicateBy":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nfunction f( v, i ) { return i + 1; };\nvar it2 = iterReplicateBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterRound":"var it = iterRound( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterRound2":"var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRound10":"var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRsqrt":"var it = iterRsqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSawtoothWave":"var it = iterSawtoothWave();\nvar v = it.next().value\nv = it.next().value\n","iterShift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterShift( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterSignum":"var it = iterSignum( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSin":"var it = iterSin( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSinc":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinc( r );\nvar v = it.next().value\nv = it.next().value\n","iterSineWave":"var it = iterSineWave();\nvar v = it.next().value\nv = it.next().value\n","iterSinh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinh( r );\nvar v = it.next().value\nv = it.next().value\n","iterSinpi":"var it = iterSinpi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSlice":"var it = iterSlice( random.iterators.randu(), 5, 10 );\nvar r = it.next().value\nr = it.next().value\n","iterSome":"var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = iterSome( arr, 3 )\n","iterSomeBy":"var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterSomeBy( arr, 3, fcn )\n","iterSpence":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSpence( r );\nvar v = it.next().value\nv = it.next().value\n","iterSqrt":"var it = iterSqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSqrt1pm1":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSqrt1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterSquaredTriangularSeq":"var it = iterSquaredTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquaresSeq":"var it = iterSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquareWave":"var it = iterSquareWave();\nvar v = it.next().value\nv = it.next().value\n","iterstdev":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar m = iterstdev( arr )\n","iterStep":"var it = iterStep( 0, 2, 10 );\nvar v = it.next().value\nv = it.next().value\n","iterStrided":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nvar it = iterStrided( arr, 2, 1 );\nvar r = it.next().value\nr = it.next().value\n","iterStridedBy":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nfunction stride( v, i ) { return (i % 10)+1; };\nvar it = iterStridedBy( arr, stride );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterSubtract":"var it1 = array2iterator( [ 1.0, 5.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterSubtract( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itersum":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = itersum( arr )\n","itersumabs":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs( arr )\n","itersumabs2":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs2( arr )\n","iterTan":"var r = random.iterators.uniform( -1.57, 1.57 );\nvar it = iterTan( r );\nvar v = it.next().value\nv = it.next().value\n","iterTanh":"var r = random.iterators.uniform( -4.0, 4.0 );\nvar it = iterTanh( r );\nvar v = it.next().value\nv = it.next().value\n","iterThunk":"var fcn = iterThunk( iterSome, 3 );\nvar arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = fcn( arr )\n","iterTriangleWave":"var it = iterTriangleWave();\nvar v = it.next().value\nv = it.next().value\n","iterTriangularSeq":"var it = iterTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterTribonnaciSeq":"var it = iterTribonnaciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterTrigamma":"var r = random.iterators.uniform( 0.01, 50.0 );\nvar it = iterTrigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterTrunc":"var it = iterTrunc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc2":"var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc10":"var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterUnion":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterUnion( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterUnique":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = iterUnique( it1 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueBy":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( a, b ) { return ( a !== b ); };\nvar it2 = iterUniqueBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( v ) { return v.toString(); };\nvar it2 = iterUniqueByHash( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUnitspace":"var it = iterUnitspace( 0, 99 );\nvar v = it.next().value\nv = it.next().value\n","iterUnshift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterUnshift( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUntilEach":"function predicate( v ) { return v !== v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterUntilEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","itervariance":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar s2 = itervariance( arr )\n","iterVercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterVersin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVersin( r );\nvar v = it.next().value\nv = it.next().value\n","iterWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterZeta":"var r = random.iterators.uniform( 1.1, 50.0 );\nvar it = iterZeta( r );\nvar v = it.next().value\nv = it.next().value\n","joinStream":"var s = joinStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = joinStream.factory( opts );\nvar s = createStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.objectMode":"var s = joinStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","kde2d":"var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\nvar y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\nvar out = kde2d( x, y )\n","kebabcase":"var out = kebabcase( 'Hello World!' )\nout = kebabcase( 'I am a tiny little teapot' )\n","keyBy":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyBy( arr, toKey )\n","keyByRight":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyByRight( arr, toKey )\n","keysIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = keysIn( obj )\n","kruskalTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = kruskalTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = kruskalTest( arr, { 'groups': groups } )\n","kstest":"var rnorm = base.random.normal.factory({ 'seed': 4839 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\nvar out = kstest( x, 'normal', 0.0, 1.0 )\nout = kstest( x, 'normal', 3.0, 1.0 )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0 )\nout.print()\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\nx = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\nout = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n","last":"var out = last( 'beep' )\nout = last( 'Boop', 2 )\nout = last( 'foo bar', 3 )\n","leveneTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = leveneTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = leveneTest( arr, { 'groups': groups } )\n","LinkedList":"var list = LinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","linspace":"var arr = linspace( 0.0, 100.0, 6 )\narr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\narr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n","linspace.assign":"var arr = [ 0, 0, 0, 0, 0, 0 ];\nvar out = linspace.assign( 0, 100, arr )\nvar bool = ( arr === out )\narr = [ 0, 0, 0, 0, 0 ];\nout = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n","LIU_NEGATIVE_OPINION_WORDS_EN":"var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n","LIU_POSITIVE_OPINION_WORDS_EN":"var list = LIU_POSITIVE_OPINION_WORDS_EN()\n","LN_HALF":"LN_HALF\n","LN_PI":"LN_PI\n","LN_SQRT_TWO_PI":"LN_SQRT_TWO_PI\n","LN_TWO_PI":"LN_TWO_PI\n","LN2":"LN2\n","LN10":"LN10\n","LOG2E":"LOG2E\n","LOG10E":"LOG10E\n","logspace":"var arr = logspace( 0, 2, 6 )\n","lowercase":"var out = lowercase( 'bEEp' )\n","lowercaseKeys":"var obj = { 'A': 1, 'B': 2 };\nvar out = lowercaseKeys( obj )\n","lowess":"var x = new Float64Array( 100 );\nvar y = new Float64Array( x.length );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = i;\n y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n }\nvar out = lowess( x, y );\nvar yhat = out.y;\nvar h = Plot( [ x, x ], [ y, yhat ] );\nh.lineStyle = [ 'none', '-' ];\nh.symbols = [ 'closed-circle', 'none' ];\nh.view( 'window' );\n","lpad":"var out = lpad( 'a', 5 )\nout = lpad( 'beep', 10, 'b' )\nout = lpad( 'boop', 12, 'beep' )\n","ltrim":"var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n","ltrimN":"var out = ltrimN( ' abc ', 2 )\nvar out = ltrimN( '!!!abc!!!', 2, '!' )\n","MALE_FIRST_NAMES_EN":"var list = MALE_FIRST_NAMES_EN()\n","map":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = map( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = map( arr, f );\nvar v = out.get( 1, 1 )\n","map.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","map2":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2( x, y, f );\nvar v = out.get( 1, 1 )\n","map2.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map2d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\nvar out = map2d( arr, f );\nout[ 0 ]\nout[ 1 ]\n","map2Right":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2Right( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2Right( x, y, f );\nvar v = out.get( 1, 1 )\n","map2Right.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2Right.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2Right.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map3d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\nvar out = map3d( arr, f );\nout[ 0 ][ 0 ]\nout[ 1 ][ 0 ]\n","map4d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\nvar out = map4d( arr, f );\nout[ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ]\n","map5d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\nvar out = map5d( arr, f );\nout[ 0 ][ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ][ 0 ]\n","mapArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nfunction clbk( v ) { return v * 2; };\nvar bar = mapArguments( foo, clbk );\nvar out = bar( 1, 2, 3 )\n","mapFun":"function fcn( i ) { return i; };\nvar arr = mapFun( fcn, 5 )\n","mapFunAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nmapFunAsync( fcn, 10, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nvar opts = { 'limit': 2 };\nmapFunAsync( fcn, 10, opts, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nvar opts = { 'series': true };\nmapFunAsync( fcn, 10, opts, done )\n","mapFunAsync.factory":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nvar opts = { 'series': true };\nvar f = mapFunAsync.factory( opts, fcn );\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nf( 10, done )\n","mapKeys":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapKeys( obj, transform )\n","mapKeysAsync":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapKeysAsync( obj, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n","mapKeysAsync.factory":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapKeysAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","mapReduce":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduce( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduce( arr, 0.0, f1, f2 )\n","mapReduceRight":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduceRight( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduceRight( arr, 0.0, f1, f2 )\n","mapRight":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = mapRight( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapRight( arr, f );\nvar v = out.get( 1, 1 )\n","mapRight.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmapRight.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmapRight.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","mapValues":"function transform( value, key ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapValues( obj, transform )\n","mapValuesAsync":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapValuesAsync( obj, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n","mapValuesAsync.factory":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapValuesAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","maskArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = maskArguments( foo, [ 1, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","MAX_ARRAY_LENGTH":"MAX_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"MAX_TYPED_ARRAY_LENGTH\n","maybeBroadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","maybeBroadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = maybeBroadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","memoize":"function factorial( n ) {\n var prod;\n var i;\n prod = 1;\n for ( i = n; i > 1; i-- ) {\n prod *= i;\n }\n return prod;\n };\nvar memoized = memoize( factorial );\nvar v = memoized( 5 )\nv = memoized( 5 )\n","merge":"var target = { 'a': 'beep' };\nvar source = { 'a': 'boop', 'b': 'bap' };\nvar out = merge( target, source )\nvar bool = ( out === target )\n","merge.factory":"var opts = {\n 'level': 100,\n 'copy': true,\n 'override': true,\n 'extend': true\n };\nvar merge = merge.factory( opts )\nmerge = merge.factory( { 'level': 2 } );\nvar target = {\n '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n };\nvar source = {\n '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n };\nvar out = merge( target, source )\nmerge = merge.factory( { 'copy': false } );\ntarget = {};\nsource = { 'a': [ 1, 2, 3 ] };\nout = merge( target, source );\nvar bool = ( out.a === source.a )\nmerge = merge.factory( { 'override': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'a': null, 'c': 'bop' };\nout = merge( target, source )\nfunction strategy( a, b, key ) {\n // a => target value\n // b => source value\n // key => object key\n if ( key === 'a' ) {\n return b;\n }\n if ( key === 'b' ) {\n return a;\n }\n return 'bebop';\n };\nmerge = merge.factory( { 'override': strategy } );\ntarget = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\nsource = { 'a': null, 'b': {}, 'c': 'bop' };\nout = merge( target, source )\nmerge = merge.factory( { 'extend': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'b': 'hello', 'c': 'world' };\nout = merge( target, source )\n","MILLISECONDS_IN_DAY":"var days = 3.14;\nvar ms = days * MILLISECONDS_IN_DAY\n","MILLISECONDS_IN_HOUR":"var hrs = 3.14;\nvar ms = hrs * MILLISECONDS_IN_HOUR\n","MILLISECONDS_IN_MINUTE":"var mins = 3.14;\nvar ms = mins * MILLISECONDS_IN_MINUTE\n","MILLISECONDS_IN_SECOND":"var secs = 3.14;\nvar ms = secs * MILLISECONDS_IN_SECOND\n","MILLISECONDS_IN_WEEK":"var weeks = 3.14;\nvar ms = weeks * MILLISECONDS_IN_WEEK\n","MINARD_NAPOLEONS_MARCH":"var data = MINARD_NAPOLEONS_MARCH();\nvar army = data.army\nvar cities = data.cities\nvar labels = data.labels\nvar rivers = data.rivers\nvar t = data.temperature\n","MINUTES_IN_DAY":"var days = 3.14;\nvar mins = days * MINUTES_IN_DAY\n","MINUTES_IN_HOUR":"var hrs = 3.14;\nvar mins = hrs * MINUTES_IN_HOUR\n","MINUTES_IN_WEEK":"var wks = 3.14;\nvar mins = wks * MINUTES_IN_WEEK\n","minutesInMonth":"var num = minutesInMonth()\nnum = minutesInMonth( 2 )\nnum = minutesInMonth( 2, 2016 )\nnum = minutesInMonth( 2, 2017 )\nnum = minutesInMonth( 'feb', 2016 )\nnum = minutesInMonth( 'february', 2016 )\n","minutesInYear":"var num = minutesInYear()\nnum = minutesInYear( 2016 )\nnum = minutesInYear( 2017 )\n","MOBY_DICK":"var data = MOBY_DICK()\n","MONTH_NAMES_EN":"var list = MONTH_NAMES_EN()\n","MONTHS_IN_YEAR":"var yrs = 3.14;\nvar mons = yrs * MONTHS_IN_YEAR\n","moveProperty":"var obj1 = { 'a': 'b' };\nvar obj2 = {};\nvar bool = moveProperty( obj1, 'a', obj2 )\nbool = moveProperty( obj1, 'c', obj2 )\n","MultiSlice":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\n","MultiSlice.prototype.ndims":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.ndims\n","MultiSlice.prototype.data":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.data\n","MultiSlice.prototype.toString":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.toString()\n","MultiSlice.prototype.toJSON":"var s = new Slice( 2, 10, 1 );\nvar ms = new MultiSlice( 2, s );\nms.toJSON()\n","namedtypedtuple":"var opts = {};\nopts.name = 'Point';\nvar factory = namedtypedtuple( [ 'x', 'y' ], opts );\nvar tuple = factory();\n","NAN":"NAN\n","naryFunction":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = naryFunction( foo, 2 );\nvar out = bar( 1, 2, 3 )\n","nativeClass":"var str = nativeClass( 'a' )\nstr = nativeClass( 5 )\nfunction Beep(){};\nstr = nativeClass( new Beep() )\n","ndarray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","ndarray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","ndarray2array":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2array( arr )\n","ndarray2fancy":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar arr = ndarray2fancy( x );\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray2fancy.factory":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar f = ndarray2fancy.factory();\nvar y = f( x );\n","ndarray2fancy.idx":"var opts = { 'dtype': 'int32' };\nvar buf = new Int32Array( [ 1, 2, 3, 4 ] );\nvar arr = array( buf, opts );\nvar idx = ndarray2fancy.idx( arr );\n","ndarray2json":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2json( arr )\n","ndarrayCastingModes":"var out = ndarrayCastingModes()\n","ndarrayDataBuffer":"var opts = { 'dtype': 'float64' };\nvar out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataType":"var opts = { 'dtype': 'float64' };\nvar dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataTypes":"var out = ndarrayDataTypes()\nout = ndarrayDataTypes( 'floating_point' )\nout = ndarrayDataTypes( 'floating_point_and_generic' )\n","ndarrayDataTypes.binary":"var dt = ndarrayDataTypes.binary\n","ndarrayDataTypes.boolean":"var dt = ndarrayDataTypes.boolean\n","ndarrayDataTypes.complex32":"var dt = ndarrayDataTypes.complex32\n","ndarrayDataTypes.complex64":"var dt = ndarrayDataTypes.complex64\n","ndarrayDataTypes.complex128":"var dt = ndarrayDataTypes.complex128\n","ndarrayDataTypes.float16":"var dt = ndarrayDataTypes.float16\n","ndarrayDataTypes.float32":"var dt = ndarrayDataTypes.float32\n","ndarrayDataTypes.float64":"var dt = ndarrayDataTypes.float64\n","ndarrayDataTypes.generic":"var dt = ndarrayDataTypes.generic\n","ndarrayDataTypes.int8":"var dt = ndarrayDataTypes.int8\n","ndarrayDataTypes.int16":"var dt = ndarrayDataTypes.int16\n","ndarrayDataTypes.int32":"var dt = ndarrayDataTypes.int32\n","ndarrayDataTypes.uint8":"var dt = ndarrayDataTypes.uint8\n","ndarrayDataTypes.uint8c":"var dt = ndarrayDataTypes.uint8c\n","ndarrayDataTypes.uint16":"var dt = ndarrayDataTypes.uint16\n","ndarrayDataTypes.uint32":"var dt = ndarrayDataTypes.uint32\n","ndarrayDispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\nvar xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\nf( x, y );\nybuf\n","ndarrayFlag":"var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n","ndarrayFlags":"var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayIndexModes":"var out = ndarrayIndexModes()\n","ndarraylike2ndarray":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarraylike2ndarray( arr )\n","ndarrayMinDataType":"var dt = ndarrayMinDataType( 3.141592653589793 )\ndt = ndarrayMinDataType( 3 )\ndt = ndarrayMinDataType( -3 )\ndt = ndarrayMinDataType( '-3' )\n","ndarrayMostlySafeCasts":"var out = ndarrayMostlySafeCasts( 'float32' )\n","ndarrayNextDataType":"var out = ndarrayNextDataType( 'float32' )\n","ndarrayOffset":"var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayOrder":"var opts = { 'order': 'row-major' };\nvar dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayOrders":"var out = ndarrayOrders()\n","ndarrayPromotionRules":"var out = ndarrayPromotionRules( 'float32', 'int32' )\n","ndarraySafeCasts":"var out = ndarraySafeCasts( 'float32' )\n","ndarraySameKindCasts":"var out = ndarraySameKindCasts( 'float32' )\n","ndarrayShape":"var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayStride":"var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n","ndarrayStrides":"var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n","ndat":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nndat( x, 0, 1 )\nndat( x, 1, 0 )\n","ndempty":"var arr = ndempty( [ 2, 2 ] )\n","ndemptyLike":"var x = ndzeros( [ 2, 2 ] )\nvar y = ndemptyLike( x )\n","ndfill":"var opts = { 'dtype': 'float64' };\nvar x = ndzeros( [ 2, 2 ], opts );\nx.get( 0, 0 )\nndfill( x, 10.0 );\nx.get( 0, 0 )\n","ndfillBy":"var opts = { 'dtype': 'float64' };\nvar x = ndzeros( [ 2, 2 ], opts );\nx.get( 0, 0 )\nfunction fcn() { return 10.0; };\nndfillBy( x, fcn );\nx.get( 0, 0 )\nx.get( 0, 1 )\nx.get( 1, 0 )\nx.get( 1, 1 )\n","ndfilter":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v > 2.0; };\nvar y = ndfilter( x, f )\n","ndfilterMap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\nvar y = ndfilterMap( x, f )\n","ndforEach":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\nndforEach( x, f );\n","ndims":"var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n","ndindex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\n","ndindex.free":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.free( idx.id )\n","ndindex.get":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.get( idx.id )\n","ndindex.cartesianIndex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = ndindex.cartesianIndex( x );\n","ndindex.linearIndex":"var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\nvar idx = ndindex.linearIndex( x );\n","ndindex.prototype.data":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.data\n","ndindex.prototype.dtype":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.dtype\n","ndindex.prototype.id":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.id\n","ndindex.prototype.isCached":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.isCached\n","ndindex.prototype.kind":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x, { 'kind': 'cartesian' } );\nidx.kind\n","ndindex.prototype.type":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.type\n","ndindex.prototype.toString":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toString()\n","ndindex.prototype.toJSON":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toJSON()\n","nditer2arrayEach":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditer2arrayEach( nditerRows( x ) );\nvar v = it.next().value\nv = it.next().value\n","nditerColumnEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumnEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerColumns":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumns( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerEntries( x );\nvar v = it.next().value\nv = it.next().value\n","nditerIndices":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerIndices( x.shape );\nvar v = it.next().value\nv = it.next().value\n","nditerInterleaveSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerInterleaveSubarrays( [ x, x ], 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrices":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrices( x );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrixEntries":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrixEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRowEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRowEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRows":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRows( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerSelectDimension":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSelectDimension( x, 0 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerStacks":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerStacks( x, [ 1, 2 ] );\nvar v = it.next().value;\nndarray2array( v )\n","nditerSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSubarrays( x, 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerValues":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerValues( x );\nvar v = it.next().value\nv = it.next().value\n","ndmap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v*10.0; };\nvar y = ndmap( x, f )\n","ndreject":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v <= 2.0; };\nvar y = ndreject( x, f );\nndarray2array( y )\n","ndslice":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar s = new MultiSlice( null, 1 )\nvar y = ndslice( x, s )\ny.shape\nndarray2array( y )\n","ndsliceAssign":"var y = ndzeros( [ 2, 2 ] )\nvar x = scalar2ndarray( 3.0 )\nvar s = new MultiSlice( null, 1 )\nvar out = ndsliceAssign( x, y, s )\nvar bool = ( out === y )\nndarray2array( y )\n","ndsliceDimension":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimension( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionFrom( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceFrom( x, 0, 1 )\ny.shape\nndarray2array( y )\n","ndsliceTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndzeros":"var arr = ndzeros( [ 2, 2 ] )\n","ndzerosLike":"var x = ndzeros( [ 2, 2 ] )\nvar y = ndzerosLike( x )\n","nextGraphemeClusterBreak":"var out = nextGraphemeClusterBreak( 'last man standing', 4 )\nout = nextGraphemeClusterBreak( 'presidential election', 8 )\nout = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\nout = nextGraphemeClusterBreak( '🌷' )\n","nextTick":"function f() { console.log( 'beep' ); };\nnextTick( f )\n","NIGHTINGALES_ROSE":"var data = NIGHTINGALES_ROSE()\n","NINF":"NINF\n","NODE_VERSION":"NODE_VERSION\n","none":"var arr = [ 0, 0, 0, 0, 0 ];\nvar bool = none( arr )\n","noneBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = noneBy( arr, negative )\n","noneByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n","noneByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","noneByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ -1, -2, -3, -4 ];\nvar bool = noneByRight( arr, positive )\n","noneByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n","noneByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","noneInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 4 };\nvar bool = noneInBy( obj, negative )\n","nonEnumerableProperties":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar props = nonEnumerableProperties( obj )\n","nonEnumerablePropertiesIn":"var props = nonEnumerablePropertiesIn( [] )\n","nonEnumerablePropertyNames":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNames( obj )\n","nonEnumerablePropertyNamesIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNamesIn( obj )\n","nonEnumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbols( obj )\n","nonEnumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbolsIn( obj )\n","noneOwnBy":"function isUnderage( v ) { return ( v < 18 ); };\nvar obj = { 'a': 11, 'b': 12, 'c': 22 };\nvar bool = noneOwnBy( obj, isUnderage )\n","nonIndexKeys":"function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = nonIndexKeys( obj )\n","noop":"noop();\n","now":"var ts = now()\n","NUM_CPUS":"NUM_CPUS\n","num2words":"var out = num2words( 123 )\nout = num2words( 16.31 )\nout = num2words( 123, { 'lang': 'de' } )\n","Number":"var v = new Number( 5 )\n","numel":"var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n","numelDimension":"var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n","numGraphemeClusters":"var out = numGraphemeClusters( 'beep' )\nout = numGraphemeClusters( '🌷' )\n","Object":"var o = new Object( null )\no = new Object( 5.0 )\no = new Object( 'beep' )\n","Object.assign":"var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n","Object.create":"var o = Object.create( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperties":"var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperty":"var o = Object.defineProperty( {}, 'a', {\n","Object.entries":"var o = Object.entries( { 'a': 1, 'b': 2 } )\n","Object.freeze":"var o = Object.freeze( { 'a': 1 } )\n","Object.getOwnPropertyDescriptor":"var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n","Object.getOwnPropertyDescriptors":"var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertyNames":"var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertySymbols":"var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n","Object.getPrototypeOf":"var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n","Object.hasOwn":"var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n","Object.is":"var o = Object.is( 1, 1 )\nvar o = Object.is( 1, '1' )\n","Object.isExtensible":"var o = Object.isExtensible( { 'a': 1 } )\n","Object.isFrozen":"var o = Object.isFrozen( { 'a': 1 } )\nvar o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n","Object.isSealed":"var o = Object.isSealed( { 'a': 1 } )\nvar o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n","Object.keys":"var o = Object.keys( { 'a': 1, 'b': 2 } )\n","Object.preventExtensions":"var o = Object.preventExtensions( { 'a': 1 } )\no.b = 2;\no\n","Object.seal":"var o = Object.seal( { 'a': 1 } )\no.b = 2;\no\ndelete o.a;\no\n","Object.setPrototypeOf":"var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\no.b\n","Object.values":"var o = Object.values( { 'a': 1, 'b': 2 } )\n","Object.prototype.toLocaleString":"var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.toString":"var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.valueOf":"var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.hasOwnProperty":"var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n","Object.prototype.isPrototypeOf":"var p = { 'a': 1 };\nvar o = { '__proto__': p };\nvar b = o.isPrototypeOf( p );\n","Object.prototype.propertyIsEnumerable":"var o = { 'a': 1, 'b': 2 };\nvar bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n","Object.prototype.constructor":"var o = new Object( null );\nvar ctr = o.constructor;\n","objectEntries":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar entries = objectEntries( obj )\n","objectEntriesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar entries = objectEntriesIn( obj )\n","objectFromEntries":"var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\nvar obj = objectFromEntries( entries )\n","objectInverse":"var obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverse( obj )\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverse( obj )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverse( obj, { 'duplicates': false } )\n","objectInverseBy":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverseBy( obj, transform )\nfunction transform( key, value ) { return value; };\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverseBy( obj, transform )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverseBy( obj, { 'duplicates': false }, transform )\n","objectKeys":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = objectKeys( obj )\n","objectValues":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar vals = objectValues( obj )\n","objectValuesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar values = objectValuesIn( obj )\n","omit":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omit( obj1, 'b' )\n","omitBy":"function predicate( key, value ) { return ( value > 1 ); };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omitBy( obj1, predicate )\n","open":"function onOpen( error, fd ) {\n if ( error ) {\n console.error( error.message );\n } else {\n close.sync( fd );\n }\n };\nopen( './beep/boop.txt', onOpen );\n","open.sync":"var fd = open.sync( './beep/boop.txt' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","openURL":"var out = openURL( 'https://google.com' );\n","ordinalize":"var out = ordinalize( '1' )\nout = ordinalize( 2, { 'suffixOnly': true } )\nout = ordinalize( '3', { 'lang': 'es' } )\n","PACE_BOSTON_HOUSE_PRICES":"var data = PACE_BOSTON_HOUSE_PRICES()\n","pad":"var out = pad( 'a', 5 )\nout = pad( 'a', 10, { 'lpad': 'b' } )\nout = pad( 'a', 12, { 'rpad': 'b' } )\nvar opts = { 'lpad': 'a', 'rpad': 'c' };\nout = pad( 'b', 11, opts )\nopts.centerRight = false;\nout = pad( 'b', 10, opts )\nopts.centerRight = true;\nout = pad( 'b', 10, opts )\nopts = { 'lpad': 'boop', 'rpad': 'woot' };\nout = pad( 'beep', 10, opts )\nout = pad( 'beep', 2 )\nopts = { 'lpad': 'b' };\nout = pad( 'beep', 2, opts )\nopts = { 'lpad': '@', 'rpad': '!' };\nout = pad( 'beep', 2, opts )\nout = pad( 'abcdef', 3, opts )\nopts.centerRight = true;\nout = pad( 'abcdef', 3, opts )\n","padjust":"var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\nvar out = padjust( pvalues, 'bh' )\nout = padjust( pvalues, 'bonferroni' )\nout = padjust( pvalues, 'by' )\nout = padjust( pvalues, 'holm' )\nout = padjust( pvalues, 'hommel' )\n","papply":"function add( x, y ) { return x + y; };\nvar add2 = papply( add, 2 );\nvar sum = add2( 3 )\n","papplyRight":"function say( text, name ) { return text + ', ' + name + '.'; };\nvar toGrace = papplyRight( say, 'Grace Hopper' );\nvar str = toGrace( 'Hello' )\nstr = toGrace( 'Thank you' )\n","parseJSON":"var obj = parseJSON( '{\"beep\":\"boop\"}' )\nfunction reviver( key, value ) {\n if ( key === '' ) { return value; }\n if ( key === 'beep' ) { return value; }\n };\nvar str = '{\"beep\":\"boop\",\"a\":\"b\"}';\nvar out = parseJSON( str, reviver )\n","pascalcase":"var out = pascalcase( 'Hello World!' )\nout = pascalcase( 'beep boop' )\n","PATH_DELIMITER":"PATH_DELIMITER\nvar path = '/usr/bin:/bin:/usr/sbin';\nvar parts = path.split( PATH_DELIMITER )\npath = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\nparts = path.split( PATH_DELIMITER )\n","PATH_DELIMITER_POSIX":"PATH_DELIMITER_POSIX\nvar PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\nvar paths = PATH.split( PATH_DELIMITER_POSIX )\n","PATH_DELIMITER_WIN32":"PATH_DELIMITER_WIN32\nvar PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\nvar paths = PATH.split( PATH_DELIMITER_WIN32 )\n","PATH_SEP":"PATH_SEP\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\nparts = 'foo/bar/baz'.split( PATH_SEP )\n","PATH_SEP_POSIX":"PATH_SEP_POSIX\nvar parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n","PATH_SEP_WIN32":"PATH_SEP_WIN32\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n","pcorrtest":"var rho = 0.5;\nvar x = new Array( 300 );\nvar y = new Array( 300 );\nfor ( var i = 0; i < 300; i++ ) {\nx[ i ] = base.random.normal( 0.0, 1.0 );\ny[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\nbase.sqrt( 1.0 - (rho*rho) ) );\n }\nvar out = pcorrtest( x, y )\nvar table = out.print()\n","percentEncode":"var out = percentEncode( '☃' )\n","PHI":"PHI\n","PI":"PI\n","PI_SQUARED":"PI_SQUARED\n","pick":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pick( obj1, 'b' )\n","pickArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = pickArguments( foo, [ 0, 2 ] );\nvar out = bar( 1, 2, 3 )\n","pickBy":"function predicate( key, value ) {\n return ( value > 1 );\n };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pickBy( obj1, predicate )\n","PINF":"PINF\n","pkg2alias":"var v = pkg2alias( '@stdlib/math/base/special/sin' )\nv = pkg2alias( '@stdlib/math-base-special-sin' )\n","pkg2related":"var v = pkg2related( '@stdlib/math/base/special/sin' )\nv = pkg2related( '@stdlib/math-base-special-sin' )\n","pkg2standalone":"var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n","PLATFORM":"PLATFORM\n","plot":"var plot = plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n","Plot":"var plot = Plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n","pluck":"var arr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nvar out = pluck( arr, 'a' )\narr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nout = pluck( arr, 'a', { 'copy': false } )\nvar bool = ( arr[ 0 ] === out[ 0 ] )\n","pop":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = pop( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = pop( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = pop( arr )\n","porterStemmer":"var out = porterStemmer( 'walking' )\nout = porterStemmer( 'walked' )\nout = porterStemmer( 'walks' )\nout = porterStemmer( '' )\n","prepend":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = prepend( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = prepend( arr, [ 3.0, 4.0 ] )\narr = { 'length': 1, '0': 1.0 };\narr = prepend( arr, [ 2.0, 3.0 ] )\n","prevGraphemeClusterBreak":"var out = prevGraphemeClusterBreak( 'last man standing', 4 )\nout = prevGraphemeClusterBreak( 'presidential election', 8 )\nout = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\nout = prevGraphemeClusterBreak( '🌷', 1 )\n","PRIMES_100K":"var list = PRIMES_100K()\n","properties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = properties( obj )\n","propertiesIn":"var props = propertiesIn( [] )\n","propertyDescriptor":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptor( obj, 'a' )\n","propertyDescriptorIn":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptorIn( obj, 'a' )\n","propertyDescriptors":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptors( obj )\n","propertyDescriptorsIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = propertyDescriptorsIn( obj )\n","propertyNames":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNames( obj )\n","propertyNamesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNamesIn( obj )\n","propertySymbols":"var s = propertySymbols( {} )\n","propertySymbolsIn":"var s = propertySymbolsIn( [] )\n","Proxy":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = new Proxy( {}, h );\np.a = 3.14;\np.a\n","Proxy.revocable":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = Proxy.revocable( {}, h );\np.proxy.a = 3.14;\np.proxy.a\np.revoke();\n","push":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = push( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = push( arr, 3.0, 4.0 )\narr = { 'length': 0 };\narr = push( arr, 1.0, 2.0 )\n","quarterOfYear":"var q = quarterOfYear( new Date() )\nq = quarterOfYear( 4 )\nq = quarterOfYear( 'June' )\nq = quarterOfYear( 'April' )\nq = quarterOfYear( 'apr' )\n","random.array.arcsine":"var out = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.arcsine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.arcsine.factory":"var fcn = random.array.arcsine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.arcsine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.arcsine.PRNG":"var prng = random.array.arcsine.PRNG;\n","random.array.arcsine.seed":"var seed = random.array.arcsine.seed;\n","random.array.arcsine.seedLength":"var len = random.array.arcsine.seedLength;\n","random.array.arcsine.state":"var out = random.array.arcsine( 3, 2.0, 5.0 )\nvar state = random.array.arcsine.state\nout = random.array.arcsine( 3, 2.0, 5.0 )\nout = random.array.arcsine( 3, 2.0, 5.0 )\nrandom.array.arcsine.state = state;\nout = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.stateLength":"var len = random.array.arcsine.stateLength;\n","random.array.arcsine.byteLength":"var sz = random.array.arcsine.byteLength;\n","random.array.bernoulli":"var out = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.bernoulli.assign( 0.5, x )\nvar bool = ( out === x )\n","random.array.bernoulli.factory":"var fcn = random.array.bernoulli.factory();\nvar out = fcn( 3, 0.5 )\nfcn = random.array.bernoulli.factory( 0.5 );\nout = fcn( 3 )\n","random.array.bernoulli.PRNG":"var prng = random.array.bernoulli.PRNG;\n","random.array.bernoulli.seed":"var seed = random.array.bernoulli.seed;\n","random.array.bernoulli.seedLength":"var len = random.array.bernoulli.seedLength;\n","random.array.bernoulli.state":"var out = random.array.bernoulli( 3, 0.5 )\nvar state = random.array.bernoulli.state\nout = random.array.bernoulli( 3, 0.5 )\nout = random.array.bernoulli( 3, 0.5 )\nrandom.array.bernoulli.state = state;\nout = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.stateLength":"var len = random.array.bernoulli.stateLength;\n","random.array.bernoulli.byteLength":"var sz = random.array.bernoulli.byteLength;\n","random.array.beta":"var out = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.beta.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.beta.factory":"var fcn = random.array.beta.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.beta.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.beta.PRNG":"var prng = random.array.beta.PRNG;\n","random.array.beta.seed":"var seed = random.array.beta.seed;\n","random.array.beta.seedLength":"var len = random.array.beta.seedLength;\n","random.array.beta.state":"var out = random.array.beta( 3, 2.0, 5.0 )\nvar state = random.array.beta.state\nout = random.array.beta( 3, 2.0, 5.0 )\nout = random.array.beta( 3, 2.0, 5.0 )\nrandom.array.beta.state = state;\nout = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.stateLength":"var len = random.array.beta.stateLength;\n","random.array.beta.byteLength":"var sz = random.array.beta.byteLength;\n","random.array.betaprime":"var out = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.betaprime.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.betaprime.factory":"var fcn = random.array.betaprime.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.betaprime.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.betaprime.PRNG":"var prng = random.array.betaprime.PRNG;\n","random.array.betaprime.seed":"var seed = random.array.betaprime.seed;\n","random.array.betaprime.seedLength":"var len = random.array.betaprime.seedLength;\n","random.array.betaprime.state":"var out = random.array.betaprime( 3, 2.0, 5.0 )\nvar state = random.array.betaprime.state\nout = random.array.betaprime( 3, 2.0, 5.0 )\nout = random.array.betaprime( 3, 2.0, 5.0 )\nrandom.array.betaprime.state = state;\nout = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.stateLength":"var len = random.array.betaprime.stateLength;\n","random.array.betaprime.byteLength":"var sz = random.array.betaprime.byteLength;\n","random.array.binomial":"var out = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.binomial.assign( 17, 0.5, x )\nvar bool = ( out === x )\n","random.array.binomial.factory":"var fcn = random.array.binomial.factory();\nvar out = fcn( 3, 17, 0.5 )\nfcn = random.array.binomial.factory( 17, 0.5 );\nout = fcn( 3 )\n","random.array.binomial.PRNG":"var prng = random.array.binomial.PRNG;\n","random.array.binomial.seed":"var seed = random.array.binomial.seed;\n","random.array.binomial.seedLength":"var len = random.array.binomial.seedLength;\n","random.array.binomial.state":"var out = random.array.binomial( 3, 17, 0.5 )\nvar state = random.array.binomial.state\nout = random.array.binomial( 3, 17, 0.5 )\nout = random.array.binomial( 3, 17, 0.5 )\nrandom.array.binomial.state = state;\nout = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.stateLength":"var len = random.array.binomial.stateLength;\n","random.array.binomial.byteLength":"var sz = random.array.binomial.byteLength;\n","random.array.cauchy":"var out = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cauchy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cauchy.factory":"var fcn = random.array.cauchy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cauchy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cauchy.PRNG":"var prng = random.array.cauchy.PRNG;\n","random.array.cauchy.seed":"var seed = random.array.cauchy.seed;\n","random.array.cauchy.seedLength":"var len = random.array.cauchy.seedLength;\n","random.array.cauchy.state":"var out = random.array.cauchy( 3, 2.0, 5.0 )\nvar state = random.array.cauchy.state\nout = random.array.cauchy( 3, 2.0, 5.0 )\nout = random.array.cauchy( 3, 2.0, 5.0 )\nrandom.array.cauchy.state = state;\nout = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.stateLength":"var len = random.array.cauchy.stateLength;\n","random.array.cauchy.byteLength":"var sz = random.array.cauchy.byteLength;\n","random.array.chi":"var out = random.array.chi( 3, 2.0 )\n","random.array.chi.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chi.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chi.factory":"var fcn = random.array.chi.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chi.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chi.PRNG":"var prng = random.array.chi.PRNG;\n","random.array.chi.seed":"var seed = random.array.chi.seed;\n","random.array.chi.seedLength":"var len = random.array.chi.seedLength;\n","random.array.chi.state":"var out = random.array.chi( 3, 2.0 )\nvar state = random.array.chi.state\nout = random.array.chi( 3, 2.0 )\nout = random.array.chi( 3, 2.0 )\nrandom.array.chi.state = state;\nout = random.array.chi( 3, 2.0 )\n","random.array.chi.stateLength":"var len = random.array.chi.stateLength;\n","random.array.chi.byteLength":"var sz = random.array.chi.byteLength;\n","random.array.chisquare":"var out = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chisquare.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chisquare.factory":"var fcn = random.array.chisquare.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chisquare.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chisquare.PRNG":"var prng = random.array.chisquare.PRNG;\n","random.array.chisquare.seed":"var seed = random.array.chisquare.seed;\n","random.array.chisquare.seedLength":"var len = random.array.chisquare.seedLength;\n","random.array.chisquare.state":"var out = random.array.chisquare( 3, 2.0 )\nvar state = random.array.chisquare.state\nout = random.array.chisquare( 3, 2.0 )\nout = random.array.chisquare( 3, 2.0 )\nrandom.array.chisquare.state = state;\nout = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.stateLength":"var len = random.array.chisquare.stateLength;\n","random.array.chisquare.byteLength":"var sz = random.array.chisquare.byteLength;\n","random.array.cosine":"var out = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cosine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cosine.factory":"var fcn = random.array.cosine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cosine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cosine.PRNG":"var prng = random.array.cosine.PRNG;\n","random.array.cosine.seed":"var seed = random.array.cosine.seed;\n","random.array.cosine.seedLength":"var len = random.array.cosine.seedLength;\n","random.array.cosine.state":"var out = random.array.cosine( 3, 2.0, 5.0 )\nvar state = random.array.cosine.state\nout = random.array.cosine( 3, 2.0, 5.0 )\nout = random.array.cosine( 3, 2.0, 5.0 )\nrandom.array.cosine.state = state;\nout = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.stateLength":"var len = random.array.cosine.stateLength;\n","random.array.cosine.byteLength":"var sz = random.array.cosine.byteLength;\n","random.array.discreteUniform":"var out = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.discreteUniform.assign( -10, 10, x )\nvar bool = ( out === x )\n","random.array.discreteUniform.factory":"var fcn = random.array.discreteUniform.factory();\nvar out = fcn( 3, -10, 10 )\nfcn = random.array.discreteUniform.factory( -10, 10 );\nout = fcn( 3 )\n","random.array.discreteUniform.PRNG":"var prng = random.array.discreteUniform.PRNG;\n","random.array.discreteUniform.seed":"var seed = random.array.discreteUniform.seed;\n","random.array.discreteUniform.seedLength":"var len = random.array.discreteUniform.seedLength;\n","random.array.discreteUniform.state":"var out = random.array.discreteUniform( 3, -10, 10 )\nvar state = random.array.discreteUniform.state\nout = random.array.discreteUniform( 3, -10, 10 )\nout = random.array.discreteUniform( 3, -10, 10 )\nrandom.array.discreteUniform.state = state;\nout = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.stateLength":"var len = random.array.discreteUniform.stateLength;\n","random.array.discreteUniform.byteLength":"var sz = random.array.discreteUniform.byteLength;\n","random.array.erlang":"var out = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.erlang.assign( 2, 5.0, x )\nvar bool = ( out === x )\n","random.array.erlang.factory":"var fcn = random.array.erlang.factory();\nvar out = fcn( 3, 2, 5.0 )\nfcn = random.array.erlang.factory( 2, 5.0 );\nout = fcn( 3 )\n","random.array.erlang.PRNG":"var prng = random.array.erlang.PRNG;\n","random.array.erlang.seed":"var seed = random.array.erlang.seed;\n","random.array.erlang.seedLength":"var len = random.array.erlang.seedLength;\n","random.array.erlang.state":"var out = random.array.erlang( 3, 2, 5.0 )\nvar state = random.array.erlang.state\nout = random.array.erlang( 3, 2, 5.0 )\nout = random.array.erlang( 3, 2, 5.0 )\nrandom.array.erlang.state = state;\nout = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.stateLength":"var len = random.array.erlang.stateLength;\n","random.array.erlang.byteLength":"var sz = random.array.erlang.byteLength;\n","random.array.exponential":"var out = random.array.exponential( 3, 2.0 )\n","random.array.exponential.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.exponential.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.exponential.factory":"var fcn = random.array.exponential.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.exponential.factory( 2.0 );\nout = fcn( 3 )\n","random.array.exponential.PRNG":"var prng = random.array.exponential.PRNG;\n","random.array.exponential.seed":"var seed = random.array.exponential.seed;\n","random.array.exponential.seedLength":"var len = random.array.exponential.seedLength;\n","random.array.exponential.state":"var out = random.array.exponential( 3, 2.0 )\nvar state = random.array.exponential.state\nout = random.array.exponential( 3, 2.0 )\nout = random.array.exponential( 3, 2.0 )\nrandom.array.exponential.state = state;\nout = random.array.exponential( 3, 2.0 )\n","random.array.exponential.stateLength":"var len = random.array.exponential.stateLength;\n","random.array.exponential.byteLength":"var sz = random.array.exponential.byteLength;\n","random.array.f":"var out = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.f.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.f.factory":"var fcn = random.array.f.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.f.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.f.PRNG":"var prng = random.array.f.PRNG;\n","random.array.f.seed":"var seed = random.array.f.seed;\n","random.array.f.seedLength":"var len = random.array.f.seedLength;\n","random.array.f.state":"var out = random.array.f( 3, 2.0, 5.0 )\nvar state = random.array.f.state\nout = random.array.f( 3, 2.0, 5.0 )\nout = random.array.f( 3, 2.0, 5.0 )\nrandom.array.f.state = state;\nout = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.stateLength":"var len = random.array.f.stateLength;\n","random.array.f.byteLength":"var sz = random.array.f.byteLength;\n","random.array.frechet":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.frechet.factory":"var fcn = random.array.frechet.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.frechet.PRNG":"var prng = random.array.frechet.PRNG;\n","random.array.frechet.seed":"var seed = random.array.frechet.seed;\n","random.array.frechet.seedLength":"var len = random.array.frechet.seedLength;\n","random.array.frechet.state":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.frechet.state\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nrandom.array.frechet.state = state;\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.stateLength":"var len = random.array.frechet.stateLength;\n","random.array.frechet.byteLength":"var sz = random.array.frechet.byteLength;\n","random.array.gamma":"var out = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gamma.factory":"var fcn = random.array.gamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gamma.PRNG":"var prng = random.array.gamma.PRNG;\n","random.array.gamma.seed":"var seed = random.array.gamma.seed;\n","random.array.gamma.seedLength":"var len = random.array.gamma.seedLength;\n","random.array.gamma.state":"var out = random.array.gamma( 3, 2.0, 5.0 )\nvar state = random.array.gamma.state\nout = random.array.gamma( 3, 2.0, 5.0 )\nout = random.array.gamma( 3, 2.0, 5.0 )\nrandom.array.gamma.state = state;\nout = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.stateLength":"var len = random.array.gamma.stateLength;\n","random.array.gamma.byteLength":"var sz = random.array.gamma.byteLength;\n","random.array.geometric":"var out = random.array.geometric( 3, 0.01 )\n","random.array.geometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.geometric.assign( 0.01, x )\nvar bool = ( out === x )\n","random.array.geometric.factory":"var fcn = random.array.geometric.factory();\nvar out = fcn( 3, 0.01 )\nfcn = random.array.geometric.factory( 0.01 );\nout = fcn( 3 )\n","random.array.geometric.PRNG":"var prng = random.array.geometric.PRNG;\n","random.array.geometric.seed":"var seed = random.array.geometric.seed;\n","random.array.geometric.seedLength":"var len = random.array.geometric.seedLength;\n","random.array.geometric.state":"var out = random.array.geometric( 3, 0.01 )\nvar state = random.array.geometric.state\nout = random.array.geometric( 3, 0.01 )\nout = random.array.geometric( 3, 0.01 )\nrandom.array.geometric.state = state;\nout = random.array.geometric( 3, 0.01 )\n","random.array.geometric.stateLength":"var len = random.array.geometric.stateLength;\n","random.array.geometric.byteLength":"var sz = random.array.geometric.byteLength;\n","random.array.gumbel":"var out = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gumbel.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gumbel.factory":"var fcn = random.array.gumbel.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gumbel.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gumbel.PRNG":"var prng = random.array.gumbel.PRNG;\n","random.array.gumbel.seed":"var seed = random.array.gumbel.seed;\n","random.array.gumbel.seedLength":"var len = random.array.gumbel.seedLength;\n","random.array.gumbel.state":"var out = random.array.gumbel( 3, 2.0, 5.0 )\nvar state = random.array.gumbel.state\nout = random.array.gumbel( 3, 2.0, 5.0 )\nout = random.array.gumbel( 3, 2.0, 5.0 )\nrandom.array.gumbel.state = state;\nout = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.stateLength":"var len = random.array.gumbel.stateLength;\n","random.array.gumbel.byteLength":"var sz = random.array.gumbel.byteLength;\n","random.array.hypergeometric":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.hypergeometric.assign( 20, 10, 7, x )\nvar bool = ( out === x )\n","random.array.hypergeometric.factory":"var fcn = random.array.hypergeometric.factory();\nvar out = fcn( 3, 20, 10, 7 )\nfcn = random.array.hypergeometric.factory( 20, 10, 7 );\nout = fcn( 3 )\n","random.array.hypergeometric.PRNG":"var prng = random.array.hypergeometric.PRNG;\n","random.array.hypergeometric.seed":"var seed = random.array.hypergeometric.seed;\n","random.array.hypergeometric.seedLength":"var len = random.array.hypergeometric.seedLength;\n","random.array.hypergeometric.state":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\nvar state = random.array.hypergeometric.state\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nrandom.array.hypergeometric.state = state;\nout = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.stateLength":"var len = random.array.hypergeometric.stateLength;\n","random.array.hypergeometric.byteLength":"var sz = random.array.hypergeometric.byteLength;\n","random.array.invgamma":"var out = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.invgamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.invgamma.factory":"var fcn = random.array.invgamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.invgamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.invgamma.PRNG":"var prng = random.array.invgamma.PRNG;\n","random.array.invgamma.seed":"var seed = random.array.invgamma.seed;\n","random.array.invgamma.seedLength":"var len = random.array.invgamma.seedLength;\n","random.array.invgamma.state":"var out = random.array.invgamma( 3, 2.0, 5.0 )\nvar state = random.array.invgamma.state\nout = random.array.invgamma( 3, 2.0, 5.0 )\nout = random.array.invgamma( 3, 2.0, 5.0 )\nrandom.array.invgamma.state = state;\nout = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.stateLength":"var len = random.array.invgamma.stateLength;\n","random.array.invgamma.byteLength":"var sz = random.array.invgamma.byteLength;\n","random.array.kumaraswamy":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.kumaraswamy.factory":"var fcn = random.array.kumaraswamy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.kumaraswamy.PRNG":"var prng = random.array.kumaraswamy.PRNG;\n","random.array.kumaraswamy.seed":"var seed = random.array.kumaraswamy.seed;\n","random.array.kumaraswamy.seedLength":"var len = random.array.kumaraswamy.seedLength;\n","random.array.kumaraswamy.state":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\nvar state = random.array.kumaraswamy.state\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nrandom.array.kumaraswamy.state = state;\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.stateLength":"var len = random.array.kumaraswamy.stateLength;\n","random.array.kumaraswamy.byteLength":"var sz = random.array.kumaraswamy.byteLength;\n","random.array.laplace":"var out = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.laplace.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.laplace.factory":"var fcn = random.array.laplace.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.laplace.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.laplace.PRNG":"var prng = random.array.laplace.PRNG;\n","random.array.laplace.seed":"var seed = random.array.laplace.seed;\n","random.array.laplace.seedLength":"var len = random.array.laplace.seedLength;\n","random.array.laplace.state":"var out = random.array.laplace( 3, 2.0, 5.0 )\nvar state = random.array.laplace.state\nout = random.array.laplace( 3, 2.0, 5.0 )\nout = random.array.laplace( 3, 2.0, 5.0 )\nrandom.array.laplace.state = state;\nout = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.stateLength":"var len = random.array.laplace.stateLength;\n","random.array.laplace.byteLength":"var sz = random.array.laplace.byteLength;\n","random.array.levy":"var out = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.levy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.levy.factory":"var fcn = random.array.levy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.levy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.levy.PRNG":"var prng = random.array.levy.PRNG;\n","random.array.levy.seed":"var seed = random.array.levy.seed;\n","random.array.levy.seedLength":"var len = random.array.levy.seedLength;\n","random.array.levy.state":"var out = random.array.levy( 3, 2.0, 5.0 )\nvar state = random.array.levy.state\nout = random.array.levy( 3, 2.0, 5.0 )\nout = random.array.levy( 3, 2.0, 5.0 )\nrandom.array.levy.state = state;\nout = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.stateLength":"var len = random.array.levy.stateLength;\n","random.array.levy.byteLength":"var sz = random.array.levy.byteLength;\n","random.array.logistic":"var out = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.logistic.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.logistic.factory":"var fcn = random.array.logistic.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.logistic.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.logistic.PRNG":"var prng = random.array.logistic.PRNG;\n","random.array.logistic.seed":"var seed = random.array.logistic.seed;\n","random.array.logistic.seedLength":"var len = random.array.logistic.seedLength;\n","random.array.logistic.state":"var out = random.array.logistic( 3, 2.0, 5.0 )\nvar state = random.array.logistic.state\nout = random.array.logistic( 3, 2.0, 5.0 )\nout = random.array.logistic( 3, 2.0, 5.0 )\nrandom.array.logistic.state = state;\nout = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.stateLength":"var len = random.array.logistic.stateLength;\n","random.array.logistic.byteLength":"var sz = random.array.logistic.byteLength;\n","random.array.lognormal":"var out = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.lognormal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.lognormal.factory":"var fcn = random.array.lognormal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.lognormal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.lognormal.PRNG":"var prng = random.array.lognormal.PRNG;\n","random.array.lognormal.seed":"var seed = random.array.lognormal.seed;\n","random.array.lognormal.seedLength":"var len = random.array.lognormal.seedLength;\n","random.array.lognormal.state":"var out = random.array.lognormal( 3, 2.0, 5.0 )\nvar state = random.array.lognormal.state\nout = random.array.lognormal( 3, 2.0, 5.0 )\nout = random.array.lognormal( 3, 2.0, 5.0 )\nrandom.array.lognormal.state = state;\nout = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.stateLength":"var len = random.array.lognormal.stateLength;\n","random.array.lognormal.byteLength":"var sz = random.array.lognormal.byteLength;\n","random.array.minstd":"var out = random.array.minstd( 3 )\n","random.array.minstd.normalized":"var out = random.array.minstd.normalized( 3 )\n","random.array.minstd.factory":"var fcn = random.array.minstd.factory();\nvar out = fcn( 3 )\n","random.array.minstd.PRNG":"var prng = random.array.minstd.PRNG;\n","random.array.minstd.seed":"var seed = random.array.minstd.seed;\n","random.array.minstd.seedLength":"var len = random.array.minstd.seedLength;\n","random.array.minstd.state":"var out = random.array.minstd( 3 )\nvar state = random.array.minstd.state;\nout = random.array.minstd( 3 )\nout = random.array.minstd( 3 )\nrandom.array.minstd.state = state;\nout = random.array.minstd( 3 )\n","random.array.minstd.stateLength":"var len = random.array.minstd.stateLength;\n","random.array.minstd.byteLength":"var sz = random.array.minstd.byteLength;\n","random.array.minstdShuffle":"var out = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.normalized":"var out = random.array.minstdShuffle.normalized( 3 )\n","random.array.minstdShuffle.factory":"var fcn = random.array.minstdShuffle.factory();\nvar out = fcn( 3 )\n","random.array.minstdShuffle.PRNG":"var prng = random.array.minstdShuffle.PRNG;\n","random.array.minstdShuffle.seed":"var seed = random.array.minstdShuffle.seed;\n","random.array.minstdShuffle.seedLength":"var len = random.array.minstdShuffle.seedLength;\n","random.array.minstdShuffle.state":"var out = random.array.minstdShuffle( 3 )\nvar state = random.array.minstdShuffle.state;\nout = random.array.minstdShuffle( 3 )\nout = random.array.minstdShuffle( 3 )\nrandom.array.minstdShuffle.state = state;\nout = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.stateLength":"var len = random.array.minstdShuffle.stateLength;\n","random.array.minstdShuffle.byteLength":"var sz = random.array.minstdShuffle.byteLength;\n","random.array.mt19937":"var out = random.array.mt19937( 3 )\n","random.array.mt19937.normalized":"var out = random.array.mt19937.normalized( 3 )\n","random.array.mt19937.factory":"var fcn = random.array.mt19937.factory();\nvar out = fcn( 3 )\n","random.array.mt19937.PRNG":"var prng = random.array.mt19937.PRNG;\n","random.array.mt19937.seed":"var seed = random.array.mt19937.seed;\n","random.array.mt19937.seedLength":"var len = random.array.mt19937.seedLength;\n","random.array.mt19937.state":"var out = random.array.mt19937( 3 )\nvar state = random.array.mt19937.state;\nout = random.array.mt19937( 3 )\nout = random.array.mt19937( 3 )\nrandom.array.mt19937.state = state;\nout = random.array.mt19937( 3 )\n","random.array.mt19937.stateLength":"var len = random.array.mt19937.stateLength;\n","random.array.mt19937.byteLength":"var sz = random.array.mt19937.byteLength;\n","random.array.negativeBinomial":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.negativeBinomial.assign( 10, 0.5, x )\nvar bool = ( out === x )\n","random.array.negativeBinomial.factory":"var fcn = random.array.negativeBinomial.factory();\nvar out = fcn( 3, 10, 0.5 )\nfcn = random.array.negativeBinomial.factory( 10, 0.5 );\nout = fcn( 3 )\n","random.array.negativeBinomial.PRNG":"var prng = random.array.negativeBinomial.PRNG;\n","random.array.negativeBinomial.seed":"var seed = random.array.negativeBinomial.seed;\n","random.array.negativeBinomial.seedLength":"var len = random.array.negativeBinomial.seedLength;\n","random.array.negativeBinomial.state":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\nvar state = random.array.negativeBinomial.state\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nrandom.array.negativeBinomial.state = state;\nout = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.stateLength":"var len = random.array.negativeBinomial.stateLength;\n","random.array.negativeBinomial.byteLength":"var sz = random.array.negativeBinomial.byteLength;\n","random.array.normal":"var out = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.normal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.normal.factory":"var fcn = random.array.normal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.normal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.normal.PRNG":"var prng = random.array.normal.PRNG;\n","random.array.normal.seed":"var seed = random.array.normal.seed;\n","random.array.normal.seedLength":"var len = random.array.normal.seedLength;\n","random.array.normal.state":"var out = random.array.normal( 3, 2.0, 5.0 )\nvar state = random.array.normal.state\nout = random.array.normal( 3, 2.0, 5.0 )\nout = random.array.normal( 3, 2.0, 5.0 )\nrandom.array.normal.state = state;\nout = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.stateLength":"var len = random.array.normal.stateLength;\n","random.array.normal.byteLength":"var sz = random.array.normal.byteLength;\n","random.array.pareto1":"var out = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.pareto1.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.pareto1.factory":"var fcn = random.array.pareto1.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.pareto1.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.pareto1.PRNG":"var prng = random.array.pareto1.PRNG;\n","random.array.pareto1.seed":"var seed = random.array.pareto1.seed;\n","random.array.pareto1.seedLength":"var len = random.array.pareto1.seedLength;\n","random.array.pareto1.state":"var out = random.array.pareto1( 3, 2.0, 5.0 )\nvar state = random.array.pareto1.state\nout = random.array.pareto1( 3, 2.0, 5.0 )\nout = random.array.pareto1( 3, 2.0, 5.0 )\nrandom.array.pareto1.state = state;\nout = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.stateLength":"var len = random.array.pareto1.stateLength;\n","random.array.pareto1.byteLength":"var sz = random.array.pareto1.byteLength;\n","random.array.poisson":"var out = random.array.poisson( 3, 2.0 )\n","random.array.poisson.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.poisson.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.poisson.factory":"var fcn = random.array.poisson.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.poisson.factory( 2.0 );\nout = fcn( 3 )\n","random.array.poisson.PRNG":"var prng = random.array.poisson.PRNG;\n","random.array.poisson.seed":"var seed = random.array.poisson.seed;\n","random.array.poisson.seedLength":"var len = random.array.poisson.seedLength;\n","random.array.poisson.state":"var out = random.array.poisson( 3, 2.0 )\nvar state = random.array.poisson.state\nout = random.array.poisson( 3, 2.0 )\nout = random.array.poisson( 3, 2.0 )\nrandom.array.poisson.state = state;\nout = random.array.poisson( 3, 2.0 )\n","random.array.poisson.stateLength":"var len = random.array.poisson.stateLength;\n","random.array.poisson.byteLength":"var sz = random.array.poisson.byteLength;\n","random.array.randu":"var out = random.array.randu( 3 )\n","random.array.randu.factory":"var fcn = random.array.randu.factory();\nvar out = fcn( 3 )\n","random.array.randu.PRNG":"var prng = random.array.randu.PRNG;\n","random.array.randu.seed":"var seed = random.array.randu.seed;\n","random.array.randu.seedLength":"var len = random.array.randu.seedLength;\n","random.array.randu.state":"var out = random.array.randu( 3 )\nvar state = random.array.randu.state;\nout = random.array.randu( 3 )\nout = random.array.randu( 3 )\nrandom.array.randu.state = state;\nout = random.array.randu( 3 )\n","random.array.randu.stateLength":"var len = random.array.randu.stateLength;\n","random.array.randu.byteLength":"var sz = random.array.randu.byteLength;\n","random.array.rayleigh":"var out = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.rayleigh.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.rayleigh.factory":"var fcn = random.array.rayleigh.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.rayleigh.factory( 2.0 );\nout = fcn( 3 )\n","random.array.rayleigh.PRNG":"var prng = random.array.rayleigh.PRNG;\n","random.array.rayleigh.seed":"var seed = random.array.rayleigh.seed;\n","random.array.rayleigh.seedLength":"var len = random.array.rayleigh.seedLength;\n","random.array.rayleigh.state":"var out = random.array.rayleigh( 3, 2.0 )\nvar state = random.array.rayleigh.state\nout = random.array.rayleigh( 3, 2.0 )\nout = random.array.rayleigh( 3, 2.0 )\nrandom.array.rayleigh.state = state;\nout = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.stateLength":"var len = random.array.rayleigh.stateLength;\n","random.array.rayleigh.byteLength":"var sz = random.array.rayleigh.byteLength;\n","random.array.t":"var out = random.array.t( 3, 2.0 )\n","random.array.t.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.t.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.t.factory":"var fcn = random.array.t.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.t.factory( 2.0 );\nout = fcn( 3 )\n","random.array.t.PRNG":"var prng = random.array.t.PRNG;\n","random.array.t.seed":"var seed = random.array.t.seed;\n","random.array.t.seedLength":"var len = random.array.t.seedLength;\n","random.array.t.state":"var out = random.array.t( 3, 2.0 )\nvar state = random.array.t.state\nout = random.array.t( 3, 2.0 )\nout = random.array.t( 3, 2.0 )\nrandom.array.t.state = state;\nout = random.array.t( 3, 2.0 )\n","random.array.t.stateLength":"var len = random.array.t.stateLength;\n","random.array.t.byteLength":"var sz = random.array.t.byteLength;\n","random.array.triangular":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.triangular.factory":"var fcn = random.array.triangular.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.triangular.PRNG":"var prng = random.array.triangular.PRNG;\n","random.array.triangular.seed":"var seed = random.array.triangular.seed;\n","random.array.triangular.seedLength":"var len = random.array.triangular.seedLength;\n","random.array.triangular.state":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.triangular.state\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nrandom.array.triangular.state = state;\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.stateLength":"var len = random.array.triangular.stateLength;\n","random.array.triangular.byteLength":"var sz = random.array.triangular.byteLength;\n","random.array.uniform":"var out = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.uniform.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.uniform.factory":"var fcn = random.array.uniform.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.uniform.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.uniform.PRNG":"var prng = random.array.uniform.PRNG;\n","random.array.uniform.seed":"var seed = random.array.uniform.seed;\n","random.array.uniform.seedLength":"var len = random.array.uniform.seedLength;\n","random.array.uniform.state":"var out = random.array.uniform( 3, 2.0, 5.0 )\nvar state = random.array.uniform.state\nout = random.array.uniform( 3, 2.0, 5.0 )\nout = random.array.uniform( 3, 2.0, 5.0 )\nrandom.array.uniform.state = state;\nout = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.stateLength":"var len = random.array.uniform.stateLength;\n","random.array.uniform.byteLength":"var sz = random.array.uniform.byteLength;\n","random.array.weibull":"var out = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.weibull.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.weibull.factory":"var fcn = random.array.weibull.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.weibull.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.weibull.PRNG":"var prng = random.array.weibull.PRNG;\n","random.array.weibull.seed":"var seed = random.array.weibull.seed;\n","random.array.weibull.seedLength":"var len = random.array.weibull.seedLength;\n","random.array.weibull.state":"var out = random.array.weibull( 3, 2.0, 5.0 )\nvar state = random.array.weibull.state\nout = random.array.weibull( 3, 2.0, 5.0 )\nout = random.array.weibull( 3, 2.0, 5.0 )\nrandom.array.weibull.state = state;\nout = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.stateLength":"var len = random.array.weibull.stateLength;\n","random.array.weibull.byteLength":"var sz = random.array.weibull.byteLength;\n","random.iterators.arcsine":"var it = random.iterators.arcsine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.bernoulli":"var it = random.iterators.bernoulli( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.beta":"var it = random.iterators.beta( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.betaprime":"var it = random.iterators.betaprime( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.binomial":"var it = random.iterators.binomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.boxMuller":"var it = random.iterators.boxMuller();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cauchy":"var it = random.iterators.cauchy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chi":"var it = random.iterators.chi( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chisquare":"var it = random.iterators.chisquare( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cosine":"var it = random.iterators.cosine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.discreteUniform":"var it = random.iterators.discreteUniform( 0, 3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.erlang":"var it = random.iterators.erlang( 1, 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.exponential":"var it = random.iterators.exponential( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.f":"var it = random.iterators.f( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.frechet":"var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gamma":"var it = random.iterators.gamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.geometric":"var it = random.iterators.geometric( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gumbel":"var it = random.iterators.gumbel( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.hypergeometric":"var it = random.iterators.hypergeometric( 20, 10, 7 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.improvedZiggurat":"var it = random.iterators.improvedZiggurat();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.invgamma":"var it = random.iterators.invgamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.kumaraswamy":"var it = random.iterators.kumaraswamy( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.laplace":"var it = random.iterators.laplace( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.levy":"var it = random.iterators.levy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.logistic":"var it = random.iterators.logistic( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.lognormal":"var it = random.iterators.lognormal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstd":"var it = random.iterators.minstd();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstdShuffle":"var it = random.iterators.minstdShuffle();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.mt19937":"var it = random.iterators.mt19937();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.negativeBinomial":"var it = random.iterators.negativeBinomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.normal":"var it = random.iterators.normal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.pareto1":"var it = random.iterators.pareto1( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.poisson":"var it = random.iterators.poisson( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randi":"var it = random.iterators.randi();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randn":"var it = random.iterators.randn();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randu":"var it = random.iterators.randu();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.rayleigh":"var it = random.iterators.rayleigh( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.t":"var it = random.iterators.t( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.triangular":"var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.uniform":"var it = random.iterators.uniform( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.weibull":"var it = random.iterators.weibull( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.streams.arcsine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.arcsine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.arcsine.factory( opts );\n","random.streams.arcsine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.bernoulli":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.bernoulli.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.bernoulli.factory( opts );\n","random.streams.bernoulli.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.beta":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.beta.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.beta.factory( opts );\n","random.streams.beta.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.betaprime":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.betaprime.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.betaprime.factory( opts );\n","random.streams.betaprime.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.binomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial( 20, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.binomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.binomial.factory( opts );\n","random.streams.binomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial.objectMode( 20, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.boxMuller":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.boxMuller.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.boxMuller.factory( opts );\n","random.streams.boxMuller.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cauchy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cauchy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cauchy.factory( opts );\n","random.streams.cauchy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chi.factory( opts );\n","random.streams.chi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chisquare":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chisquare.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chisquare.factory( opts );\n","random.streams.chisquare.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cosine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cosine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cosine.factory( opts );\n","random.streams.cosine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.discreteUniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform( 2, 5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.discreteUniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.discreteUniform.factory( opts );\n","random.streams.discreteUniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform.objectMode( 2, 5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.erlang":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang( 2, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.erlang.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.erlang.factory( opts );\n","random.streams.erlang.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang.objectMode( 2, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.exponential":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.exponential.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.exponential.factory( opts );\n","random.streams.exponential.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.f":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.f.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.f.factory( opts );\n","random.streams.f.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.frechet":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.frechet.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.frechet.factory( opts );\n","random.streams.frechet.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gamma.factory( opts );\n","random.streams.gamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.geometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.geometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.geometric.factory( opts );\n","random.streams.geometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gumbel":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gumbel.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gumbel.factory( opts );\n","random.streams.gumbel.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.hypergeometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric( 5, 3, 2, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.hypergeometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.hypergeometric.factory( opts );\n","random.streams.hypergeometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.improvedZiggurat.factory( opts );\n","random.streams.improvedZiggurat.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.invgamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.invgamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.invgamma.factory( opts );\n","random.streams.invgamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.kumaraswamy.factory( opts );\n","random.streams.kumaraswamy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.laplace":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.laplace.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.laplace.factory( opts );\n","random.streams.laplace.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.levy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.levy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.levy.factory( opts );\n","random.streams.levy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.logistic":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.logistic.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.logistic.factory( opts );\n","random.streams.logistic.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.lognormal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.lognormal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.lognormal.factory( opts );\n","random.streams.lognormal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstd":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstd.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstd.factory( opts );\n","random.streams.minstd.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstdShuffle.factory( opts );\n","random.streams.minstdShuffle.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.mt19937":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.mt19937.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.mt19937.factory( opts );\n","random.streams.mt19937.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial( 20.0, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.negativeBinomial.factory( opts );\n","random.streams.negativeBinomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.normal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.normal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.normal.factory( opts );\n","random.streams.normal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.pareto1":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.pareto1.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.pareto1.factory( opts );\n","random.streams.pareto1.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.poisson":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.poisson.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.poisson.factory( opts );\n","random.streams.poisson.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randi.factory( opts );\n","random.streams.randi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randn":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randn.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randn.factory( opts );\n","random.streams.randn.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randu":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randu.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randu.factory( opts );\n","random.streams.randu.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.rayleigh":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.rayleigh.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.rayleigh.factory( opts );\n","random.streams.rayleigh.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.t":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.t.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.t.factory( opts );\n","random.streams.t.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.triangular":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.triangular.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.triangular.factory( opts );\n","random.streams.triangular.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.uniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.uniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.uniform.factory( opts );\n","random.streams.uniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.weibull":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.weibull.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.weibull.factory( opts );\n","random.streams.weibull.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.strided.arcsine":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n","random.strided.arcsine.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.bernoulli":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n","random.strided.bernoulli.factory":"var fcn = random.strided.bernoulli.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.PRNG":"var prng = random.strided.bernoulli.PRNG;\n","random.strided.bernoulli.seed":"var seed = random.strided.bernoulli.seed;\n","random.strided.bernoulli.seedLength":"var len = random.strided.bernoulli.seedLength;\n","random.strided.bernoulli.state":"var out = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nvar state = random.strided.bernoulli.state\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nrandom.strided.bernoulli.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.stateLength":"var len = random.strided.bernoulli.stateLength;\n","random.strided.bernoulli.byteLength":"var sz = random.strided.bernoulli.byteLength;\n","random.strided.beta":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta( 3, a, -2, b, 1, out, 1 )\n","random.strided.beta.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.betaprime":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n","random.strided.betaprime.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.chi":"var out = azeros( 5, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chi.factory":"var fcn = random.strided.chi.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.PRNG":"var prng = random.strided.chi.PRNG;\n","random.strided.chi.seed":"var seed = random.strided.chi.seed;\n","random.strided.chi.seedLength":"var len = random.strided.chi.seedLength;\n","random.strided.chi.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chi.state\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chi.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.stateLength":"var len = random.strided.chi.stateLength;\n","random.strided.chi.byteLength":"var sz = random.strided.chi.byteLength;\n","random.strided.chisquare":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chisquare.factory":"var fcn = random.strided.chisquare.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.PRNG":"var prng = random.strided.chisquare.PRNG;\n","random.strided.chisquare.seed":"var seed = random.strided.chisquare.seed;\n","random.strided.chisquare.seedLength":"var len = random.strided.chisquare.seedLength;\n","random.strided.chisquare.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chisquare.state\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chisquare.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.stateLength":"var len = random.strided.chisquare.stateLength;\n","random.strided.chisquare.byteLength":"var sz = random.strided.chisquare.byteLength;\n","random.strided.cosine":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n","random.strided.cosine.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n","random.strided.discreteUniform":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.discreteUniform.ndarray":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.exponential":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.exponential.factory":"var fcn = random.strided.exponential.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.PRNG":"var prng = random.strided.exponential.PRNG;\n","random.strided.exponential.seed":"var seed = random.strided.exponential.seed;\n","random.strided.exponential.seedLength":"var len = random.strided.exponential.seedLength;\n","random.strided.exponential.state":"var out = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.exponential.state\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.exponential.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.stateLength":"var len = random.strided.exponential.stateLength;\n","random.strided.exponential.byteLength":"var sz = random.strided.exponential.byteLength;\n","random.strided.gamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.gamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.geometric":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n","random.strided.geometric.factory":"var fcn = random.strided.geometric.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.PRNG":"var prng = random.strided.geometric.PRNG;\n","random.strided.geometric.seed":"var seed = random.strided.geometric.seed;\n","random.strided.geometric.seedLength":"var len = random.strided.geometric.seedLength;\n","random.strided.geometric.state":"var out = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nvar state = random.strided.geometric.state\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nrandom.strided.geometric.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.stateLength":"var len = random.strided.geometric.stateLength;\n","random.strided.geometric.byteLength":"var sz = random.strided.geometric.byteLength;\n","random.strided.invgamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.invgamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.lognormal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.lognormal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.minstd":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd( out.length, out, 1 )\n","random.strided.minstd.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.ndarray( out.length, out, 1, 0 )\n","random.strided.minstd.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized( out.length, out, 1 )\n","random.strided.minstd.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle( out.length, out, 1 )\n","random.strided.minstdShuffle.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized( out.length, out, 1 )\n","random.strided.minstdShuffle.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937( out.length, out, 1 )\n","random.strided.mt19937.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized( out.length, out, 1 )\n","random.strided.mt19937.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.normal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.normal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.poisson":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.poisson.factory":"var fcn = random.strided.poisson.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.PRNG":"var prng = random.strided.poisson.PRNG;\n","random.strided.poisson.seed":"var seed = random.strided.poisson.seed;\n","random.strided.poisson.seedLength":"var len = random.strided.poisson.seedLength;\n","random.strided.poisson.state":"var out = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.poisson.state\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.poisson.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.stateLength":"var len = random.strided.poisson.stateLength;\n","random.strided.poisson.byteLength":"var sz = random.strided.poisson.byteLength;\n","random.strided.randu":"var out = azeros( 5, 'generic' );\nrandom.strided.randu( out.length, out, 1 )\n","random.strided.randu.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.randu.ndarray( out.length, out, 1, 0 )\n","random.strided.rayleigh":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.rayleigh.factory":"var fcn = random.strided.rayleigh.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.PRNG":"var prng = random.strided.rayleigh.PRNG;\n","random.strided.rayleigh.seed":"var seed = random.strided.rayleigh.seed;\n","random.strided.rayleigh.seedLength":"var len = random.strided.rayleigh.seedLength;\n","random.strided.rayleigh.state":"var out = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.rayleigh.state\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.rayleigh.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.stateLength":"var len = random.strided.rayleigh.stateLength;\n","random.strided.rayleigh.byteLength":"var sz = random.strided.rayleigh.byteLength;\n","random.strided.t":"var out = azeros( 5, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.t.factory":"var fcn = random.strided.t.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.PRNG":"var prng = random.strided.t.PRNG;\n","random.strided.t.seed":"var seed = random.strided.t.seed;\n","random.strided.t.seedLength":"var len = random.strided.t.seedLength;\n","random.strided.t.state":"var out = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.t.state\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.t.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.stateLength":"var len = random.strided.t.stateLength;\n","random.strided.t.byteLength":"var sz = random.strided.t.byteLength;\n","random.strided.uniform":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.uniform.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.weibull":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull( 3, a, -2, b, 1, out, 1 )\n","random.strided.weibull.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","ranks":"var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\nvar out = ranks( arr )\narr = [ 2, 2, 1, 4, 3 ];\nout = ranks( arr )\narr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\nout = ranks( arr )\n","readDir":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadDir( './beep/boop', onRead );\n","readDir.sync":"var out = readDir.sync( './beep/boop' );\n","readFile":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadFile( './beep/boop.js', onRead );\n","readFile.sync":"var out = readFile.sync( './beep/boop.js' );\n","readFileList":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nvar filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nreadFileList( filepaths, onRead );\n","readFileList.sync":"var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nvar out = readFileList.sync( filepaths );\n","readJSON":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadJSON( './beep/boop.json', onRead );\n","readJSON.sync":"var out = readJSON.sync( './beep/boop.json' );\n","readWASM":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadWASM( './beep/boop.wasm', onRead );\n","readWASM.sync":"var out = readWASM.sync( './beep/boop.wasm' );\n","real":"var z = new Complex128( 5.0, 3.0 );\nvar re = real( z )\n","realarray":"var arr = realarray()\narr = realarray( 'float32' )\nvar arr = realarray( 5 )\narr = realarray( 5, 'int32' )\nvar arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = realarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = realarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = realarray( buf, 0, 4, 'float32' )\n","realarrayCtors":"var ctor = realarrayCtors( 'float64' )\nctor = realarrayCtors( 'float' )\n","realarrayDataTypes":"var out = realarrayDataTypes()\n","realf":"var z = new Complex64( 5.0, 3.0 );\nvar re = realf( z )\n","realmax":"var m = realmax( 'float16' )\nm = realmax( 'float32' )\n","realmin":"var m = realmin( 'float16' )\nm = realmin( 'float32' )\n","reBasename":"var RE = reBasename()\nvar RE_POSIX = reBasename( 'posix' );\nvar RE_WIN32 = reBasename( 'win32' );\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reBasename.REGEXP":"var RE = reBasename.REGEXP\n","reBasename.REGEXP_POSIX":"var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reBasename.REGEXP_WIN32":"var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reBasenamePosix":"var RE_BASENAME_POSIX = reBasenamePosix();\nvar base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n","reBasenamePosix.REGEXP":"var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n","reBasenameWindows":"var RE_BASENAME_WINDOWS = reBasenameWindows();\nvar base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n","reBasenameWindows.REGEXP":"var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n","reColorHexadecimal":"var RE = reColorHexadecimal();\nvar bool = RE.test( 'ffffff' )\nbool = RE.test( '000' )\nbool = RE.test( 'beep' )\n","reColorHexadecimal.REGEXP":"var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP.test( '000' )\nbool = reColorHexadecimal.REGEXP.test( 'beep' )\n","reColorHexadecimal.REGEXP_SHORTHAND":"var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n","reColorHexadecimal.REGEXP_EITHER":"var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n","reDecimalNumber":"var RE = reDecimalNumber();\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\nbool = RE.test( '0.0' )\nbool = RE.test( '.0' )\nbool = RE.test( '0' )\nbool = RE.test( 'beep' )\nvar re = reDecimalNumber({ 'flags': 'g' });\nvar str = '1.234 5.6, 7.8';\nvar out = str.match( re )\n","reDecimalNumber.REGEXP":"var RE = reDecimalNumber.REGEXP;\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\n","reDecimalNumber.REGEXP_CAPTURE":"var RE = reDecimalNumber.REGEXP_CAPTURE;\nvar str = '1.02';\nvar out = replace( str, RE, '$1 x $1' )\n","reDirname":"var RE = reDirname()\nvar RE_POSIX = reDirname( 'posix' );\nvar dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reDirname( 'win32' );\ndir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reDirname.REGEXP":"var RE = reDirname.REGEXP\n","reDirname.REGEXP_POSIX":"var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirname.REGEXP_WIN32":"var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reDirnamePosix":"var RE = reDirnamePosix();\nvar dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\ndir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\ndir = RE.exec( 'foo/file.pdf' )[ 1 ]\ndir = RE.exec( '/foo/bar/file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '.' )[ 1 ]\ndir = RE.exec( './' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnamePosix.REGEXP":"var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirnameWindows":"var RE = reDirnameWindows();\nvar dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\ndir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\ndir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\ndir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnameWindows.REGEXP":"var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n","reduce":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduce( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduce( arr, 0.0, f )\n","reduce2d":"var f = naryFunction( base.add, 2 );\nvar arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\nvar out = reduce2d( arr, [ 0, 0 ], f )\n","reduceAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n","reduceAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 2000, 1500, 1000 ];\nf( arr, acc, done )\n","reduceRight":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduceRight( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduceRight( arr, 0.0, f )\n","reduceRightAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n","reduceRightAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceRightAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 1000, 1500, 2000 ];\nf( arr, acc, done )\n","reDurationString":"var RE = reDurationString();\nvar parts = RE.exec( '3d2ms' )\nparts = RE.exec( '4h3m20s' )\n","reDurationString.REGEXP":"var bool = reDurationString.REGEXP.test( '3d2ms' )\nbool = reDurationString.REGEXP.test( 'foo' )\n","reEOL":"var RE_EOL = reEOL();\nvar bool = RE_EOL.test( '\\n' )\nbool = RE_EOL.test( '\\r\\n' )\nbool = RE_EOL.test( '\\\\r\\\\n' )\n","reEOL.REGEXP":"var bool = reEOL.REGEXP.test( 'abc' )\n","reEOL.REGEXP_CAPTURE":"var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n","reExtendedLengthPath":"var RE = reExtendedLengthPath();\nvar path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\nvar bool = RE.test( path )\npath = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\nbool = RE.test( path )\npath = 'C:\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '/c/foo/bar';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\n","reExtendedLengthPath.REGEXP":"var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n","reExtname":"var RE = reExtname()\nvar RE_POSIX = reExtname( 'posix' );\nvar ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reExtname( 'win32' );\next = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reExtname.REGEXP":"var RE = reExtname.REGEXP\n","reExtname.REGEXP_POSIX":"var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtname.REGEXP_WIN32":"var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reExtnamePosix":"var RE = reExtnamePosix();\nvar ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\next = RE.exec( './foo/bar/.gitignore' )[ 1 ]\next = RE.exec( 'foo/file.pdf' )[ 1 ]\next = RE.exec( '/foo/bar/file' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '.' )[ 1 ]\next = RE.exec( './' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnamePosix.REGEXP":"var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtnameWindows":"var RE = reExtnameWindows();\nvar ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\next = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\next = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\next = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\next = RE.exec( 'beep\\\\boop.' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnameWindows.REGEXP":"var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reFilename":"var RE = reFilename()\nvar RE_POSIX = reFilename( 'posix' );\nvar parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\nvar RE_WIN32 = reFilename( 'win32' );\nparts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reFilename.REGEXP":"var RE = reFilename.REGEXP\n","reFilename.REGEXP_POSIX":"var f = '/foo/bar/index.js';\nvar parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n","reFilename.REGEXP_WIN32":"var f = 'C:\\\\foo\\\\bar\\\\index.js';\nvar parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n","reFilenamePosix":"var RE = reFilenamePosix();\nvar parts = RE.exec( '/foo/bar/index.js' ).slice()\nparts = RE.exec( './foo/bar/.gitignore' ).slice()\nparts = RE.exec( 'foo/file.pdf' ).slice()\nparts = RE.exec( '/foo/bar/file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenamePosix.REGEXP":"var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n","reFilenameWindows":"var RE = reFilenameWindows();\nvar parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\nparts = RE.exec( 'foo\\\\file.pdf' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenameWindows.REGEXP":"var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n","reFromString":"var re = reFromString( '/beep/' )\nre = reFromString( '/beep' )\n","reFunctionName":"var RE_FUNCTION_NAME = reFunctionName();\nfunction beep() { return 'boop'; };\nvar name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\nname = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n","reFunctionName.REGEXP":"var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n","regexp2json":"var json = regexp2json( /ab+c/ )\n","reim":"var z = new Complex128( 5.0, 3.0 );\nvar out = reim( z )\n","reimf":"var z = new Complex64( 5.0, 3.0 );\nvar out = reimf( z )\n","rejectArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v === 2 ); };\nvar bar = rejectArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","removeFirst":"var out = removeFirst( 'beep' )\nout = removeFirst( 'Boop' )\nout = removeFirst( 'foo bar', 4 )\n","removeLast":"var out = removeLast( 'beep' )\nout = removeLast( 'Boop' )\nout = removeLast( 'foo bar', 4 )\n","removePunctuation":"var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\nvar out = removePunctuation( str )\nstr = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\nout = removePunctuation( str )\n","removeUTF8BOM":"var out = removeUTF8BOM( '\\ufeffbeep' )\n","removeWords":"var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\nout = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n","rename":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nrename( './beep/boop.txt', './beep/foo.txt', done );\n","rename.sync":"var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n","reNativeFunction":"var RE = reNativeFunction();\nvar bool = RE.test( Date.toString() )\nbool = RE.test( (function noop() {}).toString() )\n","reNativeFunction.REGEXP":"var bool = reNativeFunction.REGEXP.test( Date.toString() )\nbool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n","reorderArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reorderArguments( foo, [ 2, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","repeat":"var out = repeat( 'a', 5 )\nout = repeat( '', 100 )\nout = repeat( 'beep', 0 )\n","replace":"var out = replace( 'beep', 'e', 'o' )\nfunction replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nout = replace( str, /([^\\s]+)/gi, replacer )\nout = replace( 'beep', /e/, 'o' )\n","replaceBefore":"var str = 'beep boop';\nvar out = replaceBefore( str, ' ', 'foo' )\nout = replaceBefore( str, 'o', 'foo' )\n","reRegExp":"var RE = reRegExp();\nvar bool = RE.test( '/^beep$/' )\nbool = RE.test( '/boop' )\nbool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\nbool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n","reRegExp.REGEXP":"var bool = reRegExp.REGEXP.test( '/^beep$/' )\nbool = reRegExp.REGEXP.test( '/boop' )\n","rescape":"var str = rescape( '[A-Z]*' )\n","reSemVer":"var RE_SEMVER = reSemVer()\nvar bool = RE_SEMVER.test( '1.0.0' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1' )\nbool = RE_SEMVER.test( 'abc' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n","reSemVer.REGEXP":"var bool = reSemVer.REGEXP.test( '1.0.0' )\nbool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n","resolveParentPath":"function onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n };\nresolveParentPath( 'package.json', onPath );\n","resolveParentPath.sync":"var out = resolveParentPath.sync( 'package.json' );\n","resolveParentPathBy":"function predicate( path, next ) {\n setTimeout( onTimeout, path );\n function onTimeout() {\n console.log( path );\n next( null, false );\n }\n };\nfunction onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n };\nresolveParentPathBy( 'package.json', predicate, onPath );\n","resolveParentPathBy.sync":"function predicate() { return false; };\nvar out = resolveParentPathBy.sync( 'package.json', predicate );\n","reUncPath":"var RE = reUncPath();\nvar path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = 'beep boop \\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server';\nbool = RE.test( path )\npath = '\\\\';\nbool = RE.test( path )\npath = '';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\nbool = RE.test( path )\npath = '//server/share';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\npath = 'foo/bar';\nbool = RE.test( path )\npath = './foo/bar';\nbool = RE.test( path )\npath = '/foo/../bar';\nbool = RE.test( path )\n","reUncPath.REGEXP":"var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = reUncPath.REGEXP.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = reUncPath.REGEXP.test( path )\n","reUtf16SurrogatePair":"var RE = reUtf16SurrogatePair();\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16SurrogatePair.REGEXP":"var RE = reUtf16SurrogatePair.REGEXP;\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16UnpairedSurrogate":"var RE = reUtf16UnpairedSurrogate();\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reUtf16UnpairedSurrogate.REGEXP":"var RE = reUtf16UnpairedSurrogate.REGEXP;\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reverseArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reverseArguments( foo );\nvar out = bar( 1, 2, 3 )\n","reverseString":"var out = reverseString( 'foo' )\nout = reverseString( 'abcdef' )\n","reviveBasePRNG":"var str = JSON.stringify( base.random.mt19937 );\nvar r = parseJSON( str, reviveBasePRNG )\n","reviveBuffer":"var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\nvar buf = parseJSON( str, reviveBuffer )\n","reviveComplex":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex )\n","reviveComplex64":"var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex64 )\n","reviveComplex128":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex128 )\n","reviveError":"var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\nvar err = JSON.parse( str, reviveError )\n","reviveRegExp":"var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\nvar v = parseJSON( str, reviveRegExp )\n","reviveTypedArray":"var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\nvar arr = parseJSON( str, reviveTypedArray )\n","reWhitespace":"var RE = reWhitespace();\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP":"var RE = reWhitespace.REGEXP;\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP_CAPTURE":"var RE = reWhitespace.REGEXP_CAPTURE;\nvar str = 'Duplicate capture';\nvar out = replace( str, RE, '$1$1' )\n","rpad":"var out = rpad( 'a', 5 )\nout = rpad( 'beep', 10, 'p' )\nout = rpad( 'beep', 12, 'boop' )\n","rtrim":"var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","rtrimN":"var out = rtrimN( ' abc ', 2 )\nvar out = rtrimN( '!!!abc!!!', 2, '!' )\n","safeintmax":"var m = safeintmax( 'float16' )\nm = safeintmax( 'float32' )\n","safeintmin":"var m = safeintmin( 'float16' )\nm = safeintmin( 'float32' )\n","sample":"var out = sample( 'abc' )\nout = sample( [ 3, 6, 9 ] )\nvar bool = ( out.length === 3 )\nout = sample( [ 3, null, NaN, 'abc', function(){} ] )\nout = sample( [ 3, 6, 9 ], { 'size': 10 } )\nout = sample( [ 0, 1 ], { 'size': 20 } )\nout = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\nout = sample( [ 0, 1 ], { 'replace': false } )\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\nout = sample( x, { 'probs': probs } )\nout = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n","sample.factory":"var mysample = sample.factory({ 'seed': 232 } );\nvar out = mysample( 'abcdefg' )\nvar pool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\nout = mysample()\nout = mysample()\nvar opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\npool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, opts );\nout = mysample()\nout = mysample()\nout = mysample()\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'size': 10 })\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'replace': false })\nout = mysample()\n","SAVOY_STOPWORDS_FIN":"var list = SAVOY_STOPWORDS_FIN()\n","SAVOY_STOPWORDS_FR":"var list = SAVOY_STOPWORDS_FR()\n","SAVOY_STOPWORDS_GER":"var list = SAVOY_STOPWORDS_GER()\n","SAVOY_STOPWORDS_IT":"var list = SAVOY_STOPWORDS_IT()\n","SAVOY_STOPWORDS_POR":"var list = SAVOY_STOPWORDS_POR()\n","SAVOY_STOPWORDS_SP":"var list = SAVOY_STOPWORDS_SP()\n","SAVOY_STOPWORDS_SWE":"var list = SAVOY_STOPWORDS_SWE()\n","scalar2array":"var x = scalar2array( 1.0 )\n","scalar2ndarray":"var x = scalar2ndarray( 1.0 )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","sdot":"var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = sdot( x, y )\nz.get()\n","SECONDS_IN_DAY":"var days = 3.14;\nvar secs = days * SECONDS_IN_DAY\n","SECONDS_IN_HOUR":"var hrs = 3.14;\nvar secs = hrs * SECONDS_IN_HOUR\n","SECONDS_IN_MINUTE":"var mins = 3.14;\nvar secs = mins * SECONDS_IN_MINUTE\n","SECONDS_IN_WEEK":"var wks = 3.14;\nvar secs = wks * SECONDS_IN_WEEK\n","secondsInMonth":"var num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n","secondsInYear":"var num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n","sentencize":"var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\nout = sentencize( 'Hello World! How are you?' )\n","seq2slice":"var s = new seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","setConfigurableReadOnly":"var obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setConfigurableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setConfigurableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setConfigurableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setMemoizedConfigurableReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedConfigurableReadOnly( obj, 'foo', foo );\nobj.foo\n","setMemoizedReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedReadOnly( obj, 'foo', foo );\nobj.foo\n","setNonEnumerableProperty":"var obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n","setNonEnumerableReadOnly":"var obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setNonEnumerableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setNonEnumerableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setNonEnumerableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setReadOnly":"var obj = {};\nsetReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","SharedArrayBuffer":"var buf = new SharedArrayBuffer( 5 )\n","SharedArrayBuffer.length":"SharedArrayBuffer.length\n","SharedArrayBuffer.prototype.byteLength":"var buf = new SharedArrayBuffer( 5 );\nbuf.byteLength\n","SharedArrayBuffer.prototype.slice":"var b1 = new SharedArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","shift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = shift( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = shift( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = shift( arr )\n","shuffle":"var data = [ 1, 2, 3 ];\nvar out = shuffle( data )\nout = shuffle( data, { 'copy': 'none' } );\nvar bool = ( data === out )\n","shuffle.factory":"var myshuffle = shuffle.factory();\nmyshuffle = shuffle.factory({ 'seed': 239 });\nvar arr = [ 0, 1, 2, 3, 4 ];\nvar out = myshuffle( arr )\nmyshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\narr = [ 1, 2, 3, 4, 5, 6 ];\nout = myshuffle( arr );\nvar bool = ( arr === out )\narr = [ 1, 2, 3, 4 ];\nout = myshuffle( arr, { 'copy': 'shallow' } );\nbool = ( arr === out )\n","sizeOf":"var s = sizeOf( 'int8' )\ns = sizeOf( 'uint32' )\n","Slice":"var s = new Slice();\ns = new Slice( 10 );\nvar s = new Slice( 2, 10 );\ns = new Slice( 2, 10, 1 );\n","Slice.prototype.start":"var s = new Slice( 10 );\ns.start\ns = new Slice( 2, 10 );\ns.start\n","Slice.prototype.stop":"var s = new Slice( 10 );\ns.stop\ns = new Slice( 2, 10 );\ns.stop\n","Slice.prototype.step":"var s = new Slice( 10 );\ns.step\ns = new Slice( 2, 10 );\ns.step\ns = new Slice( 2, 10, 1 );\ns.step\n","Slice.prototype.toString":"var s = new Slice( 10 );\ns.toString()\ns = new Slice( 2, 10, 1 );\ns.toString()\n","Slice.prototype.toJSON":"var s = new Slice( 10 );\ns.toJSON()\ns = new Slice( 2, 10, 1 );\ns.toJSON()\n","snakecase":"var out = snakecase( 'Hello World!' )\nout = snakecase( 'I am a tiny little teapot' )\n","some":"var arr = [ 0, 0, 1, 2, 3 ];\nvar bool = some( arr, 3 )\n","someBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, -3, 4, -1 ];\nvar bool = someBy( arr, 2, negative )\n","someByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n","someByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, 2, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, 2, done )\n","someByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, -2, 3, 4 ];\nvar bool = someByRight( arr, 2, negative )\n","someByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n","someByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, 2, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, 2, done )\n","someInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\nvar bool = someInBy( obj, 2, negative )\n","someOwnBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\nvar bool = someOwnBy( obj, 2, negative )\n","SOTU":"var out = SOTU()\nvar opts = { 'name': 'Barack Obama' };\nout = SOTU( opts )\nopts = { 'party': [ 'Democratic', 'Federalist' ] };\nout = SOTU( opts )\nopts = { 'year': [ 2008, 2009, 2011 ] };\nout = SOTU( opts )\nopts = { 'range': [ 2008, 2016 ] }\nout = SOTU( opts )\n","SPACHE_REVISED":"var list = SPACHE_REVISED()\n","SPAM_ASSASSIN":"var data = SPAM_ASSASSIN()\n","SparklineBase":"var sparkline = new SparklineBase()\nvar data = [ 1, 2, 3 ];\nsparkline = new SparklineBase( data )\n","sparsearray2iterator":"var it = sparsearray2iterator( [ 1, , 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","sparsearray2iteratorRight":"var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\nvar v = it.next().value\nv = it.next().value\n","splitStream":"var s = splitStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = splitStream.factory( opts );\nvar s = createStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.objectMode":"var s = splitStream.objectMode();\ns.write( 'a\\nb\\c' );\ns.end();\n","SQRT_EPS":"SQRT_EPS\n","SQRT_HALF":"SQRT_HALF\n","SQRT_HALF_PI":"SQRT_HALF_PI\n","SQRT_PHI":"SQRT_PHI\n","SQRT_PI":"SQRT_PI\n","SQRT_THREE":"SQRT_THREE\n","SQRT_TWO":"SQRT_TWO\n","SQRT_TWO_PI":"SQRT_TWO_PI\n","SSA_US_BIRTHS_2000_2014":"var data = SSA_US_BIRTHS_2000_2014()\n","sswap":"var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\nsswap( x, y );\nx.data\ny.data\n","Stack":"var s = Stack();\ns.push( 'foo' ).push( 'bar' );\ns.length\ns.pop()\ns.length\ns.pop()\ns.length\n","standalone2pkg":"var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n","STANDARD_CARD_DECK":"var list = STANDARD_CARD_DECK()\n","startcase":"var out = startcase( 'beep boop' )\n","startsWith":"var bool = startsWith( 'Beep', 'Be' )\nbool = startsWith( 'Beep', 'ep' )\nbool = startsWith( 'Beep', 'ee', 1 )\nbool = startsWith( 'Beep', 'ee', -3 )\nbool = startsWith( 'Beep', '' )\n","STOPWORDS_EN":"var list = STOPWORDS_EN()\n","strided.abs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( 2, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2By":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.abs2By.ndarray":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -1.0, -2.0, -3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.absBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.absBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.absBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acosBy":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acosBy.ndarray":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 0.707, 0.866, -0.707 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoshBy":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoshBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoshBy.ndarray":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 1.5, 2.0, 2.5 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acotBy":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acotBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acotBy.ndarray":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -2.5, -1.5, -0.5, 0.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acothBy":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acothBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acothBy.ndarray":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -5.0, -4.0, -3.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acovercosBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acovercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acovercosBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.add":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.add.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.addBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.addBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.addBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ahavercosBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahavercosBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ahaversinBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahaversinBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinhBy":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinhBy.ndarray":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.0, 2.0, -2.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanBy":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -1.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanhBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanhBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.avercosBy":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.avercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.avercosBy.ndarray":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -1.57, -0.5, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.aversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.aversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.aversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.binetBy":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.binetBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.binetBy.ndarray":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 2.0, 3.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.cbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.cbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cbrtBy":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cbrtBy.ndarray":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 9.0, -27.0, 81.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cosBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cosBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.deg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.deg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.dataTypes":"var out = strided.dataTypes()\n","strided.dcbrtBy":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy( x.length, x, 1, y, 1, clbk )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.dcbrtBy.ndarray":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.dispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1 );\ny\nf = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\ny\n","strided.dispatchBy":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\ny\nf = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\ny\n","strided.floor":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.floor.ndarray":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.inv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.inv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.mul":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.mul.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.mulBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.mulBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.rsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.rsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sinBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sinBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.sqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sqrtBy":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sqrtBy.ndarray":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 122.0, 50.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sub":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.sub.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.subBy":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.subBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.subBy.ndarray":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 11.0, 12.0, 13.0, 14.0 ];\ny = [ 8.0, 7.0, 6.0, 5.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.trunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.trunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","stridedarray2iterator":"var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\nvar v = it.next().value\nv = it.next().value\n","stridedArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","stridedArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = stridedArrayStream.factory( opts );\n","stridedArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","string2buffer":"var b = string2buffer( 'beep boop' )\nb = string2buffer( '7468697320697320612074c3a97374', 'hex' );\nb.toString()\n","sub2ind":"var d = [ 3, 3, 3 ];\nvar idx = sub2ind( d, 1, 2, 2 )\n","substringAfter":"var out = substringAfter( 'Hello World!', 'World' )\nout = substringAfter( 'Hello World!', 'Hello ' )\nout = substringAfter( 'Hello World!', 'l', 5 )\n","substringAfterLast":"var out = substringAfterLast( 'beep boop beep baz', 'beep' )\nout = substringAfterLast( 'Hello World!', 'Hello ' )\nout = substringAfterLast( 'Hello World!', 'o', 5 )\n","substringBefore":"var str = 'beep boop';\nvar out = substringBefore( str, ' ' )\nout = substringBefore( str, 'o' )\n","substringBeforeLast":"var str = 'Beep Boop Beep';\nvar out = substringBeforeLast( str, 'Beep' )\nout = substringBeforeLast( str, 'Boop' )\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n","Symbol":"var s = ( Symbol ) ? Symbol( 'beep' ) : null\n","tabulate":"var collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulate( collection )\n","tabulateBy":"function indicator( value ) { return value[ 0 ]; };\nvar collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulateBy( collection, indicator )\n","tabulateByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n","tabulateByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = tabulateByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 750 ];\nf( arr, done )\n","thunk":"var fcn = thunk( base.add, 2, 3 );\nvar v = fcn()\nv = fcn()\n","tic":"var t = tic()\n","timeit":"var code = 'var x = Math.pow( Math.random(), 3 );';\ncode += 'if ( x !== x ) {';\ncode += 'throw new Error( \\'Something went wrong.\\' );';\ncode += '}';\nfunction done( error, results ) {\n if ( error ) {\n throw error;\n }\n console.dir( results );\n };\ntimeit( code, done )\n","tmpdir":"var dir = tmpdir()\n","toc":"var start = tic();\nvar delta = toc( start )\n","tokenize":"var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\nout = tokenize( 'Hello World!', true )\n","transformStream":"var s = transformStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = transformStream.factory( opts );\nfunction fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar s = createStream( fcn );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.objectMode":"var s = transformStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","transformStream.ctor":"function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar opts = { 'highWaterMark': 64, 'transform': fcn };\nvar customStream = transformStream.ctor( opts );\nvar s = customStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","trim":"var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","truncate":"var str = 'beep boop';\nvar out = truncate( str, 5 )\nout = truncate( str, 5, '|' )\n","truncateMiddle":"var str = 'beep boop';\nvar out = truncateMiddle( str, 5 )\nout = truncateMiddle( str, 5, '|' )\n","trycatch":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n };\nvar z = trycatch( x, -1.0 )\n","trycatchAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n // process error...\n }\n console.log( result );\n };\ntrycatchAsync( x, 'boop', done )\n","tryFunction":"function fcn() { throw new Error( 'beep boop' ); };\nvar f = tryFunction( fcn );\nvar out = f();\nout.message\n","tryRequire":"var out = tryRequire( '_unknown_module_id_' )\n","trythen":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n };\nfunction y() {\n return -1.0;\n };\nvar z = trythen( x, y )\n","trythenAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ntrythenAsync( x, y, done )\n","ttest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ttest( x )\nrnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\nx = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n y[ i ] = rnorm();\n }\nout = ttest( x, y )\nvar table = out.print()\nvar arr = [ 2, 4, 3, 1, 0 ];\nout = ttest( arr, { 'alpha': 0.01 } );\ntable = out.print()\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest( arr, { 'alternative': 'greater' } );\ntable = out.print()\n","ttest2":"var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\nvar y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\nvar out = ttest2( x, y )\nvar table = out.print()\nout = ttest2( x, y, { 'alpha': 0.1 } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'greater' } );\ntable = out.print()\nx = [ 2, 3, 1, 4 ];\ny = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\nout = ttest2( x, y, { 'variance': 'equal' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 3.0 );\n }\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 1.0, 3.0 );\n }\nout = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n","TWO_PI":"TWO_PI\n","typedarray":"var arr = typedarray()\narr = typedarray( 'float32' )\nvar arr = typedarray( 5 )\narr = typedarray( 5, 'int32' )\nvar arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = typedarray( buf, 0, 4, 'float32' )\n","typedarray2json":"var arr = new Float64Array( 2 );\narr[ 0 ] = 5.0;\narr[ 1 ] = 3.0;\nvar json = typedarray2json( arr )\n","typedarrayCtors":"var ctor = typedarrayCtors( 'float64' )\nctor = typedarrayCtors( 'float' )\n","typedarrayDataTypes":"var out = typedarrayDataTypes()\n","typedarraypool":"var arr = typedarraypool()\narr = typedarraypool( 'float32' )\nvar arr = typedarraypool( 5 )\narr = typedarraypool( 5, 'int32' )\nvar arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool( arr1, 'float32' )\n","typedarraypool.malloc":"var arr = typedarraypool.malloc()\narr = typedarraypool.malloc( 'float32' )\nvar arr = typedarraypool.malloc( 5 )\narr = typedarraypool.malloc( 5, 'int32' )\nvar arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\n","typedarraypool.calloc":"var arr = typedarraypool.calloc()\narr = typedarraypool.calloc( 'float32' )\nvar arr = typedarraypool.calloc( 5 )\narr = typedarraypool.calloc( 5, 'int32' )\n","typedarraypool.free":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\n","typedarraypool.clear":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\ntypedarraypool.clear();\n","typedarraypool.highWaterMark":"typedarraypool.highWaterMark\n","typedarraypool.nbytes":"var arr = typedarraypool( 5 )\ntypedarraypool.nbytes\n","typedarraypool.factory":"var pool = typedarraypool.factory();\nvar arr1 = pool( 3, 'float64' )\n","typemax":"var m = typemax( 'int8' )\nm = typemax( 'uint32' )\n","typemin":"var m = typemin( 'int8' )\nm = typemin( 'uint32' )\n","typeOf":"var t = typeOf( 'a' )\nt = typeOf( 5 )\nt = typeOf( NaN )\nt = typeOf( true )\nt = typeOf( false )\nt = typeOf( null )\nt = typeOf( undefined )\nt = typeOf( [] )\nt = typeOf( {} )\nt = typeOf( function noop() {} )\nt = typeOf( Symbol( 'beep' ) )\nt = typeOf( /.+/ )\nt = typeOf( new String( 'beep' ) )\nt = typeOf( new Number( 5 ) )\nt = typeOf( new Boolean( false ) )\nt = typeOf( new Array() )\nt = typeOf( new Object() )\nt = typeOf( new Int8Array( 10 ) )\nt = typeOf( new Uint8Array( 10 ) )\nt = typeOf( new Uint8ClampedArray( 10 ) )\nt = typeOf( new Int16Array( 10 ) )\nt = typeOf( new Uint16Array( 10 ) )\nt = typeOf( new Int32Array( 10 ) )\nt = typeOf( new Uint32Array( 10 ) )\nt = typeOf( new Float32Array( 10 ) )\nt = typeOf( new Float64Array( 10 ) )\nt = typeOf( new ArrayBuffer( 10 ) )\nt = typeOf( new Date() )\nt = typeOf( new RegExp( '.+' ) )\nt = typeOf( new Map() )\nt = typeOf( new Set() )\nt = typeOf( new WeakMap() )\nt = typeOf( new WeakSet() )\nt = typeOf( new Error( 'beep' ) )\nt = typeOf( new TypeError( 'beep' ) )\nt = typeOf( new SyntaxError( 'beep' ) )\nt = typeOf( new ReferenceError( 'beep' ) )\nt = typeOf( new URIError( 'beep' ) )\nt = typeOf( new RangeError( 'beep' ) )\nt = typeOf( new EvalError( 'beep' ) )\nt = typeOf( Math )\nt = typeOf( JSON )\nfunction beep() { return arguments; };\nt = typeOf( beep() )\nt = typeOf( new Buffer( 10 ) )\nfunction Person() { return this };\nt = typeOf( new Person() )\nvar Foo = function () { return this; };\nt = typeOf( new Foo() )\n","UINT8_MAX":"UINT8_MAX\n","UINT8_NUM_BYTES":"UINT8_NUM_BYTES\n","Uint8Array":"var arr = new Uint8Array()\nvar arr = new Uint8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8Array( buf, 0, 4 )\n","Uint8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n","Uint8Array.of":"var arr = Uint8Array.of( 1, 2 )\n","Uint8Array.BYTES_PER_ELEMENT":"Uint8Array.BYTES_PER_ELEMENT\n","Uint8Array.name":"Uint8Array.name\n","Uint8Array.prototype.buffer":"var arr = new Uint8Array( 5 );\narr.buffer\n","Uint8Array.prototype.byteLength":"var arr = new Uint8Array( 5 );\narr.byteLength\n","Uint8Array.prototype.byteOffset":"var arr = new Uint8Array( 5 );\narr.byteOffset\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8Array.prototype.length":"var arr = new Uint8Array( 5 );\narr.length\n","Uint8Array.prototype.copyWithin":"var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8Array.prototype.entries":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.every":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8Array.prototype.fill":"var arr = new Uint8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8Array.prototype.filter":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8Array.prototype.find":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8Array.prototype.findIndex":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8Array.prototype.forEach":"var arr = new Uint8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8Array.prototype.includes":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8Array.prototype.indexOf":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8Array.prototype.join":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8Array.prototype.keys":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.lastIndexOf":"var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8Array.prototype.map":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8Array.prototype.reduce":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8Array.prototype.reduceRight":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8Array.prototype.reverse":"var arr = new Uint8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8Array.prototype.set":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8Array.prototype.slice":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8Array.prototype.some":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8Array.prototype.sort":"var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8Array.prototype.subarray":"var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8Array.prototype.toLocaleString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8Array.prototype.toString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint8Array.prototype.values":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray":"var arr = new Uint8ClampedArray()\nvar arr = new Uint8ClampedArray( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8ClampedArray( buf, 0, 4 )\n","Uint8ClampedArray.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n","Uint8ClampedArray.of":"var arr = Uint8ClampedArray.of( 1, 2 )\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"Uint8ClampedArray.BYTES_PER_ELEMENT\n","Uint8ClampedArray.name":"Uint8ClampedArray.name\n","Uint8ClampedArray.prototype.buffer":"var arr = new Uint8ClampedArray( 5 );\narr.buffer\n","Uint8ClampedArray.prototype.byteLength":"var arr = new Uint8ClampedArray( 5 );\narr.byteLength\n","Uint8ClampedArray.prototype.byteOffset":"var arr = new Uint8ClampedArray( 5 );\narr.byteOffset\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8ClampedArray( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8ClampedArray.prototype.length":"var arr = new Uint8ClampedArray( 5 );\narr.length\n","Uint8ClampedArray.prototype.copyWithin":"var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8ClampedArray.prototype.entries":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.every":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8ClampedArray.prototype.fill":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8ClampedArray.prototype.filter":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8ClampedArray.prototype.find":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8ClampedArray.prototype.findIndex":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8ClampedArray.prototype.forEach":"var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8ClampedArray.prototype.includes":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8ClampedArray.prototype.indexOf":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8ClampedArray.prototype.join":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8ClampedArray.prototype.keys":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.lastIndexOf":"var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8ClampedArray.prototype.map":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8ClampedArray.prototype.reduce":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8ClampedArray.prototype.reduceRight":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8ClampedArray.prototype.reverse":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8ClampedArray.prototype.set":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8ClampedArray.prototype.slice":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8ClampedArray.prototype.some":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8ClampedArray.prototype.sort":"var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8ClampedArray.prototype.subarray":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8ClampedArray.prototype.toLocaleString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8ClampedArray.prototype.toString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toString()\n","Uint8ClampedArray.prototype.values":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT16_MAX":"UINT16_MAX\n","UINT16_NUM_BYTES":"UINT16_NUM_BYTES\n","Uint16Array":"var arr = new Uint16Array()\nvar arr = new Uint16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Uint16Array( buf, 0, 4 )\n","Uint16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n","Uint16Array.of":"var arr = Uint16Array.of( 1, 2 )\n","Uint16Array.BYTES_PER_ELEMENT":"Uint16Array.BYTES_PER_ELEMENT\n","Uint16Array.name":"Uint16Array.name\n","Uint16Array.prototype.buffer":"var arr = new Uint16Array( 5 );\narr.buffer\n","Uint16Array.prototype.byteLength":"var arr = new Uint16Array( 5 );\narr.byteLength\n","Uint16Array.prototype.byteOffset":"var arr = new Uint16Array( 5 );\narr.byteOffset\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint16Array.prototype.length":"var arr = new Uint16Array( 5 );\narr.length\n","Uint16Array.prototype.copyWithin":"var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint16Array.prototype.entries":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.every":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint16Array.prototype.fill":"var arr = new Uint16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint16Array.prototype.filter":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint16Array.prototype.find":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint16Array.prototype.findIndex":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint16Array.prototype.forEach":"var arr = new Uint16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint16Array.prototype.includes":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint16Array.prototype.indexOf":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint16Array.prototype.join":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint16Array.prototype.keys":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.lastIndexOf":"var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint16Array.prototype.map":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint16Array.prototype.reduce":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint16Array.prototype.reduceRight":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint16Array.prototype.reverse":"var arr = new Uint16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint16Array.prototype.set":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint16Array.prototype.slice":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint16Array.prototype.some":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint16Array.prototype.sort":"var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint16Array.prototype.subarray":"var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint16Array.prototype.toLocaleString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint16Array.prototype.toString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint16Array.prototype.values":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT32_MAX":"UINT32_MAX\n","UINT32_NUM_BYTES":"UINT32_NUM_BYTES\n","Uint32Array":"var arr = new Uint32Array()\nvar arr = new Uint32Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Uint32Array( buf, 0, 4 )\n","Uint32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n","Uint32Array.of":"var arr = Uint32Array.of( 1, 2 )\n","Uint32Array.BYTES_PER_ELEMENT":"Uint32Array.BYTES_PER_ELEMENT\n","Uint32Array.name":"Uint32Array.name\n","Uint32Array.prototype.buffer":"var arr = new Uint32Array( 5 );\narr.buffer\n","Uint32Array.prototype.byteLength":"var arr = new Uint32Array( 5 );\narr.byteLength\n","Uint32Array.prototype.byteOffset":"var arr = new Uint32Array( 5 );\narr.byteOffset\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint32Array.prototype.length":"var arr = new Uint32Array( 5 );\narr.length\n","Uint32Array.prototype.copyWithin":"var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint32Array.prototype.entries":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.every":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint32Array.prototype.fill":"var arr = new Uint32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint32Array.prototype.filter":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint32Array.prototype.find":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint32Array.prototype.findIndex":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint32Array.prototype.forEach":"var arr = new Uint32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint32Array.prototype.includes":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint32Array.prototype.indexOf":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint32Array.prototype.join":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint32Array.prototype.keys":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.lastIndexOf":"var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint32Array.prototype.map":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint32Array.prototype.reduce":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint32Array.prototype.reduceRight":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint32Array.prototype.reverse":"var arr = new Uint32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint32Array.prototype.set":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint32Array.prototype.slice":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint32Array.prototype.some":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint32Array.prototype.sort":"var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint32Array.prototype.subarray":"var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint32Array.prototype.toLocaleString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint32Array.prototype.toString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint32Array.prototype.values":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","umask":"var mask = umask()\nmask = umask( { 'symbolic': true } )\n","uncapitalize":"var out = uncapitalize( 'Beep' )\nout = uncapitalize( 'bOOp' )\n","uncapitalizeKeys":"var obj = { 'AA': 1, 'BB': 2 };\nvar out = uncapitalizeKeys( obj )\n","uncurry":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n };\nvar fcn = uncurry( addX );\nvar sum = fcn( 2, 3 )\nfunction add( x ) {\n return function add( y ) {\n return x + y;\n };\n };\nfcn = uncurry( add, 2 );\nsum = fcn( 9 )\nfunction addX( x ) {\n this.x = x;\n return addY;\n };\nfunction addY( y ) {\n return this.x + y;\n };\nfcn = uncurry( addX, {} );\nsum = fcn( 2, 3 )\n","uncurryRight":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n };\nvar fcn = uncurryRight( addX );\nvar sum = fcn( 3, 2 )\nfunction add( y ) {\n return function add( x ) {\n return x + y;\n };\n };\nfcn = uncurryRight( add, 2 );\nsum = fcn( 9 )\nfunction addY( y ) {\n this.y = y;\n return addX;\n };\nfunction addX( x ) {\n return x + this.y;\n };\nfcn = uncurryRight( addY, {} );\nsum = fcn( 3, 2 )\n","UNICODE_MAX":"UNICODE_MAX\n","UNICODE_MAX_BMP":"UNICODE_MAX_BMP\n","UnicodeColumnChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeColumnChartSparkline( data );\nchart.render()\n","UnicodeLineChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeLineChartSparkline( data );\nchart.render()\n","UnicodeSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeSparkline( data );\nchart.render()\nchart.type = 'line';\nchart.render()\n","UnicodeTristateChartSparkline":"var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\nvar chart = new UnicodeTristateChartSparkline( data );\nchart.render()\n","UnicodeUpDownChartSparkline":"var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\nvar chart = new UnicodeUpDownChartSparkline( data );\nchart.render()\n","UnicodeWinLossChartSparkline":"var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\nvar chart = new UnicodeWinLossChartSparkline( data );\nchart.render()\n","unlink":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nunlink( './beep/boop.txt', done );\n","unlink.sync":"var out = unlink.sync( './beep/boop.txt' );\n","unshift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = unshift( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = unshift( arr, 3.0, 4.0 )\narr = { 'length': 1, '0': 1.0 };\narr = unshift( arr, 2.0, 3.0 )\n","until":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nuntil( predicate, beep )\n","untilAsync":"function predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nuntilAsync( predicate, fcn, done )\n","untilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nuntilEach( arr, predicate, logger )\n","untilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nuntilEachRight( arr, predicate, logger )\n","unzip":"var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nvar out = unzip( arr )\narr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nout = unzip( arr, [ 0, 2 ] )\n","uppercase":"var out = uppercase( 'bEEp' )\n","uppercaseKeys":"var obj = { 'a': 1, 'b': 2 };\nvar out = uppercaseKeys( obj )\n","US_STATES_ABBR":"var list = US_STATES_ABBR()\n","US_STATES_CAPITALS":"var list = US_STATES_CAPITALS()\n","US_STATES_CAPITALS_NAMES":"var out = US_STATES_CAPITALS_NAMES()\n","US_STATES_NAMES":"var list = US_STATES_NAMES()\n","US_STATES_NAMES_CAPITALS":"var out = US_STATES_NAMES_CAPITALS()\n","utf16ToUTF8Array":"var str = '☃';\nvar out = utf16ToUTF8Array( str )\n","vartest":"var x = [ 610, 610, 550, 590, 565, 570 ];\nvar y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\nvar out = vartest( x, y )\nvar table = out.print()\n","waterfall":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nwaterfall( fcns, done );\n","waterfall.factory":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nvar waterfall = waterfall.factory( fcns, done );\nwaterfall();\nwaterfall();\nwaterfall();\n","WebAssemblyMemory":"var mem = new WebAssemblyMemory( { 'initial': 0 } )\n","WebAssemblyMemory.prototype.buffer":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.buffer\n","WebAssemblyMemory.prototype.grow":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.grow( 1 )\n","whileAsync":"function predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nwhileAsync( predicate, fcn, done )\n","whileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nwhileEach( arr, predicate, logger )\n","whileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nwhileEachRight( arr, predicate, logger )\n","whilst":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nwhilst( predicate, beep )\n","wilcoxon":"var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\nvar out = wilcoxon( x )\nrunif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\nvar x = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = runif();\n y[ i ] = runif();\n }\nout = wilcoxon( x, y )\nvar table = out.print()\nout = wilcoxon( arr, { 'alpha': 0.01 });\ntable = out.print()\nout = wilcoxon( arr, { 'mu': 10 })\nout = wilcoxon( arr, { 'alternative': 'less' });\ntable = out.print()\nout = wilcoxon( arr, { 'alternative': 'greater' });\ntable = out.print()\n","writableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = writableProperties( obj )\n","writablePropertiesIn":"var props = writablePropertiesIn( [] )\n","writablePropertyNames":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNames( obj )\n","writablePropertyNamesIn":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNamesIn( obj )\n","writablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbols( obj )\n","writablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbolsIn( obj )\n","writeFile":"function onWrite( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nwriteFile( './beep/boop.txt', 'beep boop', onWrite );\n","writeFile.sync":"var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n","zip":"var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\nvar opts = { 'trunc': false };\nout = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n","ztest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ztest( x, 2.0 )\narr = [ 2, 4, 3, 1, 0 ];\nout = ztest( arr, 2.0, { 'alpha': 0.01 } );\ntable = out.print()\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'alternative': 'less' } )\nout = ztest( arr, 1.0, { 'alternative': 'greater' } )\n","ztest2":"var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\nvar y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\nvar out = ztest2( x, y, 2.0, 2.0 )\nvar table = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 1.0 );\n }\ny = new Array( 100 );\n for ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 0.0, 2.0 );\n }\nout = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n"} diff --git a/lib/node_modules/@stdlib/repl/help/data/data.csv b/lib/node_modules/@stdlib/repl/help/data/data.csv index 51c417924229..ec8fd9195392 100644 --- a/lib/node_modules/@stdlib/repl/help/data/data.csv +++ b/lib/node_modules/@stdlib/repl/help/data/data.csv @@ -229,7 +229,7 @@ base.cbrt,"\nbase.cbrt( x )\n Computes the cube root of a double-precision fl base.cbrtf,"\nbase.cbrtf( x )\n Computes the cube root of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrtf( 64.0 )\n 4.0\n > y = base.cbrtf( 27.0 )\n 3.0\n > y = base.cbrtf( 0.0 )\n 0.0\n > y = base.cbrtf( -0.0 )\n -0.0\n > y = base.cbrtf( -9.0 )\n ~-2.08\n > y = base.cbrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.sqrtf\n" base.cceil,"\nbase.cceil( z )\n Rounds each component of a double-precision complex floating-point number\n toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n [ -1.0, 3.0 ]\n\n See Also\n --------\n base.cceiln, base.cfloor, base.cround\n" base.cceilf,"\nbase.cceilf( z )\n Rounds each component of a single-precision complex floating-point number\n toward positive infinity.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n [ -1.0, 3.0 ]\n\n See Also\n --------\n base.cceil\n" -base.cceiln,"\nbase.cceiln( z, n )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n \n > var re = real( out )\n 5.56\n > var im = imag( out )\n -3.33\n\n See Also\n --------\n base.cceil, base.cfloorn, base.croundn\n" +base.cceiln,"\nbase.cceiln( z, n )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n [ 5.56, -3.33 ]\n\n See Also\n --------\n base.cceil, base.cfloorn, base.croundn\n" base.ccis,"\nbase.ccis( z )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.ccis( new Complex128( 0.0, 0.0 ) )\n [ 1.0, 0.0 ]\n > y = base.ccis( new Complex128( 1.0, 0.0 ) )\n [ ~0.540, ~0.841 ]\n\n" base.cdiv,"\nbase.cdiv( z1, z2 )\n Divides two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( -13.0, -1.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var y = base.cdiv( z1, z2 )\n \n > var re = real( y )\n 5.0\n > var im = imag( y )\n 3.0\n\n\nbase.cdiv.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Divides two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cdiv.assign( -13.0, -1.0, -2.0, 1.0, out, 1, 0 )\n [ 5.0, 3.0 ]\n\n\nbase.cdiv.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Divides two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ -13.0, -1.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cdiv.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n base.cadd, base.cmul, base.csub" base.cdiv.assign,"\nbase.cdiv.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Divides two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cdiv.assign( -13.0, -1.0, -2.0, 1.0, out, 1, 0 )\n [ 5.0, 3.0 ]" @@ -2445,8 +2445,8 @@ base.strided.ssort2ins,"\nbase.strided.ssort2ins( N, order, x, strideX, y, strid base.strided.ssort2ins.ndarray,"\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins" base.strided.ssort2sh,"\nbase.strided.ssort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh\n" base.strided.ssort2sh.ndarray,"\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh" -base.strided.ssorthp,"\nbase.strided.ssorthp( N, order, x, stride )\n Sorts a single-precision floating-point strided array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns the strided\n array unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for the strided array.\n\n Returns\n -------\n x: Float32Array\n Input array the strided array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssorthp( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for the strided array.\n\n offset: integer\n Starting index of the strided array.\n\n Returns\n -------\n x: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp\n" -base.strided.ssorthp.ndarray,"\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for the strided array.\n\n offset: integer\n Starting index of the strided array.\n\n Returns\n -------\n x: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp" +base.strided.ssorthp,"\nbase.strided.ssorthp( N, order, x, strideX )\n Sorts a single-precision floating-point strided array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns the strided array\n unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssorthp( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp\n" +base.strided.ssorthp.ndarray,"\nbase.strided.ssorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp" base.strided.ssortins,"\nbase.strided.ssortins( N, order, x, stride )\n Sorts a single-precision floating-point strided array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssortins( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins\n" base.strided.ssortins.ndarray,"\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins" base.strided.ssortsh,"\nbase.strided.ssortsh( N, order, x, stride )\n Sorts a single-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssortsh( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh\n" @@ -2713,9 +2713,9 @@ Complex128.prototype.byteLength,"\nComplex128.prototype.byteLength\n Length ( COMPLEX128_NAN,"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX128_NAN\n \n\n See Also\n --------\n COMPLEX64_NAN\n" COMPLEX128_NUM_BYTES,"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n\n Examples\n --------\n > COMPLEX128_NUM_BYTES\n 16\n\n See Also\n --------\n COMPLEX64_NUM_BYTES, FLOAT64_NUM_BYTES\n" COMPLEX128_ZERO,"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX128_ZERO\n \n\n See Also\n --------\n COMPLEX64_ZERO\n" -Complex128Array,"\nComplex128Array()\n A 128-bit complex number array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex128Array()\n \n\n\nComplex128Array( length )\n Creates a 128-bit complex number array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex128Array( complexarray )\n Creates a 64-bit complex number array from another complex number array.\n\n Parameters\n ----------\n complexarray: Complex128Array\n Complex array from which to generate another complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr2 = new Complex128Array( arr1 )\n \n > var len = arr2.length\n 2\n\n\nComplex128Array( typedarray )\n Creates a 128-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr = new Complex128Array( buf )\n \n > var len = arr.length\n 2\n\n\nComplex128Array( obj )\n Creates a 128-bit complex number array from an array-like object or \n iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var len = arr1.length\n 2\n > var buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\n > var arr2 = new Complex128Array( buf )\n \n > len = arr2.length\n 2\n\n\nComplex128Array( buffer[, byteOffset[, length]] )\n Returns a 128-bit complex number array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 480 );\n > var arr1 = new Complex128Array( buf )\n \n > var len = arr1.length\n 30\n > var arr2 = new Complex128Array( buf, 16 )\n \n > len = arr2.length\n 29\n > var arr3 = new Complex128Array( buf, 16, 20 )\n \n > len = arr3.length\n 20\n\n\nComplex128Array.from( src[, clbk[, thisArg]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n \n Returns\n -------\n out: Complex128Array\n A typed array.\n \n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n\n\nComplex128Array.of( element0[, element1[, ...elementN]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number|ComplexLike\n Array element.\n\n element1: number |ComplexLike(optional)\n Array element.\n\n elementN: ...number|ComplexLike (optional)\n Array elements.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex128( 1.0, -1.0 );\n > var z2 = new Complex128( 2.0, -2.0 );\n > arr = Complex128Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n\n\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n 16\n\n\nComplex128Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex128Array.name\n 'Complex128Array'\n\n\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > var buf = arr.buffer\n \n\n\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var nbytes = arr.byteLength\n 160\n\n\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 480 );\n > arr = new Complex128Array( buf, 128 )\n \n > offset = arr.byteOffset\n 128\n\n\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 16\n\n\nComplex128Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex128Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n\n\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, ]\n > var re = real( v[ 1 ] )\n 1.0\n > var im = imag( v[ 1 ] )\n -1.0\n > v = it.next().value\n [ 1, ]\n > re = real( v[ 1 ] )\n 2.0\n > im = imag( v[ 1 ] )\n -2.0\n > v = it.next().value\n [ 2, ]\n > re = real( v[ 1 ] )\n 3.0\n > im = imag( v[ 1 ] )\n -3.0\n > var bool = it.next().done\n true\n\n\nComplex128Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) > 0.0 ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nComplex128Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex128\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex128Array( 3 )\n \n > arr.fill( new Complex128( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n 1.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n\n\nComplex128Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n 2.0\n\n\nComplex128Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n 1.0\n\n\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context. \n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n 2.0\n\n\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1\n\n\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'\n\n\nComplex128Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n\n\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n false\n\n\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n -1\n\n\nComplex128Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n \n Returns\n -------\n out: string\n Array serialized as a string.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'\n\n\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n 0\n\n\nComplex128Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n \n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n\n\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element. \n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.cadd )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.cadd )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n -1.0\n\n\nComplex128Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex128|Complex128Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > arr.set( new Complex128( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n\n\nComplex128Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n \n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n \n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nComplex128Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n \n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'\n\n\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n 3.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n 2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n\n\nComplex128Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n \n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n -1.0\n > v = it.next().value\n \n > re = real( v )\n 2.0\n > im = imag( v )\n -2.0\n > var bool = it.next().done\n true\n\n\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: Complex128\n Element value. \n\n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\n See Also\n --------\n Complex64Array, complex, Complex128" -Complex128Array.from,"\nComplex128Array.from( src[, clbk[, thisArg]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n \n Returns\n -------\n out: Complex128Array\n A typed array.\n \n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0" -Complex128Array.of,"\nComplex128Array.of( element0[, element1[, ...elementN]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number|ComplexLike\n Array element.\n\n element1: number |ComplexLike(optional)\n Array element.\n\n elementN: ...number|ComplexLike (optional)\n Array elements.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex128( 1.0, -1.0 );\n > var z2 = new Complex128( 2.0, -2.0 );\n > arr = Complex128Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0" +Complex128Array,"\nComplex128Array()\n A 128-bit complex number array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex128Array()\n \n\n\nComplex128Array( length )\n Creates a 128-bit complex number array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex128Array( complexarray )\n Creates a 64-bit complex number array from another complex number array.\n\n Parameters\n ----------\n complexarray: Complex128Array\n Complex array from which to generate another complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr2 = new Complex128Array( arr1 )\n \n > var len = arr2.length\n 2\n\n\nComplex128Array( typedarray )\n Creates a 128-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr = new Complex128Array( buf )\n \n > var len = arr.length\n 2\n\n\nComplex128Array( obj )\n Creates a 128-bit complex number array from an array-like object or\n iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var len = arr1.length\n 2\n > var buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\n > var arr2 = new Complex128Array( buf )\n \n > len = arr2.length\n 2\n\n\nComplex128Array( buffer[, byteOffset[, length]] )\n Returns a 128-bit complex number array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 480 );\n > var arr1 = new Complex128Array( buf )\n \n > var len = arr1.length\n 30\n > var arr2 = new Complex128Array( buf, 16 )\n \n > len = arr2.length\n 29\n > var arr3 = new Complex128Array( buf, 16, 20 )\n \n > len = arr3.length\n 20\n\n\nComplex128Array.from( src[, clbk[, thisArg]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.of( element0[, element1[, ...elementN]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number|ComplexLike\n Array element.\n\n element1: number |ComplexLike(optional)\n Array element.\n\n elementN: ...number|ComplexLike (optional)\n Array elements.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex128( 1.0, -1.0 );\n > var z2 = new Complex128( 2.0, -2.0 );\n > arr = Complex128Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n\n\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n 16\n\n\nComplex128Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex128Array.name\n 'Complex128Array'\n\n\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > var buf = arr.buffer\n \n\n\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var nbytes = arr.byteLength\n 160\n\n\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 480 );\n > arr = new Complex128Array( buf, 128 )\n \n > offset = arr.byteOffset\n 128\n\n\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 16\n\n\nComplex128Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex128Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, [ 1.0, -1.0 ] ]\n > v = it.next().value\n [ 1, [ 2.0, -2.0 ] ]\n > v = it.next().value\n [ 2, [ 3.0, -3.0 ] ]\n > var bool = it.next().done\n true\n\n\nComplex128Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) > 0.0 ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nComplex128Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex128\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( 3 )\n \n > arr.fill( new Complex128( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, 1.0 ]\n > z = arr.get( 1 )\n [ 1.0, 1.0 ]\n > z = arr.get( 2 )\n [ 1.0, 1.0 ]\n\n\nComplex128Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n [ 2.0, 2.0 ]\n\n\nComplex128Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n [ 1.0, 1.0 ]\n\n\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n [ 2.0, 2.0 ]\n\n\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1\n\n\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'\n\n\nComplex128Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n false\n\n\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n -1\n\n\nComplex128Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'\n\n\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n 0\n\n\nComplex128Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n\n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n [ 1.0, -1.0 ]\n > z = out.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.cadd )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.cadd )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 1.0, -1.0 ]\n\n\nComplex128Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex128|Complex128Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > arr.set( new Complex128( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n [ 2.0, -2.0 ]\n > z = out.get( 1 )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nComplex128Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'\n\n\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n 3.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n 2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n\n\nComplex128Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n -1.0\n > v = it.next().value\n \n > re = real( v )\n 2.0\n > im = imag( v )\n -2.0\n > var bool = it.next().done\n true\n\n\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: Complex128\n Element value.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\n See Also\n --------\n Complex64Array, complex, Complex128" +Complex128Array.from,"\nComplex128Array.from( src[, clbk[, thisArg]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 2.0, -2.0 ]" +Complex128Array.of,"\nComplex128Array.of( element0[, element1[, ...elementN]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number|ComplexLike\n Array element.\n\n element1: number |ComplexLike(optional)\n Array element.\n\n elementN: ...number|ComplexLike (optional)\n Array elements.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex128( 1.0, -1.0 );\n > var z2 = new Complex128( 2.0, -2.0 );\n > arr = Complex128Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]" Complex128Array.BYTES_PER_ELEMENT,"\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n 16" Complex128Array.name,"\nComplex128Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex128Array.name\n 'Complex128Array'" Complex128Array.prototype.buffer,"\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > var buf = arr.buffer\n " @@ -2723,38 +2723,38 @@ Complex128Array.prototype.byteLength,"\nComplex128Array.prototype.byteLength\n Complex128Array.prototype.byteOffset,"\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 480 );\n > arr = new Complex128Array( buf, 128 )\n \n > offset = arr.byteOffset\n 128" Complex128Array.prototype.BYTES_PER_ELEMENT,"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 16" Complex128Array.prototype.length,"\nComplex128Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10" -Complex128Array.prototype.at,"\nComplex128Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0" -Complex128Array.prototype.copyWithin,"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0" -Complex128Array.prototype.entries,"\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, ]\n > var re = real( v[ 1 ] )\n 1.0\n > var im = imag( v[ 1 ] )\n -1.0\n > v = it.next().value\n [ 1, ]\n > re = real( v[ 1 ] )\n 2.0\n > im = imag( v[ 1 ] )\n -2.0\n > v = it.next().value\n [ 2, ]\n > re = real( v[ 1 ] )\n 3.0\n > im = imag( v[ 1 ] )\n -3.0\n > var bool = it.next().done\n true" +Complex128Array.prototype.at,"\nComplex128Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n [ 2.0, -2.0 ]" +Complex128Array.prototype.copyWithin,"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]" +Complex128Array.prototype.entries,"\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, [ 1.0, -1.0 ] ]\n > v = it.next().value\n [ 1, [ 2.0, -2.0 ] ]\n > v = it.next().value\n [ 2, [ 3.0, -3.0 ] ]\n > var bool = it.next().done\n true" Complex128Array.prototype.every,"\nComplex128Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) > 0.0 ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true" -Complex128Array.prototype.fill,"\nComplex128Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex128\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex128Array( 3 )\n \n > arr.fill( new Complex128( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n 1.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0" -Complex128Array.prototype.filter,"\nComplex128Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n 2.0" -Complex128Array.prototype.find,"\nComplex128Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n 1.0" -Complex128Array.prototype.findIndex,"\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0" -Complex128Array.prototype.findLast,"\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context. \n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n 2.0" -Complex128Array.prototype.findLastIndex,"\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1" -Complex128Array.prototype.forEach,"\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'" -Complex128Array.prototype.get,"\nComplex128Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0" -Complex128Array.prototype.includes,"\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n false" -Complex128Array.prototype.indexOf,"\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n -1" -Complex128Array.prototype.join,"\nComplex128Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n \n Returns\n -------\n out: string\n Array serialized as a string.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'" -Complex128Array.prototype.keys,"\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true" -Complex128Array.prototype.lastIndexOf,"\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n 0" -Complex128Array.prototype.map,"\nComplex128Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n \n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0" -Complex128Array.prototype.reduce,"\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element. \n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.cadd )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0" -Complex128Array.prototype.reduceRight,"\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.cadd )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0" -Complex128Array.prototype.reverse,"\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n -1.0" -Complex128Array.prototype.set,"\nComplex128Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex128|Complex128Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > arr.set( new Complex128( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0" -Complex128Array.prototype.slice,"\nComplex128Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n \n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0" -Complex128Array.prototype.some,"\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n \n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true" -Complex128Array.prototype.sort,"\nComplex128Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n \n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0" +Complex128Array.prototype.fill,"\nComplex128Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex128\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( 3 )\n \n > arr.fill( new Complex128( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, 1.0 ]\n > z = arr.get( 1 )\n [ 1.0, 1.0 ]\n > z = arr.get( 2 )\n [ 1.0, 1.0 ]" +Complex128Array.prototype.filter,"\nComplex128Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n [ 2.0, 2.0 ]" +Complex128Array.prototype.find,"\nComplex128Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n [ 1.0, 1.0 ]" +Complex128Array.prototype.findIndex,"\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0" +Complex128Array.prototype.findLast,"\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n [ 2.0, 2.0 ]" +Complex128Array.prototype.findLastIndex,"\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1" +Complex128Array.prototype.forEach,"\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'" +Complex128Array.prototype.get,"\nComplex128Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n [ 2.0, -2.0 ]" +Complex128Array.prototype.includes,"\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n false" +Complex128Array.prototype.indexOf,"\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n -1" +Complex128Array.prototype.join,"\nComplex128Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'" +Complex128Array.prototype.keys,"\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true" +Complex128Array.prototype.lastIndexOf,"\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n 0" +Complex128Array.prototype.map,"\nComplex128Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n\n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n [ 1.0, -1.0 ]\n > z = out.get( 1 )\n [ 2.0, -2.0 ]" +Complex128Array.prototype.reduce,"\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.cadd )\n [ 3.0, -3.0 ]" +Complex128Array.prototype.reduceRight,"\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.cadd )\n [ 3.0, -3.0 ]" +Complex128Array.prototype.reverse,"\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 1.0, -1.0 ]" +Complex128Array.prototype.set,"\nComplex128Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex128|Complex128Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > arr.set( new Complex128( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]" +Complex128Array.prototype.slice,"\nComplex128Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n [ 2.0, -2.0 ]\n > z = out.get( 1 )\n [ 3.0, -3.0 ]" +Complex128Array.prototype.some,"\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true" +Complex128Array.prototype.sort,"\nComplex128Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 3.0, -3.0 ]" Complex128Array.prototype.subarray,"\nComplex128Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0" -Complex128Array.prototype.toLocaleString,"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'" -Complex128Array.prototype.toReversed,"\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n 3.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n 2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0" -Complex128Array.prototype.toSorted,"\nComplex128Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n \n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0" -Complex128Array.prototype.toString,"\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'" -Complex128Array.prototype.values,"\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n -1.0\n > v = it.next().value\n \n > re = real( v )\n 2.0\n > im = imag( v )\n -2.0\n > var bool = it.next().done\n true" -Complex128Array.prototype.with,"\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: Complex128\n Element value. \n\n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\n See Also\n --------\n Complex64Array, complex, Complex128" +Complex128Array.prototype.toLocaleString,"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'" +Complex128Array.prototype.toReversed,"\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n 3.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n 2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0" +Complex128Array.prototype.toSorted,"\nComplex128Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0" +Complex128Array.prototype.toString,"\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'" +Complex128Array.prototype.values,"\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n -1.0\n > v = it.next().value\n \n > re = real( v )\n 2.0\n > im = imag( v )\n -2.0\n > var bool = it.next().done\n true" +Complex128Array.prototype.with,"\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: Complex128\n Element value.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\n See Also\n --------\n Complex64Array, complex, Complex128" complexarray,"\ncomplexarray( [dtype] )\n Creates a complex typed array.\n\n The function supports the following data types:\n\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n\n The default typed array data type is `complex128`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray()\n \n > arr = complexarray( 'complex64' )\n \n\n\ncomplexarray( length[, dtype] )\n Returns a complex number typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray( 5 )\n \n > arr = complexarray( 5, 'complex64' )\n \n\n\ncomplexarray( complexarray[, dtype] )\n Creates a complex number typed array from another complex number typed\n array.\n\n Parameters\n ----------\n complexarray: ComplexArray\n Complex number typed array from which to generate another complex number\n typed array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( obj[, dtype] )\n Creates a complex number typed array from an array-like object or iterable.\n\n If an array-like object contains interleaved real and imaginary components,\n the array-like object must have a length which is a multiple of two.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a complex number typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first array element.\n Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = complexarray( buf, 0, 8, 'complex64' )\n \n\n See Also\n --------\n typedarray, realarray\n" complexarrayCtors,"\ncomplexarrayCtors( dtype )\n Returns a complex typed array constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Complex typed array constructor.\n\n Examples\n --------\n > var ctor = complexarrayCtors( 'complex64' )\n \n > ctor = complexarrayCtors( 'float32' )\n null\n\n See Also\n --------\n arrayCtors, typedarrayCtors, realarrayCtors\n" complexarrayDataTypes,"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n\n Returns\n -------\n out: Array\n List of complex typed array data types.\n\n Examples\n --------\n > var out = complexarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, typedarrayDataTypes, realarrayDataTypes, ndarrayDataTypes\n" diff --git a/lib/node_modules/@stdlib/repl/help/data/data.json b/lib/node_modules/@stdlib/repl/help/data/data.json index e7a1922a10dc..6f2b4eda45a1 100644 --- a/lib/node_modules/@stdlib/repl/help/data/data.json +++ b/lib/node_modules/@stdlib/repl/help/data/data.json @@ -1 +1 @@ -{"abs":"\nabs( x[, options] )\n Computes the absolute value for each element in an ndarray.\n\n The function returns an ndarray having the same shape as the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array. Must have a numeric or \"generic\" data type.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Output array data type. Must be a real-valued or \"generic\" data type.\n\n options.order: string (optional)\n Output array order. Must be either row-major (C-style) or column-major\n (Fortran-style). By default, the order of the output array is the same\n as the input array.\n\n Returns\n -------\n y: ndarray\n Output array containing element-wise results.\n\n Examples\n --------\n > var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\n > var x = array( arr );\n > var y = abs( x )\n [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]\n\n\nabs.assign( x, y )\n Computes the absolute value for each element in an ndarray and assigns\n results to a provided output ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array. Must have a numeric or \"generic\" data type.\n\n y: ndarray\n Output array.\n\n Returns\n -------\n y: ndarray\n Output array.\n\n Examples\n --------\n > var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\n > var x = array( arr );\n > var sh = ndarrayShape( x );\n > var y = ndzeros( sh );\n > var out = abs.assign( x, y )\n [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]\n > var bool = ( out === y )\n true\n\n","abs.assign":"\nabs.assign( x, y )\n Computes the absolute value for each element in an ndarray and assigns\n results to a provided output ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array. Must have a numeric or \"generic\" data type.\n\n y: ndarray\n Output array.\n\n Returns\n -------\n y: ndarray\n Output array.\n\n Examples\n --------\n > var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\n > var x = array( arr );\n > var sh = ndarrayShape( x );\n > var y = ndzeros( sh );\n > var out = abs.assign( x, y )\n [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]\n > var bool = ( out === y )\n true","acartesianPower":"\nacartesianPower( x, n )\n Returns the Cartesian power.\n\n If provided an empty array, the function returns an empty array.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n n: integer\n Power.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = acartesianPower( x, 2 )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianProduct, acartesianSquare\n","acartesianProduct":"\nacartesianProduct( x1, x2 )\n Returns the Cartesian product.\n\n If provided one or more empty arrays, the function returns an empty array.\n\n Parameters\n ----------\n x1: ArrayLikeObject\n First input array.\n\n x2: ArrayLikeObject\n Second input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x1 = [ 1, 2 ];\n > var x2 = [ 3, 4 ];\n > var out = acartesianProduct( x1, x2 )\n [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n See Also\n --------\n acartesianPower, acartesianSquare\n","acartesianSquare":"\nacartesianSquare( x )\n Returns the Cartesian square.\n\n If provided an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var out = acartesianSquare( [ 1, 2 ] )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianPower, acartesianProduct\n","acronym":"\nacronym( str[, options] )\n Generates an acronym for a given string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n options: Object (optional)\n Options.\n\n options.stopwords: Array (optional)\n Array of custom stop words.\n\n Returns\n -------\n out: string\n Acronym for the given string.\n\n Examples\n --------\n > var out = acronym( 'the quick brown fox' )\n 'QBF'\n > out = acronym( 'Hard-boiled eggs' )\n 'HBE'\n","aempty":"\naempty( length[, dtype] )\n Creates an uninitialized array having a specified length.\n\n In browser environments, the function always returns zero-filled arrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled array.\n\n In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n is *not* initialized. Memory contents are unknown and may contain\n *sensitive* data.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aempty( 2 )\n \n > arr = aempty( 2, 'float32' )\n \n\n See Also\n --------\n aemptyLike, afull, aones, azeros, ndempty\n","aemptyLike":"\naemptyLike( x[, dtype] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n\n In browser environments, the function always returns zero-filled arrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled array.\n\n In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n is *not* initialized. Memory contents are unknown and may contain\n *sensitive* data.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var arr = aemptyLike( x )\n \n > arr = aemptyLike( x, 'float32' )\n \n\n See Also\n --------\n aempty, afullLike, aonesLike, azerosLike, ndemptyLike\n","AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_111\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_96\n","afull":"\nafull( length, value[, dtype] )\n Returns a filled array having a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n value: any\n Fill value.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = afull( 2, 1.0 )\n [ 1.0, 1.0 ]\n > arr = afull( 2, 1.0, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afullLike, aones, azeros\n","afullLike":"\nafullLike( x[, dtype] )\n Returns a filled array having the same length and data type as a provided\n input array.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = afullLike( x, 1.0 )\n [ 1.0, 1.0 ]\n > y = afullLike( x, 1.0, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afull, aonesLike, azerosLike\n","alias2pkg":"\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","alias2related":"\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( 'base.sin' )\n [...]\n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","alias2standalone":"\nalias2standalone( alias )\n Returns the standalone package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Standalone package name.\n\n Examples\n --------\n > var v = alias2standalone( 'base.sin' )\n '@stdlib/math-base-special-sin'\n\n See Also\n --------\n alias2pkg, alias2related, aliases, pkg2alias, pkg2standalone\n","aliases":"\naliases( [namespace] )\n Returns a list of standard library aliases.\n\n Parameters\n ----------\n namespace: string (optional)\n Namespace filter.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n > o = aliases( '@stdlib/math/base/special' )\n [...]\n\n See Also\n --------\n alias2pkg, alias2related, pkg2alias\n","allocUnsafe":"\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","amskfilter":"\namskfilter( x, mask )\n Returns a new array by applying a mask to a provided input array.\n\n If a mask array element is truthy, the corresponding element in `x` is\n included in the output array; otherwise, the corresponding element in `x` is\n \"masked\" and thus excluded from the output array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n mask: Array|TypedArray|Object\n Mask array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = amskfilter( x, [ 0, 1, 0, 1 ] )\n [ 2, 4 ]\n\n See Also\n --------\n amskreject\n","amskput":"\namskput( x, mask, values[, options] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n\n In broadcasting modes, the function supports broadcasting a values array\n containing a single element against the number of falsy values in the mask\n array.\n\n In repeat mode, the function supports recycling elements in a values array\n to satisfy the number of falsy values in the mask array.\n\n The function mutates the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n mask: ArrayLikeObject\n Mask array. If a mask array element is falsy, the corresponding element\n in `x` is *replaced*; otherwise, the corresponding element in `x` is\n \"masked\" and thus left unchanged.\n\n values: ArrayLikeObject\n Values to set.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n String specifying behavior when the number of values to set does not\n equal the number of falsy mask values. The function supports the\n following modes:\n\n - 'strict': specifies that the function must raise an exception when the\n number of values does not *exactly* equal the number of falsy mask\n values.\n - 'non_strict': specifies that the function must raise an exception when\n the function is provided insufficient values to satisfy the mask array.\n - 'strict_broadcast': specifies that the function must broadcast a\n single-element values array and otherwise raise an exception when the\n number of values does not **exactly** equal the number of falsy mask\n values.\n - 'broadcast': specifies that the function must broadcast a single-\n element values array and otherwise raise an exception when the function\n is provided insufficient values to satisfy the mask array.\n - 'repeat': specifies that the function must reuse provided values when\n replacing elements in `x` in order to satisfy the mask array.\n\n Default: 'repeat'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n aplace, aput, atake\n","amskreject":"\namskreject( x, mask )\n Returns a new array by applying a mask to a provided input array.\n\n If a mask array element is falsy, the corresponding element in `x` is\n included in the output array; otherwise, the corresponding element in `x` is\n \"masked\" and thus excluded from the output array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n mask: Array|TypedArray|Object\n Mask array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = amskreject( x, [ 0, 1, 0, 1 ] )\n [ 1, 3 ]\n\n See Also\n --------\n amskfilter\n","anans":"\nanans( length[, dtype] )\n Returns an array filled with NaNs and having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = anans( 2 )\n [ NaN, NaN ]\n > arr = anans( 2, 'float32' )\n [ NaN, NaN ]\n\n See Also\n --------\n afull, anansLike, aones, azeros\n","anansLike":"\nanansLike( x[, dtype] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = anansLike( x )\n [ NaN, NaN ]\n > y = anansLike( x, 'float32' )\n [ NaN, NaN ]\n\n See Also\n --------\n afullLike, anans, aonesLike, azerosLike\n","anova1":"\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatment: Object\n Treatment results.\n\n out.treatment.df: number\n Treatment degrees of freedom.\n\n out.treatment.ss: number\n Treatment sum of squares.\n\n out.treatment.ms: number\n Treatment mean sum of squares.\n\n out.error: Object\n Error results.\n\n out.error.df: number\n Error degrees of freedom.\n\n out.error.ss: number\n Error sum of squares.\n\n out.error.ms: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n","any":"\nany( collection )\n Tests whether at least one element in a collection is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an element is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 1 ];\n > var bool = any( arr )\n true\n\n See Also\n --------\n anyBy, every, forEach, none, some\n","anyBy":"\nanyBy( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4, -1 ];\n > var bool = anyBy( arr, negative )\n true\n\n See Also\n --------\n anyByAsync, anyByRight, everyBy, forEach, noneBy, someBy\n","anyByAsync":"\nanyByAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync\n","anyByAsync.factory":"\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync","anyByRight":"\nanyByRight( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, 2, 3, 4 ];\n > var bool = anyByRight( arr, negative )\n true\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByRight, forEachRight, noneByRight, someByRight\n","anyByRightAsync":"\nanyByRightAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync","anyInBy":"\nanyInBy( object, predicate[, thisArg ] )\n Tests whether at least one value in an object passes a test implemented by\n a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: the value of the current property being processed in the object\n - key: the key of the current property being processed in the object\n - object: the input object\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate. It must be non-null.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any value; otherwise, it returns `false`.\n\n Examples\n --------\n > function isNegative(value) { return value < 0 }\n > var obj = { a: 1, b: -2, c: 3, d: 4 }\n > var result = anyInBy(obj, isNegative)\n true\n\n See Also\n --------\n anyBy, anyOwnBy, everyInBy, someInBy","anyOwnBy":"\nanyOwnBy( object, predicate[, thisArg ] )\n Tests whether at least one own property of an object passes a\n test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return\n value.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for one own property; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var obj = { 'a': -1, 'b': 2, 'c': -3 };\n > var bool = anyOwnBy( obj, positive )\n true\n\n See Also\n --------\n anyBy, anyInBy, everyOwnBy, someOwnBy\n","aones":"\naones( length[, dtype] )\n Returns an array filled with ones and having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aones( 2 )\n [ 1.0, 1.0 ]\n > arr = aones( 2, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afull, anans, aonesLike, azeros\n","aonesLike":"\naonesLike( x[, dtype] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = aonesLike( x )\n [ 1.0, 1.0 ]\n > y = aonesLike( x, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afullLike, anansLike, aones, azerosLike\n","aoneTo":"\naoneTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aoneTo( 2 )\n [ 1.0, 2.0 ]\n > arr = aoneTo( 2, 'float32' )\n [ 1.0, 2.0 ]\n\n See Also\n --------\n afull, aones, aoneToLike, azeroTo\n","aoneToLike":"\naoneToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aoneToLike( [ 0, 0 ] )\n [ 1, 2 ]\n > arr = aoneToLike( [ 0, 0 ], 'float32' )\n [ 1.0, 2.0 ]\n\n See Also\n --------\n afullLike, aonesLike, aoneTo, azeroToLike\n","APERY":"\nAPERY\n Apéry's constant.\n\n Examples\n --------\n > APERY\n 1.2020569031595942\n\n","aplace":"\naplace( x, mask, values[, options] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n\n In broadcasting modes, the function supports broadcasting a values array\n containing a single element against the number of truthy values in the mask\n array.\n\n In repeat mode, the function supports recycling elements in a values array\n to satisfy the number of truthy values in the mask array.\n\n The function mutates the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n mask: ArrayLikeObject\n Mask array. If a mask array element is truthy, the corresponding element\n in `x` is *replaced*; otherwise, the corresponding element in `x` is\n \"masked\" and thus left unchanged.\n\n values: ArrayLikeObject\n Values to set.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n String specifying behavior when the number of values to set does not\n equal the number of truthy mask values. The function supports the\n following modes:\n\n - 'strict': specifies that the function must raise an exception when the\n number of values does not *exactly* equal the number of truthy mask\n values.\n - 'non_strict': specifies that the function must raise an exception when\n the function is provided insufficient values to satisfy the mask array.\n - 'strict_broadcast': specifies that the function must broadcast a\n single-element values array and otherwise raise an exception when the\n number of values does not **exactly** equal the number of truthy mask\n values.\n - 'broadcast': specifies that the function must broadcast a single-\n element values array and otherwise raise an exception when the function\n is provided insufficient values to satisfy the mask array.\n - 'repeat': specifies that the function must reuse provided values when\n replacing elements in `x` in order to satisfy the mask array.\n\n Default: 'repeat'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n amskput, aput, atake\n","append":"\nappend( collection1, collection2 )\n Adds the elements of one collection to the end of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = append( arr, [ 6.0, 7.0 ] )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = append( arr, [ 3.0, 4.0 ] )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = append( arr, [ 1.0, 2.0 ] )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n prepend, push\n","aput":"\naput( x, indices, values[, options] )\n Replaces specified elements of an array with provided values.\n\n The function supports broadcasting a `values` array containing a single\n element against an `indices` array containing one or more elements.\n\n The function mutates the input array.\n\n Because each index is only validated at the time of replacing a particular\n element, mutation may occur even when one or more indices are out-of-bounds,\n including when the index mode indicates to raise an exception.\n\n If `indices` is an empty array, the function returns the input array\n unchanged.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n indices: ArrayLikeObject\n List of element indices.\n\n values: ArrayLikeObject\n Values to set. When `indices` contains one or more elements, `values`\n must be broadcast compatible with `indices` (i.e., must have either one\n element or the same number of elements as `indices`).\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n Specifies how to handle an index outside the interval [0, max], where\n `max` is the maximum possible array index. If equal to 'throw', the\n function throws an error. If equal to 'normalize', the function throws\n an error if provided an out-of-bounds normalized index. If equal to\n 'wrap', the function wraps around an index using modulo arithmetic. If\n equal to 'clamp', the function sets an index to either 0 (minimum index)\n or the maximum index. Default: 'normalize'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = aput( x, [ 1, 3 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n amskput, aplace, atake\n","ARCH":"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n\n Current possible values:\n\n - arm\n - arm64\n - ia32\n - mips\n - mipsel\n - ppc\n - ppc64\n - s390\n - s390x\n - x32\n - x64\n\n Examples\n --------\n > ARCH\n \n\n See Also\n --------\n PLATFORM\n","argumentFunction":"\nargumentFunction( idx )\n Returns a function which always returns a specified argument.\n\n The input argument corresponds to the zero-based index of the argument to\n return.\n\n Parameters\n ----------\n idx: integer\n Argument index to return (zero-based).\n\n Returns\n -------\n out: Function\n Argument function.\n\n Examples\n --------\n > var argn = argumentFunction( 1 );\n > var v = argn( 3.14, -3.14, 0.0 )\n -3.14\n > v = argn( -1.0, -0.0, 1.0 )\n -0.0\n > v = argn( 'beep', 'boop', 'bop' )\n 'boop'\n > v = argn( 'beep' )\n undefined\n\n See Also\n --------\n constantFunction, identity\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n\n The first element is the absolute pathname of the executable that started\n the calling process.\n\n The second element is the path of the executed file.\n\n Any additional elements are additional command-line arguments.\n\n In browser environments, the array is empty.\n\n Examples\n --------\n > var execPath = ARGV[ 0 ]\n e.g., /usr/local/bin/node\n\n See Also\n --------\n ENV\n","array":"\narray( [buffer,] [options] )\n Returns a multidimensional array.\n\n Parameters\n ----------\n buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source.\n\n options: Object (optional)\n Options.\n\n options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source. If provided along with a `buffer` argument, the argument\n takes precedence.\n\n options.dtype: string|DataType (optional)\n Underlying storage data type. If not specified and a data source is\n provided, the data type is inferred from the provided data source. If an\n input data source is not of the same type, this option specifies the\n data type to which to cast the input data. For non-ndarray generic array\n data sources, the function casts generic array data elements to the\n default data type. In order to prevent this cast, the `dtype` option\n must be explicitly set to `'generic'`. Any time a cast is required, the\n `copy` option is set to `true`, as memory must be copied from the data\n source to an output data buffer. Default: 'float64'.\n\n options.order: string (optional)\n Specifies the memory layout of the data source as either row-major (C-\n style) or column-major (Fortran-style). The option may be one of the\n following values:\n\n - 'row-major': the order of the returned array is row-major.\n - 'column-major': the order of the returned array is column-major.\n - 'any': if a data source is column-major and not row-major, the order\n of the returned array is column-major; otherwise, the order of the\n returned array is row-major.\n - 'same': the order of the returned array matches the order of an input\n data source.\n\n Note that specifying an order which differs from the order of a\n provided data source does *not* entail a conversion from one memory\n layout to another. In short, this option is descriptive, not\n prescriptive. Default: 'row-major'.\n\n options.shape: Array (optional)\n Array shape (dimensions). If a shape is not specified, the function\n attempts to infer a shape based on a provided data source. For example,\n if provided a nested array, the function resolves nested array\n dimensions. If provided a multidimensional array data source, the\n function uses the array's associated shape. For most use cases, such\n inference suffices. For the remaining use cases, specifying a shape is\n necessary. For example, provide a shape to create a multidimensional\n array view over a linear data buffer, ignoring any existing shape meta\n data associated with a provided data source.\n\n options.flatten: boolean (optional)\n Boolean indicating whether to automatically flatten generic array data\n sources. If an array shape is not specified, the shape is inferred from\n the dimensions of nested arrays prior to flattening. If a use case\n requires partial flattening, partially flatten prior to invoking this\n function and set the option value to `false` to prevent further\n flattening during invocation. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to (shallow) copy source data to a new data\n buffer. The function does *not* perform a deep copy. To prevent\n undesired shared changes in state for generic arrays containing objects,\n perform a deep copy prior to invoking this function. Default: false.\n\n options.ndmin: integer (optional)\n Specifies the minimum number of dimensions. If an array shape has fewer\n dimensions than required by `ndmin`, the function prepends singleton\n dimensions to the array shape in order to satisfy the dimensions\n requirement. Default: 0.\n\n options.casting: string (optional)\n Specifies the casting rule used to determine acceptable casts. The\n option may be one of the following values:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'mostly-safe': allow \"safe casts\" and, for floating-point data types,\n downcasts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers\n and floats).\n\n Default: 'safe'.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. The\n option may be one of the following values:\n\n - 'throw': an ndarray instance throws an error when an index exceeds\n array dimensions.\n - 'normalize': an ndarray instance normalizes negative indices and\n throws an error when an index exceeds array dimensions.\n - 'wrap': an ndarray instance wraps around indices exceeding array\n dimensions using modulo arithmetic.\n - 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index.\n\n Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to\n\n - 'throw': an ndarray instance throws an error when a subscript exceeds\n array dimensions.\n - 'normalize': an ndarray instance normalizes negative subscripts and\n throws an error when a subscript exceeds array dimensions.\n - 'wrap': an ndarray instance wraps around subscripts exceeding array\n dimensions using modulo arithmetic.\n - 'clamp': an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index.\n\n If the number of modes is fewer than the number of dimensions, the\n function recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Multidimensional array.\n\n Examples\n --------\n // Create a 2x2 matrix:\n > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n ndarray\n","array2buffer":"\narray2buffer( arr )\n Allocates a buffer using an octet array.\n\n Parameters\n ----------\n arr: Array\n Array (or array-like object) of octets from which to copy.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n Buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","array2fancy":"\narray2fancy( x[, options] )\n Converts an array to an object supporting fancy indexing.\n\n An array supporting fancy indexing is an array which supports slicing via\n indexing expressions for both retrieval and assignment.\n\n A fancy array shares the *same* data as the provided input array. Hence, any\n mutations to the returned array will affect the underlying input array and\n vice versa.\n\n For operations returning a new array (e.g., when slicing or invoking an\n instance method), a fancy array returns a new fancy array having the same\n configuration as specified by provided options.\n\n A fancy array supports indexing using positive and negative integers (both\n numeric literals and strings), Slice instances, subsequence expressions,\n mask arrays, boolean arrays, and integer arrays.\n\n A fancy array supports all properties and methods of the input array, and,\n thus, a fancy array can be consumed by any API which supports array-like\n objects.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on array views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use (e.g., in the\n REPL) and scripting. For performance critical applications, prefer\n equivalent functional APIs supporting array-like objects.\n\n Fancy arrays support broadcasting in which assigned scalars and single-\n element arrays are repeated (without additional memory allocation) to match\n the length of a target array instance.\n\n Fancy array broadcasting follows the same rules as for ndarrays.\n\n Consequently, when assigning arrays to slices, the array on the right-hand-\n side must be broadcast-compatible with number of elements in the slice.\n\n Fancy arrays support (mostly) safe casts (i.e., any cast which can be\n performed without overflow or loss of precision, with the exception of\n floating-point arrays which are also allowed to downcast from higher\n precision to lower precision).\n\n When attempting to perform an unsafe cast, fancy arrays will raise an\n exception.\n\n When assigning a real-valued scalar to a complex number array (e.g.,\n Complex128Array or Complex64Array), a fancy array will cast the real-valued\n scalar to a complex number argument having an imaginary component equal to\n zero.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array supporting fancy indexing.\n\n Examples\n --------\n > var y = array2fancy( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]\n\n\narray2fancy.factory( [options] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an array to an object supporting fancy indexing.\n\n Examples\n --------\n > var f = array2fancy.factory();\n > var y = f( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]\n\n\narray2fancy.idx( x[, options] )\n Wraps a provided array as an array index object.\n\n For documentation and usage, see `ArrayIndex`.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n See Also\n --------\n aslice, FancyArray\n","array2fancy.factory":"\narray2fancy.factory( [options] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an array to an object supporting fancy indexing.\n\n Examples\n --------\n > var f = array2fancy.factory();\n > var y = f( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]","array2fancy.idx":"\narray2fancy.idx( x[, options] )\n Wraps a provided array as an array index object.\n\n For documentation and usage, see `ArrayIndex`.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n See Also\n --------\n aslice, FancyArray","array2iterator":"\narray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, circarray2iterator, array2iteratorRight, stridedarray2iterator\n","array2iteratorRight":"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator\n","ArrayBuffer":"\nArrayBuffer( size )\n Returns an array buffer having a specified number of bytes.\n\n Buffer contents are initialized to 0.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: ArrayBuffer\n An array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n\n\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1\n\n\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true\n\n\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","ArrayBuffer.length":"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1","ArrayBuffer.isView":"\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","arraybuffer2buffer":"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n Allocates a buffer from an ArrayBuffer.\n\n The behavior of this function varies across Node.js versions due to changes\n in the underlying Node.js APIs:\n\n - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n returns a view of an ArrayBuffer without copying the underlying memory.\n - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n Buffer which is not an ArrayBuffer view.\n - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n the underlying memory.\n\n Parameters\n ----------\n buf: ArrayBuffer\n Input array buffer.\n\n byteOffset: integer (optional)\n Index offset specifying the location of the first byte.\n\n length: integer (optional)\n Number of bytes to expose from the underlying ArrayBuffer.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var ab = new ArrayBuffer( 10 )\n \n > var buf = arraybuffer2buffer( ab )\n \n > var len = buf.length\n 10\n > buf = arraybuffer2buffer( ab, 2, 6 )\n \n > len = buf.length\n 6\n\n See Also\n --------\n Buffer, array2buffer, copyBuffer, string2buffer\n","arrayCtors":"\narrayCtors( dtype )\n Returns an array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = arrayCtors( 'float64' )\n \n > ctor = arrayCtors( 'float' )\n null\n\n See Also\n --------\n typedarrayCtors\n","arrayDataType":"\narrayDataType( array )\n Returns the data type of an array.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n array: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > var dt = arrayDataType( arr )\n 'float64'\n > dt = arrayDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataTypes\n","arrayDataTypes":"\narrayDataTypes( [kind] )\n Returns a list of array data types.\n\n When not provided a data type \"kind\", the function returns an array\n containing the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n The function supports the following data type \"kinds\":\n\n - floating_point: floating-point data types.\n - real_floating_point: real-valued floating-point data types.\n - complex_floating_point: complex-valued floating-point data types.\n - boolean: boolean data types.\n - integer: integer data types.\n - signed_integer: signed integer data types.\n - unsigned_integer: unsigned integer data types.\n - real: real-valued data types.\n - numeric: numeric data types.\n - typed: typed data types.\n - integer_index: integer index data types.\n - boolean_index: boolean index data types.\n - mask_index: mask index data types.\n - typed_index: typed index data types.\n - index: index data types.\n - all: all data types.\n\n Additionally, the function supports extending the \"kinds\" listed above by\n appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n Parameters\n ----------\n kind: string (optional)\n Data type kind.\n\n Returns\n -------\n out: Array\n List of array data types.\n\n Examples\n --------\n > var out = arrayDataTypes()\n [...]\n > out = arrayDataTypes( 'floating_point' )\n [...]\n > out = arrayDataTypes( 'floating_point_and_generic' )\n [...]\n\n See Also\n --------\n typedarrayDataTypes, ndarrayDataTypes\n","ArrayIndex":"\nArrayIndex( x[, options] )\n Wraps a provided array as an array index object.\n\n Array index instances have no explicit functionality; however, they are used\n by \"fancy\" arrays for element retrieval and assignment.\n\n By default, an instance is invalidated and removed from an internal cache\n immediately after a consumer resolves the underlying data associated with an\n instance using the `get` static method. Immediate invalidation and cache\n removal ensures that references to the underlying array are not the source\n of memory leaks.\n\n Because instances leverage an internal cache implementing the Singleton\n pattern, one must be sure to use the same constructor as consumers. If one\n uses a different constructor, the consumer will *not* be able to resolve the\n original wrapped array, as the consumer will attempt to resolve an instance\n in the wrong internal cache.\n\n Because non-persisted instances are freed after first use, in order to avoid\n holding onto memory and to allow garbage collection, one should avoid\n scenarios in which an instance is never used.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n\n\nArrayIndex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.free( idx.id )\n \n\n\nArrayIndex.get( id )\n Returns the array associated with the instance having a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing array data.\n\n out.data: Array|TypedArray|Object\n The underlying array associated with the provided identifier.\n\n out.type: string\n The type of array index.\n\n out.dtype: string\n The data type of the underlying array.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.get( idx.id )\n {...}\n\n\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array data.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.data\n [ 1, 2, 3, 4 ]\n\n\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.dtype\n 'generic'\n\n\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.id\n \n\n\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an array index is actively cached.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.isCached\n true\n\n\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n\n Returns\n -------\n out: string\n Array index type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.type\n \n\n\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toString()\n \n\n\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toJSON()\n { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n See Also\n --------\n array2fancy\n","ArrayIndex.free":"\nArrayIndex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.free( idx.id )\n ","ArrayIndex.get":"\nArrayIndex.get( id )\n Returns the array associated with the instance having a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing array data.\n\n out.data: Array|TypedArray|Object\n The underlying array associated with the provided identifier.\n\n out.type: string\n The type of array index.\n\n out.dtype: string\n The data type of the underlying array.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.get( idx.id )\n {...}","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array data.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.data\n [ 1, 2, 3, 4 ]","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.dtype\n 'generic'","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.id\n ","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an array index is actively cached.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.isCached\n true","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n\n Returns\n -------\n out: string\n Array index type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.type\n ","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toString()\n ","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toJSON()\n { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n See Also\n --------\n array2fancy","arrayMinDataType":"\narrayMinDataType( value )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n Array data type.\n\n Examples\n --------\n > var dt = arrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = arrayMinDataType( 3 )\n 'uint8'\n > dt = arrayMinDataType( -3 )\n 'int8'\n > dt = arrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n arrayDataTypes, arrayPromotionRules, arraySafeCasts\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type value.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be cast.\n\n Examples\n --------\n > var out = arrayMostlySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, arraySameKindCasts, ndarrayMostlySafeCasts\n","arrayNextDataType":"\narrayNextDataType( [dtype] )\n Returns the next larger array data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = arrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n arrayDataType, arrayDataTypes\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1, dtype2] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: any (optional)\n Array data type.\n\n dtype2: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = arrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n arrayDataTypes, arraySafeCasts, ndarrayPromotionRules\n","arraySafeCasts":"\narraySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = arraySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arrayMostlySafeCasts, arraySameKindCasts, ndarraySafeCasts\n","arraySameKindCasts":"\narraySameKindCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast or cast within\n the same \"kind\".\n\n Examples\n --------\n > var out = arraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, ndarraySameKindCasts\n","arrayShape":"\narrayShape( arr )\n Determines array dimensions.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Array shape.\n\n Examples\n --------\n > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ 2, 3 ]\n\n See Also\n --------\n ndarray\n","arrayStream":"\narrayStream( src[, options] )\n Creates a readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = arrayStream( [ 1, 2, 3 ] );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream\n","arrayStream.factory":"\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );","arrayStream.objectMode":"\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream","arrayview2iterator":"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, stridedarray2iterator, arrayview2iteratorRight\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, stridedarray2iterator, arrayview2iterator\n","aslice":"\naslice( x[, start[, end]] )\n Returns a shallow copy of a portion of an array.\n\n If provided an array-like object having a `slice` method, the function\n defers execution to that method and assumes that the method has the\n following signature:\n\n x.slice( start, end )\n\n If provided an array-like object without a `slice` method, the function\n copies input array elements to a new generic array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n start: integer (optional)\n Starting index (inclusive). Default: 0.\n\n end: integer (optional)\n Ending index (exclusive). Default: x.length.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = aslice( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1 )\n [ 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n [ 2, 3 ]\n\n See Also\n --------\n atake\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n\n See Also\n --------\n Symbol, IteratorSymbol\n","atake":"\natake( x, indices[, options] )\n Takes elements from an array.\n\n If `indices` is an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n indices: ArrayLikeObject\n List of element indices.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n Specifies how to handle an index outside the interval [0, max], where\n `max` is the maximum possible array index. If equal to 'throw', the\n function throws an error. If equal to 'normalize', the function throws\n an error if provided an out-of-bounds normalized index. If equal to\n 'wrap', the function wraps around an index using modulo arithmetic. If\n equal to 'clamp', the function sets an index to either 0 (minimum index)\n or the maximum index. Default: 'normalize'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = atake( x, [ 1, 3 ] )\n [ 2, 4 ]\n\n See Also\n --------\n aput, aslice\n","azeros":"\nazeros( length[, dtype] )\n Returns a zero-filled array having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeros( 2 )\n [ 0.0, 0.0 ]\n > arr = azeros( 2, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aempty, afull, anans, aones, azerosLike, ndzeros\n","azerosLike":"\nazerosLike( x[, dtype] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = azerosLike( x )\n [ 0.0, 0.0 ]\n > y = azerosLike( x, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aonesLike, azeros, ndzerosLike\n","azeroTo":"\nazeroTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroTo( 2 )\n [ 0.0, 1.0 ]\n > arr = azeroTo( 2, 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aempty, afull, aoneTo, azeroToLike, azeros\n","azeroToLike":"\nazeroToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroToLike( [ 0, 0 ] )\n [ 0, 1 ]\n > arr = azeroToLike( [ 0, 0 ], 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aoneToLike, aonesLike, azeroTo, azerosLike\n","bartlettTest":"\nbartlettTest( ...x[, options] )\n Computes Bartlett’s test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = bartlettTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = bartlettTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, leveneTest\n","base.abs":"\nbase.abs( x )\n Computes the absolute value of a double-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.abs( -1.0 )\n 1.0\n > y = base.abs( 2.0 )\n 2.0\n > y = base.abs( 0.0 )\n 0.0\n > y = base.abs( -0.0 )\n 0.0\n > y = base.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf, base.labs\n","base.abs2":"\nbase.abs2( x )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2( -1.0 )\n 1.0\n > y = base.abs2( 2.0 )\n 4.0\n > y = base.abs2( 0.0 )\n 0.0\n > y = base.abs2( -0.0 )\n 0.0\n > y = base.abs2( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f\n","base.abs2f":"\nbase.abs2f( x )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2f( -1.0 )\n 1.0\n > y = base.abs2f( 2.0 )\n 4.0\n > y = base.abs2f( 0.0 )\n 0.0\n > y = base.abs2f( -0.0 )\n 0.0\n > y = base.abs2f( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf\n","base.absdiff":"\nbase.absdiff( x, y )\n Computes the absolute difference.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Absolute difference.\n\n Examples\n --------\n > var d = base.absdiff( 2.0, 5.0 )\n 3.0\n > d = base.absdiff( -1.0, 3.14 )\n ~4.14\n > d = base.absdiff( 10.1, -2.05 )\n ~12.15\n > d = base.absdiff( -0.0, 0.0 )\n +0.0\n > d = base.absdiff( NaN, 5.0 )\n NaN\n > d = base.absdiff( PINF, NINF )\n Infinity\n > d = base.absdiff( PINF, PINF )\n NaN\n\n See Also\n --------\n base.reldiff, base.epsdiff\n","base.absf":"\nbase.absf( x )\n Computes the absolute value of a single-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.absf( -1.0 )\n 1.0\n > y = base.absf( 2.0 )\n 2.0\n > y = base.absf( 0.0 )\n 0.0\n > y = base.absf( -0.0 )\n 0.0\n > y = base.absf( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f, base.labs\n","base.acartesianPower":"\nbase.acartesianPower( x, n )\n Returns the Cartesian power.\n\n If provided an empty array, the function returns an empty array.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n n: integer\n Power.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = base.acartesianPower( x, 2 )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianPower, base.acartesianProduct, base.acartesianSquare\n","base.acartesianProduct":"\nbase.acartesianProduct( x1, x2 )\n Returns the Cartesian product.\n\n If provided one or more empty arrays, the function returns an empty array.\n\n Parameters\n ----------\n x1: ArrayLikeObject\n First input array.\n\n x2: ArrayLikeObject\n Second input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x1 = [ 1, 2 ];\n > var x2 = [ 3, 4 ];\n > var out = base.acartesianProduct( x1, x2 )\n [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n See Also\n --------\n acartesianProduct, base.acartesianPower, base.acartesianSquare\n","base.acartesianSquare":"\nbase.acartesianSquare( x )\n Returns the Cartesian square.\n\n If provided an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = base.acartesianSquare( x )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianSquare, base.acartesianPower, base.acartesianProduct\n","base.acos":"\nbase.acos( x )\n Compute the arccosine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acos( 1.0 )\n 0.0\n > y = base.acos( 0.707 )\n ~0.7855\n > y = base.acos( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asin, base.atan\n","base.acosd":"\nbase.acosd( x )\n Computes the arccosine (in degrees) of a double-precision floating-point \n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in degrees).\n\n Examples\n --------\n > var y = base.acosd( 0.0 )\n 90.0\n > y = base.acosd( PI/6.0 )\n ~58.43\n > y = base.acosd( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.acosdf, base.acosh, base.asind, base.atand\n","base.acosdf":"\nbase.acosdf( x )\n Computes the arccosine (in degrees) of a single-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in degrees).\n\n Examples\n --------\n > var y = base.acosdf( 0.0 )\n 90.0\n > y = base.acosdf( FLOAT32_PI / 6.0 )\n ~58.43\n > y = base.acosdf( NaN )\n NaN\n\n See Also\n --------\n base.acosd, base.acosf, base.asindf\n","base.acosf":"\nbase.acosf( x )\n Computes the arccosine of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acosf( 1.0 )\n 0.0\n > y = base.acosf( 0.707 )\n ~0.7855\n > y = base.acosf( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.acosh, base.asinf, base.atanf\n","base.acosh":"\nbase.acosh( x )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n\n If `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosine.\n\n Examples\n --------\n > var y = base.acosh( 1.0 )\n 0.0\n > y = base.acosh( 2.0 )\n ~1.317\n > y = base.acosh( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atanh\n","base.acot":"\nbase.acot( x )\n Computes the inverse cotangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse cotangent (in radians).\n\n Examples\n --------\n > var y = base.acot( 2.0 )\n ~0.4636\n > y = base.acot( 0.0 )\n ~1.5708\n > y = base.acot( 0.5 )\n ~1.1071\n > y = base.acot( 1.0 )\n ~0.7854\n > y = base.acot( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.atan, base.cot\n","base.acotd":"\nbase.acotd( x )\n Computes the arccotangent (in degrees) of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccotangent (in degrees).\n\n Examples\n --------\n > var y = base.acotd( 0.0 )\n 90.0\n > y = base.acotd( PI/6.0 )\n ~62.36\n > y = base.acotd( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acotdf, base.acoth, base.atand, base.cotd\n","base.acotdf":"\nbase.acotdf( x )\n Computes the arccotangent (in degrees) of a single-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccotangent (in degrees).\n\n Examples\n --------\n > var y = base.acotdf( 0.0 )\n 90.0\n > y = base.acotdf( FLOAT32_PI/6.0 )\n ~62.36\n > y = base.acotdf( NaN )\n NaN\n\n See Also\n --------\n base.acotd, base.acotf\n","base.acotf":"\nbase.acotf( x )\n Computes the inverse cotangent of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse cotangent (in radians).\n\n Examples\n --------\n > var y = base.acotf( 2.0 )\n ~0.4636\n > y = base.acotf( 0.0 )\n ~1.5708\n > y = base.acotf( 0.5 )\n ~1.1071\n > y = base.acotf( 1.0 )\n ~0.7854\n > y = base.acotf( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acoth, base.atanf\n","base.acoth":"\nbase.acoth( x )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n\n The domain of the inverse hyperbolic cotangent is the union of the intervals\n (-inf,-1] and [1,inf).\n\n If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse hyperbolic cotangent.\n\n Examples\n --------\n > var y = base.acoth( 2.0 )\n ~0.5493\n > y = base.acoth( 0.0 )\n NaN\n > y = base.acoth( 0.5 )\n NaN\n > y = base.acoth( 1.0 )\n Infinity\n > y = base.acoth( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.acot, base.asinh, base.atanh\n","base.acovercos":"\nbase.acovercos( x )\n Computes the inverse coversed cosine.\n\n The inverse coversed cosine is defined as `asin(x-1)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed cosine.\n\n Examples\n --------\n > var y = base.acovercos( 1.5 )\n ~0.5236\n > y = base.acovercos( -0.0 )\n ~-1.5708\n\n See Also\n --------\n base.acoversin, base.avercos, base.covercos, base.vercos\n","base.acoversin":"\nbase.acoversin( x )\n Computes the inverse coversed sine.\n\n The inverse coversed sine is defined as `asin(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed sine.\n\n Examples\n --------\n > var y = base.acoversin( 1.5 )\n ~-0.5236\n > y = base.acoversin( 0.0 )\n ~1.5708\n\n See Also\n --------\n base.acovercos, base.aversin, base.coversin, base.versin\n","base.acsc":"\nbase.acsc( x )\n Computes the arccosecant of a number.\n\n If `|x| < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in radians).\n\n Examples\n --------\n > var y = base.acsc( 1.0 )\n ~1.57\n > y = base.acsc( PI )\n ~0.32\n > y = base.acsc( -PI )\n ~-0.32\n > y = base.acsc( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acsch, base.asec, base.asin, base.csc\n","base.acscd":"\nbase.acscd( x )\n Computes the arccosecant of (in degrees) a double-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in degrees).\n\n Examples\n --------\n > var y = base.acscd( 0.0 )\n NaN\n > y = base.acscd( PI/6.0 )\n NaN\n > y = base.acscd( 1 )\n 90.0\n > y = base.acscd( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecd, base.asind, base.cscd\n","base.acscdf":"\nbase.acscdf( x )\n Computes the arccosecant (in degrees) of a single-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in degrees).\n\n Examples\n --------\n > var y = base.acscdf( 0.0 )\n NaN\n > y = base.acscdf( 3.1415927410125732 / 6.0 )\n NaN\n > y = base.acscdf( 1.0 )\n 90.0\n > y = base.acscdf( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecdf, base.asindf\n","base.acscf":"\nbase.acscf( x )\n Computes the arccosecant of a single-precision floating-point number.\n\n If `|x| < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in radians).\n\n Examples\n --------\n > var y = base.acscf( 1.0 )\n ~1.57\n > y = base.acscf( 3.141592653589793 )\n ~0.32\n > y = base.acscf( -3.141592653589793 )\n ~-0.32\n > y = base.acscf( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecf, base.asinf\n","base.acsch":"\nbase.acsch( x )\n Computes the hyperbolic arccosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosecant.\n\n Examples\n --------\n > var y = base.acsch( 0.0 )\n Infinity\n > y = base.acsch( -1.0 )\n ~-0.881\n > y = base.acsch( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.acsc, base.asech, base.asinh, base.csc, base.csch\n","base.add":"\nbase.add( x, y )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Sum.\n\n Examples\n --------\n > var v = base.add( -1.0, 5.0 )\n 4.0\n > v = base.add( 2.0, 5.0 )\n 7.0\n > v = base.add( 0.0, 5.0 )\n 5.0\n > v = base.add( -0.0, 0.0 )\n 0.0\n > v = base.add( NaN, NaN )\n NaN\n\n See Also\n --------\n base.div, base.mul, base.sub\n","base.add3":"\nbase.add3( x, y, z )\n Computes the sum of three double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add3( -1.0, 5.0, 2.0 )\n 6.0\n > v = base.add3( 2.0, 5.0, 2.0 )\n 9.0\n > v = base.add3( 0.0, 5.0, 2.0 )\n 7.0\n > v = base.add3( -0.0, 0.0, -0.0 )\n 0.0\n > v = base.add3( NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.add4":"\nbase.add4( x, y, z, w )\n Computes the sum of four double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n w: number\n Fourth input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\n 3.0\n > v = base.add4( 2.0, 5.0, 2.0, -3.0 )\n 6.0\n > v = base.add4( 0.0, 5.0, 2.0, -3.0 )\n 4.0\n > v = base.add4( -0.0, 0.0, -0.0, -0.0 )\n 0.0\n > v = base.add4( NaN, NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.add5":"\nbase.add5( x, y, z, w, u )\n Computes the sum of five double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n w: number\n Fourth input value.\n\n u: number\n Fifth input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\n 7.0\n > v = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\n 10.0\n > v = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\n 8.0\n > v = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\n 0.0\n > v = base.add5( NaN, NaN, NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.addf":"\nbase.addf( x, y )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Sum.\n\n Examples\n --------\n > var v = base.addf( -1.0, 5.0 )\n 4.0\n > v = base.addf( 2.0, 5.0 )\n 7.0\n > v = base.addf( 0.0, 5.0 )\n 5.0\n > v = base.addf( -0.0, 0.0 )\n 0.0\n > v = base.addf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.divf, base.mulf, base.subf\n","base.afilled":"\nbase.afilled( value, len )\n Returns a filled \"generic\" array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled( 0.0, 3 )\n [ 0.0, 0.0, 0.0 ]\n\n","base.afilled2d":"\nbase.afilled2d( value, shape )\n Returns a filled two-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled2d( 0.0, [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilled2dBy":"\nbase.afilled2dBy( shape, clbk[, thisArg] )\n Returns a filled two-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled2dBy( [ 1, 3 ], clbk )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.afilled2d\n","base.afilled3d":"\nbase.afilled3d( value, shape )\n Returns a filled three-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n","base.afilled3dBy":"\nbase.afilled3dBy( shape, clbk[, thisArg] )\n Returns a filled three-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n See Also\n --------\n base.afilled3d\n","base.afilled4d":"\nbase.afilled4d( value, shape )\n Returns a filled four-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n","base.afilled4dBy":"\nbase.afilled4dBy( shape, clbk[, thisArg] )\n Returns a filled four-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n See Also\n --------\n base.afilled4d\n","base.afilled5d":"\nbase.afilled5d( value, shape )\n Returns a filled five-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n","base.afilled5dBy":"\nbase.afilled5dBy( shape, clbk[, thisArg] )\n Returns a filled five-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n See Also\n --------\n base.afilled5d\n","base.afilledBy":"\nbase.afilledBy( len, clbk[, thisArg] )\n Returns a filled \"generic\" array according to a provided callback function.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilledBy( 3, clbk )\n [ 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n base.afilled\n","base.afillednd":"\nbase.afillednd( value, shape )\n Returns a filled n-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afillednd( 0.0, [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilledndBy":"\nbase.afilledndBy( shape, clbk[, thisArg] )\n Returns a filled n-dimensional nested array according to a callback\n function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilledndBy( [ 1, 3 ], clbk )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.afillednd\n","base.afilter":"\nbase.afilter( x, predicate[, thisArg] )\n Returns a shallow copy of an array containing only those elements which pass\n a test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the input array.\n\n If provided an array-like object having a `filter` method , the function\n defers execution to that method and assumes that the method has the\n following signature:\n\n x.filter( predicate, thisArg )\n\n If provided an array-like object without a `filter` method, the function\n performs a linear scan and always returns a generic array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > function f( v ) { return ( v > 0 ); };\n > var x = [ 1, -2, -3, 4 ];\n > var out = base.afilter( x, f )\n [ 1, 4 ]\n\n","base.afirst":"\nbase.afirst( arr )\n Returns the first element of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: any\n First element.\n\n Examples\n --------\n > var out = base.afirst( [ 1, 2, 3 ] )\n 1\n\n","base.aflatten":"\nbase.aflatten( x, shape, colexicographic )\n Flattens an n-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten( x, [ 2, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten( x, [ 2, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflattenBy\n","base.aflatten.assign":"\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflattenBy","base.aflatten2d":"\nbase.aflatten2d( x, shape, colexicographic )\n Flattens a two-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten2d( x, [ 2, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten2d( x, [ 2, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten2dBy\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten2dBy","base.aflatten2dBy":"\nbase.aflatten2dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten2d\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten2d","base.aflatten3d":"\nbase.aflatten3d( x, shape, colexicographic )\n Flattens a three-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = base.aflatten3d( x, [ 2, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten3d( x, [ 2, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten3dBy\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten3dBy","base.aflatten3dBy":"\nbase.aflatten3dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten3d\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten3d","base.aflatten4d":"\nbase.aflatten4d( x, shape, colexicographic )\n Flattens a four-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten4dBy\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten4dBy","base.aflatten4dBy":"\nbase.aflatten4dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten4d\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten4d","base.aflatten5d":"\nbase.aflatten5d( x, shape, colexicographic )\n Flattens a five-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten5dBy\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten5dBy","base.aflatten5dBy":"\nbase.aflatten5dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten5d\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten5d","base.aflattenBy":"\nbase.aflattenBy( x, shape, colex, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten","base.afliplr2d":"\nbase.afliplr2d( x )\n Reverses the order of elements along the last dimension of a two-dimensional\n nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ [ 2, 1 ], [ 4, 3 ] ]\n\n See Also\n --------\n base.afliplr3d, base.afliplr4d, base.afliplr5d\n","base.afliplr3d":"\nbase.afliplr3d( x )\n Reverses the order of elements along the last dimension of a three-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n [ [ [ 2, 1 ], [ 4, 3 ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr4d, base.afliplr5d\n","base.afliplr4d":"\nbase.afliplr4d( x )\n Reverses the order of elements along the last dimension of a four-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr3d, base.afliplr5d\n","base.afliplr5d":"\nbase.afliplr5d( x )\n Reverses the order of elements along the last dimension of a five-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n [ [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr3d, base.afliplr4d\n","base.aflipud2d":"\nbase.aflipud2d( x )\n Reverses the order of elements along the first dimension of a two-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ [ 3, 4 ], [ 1, 2 ] ]\n\n See Also\n --------\n base.aflipud3d, base.aflipud4d, base.aflipud5d\n","base.aflipud3d":"\nbase.aflipud3d( x )\n Reverses the order of elements along the second-to-last dimension of a\n three-dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n [ [ [ 3, 4 ], [ 1, 2 ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud4d, base.aflipud5d\n","base.aflipud4d":"\nbase.aflipud4d( x )\n Reverses the order of elements along the second-to-last dimension of a four-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud3d, base.aflipud5d\n","base.aflipud5d":"\nbase.aflipud5d( x )\n Reverses the order of elements along the second-to-last dimension of a five-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n [ [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud3d, base.aflipud4d\n","base.ahavercos":"\nbase.ahavercos( x )\n Computes the inverse half-value versed cosine.\n\n The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed cosine.\n\n Examples\n --------\n > var y = base.ahavercos( 0.5 )\n ~1.5708\n > y = base.ahavercos( 0.0 )\n ~3.1416\n\n See Also\n --------\n base.ahaversin, base.havercos, base.vercos\n","base.ahaversin":"\nbase.ahaversin( x )\n Computes the inverse half-value versed sine.\n\n The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed sine.\n\n Examples\n --------\n > var y = base.ahaversin( 0.5 )\n ~1.5708\n > y = base.ahaversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.ahavercos, base.haversin, base.versin\n","base.altcase":"\nbase.altcase( str )\n Converts a string to alternate case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Alternate-cased string.\n\n Examples\n --------\n > var out = base.altcase( 'Hello World!' )\n 'hElLo wOrLd!'\n > out = base.altcase( 'I am a tiny little teapot' )\n 'i aM A TiNy lItTlE TeApOt'\n\n See Also\n --------\n base.lowercase, base.uppercase","base.aones":"\nbase.aones( len )\n Returns a \"generic\" array filled with ones.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones( 3 )\n [ 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n base.azeros, base.aones2d, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones2d":"\nbase.aones2d( shape )\n Returns a two-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones2d( [ 1, 3 ] )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.azeros2d, base.aones, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones3d":"\nbase.aones3d( shape )\n Returns a three-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones3d( [ 1, 1, 3 ] )\n [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n See Also\n --------\n base.azeros3d, base.aones, base.aones2d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones4d":"\nbase.aones4d( shape )\n Returns a four-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones4d( [ 1, 1, 1, 3 ] )\n [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n See Also\n --------\n base.azeros4d, base.aones, base.aones2d, base.aones3d, base.aones5d, base.aonesnd\n","base.aones5d":"\nbase.aones5d( shape )\n Returns a five-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n See Also\n --------\n base.azeros5d, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aonesnd\n","base.aonesnd":"\nbase.aonesnd( shape )\n Returns an n-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aonesnd( [ 1, 3 ] )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.azerosnd, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aones5d\n","base.aoneTo":"\nbase.aoneTo( n )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n\n If `n` is a non-integer value greater than zero, the function returns an\n array having `ceil(n)` elements.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: number\n Number of elements.\n\n Returns\n -------\n out: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = base.aoneTo( 6 )\n [ 1, 2, 3, 4, 5, 6 ]\n\n\nbase.aoneTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.aoneTo.assign( out, -1, out.length-1 );\n > out\n [ 6, 5, 4, 3, 2, 1 ]\n\n See Also\n --------\n base.azeroTo, base.aones\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.aoneTo.assign( out, -1, out.length-1 );\n > out\n [ 6, 5, 4, 3, 2, 1 ]\n\n See Also\n --------\n base.azeroTo, base.aones","base.args2multislice":"\nbase.args2multislice( args )\n Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n\n Parameters\n ----------\n args: Array\n Constructor arguments.\n\n Returns\n -------\n s: MultiSlice\n MultiSlice instance.\n\n Examples\n --------\n > var args = [ null, null, null ];\n > var s = new base.args2multislice( args );\n > s.data\n [ null, null, null ]\n > args = [ 10, new Slice( 0, 10, 1 ), null ];\n > s = new base.args2multislice( args );\n > s.data\n [ 10, , null ]\n\n","base.asec":"\nbase.asec( x )\n Computes the inverse (arc) secant of a number.\n\n If `x > -1` and `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse (arc) secant.\n\n Examples\n --------\n > var y = base.asec( 1.0 )\n 0.0\n > y = base.asec( 2.0 )\n ~1.0472\n > y = base.asec( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acsc, base.asech, base.acos\n","base.asecd":"\nbase.asecd( x )\n Computes the arcsecant (in degrees) of a double-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsecant (in degrees).\n\n Examples\n --------\n > var y = base.asecd( 0.0 )\n NaN\n > y = base.asecd( 2 )\n ~60.0\n > y = base.asecd( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech, base.acosd, base.secd\n","base.asecdf":"\nbase.asecdf( x )\n Computes the arcsecant (in degrees) of a single-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsecant (in degrees).\n\n Examples\n --------\n > var y = base.asecdf( 2.0 )\n ~60.0\n > y = base.asecdf( 0.0 )\n NaN\n > y = base.asecdf( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech, base.acosdf\n","base.asecf":"\nbase.asecf( x )\n Computes the inverse (arc) secant of a single-precision\n floating-point number.\n\n If `x > -1` and `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse (arc) secant.\n\n Examples\n --------\n > var y = base.asecf( 1.0 )\n 0.0\n > y = base.asecf( 2.0 )\n ~1.0472\n > y = base.asecf( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech, base.acosf\n","base.asech":"\nbase.asech( x )\n Computes the hyperbolic arcsecant of a number.\n\n If `x < 0` or `x > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsecant.\n\n Examples\n --------\n > var y = base.asech( 1.0 )\n 0.0\n > y = base.asech( 0.5 )\n ~1.317\n > y = base.asech( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asec, base.asech, base.acoth\n","base.asin":"\nbase.asin( x )\n Computes the arcsine of a double-precision floating-point number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asin( 0.0 )\n 0.0\n > y = base.asin( -PI/6.0 )\n ~-0.551\n > y = base.asin( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atan\n","base.asind":"\nbase.asind( x )\n Computes the arcsine (in degrees) of a double-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in degrees).\n\n Examples\n --------\n > var y = base.asind( 0.0 )\n 0.0\n > y = base.asind( PI / 6.0 )\n ~31.57\n > y = base.asind( NaN )\n NaN\n\n See Also\n --------\n base.asin, base.asinh, base.atand\n","base.asindf":"\nbase.asindf( x )\n Computes the arcsine (in degrees) of a single-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in degrees).\n\n Examples\n --------\n > var y = base.asindf( 0.0 )\n 0.0\n > y = base.asindf( 3.1415927410125732 / 6.0 )\n ~31.57\n > y = base.asindf( NaN )\n NaN\n\n See Also\n --------\n base.asinf, base.asind\n","base.asinf":"\nbase.asinf( x )\n Computes the arcsine of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asinf( 0.0 )\n 0.0\n > y = base.asinf( -3.14/6.0 )\n ~-0.551\n > y = base.asinf( NaN )\n NaN\n\n See Also\n --------\n base.asin, base.asindf\n","base.asinh":"\nbase.asinh( x )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsine.\n\n Examples\n --------\n > var y = base.asinh( 0.0 )\n 0.0\n > y = base.asinh( 2.0 )\n ~1.444\n > y = base.asinh( -2.0 )\n ~-1.444\n > y = base.asinh( NaN )\n NaN\n > y = base.asinh( NINF )\n -Infinity\n > y = base.asinh( PINF )\n Infinity\n\n See Also\n --------\n base.acosh, base.asin, base.atanh\n","base.atan":"\nbase.atan( x )\n Computes the arctangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atan( 0.0 )\n ~0.0\n > y = base.atan( -PI/2.0 )\n ~-1.004\n > y = base.atan( PI/2.0 )\n ~1.004\n > y = base.atan( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asin, base.atanh\n","base.atan2":"\nbase.atan2( y, x )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n\n Parameters\n ----------\n y: number\n Coordinate along y-axis.\n\n x: number\n Coordinate along x-axis.\n\n Returns\n -------\n out: number\n Angle (in radians).\n\n Examples\n --------\n > var v = base.atan2( 2.0, 2.0 )\n ~0.785\n > v = base.atan2( 6.0, 2.0 )\n ~1.249\n > v = base.atan2( -1.0, -1.0 )\n ~-2.356\n > v = base.atan2( 3.0, 0.0 )\n ~1.571\n > v = base.atan2( -2.0, 0.0 )\n ~-1.571\n > v = base.atan2( 0.0, 0.0 )\n 0.0\n > v = base.atan2( 3.0, NaN )\n NaN\n > v = base.atan2( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.atan\n","base.atand":"\nbase.atand( x )\n Computes the arctangent (in degrees) of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in degrees).\n\n Examples\n --------\n > var y = base.atand( 0.0 )\n 0.0\n > y = base.atand( PI/6.0 )\n ~27.64\n > y = base.atand( NaN )\n NaN\n\n See Also\n --------\n base.atan, base.atanh, base.acosd\n","base.atanf":"\nbase.atanf( x )\n Computes the arctangent of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atanf( 0.0 )\n 0.0\n > y = base.atanf( -3.14/4.0 )\n ~-0.666\n > y = base.atanf( 3.14/4.0 )\n ~0.666\n > y = base.atanf( NaN )\n NaN\n\n See Also\n --------\n base.atan, base.atanh, base.acosf\n","base.atanh":"\nbase.atanh( x )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arctangent.\n\n Examples\n --------\n > var y = base.atanh( 0.0 )\n 0.0\n > y = base.atanh( 0.9 )\n ~1.472\n > y = base.atanh( 1.0 )\n Infinity\n > y = base.atanh( -1.0 )\n -Infinity\n > y = base.atanh( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asinh, base.atan\n","base.avercos":"\nbase.avercos( x )\n Computes the inverse versed cosine.\n\n The inverse versed cosine is defined as `acos(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed cosine.\n\n Examples\n --------\n > var y = base.avercos( -1.5 )\n ~2.0944\n > y = base.avercos( -0.0 )\n 0.0\n\n See Also\n --------\n base.aversin, base.versin\n","base.aversin":"\nbase.aversin( x )\n Computes the inverse versed sine.\n\n The inverse versed sine is defined as `acos(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed sine.\n\n Examples\n --------\n > var y = base.aversin( 1.5 )\n ~2.0944\n > y = base.aversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.avercos, base.vercos\n","base.azeros":"\nbase.azeros( len )\n Returns a zero-filled \"generic\" array.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros( 3 )\n [ 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.aones, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros2d":"\nbase.azeros2d( shape )\n Returns a zero-filled two-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros2d( [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n See Also\n --------\n base.azeros, base.aones2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros3d":"\nbase.azeros3d( shape )\n Returns a zero-filled three-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros3d( [ 1, 1, 3 ] )\n [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n See Also\n --------\n base.azeros, base.aones3d, base.azeros2d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros4d":"\nbase.azeros4d( shape )\n Returns a zero-filled four-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros4d( [ 1, 1, 1, 3 ] )\n [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n See Also\n --------\n base.azeros, base.aones4d, base.azeros2d, base.azeros3d, base.azeros5d, base.azerosnd\n","base.azeros5d":"\nbase.azeros5d( shape )\n Returns a zero-filled five-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros5d( [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n See Also\n --------\n base.azeros, base.aones5d, base.azeros2d, base.azeros3d, base.azeros4d, base.azerosnd\n","base.azerosnd":"\nbase.azerosnd( shape )\n Returns a zero-filled n-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azerosnd( [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n See Also\n --------\n base.azeros, base.aonesnd, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d\n","base.azeroTo":"\nbase.azeroTo( n )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n\n If `n` is a non-integer value greater than zero, the function returns an\n array having `ceil(n)` elements.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: number\n Number of elements.\n\n Returns\n -------\n out: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = base.azeroTo( 6 )\n [ 0, 1, 2, 3, 4, 5 ]\n\n\nbase.azeroTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.azeroTo.assign( out, -1, out.length-1 );\n > out\n [ 5, 4, 3, 2, 1, 0 ]\n\n See Also\n --------\n base.aoneTo\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.azeroTo.assign( out, -1, out.length-1 );\n > out\n [ 5, 4, 3, 2, 1, 0 ]\n\n See Also\n --------\n base.aoneTo","base.bernoulli":"\nbase.bernoulli( n )\n Computes the nth Bernoulli number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Bernoulli number.\n\n Examples\n --------\n > var y = base.bernoulli( 0 )\n 1.0\n > y = base.bernoulli( 1 )\n 0.5\n > y = base.bernoulli( 2 )\n ~0.167\n > y = base.bernoulli( 3 )\n 0.0\n > y = base.bernoulli( 4 )\n ~-0.033\n > y = base.bernoulli( 5 )\n 0.0\n > y = base.bernoulli( 20 )\n ~-529.124\n > y = base.bernoulli( 260 )\n -Infinity\n > y = base.bernoulli( 262 )\n Infinity\n > y = base.bernoulli( NaN )\n NaN\n\n","base.besselj0":"\nbase.besselj0( x )\n Computes the Bessel function of the first kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj0( 0.0 )\n 1.0\n > y = base.besselj0( 1.0 )\n ~0.765\n > y = base.besselj0( PINF )\n 0.0\n > y = base.besselj0( NINF )\n 0.0\n > y = base.besselj0( NaN )\n NaN\n\n See Also\n --------\n base.besselj1, base.bessely0, base.bessely1\n","base.besselj1":"\nbase.besselj1( x )\n Computes the Bessel function of the first kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj1( 0.0 )\n 0.0\n > y = base.besselj1( 1.0 )\n ~0.440\n > y = base.besselj1( PINF )\n 0.0\n > y = base.besselj1( NINF )\n 0.0\n > y = base.besselj1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.bessely0, base.bessely1\n","base.bessely0":"\nbase.bessely0( x )\n Computes the Bessel function of the second kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely0( 0.0 )\n -Infinity\n > y = base.bessely0( 1.0 )\n ~0.088\n > y = base.bessely0( -1.0 )\n NaN\n > y = base.bessely0( PINF )\n 0.0\n > y = base.bessely0( NINF )\n NaN\n > y = base.bessely0( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely1\n","base.bessely1":"\nbase.bessely1( x )\n Computes the Bessel function of the second kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely1( 0.0 )\n -Infinity\n > y = base.bessely1( 1.0 )\n ~-0.781\n > y = base.bessely1( -1.0 )\n NaN\n > y = base.bessely1( PINF )\n 0.0\n > y = base.bessely1( NINF )\n NaN\n > y = base.bessely1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely0\n","base.beta":"\nbase.beta( x, y )\n Evaluates the beta function.\n\n Parameters\n ----------\n x: number\n First function parameter (nonnegative).\n\n y: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Evaluated beta function.\n\n Examples\n --------\n > var v = base.beta( 0.0, 0.5 )\n Infinity\n > v = base.beta( 1.0, 1.0 )\n 1.0\n > v = base.beta( -1.0, 2.0 )\n NaN\n > v = base.beta( 5.0, 0.2 )\n ~3.382\n > v = base.beta( 4.0, 1.0 )\n 0.25\n > v = base.beta( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.betainc, base.betaincinv, base.betaln\n","base.betainc":"\nbase.betainc( x, a, b[, regularized[, upper]] )\n Computes the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betainc( 0.5, 2.0, 2.0 )\n 0.5\n > y = base.betainc( 0.5, 2.0, 2.0, false )\n ~0.083\n > y = base.betainc( 0.2, 1.0, 2.0 )\n 0.36\n > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n 0.64\n > y = base.betainc( NaN, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.8, NaN, 1.0 )\n NaN\n > y = base.betainc( 0.8, 1.0, NaN )\n NaN\n > y = base.betainc( 1.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betainc( 0.5, 2.0, -2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betaincinv, base.betaln\n","base.betaincinv":"\nbase.betaincinv( p, a, b[, upper] )\n Computes the inverse of the lower incomplete beta function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second and third arguments are `a` and `b`,\n respectively.\n\n By default, the function inverts the lower regularized incomplete beta\n function. To invert the upper function, set the `upper` argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n ~0.327\n > y = base.betaincinv( 0.4, 3.0, 3.0 )\n ~0.446\n > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n ~0.554\n > y = base.betaincinv( 0.4, 1.0, 6.0 )\n ~0.082\n > y = base.betaincinv( 0.8, 1.0, 6.0 )\n ~0.235\n > y = base.betaincinv( NaN, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, NaN, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, 1.0, NaN )\n NaN\n > y = base.betaincinv( 1.2, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 0.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, -2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, 0.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaln\n","base.betaln":"\nbase.betaln( a, b )\n Evaluates the natural logarithm of the beta function.\n\n Parameters\n ----------\n a: number\n First function parameter (nonnegative).\n\n b: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Natural logarithm of the beta function.\n\n Examples\n --------\n > var v = base.betaln( 0.0, 0.0 )\n Infinity\n > v = base.betaln( 1.0, 1.0 )\n 0.0\n > v = base.betaln( -1.0, 2.0 )\n NaN\n > v = base.betaln( 5.0, 0.2 )\n ~1.218\n > v = base.betaln( 4.0, 1.0 )\n ~-1.386\n > v = base.betaln( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaincinv\n","base.binet":"\nbase.binet( x )\n Evaluates Binet's formula extended to real numbers.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function result.\n\n Examples\n --------\n > var y = base.binet( 0.0 )\n 0.0\n > y = base.binet( 1.0 )\n 1.0\n > y = base.binet( 2.0 )\n 1.0\n > y = base.binet( 3.0 )\n 2.0\n > y = base.binet( 4.0 )\n 3.0\n > y = base.binet( 5.0 )\n ~5.0\n > y = base.binet( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negafibonacci\n","base.binomcoef":"\nbase.binomcoef( n, k )\n Computes the binomial coefficient of two integers.\n\n If `k < 0`, the function returns `0`.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = base.binomcoef( 8, 2 )\n 28\n > v = base.binomcoef( 0, 0 )\n 1\n > v = base.binomcoef( -4, 2 )\n 10\n > v = base.binomcoef( 5, 3 )\n 10\n > v = base.binomcoef( NaN, 3 )\n NaN\n > v = base.binomcoef( 5, NaN )\n NaN\n > v = base.binomcoef( NaN, NaN )\n NaN\n\n","base.binomcoefln":"\nbase.binomcoefln( n, k )\n Computes the natural logarithm of the binomial coefficient of two integers.\n\n If `k < 0`, the function returns negative infinity.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Natural logarithm of the binomial coefficient.\n\n Examples\n --------\n > var v = base.binomcoefln( 8, 2 )\n ~3.332\n > v = base.binomcoefln( 0, 0 )\n 0.0\n > v = base.binomcoefln( -4, 2 )\n ~2.303\n > v = base.binomcoefln( 88, 3 )\n ~11.606\n > v = base.binomcoefln( NaN, 3 )\n NaN\n > v = base.binomcoefln( 5, NaN )\n NaN\n > v = base.binomcoefln( NaN, NaN )\n NaN\n\n","base.boxcox":"\nbase.boxcox( x, lambda )\n Computes a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox( 1.0, 2.5 )\n 0.0\n > v = base.boxcox( 4.0, 2.5 )\n 12.4\n > v = base.boxcox( 10.0, 2.5 )\n ~126.0911\n > v = base.boxcox( 2.0, 0.0 )\n ~0.6931\n > v = base.boxcox( -1.0, 2.5 )\n NaN\n > v = base.boxcox( 0.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcoxinv, base.boxcox1p, base.boxcox1pinv","base.boxcox1p":"\nbase.boxcox1p( x, lambda )\n Computes a one-parameter Box-Cox transformation of 1+x.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1p( 1.0, 2.5 )\n ~1.8627\n > v = base.boxcox1p( 4.0, 2.5 )\n ~21.9607\n > v = base.boxcox1p( 10.0, 2.5 )\n ~160.1246\n > v = base.boxcox1p( 2.0, 0.0 )\n ~1.0986\n > v = base.boxcox1p( -1.0, 2.5 )\n -0.4\n > v = base.boxcox1p( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1p( -1.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcox, base.boxcox1pinv, base.boxcoxinv","base.boxcox1pinv":"\nbase.boxcox1pinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1pinv( 1.0, 2.5 )\n ~0.6505\n > v = base.boxcox1pinv( 4.0, 2.5 )\n ~1.6095\n > v = base.boxcox1pinv( 10.0, 2.5 )\n ~2.6812\n > v = base.boxcox1pinv( 2.0, 0.0 )\n ~6.3891\n > v = base.boxcox1pinv( -1.0, 2.5 )\n NaN\n > v = base.boxcox1pinv( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1pinv( 1.0, NaN )\n NaN\n > v = base.boxcox1pinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcoxinv","base.boxcoxinv":"\nbase.boxcoxinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcoxinv( 1.0, 2.5 )\n ~1.6505\n > v = base.boxcoxinv( 4.0, 2.5 )\n ~2.6095\n > v = base.boxcoxinv( 10.0, 2.5 )\n ~3.6812\n > v = base.boxcoxinv( 2.0, 0.0 )\n ~7.3891\n > v = base.boxcoxinv( -1.0, 2.5 )\n NaN\n > v = base.boxcoxinv( 0.0, -1.0 )\n 1.0\n > v = base.boxcoxinv( 1.0, NaN )\n NaN\n > v = base.boxcoxinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcox1pinv","base.cabs":"\nbase.cabs( z )\n Computes the absolute value of a double-precision complex floating-point\n number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n ~5.831\n\n See Also\n --------\n base.cabs2, base.abs\n","base.cabs2":"\nbase.cabs2( z )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n 34.0\n\n See Also\n --------\n base.cabs, base.abs2\n","base.cabs2f":"\nbase.cabs2f( z )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n 34.0\n\n See Also\n --------\n base.cabs2, base.cabsf, base.abs2f\n","base.cabsf":"\nbase.cabsf( z )\n Computes the absolute value of a single-precision complex floating-point\n number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n ~5.831\n\n See Also\n --------\n base.cabs, base.cabs2f, base.absf\n","base.cadd":"\nbase.cadd( z1, z2 )\n Adds two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var out = base.cadd( z, z )\n \n > var re = real( out )\n 10.0\n > var im = imag( out )\n 6.0\n\n\nbase.cadd.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Adds two double-precision complex floating-point numbers and assigns results\n to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cadd.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n\nbase.cadd.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Adds two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cadd.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.cdiv, base.cmul, base.csub\n","base.cadd.assign":"\nbase.cadd.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Adds two double-precision complex floating-point numbers and assigns results\n to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cadd.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ 3.0, 4.0 ]","base.cadd.strided":"\nbase.cadd.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Adds two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cadd.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.cdiv, base.cmul, base.csub","base.caddf":"\nbase.caddf( z1, z2 )\n Adds two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var out = base.caddf( z, z )\n \n > var re = realf( out )\n 10.0\n > var im = imagf( out )\n 6.0\n\n\nbase.caddf.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Adds two single-precision complex floating-point numbers and assigns results\n to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float32Array( 2 );\n > base.caddf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n\nbase.caddf.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Adds two single-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float32Array( [ 5.0, 3.0 ] );\n > var z2 = new Float32Array( [ -2.0, 1.0 ] );\n > var out = new Float32Array( 2 );\n > base.caddf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.cadd, base.cmulf, base.csubf\n","base.caddf.assign":"\nbase.caddf.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Adds two single-precision complex floating-point numbers and assigns results\n to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float32Array( 2 );\n > base.caddf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ 3.0, 4.0 ]","base.caddf.strided":"\nbase.caddf.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Adds two single-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float32Array( [ 5.0, 3.0 ] );\n > var z2 = new Float32Array( [ -2.0, 1.0 ] );\n > var out = new Float32Array( 2 );\n > base.caddf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.cadd, base.cmulf, base.csubf","base.camelcase":"\nbase.camelcase( str )\n Converts a string to camel case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Camel-cased string.\n\n Examples\n --------\n > var out = base.camelcase( 'Hello World!' )\n 'helloWorld'\n > out = base.camelcase( 'beep boop' )\n 'beepBoop'\n\n See Also\n --------\n base.constantcase, base.lowercase, base.snakecase, base.uppercase","base.capitalize":"\nbase.capitalize( str )\n Capitalizes the first character in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = base.capitalize( 'beep' )\n 'Beep'\n > out = base.capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n base.lowercase, base.uppercase\n","base.cbrt":"\nbase.cbrt( x )\n Computes the cube root of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrt( 64.0 )\n 4.0\n > y = base.cbrt( 27.0 )\n 3.0\n > y = base.cbrt( 0.0 )\n 0.0\n > y = base.cbrt( -0.0 )\n -0.0\n > y = base.cbrt( -9.0 )\n ~-2.08\n > y = base.cbrt( NaN )\n NaN\n\n See Also\n --------\n base.pow, base.sqrt\n","base.cbrtf":"\nbase.cbrtf( x )\n Computes the cube root of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrtf( 64.0 )\n 4.0\n > y = base.cbrtf( 27.0 )\n 3.0\n > y = base.cbrtf( 0.0 )\n 0.0\n > y = base.cbrtf( -0.0 )\n -0.0\n > y = base.cbrtf( -9.0 )\n ~-2.08\n > y = base.cbrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.sqrtf\n","base.cceil":"\nbase.cceil( z )\n Rounds each component of a double-precision complex floating-point number\n toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n [ -1.0, 3.0 ]\n\n See Also\n --------\n base.cceiln, base.cfloor, base.cround\n","base.cceilf":"\nbase.cceilf( z )\n Rounds each component of a single-precision complex floating-point number\n toward positive infinity.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n [ -1.0, 3.0 ]\n\n See Also\n --------\n base.cceil\n","base.cceiln":"\nbase.cceiln( z, n )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n \n > var re = real( out )\n 5.56\n > var im = imag( out )\n -3.33\n\n See Also\n --------\n base.cceil, base.cfloorn, base.croundn\n","base.ccis":"\nbase.ccis( z )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.ccis( new Complex128( 0.0, 0.0 ) )\n [ 1.0, 0.0 ]\n > y = base.ccis( new Complex128( 1.0, 0.0 ) )\n [ ~0.540, ~0.841 ]\n\n","base.cdiv":"\nbase.cdiv( z1, z2 )\n Divides two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( -13.0, -1.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var y = base.cdiv( z1, z2 )\n \n > var re = real( y )\n 5.0\n > var im = imag( y )\n 3.0\n\n\nbase.cdiv.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Divides two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cdiv.assign( -13.0, -1.0, -2.0, 1.0, out, 1, 0 )\n [ 5.0, 3.0 ]\n\n\nbase.cdiv.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Divides two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ -13.0, -1.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cdiv.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n base.cadd, base.cmul, base.csub","base.cdiv.assign":"\nbase.cdiv.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Divides two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cdiv.assign( -13.0, -1.0, -2.0, 1.0, out, 1, 0 )\n [ 5.0, 3.0 ]","base.cdiv.strided":"\nbase.cdiv.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Divides two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ -13.0, -1.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cdiv.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n base.cadd, base.cmul, base.csub","base.ceil":"\nbase.ceil( x )\n Rounds a double-precision floating-point number toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil( 3.14 )\n 4.0\n > y = base.ceil( -4.2 )\n -4.0\n > y = base.ceil( -4.6 )\n -4.0\n > y = base.ceil( 9.5 )\n 10.0\n > y = base.ceil( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceiln, base.floor, base.round\n","base.ceil2":"\nbase.ceil2( x )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil2( 3.14 )\n 4.0\n > y = base.ceil2( -4.2 )\n -4.0\n > y = base.ceil2( -4.6 )\n -4.0\n > y = base.ceil2( 9.5 )\n 16.0\n > y = base.ceil2( 13.0 )\n 16.0\n > y = base.ceil2( -13.0 )\n -8.0\n > y = base.ceil2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil10, base.floor2, base.round2\n","base.ceil10":"\nbase.ceil10( x )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil10( 3.14 )\n 10.0\n > y = base.ceil10( -4.2 )\n -1.0\n > y = base.ceil10( -4.6 )\n -1.0\n > y = base.ceil10( 9.5 )\n 10.0\n > y = base.ceil10( 13.0 )\n 100.0\n > y = base.ceil10( -13.0 )\n -10.0\n > y = base.ceil10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil2, base.floor10, base.round10\n","base.ceilb":"\nbase.ceilb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.ceilb( 3.14159, -4, 10 )\n 3.1416\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.ceilb( 3.14159, 0, 2 )\n 4.0\n\n // Round to nearest multiple of two toward positive infinity:\n > y = base.ceilb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceil, base.ceiln, base.floorb, base.roundb\n","base.ceilf":"\nbase.ceilf( x )\n Rounds a single-precision floating-point number toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilf( 3.14 )\n 4.0\n > y = base.ceilf( -4.2 )\n -4.0\n > y = base.ceilf( -4.6 )\n -4.0\n > y = base.ceilf( 9.5 )\n 10.0\n > y = base.ceilf( -0.0 )\n -0.0\n\n See Also\n --------\n base.floorf\n","base.ceiln":"\nbase.ceiln( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.ceiln( 3.14159, -2 )\n 3.15\n\n // If `n = 0`, standard round toward positive infinity behavior:\n > y = base.ceiln( 3.14159, 0 )\n 4.0\n\n // Round to nearest thousand:\n > y = base.ceiln( 12368.0, 3 )\n 13000.0\n\n\n See Also\n --------\n base.ceil, base.ceilb, base.floorn, base.roundn\n","base.ceilsd":"\nbase.ceilsd( x, n, b )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilsd( 3.14159, 5, 10 )\n 3.1416\n > y = base.ceilsd( 3.14159, 1, 10 )\n 4.0\n > y = base.ceilsd( 12368.0, 2, 10 )\n 13000.0\n > y = base.ceilsd( 0.0313, 2, 2 )\n 0.046875\n\n See Also\n --------\n base.ceil, base.floorsd, base.roundsd, base.truncsd\n","base.cexp":"\nbase.cexp( z )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.cexp( new Complex128( 0.0, 0.0 ) )\n [ 1.0, 0.0 ]\n > y = base.cexp( new Complex128( 0.0, 1.0 ) )\n [ ~0.540, ~0.841 ]\n\n","base.cflipsign":"\nbase.cflipsign( z, y )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\n [ 4.2, -5.5 ]\n\n See Also\n --------\n base.cneg, base.csignum\n","base.cflipsignf":"\nbase.cflipsignf( z, y )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\n [ 4.0, -5.0 ]\n\n See Also\n --------\n base.cnegf, base.cflipsign\n","base.cfloor":"\nbase.cfloor( z )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n base.cceil, base.cfloorn, base.cround\n","base.cfloorn":"\nbase.cfloorn( z, n )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n z: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\n [ 5.55, -3.34 ]\n\n See Also\n --------\n base.cceiln, base.cfloor, base.croundn\n","base.cidentity":"\nbase.cidentity( z )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex128\n Input value.\n\n Returns\n -------\n v: Complex128\n Input value.\n\n Examples\n --------\n > var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\n \n > var re = real( v )\n -1.0\n > var img = imag( v )\n 2.0\n\n See Also\n --------\n base.cidentityf, base.identity\n","base.cidentityf":"\nbase.cidentityf( z )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex64\n Input value.\n\n Returns\n -------\n v: Complex64\n Input value.\n\n Examples\n --------\n > var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\n \n > var re = realf( v )\n -1.0\n > var img = imagf( v )\n 2.0\n\n See Also\n --------\n base.cidentity, base.identityf\n","base.cinv":"\nbase.cinv( z )\n Computes the inverse of a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n [ 0.1, -0.2 ]\n\n See Also\n --------\n base.cdiv, base.cinvf\n","base.cinvf":"\nbase.cinvf( z )\n Computes the inverse of a single-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cinvf( new Complex64( 2.0, 4.0 ) )\n [ ~0.1, ~-0.2 ]\n\n See Also\n --------\n base.cinv\n","base.clamp":"\nbase.clamp( v, min, max )\n Restricts a double-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clamp( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clamp( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clamp( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clamp( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clampf, base.wrap\n","base.clampf":"\nbase.clampf( v, min, max )\n Restricts a single-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clampf( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clampf( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clampf( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clampf( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.cmul":"\nbase.cmul( z1, z2 )\n Multiplies two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.cmul( z1, z2 )\n \n > var re = real( out )\n -13.0\n > var im = imag( out )\n -1.0\n\n\nbase.cmul.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n\nbase.cmul.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub\n","base.cmul.assign":"\nbase.cmul.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]","base.cmul.strided":"\nbase.cmul.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub","base.cmulf":"\nbase.cmulf( z1, z2 )\n Multiplies two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.cmulf( z1, z2 )\n \n > var re = realf( out )\n -13.0\n > var im = imagf( out )\n -1.0\n\n\nbase.cmulf.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two single-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float32Array( 2 );\n > base.cmulf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n\nbase.cmulf.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two single-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float32Array( [ 5.0, 3.0 ] );\n > var z2 = new Float32Array( [ -2.0, 1.0 ] );\n > var out = new Float32Array( 2 );\n > base.cmulf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.caddf, base.cmul, base.csubf\n","base.cmulf.assign":"\nbase.cmulf.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two single-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float32Array( 2 );\n > base.cmulf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]","base.cmulf.strided":"\nbase.cmulf.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two single-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float32Array( [ 5.0, 3.0 ] );\n > var z2 = new Float32Array( [ -2.0, 1.0 ] );\n > var out = new Float32Array( 2 );\n > base.cmulf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.caddf, base.cmul, base.csubf","base.cneg":"\nbase.cneg( z )\n Negates a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( -4.2, 5.5 )\n \n > var v = base.cneg( z )\n \n > var re = real( v )\n 4.2\n > var im = imag( v )\n -5.5\n\n See Also\n --------\n base.cabs\n","base.cnegf":"\nbase.cnegf( z )\n Negates a single-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( -4.0, 5.0 )\n \n > var v = base.cnegf( z )\n \n > var re = realf( v )\n 4.0\n > var im = imagf( v )\n -5.0\n\n See Also\n --------\n base.cneg, base.cabsf\n","base.codePointAt":"\nbase.codePointAt( str, idx, backward )\n Returns a Unicode code point from a string at a specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n idx: integer\n Position. If less than `0`, the string position is determined relative\n to the end of the input string.\n\n backward: boolean\n Backward iteration for low surrogates.\n\n Returns\n -------\n out: integer\n Unicode code point.\n\n Examples\n --------\n > var out = base.codePointAt( 'last man standing', 4, false )\n 32\n > out = base.codePointAt( 'presidential election', 8, true )\n 116\n > out = base.codePointAt( 'अनुच्छेद', 2, false )\n 2369\n > out = base.codePointAt( '🌷', 1, true )\n 127799\n","base.constantcase":"\nbase.constantcase( str )\n Converts a string to constant case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Constant-cased string.\n\n Examples\n --------\n > var out = base.constantcase( 'Hello World!' )\n 'HELLO_WORLD'\n > out = base.constantcase( 'I am a tiny little teapot' )\n 'I_AM_A_TINY_LITTLE_TEAPOT'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.continuedFraction":"\nbase.continuedFraction( generator[, options] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n\n `generator` can be either a function which returns an array with two\n elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n By default, the function computes\n\n a1\n ---------------\n b1 + a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n To evaluate\n\n b0 +\t a1\n ---------------\n b1 +\t a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n set the `keep` option to `true`.\n\n Parameters\n ----------\n generator: Function\n Function returning terms of continued fraction expansion.\n\n options: Object (optional)\n Options.\n\n options.maxIter: integer (optional)\n Maximum number of iterations. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n current term times the tolerance. Default: `2.22e-16`.\n\n options.keep: boolean (optional)\n Boolean indicating whether to keep the `b0` term in the continued\n fraction. Default: `false`.\n\n Returns\n -------\n out: number\n Value of continued fraction.\n\n Examples\n --------\n // Continued fraction for (e-1)^(-1):\n > function closure() {\n ... var i = 0;\n ... return function() {\n ... i += 1;\n ... return [ i, i ];\n ... };\n ... };\n > var gen = closure();\n > var out = base.continuedFraction( gen )\n ~0.582\n\n // Using an ES6 generator:\n > function* generator() {\n ... var i = 0;\n ... while ( true ) {\n ... i += 1;\n ... yield [ i, i ];\n ... }\n ... };\n > gen = generator();\n > out = base.continuedFraction( gen )\n ~0.582\n\n // Set options:\n > out = base.continuedFraction( generator(), { 'keep': true } )\n ~1.718\n > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n ~0.582\n > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n ~0.579\n\n","base.copysign":"\nbase.copysign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysign( -3.14, 10.0 )\n 3.14\n > z = base.copysign( 3.14, -1.0 )\n -3.14\n > z = base.copysign( 1.0, -0.0 )\n -1.0\n > z = base.copysign( -3.14, -0.0 )\n -3.14\n > z = base.copysign( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.flipsign\n","base.copysignf":"\nbase.copysignf( x, y )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Single-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysignf( -3.0, 10.0 )\n 3.0\n > z = base.copysignf( 3.0, -1.0 )\n -3.0\n > z = base.copysignf( 1.0, -0.0 )\n -1.0\n > z = base.copysignf( -3.0, -0.0 )\n -3.0\n > z = base.copysignf( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.copysign, base.flipsignf\n","base.cos":"\nbase.cos( x )\n Computes the cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cos( 0.0 )\n 1.0\n > y = base.cos( PI/4.0 )\n ~0.707\n > y = base.cos( -PI/6.0 )\n ~0.866\n > y = base.cos( NaN )\n NaN\n\n See Also\n --------\n base.cospi, base.cosm1, base.sin, base.tan\n","base.cosd":"\nbase.cosd( x )\n Computes the cosine of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cosd( 0.0 )\n 1.0\n > y = base.cosd( 90.0 )\n 0.0\n > y = base.cosd( 60.0 )\n ~0.5\n > y = base.cosd( NaN )\n NaN\n\n See Also\n --------\n base.tand\n","base.cosh":"\nbase.cosh( x )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic cosine.\n\n Examples\n --------\n > var y = base.cosh( 0.0 )\n 1.0\n > y = base.cosh( 2.0 )\n ~3.762\n > y = base.cosh( -2.0 )\n ~3.762\n > y = base.cosh( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinh, base.tanh\n","base.cosm1":"\nbase.cosm1( x )\n Computes the cosine of a number minus one.\n\n This function should be used instead of manually calculating `cos(x)-1` when\n `x` is near unity.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine minus one.\n\n Examples\n --------\n > var y = base.cosm1( 0.0 )\n 0.0\n > y = base.cosm1( PI/4.0 )\n ~-0.293\n > y = base.cosm1( -PI/6.0 )\n ~-0.134\n > y = base.cosm1( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cospi":"\nbase.cospi( x )\n Computes the value of `cos(πx)`.\n\n This function computes `cos(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.cospi( 0.0 )\n 1.0\n > y = base.cospi( 0.5 )\n 0.0\n > y = base.cospi( 0.1 )\n ~0.951\n > y = base.cospi( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cot":"\nbase.cot( x )\n Computes the cotangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cotangent.\n\n Examples\n --------\n > var y = base.cot( 0.0 )\n Infinity\n > y = base.cot( -PI/4.0 )\n ~-1.0\n > y = base.cot( PI/4.0 )\n ~1.0\n > y = base.cot( NaN )\n NaN\n\n See Also\n --------\n base.csc, base.tan\n","base.cotd":"\nbase.cotd( x )\n Computes the cotangent of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cotangent.\n\n Examples\n --------\n > var y = base.cotd( 0.0 )\n Infinity\n > y = base.cotd( 90.0 )\n 0.0\n > y = base.cotd( 60.0 )\n ~0.58\n > y = base.cotd( NaN )\n NaN\n\n See Also\n --------\n base.cscd, base.secd, base.tand\n","base.coth":"\nbase.coth( x )\n Computes the hyperbolic cotangent of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic cotangent.\n\n Examples\n --------\n > var y = base.coth( 0.0 )\n Infinity\n > y = base.coth( -0.0 )\n -Infinity\n > y = base.coth( 2.0 )\n ~1.0373\n > y = base.coth( -2.0 )\n ~-1.0373\n > y = base.coth( +Infinity )\n ~1\n > y = base.coth( -Infinity )\n ~-1\n > y = base.coth( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.cot, base.csch, base.tanh\n","base.covercos":"\nbase.covercos( x )\n Computes the coversed cosine.\n\n The coversed cosine is defined as `1 + sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed cosine.\n\n Examples\n --------\n > var y = base.covercos( 3.14 )\n ~1.0016\n > y = base.covercos( -4.2 )\n ~1.8716\n > y = base.covercos( -4.6 )\n ~1.9937\n > y = base.covercos( 9.5 )\n ~0.9248\n > y = base.covercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.coversin, base.vercos\n","base.coversin":"\nbase.coversin( x )\n Computes the coversed sine.\n\n The coversed sine is defined as `1 - sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed sine.\n\n Examples\n --------\n > var y = base.coversin( 3.14 )\n ~0.9984\n > y = base.coversin( -4.2 )\n ~0.1284\n > y = base.coversin( -4.6 )\n ~0.0063\n > y = base.coversin( 9.5 )\n ~1.0752\n > y = base.coversin( -0.0 )\n 1.0\n\n See Also\n --------\n base.covercos, base.versin\n","base.cphase":"\nbase.cphase( z )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n\n The argument of a complex number, also known as the phase, is the angle of\n the radius extending from the origin to the complex number plotted in the\n complex plane and the positive real axis.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n phi: number\n Argument.\n\n Examples\n --------\n > var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n ~0.5404\n\n See Also\n --------\n base.cabs\n","base.cpolar":"\nbase.cpolar( z )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Array\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n [ ~5.83, ~0.5404 ]\n\n\nbase.cpolar.assign( z, out, stride, offset )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n out: Array|TypedArray|Object\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase","base.cpolar.assign":"\nbase.cpolar.assign( z, out, stride, offset )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n out: Array|TypedArray|Object\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase","base.cround":"\nbase.cround( z )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Rounded complex number.\n\n Examples\n --------\n > var v = base.cround( new Complex128( 5.5, 3.3 ) )\n [ 6.0, 3.0 ]\n\n See Also\n --------\n base.cceil, base.cfloor, base.croundn\n","base.croundn":"\nbase.croundn( z, n )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\n [ 5.56, -3.34 ]\n\n See Also\n --------\n base.cceiln, base.cfloorn, base.cround\n","base.csc":"\nbase.csc( x )\n Computes the cosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosecant.\n\n Examples\n --------\n > var y = base.csc( 0.0 )\n Infinity\n > y = base.csc( PI/2.0 )\n ~1.0\n > y = base.csc( -PI/6.0 )\n ~-2.0\n > y = base.csc( NaN )\n NaN\n\n See Also\n --------\n base.cot, base.sin","base.cscd":"\nbase.cscd( x )\n Computes the cosecant of a degree.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cosecant.\n\n Examples\n --------\n > var y = base.cscd( 1.0 )\n ~57.30\n > y = base.cscd( PI )\n ~18.25\n > y = base.cscd( -PI )\n ~-18.25\n > y = base.cscd( NaN )\n NaN\n\n See Also\n --------\n base.cotd, base.secd\n","base.csch":"\nbase.csch( x )\n Computes the hyperbolic cosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic cosecant.\n\n Examples\n --------\n > var y = base.csch( +0.0 )\n +Infinity\n > var y = base.csch( -0.0 )\n -Infinity\n > var y = base.csch( +Infinity )\n +0.0\n > var y = base.csch( -Infinity )\n -0.0\n > y = base.csch( 2.0 )\n ~0.2757\n > y = base.csch( -2.0 )\n ~-0.2757\n > y = base.csch( NaN )\n NaN\n\n See Also\n --------\n base.acsch, base.csc, base.coth, base.sinh\n","base.csignum":"\nbase.csignum( z )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.csignum( new Complex128( -4.2, 5.5 ) )\n [ -0.6069136033622302, 0.79476781392673 ]\n\n See Also\n --------\n base.signum\n","base.csub":"\nbase.csub( z1, z2 )\n Subtracts two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.csub( z1, z2 )\n \n > var re = real( out )\n 7.0\n > var im = imag( out )\n 2.0\n\n See Also\n --------\n base.cadd, base.cdiv, base.cmul\n","base.csubf":"\nbase.csubf( z1, z2 )\n Subtracts two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.csubf( z1, z2 )\n \n > var re = realf( out )\n 7.0\n > var im = imagf( out )\n 2.0\n\n See Also\n --------\n base.caddf, base.cmulf, base.csub\n","base.deg2rad":"\nbase.deg2rad( x )\n Converts an angle from degrees to radians.\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2rad( 90.0 )\n ~1.571\n > r = base.deg2rad( -45.0 )\n ~-0.785\n > r = base.deg2rad( NaN )\n NaN\n\n See Also\n --------\n base.rad2deg\n","base.deg2radf":"\nbase.deg2radf( x )\n Converts an angle from degrees to radians (single-precision).\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2radf( 90.0 )\n ~1.571\n > r = base.deg2radf( -45.0 )\n ~-0.785\n > r = base.deg2radf( NaN )\n NaN\n\n See Also\n --------\n base.deg2rad, base.rad2degf\n","base.digamma":"\nbase.digamma( x )\n Evaluates the digamma function.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.digamma( -2.5 )\n ~1.103\n > y = base.digamma( 1.0 )\n ~-0.577\n > y = base.digamma( 10.0 )\n ~2.252\n > y = base.digamma( NaN )\n NaN\n > y = base.digamma( -1.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.trigamma\n","base.diracDelta":"\nbase.diracDelta( x )\n Evaluates the Dirac delta function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.diracDelta( 3.14 )\n 0.0\n > y = base.diracDelta( 0.0 )\n Infinity\n\n See Also\n --------\n base.kroneckerDelta\n","base.div":"\nbase.div( x, y )\n Divides two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value (dividend).\n\n y: number\n Second input value (divisor).\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.div( -1.0, 5.0 )\n -0.2\n > v = base.div( 2.0, 5.0 )\n 0.4\n > v = base.div( 0.0, 5.0 )\n 0.0\n > v = base.div( -0.0, 5.0 )\n -0.0\n > v = base.div( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.mul, base.sub\n","base.divf":"\nbase.divf( x, y )\n Divides two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value (dividend).\n\n y: number\n Second input value (divisor).\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.divf( -1.0, 5.0 )\n ~-0.2\n > v = base.divf( 2.0, 5.0 )\n ~0.4\n > v = base.divf( 0.0, 5.0 )\n 0.0\n > v = base.divf( -0.0, 5.0 )\n -0.0\n > v = base.divf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.div, base.mulf, base.subf\n","base.dotcase":"\nbase.dotcase( str )\n Converts a string to dot case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Dot-cased string.\n\n Examples\n --------\n > var out = base.dotcase( 'Hello World!' )\n 'hello.world'\n > out = base.dotcase( 'I am a tiny little teapot' )\n 'i.am.a.tiny.little.teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a, b] )\n Returns an arcsine distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be less than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n arcsine: Object\n Distribution instance.\n\n arcsine.a: number\n Minimum support. If set, the value must be less than `b`.\n\n arcsine.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n arcsine.entropy: number\n Read-only property which returns the differential entropy.\n\n arcsine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n arcsine.mean: number\n Read-only property which returns the expected value.\n\n arcsine.median: number\n Read-only property which returns the median.\n\n arcsine.mode: number\n Read-only property which returns the mode.\n\n arcsine.skewness: number\n Read-only property which returns the skewness.\n\n arcsine.stdev: number\n Read-only property which returns the standard deviation.\n\n arcsine.variance: number\n Read-only property which returns the variance.\n\n arcsine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n arcsine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n arcsine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n arcsine.pdf: Function\n Evaluates the probability density function (PDF).\n\n arcsine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n > arcsine.a\n 0.0\n > arcsine.b\n 1.0\n > arcsine.entropy\n ~-0.242\n > arcsine.kurtosis\n -1.5\n > arcsine.mean\n 0.5\n > arcsine.median\n 0.5\n > arcsine.mode\n 0.0\n > arcsine.skewness\n 0.0\n > arcsine.stdev\n ~0.354\n > arcsine.variance\n 0.125\n > arcsine.cdf( 0.8 )\n ~0.705\n > arcsine.logcdf( 0.8 )\n ~-0.35\n > arcsine.logpdf( 0.4 )\n ~-0.431\n > arcsine.pdf( 0.8 )\n ~0.796\n > arcsine.quantile( 0.8 )\n ~0.905\n\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n ~0.795\n > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n ~0.333\n > y = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705\n\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a, b )\n Returns the differential entropy of an arcsine distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n ~-0.242\n > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n ~1.838\n > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n ~1.55\n\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a, b )\n Returns the excess kurtosis of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n -1.5\n\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n ~-0.229\n > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n ~-1.1\n > y = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35\n\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n ~-1.838\n > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n ~-0.308\n > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity\n\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a, b )\n Returns the expected value of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a, b )\n Returns the median of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.arcsine.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a, b )\n Returns the mode of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.mode( 4.0, 12.0 )\n 4.0\n > v = base.dists.arcsine.mode( 2.0, 8.0 )\n 2.0\n\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x, a, b )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n ~0.159\n > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n ~0.735\n > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p, a, b )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n ~0.905\n > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n ~5.0\n\n > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618\n\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a, b )\n Returns the skewness of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a, b )\n Returns the standard deviation of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n ~0.354\n > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n ~2.121\n\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a, b )\n Returns the variance of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n ~0.125\n > v = base.dists.arcsine.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.variance( 2.0, 8.0 )\n ~4.5\n\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p] )\n Returns a Bernoulli distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n bernoulli: Object\n Distribution instance.\n\n bernoulli.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n bernoulli.entropy: number\n Read-only property which returns the differential entropy.\n\n bernoulli.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n bernoulli.mean: number\n Read-only property which returns the expected value.\n\n bernoulli.median: number\n Read-only property which returns the median.\n\n bernoulli.skewness: number\n Read-only property which returns the skewness.\n\n bernoulli.stdev: number\n Read-only property which returns the standard deviation.\n\n bernoulli.variance: number\n Read-only property which returns the variance.\n\n bernoulli.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n bernoulli.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n bernoulli.pmf: Function\n Evaluates the probability mass function (PMF).\n\n bernoulli.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n > bernoulli.p\n 0.6\n > bernoulli.entropy\n ~0.673\n > bernoulli.kurtosis\n ~-1.833\n > bernoulli.mean\n 0.6\n > bernoulli.median\n 1.0\n > bernoulli.skewness\n ~-0.408\n > bernoulli.stdev\n ~0.49\n > bernoulli.variance\n ~0.24\n > bernoulli.cdf( 0.5 )\n 0.4\n > bernoulli.mgf( 3.0 )\n ~12.451\n > bernoulli.pmf( 0.0 )\n 0.4\n > bernoulli.quantile( 0.7 )\n 1.0\n\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n 0.5\n > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n 0.9\n > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n 0.0\n > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n 1.0\n > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.bernoulli.cdf( 0.0, NaN )\n NaN\n // Invalid probability:\n > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5\n\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.bernoulli.entropy( 0.1 )\n ~0.325\n > v = base.dists.bernoulli.entropy( 0.5 )\n ~0.693\n\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.bernoulli.kurtosis( 0.1 )\n ~5.111\n > v = base.dists.bernoulli.kurtosis( 0.5 )\n -2.0\n\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mean( 0.1 )\n 0.1\n > v = base.dists.bernoulli.mean( 0.5 )\n 0.5\n\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p )\n Returns the median of a Bernoulli distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.bernoulli.median( 0.1 )\n 0\n > v = base.dists.bernoulli.median( 0.8 )\n 1\n\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n ~1.111\n > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n ~1.246\n > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855\n\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n\n For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n `0` for `p = 0.5`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mode( 0.1 )\n 0\n > v = base.dists.bernoulli.mode( 0.8 )\n 1\n\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x, p )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n 0.3\n > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n 0.3\n > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.bernoulli.pmf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5\n\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r, p )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n 1\n > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n 0\n > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n 0\n\n > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1\n\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.bernoulli.skewness( 0.1 )\n ~2.667\n > v = base.dists.bernoulli.skewness( 0.5 )\n 0.0\n\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.bernoulli.stdev( 0.1 )\n ~0.3\n > v = base.dists.bernoulli.stdev( 0.5 )\n 0.5\n\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.bernoulli.variance( 0.1 )\n ~0.09\n > v = base.dists.bernoulli.variance( 0.5 )\n 0.25\n\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α, β] )\n Returns a beta distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n beta: Object\n Distribution instance.\n\n beta.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n beta.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n beta.entropy: number\n Read-only property which returns the differential entropy.\n\n beta.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n beta.mean: number\n Read-only property which returns the expected value.\n\n beta.median: number\n Read-only property which returns the median.\n\n beta.mode: number\n Read-only property which returns the mode.\n\n beta.skewness: number\n Read-only property which returns the skewness.\n\n beta.stdev: number\n Read-only property which returns the standard deviation.\n\n beta.variance: number\n Read-only property which returns the variance.\n\n beta.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n beta.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n beta.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n beta.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n beta.pdf: Function\n Evaluates the probability density function (PDF).\n\n beta.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n > beta.alpha\n 1.0\n > beta.beta\n 1.0\n > beta.entropy\n 0.0\n > beta.kurtosis\n -1.2\n > beta.mean\n 0.5\n > beta.median\n 0.5\n > beta.mode\n NaN\n > beta.skewness\n 0.0\n > beta.stdev\n ~0.289\n > beta.variance\n ~0.0833\n > beta.cdf( 0.8 )\n 0.8\n > beta.logcdf( 0.8 )\n ~-0.223\n > beta.logpdf( 1.0 )\n 0.0\n > beta.mgf( 3.14 )\n ~7.0394\n > beta.pdf( 1.0 )\n 1.0\n > beta.quantile( 0.8 )\n 0.8\n\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n ~0.813\n > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n ~0.104\n > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n ~0.967\n > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369\n\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α, β )\n Returns the differential entropy of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.beta.entropy( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.entropy( 4.0, 12.0 )\n ~-0.869\n > v = base.dists.beta.entropy( 8.0, 2.0 )\n ~-0.795\n\n > v = base.dists.beta.entropy( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.entropy( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.entropy( 2.0, NaN )\n NaN\n > v = base.dists.beta.entropy( NaN, 2.0 )\n NaN\n\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α, β )\n Returns the excess kurtosis of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n -1.2\n > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n ~0.082\n > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n ~0.490\n\n > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.beta.kurtosis( NaN, 2.0 )\n NaN\n\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n ~-0.208\n > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n ~-2.263\n > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n ~-0.034\n > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997\n\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n ~0.223\n > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n ~-0.041\n > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n ~-0.556\n > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364\n\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364","base.dists.beta.mean":"\nbase.dists.beta.mean( α, β )\n Returns the expected value of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.beta.mean( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.mean( 4.0, 12.0 )\n 0.25\n > v = base.dists.beta.mean( 8.0, 2.0 )\n 0.8\n\n","base.dists.beta.median":"\nbase.dists.beta.median( α, β )\n Returns the median of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.beta.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.median( 4.0, 12.0 )\n ~0.239\n > v = base.dists.beta.median( 8.0, 2.0 )\n ~0.820\n\n > v = base.dists.beta.median( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.median( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.median( 2.0, NaN )\n NaN\n > v = base.dists.beta.median( NaN, 2.0 )\n NaN\n\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n ~1.297\n > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n ~1.186\n > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n ~5.575\n > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n ~0.676\n\n > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168\n\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168","base.dists.beta.mode":"\nbase.dists.beta.mode( α, β )\n Returns the mode of a beta distribution.\n\n If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.beta.mode( 4.0, 12.0 )\n ~0.214\n > v = base.dists.beta.mode( 8.0, 2.0 )\n ~0.875\n > v = base.dists.beta.mode( 1.0, 1.0 )\n NaN\n\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n 1.25\n > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n ~0.96\n > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n ~0.573\n > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695\n\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p, α, β )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n ~0.894\n > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n ~0.686\n > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433\n\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α, β )\n Returns the skewness of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.beta.skewness( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.skewness( 4.0, 12.0 )\n ~0.529\n > v = base.dists.beta.skewness( 8.0, 2.0 )\n ~-0.829\n\n > v = base.dists.beta.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.skewness( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.skewness( 2.0, NaN )\n NaN\n > v = base.dists.beta.skewness( NaN, 2.0 )\n NaN\n\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α, β )\n Returns the standard deviation of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.beta.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.beta.stdev( 4.0, 12.0 )\n ~0.105\n > v = base.dists.beta.stdev( 8.0, 2.0 )\n ~0.121\n\n > v = base.dists.beta.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.stdev( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.stdev( 2.0, NaN )\n NaN\n > v = base.dists.beta.stdev( NaN, 2.0 )\n NaN\n\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α, β )\n Returns the variance of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.beta.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.beta.variance( 4.0, 12.0 )\n ~0.011\n > v = base.dists.beta.variance( 8.0, 2.0 )\n ~0.015\n\n > v = base.dists.beta.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.variance( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.variance( 2.0, NaN )\n NaN\n > v = base.dists.beta.variance( NaN, 2.0 )\n NaN\n\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α, β] )\n Returns a beta prime distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n betaprime: Object\n Distribution instance.\n\n betaprime.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n betaprime.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n betaprime.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n betaprime.mean: number\n Read-only property which returns the expected value.\n\n betaprime.mode: number\n Read-only property which returns the mode.\n\n betaprime.skewness: number\n Read-only property which returns the skewness.\n\n betaprime.stdev: number\n Read-only property which returns the standard deviation.\n\n betaprime.variance: number\n Read-only property which returns the variance.\n\n betaprime.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n betaprime.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n betaprime.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n betaprime.pdf: Function\n Evaluates the probability density function (PDF).\n\n betaprime.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n > betaprime.alpha\n 6.0\n > betaprime.beta\n 5.0\n > betaprime.kurtosis\n 44.4\n > betaprime.mean\n 1.5\n > betaprime.mode\n ~0.833\n > betaprime.skewness\n ~3.578\n > betaprime.stdev\n ~1.118\n > betaprime.variance\n 1.25\n > betaprime.cdf( 0.8 )\n ~0.25\n > betaprime.logcdf( 0.8 )\n ~-1.387\n > betaprime.logpdf( 1.0 )\n ~-0.486\n > betaprime.pdf( 1.0 )\n ~0.615\n > betaprime.quantile( 0.8 )\n ~2.06\n\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n ~0.333\n > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n ~0.539\n > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n ~0.074\n > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n ~0.38\n > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319\n\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α, β )\n Returns the excess kurtosis of a beta prime distribution.\n\n If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n ~26.143\n > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n ~5.764\n > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n ~19.962\n\n > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n NaN\n\n > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n NaN\n\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n ~-1.099\n > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n ~-0.618\n > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n ~-2.603\n > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n ~-0.968\n > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143\n\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n ~-0.811\n > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n ~-0.13\n > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n ~-0.547\n > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n ~-0.43\n > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805\n\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α, β )\n Returns the expected value of a beta prime distribution.\n\n If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n 1.0\n > v = base.dists.betaprime.mean( 4.0, 12.0 )\n ~0.364\n > v = base.dists.betaprime.mean( 8.0, 2.0 )\n 8.0\n\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α, β )\n Returns the mode of a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n 0.0\n > v = base.dists.betaprime.mode( 4.0, 12.0 )\n ~0.231\n > v = base.dists.betaprime.mode( 8.0, 2.0 )\n ~2.333\n\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n ~0.444\n > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n ~0.878\n > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n ~0.579\n > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n ~0.65\n > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447\n\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p, α, β )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n ~8.472\n > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n ~2.187\n > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763\n\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α, β )\n Returns the skewness of a beta prime distribution.\n\n If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n ~6.261\n > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n ~1.724\n > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n ~5.729\n\n > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n NaN\n\n > v = base.dists.betaprime.skewness( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.skewness( NaN, 4.0 )\n NaN\n\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α, β )\n Returns the standard deviation of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n ~1.491\n > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n ~0.223\n > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n ~8.219\n\n > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.stdev( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.stdev( NaN, 3.0 )\n NaN\n\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α, β )\n Returns the variance of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n ~2.222\n > v = base.dists.betaprime.variance( 4.0, 12.0 )\n ~0.05\n > v = base.dists.betaprime.variance( 8.0, 2.5 )\n ~67.556\n\n > v = base.dists.betaprime.variance( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.variance( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.variance( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.variance( NaN, 3.0 )\n NaN\n\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n, p] )\n Returns a binomial distribution object.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials. Must be a positive integer. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n binomial: Object\n Distribution instance.\n\n binomial.n: number\n Number of trials. If set, the value must be a positive integer.\n\n binomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n binomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n binomial.mean: number\n Read-only property which returns the expected value.\n\n binomial.median: number\n Read-only property which returns the median.\n\n binomial.mode: number\n Read-only property which returns the mode.\n\n binomial.skewness: number\n Read-only property which returns the skewness.\n\n binomial.stdev: number\n Read-only property which returns the standard deviation.\n\n binomial.variance: number\n Read-only property which returns the variance.\n\n binomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n binomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n binomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n binomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n binomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n > binomial.n\n 8.0\n > binomial.p\n 0.5\n > binomial.kurtosis\n -0.25\n > binomial.mean\n 4.0\n > binomial.median\n 4.0\n > binomial.mode\n 4.0\n > binomial.skewness\n 0.0\n > binomial.stdev\n ~1.414\n > binomial.variance\n 2.0\n > binomial.cdf( 2.9 )\n ~0.145\n > binomial.logpmf( 3.0 )\n ~-1.52\n > binomial.mgf( 0.2 )\n ~2.316\n > binomial.pmf( 3.0 )\n ~0.219\n > binomial.quantile( 0.8 )\n 5.0\n\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x, n, p )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n ~0.411\n > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n 1.0\n > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n ~0.834\n > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011\n\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n, p )\n Returns the entropy of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.binomial.entropy( 100, 0.1 )\n ~2.511\n > v = base.dists.binomial.entropy( 20, 0.5 )\n ~2.223\n > v = base.dists.binomial.entropy( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.entropy( 20, 1.1 )\n NaN\n > v = base.dists.binomial.entropy( 20, NaN )\n NaN\n\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n, p )\n Returns the excess kurtosis of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n ~0.051\n > v = base.dists.binomial.kurtosis( 20, 0.5 )\n ~-0.1\n > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, 1.1 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, NaN )\n NaN\n\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x, n, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n ~-1.583\n > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n -Infinity\n > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n ~-1.606\n > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n ~-5.108\n > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402\n\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n, p )\n Returns the expected value of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.binomial.mean( 100, 0.1 )\n 10.0\n > v = base.dists.binomial.mean( 20, 0.5 )\n 10.0\n > v = base.dists.binomial.mean( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mean( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mean( 20, NaN )\n NaN\n\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n, p )\n Returns the median of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.binomial.median( 100, 0.1 )\n 10\n > v = base.dists.binomial.median( 20, 0.5 )\n 10\n > v = base.dists.binomial.median( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.median( 20, 1.1 )\n NaN\n > v = base.dists.binomial.median( 20, NaN )\n NaN\n\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t, n, p )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n ~11.471\n > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n ~4.798e+29\n > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n ~99.338\n > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n 1.0\n\n > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n NaN\n\n > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013\n\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n, p )\n Returns the mode of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.binomial.mode( 100, 0.1 )\n 10\n > v = base.dists.binomial.mode( 20, 0.5 )\n 10\n > v = base.dists.binomial.mode( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mode( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mode( 20, NaN )\n NaN\n\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x, n, p )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n ~0.205\n > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n 0.0\n > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n ~0.201\n > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246\n\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r, n, p )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n 3\n > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n 5\n > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n 4\n > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n 0\n > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n 10\n\n > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7\n\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n, p )\n Returns the skewness of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.binomial.skewness( 100, 0.1 )\n ~0.267\n > v = base.dists.binomial.skewness( 20, 0.5 )\n 0.0\n > v = base.dists.binomial.skewness( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.skewness( 20, 1.1 )\n NaN\n > v = base.dists.binomial.skewness( 20, NaN )\n NaN\n\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n, p )\n Returns the standard deviation of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.binomial.stdev( 100, 0.1 )\n 3.0\n > v = base.dists.binomial.stdev( 20, 0.5 )\n ~2.236\n > v = base.dists.binomial.stdev( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.stdev( 20, 1.1 )\n NaN\n > v = base.dists.binomial.stdev( 20, NaN )\n NaN\n\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n, p )\n Returns the variance of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.binomial.variance( 100, 0.1 )\n 9\n > v = base.dists.binomial.variance( 20, 0.5 )\n 5\n > v = base.dists.binomial.variance( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.variance( 20, 1.1 )\n NaN\n > v = base.dists.binomial.variance( 20, NaN )\n NaN\n\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n Returns a Cauchy distribution object.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter. Default: `0.0`.\n\n Ɣ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cauchy: Object\n Distribution instance.\n\n cauchy.x0: number\n Location parameter.\n\n cauchy.gamma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cauchy.entropy: number\n Read-only property which returns the differential entropy.\n\n cauchy.median: number\n Read-only property which returns the median.\n\n cauchy.mode: number\n Read-only property which returns the mode.\n\n cauchy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cauchy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cauchy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cauchy.pdf: Function\n Evaluates the probability density function (PDF).\n\n cauchy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n > cauchy.x0\n 0.0\n > cauchy.gamma\n 1.0\n > cauchy.entropy\n ~2.531\n > cauchy.median\n 0.0\n > cauchy.mode\n 0.0\n > cauchy.cdf( 0.8 )\n ~0.715\n > cauchy.logcdf( 1.0 )\n ~-0.288\n > cauchy.logpdf( 1.0 )\n ~-1.838\n > cauchy.pdf( 1.0 )\n ~0.159\n > cauchy.quantile( 0.8 )\n ~1.376\n\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n ~0.852\n > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n ~0.648\n > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n 0.25\n > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447\n\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0, Ɣ )\n Returns the differential entropy of a Cauchy distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n ~4.477\n > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n ~1.838\n > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n ~-0.16\n > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n ~-0.435\n > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n ~-1.386\n > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804\n\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n ~-1.838\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n ~-3.457\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n ~-2.349\n > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838\n\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0, Ɣ )\n Returns the median of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.cauchy.median( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.median( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.median( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0, Ɣ )\n Returns the mode of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.mode( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.mode( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n ~0.159\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n ~0.0315\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n ~0.095\n > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159\n\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n ~0.547\n > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n ~12.753\n > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n ~3.845\n\n > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chi.cdf( 2.0, 3.0 )\n ~0.739\n > y = base.dists.chi.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chi.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chi.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chi.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chi.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chi.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77\n\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k] )\n Returns a chi distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chi: Object\n Distribution instance.\n\n chi.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chi.entropy: number\n Read-only property which returns the differential entropy.\n\n chi.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chi.mean: number\n Read-only property which returns the expected value.\n\n chi.mode: number\n Read-only property which returns the mode.\n\n chi.skewness: number\n Read-only property which returns the skewness.\n\n chi.stdev: number\n Read-only property which returns the standard deviation.\n\n chi.variance: number\n Read-only property which returns the variance.\n\n chi.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chi.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n chi.pdf: Function\n Evaluates the probability density function (PDF).\n\n chi.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chi = base.dists.chi.Chi( 6.0 );\n > chi.k\n 6.0\n > chi.entropy\n ~1.04\n > chi.kurtosis\n ~0.025\n > chi.mean\n ~2.35\n > chi.mode\n ~2.236\n > chi.skewness\n ~0.318\n > chi.stdev\n ~0.691\n > chi.variance\n ~0.478\n > chi.cdf( 1.0 )\n ~0.014\n > chi.logpdf( 1.5 )\n ~-1.177\n > chi.pdf( 1.5 )\n ~0.308\n > chi.quantile( 0.5 )\n ~2.313\n\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k )\n Returns the differential entropy of a chi distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chi.entropy( 11.0 )\n ~1.056\n > v = base.dists.chi.entropy( 1.5 )\n ~0.878\n\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k )\n Returns the excess kurtosis of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chi.kurtosis( 9.0 )\n ~0.011\n > v = base.dists.chi.kurtosis( 1.5 )\n ~0.424\n\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n ~-4.35\n > y = base.dists.chi.logpdf( 0.7, 0.7 )\n ~-0.622\n > y = base.dists.chi.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086\n\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086","base.dists.chi.mean":"\nbase.dists.chi.mean( k )\n Returns the expected value of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chi.mean( 11.0 )\n ~3.242\n > v = base.dists.chi.mean( 4.5 )\n ~2.008\n\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k )\n Returns the mode of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chi.mode( 11.0 )\n ~3.162\n > v = base.dists.chi.mode( 1.5 )\n ~0.707\n\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chi.pdf( 0.3, 4.0 )\n ~0.013\n > y = base.dists.chi.pdf( 0.7, 0.7 )\n ~0.537\n > y = base.dists.chi.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337\n\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p, k )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chi.quantile( 0.8, 1.0 )\n ~1.282\n > y = base.dists.chi.quantile( 0.5, 4.0 )\n ~1.832\n > y = base.dists.chi.quantile( 0.8, 0.1 )\n ~0.116\n > y = base.dists.chi.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chi.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chi.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chi.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chi.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552\n\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k )\n Returns the skewness of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chi.skewness( 11.0 )\n ~0.225\n > v = base.dists.chi.skewness( 1.5 )\n ~0.763\n\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k )\n Returns the standard deviation of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chi.stdev( 11.0 )\n ~0.699\n > v = base.dists.chi.stdev( 1.5 )\n ~0.637\n\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k )\n Returns the variance of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chi.variance( 11.0 )\n ~0.488\n > v = base.dists.chi.variance( 1.5 )\n ~0.406\n\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n ~0.428\n > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chisquare.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727\n\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k] )\n Returns a chi-squared distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chisquare: Object\n Distribution instance.\n\n chisquare.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chisquare.entropy: number\n Read-only property which returns the differential entropy.\n\n chisquare.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chisquare.mean: number\n Read-only property which returns the expected value.\n\n chisquare.median: number\n Read-only property which returns the median.\n\n chisquare.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n chisquare.mode: number\n Read-only property which returns the mode.\n\n chisquare.skewness: number\n Read-only property which returns the skewness.\n\n chisquare.stdev: number\n Read-only property which returns the standard deviation.\n\n chisquare.variance: number\n Read-only property which returns the variance.\n\n chisquare.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chisquare.pdf: Function\n Evaluates the probability density function (PDF).\n\n chisquare.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n > chisquare.k\n 6.0\n > chisquare.entropy\n ~2.541\n > chisquare.kurtosis\n 2.0\n > chisquare.mean\n 6.0\n > chisquare.median\n ~5.348\n > chisquare.mode\n 4.0\n > chisquare.skewness\n ~1.155\n > chisquare.stdev\n ~3.464\n > chisquare.variance\n 12.0\n > chisquare.cdf( 3.0 )\n ~0.191\n > chisquare.mgf( 0.2 )\n ~4.63\n > chisquare.pdf( 1.5 )\n ~0.066\n > chisquare.quantile( 0.5 )\n ~5.348\n\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k )\n Returns the differential entropy of a chi-squared distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chisquare.entropy( 11.0 )\n ~2.901\n > v = base.dists.chisquare.entropy( 1.5 )\n ~1.375\n\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k )\n Returns the excess kurtosis of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chisquare.kurtosis( 9.0 )\n ~1.333\n > v = base.dists.chisquare.kurtosis( 1.5 )\n 8.0\n\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n ~-2.74\n > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n ~-1.295\n > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075\n\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k )\n Returns the expected value of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chisquare.mean( 11.0 )\n 11.0\n > v = base.dists.chisquare.mean( 4.5 )\n 4.5\n\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k )\n Returns the median of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var k = base.dists.chisquare.median( 9.0 )\n ~8.343\n > k = base.dists.chisquare.median( 2.0 )\n ~1.386\n\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t, k )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.chisquare.mgf( 0.4, 2 )\n ~5.0\n > y = base.dists.chisquare.mgf( -1.0, 5.0 )\n ~0.0642\n > y = base.dists.chisquare.mgf( 0.0, 10.0 )\n 1.0\n\n\nbase.dists.chisquare.mgf.factory( k )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n > var y = mymgf( 0.2 )\n ~1.291\n > y = mymgf( 0.4 )\n ~2.236\n\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n > var y = mymgf( 0.2 )\n ~1.291\n > y = mymgf( 0.4 )\n ~2.236","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k )\n Returns the mode of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chisquare.mode( 11.0 )\n 9.0\n > v = base.dists.chisquare.mode( 1.5 )\n 0.0\n\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n ~0.065\n > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n ~0.274\n > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126\n\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p, k )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n ~1.642\n > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n ~3.357\n > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n ~0.014\n > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408\n\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k )\n Returns the skewness of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chisquare.skewness( 11.0 )\n ~0.853\n > v = base.dists.chisquare.skewness( 1.5 )\n ~2.309\n\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k )\n Returns the standard deviation of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chisquare.stdev( 11.0 )\n ~4.69\n > v = base.dists.chisquare.stdev( 1.5 )\n ~1.732\n\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k )\n Returns the variance of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chisquare.variance( 11.0 )\n 22.0\n > v = base.dists.chisquare.variance( 1.5 )\n 3.0\n\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n ~0.971\n > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n ~0.196\n\n > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015\n\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ, s] )\n Returns a raised cosine distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cosine: Object\n Distribution instance.\n\n cosine.mu: number\n Location parameter.\n\n cosine.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cosine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n cosine.mean: number\n Read-only property which returns the expected value.\n\n cosine.median: number\n Read-only property which returns the median.\n\n cosine.mode: number\n Read-only property which returns the mode.\n\n cosine.skewness: number\n Read-only property which returns the skewness.\n\n cosine.stdev: number\n Read-only property which returns the standard deviation.\n\n cosine.variance: number\n Read-only property which returns the variance.\n\n cosine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cosine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cosine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cosine.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n cosine.pdf: Function\n Evaluates the probability density function (PDF).\n\n cosine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n > cosine.mu\n -2.0\n > cosine.s\n 3.0\n > cosine.kurtosis\n ~-0.594\n > cosine.mean\n -2.0\n > cosine.median\n -2.0\n > cosine.mode\n -2.0\n > cosine.skewness\n 0.0\n > cosine.stdev\n ~1.085\n > cosine.variance\n ~1.176\n > cosine.cdf( 0.5 )\n ~0.996\n > cosine.logcdf( 0.5 )\n ~-0.004\n > cosine.logpdf( -1.0 )\n ~-1.386\n > cosine.mgf( 0.2 )\n ~0.686\n > cosine.pdf( -2.0 )\n ~0.333\n > cosine.quantile( 0.9 )\n ~-0.553\n\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ, s )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x, μ, s )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n ~-0.029\n > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n ~-1.632\n\n > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2\n\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n ~-2.485\n > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n ~-3.307\n > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693\n\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ, s )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.cosine.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mean( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mean( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ, s )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.cosine.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.median( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.median( 0.0, NaN )\n NaN\n > y = base.dists.cosine.median( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n ~7.234\n > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n ~1.606e+47\n\n > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n NaN\n > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57\n\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ, s )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.cosine.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mode( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mode( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n ~0.083\n > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n ~0.048\n > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083\n\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p, μ, s )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n ~0.327\n > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n ~4.0\n\n > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586\n\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ, s )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.cosine.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.skewness( 0.0, NaN )\n NaN\n > y = base.dists.cosine.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ, s )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n ~0.362\n > y = base.dists.cosine.stdev( 4.0, 2.0 )\n ~0.723\n > y = base.dists.cosine.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.stdev( 0.0, NaN )\n NaN\n > y = base.dists.cosine.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ, s )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.cosine.variance( 0.0, 1.0 )\n ~0.131\n > y = base.dists.cosine.variance( 4.0, 2.0 )\n ~0.523\n > y = base.dists.cosine.variance( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.variance( 0.0, NaN )\n NaN\n > y = base.dists.cosine.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x, μ )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0\n\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ] )\n Returns a degenerate distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Constant value of distribution.\n\n Returns\n -------\n degenerate: Object\n Distribution instance.\n\n degenerate.mu: number\n Constant value of distribution.\n\n degenerate.entropy: number\n Read-only property which returns the differential entropy.\n\n degenerate.mean: number\n Read-only property which returns the expected value.\n\n degenerate.median: number\n Read-only property which returns the median.\n\n degenerate.stdev: number\n Read-only property which returns the standard deviation.\n\n degenerate.variance: number\n Read-only property which returns the variance.\n\n degenerate.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n degenerate.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n degenerate.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n degenerate.logpmf: Function\n Evaluates the natural logarithm of the probability mass function\n (PMF).\n\n degenerate.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n degenerate.pmf: Function\n Evaluates the probability mass function (PMF).\n\n degenerate.pdf: Function\n Evaluates the probability density function (PDF).\n\n degenerate.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n > degenerate.mu\n 2.0\n > degenerate.entropy\n 0.0\n > degenerate.mean\n 2.0\n > degenerate.mode\n 2.0\n > degenerate.median\n 2.0\n > degenerate.stdev\n 0.0\n > degenerate.variance\n 0.0\n > degenerate.cdf( 0.5 )\n 0.0\n > degenerate.logcdf( 2.5 )\n 0.0\n > degenerate.logpdf( 0.5 )\n -Infinity\n > degenerate.logpmf( 2.5 )\n -Infinity\n > degenerate.mgf( 0.2 )\n ~1.492\n > degenerate.pdf( 2.0 )\n +Infinity\n > degenerate.pmf( 2.0 )\n 1.0\n > degenerate.quantile( 0.7 )\n 2.0\n\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.degenerate.entropy( 20.0 )\n 0.0\n > v = base.dists.degenerate.entropy( -10.0 )\n 0.0\n\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x, μ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logcdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0\n\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x, μ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x, μ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0\n\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.degenerate.mean( 20.0 )\n 20.0\n > v = base.dists.degenerate.mean( -10.0 )\n -10.0\n\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ )\n Returns the median of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.degenerate.median( 20.0 )\n 20.0\n > v = base.dists.degenerate.median( -10.0 )\n -10.0\n\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x, μ )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n ~2.718\n > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n ~403.429\n > y = base.dists.degenerate.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.mgf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718\n\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ )\n Returns the mode of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.degenerate.mode( 20.0 )\n 20.0\n > v = base.dists.degenerate.mode( -10.0 )\n -10.0\n\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x, μ )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.pdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x, μ )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.pmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0\n\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p, μ )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n 2.0\n > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n 4.0\n > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.degenerate.stdev( 20.0 )\n 0.0\n > v = base.dists.degenerate.stdev( -10.0 )\n 0.0\n\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ )\n Returns the variance of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.degenerate.variance( 20.0 )\n 0.0\n > v = base.dists.degenerate.variance( -10.0 )\n 0.0\n\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n ~0.909\n > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n ~0.333\n > y = base.dists.discreteUniform.cdf( PINF, 2, 4 )\n 1.0\n > y = base.dists.discreteUniform.cdf( NINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818\n\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n Returns a discrete uniform distribution object.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n b: integer (optional)\n Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n Returns\n -------\n discreteUniform: Object\n Distribution instance.\n\n discreteUniform.a: integer\n Minimum support. If set, the value must be an integer smaller than or\n equal to `b`.\n\n discreteUniform.b: integer\n Maximum support. If set, the value must be an integer greater than or\n equal to `a`.\n\n discreteUniform.entropy: number\n Read-only property which returns the entropy.\n\n discreteUniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n discreteUniform.mean: number\n Read-only property which returns the expected value.\n\n discreteUniform.median: number\n Read-only property which returns the median.\n\n discreteUniform.skewness: number\n Read-only property which returns the skewness.\n\n discreteUniform.stdev: number\n Read-only property which returns the standard deviation.\n\n discreteUniform.variance: number\n Read-only property which returns the variance.\n\n discreteUniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n discreteUniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n discreteUniform.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n discreteUniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n discreteUniform.pmf: Function\n Evaluates the probability mass function (PMF).\n\n discreteUniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n > discreteUniform.a\n -2\n > discreteUniform.b\n 2\n > discreteUniform.entropy\n ~1.609\n > discreteUniform.kurtosis\n -1.3\n > discreteUniform.mean\n 0.0\n > discreteUniform.median\n 0.0\n > discreteUniform.skewness\n 0.0\n > discreteUniform.stdev\n ~1.414\n > discreteUniform.variance\n 2.0\n > discreteUniform.cdf( 0.8 )\n 0.6\n > discreteUniform.logcdf( 0.5 )\n ~-0.511\n > discreteUniform.logpmf( 1.0 )\n ~-1.609\n > discreteUniform.mgf( 0.8 )\n ~1.766\n > discreteUniform.pmf( 0.0 )\n 0.2\n > discreteUniform.quantile( 0.8 )\n 2.0\n\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a, b )\n Returns the entropy of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.entropy( 0, 1 )\n ~0.693\n > v = base.dists.discreteUniform.entropy( 4, 12 )\n ~2.197\n > v = base.dists.discreteUniform.entropy( 2, 8 )\n ~1.946\n\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a, b )\n Returns the excess kurtosis of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n -2.0\n > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n ~-1.23\n > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n ~-1.214\n\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n ~-0.095\n > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n ~-1.099\n > y = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201\n\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x, a, b )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n ~-1.609\n > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n ~-2.197\n > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity\n\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a, b )\n Returns the expected value of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.mean( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.mean( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.mean( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a, b )\n Returns the median of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.median( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.median( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.median( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n ~689.475\n > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n ~0.697\n > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n ~4.195\n > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n NaN\n > y = base.dists.discreteUniform.mgf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722\n\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x, a, b )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n ~0.2\n > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n 0.0\n > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n ~0.111\n > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0\n\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p, a, b )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n If provided `a > b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n 1\n > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n 5\n\n > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n NaN\n > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n NaN\n\n > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n NaN\n\n > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4\n\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a, b )\n Returns the skewness of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.skewness( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 4, 12 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 2, 8 )\n 0.0\n\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a, b )\n Returns the standard deviation of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.stdev( 0, 1 )\n ~0.5\n > v = base.dists.discreteUniform.stdev( 4, 12 )\n ~2.582\n > v = base.dists.discreteUniform.stdev( 2, 8 )\n 2.0\n\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a, b )\n Returns the variance of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.variance( 0, 1 )\n ~0.25\n > v = base.dists.discreteUniform.variance( 4, 12 )\n ~6.667\n > v = base.dists.discreteUniform.variance( 2, 8 )\n 4.0\n\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n ~0.865\n > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n ~0.323\n > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( PINF, 4, 2.0 )\n 1.0\n > y = base.dists.erlang.cdf( NINF, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264\n\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k, λ )\n Returns the differential entropy of an Erlang distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.erlang.entropy( 1, 1.0 )\n ~1.0\n > v = base.dists.erlang.entropy( 4, 12.0 )\n ~-0.462\n > v = base.dists.erlang.entropy( 8, 2.0 )\n ~1.723\n\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k, λ] )\n Returns an Erlang distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be a positive integer. Default: `1.0`.\n\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n erlang: Object\n Distribution instance.\n\n erlang.k: number\n Shape parameter. If set, the value must be a positive integer.\n\n erlang.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n erlang.entropy: number\n Read-only property which returns the differential entropy.\n\n erlang.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n erlang.mean: number\n Read-only property which returns the expected value.\n\n erlang.mode: number\n Read-only property which returns the mode.\n\n erlang.skewness: number\n Read-only property which returns the skewness.\n\n erlang.stdev: number\n Read-only property which returns the standard deviation.\n\n erlang.variance: number\n Read-only property which returns the variance.\n\n erlang.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n erlang.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n erlang.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n erlang.pdf: Function\n Evaluates the probability density function (PDF).\n\n erlang.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n > erlang.k\n 6\n > erlang.lambda\n 5.0\n > erlang.entropy\n ~0.647\n > erlang.kurtosis\n 1.0\n > erlang.mean\n 1.2\n > erlang.mode\n 1.0\n > erlang.skewness\n ~0.816\n > erlang.stdev\n ~0.49\n > erlang.variance\n 0.24\n > erlang.cdf( 3.0 )\n ~0.997\n > erlang.logpdf( 3.0 )\n ~-4.638\n > erlang.mgf( -0.5 )\n ~0.564\n > erlang.pdf( 3.0 )\n ~0.01\n > erlang.quantile( 0.8 )\n ~1.581\n\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k, λ )\n Returns the excess kurtosis of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n 6.0\n > v = base.dists.erlang.kurtosis( 4, 12.0 )\n 1.5\n > v = base.dists.erlang.kurtosis( 8, 2.0 )\n 0.75\n\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x, k, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n ~-0.1\n > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n ~-0.111\n > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382\n\n\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k, λ )\n Returns the expected value of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.erlang.mean( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.mean( 4, 12.0 )\n ~0.333\n > v = base.dists.erlang.mean( 8, 2.0 )\n 4.0\n\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t, k, λ )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n ~1.429\n > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n ~9.0\n > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n ~0.444\n\n > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25\n\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k, λ )\n Returns the mode of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.erlang.mode( 1, 1.0 )\n 0.0\n > v = base.dists.erlang.mode( 4, 12.0 )\n 0.25\n > v = base.dists.erlang.mode( 8, 2.0 )\n 3.5\n\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n ~0.905\n > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n ~0.895\n > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15\n\n\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p, k, λ )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive number for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n ~2.994\n > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n ~1.836\n\n > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n NaN\n\n > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n NaN\n\n // Non-integer shape parameter:\n > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n NaN\n // Non-positive shape parameter:\n > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452\n\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k, λ )\n Returns the skewness of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.erlang.skewness( 1, 1.0 )\n 2.0\n > v = base.dists.erlang.skewness( 4, 12.0 )\n 1.0\n > v = base.dists.erlang.skewness( 8, 2.0 )\n ~0.707\n\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k, λ )\n Returns the standard deviation of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.erlang.stdev( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.stdev( 4, 12.0 )\n ~0.167\n > v = base.dists.erlang.stdev( 8, 2.0 )\n ~1.414\n\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k, λ )\n Returns the variance of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.erlang.variance( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.variance( 4, 12.0 )\n ~0.028\n > v = base.dists.erlang.variance( 8, 2.0 )\n 2.0\n\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n ~0.181\n > y = base.dists.exponential.cdf( 1.0, 2.0 )\n ~0.865\n > y = base.dists.exponential.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.exponential.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.cdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.cdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777\n\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ )\n Returns the differential entropy of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.exponential.entropy( 11.0 )\n ~-1.398\n > v = base.dists.exponential.entropy( 4.5 )\n ~-0.504\n\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ] )\n Returns an exponential distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n exponential: Object\n Distribution instance.\n\n exponential.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n exponential.entropy: number\n Read-only property which returns the differential entropy.\n\n exponential.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n exponential.mean: number\n Read-only property which returns the expected value.\n\n exponential.median: number\n Read-only property which returns the median.\n\n exponential.mode: number\n Read-only property which returns the mode.\n\n exponential.skewness: number\n Read-only property which returns the skewness.\n\n exponential.stdev: number\n Read-only property which returns the standard deviation.\n\n exponential.variance: number\n Read-only property which returns the variance.\n\n exponential.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n exponential.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n exponential.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n exponential.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n exponential.pdf: Function\n Evaluates the probability density function (PDF).\n\n exponential.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var exponential = base.dists.exponential.Exponential( 6.0 );\n > exponential.lambda\n 6.0\n > exponential.entropy\n ~-0.792\n > exponential.kurtosis\n 6.0\n > exponential.mean\n ~0.167\n > exponential.median\n ~0.116\n > exponential.mode\n 0.0\n > exponential.skewness\n 2.0\n > exponential.stdev\n ~0.167\n > exponential.variance\n ~0.028\n > exponential.cdf( 1.0 )\n ~0.998\n > exponential.logcdf( 1.0 )\n ~-0.002\n > exponential.logpdf( 1.5 )\n ~-7.208\n > exponential.mgf( -0.5 )\n ~0.923\n > exponential.pdf( 1.5 )\n ~0.001\n > exponential.quantile( 0.5 )\n ~0.116\n\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ )\n Returns the excess kurtosis of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.exponential.kurtosis( 11.0 )\n 6.0\n > v = base.dists.exponential.kurtosis( 4.5 )\n 6.0\n\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x, λ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n ~-1.708\n > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n ~-0.145\n > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.exponential.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.logcdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252\n\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n ~0.186\n > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n ~-1.757\n > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.exponential.logpdf( 0, NaN )\n NaN\n > y = base.dists.exponential.logpdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193\n\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ )\n Returns the expected value of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.exponential.mean( 11.0 )\n ~0.091\n > v = base.dists.exponential.mean( 4.5 )\n ~0.222\n\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ )\n Returns the median of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.exponential.median( 11.0 )\n ~0.063\n > v = base.dists.exponential.median( 4.5 )\n ~0.154\n\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t, λ )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var v = base.dists.exponential.mgf( 2.0, 3.0 )\n 3.0\n > v = base.dists.exponential.mgf( 0.4, 1.2 )\n 1.5\n > v = base.dists.exponential.mgf( 0.8, 1.6 )\n 2.0\n > v = base.dists.exponential.mgf( 4.0, 3.0 )\n NaN\n > v = base.dists.exponential.mgf( NaN, 3.0 )\n NaN\n > v = base.dists.exponential.mgf( 2.0, NaN )\n NaN\n\n\nbase.dists.exponential.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n mg: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n > var y = myMGF( 3.0 )\n 4.0\n > y = myMGF( 0.5 )\n ~1.143\n\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n mg: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n > var y = myMGF( 3.0 )\n 4.0\n > y = myMGF( 0.5 )\n ~1.143","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ )\n Returns the mode of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.exponential.mode( 11.0 )\n 0.0\n > v = base.dists.exponential.mode( 4.5 )\n 0.0\n\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x, λ )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n ~1.205\n > y = base.dists.exponential.pdf( 2.0, 0.7 )\n ~0.173\n > y = base.dists.exponential.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.exponential.pdf( 0, NaN )\n NaN\n > y = base.dists.exponential.pdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.pdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112\n\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p, λ )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n ~1.609\n > y = base.dists.exponential.quantile( 0.5, 4.0 )\n ~0.173\n > y = base.dists.exponential.quantile( 0.5, 0.1 )\n ~6.931\n\n > y = base.dists.exponential.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.exponential.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.quantile( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ )\n Returns the skewness of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.exponential.skewness( 11.0 )\n 2.0\n > v = base.dists.exponential.skewness( 4.5 )\n 2.0\n\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ )\n Returns the standard deviation of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.exponential.stdev( 9.0 )\n ~0.11\n > v = base.dists.exponential.stdev( 1.0 )\n 1.0\n\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ )\n Returns the variance of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.exponential.variance( 9.0 )\n ~0.012\n > v = base.dists.exponential.variance( 1.0 )\n 1.0\n\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x, d1, d2 )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n ~0.608\n > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n ~0.737\n > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > var y = base.dists.f.cdf( PINF, 4.0, 2.0 )\n 1.0\n > var y = base.dists.f.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n NaN\n\n > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n NaN\n > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884\n\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884","base.dists.f.entropy":"\nbase.dists.f.entropy( d1, d2 )\n Returns the differential entropy of an F distribution (in nats).\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.f.entropy( 3.0, 7.0 )\n ~1.298\n > v = base.dists.f.entropy( 4.0, 12.0 )\n ~1.12\n > v = base.dists.f.entropy( 8.0, 2.0 )\n ~2.144\n\n","base.dists.f.F":"\nbase.dists.f.F( [d1, d2] )\n Returns an F distribution object.\n\n Parameters\n ----------\n d1: number (optional)\n Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n d2: number (optional)\n Denominator degrees of freedom. Must be greater than `0`.\n Default: `1.0`.\n\n Returns\n -------\n f: Object\n Distribution instance.\n\n f.d1: number\n Numerator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.d2: number\n Denominator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.entropy: number\n Read-only property which returns the differential entropy.\n\n f.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n f.mean: number\n Read-only property which returns the expected value.\n\n f.mode: number\n Read-only property which returns the mode.\n\n f.skewness: number\n Read-only property which returns the skewness.\n\n f.stdev: number\n Read-only property which returns the standard deviation.\n\n f.variance: number\n Read-only property which returns the variance.\n\n f.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n f.pdf: Function\n Evaluates the probability density function (PDF).\n\n f.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var f = base.dists.f.F( 6.0, 9.0 );\n > f.d1\n 6.0\n > f.d2\n 9.0\n > f.entropy\n ~1.134\n > f.kurtosis\n ~104.564\n > f.mean\n ~1.286\n > f.mode\n ~0.545\n > f.skewness\n ~4.535\n > f.stdev\n ~1.197\n > f.variance\n ~1.433\n > f.cdf( 3.0 )\n ~0.932\n > f.pdf( 2.5 )\n ~0.095\n > f.quantile( 0.8 )\n ~1.826\n\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1, d2 )\n Returns the excess kurtosis of an F distribution.\n\n If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n ~124.667\n > v = base.dists.f.kurtosis( 4.0, 12.0 )\n ~26.143\n > v = base.dists.f.kurtosis( 8.0, 9.0 )\n ~100.167\n\n","base.dists.f.mean":"\nbase.dists.f.mean( d1, d2 )\n Returns the expected value of an F distribution.\n\n If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.f.mean( 3.0, 5.0 )\n ~1.667\n > v = base.dists.f.mean( 4.0, 12.0 )\n ~1.2\n > v = base.dists.f.mean( 8.0, 4.0 )\n 2.0\n\n","base.dists.f.mode":"\nbase.dists.f.mode( d1, d2 )\n Returns the mode of an F distribution.\n\n If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.f.mode( 3.0, 5.0 )\n ~0.238\n > v = base.dists.f.mode( 4.0, 12.0 )\n ~0.429\n > v = base.dists.f.mode( 8.0, 4.0 )\n 0.5\n\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x, d1, d2 )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n ~0.057\n > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n ~0.915\n > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n NaN\n > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166\n\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166","base.dists.f.quantile":"\nbase.dists.f.quantile( p, d1, d2 )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n ~9.472\n > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n ~1.207\n\n > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382\n\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382","base.dists.f.skewness":"\nbase.dists.f.skewness( d1, d2 )\n Returns the skewness of an F distribution.\n\n If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.f.skewness( 3.0, 7.0 )\n 11.0\n > v = base.dists.f.skewness( 4.0, 12.0 )\n ~3.207\n > v = base.dists.f.skewness( 8.0, 7.0 )\n ~10.088\n\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1, d2 )\n Returns the standard deviation of an F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.f.stdev( 3.0, 5.0 )\n ~3.333\n > v = base.dists.f.stdev( 4.0, 12.0 )\n ~1.122\n > v = base.dists.f.stdev( 8.0, 5.0 )\n ~2.764\n\n","base.dists.f.variance":"\nbase.dists.f.variance( d1, d2 )\n Returns the variance of an F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.f.variance( 3.0, 5.0 )\n ~11.111\n > v = base.dists.f.variance( 4.0, 12.0 )\n ~1.26\n > v = base.dists.f.variance( 8.0, 5.0 )\n ~7.639\n\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x, α, s, m )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n ~0.914\n > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n ~0.105\n > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n ~0.018\n > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034\n\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α, s, m )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n ~2.154\n > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n ~1.028\n > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α, s, m] )\n Returns a Fréchet distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n m: number (optional)\n Location parameter. Default: `0.0`.\n\n Returns\n -------\n frechet: Object\n Distribution instance.\n\n frechet.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n frechet.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n frechet.m: number\n Location parameter.\n\n frechet.entropy: number\n Read-only property which returns the differential entropy.\n\n frechet.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n frechet.mean: number\n Read-only property which returns the expected value.\n\n frechet.median: number\n Read-only property which returns the median.\n\n frechet.mode: number\n Read-only property which returns the mode.\n\n frechet.skewness: number\n Read-only property which returns the skewness.\n\n frechet.stdev: number\n Read-only property which returns the standard deviation.\n\n frechet.variance: number\n Read-only property which returns the variance.\n\n frechet.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n frechet.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n frechet.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n frechet.pdf: Function\n Evaluates the probability density function (PDF).\n\n frechet.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n > frechet.alpha\n 1.0\n > frechet.s\n 1.0\n > frechet.m\n 0.0\n > frechet.entropy\n ~2.154\n > frechet.kurtosis\n Infinity\n > frechet.mean\n Infinity\n > frechet.median\n ~1.443\n > frechet.mode\n 0.5\n > frechet.skewness\n Infinity\n > frechet.stdev\n Infinity\n > frechet.variance\n Infinity\n > frechet.cdf( 0.8 )\n ~0.287\n > frechet.logcdf( 0.8 )\n -1.25\n > frechet.logpdf( 0.8 )\n ~-0.804\n > frechet.pdf( 0.8 )\n ~0.448\n > frechet.quantile( 0.8 )\n ~4.481\n\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α, s, m )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 4` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n ~45.092\n > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n ~45.092\n > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x, α, s, m )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n ~-0.09\n > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n ~-2.25\n > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n -4.0\n > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375\n\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x, α, s, m )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n ~-2.72\n > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n ~-1.901\n > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n ~-0.307\n > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11\n\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α, s, m )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 1` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n ~3.451\n > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α, s, m )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n ~3.192\n > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n ~-0.808\n > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n ~5.163\n > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α, s, m )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n ~2.891\n > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n ~-1.109\n > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n ~1.222\n > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x, α, s, m )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368\n\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p, α, s, m )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n ~4.963\n > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n ~5.56\n > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n ~6.491\n > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576\n\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α, s, m )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 3` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n ~5.605\n > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n ~5.605\n > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α, s, m )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n ~1.041\n > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n ~1.041\n > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α, s, m )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n ~1.083\n > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n ~1.083\n > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n ~0.323\n > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0` when `α = 0.0`:\n > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264\n\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α, β )\n Returns the differential entropy of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.entropy( 4.0, 12.0 )\n ~-0.462\n > v = base.dists.gamma.entropy( 8.0, 2.0 )\n ~1.723\n\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α, β] )\n Returns a gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gamma: Object\n Distribution instance.\n\n gamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n gamma.beta: number\n Rate parameter. If set, the value must be greater than `0`.\n\n gamma.entropy: number\n Read-only property which returns the differential entropy.\n\n gamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gamma.mean: number\n Read-only property which returns the expected value.\n\n gamma.mode: number\n Read-only property which returns the mode.\n\n gamma.skewness: number\n Read-only property which returns the skewness.\n\n gamma.stdev: number\n Read-only property which returns the standard deviation.\n\n gamma.variance: number\n Read-only property which returns the variance.\n\n gamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gamma.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gamma.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n gamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n > gamma.alpha\n 6.0\n > gamma.beta\n 5.0\n > gamma.entropy\n ~0.647\n > gamma.kurtosis\n 1.0\n > gamma.mean\n 1.2\n > gamma.mode\n 1.0\n > gamma.skewness\n ~0.816\n > gamma.stdev\n ~0.49\n > gamma.variance\n 0.24\n > gamma.cdf( 0.8 )\n ~0.215\n > gamma.logcdf( 0.8 )\n ~-1.538\n > gamma.logpdf( 1.0 )\n ~-0.131\n > gamma.mgf( -0.5 )\n ~0.564\n > gamma.pdf( 1.0 )\n ~0.877\n > gamma.quantile( 0.8 )\n ~1.581\n\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α, β )\n Returns the excess kurtosis of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n 1.5\n > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n 0.75\n\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x, α, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\n ~-0.047\n > y = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\n ~-2.352\n > y = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.logcdf.factory( α, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n > var y = mylogCDF( 2.0 )\n ~-0.006\n\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n > var y = mylogCDF( 2.0 )\n ~-0.006","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x, α, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.919\n > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646\n\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α, β )\n Returns the expected value of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.gamma.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.mean( 4.0, 12.0 )\n ~0.333\n > v = base.dists.gamma.mean( 8.0, 2.0 )\n 4.0\n\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n ~1.414\n > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n ~1.111\n > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n ~0.198\n\n > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375\n\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α, β )\n Returns the mode of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.gamma.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.gamma.mode( 4.0, 12.0 )\n 0.25\n > v = base.dists.gamma.mode( 8.0, 2.0 )\n 3.5\n\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n ~0.054\n > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026\n\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p, α, β )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n ~2.994\n > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n ~1.836\n\n > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688\n\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α, β )\n Returns the skewness of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.gamma.skewness( 4.0, 12.0 )\n 1.0\n > v = base.dists.gamma.skewness( 8.0, 2.0 )\n ~0.707\n\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α, β )\n Returns the standard deviation of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.stdev( 4.0, 12.0 )\n ~0.167\n > v = base.dists.gamma.stdev( 8.0, 2.0 )\n ~1.414\n\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α, β )\n Returns the variance of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.gamma.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.variance( 4.0, 12.0 )\n ~0.028\n > v = base.dists.gamma.variance( 8.0, 2.0 )\n 2.0\n\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n 0.875\n > y = base.dists.geometric.cdf( 2.0, 0.1 )\n ~0.271\n > y = base.dists.geometric.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.geometric.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.cdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75\n\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.geometric.entropy( 0.1 )\n ~3.251\n > v = base.dists.geometric.entropy( 0.5 )\n ~1.386\n\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p] )\n Returns a geometric distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n geometric: Object\n Distribution instance.\n\n geometric.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n geometric.entropy: number\n Read-only property which returns the differential entropy.\n\n geometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n geometric.mean: number\n Read-only property which returns the expected value.\n\n geometric.median: number\n Read-only property which returns the median.\n\n geometric.mode: number\n Read-only property which returns the mode.\n\n geometric.skewness: number\n Read-only property which returns the skewness.\n\n geometric.stdev: number\n Read-only property which returns the standard deviation.\n\n geometric.variance: number\n Read-only property which returns the variance.\n\n geometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n geometric.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n geometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n geometric.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n geometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n geometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var geometric = base.dists.geometric.Geometric( 0.6 );\n > geometric.p\n 0.6\n > geometric.entropy\n ~1.122\n > geometric.kurtosis\n ~6.9\n > geometric.mean\n ~0.667\n > geometric.median\n 0.0\n > geometric.mode\n 0.0\n > geometric.skewness\n ~2.214\n > geometric.stdev\n ~1.054\n > geometric.variance\n ~1.111\n > geometric.cdf( 3.0 )\n ~0.974\n > geometric.logcdf( 3.0 )\n ~-0.026\n > geometric.logpmf( 4.0 )\n ~-4.176\n > geometric.mgf( 0.5 )\n ~2.905\n > geometric.pmf( 2.0 )\n ~0.096\n > geometric.quantile( 0.7 )\n 1.0\n\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.geometric.kurtosis( 0.1 )\n ~6.011\n > v = base.dists.geometric.kurtosis( 0.5 )\n 6.5\n\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x, p )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n ~-0.134\n > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n ~-1.306\n > y = base.dists.geometric.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.geometric.logcdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.logcdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288\n\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x, p )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n ~-2.631\n > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n ~-2.765\n > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.geometric.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.logpmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386\n\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.geometric.mean( 0.1 )\n 9.0\n > v = base.dists.geometric.mean( 0.5 )\n 1.0\n\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p )\n Returns the median of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.geometric.median( 0.1 )\n 6\n > v = base.dists.geometric.median( 0.5 )\n 0\n\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `t >= -ln(1-p)`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n ~1.569\n > y = base.dists.geometric.mgf( 0.4, 0.5 )\n ~2.936\n // Case: t >= -ln(1-p)\n > y = base.dists.geometric.mgf( 0.8, 0.5 )\n NaN\n > y = base.dists.geometric.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783\n\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p )\n Returns the mode of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.geometric.mode( 0.1 )\n 0\n > v = base.dists.geometric.mode( 0.5 )\n 0\n\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x, p )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n ~0.072\n > y = base.dists.geometric.pmf( 2.0, 0.7 )\n ~0.063\n > y = base.dists.geometric.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.geometric.pmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.pmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25\n\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r, p )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n 3\n > y = base.dists.geometric.quantile( 0.5, 0.4 )\n 1\n > y = base.dists.geometric.quantile( 0.9, 0.1 )\n 21\n\n > y = base.dists.geometric.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.geometric.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.geometric.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.geometric.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.geometric.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity\n\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.geometric.skewness( 0.1 )\n ~2.003\n > v = base.dists.geometric.skewness( 0.5 )\n ~2.121\n\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.geometric.stdev( 0.1 )\n ~9.487\n > v = base.dists.geometric.stdev( 0.5 )\n ~1.414\n\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p )\n Returns the variance of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.geometric.variance( 0.1 )\n ~90.0\n > v = base.dists.geometric.variance( 0.5 )\n 2.0\n\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x, μ, β )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368\n\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ, β )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n ~1.577\n > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n ~2.27\n > y = base.dists.gumbel.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ, β] )\n Returns a Gumbel distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gumbel: Object\n Distribution instance.\n\n gumbel.mu: number\n Location parameter.\n\n gumbel.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n gumbel.entropy: number\n Read-only property which returns the differential entropy.\n\n gumbel.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gumbel.mean: number\n Read-only property which returns the expected value.\n\n gumbel.median: number\n Read-only property which returns the median.\n\n gumbel.mode: number\n Read-only property which returns the mode.\n\n gumbel.skewness: number\n Read-only property which returns the skewness.\n\n gumbel.stdev: number\n Read-only property which returns the standard deviation.\n\n gumbel.variance: number\n Read-only property which returns the variance.\n\n gumbel.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gumbel.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gumbel.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gumbel.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gumbel.pdf: Function\n Evaluates the probability density function (PDF).\n\n gumbel.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n > gumbel.mu\n -2.0\n > gumbel.beta\n 3.0\n > gumbel.entropy\n ~2.676\n > gumbel.kurtosis\n 2.4\n > gumbel.mean\n ~-0.268\n > gumbel.median\n ~-0.9\n > gumbel.mode\n -2.0\n > gumbel.skewness\n ~1.14\n > gumbel.stdev\n ~3.848\n > gumbel.variance\n ~14.804\n > gumbel.cdf( 0.8 )\n ~0.675\n > gumbel.logcdf( 0.8 )\n ~-0.393\n > gumbel.logpdf( 1.0 )\n ~-2.466\n > gumbel.mgf( 0.2 )\n ~1.487\n > gumbel.pdf( 1.0 )\n ~0.085\n > gumbel.quantile( 0.8 )\n ~2.5\n\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ, β )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x, μ, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n ~-0.036\n > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n ~-1.948\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n ~-1.0\n > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0\n\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x, μ, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n ~-1.693\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n ~-1\n > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n ~-2.411\n > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061\n\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ, β )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n ~0.577\n > y = base.dists.gumbel.mean( 4.0, 2.0 )\n ~5.154\n > y = base.dists.gumbel.mean( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mean( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ, β )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.gumbel.median( 0.0, 1.0 )\n ~0.367\n > y = base.dists.gumbel.median( 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.median( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.median( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.median( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t, μ, β )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n 6.0\n > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n ~1.298\n\n > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n NaN\n\n // Case: `t >= 1/beta`\n > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n NaN\n\n // Non-positive scale parameter:\n > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0\n\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ, β )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.gumbel.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.gumbel.mode( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mode( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x, μ, β )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n ~0.184\n > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n ~0.09\n > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127\n\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p, μ, β )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n ~1.5\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n ~5.466\n\n > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062\n\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ, β )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ, β )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n ~1.283\n > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n ~2.565\n > y = base.dists.gumbel.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ, β )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n ~1.645\n > y = base.dists.gumbel.variance( 4.0, 2.0 )\n ~6.58\n > y = base.dists.gumbel.variance( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.variance( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x, N, K, n )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceeds population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n 1.0\n > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n ~0.214\n\n > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031\n\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n Returns a hypergeometric distribution object.\n\n Parameters\n ----------\n N: integer (optional)\n Population size. Must be a nonnegative integer larger than or equal to\n `K` and `n`.\n\n K: integer (optional)\n Subpopulation size. Must be a nonnegative integer smaller than or equal\n to `N`.\n\n n: integer (optional)\n Number of draws. Must be a nonnegative integer smaller than or equal to\n `N`.\n\n Returns\n -------\n hypergeometric: Object\n Distribution instance.\n\n hypergeometric.N: number\n Population size. If set, the value must be a nonnegative integer larger\n than or equal to `K` and `n`.\n\n hypergeometric.K: number\n Subpopulation size. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.n: number\n Number of draws. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n hypergeometric.mean: number\n Read-only property which returns the expected value.\n\n hypergeometric.mode: number\n Read-only property which returns the mode.\n\n hypergeometric.skewness: number\n Read-only property which returns the skewness.\n\n hypergeometric.stdev: number\n Read-only property which returns the standard deviation.\n\n hypergeometric.variance: number\n Read-only property which returns the variance.\n\n hypergeometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n hypergeometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n hypergeometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n hypergeometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n > hypergeometric.N\n 100.0\n > hypergeometric.K\n 70.0\n > hypergeometric.n\n 20.0\n > hypergeometric.kurtosis\n ~-0.063\n > hypergeometric.mean\n 14.0\n > hypergeometric.mode\n 14.0\n > hypergeometric.skewness\n ~-0.133\n > hypergeometric.stdev\n ~1.842\n > hypergeometric.variance\n ~3.394\n > hypergeometric.cdf( 2.9 )\n ~0.0\n > hypergeometric.logpmf( 10 )\n ~-3.806\n > hypergeometric.pmf( 10 )\n ~0.022\n > hypergeometric.quantile( 0.8 )\n 16.0\n\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N, K, n )\n Returns the excess kurtosis of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceed population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n ~-0.326\n > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K`, or draws `n`\n which is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n ~-0.56\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n -Infinity\n\n > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524\n\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N, K, n )\n Returns the expected value of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n 2.75\n > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N, K, n )\n Returns the mode of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n 3\n > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n 1\n\n > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x, N, K, n )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n ~0.571\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n 0.0\n\n > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029\n\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p, N, K, n )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n 5\n > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n 15\n > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n 1\n > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n 0\n > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n 20\n\n > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4\n\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N, K, n )\n Returns the skewness of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n ~-0.258\n > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N, K, n )\n Returns the standard deviation of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n ~0.829\n > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N, K, n )\n Returns the variance of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n ~0.688\n > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n 0.25\n\n > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n NaN\n\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n ~0.607\n > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n ~0.986\n > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974\n\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α, β )\n Returns the differential entropy of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n ~2.154\n > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n ~1.996\n > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n ~-0.922\n\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α, β] )\n Returns an inverse gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n invgamma: Object\n Distribution instance.\n\n invgamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n invgamma.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n invgamma.entropy: number\n Read-only property which returns the differential entropy.\n\n invgamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n invgamma.mean: number\n Read-only property which returns the expected value.\n\n invgamma.mode: number\n Read-only property which returns the mode.\n\n invgamma.skewness: number\n Read-only property which returns the skewness.\n\n invgamma.stdev: number\n Read-only property which returns the standard deviation.\n\n invgamma.variance: number\n Read-only property which returns the variance.\n\n invgamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n invgamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n invgamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n invgamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n > invgamma.alpha\n 6.0\n > invgamma.beta\n 5.0\n > invgamma.entropy\n ~0.454\n > invgamma.kurtosis\n 19.0\n > invgamma.mean\n 1.0\n > invgamma.mode\n ~0.714\n > invgamma.skewness\n ~2.667\n > invgamma.stdev\n 0.5\n > invgamma.variance\n 0.25\n > invgamma.cdf( 0.8 )\n ~0.406\n > invgamma.pdf( 1.0 )\n ~0.877\n > invgamma.logpdf( 1.0 )\n ~-0.131\n > invgamma.quantile( 0.8 )\n ~1.281\n\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α, β )\n Returns the excess kurtosis of an inverse gamma distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n 12.0\n > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n 19.0\n > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n ~8.7\n\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.112\n > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n ~-1.781\n > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464\n\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α, β )\n Returns the expected value of an inverse gamma distribution.\n\n If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n 4.0\n > v = base.dists.invgamma.mean( 8.0, 2.0 )\n ~0.286\n\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α, β )\n Returns the mode of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n 0.5\n > v = base.dists.invgamma.mode( 4.0, 12.0 )\n 2.4\n > v = base.dists.invgamma.mode( 8.0, 2.0 )\n ~0.222\n\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n ~0.121\n > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n ~0.168\n > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231\n\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p, α, β )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n ~1.213\n > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n ~0.545\n > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n\n // Non-positive rate parameter:\n > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989\n\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α, β )\n Returns the skewness of an inverse gamma distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n ~5.657\n > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n ~1.96\n\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α, β )\n Returns the standard deviation of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n ~1.01\n > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n ~0.117\n\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α, β )\n Returns the variance of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n ~1.021\n > v = base.dists.invgamma.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.invgamma.variance( 8.0, 2.0 )\n ~0.014\n\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n ~0.5\n > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n ~0.684\n > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n ~0.078\n > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n ~0.878\n > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548\n\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n Returns a Kumaraswamy's double bounded distribution object.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n b: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n kumaraswamy: Object\n Distribution instance.\n\n kumaraswamy.a: number\n First shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.b: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n kumaraswamy.mean: number\n Read-only property which returns the expected value.\n\n kumaraswamy.mode: number\n Read-only property which returns the mode.\n\n kumaraswamy.skewness: number\n Read-only property which returns the skewness.\n\n kumaraswamy.stdev: number\n Read-only property which returns the standard deviation.\n\n kumaraswamy.variance: number\n Read-only property which returns the variance.\n\n kumaraswamy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n kumaraswamy.pdf: Function\n Evaluates the probability density function (PDF).\n\n kumaraswamy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n > kumaraswamy.a\n 6.0\n > kumaraswamy.b\n 5.0\n > kumaraswamy.kurtosis\n ~3.194\n > kumaraswamy.mean\n ~0.696\n > kumaraswamy.mode\n ~0.746\n > kumaraswamy.skewness\n ~-0.605\n > kumaraswamy.stdev\n ~0.126\n > kumaraswamy.variance\n ~0.016\n > kumaraswamy.cdf( 0.8 )\n ~0.781\n > kumaraswamy.pdf( 1.0 )\n ~0.0\n > kumaraswamy.quantile( 0.8 )\n ~0.807\n\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a, b )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n ~1.8\n > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n ~2.704\n > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n ~4.311\n\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n ~-0.38\n > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n ~-2.546\n > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n ~-0.13\n > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602\n\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n ~0.523\n > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n ~-0.264\n > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n ~0.522\n > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091\n\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a, b )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n ~0.512\n > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n ~0.481\n > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n ~0.846\n\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a, b )\n Returns the median of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n ~0.487\n > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n ~0.856\n\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a, b )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n ~0.543\n > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n ~0.503\n > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n ~0.875\n\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x, a, b )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n ~1.688\n > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n ~0.768\n > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n ~1.686\n > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913\n\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p, a, b )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n ~0.399\n > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n ~0.325\n > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n ~0.759\n\n > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09\n\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a, b )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n ~1.154e-15\n > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n ~-0.201\n > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n ~-0.94\n\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a, b )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n ~0.13\n > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n ~0.062\n\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a, b )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n ~0.017\n > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n ~0.004\n\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x, μ, b )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n ~0.932\n > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n ~0.094\n > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5\n\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ, b )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n ~1.693\n > y = base.dists.laplace.entropy( 4.0, 2.0 )\n ~2.386\n > y = base.dists.laplace.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.entropy( 0.0, NaN )\n NaN\n > y = base.dists.laplace.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ, b )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ, b] )\n Returns a Laplace distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n b: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n laplace: Object\n Distribution instance.\n\n laplace.mu: number\n Location parameter.\n\n laplace.b: number\n Scale parameter. If set, the value must be greater than `0`.\n\n laplace.entropy: number\n Read-only property which returns the differential entropy.\n\n laplace.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n laplace.mean: number\n Read-only property which returns the expected value.\n\n laplace.median: number\n Read-only property which returns the median.\n\n laplace.mode: number\n Read-only property which returns the mode.\n\n laplace.skewness: number\n Read-only property which returns the skewness.\n\n laplace.stdev: number\n Read-only property which returns the standard deviation.\n\n laplace.variance: number\n Read-only property which returns the variance.\n\n laplace.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n laplace.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n laplace.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n laplace.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n laplace.pdf: Function\n Evaluates the probability density function (PDF).\n\n laplace.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n > laplace.mu\n -2.0\n > laplace.b\n 3.0\n > laplace.entropy\n ~2.792\n > laplace.kurtosis\n 3.0\n > laplace.mean\n -2.0\n > laplace.median\n -2.0\n > laplace.mode\n -2.0\n > laplace.skewness\n 0.0\n > laplace.stdev\n ~4.243\n > laplace.variance\n 18.0\n > laplace.cdf( 0.8 )\n ~0.803\n > laplace.logcdf( 0.8 )\n ~-0.219\n > laplace.logpdf( 1.0 )\n ~-2.792\n > laplace.mgf( 0.2 )\n ~1.047\n > laplace.pdf( 2.0 )\n ~0.044\n > laplace.quantile( 0.9 )\n ~2.828\n\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x, μ, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n ~-0.07\n > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n ~-2.36\n > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693\n\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x, μ, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n ~-2.693\n > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n ~-2.792\n > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n ~-1.958\n > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386\n\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ, b )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.laplace.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mean( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mean( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ, b )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.laplace.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.median( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.median( 0.0, NaN )\n NaN\n > y = base.dists.laplace.median( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t, μ, b )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n ~1.333\n > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n ~0.019\n > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n NaN\n > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758\n\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ, b )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.laplace.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mode( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mode( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x, μ, b )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n ~0.068\n > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n ~0.061\n > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n ~0.141\n > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25\n\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p, μ, b )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n ~0.916\n > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n 4.0\n\n > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833\n\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ, b )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.laplace.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.skewness( 0.0, NaN )\n NaN\n > y = base.dists.laplace.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ, b )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n ~1.414\n > y = base.dists.laplace.stdev( 4.0, 2.0 )\n ~2.828\n > y = base.dists.laplace.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.stdev( 0.0, NaN )\n NaN\n > y = base.dists.laplace.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ, b )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.laplace.variance( 0.0, 1.0 )\n 2.0\n > y = base.dists.laplace.variance( 4.0, 2.0 )\n 8.0\n > y = base.dists.laplace.variance( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.variance( 0.0, NaN )\n NaN\n > y = base.dists.laplace.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x, μ, c )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n ~0.48\n > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n ~0.221\n > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n 0.0\n > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0\n\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ, c )\n Returns the differential entropy of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.levy.entropy( 0.0, 1.0 )\n ~3.324\n > y = base.dists.levy.entropy( 4.0, 2.0 )\n ~4.018\n > y = base.dists.levy.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.levy.entropy( 0.0, NaN )\n NaN\n > y = base.dists.levy.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ, c] )\n Returns a Lévy distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n c: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n levy: Object\n Distribution instance.\n\n levy.mu: number\n Location parameter.\n\n levy.c: number\n Scale parameter. If set, the value must be greater than `0`.\n\n levy.entropy: number\n Read-only property which returns the differential entropy.\n\n levy.mean: number\n Read-only property which returns the expected value.\n\n levy.median: number\n Read-only property which returns the median.\n\n levy.mode: number\n Read-only property which returns the mode.\n\n levy.stdev: number\n Read-only property which returns the standard deviation.\n\n levy.variance: number\n Read-only property which returns the variance.\n\n levy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n levy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n levy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n levy.pdf: Function\n Evaluates the probability density function (PDF).\n\n levy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n > levy.mu\n -2.0\n > levy.c\n 3.0\n > levy.entropy\n ~4.423\n > levy.mean\n Infinity\n > levy.median\n ~4.594\n > levy.mode\n -1.0\n > levy.stdev\n Infinity\n > levy.variance\n Infinity\n > levy.cdf( 0.8 )\n ~0.3\n > levy.logcdf( 0.8 )\n ~-1.2\n > levy.logpdf( 1.0 )\n ~-2.518\n > levy.pdf( 1.0 )\n ~0.081\n > levy.quantile( 0.8 )\n ~44.74\n\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x, μ, c )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n ~-0.735\n > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n ~-1.51\n > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n -Infinity\n > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity\n\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x, μ, c )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n ~-2.209\n > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572\n\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572","base.dists.levy.mean":"\nbase.dists.levy.mean( μ, c )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.levy.mean( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.mean( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.mean( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mean( 0.0, NaN )\n NaN\n > y = base.dists.levy.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.median":"\nbase.dists.levy.median( μ, c )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.levy.median( 0.0, 1.0 )\n ~2.198\n > y = base.dists.levy.median( 4.0, 3.0 )\n ~10.594\n > y = base.dists.levy.median( NaN, 1.0 )\n NaN\n > y = base.dists.levy.median( 0.0, NaN )\n NaN\n > y = base.dists.levy.median( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ, c )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.levy.mode( 0.0, 1.0 )\n ~0.333\n > y = base.dists.levy.mode( 4.0, 3.0 )\n 5.0\n > y = base.dists.levy.mode( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mode( 0.0, NaN )\n NaN\n > y = base.dists.levy.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x, μ, c )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n ~0.11\n > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208\n\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p, μ, c )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n ~15.58\n > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n ~8.396\n\n > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396\n\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ, c )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.levy.stdev( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.stdev( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.levy.stdev( 0.0, NaN )\n NaN\n > y = base.dists.levy.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ, c )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.levy.variance( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.variance( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.variance( NaN, 1.0 )\n NaN\n > y = base.dists.levy.variance( 0.0, NaN )\n NaN\n > y = base.dists.levy.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n ~0.881\n > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n ~0.159\n\n > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209\n\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ, s )\n Returns the differential entropy of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n 2.0\n > y = base.dists.logistic.entropy( 4.0, 2.0 )\n ~2.693\n > y = base.dists.logistic.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.entropy( 0.0, NaN )\n NaN\n > y = base.dists.logistic.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ, s )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n NaN\n\n\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x, μ, s )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n ~-0.127\n > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n ~-1.84\n > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567\n\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ, s] )\n Returns a logistic distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n logistic: Object\n Distribution instance.\n\n logistic.mu: number\n Location parameter.\n\n logistic.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n logistic.entropy: number\n Read-only property which returns the differential entropy.\n\n logistic.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n logistic.mean: number\n Read-only property which returns the expected value.\n\n logistic.median: number\n Read-only property which returns the median.\n\n logistic.mode: number\n Read-only property which returns the mode.\n\n logistic.skewness: number\n Read-only property which returns the skewness.\n\n logistic.stdev: number\n Read-only property which returns the standard deviation.\n\n logistic.variance: number\n Read-only property which returns the variance.\n\n logistic.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n logistic.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n logistic.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n logistic.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n logistic.pdf: Function\n Evaluates the probability density function (PDF).\n\n logistic.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n > logistic.mu\n -2.0\n > logistic.s\n 3.0\n > logistic.entropy\n ~3.1\n > logistic.kurtosis\n 1.2\n > logistic.mean\n -2.0\n > logistic.median\n -2.0\n > logistic.mode\n -2.0\n > logistic.skewness\n 0.0\n > logistic.stdev\n ~5.441\n > logistic.variance\n ~29.609\n > logistic.cdf( 0.8 )\n ~0.718\n > logistic.logcdf( 0.8 )\n ~-0.332\n > logistic.logpdf( 2.0 )\n ~-2.9\n > logistic.mgf( 0.2 )\n ~1.329\n > logistic.pdf( 2.0 )\n ~0.055\n > logistic.quantile( 0.9 )\n ~4.592\n\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n ~-2.254\n > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n ~-3.351\n > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079\n\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ, s )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.logistic.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mean( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mean( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ, s )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.logistic.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.median( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.median( 0.0, NaN )\n NaN\n > y = base.dists.logistic.median( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n ~9.15\n > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n ~1.971\n > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n ~1.921\n > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n Infinity\n > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity\n\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ, s )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.logistic.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mode( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mode( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n ~0.105\n > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n ~0.035\n > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125\n\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p, μ, s )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n ~1.386\n > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ, s )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.logistic.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.skewness( 0.0, NaN )\n NaN\n > y = base.dists.logistic.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ, s )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n ~1.814\n > y = base.dists.logistic.stdev( 4.0, 2.0 )\n ~3.628\n > y = base.dists.logistic.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.stdev( 0.0, NaN )\n NaN\n > y = base.dists.logistic.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ, s )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.logistic.variance( 0.0, 1.0 )\n ~3.29\n > y = base.dists.logistic.variance( 4.0, 2.0 )\n ~13.159\n > y = base.dists.logistic.variance( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.variance( 0.0, NaN )\n NaN\n > y = base.dists.logistic.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n ~0.756\n > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n ~0.003\n\n > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141\n\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ, σ )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n ~7.112\n > y = base.dists.lognormal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ, σ )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n ~110.936\n > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n ~9220556.977\n > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ, σ] )\n Returns a lognormal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n lognormal: Object\n Distribution instance.\n\n lognormal.mu: number\n Location parameter.\n\n lognormal.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n lognormal.entropy: number\n Read-only property which returns the differential entropy.\n\n lognormal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n lognormal.mean: number\n Read-only property which returns the expected value.\n\n lognormal.median: number\n Read-only property which returns the median.\n\n lognormal.mode: number\n Read-only property which returns the mode.\n\n lognormal.skewness: number\n Read-only property which returns the skewness.\n\n lognormal.stdev: number\n Read-only property which returns the standard deviation.\n\n lognormal.variance: number\n Read-only property which returns the variance.\n\n lognormal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n lognormal.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n lognormal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n lognormal.pdf: Function\n Evaluates the probability density function (PDF).\n\n lognormal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n > lognormal.mu\n -2.0\n > lognormal.sigma\n 3.0\n > lognormal.entropy\n ~0.518\n > lognormal.kurtosis\n 4312295840576300\n > lognormal.mean\n ~12.182\n > lognormal.median\n ~0.135\n > lognormal.mode\n ~0.0\n > lognormal.skewness\n ~729551.383\n > lognormal.stdev\n ~1096.565\n > lognormal.variance\n ~1202455.871\n > lognormal.cdf( 0.8 )\n ~0.723\n > lognormal.logcdf( 0.8 )\n ~-4.334\n > lognormal.logpdf( 2.0 )\n ~-3.114\n > lognormal.pdf( 2.0 )\n ~0.044\n > lognormal.quantile( 0.9 )\n ~6.326\n\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x, μ, σ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logcdf.\n\n Examples\n --------\n > var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\n ~-0.2799\n > y = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\n ~-1.442\n > y = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n -Infinity\n\n\nbase.dists.lognormal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-9.732\n\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-9.732","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n ~-1.852\n > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n ~-0.919\n > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n ~-5.419\n > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672\n\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ, σ )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n ~1.649\n > y = base.dists.lognormal.mean( 4.0, 2.0 )\n ~403.429\n > y = base.dists.lognormal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mean( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ, σ )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.lognormal.median( 0.0, 1.0 )\n 1.0\n > y = base.dists.lognormal.median( 5.0, 2.0 )\n ~148.413\n > y = base.dists.lognormal.median( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.median( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ, σ )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n ~0.368\n > y = base.dists.lognormal.mode( 5.0, 2.0 )\n ~2.718\n > y = base.dists.lognormal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mode( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n ~0.157\n > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n ~0.399\n > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n ~0.004\n > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025\n\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p, μ, σ )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n ~2.32\n > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n ~54.598\n > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901\n\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ, σ )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n ~6.185\n > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n ~414.359\n > y = base.dists.lognormal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ, σ )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n ~2.161\n > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n ~2953.533\n > y = base.dists.lognormal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ, σ )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n ~4.671\n > y = base.dists.lognormal.variance( 4.0, 2.0 )\n ~8723355.729\n > y = base.dists.lognormal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.variance( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x, r, p )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n ~0.617\n > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n ~0.622\n > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n ~0.034\n > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n ~0.859\n > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n ~0.131\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668\n\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r, p )\n Returns the excess kurtosis of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n ~0.061\n > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n ~0.325\n\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x, r, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n ~-1.853\n > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n ~-2.818\n > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n ~-4.115\n > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n ~-1.054\n > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n ~-3.292\n > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n ~-2.976\n\n > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795\n\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r, p )\n Returns the expected value of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n 400\n > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n 20\n\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x, r, p )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n ~267.839\n > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n ~9.347\n > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n ~42822.023\n\n > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83\n\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r, p )\n Returns the mode of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n 396\n > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n 19\n\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n Returns a negative binomial distribution object.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped. Must be a positive\n number. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n nbinomial: Object\n Distribution instance.\n\n nbinomial.r: number\n Number of trials. If set, the value must be a positive number.\n\n nbinomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n nbinomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n nbinomial.mean: number\n Read-only property which returns the expected value.\n\n nbinomial.mode: number\n Read-only property which returns the mode.\n\n nbinomial.skewness: number\n Read-only property which returns the skewness.\n\n nbinomial.stdev: number\n Read-only property which returns the standard deviation.\n\n nbinomial.variance: number\n Read-only property which returns the variance.\n\n nbinomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n nbinomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n nbinomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n nbinomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n nbinomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n > nbinomial.r\n 8.0\n > nbinomial.p\n 0.5\n > nbinomial.kurtosis\n 0.8125\n > nbinomial.mean\n 8.0\n > nbinomial.mode\n 7.0\n > nbinomial.skewness\n 0.75\n > nbinomial.stdev\n 4.0\n > nbinomial.variance\n 16.0\n > nbinomial.cdf( 2.9 )\n ~0.055\n > nbinomial.logpmf( 3.0 )\n ~-2.837\n > nbinomial.mgf( 0.2 )\n ~36.675\n > nbinomial.pmf( 3.0 )\n ~0.059\n > nbinomial.quantile( 0.8 )\n 11.0\n\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x, r, p )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n ~0.157\n > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n ~0.06\n > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n ~0.016\n > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n ~0.037\n > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n ~0.051\n\n > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061\n\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k, r, p )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n\n If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n k: number\n Input probability.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n 106\n > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n 8\n > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n 14\n > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n 0\n\n > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n 12\n > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n 10\n\n > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16\n\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r, p )\n Returns the skewness of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n ~0.201\n > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n ~0.474\n\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r, p )\n Returns the standard deviation of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n ~44.721\n > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n ~6.325\n\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r, p )\n Returns the variance of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n 2000.0\n > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n 40.0\n\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n ~0.977\n > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n 0.5\n > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n ~0.006\n > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5\n\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ, σ )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.normal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.normal.entropy( 4.0, 3.0 )\n ~2.518\n > y = base.dists.normal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.normal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.normal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ, σ )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x, μ, σ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logcdf.\n\n Examples\n --------\n > var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\n ~-0.023\n > y = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\n ~-5.082\n > y = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logcdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.normal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.693\n\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.693","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n ~-2.919\n > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n ~-4.737\n > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612\n\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612","base.dists.normal.mean":"\nbase.dists.normal.mean( μ, σ )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.normal.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mean( 0.0, NaN )\n NaN\n > y = base.dists.normal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.median":"\nbase.dists.normal.median( μ, σ )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.normal.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.median( NaN, 1.0 )\n NaN\n > y = base.dists.normal.median( 0.0, NaN )\n NaN\n > y = base.dists.normal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x, μ, σ )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n ~7.389\n > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n ~0.1353\n > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182\n\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182","base.dists.normal.mode":"\nbase.dists.normal.mode( μ, σ )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.normal.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mode( 0.0, NaN )\n NaN\n > y = base.dists.normal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ, σ] )\n Returns a normal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Mean parameter. Default: `0.0`.\n\n σ: number (optional)\n Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n normal: Object\n Distribution instance.\n\n normal.mu: number\n Mean parameter.\n\n normal.sigma: number\n Standard deviation. If set, the value must be greater than `0`.\n\n normal.entropy: number\n Read-only property which returns the differential entropy.\n\n normal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n normal.mean: number\n Read-only property which returns the expected value.\n\n normal.median: number\n Read-only property which returns the median.\n\n normal.mode: number\n Read-only property which returns the mode.\n\n normal.skewness: number\n Read-only property which returns the skewness.\n\n normal.stdev: number\n Read-only property which returns the standard deviation.\n\n normal.variance: number\n Read-only property which returns the variance.\n\n normal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n normal.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n normal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n normal.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n normal.pdf: Function\n Evaluates the probability density function (PDF).\n\n normal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n > normal.mu\n -2.0\n > normal.sigma\n 3.0\n > normal.entropy\n ~2.518\n > normal.kurtosis\n 0.0\n > normal.mean\n -2.0\n > normal.median\n -2.0\n > normal.mode\n -2.0\n > normal.skewness\n 0.0\n > normal.stdev\n 3.0\n > normal.variance\n 9.0\n > normal.cdf( 0.8 )\n ~0.825\n > normal.logcdf( 0.8 )\n ~-0.193\n > normal.logpdf( 2.0 )\n ~-2.9\n > normal.mgf( 0.2 )\n ~0.803\n > normal.pdf( 2.0 )\n ~0.055\n > normal.quantile( 0.9 )\n ~1.845\n\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n ~0.054\n > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n ~0.009\n > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199\n\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p, μ, σ )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n ~0.842\n > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n 8.0\n > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n 8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ, σ )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.normal.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.skewness( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.normal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.normal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ, σ )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.normal.stdev( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.stdev( 4.0, 3.0 )\n 3.0\n > y = base.dists.normal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.normal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.normal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ, σ )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.normal.variance( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.variance( 4.0, 3.0 )\n 9.0\n > y = base.dists.normal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.normal.variance( 0.0, NaN )\n NaN\n > y = base.dists.normal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n 0.5\n > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n ~0.36\n > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n 0.75\n > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893\n\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α, β )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n ~2.473\n > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n ~2.349\n > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n ~-0.261\n\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α, β )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n ~70.8\n > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n ~146.444\n > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n ~19.725\n\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n ~-1.022\n > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n ~-0.288\n > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114\n\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n ~-2.773\n > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n ~-3.689\n > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n ~-1.561\n > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n ~-5.238\n > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079\n\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α, β )\n Returns the expected value of a Pareto (Type I) distribution.\n\n If `0 < α <= 1`, the function returns `Infinity`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.mean( 4.0, 12.0 )\n 16.0\n > v = base.dists.pareto1.mean( 8.0, 2.0 )\n ~2.286\n\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α, β )\n Returns the median of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.pareto1.median( 0.8, 1.0 )\n ~2.378\n > v = base.dists.pareto1.median( 4.0, 12.0 )\n ~14.27\n > v = base.dists.pareto1.median( 8.0, 2.0 )\n ~2.181\n\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α, β )\n Returns the mode of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n 1.0\n > v = base.dists.pareto1.mode( 4.0, 12.0 )\n 12.0\n > v = base.dists.pareto1.mode( 8.0, 2.0 )\n 2.0\n\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α, β] )\n Returns a Pareto (Type I) distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n pareto1: Object\n Distribution instance.\n\n pareto1.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n pareto1.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n pareto1.entropy: number\n Read-only property which returns the differential entropy.\n\n pareto1.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n pareto1.mean: number\n Read-only property which returns the expected value.\n\n pareto1.median: number\n Read-only property which returns the median.\n\n pareto1.mode: number\n Read-only property which returns the mode.\n\n pareto1.skewness: number\n Read-only property which returns the skewness.\n\n pareto1.variance: number\n Read-only property which returns the variance.\n\n pareto1.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n pareto1.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF).\n\n pareto1.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (logPDF).\n\n pareto1.pdf: Function\n Evaluates the probability density function (PDF).\n\n pareto1.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n > pareto1.alpha\n 6.0\n > pareto1.beta\n 5.0\n > pareto1.entropy\n ~0.984\n > pareto1.kurtosis\n ~35.667\n > pareto1.mean\n 6.0\n > pareto1.median\n ~5.612\n > pareto1.mode\n 5.0\n > pareto1.skewness\n ~3.81\n > pareto1.variance\n 1.5\n > pareto1.cdf( 7.0 )\n ~0.867\n > pareto1.logcdf( 7.0 )\n ~-0.142\n > pareto1.logpdf( 5.0 )\n ~0.182\n > pareto1.pdf( 5.0 )\n 1.2\n > pareto1.quantile( 0.8 )\n ~6.538\n\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n ~0.063\n > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n 0.025\n > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n ~0.21\n > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n ~0.005\n > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125\n\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p, α, β )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n ~2.236\n > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n ~50.0\n > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n ~11.111\n\n > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952\n\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α, β )\n Returns the skewness of a Pareto (Type I) distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n ~11.784\n > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n ~7.071\n > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n ~3.118\n\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α, β )\n Returns the standard deviation of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.pareto1.stdev( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.stdev( 4.0, 12.0 )\n ~5.657\n > v = base.dists.pareto1.stdev( 8.0, 2.0 )\n ~0.33\n\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α, β )\n Returns the variance of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.variance( 4.0, 12.0 )\n 32.0\n > v = base.dists.pareto1.variance( 8.0, 2.0 )\n ~0.109\n\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n ~0.986\n > y = base.dists.poisson.cdf( 2.0, 10.0 )\n ~0.003\n > y = base.dists.poisson.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.poisson.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.poisson.cdf( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.poisson.cdf( 10.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932\n\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ )\n Returns the entropy of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.poisson.entropy( 11.0 )\n ~2.61\n > v = base.dists.poisson.entropy( 4.5 )\n ~2.149\n\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ )\n Returns the excess kurtosis of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.poisson.kurtosis( 11.0 )\n ~0.091\n > v = base.dists.poisson.kurtosis( 4.5 )\n ~0.222\n\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x, λ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n ~-1.784\n > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n ~-1.901\n > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.logpmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n 0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0\n\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ )\n Returns the expected value of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.poisson.mean( 11.0 )\n 11.0\n > v = base.dists.poisson.mean( 4.5 )\n 4.5\n\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ )\n Returns the median of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.poisson.median( 11.0 )\n 11\n > v = base.dists.poisson.median( 4.5 )\n 4\n\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x, λ )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.poisson.mgf( 1.0, 1.5 )\n ~13.163\n > y = base.dists.poisson.mgf( 0.5, 0.5 )\n ~1.383\n > y = base.dists.poisson.mgf( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.mgf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.mgf( -2.0, -1.0 )\n NaN\n\n\nbase.dists.poisson.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n > var y = myMGF( 0.1 )\n ~1.234\n\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n > var y = myMGF( 0.1 )\n ~1.234","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ )\n Returns the mode of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.poisson.mode( 11.0 )\n 11\n > v = base.dists.poisson.mode( 4.5 )\n 4\n\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x, λ )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n ~0.168\n > y = base.dists.poisson.pmf( 1.0, 3.0 )\n ~0.149\n > y = base.dists.poisson.pmf( -1.0, 2.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.pmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.pmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.pmf( 2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368\n\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ] )\n Returns a Poisson distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n poisson: Object\n Distribution instance.\n\n poisson.lambda: number\n Mean parameter. If set, the value must be greater than `0`.\n\n poisson.entropy: number\n Read-only property which returns the differential entropy.\n\n poisson.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n poisson.mean: number\n Read-only property which returns the expected value.\n\n poisson.median: number\n Read-only property which returns the median.\n\n poisson.mode: number\n Read-only property which returns the mode.\n\n poisson.skewness: number\n Read-only property which returns the skewness.\n\n poisson.stdev: number\n Read-only property which returns the standard deviation.\n\n poisson.variance: number\n Read-only property which returns the variance.\n\n poisson.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n poisson.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n poisson.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n poisson.pmf: Function\n Evaluates the probability mass function (PMF).\n\n poisson.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var poisson = base.dists.poisson.Poisson( 6.0 );\n > poisson.lambda\n 6.0\n > poisson.entropy\n ~2.3\n > poisson.kurtosis\n ~0.167\n > poisson.mean\n 6.0\n > poisson.median\n 6.0\n > poisson.mode\n 6.0\n > poisson.skewness\n ~0.408\n > poisson.stdev\n ~2.449\n > poisson.variance\n 6.0\n > poisson.cdf( 4.0 )\n ~0.285\n > poisson.logpmf( 2.0 )\n ~-3.11\n > poisson.mgf( 0.5 )\n ~49.025\n > poisson.pmf( 2.0 )\n ~0.045\n > poisson.quantile( 0.5 )\n 6.0\n\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p, λ )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n 2\n > y = base.dists.poisson.quantile( 0.9, 4.0 )\n 7\n > y = base.dists.poisson.quantile( 0.1, 200.0 )\n 182\n\n > y = base.dists.poisson.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.poisson.quantile( -0.2, 0.0 )\n NaN\n\n > y = base.dists.poisson.quantile( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.quantile( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.quantile( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.quantile( 0.1, 0.0 )\n 0.0\n > y = base.dists.poisson.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ )\n Returns the skewness of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.poisson.skewness( 11.0 )\n ~0.302\n > v = base.dists.poisson.skewness( 4.5 )\n ~0.471\n\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ )\n Returns the standard deviation of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.poisson.stdev( 11.0 )\n ~3.317\n > v = base.dists.poisson.stdev( 4.5 )\n ~2.121\n\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ )\n Returns the variance of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.poisson.variance( 11.0 )\n 11.0\n > v = base.dists.poisson.variance( 4.5 )\n 4.5\n\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x, sigma )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n ~0.199\n > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n ~0.118\n > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.cdf( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n 1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393\n\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ )\n Returns the differential entropy of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.rayleigh.entropy( 11.0 )\n ~3.34\n > v = base.dists.rayleigh.entropy( 4.5 )\n ~2.446\n\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ )\n Returns the excess kurtosis of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.rayleigh.kurtosis( 11.0 )\n ~0.245\n > v = base.dists.rayleigh.kurtosis( 4.5 )\n ~0.245\n\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x, sigma )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n ~-1.613\n > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n ~-2.141\n > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933\n\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x, sigma )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n ~-1.249\n > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n ~-1.986\n > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886\n\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ )\n Returns the expected value of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mean( 11.0 )\n ~13.786\n > v = base.dists.rayleigh.mean( 4.5 )\n ~5.64\n\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ )\n Returns the median of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.rayleigh.median( 11.0 )\n ~12.952\n > v = base.dists.rayleigh.median( 4.5 )\n ~5.298\n\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t, sigma )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n ~678.508\n > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n ~38.65\n > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n ~-0.947\n > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.mgf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888\n\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ )\n Returns the mode of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mode( 11.0 )\n 11.0\n > v = base.dists.rayleigh.mode( 4.5 )\n 4.5\n\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x, sigma )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n ~0.287\n > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n ~0.137\n > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n Infinity\n > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n 0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152\n\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p, sigma )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative probability for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n ~1.794\n > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n ~4.71\n\n > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n NaN\n\n > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ] )\n Returns a Rayleigh distribution object.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n rayleigh: Object\n Distribution instance.\n\n rayleigh.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n rayleigh.entropy: number\n Read-only property which returns the differential entropy.\n\n rayleigh.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n rayleigh.mean: number\n Read-only property which returns the expected value.\n\n rayleigh.median: number\n Read-only property which returns the median.\n\n rayleigh.mode: number\n Read-only property which returns the mode.\n\n rayleigh.skewness: number\n Read-only property which returns the skewness.\n\n rayleigh.stdev: number\n Read-only property which returns the standard deviation.\n\n rayleigh.variance: number\n Read-only property which returns the variance.\n\n rayleigh.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n rayleigh.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n rayleigh.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n rayleigh.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n rayleigh.pdf: Function\n Evaluates the probability density function (PDF).\n\n rayleigh.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n > rayleigh.sigma\n 6.0\n > rayleigh.entropy\n ~2.734\n > rayleigh.kurtosis\n ~0.245\n > rayleigh.mean\n ~7.52\n > rayleigh.median\n ~7.064\n > rayleigh.mode\n 6.0\n > rayleigh.skewness\n ~0.631\n > rayleigh.stdev\n ~3.931\n > rayleigh.variance\n ~15.451\n > rayleigh.cdf( 1.0 )\n ~0.014\n > rayleigh.logcdf( 1.0 )\n ~-4.284\n > rayleigh.logpdf( 1.5 )\n ~-3.209\n > rayleigh.mgf( -0.5 )\n ~-0.91\n > rayleigh.pdf( 1.5 )\n ~0.04\n > rayleigh.quantile( 0.5 )\n ~7.064\n\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ )\n Returns the skewness of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.rayleigh.skewness( 11.0 )\n ~0.631\n > v = base.dists.rayleigh.skewness( 4.5 )\n ~0.631\n\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ )\n Returns the standard deviation of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.rayleigh.stdev( 9.0 )\n ~5.896\n > v = base.dists.rayleigh.stdev( 4.5 )\n ~2.948\n\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ )\n Returns the variance of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.rayleigh.variance( 9.0 )\n ~34.765\n > v = base.dists.rayleigh.variance( 4.5 )\n ~8.691\n\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x, n )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `x`, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.signrank.cdf( 3, 7 )\n ~0.039\n > y = base.dists.signrank.cdf( 1.8, 3 )\n ~0.375\n > y = base.dists.signrank.cdf( -1.0, 40 )\n 0.0\n > y = base.dists.signrank.cdf( NaN, 10 )\n NaN\n > y = base.dists.signrank.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.cdf.factory( n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.signrank.cdf.factory( 8 );\n > var y = myCDF( 5.7 )\n ~0.055\n > y = myCDF( 2.2 )\n ~0.012\n\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.signrank.cdf.factory( 8 );\n > var y = myCDF( 5.7 )\n ~0.055\n > y = myCDF( 2.2 )\n ~0.012","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x, n )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `x`, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.signrank.pdf( 3, 7 )\n ~0.0156\n > y = base.dists.signrank.pdf( 1.8, 3 )\n 0.0\n > y = base.dists.signrank.pdf( -1.0, 40 )\n 0.0\n > y = base.dists.signrank.pdf( NaN, 10 )\n NaN\n > y = base.dists.signrank.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.pdf.factory( n )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.signrank.pdf.factory( 8 );\n > var y = myPDF( 6.0 )\n ~0.0156\n > y = myPDF( 2.0 )\n ~0.0039\n\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.signrank.pdf.factory( 8 );\n > var y = myPDF( 6.0 )\n ~0.0156\n > y = myPDF( 2.0 )\n ~0.0039","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p, n )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.signrank.quantile( 0.8, 5 )\n 11\n > y = base.dists.signrank.quantile( 0.5, 4 )\n 5\n\n > y = base.dists.signrank.quantile( 1.1, 5 )\n NaN\n > y = base.dists.signrank.quantile( -0.2, 5 )\n NaN\n\n > y = base.dists.signrank.quantile( NaN, 5 )\n NaN\n > y = base.dists.signrank.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.quantile.factory( n )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n > var y = myQuantile( 0.4 )\n 16\n > y = myQuantile( 1.0 )\n 36\n\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n > var y = myQuantile( 0.4 )\n 16\n > y = myQuantile( 1.0 )\n 36","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x, r, v[, nranges] )\n Evaluates the cumulative distribution function (CDF) of a studentized range\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\n ~0.0644\n\n > y = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n ~0.913\n\n\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n\n Parameters\n ----------\n r: number\n Number of samples.\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n > var y = mycdf( 3.0 )\n ~0.712\n > y = mycdf( 1.0 )\n ~0.216\n\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n\n Parameters\n ----------\n r: number\n Number of samples.\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n > var y = mycdf( 3.0 )\n ~0.712\n > y = mycdf( 1.0 )\n ~0.216","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p, r, v[, nranges] )\n Evaluates the quantile function for a studentized range distribution.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = quantile( 0.5, 3.0, 2.0 )\n ~0.0644\n\n > y = quantile( 0.9, 17.0, 2.0 )\n ~0.913\n\n > y = quantile( 0.5, 3.0, 2.0, 2 )\n ~0.01\n\n > y = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\n NaN\n\n > y = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\n NaN\n > y = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\n NaN\n\n > y = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n NaN\n\n\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n\n Parameters\n ----------\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = quantile.factory( 3.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~1.791\n\n > y = myQuantile( 0.8 )\n ~3.245\n\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n\n Parameters\n ----------\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = quantile.factory( 3.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~1.791\n\n > y = myQuantile( 0.8 )\n ~3.245","base.dists.t.cdf":"\nbase.dists.t.cdf( x, v )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.t.cdf( 2.0, 0.1 )\n ~0.611\n > y = base.dists.t.cdf( 1.0, 2.0 )\n ~0.789\n > y = base.dists.t.cdf( -1.0, 4.0 )\n ~0.187\n > y = base.dists.t.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.cdf( 0.0, NaN )\n NaN\n > y = base.dists.t.cdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699\n\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699","base.dists.t.entropy":"\nbase.dists.t.entropy( v )\n Returns the differential entropy of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.t.entropy( 11.0 )\n ~1.512\n > v = base.dists.t.entropy( 4.5 )\n ~1.652\n\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v )\n Returns the excess kurtosis of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 2`, the function returns `NaN`.\n\n If provided `2 < v <= 4`, the function returns positive infinity.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.t.kurtosis( 11.0 )\n ~0.857\n > v = base.dists.t.kurtosis( 4.5 )\n 12.0\n\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x, v )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.t.logcdf( 2.0, 0.1 )\n ~-0.493\n > y = base.dists.t.logcdf( 1.0, 2.0 )\n ~-0.237\n > y = base.dists.t.logcdf( -1.0, 4.0 )\n ~-1.677\n > y = base.dists.t.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.logcdf( 0.0, NaN )\n NaN\n > y = base.dists.t.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.logcdf.factory( v )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.203\n > y = mylogcdf( 1.0 )\n ~-0.358\n\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.203\n > y = mylogcdf( 1.0 )\n ~-0.358","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x, v )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Student's t distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.t.logpdf( 0.3, 4.0 )\n ~-1.036\n > y = base.dists.t.logpdf( 2.0, 0.7 )\n ~-2.841\n > y = base.dists.t.logpdf( -1.0, 0.5 )\n ~-2.134\n > y = base.dists.t.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.t.logpdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.logpdf.factory( v )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n > var y = mylogPDF( 1.0 )\n ~-1.576\n\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n > var y = mylogPDF( 1.0 )\n ~-1.576","base.dists.t.mean":"\nbase.dists.t.mean( v )\n Returns the expected value of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.t.mean( 11.0 )\n 0.0\n > v = base.dists.t.mean( 4.5 )\n 0.0\n\n","base.dists.t.median":"\nbase.dists.t.median( v )\n Returns the median of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.t.median( 11.0 )\n 0.0\n > v = base.dists.t.median( 4.5 )\n 0.0\n\n","base.dists.t.mode":"\nbase.dists.t.mode( v )\n Returns the mode of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.t.mode( 11.0 )\n 0.0\n > v = base.dists.t.mode( 4.5 )\n 0.0\n\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x, v )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.t.pdf( 0.3, 4.0 )\n ~0.355\n > y = base.dists.t.pdf( 2.0, 0.7 )\n ~0.058\n > y = base.dists.t.pdf( -1.0, 0.5 )\n ~0.118\n > y = base.dists.t.pdf( 0.0, NaN )\n NaN\n > y = base.dists.t.pdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.pdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207\n\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207","base.dists.t.quantile":"\nbase.dists.t.quantile( p, v )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.t.quantile( 0.8, 1.0 )\n ~1.376\n > y = base.dists.t.quantile( 0.1, 1.0 )\n ~-3.078\n > y = base.dists.t.quantile( 0.5, 0.1 )\n 0.0\n\n > y = base.dists.t.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.t.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.t.quantile( 0.0, NaN )\n NaN\n\n > y = base.dists.t.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533\n\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533","base.dists.t.skewness":"\nbase.dists.t.skewness( v )\n Returns the skewness of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 3`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.t.skewness( 11.0 )\n 0.0\n > v = base.dists.t.skewness( 4.5 )\n 0.0\n\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v )\n Returns the standard deviation of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.t.stdev( 9.0 )\n ~1.134\n > v = base.dists.t.stdev( 4.5 )\n ~1.342\n\n","base.dists.t.T":"\nbase.dists.t.T( [v] )\n Returns a Student's t distribution object.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n t: Object\n Distribution instance.\n\n t.v: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n t.entropy: number\n Read-only property which returns the differential entropy.\n\n t.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n t.mean: number\n Read-only property which returns the expected value.\n\n t.median: number\n Read-only property which returns the median.\n\n t.mode: number\n Read-only property which returns the mode.\n\n t.skewness: number\n Read-only property which returns the skewness.\n\n t.stdev: number\n Read-only property which returns the standard deviation.\n\n t.variance: number\n Read-only property which returns the variance.\n\n t.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n t.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n t.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n t.pdf: Function\n Evaluates the probability density function (PDF).\n\n t.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var t = base.dists.t.T( 6.0 );\n > t.v\n 6.0\n > t.entropy\n ~1.592\n > t.kurtosis\n 3.0\n > t.mean\n 0.0\n > t.median\n 0.0\n > t.mode\n 0.0\n > t.skewness\n 0.0\n > t.stdev\n ~1.225\n > t.variance\n 1.5\n > t.cdf( 1.0 )\n ~0.822\n > t.logcdf( 1.0 )\n ~-0.196\n > t.logpdf( 1.5 )\n ~-2.075\n > t.pdf( 1.5 )\n ~0.126\n > t.quantile( 0.8 )\n ~0.906\n\n","base.dists.t.variance":"\nbase.dists.t.variance( v )\n Returns the variance of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.t.variance( 9.0 )\n ~1.286\n > v = base.dists.t.variance( 4.5 )\n ~1.8\n\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x, a, b, c )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n 0.875\n > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n 0.75\n > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.278\n > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95\n\n\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a, b, c )\n Returns the differential entropy of a triangular distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n ~-0.193\n > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n ~1.886\n > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n ~1.599\n\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a, b, c )\n Returns the excess kurtosis of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n -0.6\n > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n -0.6\n > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n -0.6\n\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x, a, b, c )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.134\n > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n ~-0.288\n > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n ~-1.281\n > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051\n\n\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x, a, b, c )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.693\n > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n 0.0\n > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n ~-2.89\n > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity\n\n\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a, b, c )\n Returns the expected value of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n ~0.6\n > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n 7.0\n > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a, b, c )\n Returns the median of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n ~0.632\n > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n ~6.708\n > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t, a, b, c )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n ~1.021\n > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n ~1.111\n > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n ~24.334\n > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n ~1.381\n > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205\n\n\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a, b, c )\n Returns the mode of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n 0.8\n > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n 5.0\n > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x, a, b, c )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n 0.5\n > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n 1.0\n > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.056\n > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0\n\n\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p, a, b, c )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n ~0.553\n > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n ~-0.452\n > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n -14.0\n > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n ~11.056\n\n > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n NaN\n\n > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n NaN\n\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225\n\n\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a, b, c )\n Returns the skewness of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n ~-0.476\n > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n ~0.532\n > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n 0.0\n\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a, b, c )\n Returns the standard deviation of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n ~0.216\n > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n ~1.78\n > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n ~1.225\n\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a, b, c] )\n Returns a triangular distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n c: number (optional)\n Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n Returns\n -------\n triangular: Object\n Distribution instance.\n\n triangular.a: number\n Minimum support. If set, the value must be smaller or equal to `b` and\n `c`.\n\n triangular.b: number\n Maximum support. If set, the value must be greater than or equal to `a`\n and `c`.\n\n triangular.c: number\n Mode. If set, the value must be greater than or equal to `a` and smaller\n than or equal to `b`.\n\n triangular.entropy: number\n Read-only property which returns the differential entropy.\n\n triangular.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n triangular.mean: number\n Read-only property which returns the expected value.\n\n triangular.median: number\n Read-only property which returns the median.\n\n triangular.mode: number\n Read-only property which returns the mode.\n\n triangular.skewness: number\n Read-only property which returns the skewness.\n\n triangular.stdev: number\n Read-only property which returns the standard deviation.\n\n triangular.variance: number\n Read-only property which returns the variance.\n\n triangular.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n triangular.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n triangular.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n triangular.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n triangular.pdf: Function\n Evaluates the probability density function (PDF).\n\n triangular.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n > triangular.a\n 0.0\n > triangular.b\n 1.0\n > triangular.c\n 0.5\n > triangular.entropy\n ~-0.193\n > triangular.kurtosis\n -0.6\n > triangular.mean\n 0.5\n > triangular.median\n 0.5\n > triangular.mode\n 0.5\n > triangular.skewness\n 0.0\n > triangular.stdev\n ~0.204\n > triangular.variance\n ~0.042\n > triangular.cdf( 0.8 )\n 0.92\n > triangular.logcdf( 0.8 )\n ~-0.083\n > triangular.logpdf( 0.8 )\n ~-0.223\n > triangular.mgf( 0.8 )\n ~1.512\n > triangular.pdf( 0.8 )\n ~0.8\n > triangular.quantile( 0.8 )\n ~0.684\n\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a, b, c )\n Returns the variance of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n ~0.047\n > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n ~3.167\n > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n ~1.5\n\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n 0.9\n > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n 0.25\n > y = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8\n\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a, b )\n Returns the differential entropy of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.entropy( 4.0, 12.0 )\n ~2.079\n > v = base.dists.uniform.entropy( 2.0, 8.0 )\n ~1.792\n\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a, b )\n Returns the excess kurtosis of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n -1.2\n\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n ~-0.105\n > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n ~-1.386\n > y = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223\n\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n ~-1.386\n > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n -infinity\n > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n 0.0\n > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity\n\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a, b )\n Returns the expected value of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.uniform.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a, b )\n Returns the median of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.uniform.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n ~372.495\n > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n ~0.688\n > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n ~3.195\n > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n NaN\n > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321\n\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x, a, b )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n 0.25\n > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n 1.0\n > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p, a, b )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n 0.8\n > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n 5.0\n\n > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2\n\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a, b )\n Returns the skewness of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.uniform.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a, b )\n Returns the standard deviation of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n ~0.289\n > v = base.dists.uniform.stdev( 4.0, 12.0 )\n ~2.309\n > v = base.dists.uniform.stdev( 2.0, 8.0 )\n ~1.732\n\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a, b] )\n Returns a uniform distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n uniform: Object\n Distribution instance.\n\n uniform.a: number\n Minimum support. If set, the value must be smaller than `b`.\n\n uniform.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n uniform.entropy: number\n Read-only property which returns the differential entropy.\n\n uniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n uniform.mean: number\n Read-only property which returns the expected value.\n\n uniform.median: number\n Read-only property which returns the median.\n\n uniform.skewness: number\n Read-only property which returns the skewness.\n\n uniform.stdev: number\n Read-only property which returns the standard deviation.\n\n uniform.variance: number\n Read-only property which returns the variance.\n\n uniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n uniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n uniform.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n uniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n uniform.pdf: Function\n Evaluates the probability density function (PDF).\n\n uniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n > uniform.a\n 0.0\n > uniform.b\n 1.0\n > uniform.entropy\n 0.0\n > uniform.kurtosis\n -1.2\n > uniform.mean\n 0.5\n > uniform.median\n 0.5\n > uniform.skewness\n 0.0\n > uniform.stdev\n ~0.289\n > uniform.variance\n ~0.083\n > uniform.cdf( 0.8 )\n 0.8\n > uniform.logcdf( 0.5 )\n ~-0.693\n > uniform.logpdf( 1.0 )\n ~-0.0\n > uniform.mgf( 0.8 )\n ~1.532\n > uniform.pdf( 0.8 )\n 1.0\n > uniform.quantile( 0.8 )\n 0.8\n\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a, b )\n Returns the variance of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.uniform.variance( 0.0, 1.0 )\n ~0.083\n > v = base.dists.uniform.variance( 4.0, 12.0 )\n ~5.333\n > v = base.dists.uniform.variance( 2.0, 8.0 )\n 3.0\n\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763\n\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k, λ )\n Returns the differential entropy of a Weibull distribution (in nats).\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.entropy( 4.0, 12.0 )\n ~2.532\n > v = base.dists.weibull.entropy( 8.0, 2.0 )\n ~0.119\n\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k, λ )\n Returns the excess kurtosis of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n ~-0.252\n > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n ~0.328\n\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x, k, λ )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n ~-0.145\n > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27\n\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x, k, λ )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n ~-3.307\n > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863\n\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k, λ )\n Returns the expected value of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.weibull.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.mean( 4.0, 12.0 )\n ~10.877\n > v = base.dists.weibull.mean( 8.0, 2.0 )\n ~1.883\n\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k, λ )\n Returns the median of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.weibull.median( 1.0, 1.0 )\n ~0.693\n > v = base.dists.weibull.median( 4.0, 12.0 )\n ~10.949\n > v = base.dists.weibull.median( 8.0, 2.0 )\n ~1.91\n\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x, k, λ )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n ~2.0\n > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n ~0.019\n\n > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137\n\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k, λ )\n Returns the mode of a Weibull distribution.\n\n If `0 < k <= 1`, the function returns `0.0`.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.weibull.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.weibull.mode( 4.0, 12.0 )\n ~11.167\n > v = base.dists.weibull.mode( 8.0, 2.0 )\n ~1.967\n\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n ~0.037\n > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155\n\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p, k, λ )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n ~1.609\n > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n ~3.33\n\n > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147\n\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k, λ )\n Returns the skewness of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.weibull.skewness( 4.0, 12.0 )\n ~-0.087\n > v = base.dists.weibull.skewness( 8.0, 2.0 )\n ~-0.534\n\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k, λ )\n Returns the standard deviation of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.stdev( 4.0, 12.0 )\n ~3.051\n > v = base.dists.weibull.stdev( 8.0, 2.0 )\n ~0.279\n\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k, λ )\n Returns the variance of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.weibull.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.variance( 4.0, 12.0 )\n ~9.311\n > v = base.dists.weibull.variance( 8.0, 2.0 )\n ~0.078\n\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k, λ] )\n Returns a Weibull distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n λ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n weibull: Object\n Distribution instance.\n\n weibull.k: number\n Shape parameter. If set, the value must be greater than `0`.\n\n weibull.lambda: number\n Scale parameter. If set, the value must be greater than `0`.\n\n weibull.entropy: number\n Read-only property which returns the differential entropy.\n\n weibull.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n weibull.mean: number\n Read-only property which returns the expected value.\n\n weibull.median: number\n Read-only property which returns the median.\n\n weibull.mode: number\n Read-only property which returns the mode.\n\n weibull.skewness: number\n Read-only property which returns the skewness.\n\n weibull.stdev: number\n Read-only property which returns the standard deviation.\n\n weibull.variance: number\n Read-only property which returns the variance.\n\n weibull.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n weibull.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n weibull.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n weibull.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n weibull.pdf: Function\n Evaluates the probability density function (PDF).\n\n weibull.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n > weibull.k\n 6.0\n > weibull.lambda\n 5.0\n > weibull.entropy\n ~1.299\n > weibull.kurtosis\n ~0.035\n > weibull.mean\n ~4.639\n > weibull.median\n ~4.704\n > weibull.mode\n ~4.85\n > weibull.skewness\n ~-0.373\n > weibull.stdev\n ~0.899\n > weibull.variance\n ~0.808\n > weibull.cdf( 3.0 )\n ~0.046\n > weibull.logcdf( 3.0 )\n ~-3.088\n > weibull.logpdf( 1.0 )\n ~-7.865\n > weibull.mgf( -0.5 )\n ~0.075\n > weibull.pdf( 3.0 )\n ~0.089\n > weibull.quantile( 0.8 )\n ~5.413\n\n","base.ellipe":"\nbase.ellipe( m )\n Computes the complete elliptic integral of the second kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipe( 0.5 )\n ~1.351\n > y = base.ellipe( -1.0 )\n ~1.910\n > y = base.ellipe( 2.0 )\n NaN\n > y = base.ellipe( PINF )\n NaN\n > y = base.ellipe( NINF )\n NaN\n > y = base.ellipe( NaN )\n NaN\n\n See Also\n --------\n base.ellipj, base.ellipk\n","base.ellipj":"\nbase.ellipj( u, m )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: Array\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var v = base.ellipj( 0.3, 0.5 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > v = base.ellipj( 0.0, 0.0 )\n [ ~0.0, ~1.0, ~1.0, ~0.0 ]\n > v = base.ellipj( Infinity, 1.0 )\n [ ~1.0, ~0.0, ~0.0, ~1.571 ]\n > v = base.ellipj( 0.0, -2.0)\n [ ~0.0, ~1.0, ~1.0, NaN ]\n > v = base.ellipj( NaN, NaN )\n [ NaN, NaN, NaN, NaN ]\n\n\nbase.ellipj.assign( u, m, out, stride, offset )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var out = new Float64Array( 4 );\n > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > var bool = ( v === out )\n true\n\n\nbase.ellipj.sn( u, m )\n Computes the Jacobi elliptic function sn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function sn.\n\n Examples\n --------\n > var v = base.ellipj.sn( 0.3, 0.5 )\n ~0.293\n\n\nbase.ellipj.cn( u, m )\n Computes the Jacobi elliptic functions cn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function cn.\n\n Examples\n --------\n > var v = base.ellipj.cn( 0.3, 0.5 )\n ~0.956\n\n\nbase.ellipj.dn( u, m )\n Computes the Jacobi elliptic function dn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function dn.\n\n Examples\n --------\n > var v = base.ellipj.dn( 0.3, 0.5 )\n ~0.978\n\n\nbase.ellipj.am( u, m )\n Computes the Jacobi amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function am.\n\n Examples\n --------\n > var v = base.ellipj.am( 0.3, 0.5 )\n ~0.298\n\n See Also\n --------\n base.ellipe, base.ellipk","base.ellipj.assign":"\nbase.ellipj.assign( u, m, out, stride, offset )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var out = new Float64Array( 4 );\n > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > var bool = ( v === out )\n true","base.ellipj.sn":"\nbase.ellipj.sn( u, m )\n Computes the Jacobi elliptic function sn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function sn.\n\n Examples\n --------\n > var v = base.ellipj.sn( 0.3, 0.5 )\n ~0.293","base.ellipj.cn":"\nbase.ellipj.cn( u, m )\n Computes the Jacobi elliptic functions cn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function cn.\n\n Examples\n --------\n > var v = base.ellipj.cn( 0.3, 0.5 )\n ~0.956","base.ellipj.dn":"\nbase.ellipj.dn( u, m )\n Computes the Jacobi elliptic function dn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function dn.\n\n Examples\n --------\n > var v = base.ellipj.dn( 0.3, 0.5 )\n ~0.978","base.ellipj.am":"\nbase.ellipj.am( u, m )\n Computes the Jacobi amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function am.\n\n Examples\n --------\n > var v = base.ellipj.am( 0.3, 0.5 )\n ~0.298\n\n See Also\n --------\n base.ellipe, base.ellipk","base.ellipk":"\nbase.ellipk( m )\n Computes the complete elliptic integral of the first kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipk( 0.5 )\n ~1.854\n > y = base.ellipk( -1.0 )\n ~1.311\n > y = base.ellipk( 2.0 )\n NaN\n > y = base.ellipk( PINF )\n NaN\n > y = base.ellipk( NINF )\n NaN\n > y = base.ellipk( NaN )\n NaN\n\n See Also\n --------\n base.ellipe, base.ellipj\n","base.endsWith":"\nbase.endsWith( str, search, len )\n Tests if a string ends with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, and is thus\n equivalent to `str.length + len`. Default: str.length.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string ends with the characters of another\n string.\n\n Examples\n --------\n > var bool = base.endsWith( 'beep', 'ep', 4 )\n true\n > bool = base.endsWith( 'Beep', 'op', 4 )\n false\n > bool = base.endsWith( 'Beep', 'ee', 3 )\n true\n > bool = base.endsWith( 'Beep', 'ee', -1 )\n true\n > bool = base.endsWith( 'beep', '', 4 )\n true\n\n See Also\n --------\n base.startsWith\n","base.epsdiff":"\nbase.epsdiff( x, y[, scale] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If computing the relative difference in units of epsilon will result in\n overflow, the function returns the maximum double-precision floating-point\n number.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference in units of double-precision floating-point epsilon.\n\n Examples\n --------\n > var d = base.epsdiff( 12.15, 12.149999999999999 )\n ~0.658\n > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n ~64761.512\n\n // Custom scale function:\n > function scale( x, y ) { return ( x > y ) ? y : x; };\n > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n ~44\n\n See Also\n --------\n base.absdiff, base.reldiff\n","base.erf":"\nbase.erf( x )\n Evaluates the error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erf( 2.0 )\n ~0.9953\n > y = base.erf( -1.0 )\n ~-0.8427\n > y = base.erf( -0.0 )\n -0.0\n > y = base.erf( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfinv, base.erfcinv\n","base.erfc":"\nbase.erfc( x )\n Evaluates the complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfc( 2.0 )\n ~0.0047\n > y = base.erfc( -1.0 )\n ~1.8427\n > y = base.erfc( 0.0 )\n 1.0\n > y = base.erfc( PINF )\n 0.0\n > y = base.erfc( NINF )\n 2.0\n > y = base.erfc( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfinv, base.erfcinv, base.erfcx\n","base.erfcinv":"\nbase.erfcinv( x )\n Evaluates the inverse complementary error function.\n\n The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcinv( 0.5 )\n ~0.4769\n > y = base.erfcinv( 0.8 )\n ~0.1791\n > y = base.erfcinv( 0.0 )\n Infinity\n > y = base.erfcinv( 2.0 )\n -Infinity\n > y = base.erfcinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfinv, base.erfcx\n","base.erfcx":"\nbase.erfcx( x )\n Evaluates the scaled complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcx( 1.0 )\n ~0.4276\n > y = base.erfcx( -1.0 )\n ~5.01\n > y = base.erfcx( 0.0 )\n 1.0\n > y = base.erfcx( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfcinv, base.erf, base.erfinv","base.erfinv":"\nbase.erfinv( x )\n Evaluates the inverse error function.\n\n If `|x| > 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfinv( 0.5 )\n ~0.4769\n > y = base.erfinv( 0.8 )\n ~0.9062\n > y = base.erfinv( 0.0 )\n 0.0\n > y = base.erfinv( -0.0 )\n -0.0\n > y = base.erfinv( -1.0 )\n -Infinity\n > y = base.erfinv( 1.0 )\n Infinity\n > y = base.erfinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfcinv\n","base.eta":"\nbase.eta( s )\n Evaluates the Dirichlet eta function for a double-precision\n floating-point number `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.eta( 0.0 )\n 0.5\n > y = base.eta( -1.0 )\n 0.25\n > y = base.eta( 1.0 )\n ~0.6931\n > y = base.eta( 3.14 )\n ~0.9096\n > y = base.eta( NaN )\n NaN\n\n","base.evalpoly":"\nbase.evalpoly( c, x )\n Evaluates a polynomial using double-precision floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n out: number\n Evaluated polynomial.\n\n Examples\n --------\n > var arr = [ 3.0, 2.0, 1.0 ];\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = base.evalpoly( arr, 10.0 )\n 123.0\n\n\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = f( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = f( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = f( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = f( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational","base.evalrational":"\nbase.evalrational( P, Q, x )\n Evaluates a rational function using double-precision floating-point\n arithmetic.\n\n A rational function `f(x)` is defined as\n\n P(x)\n f(x) = ----\n Q(x)\n\n where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n For polynomials of different degree, the coefficient array for the lower\n degree polynomial should be padded with zeros.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the rational function.\n\n Returns\n -------\n out: number\n Evaluated rational function.\n\n Examples\n --------\n // 2x^3 + 4x^2 - 5x^1 - 6x^0\n > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n // 0.5x^1 + 3x^0\n > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n // Evaluate the rational function:\n > var v = base.evalrational( P, Q, 6.0 )\n 90.0\n\n\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var f = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = f( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = f( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly\n","base.evalrational.factory":"\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var f = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = f( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = f( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly","base.exp":"\nbase.exp( x )\n Evaluates the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp( 4.0 )\n ~54.5982\n > y = base.exp( -9.0 )\n ~1.234e-4\n > y = base.exp( 0.0 )\n 1.0\n > y = base.exp( NaN )\n NaN\n\n See Also\n --------\n base.exp10, base.exp2, base.expm1, base.ln\n","base.exp2":"\nbase.exp2( x )\n Evaluates the base 2 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp2( 3.0 )\n 8.0\n > y = base.exp2( -9.0 )\n ~0.002\n > y = base.exp2( 0.0 )\n 1.0\n > y = base.exp2( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp10, base.log2\n","base.exp10":"\nbase.exp10( x )\n Evaluates the base 10 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp10( 3.0 )\n 1000\n > y = base.exp10( -9.0 )\n 1.0e-9\n > y = base.exp10( 0.0 )\n 1.0\n > y = base.exp10( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp2, base.log10\n","base.expit":"\nbase.expit( x )\n Evaluates the standard logistic function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expit( 0.0 )\n 0.5\n > y = base.expit( 1.0 )\n ~0.731\n > y = base.expit( -1.0 )\n ~0.269\n > y = base.expit( Infinity )\n 1.0\n > y = base.expit( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.logit","base.expm1":"\nbase.expm1( x )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1( 0.2 )\n ~0.221\n > y = base.expm1( -9.0 )\n ~-1.0\n > y = base.expm1( 0.0 )\n 0.0\n > y = base.expm1( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.expm1rel\n","base.expm1rel":"\nbase.expm1rel( x )\n Relative error exponential.\n\n When `x` is near zero,\n\n e^x - 1\n\n can suffer catastrophic cancellation (i.e., significant loss of precision).\n This function avoids the loss of precision when `x` is near zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1rel( 0.0 )\n 1.0\n > y = base.expm1rel( 1.0 )\n ~1.718\n > y = base.expm1rel( -1.0 )\n ~0.632\n > y = base.expm1rel( NaN )\n NaN\n\t\n See Also\n --------\n base.exp, base.expm1\n","base.exponent":"\nbase.exponent( x )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponent( 3.14e-307 )\n -1019\n > exponent = base.exponent( -3.14 )\n 1\n > exponent = base.exponent( 0.0 )\n -1023\n > exponent = base.exponent( NaN )\n 1024\n\n See Also\n --------\n base.exponentf\n","base.exponentf":"\nbase.exponentf( x )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\n 114\n > exponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\n -112\n > exponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\n 1\n > exponent = base.exponentf( 0.0 )\n -127\n > exponent = base.exponentf( NaN )\n 128\n\n See Also\n --------\n base.exponent\n","base.factorial":"\nbase.factorial( x )\n Evaluates the factorial of `x`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Factorial.\n\n Examples\n --------\n > var y = base.factorial( 3.0 )\n 6.0\n > y = base.factorial( -1.5 )\n ~-3.545\n > y = base.factorial( -0.5 )\n ~1.772\n > y = base.factorial( 0.5 )\n ~0.886\n > y = base.factorial( -10.0 )\n NaN\n > y = base.factorial( 171.0 )\n Infinity\n > y = base.factorial( NaN )\n NaN\n\n See Also\n --------\n base.factorialln\n","base.factorial2":"\nbase.factorial2( n )\n Evaluates the double factorial of `n`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: number\n Input value.\n\n Returns\n -------\n y: number\n Double factorial.\n\n Examples\n --------\n > var y = base.factorial2( 3 )\n 3\n > y = base.factorial2( 5 )\n 15\n > y = base.factorial2( 6 )\n 48\n > y = base.factorial2( 301 )\n Infinity\n > y = base.factorial2( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.factorialln":"\nbase.factorialln( x )\n Evaluates the natural logarithm of the factorial of `x`.\n\n For input values other than negative integers, the function returns\n\n ln( x! ) = ln( Γ(x+1) )\n\n where `Γ` is the Gamma function. For negative integers, the function returns\n `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the factorial of `x`.\n\n Examples\n --------\n > var y = base.factorialln( 3.0 )\n ~1.792\n > y = base.factorialln( 2.4 )\n ~1.092\n > y = base.factorialln( -1.0 )\n NaN\n > y = base.factorialln( -1.5 )\n ~1.266\n > y = base.factorialln( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.fallingFactorial":"\nbase.fallingFactorial( x, n )\n Computes the falling factorial of `x` and `n`.\n\n If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.fallingFactorial( 0.9, 5 )\n ~0.644\n > v = base.fallingFactorial( -9.0, 3 )\n -990.0\n > v = base.fallingFactorial( 0.0, 2 )\n 0.0\n > v = base.fallingFactorial( 3.0, -2 )\n NaN\n\n See Also\n --------\n base.risingFactorial\n","base.fibonacci":"\nbase.fibonacci( n )\n Computes the nth Fibonacci number.\n\n Fibonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2}\n\n with seed values F_0 = 0 and F_1 = 1.\n\n If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Fibonacci number.\n\n Examples\n --------\n > var y = base.fibonacci( 0 )\n 0\n > y = base.fibonacci( 1 )\n 1\n > y = base.fibonacci( 2 )\n 1\n > y = base.fibonacci( 3 )\n 2\n > y = base.fibonacci( 4 )\n 3\n > y = base.fibonacci( 79 )\n NaN\n > y = base.fibonacci( NaN )\n NaN\n\n See Also\n --------\n base.binet, base.fibonacciIndex, base.lucas, base.negafibonacci\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F )\n Computes the Fibonacci number index.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n F: integer\n Fibonacci number.\n\n Returns\n -------\n n: number\n Fibonacci number index.\n\n Examples\n --------\n > var n = base.fibonacciIndex( 2 )\n 3\n > n = base.fibonacciIndex( 3 )\n 4\n > n = base.fibonacciIndex( 5 )\n 5\n > n = base.fibonacciIndex( NaN )\n NaN\n > n = base.fibonacciIndex( 1 )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.fibpoly":"\nbase.fibpoly( n, x )\n Evaluates a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Fibonacci polynomial.\n\n Returns\n -------\n out: number\n Evaluated Fibonacci polynomial.\n\n Examples\n --------\n // 2^4 + 3*2^2 + 1\n > var v = base.fibpoly( 5, 2.0 )\n 29.0\n\n\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly","base.firstCodePoint":"\nbase.firstCodePoint( str, n )\n Returns the first `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstCodePoint( 'beep', 1 )\n 'b'\n > out = base.firstCodePoint( 'Boop', 1 )\n 'B'\n > out = base.firstCodePoint( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodeUnit, base.firstGraphemeCluster, base.lastCodePoint, base.removeFirstCodePoint, firstChar\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str, n )\n Returns the first `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstCodeUnit( 'beep', 1 )\n 'b'\n > out = base.firstCodeUnit( 'Boop', 1 )\n 'B'\n > out = base.firstCodeUnit( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodePoint, base.firstGraphemeCluster, base.last, base.removeFirst, firstChar\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str, n )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstGraphemeCluster( 'beep', 1 )\n 'b'\n > out = base.firstGraphemeCluster( 'Boop', 1 )\n 'B'\n > out = base.firstGraphemeCluster( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodeUnit, base.firstCodePoint, base.lastGraphemeCluster, base.removeFirstGraphemeCluster, firstChar\n","base.flipsign":"\nbase.flipsign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n or `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`; otherwise, behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsign( -3.0, 10.0 )\n -3.0\n > z = base.flipsign( -3.0, -1.0 )\n 3.0\n > z = base.flipsign( 1.0, -0.0 )\n -1.0\n > z = base.flipsign( -3.0, -0.0 )\n 3.0\n > z = base.flipsign( -0.0, 1.0 )\n -0.0\n > z = base.flipsign( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysign\n","base.flipsignf":"\nbase.flipsignf( x, y )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `255`, a significand greater than `0`, and a sign bit equal to either `1` or\n `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`; otherwise, behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Single-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsignf( -3.0, 10.0 )\n -3.0\n > z = base.flipsignf( -3.0, -1.0 )\n 3.0\n > z = base.flipsignf( 1.0, -0.0 )\n -1.0\n > z = base.flipsignf( -3.0, -0.0 )\n 3.0\n > z = base.flipsignf( -0.0, 1.0 )\n -0.0\n > z = base.flipsignf( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysignf, base.flipsign\n","base.float32ToInt32":"\nbase.float32ToInt32( x )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\n 0\n > y = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\n -3\n > y = base.float32ToInt32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToInt32( FLOAT32_PINF )\n 0\n > y = base.float32ToInt32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToUint32","base.float32ToUint32":"\nbase.float32ToUint32( x )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\n 0\n > y = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\n 4294967293\n > y = base.float32ToUint32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToUint32( FLOAT32_PINF )\n 0\n > y = base.float32ToUint32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToInt32","base.float64ToFloat32":"\nbase.float64ToFloat32( x )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: float\n Nearest single-precision floating-point number.\n\n Examples\n --------\n > var y = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n","base.float64ToInt32":"\nbase.float64ToInt32( x )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToInt32( 4294967295.0 )\n -1\n > y = base.float64ToInt32( 3.14 )\n 3\n > y = base.float64ToInt32( -3.14 )\n -3\n > y = base.float64ToInt32( NaN )\n 0\n > y = base.float64ToInt32( PINF )\n 0\n > y = base.float64ToInt32( NINF )\n 0\n\n See Also\n --------\n base.float64ToUint32","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n Returns\n -------\n out: Uint8Array\n Byte array.\n\n Examples\n --------\n > var y = base.float64ToInt64Bytes( 4294967297.0 )\n \n\n\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Uint8Array( 16 );\n > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n \n\n See Also\n --------\n base.float64ToInt32","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Uint8Array( 16 );\n > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n \n\n See Also\n --------\n base.float64ToInt32","base.float64ToUint32":"\nbase.float64ToUint32( x )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToUint32( 4294967297.0 )\n 1\n > y = base.float64ToUint32( 3.14 )\n 3\n > y = base.float64ToUint32( -3.14 )\n 4294967293\n > y = base.float64ToUint32( NaN )\n 0\n > y = base.float64ToUint32( PINF )\n 0\n > y = base.float64ToUint32( NINF )\n 0\n\n See Also\n --------\n base.float64ToInt32","base.floor":"\nbase.floor( x )\n Rounds a double-precision floating-point number toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor( 3.14 )\n 3.0\n > y = base.floor( -4.2 )\n -5.0\n > y = base.floor( -4.6 )\n -5.0\n > y = base.floor( 9.5 )\n 9.0\n > y = base.floor( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.round\n","base.floor2":"\nbase.floor2( x )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor2( 3.14 )\n 2.0\n > y = base.floor2( -4.2 )\n -8.0\n > y = base.floor2( -4.6 )\n -8.0\n > y = base.floor2( 9.5 )\n 8.0\n > y = base.floor2( 13.0 )\n 8.0\n > y = base.floor2( -13.0 )\n -16.0\n > y = base.floor2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor, base.floor10, base.round2\n","base.floor10":"\nbase.floor10( x )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor10( 3.14 )\n 1.0\n > y = base.floor10( -4.2 )\n -10.0\n > y = base.floor10( -4.6 )\n -10.0\n > y = base.floor10( 9.5 )\n 1.0\n > y = base.floor10( 13.0 )\n 10.0\n > y = base.floor10( -13.0 )\n -100.0\n > y = base.floor10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor, base.floor2, base.round10\n","base.floorb":"\nbase.floorb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.floorb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward negative infinity:\n > y = base.floorb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floor, base.floorn, base.roundb\n","base.floorf":"\nbase.floorf( x )\n Rounds a single-precision floating-point number toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorf( 3.14 )\n 3.0\n > y = base.floorf( -4.2 )\n -5.0\n > y = base.floorf( -4.6 )\n -5.0\n > y = base.floorf( 9.5 )\n 9.0\n > y = base.floorf( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceilf, base.floor\n","base.floorn":"\nbase.floorn( x, n )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round toward negative infinity behavior:\n > y = base.floorn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.floorn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floor, base.floorb, base.roundn\n","base.floorsd":"\nbase.floorsd( x, n, b )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorsd( 3.14159, 5, 10 )\n 3.1415\n > y = base.floorsd( 3.14159, 1, 10 )\n 3.0\n > y = base.floorsd( 12368.0, 2, 10 )\n 12000.0\n > y = base.floorsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floor, base.roundsd, base.truncsd\n","base.forEachChar":"\nbase.forEachChar( str, clbk[, thisArg] )\n Invokes a function for each UTF-16 code unit in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each UTF-16 code unit in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachChar( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachCodePoint, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str, clbk[, thisArg] )\n Invokes a function for each Unicode code point in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: code point.\n - index: starting code point index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each Unicode code point in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachCodePoint( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str, clbk[, thisArg] )\n Invokes a function for each Unicode code point in a string, iterating from\n right to left.\n\n When invoked, the provided function is provided three arguments:\n\n - value: code point.\n - index: starting code point index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each Unicode code point in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachCodePointRight( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachCodePoint, base.forEachRight\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str, clbk[, thisArg] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: grapheme cluster.\n - index: starting grapheme cluster index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each grapheme cluster in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachGraphemeCluster( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachCodePoint, forEachChar\n","base.forEachRight":"\nbase.forEachRight( str, clbk[, thisArg] )\n Invokes a function for each UTF-16 code unit in a string, iterating from\n right to left.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n Function to invoke for each UTF-16 code unit in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachRight( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachCodePointRight\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens, ...args )\n Generate string from a token array by interpolating values.\n\n Parameters\n ----------\n tokens: Array\n Array of string parts and format identifier objects.\n\n args: ...any\n Variable values.\n\n Returns\n -------\n out: string\n Formatted string.\n\n Examples\n --------\n > var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\n 'beep boop'\n > out = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\n 'baz 1.00'\n > out = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n ' 12'\n\n See Also\n --------\n base.formatTokenize\n","base.formatTokenize":"\nbase.formatTokenize( str )\n Tokenize a string into an array of string parts and format identifier\n objects.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: Array\n Array of string parts and format identifier objects.\n\n Examples\n --------\n > var out = base.formatTokenize( 'Hello %s!' )\n [ 'Hello ', {...}, '!' ]\n > out = base.formatTokenize( '%s %s %d' )\n [ {...}, ' ', {...}, ' ', {...}, ' ' ]\n > out = base.formatTokenize( 'Pi: %.2f' )\n [ 'Pi: ', {...} ]\n\n See Also\n --------\n base.formatInterpolate\n","base.fresnel":"\nbase.fresnel( x )\n Computes the Fresnel integrals S(x) and C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: Array\n S(x) and C(x).\n\n Examples\n --------\n > var y = base.fresnel( 0.0 )\n [ ~0.0, ~0.0 ]\n > y = base.fresnel( 1.0 )\n [ ~0.438, ~0.780 ]\n > y = base.fresnel( PINF )\n [ ~0.5, ~0.5 ]\n > y = base.fresnel( NINF )\n [ ~-0.5, ~-0.5 ]\n > y = base.fresnel( NaN )\n [ NaN, NaN ]\n\n\nbase.fresnel.assign( x, out, stride, offset )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n S(x) and C(x).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels","base.fresnel.assign":"\nbase.fresnel.assign( x, out, stride, offset )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n S(x) and C(x).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels","base.fresnelc":"\nbase.fresnelc( x )\n Computes the Fresnel integral C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n C(x).\n\n Examples\n --------\n > var y = base.fresnelc( 0.0 )\n ~0.0\n > y = base.fresnelc( 1.0 )\n ~0.780\n > y = base.fresnelc( PINF )\n ~0.5\n > y = base.fresnelc( NINF )\n ~-0.5\n > y = base.fresnelc( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnels\n","base.fresnels":"\nbase.fresnels( x )\n Computes the Fresnel integral S(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n S(x).\n\n Examples\n --------\n > var y = base.fresnels( 0.0 )\n ~0.0\n > y = base.fresnels( 1.0 )\n ~0.438\n > y = base.fresnels( PINF )\n ~0.5\n > y = base.fresnels( NINF )\n ~-0.5\n > y = base.fresnels( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnelc\n","base.frexp":"\nbase.frexp( x )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = base.frexp( 4.0 )\n [ 0.5, 3 ]\n > out = base.frexp( 0.0 )\n [ 0.0, 0 ]\n > out = base.frexp( -0.0 )\n [ -0.0, 0 ]\n > out = base.frexp( NaN )\n [ NaN, 0 ]\n > out = base.frexp( PINF )\n [ Infinity, 0 ]\n > out = base.frexp( NINF )\n [ -Infinity, 0 ]\n\n\nbase.frexp.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.frexp.assign( 4.0, out, 1, 0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp\n","base.frexp.assign":"\nbase.frexp.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.frexp.assign( 4.0, out, 1, 0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp","base.fromBinaryString":"\nbase.fromBinaryString( bstr )\n Creates a double-precision floating-point number from a literal bit\n representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var bstr;\n > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n > var val = base.fromBinaryString( bstr )\n 4.0\n > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n > val = base.fromBinaryString( bstr )\n 3.141592653589793\n > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n > val = base.fromBinaryString( bstr )\n -1.0e308\n\n // The function handles subnormals:\n > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n > val = base.fromBinaryString( bstr )\n -3.14e-320\n > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n > val = base.fromBinaryString( bstr )\n 5.0e-324\n\n // The function handles special values:\n > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n 0.0\n > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -0.0\n > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n NaN\n > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n Infinity\n > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -Infinity\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var bstr = '01000000100000000000000000000000';\n > var val = base.fromBinaryStringf( bstr )\n 4.0\n > bstr = '01000000010010010000111111011011';\n > val = base.fromBinaryStringf( bstr )\n ~3.14\n > bstr = '11111111011011000011101000110011';\n > val = base.fromBinaryStringf( bstr )\n ~-3.14e+38\n\n // The function handles subnormals:\n > bstr = '10000000000000000000000000010110';\n > val = base.fromBinaryStringf( bstr )\n ~-3.08e-44\n > bstr = '00000000000000000000000000000001';\n > val = base.fromBinaryStringf( bstr )\n ~1.40e-45\n\n // The function handles special values:\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n 0.0\n > bstr = '10000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -0.0\n > bstr = '01111111110000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n NaN\n > bstr = '01111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n Infinity\n > bstr = '11111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -Infinity\n\n See Also\n --------\n base.toBinaryStringf, base.fromBinaryString\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr )\n Creates an unsigned 8-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 8-bit integer.\n\n Examples\n --------\n > var bstr = '01010101';\n > var val = base.fromBinaryStringUint8( bstr )\n 85\n > bstr = '00000000';\n > val = base.fromBinaryStringUint8( bstr )\n 0\n > bstr = '00000010';\n > val = base.fromBinaryStringUint8( bstr )\n 2\n > bstr = '11111111';\n > val = base.fromBinaryStringUint8( bstr )\n 255\n\n See Also\n --------\n base.fromBinaryStringUint16, base.fromBinaryStringUint32, base.toBinaryStringUint8\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr )\n Creates an unsigned 16-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 16-bit integer.\n\n Examples\n --------\n > var bstr = '0101010101010101';\n > var val = base.fromBinaryStringUint16( bstr )\n 21845\n > bstr = '0000000000000000';\n > val = base.fromBinaryStringUint16( bstr )\n 0\n > bstr = '0000000000000010';\n > val = base.fromBinaryStringUint16( bstr )\n 2\n > bstr = '1111111111111111';\n > val = base.fromBinaryStringUint16( bstr )\n 65535\n\n See Also\n --------\n base.toBinaryStringUint16, base.fromBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr )\n Creates an unsigned 32-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var bstr = '01010101010101010101010101010101';\n > var val = base.fromBinaryStringUint32( bstr )\n 1431655765\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringUint32( bstr )\n 0\n > bstr = '00000000000000000000000000000010';\n > val = base.fromBinaryStringUint32( bstr )\n 2\n > bstr = '11111111111111111111111111111111';\n > val = base.fromBinaryStringUint32( bstr )\n 4294967295\n\n See Also\n --------\n base.fromBinaryStringUint16, base.toBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes, stride, offset )\n Converts a signed 64-bit integer byte array to a double-precision floating-\n point number.\n\n The function assumes host byte order (endianness).\n\n Parameters\n ----------\n bytes: Array|TypedArray|Object\n Byte array.\n\n stride: integer\n Index stride.\n\n offset: integer\n Index offset.\n\n Returns\n -------\n out: number\n Number.\n\n Examples\n --------\n > var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\n > var y = base.fromInt64Bytes( bytes, 1, 0 )\n -1.0\n\n See Also\n --------\n base.float64ToInt64Bytes","base.fromWordf":"\nbase.fromWordf( word )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n\n Parameters\n ----------\n word: integer\n Unsigned integer.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var word = 1068180177; // => 0 01111111 01010110010001011010001\n > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n 1.3370000123977661\n\n See Also\n --------\n base.fromWords\n","base.fromWords":"\nbase.fromWords( high, low )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n Parameters\n ----------\n high: integer\n Higher order word (unsigned 32-bit integer).\n\n low: integer\n Lower order word (unsigned 32-bit integer).\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var v = base.fromWords( 1774486211, 2479577218 )\n 3.14e201\n > v = base.fromWords( 3221823995, 1413754136 )\n -3.141592653589793\n > v = base.fromWords( 0, 0 )\n 0.0\n > v = base.fromWords( 2147483648, 0 )\n -0.0\n > v = base.fromWords( 2146959360, 0 )\n NaN\n > v = base.fromWords( 2146435072, 0 )\n Infinity\n > v = base.fromWords( 4293918720, 0 )\n -Infinity\n\n See Also\n --------\n base.fromWordf\n","base.gamma":"\nbase.gamma( x )\n Evaluates the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma( 4.0 )\n 6.0\n > y = base.gamma( -1.5 )\n ~2.363\n > y = base.gamma( -0.5 )\n ~-3.545\n > y = base.gamma( 0.5 )\n ~1.772\n > y = base.gamma( 0.0 )\n Infinity\n > y = base.gamma( -0.0 )\n -Infinity\n > y = base.gamma( NaN )\n NaN\n\n See Also\n --------\n base.gamma1pm1, base.gammainc, base.gammaincinv, base.gammaln\n","base.gamma1pm1":"\nbase.gamma1pm1( x )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma1pm1( 0.2 )\n ~-0.082\n > y = base.gamma1pm1( -6.7 )\n ~-0.991\n > y = base.gamma1pm1( 0.0 )\n 0.0\n > y = base.gamma1pm1( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv, base.gammaln\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z, delta )\n Computes the ratio of two gamma functions.\n\n The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n Parameters\n ----------\n z: number\n First gamma parameter.\n\n delta: number\n Difference.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n ~0.042\n > y = base.gammaDeltaRatio( 4.0, 0.5 )\n ~0.516\n > y = base.gammaDeltaRatio( 100.0, 0.0 )\n 1.0\n > y = base.gammaDeltaRatio( NaN, 3.0 )\n NaN\n > y = base.gammaDeltaRatio( 5.0, NaN )\n NaN\n > y = base.gammaDeltaRatio( NaN, NaN )\n NaN\n\n See Also\n --------\n base.gamma\n","base.gammainc":"\nbase.gammainc( x, s[, regularized[, upper]] )\n Computes the regularized incomplete gamma function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete gamma functions, respectively.\n\n If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n s: number\n Second function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete gamma function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete gamma function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammainc( 6.0, 2.0 )\n ~0.9826\n > y = base.gammainc( 1.0, 2.0, true, true )\n ~0.7358\n > y = base.gammainc( 7.0, 5.0 )\n ~0.8270\n > y = base.gammainc( 7.0, 5.0, false )\n ~19.8482\n > y = base.gammainc( NaN, 2.0 )\n NaN\n > y = base.gammainc( 6.0, NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammaincinv, base.gammaln\n","base.gammaincinv":"\nbase.gammaincinv( p, a[, upper] )\n Computes the inverse of the lower incomplete gamma function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second argument is the scale factor `a`.\n\n By default, the function inverts the lower regularized incomplete gamma\n function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Scale parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaincinv( 0.5, 2.0 )\n ~1.678\n > y = base.gammaincinv( 0.1, 10.0 )\n ~6.221\n > y = base.gammaincinv( 0.75, 3.0 )\n ~3.92\n > y = base.gammaincinv( 0.75, 3.0, true )\n ~1.727\n > y = base.gammaincinv( 0.75, NaN )\n NaN\n > y = base.gammaincinv( NaN, 3.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammainc, base.gammaln\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x )\n Calculates the Lanczos sum for the approximation of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSum( 4.0 )\n ~950.366\n > y = base.gammaLanczosSum( -1.5 )\n ~1373366.245\n > y = base.gammaLanczosSum( -0.5 )\n ~-699841.735\n > y = base.gammaLanczosSum( 0.5 )\n ~96074.186\n > y = base.gammaLanczosSum( 0.0 )\n Infinity\n > y = base.gammaLanczosSum( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSumExpGScaled\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Scaled Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n ~0.018\n > y = base.gammaLanczosSumExpGScaled( -1.5 )\n ~25.337\n > y = base.gammaLanczosSumExpGScaled( -0.5 )\n ~-12.911\n > y = base.gammaLanczosSumExpGScaled( 0.5 )\n ~1.772\n > y = base.gammaLanczosSumExpGScaled( 0.0 )\n Infinity\n > y = base.gammaLanczosSumExpGScaled( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSum\n","base.gammaln":"\nbase.gammaln( x )\n Evaluates the natural logarithm of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the gamma function.\n\n Examples\n --------\n > var y = base.gammaln( 1.0 )\n 0.0\n > y = base.gammaln( 2.0 )\n 0.0\n > y = base.gammaln( 4.0 )\n ~1.792\n > y = base.gammaln( -0.5 )\n ~1.266\n > y = base.gammaln( 0.5 )\n ~0.572\n > y = base.gammaln( 0.0 )\n Infinity\n > y = base.gammaln( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv\n","base.gammasgn":"\nbase.gammasgn( x )\n Computes the sign of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Sign of the gamma function.\n\n Examples\n --------\n > var y = base.gammasgn( 1.0 )\n 1.0\n > y = base.gammasgn( -2.5 )\n -1.0\n > y = base.gammasgn( 0.0 )\n 0.0\n > y = base.gammasgn( NaN )\n NaN\n\n See Also\n --------\n base.gamma","base.gcd":"\nbase.gcd( a, b )\n Computes the greatest common divisor (gcd).\n\n If both `a` and `b` are `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First number.\n\n b: integer\n Second number.\n\n Returns\n -------\n out: integer\n Greatest common divisor.\n\n Examples\n --------\n > var v = base.gcd( 48, 18 )\n 6\n\n See Also\n --------\n base.lcm\n","base.getHighWord":"\nbase.getHighWord( x )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Higher order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getHighWord( 3.14e201 )\n 1774486211\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.getLowWord":"\nbase.getLowWord( x )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Lower order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getLowWord( 3.14e201 )\n 2479577218\n\n See Also\n --------\n base.getHighWord, base.setHighWord\n","base.hacovercos":"\nbase.hacovercos( x )\n Computes the half-value coversed cosine.\n\n The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed cosine.\n\n Examples\n --------\n > var y = base.hacovercos( 3.14 )\n ~0.5008\n > y = base.hacovercos( -4.2 )\n ~0.9358\n > y = base.hacovercos( -4.6 )\n ~0.9968\n > y = base.hacovercos( 9.5 )\n ~0.4624\n > y = base.hacovercos( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacoversin, base.havercos\n","base.hacoversin":"\nbase.hacoversin( x )\n Computes the half-value coversed sine.\n\n The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed sine.\n\n Examples\n --------\n > var y = base.hacoversin( 3.14 )\n ~0.4992\n > y = base.hacoversin( -4.2 )\n ~0.0642\n > y = base.hacoversin( -4.6 )\n ~0.0032\n > y = base.hacoversin( 9.5 )\n ~0.538\n > y = base.hacoversin( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacovercos, base.haversin\n","base.havercos":"\nbase.havercos( x )\n Computes the half-value versed cosine.\n\n The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed cosine.\n\n Examples\n --------\n > var y = base.havercos( 3.14 )\n ~0.0\n > y = base.havercos( -4.2 )\n ~0.2549\n > y = base.havercos( -4.6 )\n ~0.4439\n > y = base.havercos( 9.5 )\n ~0.0014\n > y = base.havercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.haversin, base.vercos\n","base.haversin":"\nbase.haversin( x )\n Computes the half-value versed sine.\n\n The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed sine.\n\n Examples\n --------\n > var y = base.haversin( 3.14 )\n ~1.0\n > y = base.haversin( -4.2 )\n ~0.7451\n > y = base.haversin( -4.6 )\n ~0.5561\n > y = base.haversin( 9.5 )\n ~0.9986\n > y = base.haversin( -0.0 )\n 0.0\n\n See Also\n --------\n base.havercos, base.versin\n","base.headercase":"\nbase.headercase( str )\n Converts a string to HTTP header case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n HTTP header-cased string.\n\n Examples\n --------\n > var out = base.headercase( 'Hello World!' )\n 'Hello-World'\n > out = base.headercase( 'beep boop' )\n 'Beep-Boop'\n\n See Also\n --------\n base.camelcase, base.pascalcase, base.uppercase","base.heaviside":"\nbase.heaviside( x[, continuity] )\n Evaluates the Heaviside function.\n\n The `continuity` parameter may be one of the following:\n\n - 'half-maximum': if `x == 0`, the function returns `0.5`.\n - 'left-continuous': if `x == 0`, the function returns `0`.\n - 'right-continuous': if `x == 0`, the function returns `1`.\n\n By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n discontinuous).\n\n Parameters\n ----------\n x: number\n Input value.\n\n continuity: string (optional)\n Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n returns `NaN`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.heaviside( 3.14 )\n 1.0\n > y = base.heaviside( -3.14 )\n 0.0\n > y = base.heaviside( 0.0 )\n NaN\n > y = base.heaviside( 0.0, 'half-maximum' )\n 0.5\n > y = base.heaviside( 0.0, 'left-continuous' )\n 0.0\n > y = base.heaviside( 0.0, 'right-continuous' )\n 1.0\n\n See Also\n --------\n base.ramp\n","base.hermitepoly":"\nbase.hermitepoly( n, x )\n Evaluates a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.hermitepoly( 1, 0.5 )\n 1.0\n > y = base.hermitepoly( -1, 0.5 )\n NaN\n > y = base.hermitepoly( 0, 0.5 )\n 1.0\n > y = base.hermitepoly( 2, 0.5 )\n -1.0\n\n\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly","base.hypot":"\nbase.hypot( x, y )\n Computes the hypotenuse avoiding overflow and underflow.\n\n If either argument is `NaN` and the other argument is not `+-Infinity`,\n the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypot( -5.0, 12.0 )\n 13.0\n > h = base.hypot( NaN, 12.0 )\n NaN\n > h = base.hypot( -0.0, -0.0 )\n 0.0\n\n","base.hypotf":"\nbase.hypotf( x, y )\n Computes the hypotenuse avoiding overflow and underflow (single-precision).\n\n If either argument is `NaN` and the other argument is not `+-Infinity`,\n the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypotf( -5.0, 12.0 )\n 13.0\n > h = base.hypotf( NaN, 12.0 )\n NaN\n > h = base.hypotf( -0.0, -0.0 )\n 0.0\n\n See Also\n --------\n base.hypot\n","base.identity":"\nbase.identity( x )\n Evaluates the identity function for a double-precision floating-point number\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Input value.\n\n Examples\n --------\n > var y = base.identity( -1.0 )\n -1.0\n > y = base.identity( 2.0 )\n 2.0\n > y = base.identity( 0.0 )\n 0.0\n > y = base.identity( -0.0 )\n -0.0\n > y = base.identity( NaN )\n NaN\n\n See Also\n --------\n base.identityf\n","base.identityf":"\nbase.identityf( x )\n Evaluates the identity function for a single-precision floating-point number\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Input value.\n\n Examples\n --------\n > var y = base.identityf( -1.0 )\n -1.0\n > y = base.identityf( 2.0 )\n 2.0\n > y = base.identityf( 0.0 )\n 0.0\n > y = base.identityf( -0.0 )\n -0.0\n > y = base.identityf( NaN )\n NaN\n\n See Also\n --------\n base.identity\n","base.imul":"\nbase.imul( a, b )\n Performs C-like multiplication of two signed 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.imul( -10|0, 4|0 )\n -40\n\n See Also\n --------\n base.imuldw\n","base.imuldw":"\nbase.imuldw( a, b )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: Array\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.imuldw( 1, 10 )\n [ 0, 10 ]\n\n\nbase.imuldw.assign( a, b, out, stride, offset )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imul","base.imuldw.assign":"\nbase.imuldw.assign( a, b, out, stride, offset )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imul","base.int2slice":"\nbase.int2slice( value, max, strict )\n Converts an integer to a Slice object.\n\n In strict mode, the function returns an error object if an input value\n exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n Parameters\n ----------\n value: integer\n Input value.\n\n max: integer\n Index upper bound (exclusive).\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance (or an error object).\n\n Examples\n --------\n > var s = base.int2slice( -1, 5, false );\n > s.start\n 4\n > s.stop\n 5\n > s.step\n 1\n\n See Also\n --------\n base.seq2slice, base.str2slice\n","base.int32ToUint32":"\nbase.int32ToUint32( x )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\n 4294967264\n > y = base.int32ToUint32( base.float64ToInt32( 3 ) )\n 3\n\n See Also\n --------\n base.uint32ToInt32\n","base.inv":"\nbase.inv( x )\n Computes the multiplicative inverse of a double-precision floating-point\n number `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.inv( -1.0 )\n -1.0\n > y = base.inv( 2.0 )\n 0.5\n > y = base.inv( 0.0 )\n Infinity\n > y = base.inv( -0.0 )\n -Infinity\n > y = base.inv( NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.invcase":"\nbase.invcase( str )\n Converts a string to inverse case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Inverse-cased string.\n\n Examples\n --------\n > var out = base.invcase( 'Hello World!' )\n 'hELLO wORLD!'\n > out = base.invcase( 'I am A tiny LITTLE teapot' )\n 'i AM a TINY little TEAPOT'\n\n See Also\n --------\n base.lowercase, base.uppercase","base.invf":"\nbase.invf( x )\n Computes the multiplicative inverse of a single-precision floating-point\n number `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.invf( -1.0 )\n -1.0\n > y = base.invf( 2.0 )\n 0.5\n > y = base.invf( 0.0 )\n Infinity\n > y = base.invf( -0.0 )\n -Infinity\n > y = base.invf( NaN )\n NaN\n\n See Also\n --------\n base.inv\n","base.isComposite":"\nbase.isComposite( x )\n Tests if a number is composite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a composite number.\n\n Examples\n --------\n > var bool = base.isComposite( 10.0 )\n true\n > bool = base.isComposite( 11.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isPrime\n","base.isCoprime":"\nbase.isCoprime( a, b )\n Tests if two numbers are coprime.\n\n Parameters\n ----------\n a: number\n First value.\n\n b: number\n Second value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the values are coprime.\n\n Examples\n --------\n > var bool = base.isCoprime( 14.0, 15.0 )\n true\n > bool = base.isCoprime( 14.0, 21.0 )\n false\n\n See Also\n --------\n base.isComposite, base.isPrime, base.gcd\n","base.isEven":"\nbase.isEven( x )\n Tests if a finite numeric value is an even number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEven( 5.0 )\n false\n > bool = base.isEven( -2.0 )\n true\n > bool = base.isEven( 0.0 )\n true\n > bool = base.isEven( NaN )\n false\n\n See Also\n --------\n base.isOdd\n","base.isEvenInt32":"\nbase.isEvenInt32( x )\n Tests if a 32-bit integer is even.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEvenInt32( 5 )\n false\n > bool = base.isEvenInt32( -2 )\n true\n > bool = base.isEvenInt32( 0 )\n true\n\n See Also\n --------\n base.isEven, base.isOddInt32\n","base.isFinite":"\nbase.isFinite( x )\n Tests if a double-precision floating-point numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinite( 5.0 )\n true\n > bool = base.isFinite( -2.0e64 )\n true\n > bool = base.isFinite( PINF )\n false\n > bool = base.isFinite( NINF )\n false\n\n See Also\n --------\n base.isInfinite\n","base.isFinitef":"\nbase.isFinitef( x )\n Tests if a single-precision floating-point numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinitef( 5.0 )\n true\n > bool = base.isFinitef( -1.0e38 )\n true\n > bool = base.isFinitef( FLOAT32_PINF )\n false\n > bool = base.isFinitef( FLOAT32_NINF )\n false\n\n See Also\n --------\n base.isInfinitef\n","base.isInfinite":"\nbase.isInfinite( x )\n Tests if a double-precision floating-point numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinite( PINF )\n true\n > bool = base.isInfinite( NINF )\n true\n > bool = base.isInfinite( 5.0 )\n false\n > bool = base.isInfinite( NaN )\n false\n\n See Also\n --------\n base.isFinite\n","base.isInfinitef":"\nbase.isInfinitef( x )\n Tests if a single-precision floating-point numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinitef( FLOAT32_PINF )\n true\n > bool = base.isInfinitef( FLOAT32_NINF )\n true\n > bool = base.isInfinitef( 5.0 )\n false\n > bool = base.isInfinitef( NaN )\n false\n\n See Also\n --------\n base.isFinitef\n","base.isInteger":"\nbase.isInteger( x )\n Tests if a finite double-precision floating-point number is an integer.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an integer.\n\n Examples\n --------\n > var bool = base.isInteger( 1.0 )\n true\n > bool = base.isInteger( 3.14 )\n false\n\n","base.isnan":"\nbase.isnan( x )\n Tests if a double-precision floating-point numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnan( NaN )\n true\n > bool = base.isnan( 7.0 )\n false\n\n See Also\n --------\n base.isnanf\n","base.isnanf":"\nbase.isnanf( x )\n Tests if a single-precision floating-point numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnanf( NaN )\n true\n > bool = base.isnanf( 7.0 )\n false\n\n See Also\n --------\n base.isnan\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x )\n Tests if a double-precision floating-point numeric value is a negative\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether the value is a negative finite number.\n\n Examples\n --------\n > var bool = base.isNegativeFinite( -3.14 )\n true\n > bool = base.isNegativeFinite( -Infinity )\n false\n > bool = base.isNegativeFinite( 2.0 )\n false\n > bool = base.isNegativeFinite( NaN )\n false\n > bool = base.isNegativeFinite( -0.0 )\n false\n\n See Also\n --------\n base.isPositiveFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a negative integer.\n\n Examples\n --------\n > var bool = base.isNegativeInteger( -1.0 )\n true\n > bool = base.isNegativeInteger( 0.0 )\n false\n > bool = base.isNegativeInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNonNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNegativeZero":"\nbase.isNegativeZero( x )\n Tests if a double-precision floating-point numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZero( -0.0 )\n true\n > bool = base.isNegativeZero( 0.0 )\n false\n\n See Also\n --------\n base.isPositiveZero\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x )\n Tests if a single-precision floating-point numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZerof( -0.0 )\n true\n > bool = base.isNegativeZerof( 0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero, base.isPositiveZerof\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x )\n Tests if a double-precision floating-point numeric value is a nonnegative\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative finite number.\n\n Examples\n --------\n > var out = base.isNonNegativeFinite( 5.0 )\n true\n > out = base.isNonNegativeFinite( 3.14 )\n true\n > out = base.isNonNegativeFinite( 0.0 )\n true\n > out = base.isNonNegativeFinite( Infinity )\n false\n > out = base.isNonNegativeFinite( -3.14 )\n false\n > out = base.isNonNegativeFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isPositiveFinite, base.isNonPositiveFinite\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative integer.\n\n Examples\n --------\n > var bool = base.isNonNegativeInteger( 1.0 )\n true\n > bool = base.isNonNegativeInteger( 0.0 )\n true\n > bool = base.isNonNegativeInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x )\n Tests if a double-precision floating-point numeric value is a nonpositive\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether the value is a nonpositive finite number.\n\n Examples\n --------\n > var bool = base.isNonPositiveFinite( -3.14 )\n true\n > var bool = base.isNonPositiveFinite( 0.0 )\n true\n > var bool = base.isNonPositiveFinite( -Infinity )\n false\n > var bool = base.isNonPositiveFinite( 3.14 )\n false\n > var bool = base.isNonPositiveFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isPositiveFinite, base.isNonNegativeFinite\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonpositive integer.\n\n Examples\n --------\n > var bool = base.isNonPositiveInteger( -1.0 )\n true\n > bool = base.isNonPositiveInteger( 0.0 )\n true\n > bool = base.isNonPositiveInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isPositiveInteger\n","base.isOdd":"\nbase.isOdd( x )\n Tests if a finite numeric value is an odd number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOdd( 5.0 )\n true\n > bool = base.isOdd( -2.0 )\n false\n > bool = base.isOdd( 0.0 )\n false\n > bool = base.isOdd( NaN )\n false\n\n See Also\n --------\n base.isEven\n","base.isOddInt32":"\nbase.isOddInt32( x )\n Tests if a 32-bit integer is odd.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOddInt32( 5 )\n true\n > bool = base.isOddInt32( -2 )\n false\n > bool = base.isOddInt32( 0 )\n false\n\n See Also\n --------\n base.isEvenInt32, base.isOdd\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x )\n Tests if a double-precision floating-point numeric value is a positive\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive finite number.\n\n Examples\n --------\n > var bool = base.isPositiveFinite( 5.0 )\n true\n > bool = base.isPositiveFinite( 3.14 )\n true\n > bool = base.isPositiveFinite( 0.0 )\n false\n > bool = base.isPositiveFinite( Infinity )\n false\n > bool = base.isPositiveFinite( -3.14 )\n false\n > bool = base.isPositiveFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive integer.\n\n Examples\n --------\n > var bool = base.isPositiveInteger( 1.0 )\n true\n > bool = base.isPositiveInteger( 0.0 )\n false\n > bool = base.isPositiveInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isNonPositiveInteger\n","base.isPositiveZero":"\nbase.isPositiveZero( x )\n Tests if a double-precision floating-point numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZero( 0.0 )\n true\n > bool = base.isPositiveZero( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x )\n Tests if a single-precision floating-point numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZerof( 0.0 )\n true\n > bool = base.isPositiveZerof( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZerof, base.isPositiveZero\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x )\n Tests whether an unsigned integer is a power of 2.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a power of 2.\n\n Examples\n --------\n > var bool = base.isPow2Uint32( 2 )\n true\n > bool = base.isPow2Uint32( 5 )\n false\n\n","base.isPrime":"\nbase.isPrime( x )\n Tests if a number is prime.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a prime number.\n\n Examples\n --------\n > var bool = base.isPrime( 11.0 )\n true\n > bool = base.isPrime( 3.14 )\n false\n\n See Also\n --------\n base.isComposite, base.isInteger\n","base.isProbability":"\nbase.isProbability( x )\n Tests if a double-precision floating-point number value is a probability.\n\n A probability is defined as a number on the closed interval [0,1].\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a probability.\n\n Examples\n --------\n > var bool = base.isProbability( 0.5 )\n true\n > bool = base.isProbability( 3.14 )\n false\n > bool = base.isProbability( NaN )\n false\n\n","base.isSafeInteger":"\nbase.isSafeInteger( x )\n Tests if a finite double-precision floating-point number is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a safe integer.\n\n Examples\n --------\n > var bool = base.isSafeInteger( 1.0 )\n true\n > bool = base.isSafeInteger( 2.0e200 )\n false\n > bool = base.isSafeInteger( 3.14 )\n false\n\n","base.kebabcase":"\nbase.kebabcase( str )\n Converts a string to kebab case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Kebab-cased string.\n\n Examples\n --------\n > var out = base.kebabcase( 'Hello World!' )\n 'hello-world'\n > out = base.kebabcase( 'I am a tiny little teapot' )\n 'i-am-a-tiny-little-teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.pascalcase, base.snakecase, base.uppercase","base.kernelBetainc":"\nbase.kernelBetainc( x, a, b, regularized, upper )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n [ ~1.277, ~0.926 ]\n > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n [ 0.36, 1.6 ]\n\n\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a, b, p, q )\n Computes the inverse of the lower incomplete beta function.\n\n Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n Parameters\n ----------\n a: number\n First function parameter (a positive number).\n\n b: number\n Second function parameter (a positive number).\n\n p: number\n Probability.\n\n q: number\n Probability equal to `1-p`.\n\n Returns\n -------\n out: Array\n Two-element array holding function value `y` and `1-y`.\n\n Examples\n --------\n > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n [ ~0.327, ~0.673 ]\n > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n [ ~0.446, ~0.554 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n [ ~0.082, ~0.918 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n [ ~0.235, ~0.765 ]\n\n See Also\n --------\n base.betaincinv\n","base.kernelCos":"\nbase.kernelCos( x, y )\n Computes the cosine of a double-precision floating-point number on the\n interval [-π/4, π/4].\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Cosine.\n\n Examples\n --------\n > var out = base.kernelCos( 0.0, 0.0 )\n ~1.0\n > out = base.kernelCos( PI/6.0, 0.0 )\n ~0.866\n > out = base.kernelCos( 0.785, -1.144e-17 )\n ~0.707\n > out = base.kernelCos( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.kernelSin, base.kernelTan\n","base.kernelLog1p":"\nbase.kernelLog1p( f )\n Evaluates a correction term for double-precision base-2 and base-10\n logarithms when `1+f` is in `[√2/2, √2]`.\n\n This function provides a common means for computing logarithms in base e.\n Argument reduction and adding the final term of the polynomial must be done\n by the caller for increased accuracy when different bases are used.\n\n Parameters\n ----------\n f: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var y = base.kernelLog1p( 1.0 )\n ~0.1931\n > y = base.kernelLog1p( 1.4142135623730951 )\n ~0.4672\n > y = base.kernelLog1p( NaN )\n NaN\n\n See Also\n --------\n base.log1p\n","base.kernelSin":"\nbase.kernelSin( x, y )\n Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Sine.\n\n Examples\n --------\n > var y = base.kernelSin( 0.0, 0.0 )\n ~0.0\n > y = base.kernelSin( PI/6.0, 0.0 )\n ~0.5\n > y = base.kernelSin( 0.619, 9.279e-18 )\n ~0.58\n\n > y = base.kernelSin( NaN, 0.0 )\n NaN\n > y = base.kernelSin( 2.0, NaN )\n NaN\n > y = base.kernelSin( NaN, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelTan, base.sin\n","base.kernelTan":"\nbase.kernelTan( x, y, k )\n Computes the tangent of a double-precision floating-point number on the\n interval [-π/4, π/4].\n\n For increased accuracy, the number for which the tangent should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n k: integer\n If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n returns the negative inverse `-1/tan(x+y)`.\n\n Returns\n -------\n out: number\n Tangent.\n\n Examples\n --------\n > var out = base.kernelTan( PI/4.0, 0.0, 1 )\n ~1.0\n > out = base.kernelTan( PI/4.0, 0.0, -1 )\n ~-1.0\n > out = base.kernelTan( PI/6.0, 0.0, 1 )\n ~0.577\n > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n ~0.783\n\n > out = base.kernelTan( NaN, 0.0, 1 )\n NaN\n > out = base.kernelTan( 3.0, NaN, 1 )\n NaN\n > out = base.kernelTan( 3.0, 0.0, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelSin, base.tan\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i, j )\n Evaluates the Kronecker delta.\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDelta( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDelta( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.diracDelta\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i, j )\n Evaluates the Kronecker delta (single-precision).\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDeltaf( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDeltaf( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.kroneckerDelta\n","base.labs":"\nbase.labs( x )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Absolute value.\n\n Examples\n --------\n > var v = base.labs( -1|0 )\n 1\n > v = base.labs( 2|0 )\n 2\n > v = base.labs( 0|0 )\n 0\n\n See Also\n --------\n base.abs\n","base.last":"\nbase.last( str, n )\n Returns the last `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.last( 'hello', 1 )\n 'o'\n > out = base.last( 'JavaScript', 6 )\n 'Script'\n > out = base.last( 'foo bar', 10 )\n 'foo bar'\n\n See Also\n --------\n base.firstCodeUnit, base.lastCodePoint, base.lastGraphemeCluster\n","base.lastCodePoint":"\nbase.lastCodePoint( str, n )\n Returns the last `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.lastCodePoint( 'hello world', 1 )\n 'd'\n > out = base.lastCodePoint( 'JavaScript', 6 )\n 'Script'\n > out = base.lastCodePoint( 'अनुच्छेद', 1 )\n 'द'\n\n See Also\n --------\n base.firstCodePoint, base.lastGraphemeCluster, base.last\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str, n )\n Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.lastGraphemeCluster( 'beep', 1 )\n 'p'\n > out = base.lastGraphemeCluster( 'Boop', 2 )\n 'op'\n > out = base.lastGraphemeCluster( 'JavaScript', 6 )\n 'Script'\n\n See Also\n --------\n base.firstGraphemeCluster, base.lastCodePoint, base.last\n","base.lcm":"\nbase.lcm( a, b )\n Computes the least common multiple (lcm).\n\n If either `a` or `b` is `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Least common multiple.\n\n Examples\n --------\n > var v = base.lcm( 21, 6 )\n 42\n\n See Also\n --------\n base.gcd\n","base.ldexp":"\nbase.ldexp( frac, exp )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n\n If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n infinity, the function returns a value equal to `frac`.\n\n Parameters\n ----------\n frac: number\n Fraction.\n\n exp: number\n Exponent.\n\n Returns\n -------\n out: number\n Double-precision floating-point number equal to `frac * 2^exp`.\n\n Examples\n --------\n > var x = base.ldexp( 0.5, 3 )\n 4.0\n > x = base.ldexp( 4.0, -2 )\n 1.0\n > x = base.ldexp( 0.0, 20 )\n 0.0\n > x = base.ldexp( -0.0, 39 )\n -0.0\n > x = base.ldexp( NaN, -101 )\n NaN\n > x = base.ldexp( PINF, 11 )\n Infinity\n > x = base.ldexp( NINF, -118 )\n -Infinity\n\n See Also\n --------\n base.frexp\n","base.leftPad":"\nbase.leftPad( str, len, pad )\n Left pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string\n String used to pad.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = base.leftPad( 'a', 5, ' ' )\n ' a'\n > out = base.leftPad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = base.leftPad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n base.rightPad\n","base.leftTrim":"\nbase.leftTrim( str )\n Trims whitespace from the beginning of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.leftTrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n See Also\n --------\n base.rightTrim, base.trim\n","base.ln":"\nbase.ln( x )\n Evaluates the natural logarithm of a double-precision floating-point number.\n\n For negative numbers, the natural logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ln( 4.0 )\n ~1.386\n > y = base.ln( 0.0 )\n -Infinity\n > y = base.ln( PINF )\n Infinity\n > y = base.ln( NaN )\n NaN\n > y = base.ln( -4.0 )\n NaN\n\n See Also\n --------\n base.exp, base.log10, base.log1p, base.log2\n","base.log":"\nbase.log( x, b )\n Computes the base `b` logarithm of a double-precision floating-point number.\n\n For negative `b` or `x`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n b: number\n Base.\n\n Returns\n -------\n y: number\n Logarithm (base `b`).\n\n Examples\n --------\n > var y = base.log( 100.0, 10.0 )\n 2.0\n > y = base.log( 16.0, 2.0 )\n 4.0\n > y = base.log( 5.0, 1.0 )\n Infinity\n > y = base.log( NaN, 2.0 )\n NaN\n > y = base.log( 1.0, NaN )\n NaN\n > y = base.log( -4.0, 2.0 )\n NaN\n > y = base.log( 4.0, -2.0 )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log10, base.log1p, base.log2\n","base.log1mexp":"\nbase.log1mexp( x )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1mexp( -10.0 )\n ~-0.00005\n > y = base.log1mexp( 0.0 )\n -Infinity\n > y = base.log1mexp( 5.0 )\n ~-0.00676\n > y = base.log1mexp( 10.0 )\n ~-0.00005\n > y = base.log1mexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1p, base.log1pexp","base.log1p":"\nbase.log1p( x )\n Evaluates the natural logarithm of `1+x`.\n\n For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n defined for negative numbers.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1p( 4.0 )\n ~1.609\n > y = base.log1p( -1.0 )\n -Infinity\n > y = base.log1p( 0.0 )\n 0.0\n > y = base.log1p( -0.0 )\n -0.0\n > y = base.log1p( -2.0 )\n NaN\n > y = base.log1p( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log\n","base.log1pexp":"\nbase.log1pexp( x )\n Evaluates the natural logarithm of `1+exp(x)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1pexp( -10.0 )\n ~0.000045\n > y = base.log1pexp( 0.0 )\n ~0.693147\n > y = base.log1pexp( 5.0 )\n ~5.006715\n > y = base.log1pexp( 34.0 )\n 34.0\n > y = base.log1pexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1mexp, base.log1p","base.log1pmx":"\nbase.log1pmx( x )\n Evaluates `ln(1+x) - x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > base.log1pmx( 1.1 )\n ~-0.358\n > base.log1pmx( 0.99 )\n ~-0.302\n > base.log1pmx( -0.99 )\n ~-3.615\n > base.log1pmx( -1.1 )\n NaN\n > base.log1pmx( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log1p","base.log2":"\nbase.log2( x )\n Evaluates the binary logarithm (base two).\n\n For negative numbers, the binary logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log2( 4.0 )\n 2.0\n > y = base.log2( 8.0 )\n 3.0\n > y = base.log2( 0.0 )\n -Infinity\n > y = base.log2( PINF )\n Infinity\n > y = base.log2( NaN )\n NaN\n > y = base.log2( -4.0 )\n NaN\n\n See Also\n --------\n base.exp2, base.ln, base.log\n","base.log10":"\nbase.log10( x )\n Evaluates the common logarithm (base 10).\n\n For negative numbers, the common logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log10( 100.0 )\n 2.0\n > y = base.log10( 8.0 )\n ~0.903\n > y = base.log10( 0.0 )\n -Infinity\n > y = base.log10( PINF )\n Infinity\n > y = base.log10( NaN )\n NaN\n > y = base.log10( -4.0 )\n NaN\n\n See Also\n --------\n base.exp10, base.ln, base.log\n","base.logaddexp":"\nbase.logaddexp( x, y )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.logaddexp( 90.0, 90.0 )\n ~90.6931\n > v = base.logaddexp( -20.0, 90.0 )\n 90.0\n > v = base.logaddexp( 0.0, -100.0 )\n ~3.7201e-44\n > v = base.logaddexp( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln\n","base.logit":"\nbase.logit( p )\n Evaluates the logit function.\n\n Let `p` be the probability of some event. The logit function is defined as\n the logarithm of the odds `p / (1-p)`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.logit( 0.2 )\n ~-1.386\n > y = base.logit( 0.9 )\n ~2.197\n > y = base.logit( -4.0 )\n NaN\n > y = base.logit( 1.5 )\n NaN\n > y = base.logit( NaN )\n NaN\n\n","base.lowercase":"\nbase.lowercase( str )\n Converts a string to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = base.lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n base.snakecase, base.uppercase\n","base.lucas":"\nbase.lucas( n )\n Computes the nth Lucas number.\n\n Lucas numbers follow the recurrence relation\n\n L_n = L_{n-1} + L_{n-2}\n\n with seed values L_0 = 2 and L_1 = 1.\n\n If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Lucas number.\n\n Examples\n --------\n > var y = base.lucas( 0 )\n 2\n > y = base.lucas( 1 )\n 1\n > y = base.lucas( 2 )\n 3\n > y = base.lucas( 3 )\n 4\n > y = base.lucas( 4 )\n 7\n > y = base.lucas( 77 )\n NaN\n > y = base.lucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.lucaspoly":"\nbase.lucaspoly( n, x )\n Evaluates a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Lucas polynomial.\n\n Returns\n -------\n out: number\n Evaluated Lucas polynomial.\n\n Examples\n --------\n // 2^5 + 5*2^3 + 5*2\n > var v = base.lucaspoly( 5, 2.0 )\n 82.0\n\n\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly","base.max":"\nbase.max( x, y )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.max( 3.14, 4.2 )\n 4.2\n > v = base.max( 3.14, NaN )\n NaN\n > v = base.max( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.maxn, base.min\n","base.maxabs":"\nbase.maxabs( x, y )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabs( 3.14, -4.2 )\n 4.2\n > v = base.maxabs( 3.14, NaN )\n NaN\n > v = base.maxabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.minabs\n","base.maxabsn":"\nbase.maxabsn( [x[, y[, ...args]]] )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n the absolute value of `-infinity`).\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabsn( 3.14, -4.2 )\n 4.2\n > v = base.maxabsn( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxabsn( 3.14, NaN )\n NaN\n > v = base.maxabsn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxn, base.maxabs, base.minabsn\n","base.maxn":"\nbase.maxn( [x[, y[, ...args]]] )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns negative infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.maxn( 3.14, 4.2 )\n 4.2\n > v = base.maxn( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxn( 3.14, NaN )\n NaN\n > v = base.maxn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.maxabsn, base.minn\n","base.min":"\nbase.min( x, y )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.min( 3.14, 4.2 )\n 3.14\n > v = base.min( 3.14, NaN )\n NaN\n > v = base.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max, base.minabs, base.minn\n","base.minabs":"\nbase.minabs( x, y )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabs( 3.14, -4.2 )\n 3.14\n > v = base.minabs( 3.14, NaN )\n NaN\n > v = base.minabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.min\n","base.minabsn":"\nbase.minabsn( [x[, y[, ...args]]] )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabsn( 3.14, -4.2 )\n 3.14\n > v = base.minabsn( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minabsn( 3.14, NaN )\n NaN\n > v = base.minabsn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabsn, base.minn, base.minabs\n","base.minmax":"\nbase.minmax( x, y )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: Array\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmax( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmax( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmax( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n\n\nbase.minmax.assign( x, y, out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs","base.minmax.assign":"\nbase.minmax.assign( x, y, out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs","base.minmaxabs":"\nbase.minmaxabs( x, y )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: Array\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabs( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabs( -5.9, 3.14)\n [ 3.14, 5.9 ]\n > v = base.minmaxabs( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabs( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n\n\nbase.minmaxabs.assign( x, y, out, stride, offset )\n Returns the minimum and maximum absolute values and assigns results to a\n provided output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x, y, out, stride, offset )\n Returns the minimum and maximum absolute values and assigns results to a\n provided output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax","base.minmaxabsn":"\nbase.minmaxabsn( [x[, y[, ...args]]] )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound and negative infinity is the least upper bound. Similar\n to zero being the identity element for the sum of an empty set and to one\n being the identity element for the product of an empty set, positive\n infinity is the identity element for the minimum and negative infinity is\n the identity element for the maximum, and thus, if not provided any\n arguments, the function returns positive infinity for both the minimum and\n maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabsn( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabsn( -5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxabsn( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabsn( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n > v = base.minmaxabsn( 3.14 )\n [ 3.14, 3.14 ]\n\n\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabsn, base.minabsn, base.minmaxn\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabsn, base.minabsn, base.minmaxn","base.minmaxn":"\nbase.minmaxn( [x[, y[, ...args]]] )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound and negative infinity is the least upper bound. Similar\n to zero being the identity element for the sum of an empty set and to one\n being the identity element for the product of an empty set, positive\n infinity is the identity element for the minimum and negative infinity is\n the identity element for the maximum, and thus, if not provided any\n arguments, the function returns positive infinity for the minimum value and\n negative infinity for the maximum value.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmaxn( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxn( 5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxn( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxn( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n > v = base.minmaxn( 3.14 )\n [ 3.14, 3.14 ]\n\n\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxn, base.minn, base.minmaxabsn","base.minmaxn.assign":"\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxn, base.minn, base.minmaxabsn","base.minn":"\nbase.minn( [x[, y[, ...args]]] )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.minn( 3.14, 4.2 )\n 3.14\n > v = base.minn( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minn( 3.14, NaN )\n NaN\n > v = base.minn( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.maxn, base.min, base.minabsn\n","base.modf":"\nbase.modf( x )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n Integral and fractional parts.\n\n Examples\n --------\n > var parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( +0.0 )\n [ +0.0, +0.0 ]\n > parts = base.modf( -0.0 )\n [ -0.0, -0.0 ]\n > parts = base.modf( PINF )\n [ Infinity, +0.0 ]\n > parts = base.modf( NINF )\n [ -Infinity, -0.0 ]\n > parts = base.modf( NaN )\n [ NaN, NaN ]\n\n\nbase.modf.assign( x, out, stride, offset )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var parts = base.modf.assign( 3.14, out, 1, 0 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true\n","base.modf.assign":"\nbase.modf.assign( x, out, stride, offset )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var parts = base.modf.assign( 3.14, out, 1, 0 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true","base.mul":"\nbase.mul( x, y )\n Multiplies two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.mul( -1.0, 5.0 )\n -5.0\n > v = base.mul( 2.0, 5.0 )\n 10.0\n > v = base.mul( 0.0, 5.0 )\n 0.0\n > v = base.mul( -0.0, 0.0 )\n -0.0\n > v = base.mul( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.div, base.sub\n","base.mulf":"\nbase.mulf( x, y )\n Multiplies two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.mulf( -1.0, 5.0 )\n -5.0\n > v = base.mulf( 2.0, 5.0 )\n 10.0\n > v = base.mulf( 0.0, 5.0 )\n 0.0\n > v = base.mulf( -0.0, 0.0 )\n -0.0\n > v = base.mulf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.divf, base.mul, base.subf\n","base.ndarray":"\nbase.ndarray( dtype, buffer, shape, strides, offset, order )\n Returns an ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n Returns\n -------\n ndarray: ndarray\n ndarray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.ndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nbase.ndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nbase.ndarray.prototype.order: string\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nbase.ndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nbase.ndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nbase.ndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nbase.ndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nbase.ndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nbase.ndarray.prototype.toLocaleString( [locales[, options]] )\n Serializes an ndarray as a locale-aware string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n Configuration options.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toLocaleString()\n '...'\n\n\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","base.ndarray.prototype.toLocaleString":"\nbase.ndarray.prototype.toLocaleString( [locales[, options]] )\n Serializes an ndarray as a locale-aware string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n Configuration options.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toLocaleString()\n '...'","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays, fcn )\n Applies a unary callback to elements in an input ndarray and assigns results\n to elements in an output ndarray.\n\n Each provided \"ndarray\" should be an object with the following properties:\n\n - dtype: data type.\n - data: data buffer.\n - shape: dimensions.\n - strides: stride lengths.\n - offset: index offset.\n - order: specifies whether an ndarray is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one input ndarray and one output ndarray.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n // Define ndarray data and meta data...\n > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dtype = 'float64';\n > var shape = [ 2, 2 ];\n > var sx = [ 2, 1 ];\n > var sy = [ 2, 1 ];\n > var ox = 0;\n > var oy = 0;\n > var order = 'row-major';\n\n // Using ndarrays...\n > var x = ndarray( dtype, xbuf, shape, sx, ox, order );\n > var y = ndarray( dtype, ybuf, shape, sy, oy, order );\n > base.ndarrayUnary( [ x, y ], base.abs );\n > y.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using minimal ndarray-like objects...\n > x = {\n ... 'dtype': dtype,\n ... 'data': xbuf,\n ... 'shape': shape,\n ... 'strides': sx,\n ... 'offset': ox,\n ... 'order': order\n ... };\n > y = {\n ... 'dtype': dtype,\n ... 'data': ybuf,\n ... 'shape': shape,\n ... 'strides': sy,\n ... 'offset': oy,\n ... 'order': order\n ... };\n > base.ndarrayUnary( [ x, y ], base.abs );\n > y.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n ndarrayDispatch\n","base.ndzeros":"\nbase.ndzeros( dtype, shape, order )\n Returns a zero-filled ndarray having a specified shape and data type.\n\n Parameters\n ----------\n dtype: string|DataType\n Underlying data type. Must be a numeric or \"generic\" data type.\n\n shape: ArrayLikeObject\n Array shape.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n base.ndarray, base.ndzerosLike\n","base.ndzerosLike":"\nbase.ndzerosLike( x )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n\n Along with data type, shape, and order, the function infers the \"class\" of\n the returned ndarray from the provided ndarray. For example, if provided a\n \"base\" ndarray, the function returns a base ndarray. If provided a non-base\n ndarray, the function returns a non-base ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n > var y = base.ndzerosLike( x )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n base.ndarray, base.ndzeros\n","base.negafibonacci":"\nbase.negafibonacci( n )\n Computes the nth negaFibonacci number.\n\n The negaFibonacci numbers follow the recurrence relation\n\n F_{n-2} = F_{n} - F_{n-1}\n\n with seed values F_0 = 0 and F_{-1} = 1.\n\n If `|n|` is greater than `78`, the function returns `NaN` as larger\n negaFibonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaFibonacci number.\n\n Examples\n --------\n > var y = base.negafibonacci( 0 )\n 0\n > y = base.negafibonacci( -1 )\n 1\n > y = base.negafibonacci( -2 )\n -1\n > y = base.negafibonacci( -3 )\n 2\n > y = base.negafibonacci( -4 )\n -3\n > y = base.negafibonacci( -79 )\n NaN\n > y = base.negafibonacci( -80 )\n NaN\n > y = base.negafibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.negalucas":"\nbase.negalucas( n )\n Computes the nth negaLucas number.\n\n The negaLucas numbers follow the recurrence relation\n\n L_{n-2} = L_{n} - L_{n-1}\n\n with seed values L_0 = 2 and L_{-1} = -1.\n\n If `|n|` is greater than `76`, the function returns `NaN` as larger\n negaLucas numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaLucas number.\n\n Examples\n --------\n > var y = base.negalucas( 0 )\n 2\n > y = base.negalucas( -1 )\n -1\n > y = base.negalucas( -2 )\n 3\n > y = base.negalucas( -3 )\n -4\n > y = base.negalucas( -4 )\n 7\n > y = base.negalucas( -77 )\n NaN\n > y = base.negalucas( -78 )\n NaN\n > y = base.negalucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.lucas, base.negafibonacci\n","base.nonfibonacci":"\nbase.nonfibonacci( n )\n Computes the nth non-Fibonacci number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Non-Fibonacci number.\n\n Examples\n --------\n > var v = base.nonfibonacci( 1 )\n 4\n > v = base.nonfibonacci( 2 )\n 6\n > v = base.nonfibonacci( 3 )\n 7\n > v = base.nonfibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.normalize":"\nbase.normalize( x )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalize( 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > var y = out[ 0 ];\n > var exponent = out[ 1 ];\n > var bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n true\n\n // Special cases:\n > out = base.normalize( 0.0 )\n [ 0.0, 0 ];\n > out = base.normalize( PINF )\n [ Infinity, 0 ]\n > out = base.normalize( NINF )\n [ -Infinity, 0 ]\n > out = base.normalize( NaN )\n [ NaN, 0 ]\n\n\nbase.normalize.assign( x, out, stride, offset )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 )\n > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n [ 1.4141234400356668e-303, -52 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef\n","base.normalize.assign":"\nbase.normalize.assign( x, out, stride, offset )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 )\n > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n [ 1.4141234400356668e-303, -52 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef","base.normalizef":"\nbase.normalizef( x )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: Array\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23 ]\n > var y = out[ 0 ];\n > var exp = out[ 1 ];\n > var bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n true\n\n // Special cases:\n > out = base.normalizef( FLOAT32_PINF )\n [ Infinity, 0 ]\n > out = base.normalizef( FLOAT32_NINF )\n [ -Infinity, 0 ]\n > out = base.normalizef( NaN )\n [ NaN, 0 ]\n\n\nbase.normalizef.assign( x, out, stride, offset )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > out = new Float32Array( 2 );\n > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize","base.normalizef.assign":"\nbase.normalizef.assign( x, out, stride, offset )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > out = new Float32Array( 2 );\n > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize","base.normalizeMultiSlice":"\nbase.normalizeMultiSlice( slice, shape, strict )\n Returns a normalized MultiSlice object.\n\n In strict mode, the function returns an error object if an input slice\n exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n Parameters\n ----------\n slice: MultiSlice\n Input slice object.\n\n shape: Array\n Maximum slice shape.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: MultiSlice|Object\n MultiSlice instance (or an error object).\n\n Examples\n --------\n > var s1 = new MultiSlice( 1, 3, null );\n > var s2 = base.normalizeMultiSlice( s1, [ 5, 5, 5 ], false );\n > var v = s2.data[ 0 ];\n > v.start\n 1\n > v.stop\n 2\n > v.step\n 1\n > v = s2.data[ 1 ];\n > v.start\n 3\n > v.stop\n 4\n > v.step\n 1\n > v = s2.data[ 2 ];\n > v.start\n 0\n > v.stop\n 5\n > v.step\n 1\n\n See Also\n --------\n base.normalizeSlice\n","base.normalizeSlice":"\nbase.normalizeSlice( slice, len, strict )\n Returns a normalized Slice object.\n\n In strict mode, the function returns an error object if an input slice\n exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n Parameters\n ----------\n slice: Slice\n Input slice object.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance (or an error object).\n\n Examples\n --------\n > var s1 = new Slice( 1, 10, 1 );\n > var s2 = base.normalizeSlice( s1, 5, false );\n > s2.start\n 1\n > s2.stop\n 5\n > s2.step\n 1\n > s1 = new Slice( -2, null, -1 );\n > s2 = base.normalizeSlice( s1, 10, false );\n > s2.start\n 8\n > s2.stop\n null\n > s2.step\n -1\n\n See Also\n --------\n base.normalizeMultiSlice\n","base.normhermitepoly":"\nbase.normhermitepoly( n, x )\n Evaluates a normalized Hermite polynomial using double-precision floating-\n point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.normhermitepoly( 1, 0.5 )\n 0.5\n > y = base.normhermitepoly( -1, 0.5 )\n NaN\n > y = base.normhermitepoly( 0, 0.5 )\n 1.0\n > y = base.normhermitepoly( 2, 0.5 )\n -0.75\n\n\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var f = base.normhermitepoly.factory( 2 );\n > var v = f( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var f = base.normhermitepoly.factory( 2 );\n > var v = f( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly","base.pascalcase":"\nbase.pascalcase( str )\n Converts a string to Pascal case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Pascal-cased string.\n\n Examples\n --------\n > var out = base.pascalcase( 'Hello World!' )\n 'HelloWorld'\n > out = base.pascalcase( 'beep boop' )\n 'BeepBoop'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.uppercase","base.pdiff":"\nbase.pdiff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdiff( 5.9, 3.14 )\n 2.76\n > v = base.pdiff( 3.14, 4.2 )\n 0.0\n > v = base.pdiff( 3.14, NaN )\n NaN\n > v = base.pdiff( -0.0, +0.0 )\n +0.0\n\n","base.pdifff":"\nbase.pdifff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdifff( 5.9, 3.15 )\n 2.75\n > v = base.pdifff( 3.14, 4.2 )\n 0.0\n > v = base.pdifff( 3.14, NaN )\n NaN\n > v = base.pdifff( -0.0, +0.0 )\n +0.0\n\n See Also\n --------\n base.pdiff\n","base.percentEncode":"\nbase.percentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = base.percentEncode( '☃' )\n '%E2%98%83'\n\n","base.polygamma":"\nbase.polygamma( n, x )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n\n If `n` is not a nonnegative integer, the function returns `NaN`.\n\n If `x` is zero or a negative odd integer, the function returns `+Infinity`.\n If `x` is a negative even integer, the function returns `NaN`.\n\n If provided `NaN` as either parameter, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Derivative order.\n\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.polygamma( 3, 1.2 )\n ~3.245\n > v = base.polygamma( 5, 1.2 )\n ~41.39\n > v = base.polygamma( 3, -4.9 )\n ~60014.239\n > v = base.polygamma( -1, 5.3 )\n NaN\n > v = base.polygamma( 2, -1.0 )\n Infinity\n\n See Also\n --------\n base.trigamma, base.digamma, base.gamma\n","base.pow":"\nbase.pow( b, x )\n Evaluates the exponential function `bˣ`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.pow( 2.0, 3.0 )\n 8.0\n > y = base.pow( 4.0, 0.5 )\n 2.0\n > y = base.pow( 100.0, 0.0 )\n 1.0\n > y = base.pow( PI, 5.0 )\n ~306.0197\n > y = base.pow( PI, -0.2 )\n ~0.7954\n > y = base.pow( NaN, 3.0 )\n NaN\n > y = base.pow( 5.0, NaN )\n NaN\n > y = base.pow( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.powm1\n","base.powm1":"\nbase.powm1( b, x )\n Evaluates `bˣ - 1`.\n\n When `b` is close to `1` and/or `x` is small, this function is more accurate\n than naively computing `bˣ` and subtracting `1`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.powm1( 2.0, 3.0 )\n 7.0\n > y = base.powm1( 4.0, 0.5 )\n 1.0\n > y = base.powm1( 0.0, 100.0 )\n -1.0\n > y = base.powm1( 100.0, 0.0 )\n 0.0\n > y = base.powm1( 0.0, 0.0 )\n 0.0\n > y = base.powm1( PI, 5.0 )\n ~305.0197\n > y = base.powm1( NaN, 3.0 )\n NaN\n > y = base.powm1( 5.0, NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.rad2deg":"\nbase.rad2deg( x )\n Converts an angle from radians to degrees.\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2deg( PI/2.0 )\n 90.0\n > d = base.rad2deg( -PI/4.0 )\n -45.0\n > d = base.rad2deg( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2deg( PI/6.0 )\n 29.999999999999996\n\n See Also\n --------\n base.deg2rad\n","base.rad2degf":"\nbase.rad2degf( x )\n Converts an angle from radians to degrees (single-precision).\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2degf( 3.141592653589793 / 2.0 )\n 90.0\n > d = base.rad2degf( -3.141592653589793 / 4.0 )\n -45.0\n > d = base.rad2degf( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2degf( 3.141592653589793 / 6.0 )\n 30.000001907348633\n\n See Also\n --------\n base.rad2deg\n","base.ramp":"\nbase.ramp( x )\n Evaluates the ramp function.\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ramp( 3.14 )\n 3.14\n > y = base.ramp( -3.14 )\n 0.0\n\n See Also\n --------\n base.heaviside\n","base.rampf":"\nbase.rampf( x )\n Evaluates the ramp function (single-precision).\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.rampf( 3.14 )\n 3.14\n > y = base.rampf( -3.14 )\n 0.0\n\n See Also\n --------\n base.ramp\n","base.random.arcsine":"\nbase.random.arcsine( a, b )\n Returns a pseudorandom number drawn from an arcsine distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 5.0 )\n \n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n \n\n\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'\n\n\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n ","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;","base.random.arcsine.state":"\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n ","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta","base.random.bernoulli":"\nbase.random.bernoulli( p )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n ","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial","base.random.beta":"\nbase.random.beta( α, β )\n Returns a pseudorandom number drawn from a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'\n\n\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.beta, random.iterators.beta, random.streams.beta\n","base.random.beta.factory":"\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.beta.NAME":"\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;","base.random.beta.seed":"\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;","base.random.beta.state":"\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n ","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.beta, random.iterators.beta, random.streams.beta","base.random.betaprime":"\nbase.random.betaprime( α, β )\n Returns a pseudorandom number drawn from a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'\n\n\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.betaprime, random.iterators.betaprime, random.streams.betaprime\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;","base.random.betaprime.state":"\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n ","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.betaprime, random.iterators.betaprime, random.streams.betaprime","base.random.binomial":"\nbase.random.binomial( n, p )\n Returns a pseudorandom number drawn from a binomial distribution.\n\n If `n` is not a positive integer or `p` is not a probability, the function\n returns `NaN`.\n\n If `n` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'\n\n\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.binomial, random.iterators.binomial, random.streams.binomial\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;","base.random.binomial.seed":"\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;","base.random.binomial.state":"\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n ","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.binomial, random.iterators.binomial, random.streams.binomial","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'\n\n\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.boxMuller, random.streams.boxMuller\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n ","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.boxMuller, random.streams.boxMuller","base.random.cauchy":"\nbase.random.cauchy( x0, Ɣ )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n\n If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'\n\n\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cauchy, random.iterators.cauchy, random.streams.cauchy\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;","base.random.cauchy.state":"\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n ","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cauchy, random.iterators.cauchy, random.streams.cauchy","base.random.chi":"\nbase.random.chi( k )\n Returns a pseudorandom number drawn from a chi distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'\n\n\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chi, random.iterators.chi, random.streams.chi\n","base.random.chi.factory":"\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();","base.random.chi.NAME":"\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;","base.random.chi.seed":"\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;","base.random.chi.state":"\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n ","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chi, random.iterators.chi, random.streams.chi","base.random.chisquare":"\nbase.random.chisquare( k )\n Returns a pseudorandom number drawn from a chi-square distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'\n\n\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chisquare, random.iterators.chisquare, random.streams.chisquare\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;","base.random.chisquare.state":"\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n ","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chisquare, random.iterators.chisquare, random.streams.chisquare","base.random.cosine":"\nbase.random.cosine( μ, s )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'\n\n\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cosine, random.iterators.cosine, random.streams.cosine\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;","base.random.cosine.seed":"\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;","base.random.cosine.state":"\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n ","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cosine, random.iterators.cosine, random.streams.cosine","base.random.discreteUniform":"\nbase.random.discreteUniform( a, b )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();\n\n\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n ","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform","base.random.erlang":"\nbase.random.erlang( k, λ )\n Returns a pseudorandom number drawn from an Erlang distribution.\n\n If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'\n\n\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.erlang, random.iterators.erlang, random.streams.erlang\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;","base.random.erlang.seed":"\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;","base.random.erlang.state":"\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n ","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.erlang, random.iterators.erlang, random.streams.erlang","base.random.exponential":"\nbase.random.exponential( λ )\n Returns a pseudorandom number drawn from an exponential distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'\n\n\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.exponential, random.iterators.exponential, random.streams.exponential\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;","base.random.exponential.seed":"\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;","base.random.exponential.state":"\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n ","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.exponential, random.iterators.exponential, random.streams.exponential","base.random.f":"\nbase.random.f( d1, d2 )\n Returns a pseudorandom number drawn from an F distribution.\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'\n\n\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.f, random.iterators.f, random.streams.f\n","base.random.f.factory":"\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.f.NAME":"\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'","base.random.f.PRNG":"\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;","base.random.f.seed":"\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;","base.random.f.seedLength":"\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;","base.random.f.state":"\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n ","base.random.f.stateLength":"\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;","base.random.f.byteLength":"\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;","base.random.f.toJSON":"\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.f, random.iterators.f, random.streams.f","base.random.frechet":"\nbase.random.frechet( α, s, m )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'\n\n\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.frechet, random.iterators.frechet, random.streams.frechet\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;","base.random.frechet.seed":"\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;","base.random.frechet.state":"\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n ","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.frechet, random.iterators.frechet, random.streams.frechet","base.random.gamma":"\nbase.random.gamma( α, β )\n Returns a pseudorandom number drawn from a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'\n\n\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gamma, random.iterators.gamma, random.streams.gamma\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;","base.random.gamma.seed":"\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;","base.random.gamma.state":"\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n ","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gamma, random.iterators.gamma, random.streams.gamma","base.random.geometric":"\nbase.random.geometric( p )\n Returns a pseudorandom number drawn from a geometric distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'\n\n\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.geometric, random.iterators.geometric, random.streams.geometric\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;","base.random.geometric.seed":"\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;","base.random.geometric.state":"\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n ","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.geometric, random.iterators.geometric, random.streams.geometric","base.random.gumbel":"\nbase.random.gumbel( μ, β )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n\n If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'\n\n\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gumbel, random.iterators.gumbel, random.streams.gumbel\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;","base.random.gumbel.state":"\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n ","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gumbel, random.iterators.gumbel, random.streams.gumbel","base.random.hypergeometric":"\nbase.random.hypergeometric( N, K, n )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n returns `NaN`.\n\n If `n > N` or `K > N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();\n\n\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n ","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.improvedZiggurat, random.streams.improvedZiggurat\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n ","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.improvedZiggurat, random.streams.improvedZiggurat","base.random.invgamma":"\nbase.random.invgamma( α, β )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'\n\n\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.invgamma, random.iterators.invgamma, random.streams.invgamma\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;","base.random.invgamma.state":"\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n ","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.invgamma, random.iterators.invgamma, random.streams.invgamma","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a, b )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n ","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy","base.random.laplace":"\nbase.random.laplace( μ, b )\n Returns a pseudorandom number drawn from a Laplace distribution.\n\n If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'\n\n\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.laplace, random.iterators.laplace, random.streams.laplace\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;","base.random.laplace.seed":"\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;","base.random.laplace.state":"\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n ","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.laplace, random.iterators.laplace, random.streams.laplace","base.random.levy":"\nbase.random.levy( μ, c )\n Returns a pseudorandom number drawn from a Lévy distribution.\n\n If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'\n\n\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.levy, random.iterators.levy, random.streams.levy\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.levy.NAME":"\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;","base.random.levy.seed":"\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;","base.random.levy.state":"\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n ","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.levy, random.iterators.levy, random.streams.levy","base.random.logistic":"\nbase.random.logistic( μ, s )\n Returns a pseudorandom number drawn from a logistic distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'\n\n\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.logistic, random.iterators.logistic, random.streams.logistic\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;","base.random.logistic.seed":"\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;","base.random.logistic.state":"\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n ","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.logistic, random.iterators.logistic, random.streams.logistic","base.random.lognormal":"\nbase.random.lognormal( μ, σ )\n Returns a pseudorandom number drawn from a lognormal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'\n\n\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.lognormal, random.iterators.lognormal, random.streams.lognormal\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;","base.random.lognormal.state":"\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n ","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.lognormal, random.iterators.lognormal, random.streams.lognormal","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838\n\n\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'\n\n\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1\n\n\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646\n\n\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();","base.random.minstd.factory":"\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646","base.random.minstd.seed":"\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;","base.random.minstd.state":"\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n ","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654\n\n\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1\n\n\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646\n\n\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n ","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775\n\n\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'\n\n\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 0\n\n\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295\n\n\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 0","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;","base.random.mt19937.state":"\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n ","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r, p )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n\n If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n If `r` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n ","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial","base.random.normal":"\nbase.random.normal( μ, σ )\n Returns a pseudorandom number drawn from a normal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'\n\n\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.normal, random.iterators.normal, random.streams.normal\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.normal.NAME":"\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;","base.random.normal.seed":"\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;","base.random.normal.state":"\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n ","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.normal, random.iterators.normal, random.streams.normal","base.random.pareto1":"\nbase.random.pareto1( α, β )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.pareto1, random.iterators.pareto1, random.streams.pareto1\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;","base.random.pareto1.state":"\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n ","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.pareto1, random.iterators.pareto1, random.streams.pareto1","base.random.poisson":"\nbase.random.poisson( λ )\n Returns a pseudorandom number drawn from a Poisson distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'\n\n\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.poisson, random.iterators.poisson, random.streams.poisson\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;","base.random.poisson.seed":"\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;","base.random.poisson.state":"\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n ","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.poisson, random.iterators.poisson, random.streams.poisson","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();\n\n\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'\n\n\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937\n","base.random.randi.factory":"\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();","base.random.randi.NAME":"\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;","base.random.randi.MIN":"\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;","base.random.randi.MAX":"\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;","base.random.randi.seed":"\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;","base.random.randi.state":"\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n ","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'\n\n\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu\n","base.random.randn.factory":"\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();","base.random.randn.NAME":"\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;","base.random.randn.seed":"\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;","base.random.randn.state":"\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n ","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number on the interval `[0,1)`.\n\n Examples\n --------\n > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'\n\n\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn\n","base.random.randu.factory":"\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();","base.random.randu.NAME":"\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;","base.random.randu.MIN":"\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;","base.random.randu.MAX":"\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;","base.random.randu.seed":"\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;","base.random.randu.state":"\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n ","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn","base.random.rayleigh":"\nbase.random.rayleigh( σ )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n ","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh","base.random.t":"\nbase.random.t( v )\n Returns a pseudorandom number drawn from a Student's t distribution.\n\n If `v <= 0` or `v` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'\n\n\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.t, random.iterators.t, random.streams.t\n","base.random.t.factory":"\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();","base.random.t.NAME":"\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'","base.random.t.PRNG":"\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;","base.random.t.seed":"\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;","base.random.t.seedLength":"\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;","base.random.t.state":"\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n ","base.random.t.stateLength":"\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;","base.random.t.byteLength":"\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;","base.random.t.toJSON":"\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.t, random.iterators.t, random.streams.t","base.random.triangular":"\nbase.random.triangular( a, b, c )\n Returns a pseudorandom number drawn from a triangular distribution.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'\n\n\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.triangular, random.iterators.triangular, random.streams.triangular\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;","base.random.triangular.seed":"\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;","base.random.triangular.state":"\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n ","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.triangular, random.iterators.triangular, random.streams.triangular","base.random.uniform":"\nbase.random.uniform( a, b )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support (inclusive).\n\n b: number\n Maximum support (exclusive).\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'\n\n\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;","base.random.uniform.seed":"\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;","base.random.uniform.state":"\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n ","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu","base.random.weibull":"\nbase.random.weibull( k, λ )\n Returns a pseudorandom number drawn from a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'\n\n\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.weibull, random.iterators.weibull, random.streams.weibull\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;","base.random.weibull.seed":"\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;","base.random.weibull.state":"\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n ","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.weibull, random.iterators.weibull, random.streams.weibull","base.rcbrt":"\nbase.rcbrt( x )\n Computes the reciprocal cube root of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal cube root.\n\n Examples\n --------\n > var y = base.rcbrt( 8.0 )\n 0.5\n > y = base.rcbrt( 1000.0 )\n 0.1\n > y = base.rcbrt( 0.0 )\n Infinity\n > y = base.rcbrt( PINF )\n 0.0\n > y = base.rcbrt( -8.0 )\n -0.5\n > y = base.rcbrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt\n","base.rcbrtf":"\nbase.rcbrtf( x )\n Computes the reciprocal cube root of a single-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal cube root.\n\n Examples\n --------\n > var y = base.rcbrtf( 8.0 )\n 0.5\n > y = base.rcbrtf( 1000.0 )\n ~0.1\n > y = base.rcbrtf( 0.0 )\n Infinity\n > y = base.rcbrtf( PINF )\n 0.0\n > y = base.rcbrtf( -8.0 )\n -0.5\n > y = base.rcbrtf( NaN )\n NaN\n\n See Also\n --------\n base.rcbrt, base.cbrtf\n","base.reldiff":"\nbase.reldiff( x, y[, scale] )\n Computes the relative difference of two real numbers.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference.\n\n Examples\n --------\n > var d = base.reldiff( 2.0, 5.0 )\n 0.6\n > d = base.reldiff( -1.0, 3.14 )\n ~1.318\n > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'max' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'min' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n 2.0\n > d = base.reldiff( -2.0, 5.0, 'mean' )\n ~4.667\n > d = base.reldiff( -2.0, 5.0, 'x' )\n 3.5\n > d = base.reldiff( 5.0, -2.0, 'x' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'y' )\n 1.4\n > d = base.reldiff( 5.0, -2.0, 'y' )\n 3.5\n\n // Custom scale function:\n > function scale( x, y ) {\n ... var s;\n ...\n ... x = base.abs( x );\n ... y = base.abs( y );\n ...\n ... // Maximum absolute value:\n ... s = (x < y ) ? y : x;\n ...\n ... // Scale in units of epsilon:\n ... return s * EPS;\n ... };\n > d = base.reldiff( 12.15, 12.149999999999999, scale )\n ~0.658\n\n See Also\n --------\n base.absdiff, base.epsdiff\n","base.removeFirst":"\nbase.removeFirst( str, n )\n Removes the first `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirst( 'beep', 1 )\n 'eep'\n > out = base.removeFirst( 'Boop', 1 )\n 'oop'\n > out = base.removeFirst( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeFirstGraphemeCluster, base.removeLast\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str, n )\n Removes the first `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirstCodePoint( 'beep', 1 )\n 'eep'\n > out = base.removeFirstCodePoint( 'Boop', 1 )\n 'oop'\n > out = base.removeFirstCodePoint( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeLastCodePoint, base.removeFirstGraphemeCluster, base.removeFirst\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str, n )\n Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirstGraphemeCluster( 'beep', 1 )\n 'eep'\n > out = base.removeFirstGraphemeCluster( 'Boop', 1 )\n 'oop'\n > out = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLast":"\nbase.removeLast( str, n )\n Removes the last `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLast( 'beep', 1 )\n 'bee'\n > out = base.removeLast( 'Boop', 1 )\n 'Boo'\n > out = base.removeLast( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeLastCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str, n )\n Removes the last `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLastCodePoint( 'beep', 1 )\n 'bee'\n > out = base.removeLastCodePoint( 'Boop', 1 )\n 'Boo'\n > out = base.removeLastCodePoint( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeLast\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str, n )\n Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLastGraphemeCluster( 'beep', 1 )\n 'bee'\n > out = base.removeLastGraphemeCluster( 'Boop', 1 )\n 'Boo'\n > out = base.removeLastGraphemeCluster( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastCodePoint, base.removeLast\n","base.rempio2":"\nbase.rempio2( x, y )\n Computes `x - nπ/2 = r`.\n\n The function returns `n` and stores the remainder `r` as the two numbers\n `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n For input values larger than `2^20 * π/2` in magnitude, the function only\n returns the last three binary digits of `n` and not the full result.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: Array|TypedArray|Object\n Remainder elements.\n\n Returns\n -------\n n: integer\n Factor of `π/2`.\n\n Examples\n --------\n > var y = [ 0.0, 0.0 ];\n > var n = base.rempio2( 128.0, y )\n 81\n > var y1 = y[ 0 ]\n ~0.765\n > var y2 = y[ 1 ]\n ~3.618e-17\n\n\n","base.repeat":"\nbase.repeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = base.repeat( 'a', 5 )\n 'aaaaa'\n > out = base.repeat( '', 100 )\n ''\n > out = base.repeat( 'beep', 0 )\n ''\n\n","base.replace":"\nbase.replace( str, search, newval )\n Replaces search occurrences with a replacement string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > var out = base.replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = base.replace( 'beep', /e/, 'o' )\n 'boep'\n\n See Also\n --------\n base.replaceAfter, base.replaceBefore, base.replaceAfterLast, base.replaceBeforeLast\n","base.replaceAfter":"\nbase.replaceAfter( str, search, replacement, fromIndex )\n Replaces the substring after the first occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\n 'beep foo'\n > out = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\n 'beep bofoo'\n > out = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\n 'Hello Wofoo'\n > out = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n 'beep boop beepfoo'\n\n See Also\n --------\n base.replaceAfterLast, base.replaceBefore, base.replaceBeforeLast\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str, search, replacement, fromIndex )\n Replaces the substring after the last occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n The function scans an input string from the starting index to the beginning\n of the string (i.e., backward).\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.replaceAfterLast( str, ' ', 'foo', str.length )\n 'beep foo'\n > out = base.replaceAfterLast( str, 'o', 'foo', str.length )\n 'beep boofoo'\n > out = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n 'Hellofoo'\n\n See Also\n --------\n base.replaceAfter, base.replaceBeforeLast, base.replaceBefore\n","base.replaceBefore":"\nbase.replaceBefore( str, search, replacement, fromIndex )\n Replaces the substring before the first occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\n 'foo boop'\n > out = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n 'foooop'\n\n See Also\n --------\n base.replaceAfter, base.replaceBeforeLast, base.replaceAfterLast\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str, search, replacement, fromIndex )\n Replaces the substring before the last occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n The function scans an input string from the starting index to the beginning\n of the string (i.e., backward).\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\n 'foo boop'\n > out = base.replaceBeforeLast( str, 'o', 'foo', str.length )\n 'fooop'\n > out = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n 'fooo World!'\n\n See Also\n --------\n base.replaceAfterLast, base.replaceAfter, base.replaceBefore\n","base.reverse":"\nbase.reverse( str )\n Reverses the UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverse( 'beep' )\n 'peeb'\n > out = base.reverse( 'Boop' )\n 'pooB'\n > out = base.reverse( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseCodePoints, base.reverseGraphemeClusters\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str )\n Reverses the Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverseCodePoints( 'beep' )\n 'peeb'\n > out = base.reverseCodePoints( 'Boop' )\n 'pooB'\n > out = base.reverseCodePoints( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseGraphemeClusters, base.reverse\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str )\n Reverses the grapheme clusters (i.e., user-perceived characters) of a\n string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverseGraphemeClusters( 'beep' )\n 'peeb'\n > out = base.reverseGraphemeClusters( 'Boop' )\n 'pooB'\n > out = base.reverseGraphemeClusters( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseCodePoints, base.reverse\n","base.rightPad":"\nbase.rightPad( str, len, pad )\n Right pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string\n String used to pad.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = base.rightPad( 'a', 5, ' ' )\n 'a '\n > out = base.rightPad( 'beep', 10, 'b' )\n 'beepbbbbbb'\n > out = base.rightPad( 'boop', 12, 'beep' )\n 'boopbeepbeep'\n\n See Also\n --------\n base.leftPad\n","base.rightTrim":"\nbase.rightTrim( str )\n Trims whitespace from the end of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.rightTrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n See Also\n --------\n base.leftTrim\n","base.risingFactorial":"\nbase.risingFactorial( x, n )\n Computes the rising factorial of `x` and `n`.\n\n If provided a non-integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.risingFactorial( 0.9, 5 )\n ~94.766\n > v = base.risingFactorial( -9.0, 3 )\n -504.0\n > v = base.risingFactorial( 0.0, 2 )\n 0.0\n > v = base.risingFactorial( 3.0, -2 )\n 0.5\n\n See Also\n --------\n base.fallingFactorial\n","base.rotl32":"\nbase.rotl32( x, shift )\n Performs a bitwise rotation to the left.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 2147483649;\n > var bStr = base.toBinaryStringUint32( x )\n '10000000000000000000000000000001'\n > var y = base.rotl32( x, 10 )\n 1536\n > bstr = base.toBinaryStringUint32( y )\n '00000000000000000000011000000000'\n\n See Also\n --------\n base.rotr32\n","base.rotr32":"\nbase.rotr32( x, shift )\n Performs a bitwise rotation to the right.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 1;\n > var bStr = base.toBinaryStringUint32( x )\n '00000000000000000000000000000001'\n > var y = base.rotr32( x, 10 )\n 4194304\n > bstr = base.toBinaryStringUint32( y )\n '00000000010000000000000000000000'\n\n See Also\n --------\n base.rotl32\n","base.round":"\nbase.round( x )\n Rounds a numeric value to the nearest integer.\n\n Ties are rounded toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round( 3.14 )\n 3.0\n > y = base.round( -4.2 )\n -4.0\n > y = base.round( -4.6 )\n -5.0\n > y = base.round( 9.5 )\n 10.0\n > y = base.round( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.roundn, base.trunc\n","base.round2":"\nbase.round2( x )\n Rounds a numeric value to the nearest power of two on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round2( 3.14 )\n 4.0\n > y = base.round2( -4.2 )\n -4.0\n > y = base.round2( -4.6 )\n -4.0\n > y = base.round2( 9.5 )\n 8.0\n > y = base.round2( 13.0 )\n 16.0\n > y = base.round2( -13.0 )\n -16.0\n > y = base.round2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round, base.round10\n","base.round10":"\nbase.round10( x )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round10( 3.14 )\n 1.0\n > y = base.round10( -4.2 )\n -1.0\n > y = base.round10( -4.6 )\n -1.0\n > y = base.round10( 9.5 )\n 10.0\n > y = base.round10( 13.0 )\n 10.0\n > y = base.round10( -13.0 )\n -10.0\n > y = base.round10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round, base.round2\n","base.roundb":"\nbase.roundb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundb( 3.14159, -2, 10 )\n 3.14\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.roundb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two:\n > y = base.roundb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.round, base.roundn\n","base.roundn":"\nbase.roundn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundn( 3.14159, -2 )\n 3.14\n\n // If `n = 0`, standard round behavior:\n > y = base.roundn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.roundn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.round, base.roundb\n","base.roundsd":"\nbase.roundsd( x, n[, b] )\n Rounds a double-precision floating-point number to the nearest value with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.roundsd( 3.14159, 3 )\n 3.14\n > y = base.roundsd( 3.14159, 1 )\n 3.0\n > y = base.roundsd( 12368.0, 2 )\n 12000.0\n > y = base.roundsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.round, base.truncsd\n","base.rsqrt":"\nbase.rsqrt( x )\n Computes the reciprocal square root of a double-precision floating-point\n number.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrt( 4.0 )\n 0.5\n > y = base.rsqrt( 100.0 )\n 0.1\n > y = base.rsqrt( 0.0 )\n Infinity\n > y = base.rsqrt( Infinity )\n 0.0\n > y = base.rsqrt( -4.0 )\n NaN\n > y = base.rsqrt( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.rsqrtf":"\nbase.rsqrtf( x )\n Computes the reciprocal square root of a single-precision floating-point\n number.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrtf( 4.0 )\n 0.5\n > y = base.rsqrtf( 0.0 )\n Infinity\n > y = base.rsqrtf( Infinity )\n 0.0\n > y = base.rsqrtf( -4.0 )\n NaN\n > y = base.rsqrtf( NaN )\n NaN\n\n See Also\n --------\n base.rsqrt, base.sqrtf\n","base.sargs2multislice":"\nbase.sargs2multislice( str )\n Creates a MultiSlice object from a comma-separated list of string-serialized\n MultiSlice constructor arguments.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string containing constructor arguments.\n\n Returns\n -------\n s: MultiSlice|null\n MultiSlice instance (or null).\n\n Examples\n --------\n > var s = new base.sargs2multislice( 'null,null,null' );\n > s.data\n [ null, null, null ]\n > s = new base.sargs2multislice( '10,Slice(0,10,1),null' );\n > s.data\n [ 10, , null ]\n\n See Also\n --------\n base.args2multislice, base.seq2multislice\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value, dtype, order )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n\n If `value` is a number and `dtype` is a complex number data type, the\n function returns a zero-dimensional ndarray containing a complex number\n whose real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n dtype: string|DataType\n Data type.\n\n order: string\n Memory layout (either 'row-major' or 'column-major').\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\n \n > var sh = ndarrayShape( x )\n []\n > var v = x.get()\n 1.0\n\n See Also\n --------\n array, base.ndarray, ndarray\n","base.secd":"\nbase.secd( x )\n Computes the secant of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Secant.\n\n Examples\n --------\n > var y = base.secd( 1.0 )\n ~1.0\n > y = base.secd( PI )\n ~1.0\n > y = base.secd( -PI )\n ~1.0\n > y = base.secd( NaN )\n NaN\n\n See Also\n --------\n base.cosd, base.cos\n","base.seq2multislice":"\nbase.seq2multislice( str, shape, strict )\n Converts a multidimensional subsequence string to a MultiSlice object.\n\n A multidimensional subsequence string is a comma-separated list of single-\n dimension indexing expressions (i.e., integers and/or subsequence strings).\n\n For example, the following\n\n 2\n :\n 2:\n :10\n 2:10\n ::-1\n 10:2:-1\n :2:\n 2:10:\n 2::2\n :10:2\n :, :, :\n 1, 2, 3\n 0:10, 1:20:2, ::-1\n ...\n :, ..., 2\n\n are all valid multidimensional subsequence strings.\n\n Providing a single nonnegative integer `i` as a single-dimension index\n indexes the same elements as the subsequence `i:i+1`.\n\n Providing a single negative integer `i` as a single-dimension index indexes\n the same elements as the subsequence `n+i:n+i+i`, where `n` is the dimension\n size.\n\n While integers index the same elements as equivalent subsequences, providing\n an integer as a single-dimension index indicates to reduce the number of\n dimensions by one (e.g., if the provided shape corresponds to an array\n having rank 2, then rank(A)-1 == rank(A['0,:'])).\n\n In contrast, providing a subsequence indicates to retain a respective\n dimension (e.g., if the provided shape corresponds to an array having rank\n 2, then rank(A) == rank(A[':,:'])).\n\n A multidimensional subsequence string can only contain **one** ellipsis\n ('...') operator. An ellipsis indicates to apply ':' to each dimension\n necessary to index all dimensions (e.g., if A has rank 4, A['1:,...,2:5']\n equals A['1:,:,:,2:5']).\n\n Except in the case of providing a single ellipsis, the number of single-\n dimension indexing expressions must equal the number of dimensions in the\n input shape.\n\n The function returns an error object if provided an invalid subsequence\n string.\n\n In strict mode, the function returns an error object if a single-dimension\n index expression which exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n increment.\n - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n exceeding index bounds.\n - ERR_SLICE_TOO_MANY_DIMENSIONS: a subsequence string has more dimensions\n than the provided shape.\n - ERR_SLICE_INSUFFICIENT_DIMENSIONS: a subsequence string has too few\n dimensions.\n - ERR_SLICE_INVALID_ELLIPSIS: a subsequence string must only contain at most\n one ellipsis.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n shape: Array\n Maximum allowed slice shape.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: MultiSlice|Object\n MultiSlice instance or an error object.\n\n Examples\n --------\n > var s = new base.seq2multislice( '1:10', [ 10 ], false );\n > s.data\n [ ]\n > s = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\n > s.data\n [ 4, , ]\n\n See Also\n --------\n base.seq2slice, base.sargs2multislice\n","base.seq2slice":"\nbase.seq2slice( str, len, strict )\n Converts a subsequence string to a Slice object.\n\n A subsequence string has the following format:\n\n ::\n\n If an increment is not specified, the default increment is one. An increment\n of zero is not allowed.\n\n The start index is inclusive.\n\n The stop index is exclusive.\n\n Both start and stop indices are optional. If not provided, the start and\n stop indices default to index extremes. Which extremes correspond to which\n index depends on whether the increment is positive or negative.\n\n Both start and stop indices can be negative; in which case, the\n corresponding index is resolved by subtracting the respective value from the\n provided length.\n\n Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n 'end-3:', etc), which supports basic subtraction and division.\n\n The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n exception is when performing a division operation when the increment is less\n than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n user expectations when 'end/d' equals a whole number and slicing from right-\n to-left. The result from a division operation is rounded down to the nearest\n integer value.\n\n In non-strict mode, the resolved slice start is clamped to the slice index\n bounds [0, len).\n\n In non-strict mode, Tte resolved slice end is upper bound clamped to the\n provided length (i.e., one greater than the last possible index).\n\n When the increment is negative, the resolved slice end value may be `null`,\n thus indicating that a non-empty slice should include the first index.\n\n The function ensures that results satisfy the convention that ':n' combined\n with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n When the provided length is zero, the function always returns a slice object\n equivalent to '0:0:'.\n\n The function returns an error object if provided an invalid subsequence\n string.\n\n In strict mode, the function returns an error object if provided a\n subsequence string which exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n increment.\n - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n exceeding index bounds.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance or an error object.\n\n Examples\n --------\n > var s = new base.seq2slice( '1:10', 10, false );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new base.seq2slice( '2:5:2', 10, false );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n base.seq2multislice, base.slice2seq\n","base.setHighWord":"\nbase.setHighWord( x, high )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n high: integer\n Unsigned 32-bit integer to replace the higher order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same lower order word as `x`.\n\n Examples\n --------\n // Set the higher order bits of `+infinity` to return `1`:\n > var high = 1072693248 >>> 0;\n > var y = base.setHighWord( PINF, high )\n 1.0\n\n See Also\n --------\n base.getHighWord, base.setLowWord\n","base.setLowWord":"\nbase.setLowWord( x, low )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n\n Setting the lower order bits of `NaN` or positive or negative infinity will\n return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n all ones and whose fraction can be any bit sequence except all zeros.\n Positive and negative infinity are defined as doubles with an exponent bit\n sequence equal to all ones and a fraction equal to all zeros. Hence,\n changing the less significant bits of positive and negative infinity\n converts each value to `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n low: integer\n Unsigned 32-bit integer to replace the lower order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same higher order word as `x`.\n\n Examples\n --------\n > var low = 5 >>> 0;\n > var x = 3.14e201;\n > var y = base.setLowWord( x, low )\n 3.139998651394392e+201\n\n // Special cases:\n > var low = 12345678;\n > var y = base.setLowWord( PINF, low )\n NaN\n > y = base.setLowWord( NINF, low )\n NaN\n > y = base.setLowWord( NaN, low )\n NaN\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.sici":"\nbase.sici( x )\n Computes the sine and cosine integrals.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n Sine and cosine integrals.\n\n Examples\n --------\n > var y = base.sici( 3.0 )\n [ ~1.849, ~0.12 ]\n > y = base.sici( 0.0 )\n [ 0.0, -Infinity ]\n > y = base.sici( -9.0 )\n [ ~-1.665, ~0.055 ]\n > y = base.sici( NaN )\n [ NaN, NaN ]\n\n\nbase.sici.assign( x, out, stride, offset )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.sici.assign( 3.0, out, 1, 0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true\n","base.sici.assign":"\nbase.sici.assign( x, out, stride, offset )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.sici.assign( 3.0, out, 1, 0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true","base.signbit":"\nbase.signbit( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbit( 4.0 )\n false\n > bool = base.signbit( -9.14e-34 )\n true\n > bool = base.signbit( 0.0 )\n false\n > bool = base.signbit( -0.0 )\n true\n\n See Also\n --------\n base.signbitf\n","base.signbitf":"\nbase.signbitf( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\n false\n > bool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\n true\n > bool = base.signbitf( 0.0 )\n false\n > bool = base.signbitf( -0.0 )\n true\n\n See Also\n --------\n base.signbit\n","base.significandf":"\nbase.significandf( x )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Significand.\n\n Examples\n --------\n > var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\n 4293751\n > s = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\n 5288021\n > s = base.significandf( base.float64ToFloat32( -3.14 ) )\n 4781507\n > s = base.significandf( 0.0 )\n 0\n > s = base.significandf( NaN )\n 4194304\n\n","base.signum":"\nbase.signum( x )\n Evaluates the signum function for a double-precision floating-point number.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signum( -5.0 )\n -1.0\n > sign = base.signum( 5.0 )\n 1.0\n > sign = base.signum( -0.0 )\n -0.0\n > sign = base.signum( 0.0 )\n 0.0\n > sign = base.signum( NaN )\n NaN\n\n","base.signumf":"\nbase.signumf( x )\n Evaluates the signum function for a single-precision floating-point number.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signumf( -5.0 )\n -1.0\n > sign = base.signumf( 5.0 )\n 1.0\n > sign = base.signumf( -0.0 )\n -0.0\n > sign = base.signumf( 0.0 )\n 0.0\n > sign = base.signumf( NaN )\n NaN\n\n See Also\n --------\n base.signum\n","base.sin":"\nbase.sin( x )\n Computes the sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Sine.\n\n Examples\n --------\n > var y = base.sin( 0.0 )\n ~0.0\n > y = base.sin( PI/2.0 )\n ~1.0\n > y = base.sin( -PI/6.0 )\n ~-0.5\n > y = base.sin( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinpi, base.tan\n","base.sinc":"\nbase.sinc( x )\n Computes the normalized cardinal sine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cardinal sine.\n\n Examples\n --------\n > var y = base.sinc( 0.5 )\n ~0.637\n > y = base.sinc( -1.2 )\n ~-0.156\n > y = base.sinc( 0.0 )\n 1.0\n > y = base.sinc( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.sincos":"\nbase.sincos( x )\n Simultaneously computes the sine and cosine of an angle measured in radians.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: Array\n Sine and cosine.\n\n Examples\n --------\n > var y = base.sincos( 0.0 )\n [ ~0.0, ~1.0 ]\n > y = base.sincos( PI/2.0 )\n [ ~1.0, ~0.0 ]\n > y = base.sincos( -PI/6.0 )\n [ ~-0.5, ~0.866 ]\n > y = base.sincos( NaN )\n [ NaN, NaN ]\n\n\nbase.sincos.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of an angle measured in radians\n and assigns the results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincos.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cos, base.sin, base.sincospi","base.sincos.assign":"\nbase.sincos.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of an angle measured in radians\n and assigns the results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincos.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cos, base.sin, base.sincospi","base.sincospi":"\nbase.sincospi( x )\n Simultaneously computes the sine and cosine of a number times π.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: Array\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var y = base.sincospi( 0.0 )\n [ 0.0, 1.0 ]\n > y = base.sincospi( 0.5 )\n [ 1.0, 0.0 ]\n > y = base.sincospi( 0.1 )\n [ ~0.309, ~0.951 ]\n > y = base.sincospi( NaN )\n [ NaN, NaN ]\n\n\nbase.sincospi.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi","base.sincospi.assign":"\nbase.sincospi.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi","base.sinh":"\nbase.sinh( x )\n Computes the hyperbolic sine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic sine.\n\n Examples\n --------\n > var y = base.sinh( 0.0 )\n 0.0\n > y = base.sinh( 2.0 )\n ~3.627\n > y = base.sinh( -2.0 )\n ~-3.627\n > y = base.sinh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sin, base.tanh\n","base.sinpi":"\nbase.sinpi( x )\n Computes the value of `sin(πx)`.\n\n The function computes `sin(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.sinpi( 0.0 )\n 0.0\n > y = base.sinpi( 0.5 )\n 1.0\n > y = base.sinpi( 0.9 )\n ~0.309\n > y = base.sinpi( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.slice2seq":"\nbase.slice2seq( slice )\n Converts a Slice object to a subsequence string.\n\n Parameters\n ----------\n slice: Slice\n Input slice.\n\n Returns\n -------\n out: string\n Subsequence string.\n\n Examples\n --------\n > var out = base.slice2seq( new Slice( 1, 10, 1 ) )\n '1:10:1'\n > out = base.slice2seq( new Slice( null, 10 ) )\n ':10'\n\n See Also\n --------\n base.seq2slice\n","base.sliceLength":"\nbase.sliceLength( slice )\n Returns the number of elements in a normalized slice.\n\n Parameters\n ----------\n slice: Slice\n Input normalized slice object.\n\n Returns\n -------\n len: integer\n Number of elements.\n\n Examples\n --------\n > var s = new Slice( 1, 10, 1 );\n > base.sliceLength( s )\n 9\n\n See Also\n --------\n base.sliceNonReducedDimensions, base.sliceReducedDimensions, base.sliceShape\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice )\n Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input slice object.\n\n Returns\n -------\n out: Array\n Dimension indices.\n\n Examples\n --------\n > var s = new MultiSlice( 1, 3, null );\n > var out = base.sliceNonReducedDimensions( s )\n [ 2 ]\n\n See Also\n --------\n base.sliceLength, base.sliceReducedDimensions, base.sliceShape\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice )\n Returns a list of reduced dimensions in an un-normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input slice object.\n\n Returns\n -------\n out: Array\n Dimension indices.\n\n Examples\n --------\n > var s = new MultiSlice( 1, 3, null );\n > var out = base.sliceReducedDimensions( s )\n [ 0, 1 ]\n\n See Also\n --------\n base.sliceLength, base.sliceNonReducedDimensions, base.sliceShape\n","base.sliceShape":"\nbase.sliceShape( slice )\n Returns the shape of a normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input normalized multi-slice object.\n\n Returns\n -------\n sh: Array\n Slice shape.\n\n Examples\n --------\n > var s = new Slice( 1, 10, 1 );\n > var ms = new MultiSlice( s, s );\n > base.sliceShape( ms )\n [ 9, 9 ]\n\n See Also\n --------\n base.sliceLength, base.sliceNonReducedDimensions, base.sliceReducedDimensions\n","base.snakecase":"\nbase.snakecase( str )\n Converts a string to snake case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Snake-cased string.\n\n Examples\n --------\n > var out = base.snakecase( 'Hello World!' )\n 'hello_world'\n > out = base.snakecase( 'I am a tiny little teapot' )\n 'i_am_a_tiny_little_teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.stickycase, base.uppercase","base.spence":"\nbase.spence( x )\n Evaluates Spence's function, which is also known as the dilogarithm.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.spence( 3.0 )\n ~-1.437\n > y = base.spence( 0.0 )\n ~1.645\n > y = base.spence( -9.0 )\n NaN\n > y = base.spence( NaN )\n NaN\n\n","base.sqrt":"\nbase.sqrt( x )\n Computes the principal square root of a double-precision floating-point\n number.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrt( 4.0 )\n 2.0\n > y = base.sqrt( 9.0 )\n 3.0\n > y = base.sqrt( 0.0 )\n 0.0\n > y = base.sqrt( -4.0 )\n NaN\n > y = base.sqrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.rsqrt\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x )\n Computes the principal square root of `1+x` minus one.\n\n This function is more accurate than the obvious approach for small `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Square root of `1+x` minus one.\n\n Examples\n --------\n > var y = base.sqrt1pm1( 3.0 )\n 1.0\n > y = base.sqrt1pm1( 0.5 )\n ~0.225\n > y = base.sqrt1pm1( 0.02 )\n ~0.01\n > y = base.sqrt1pm1( -0.5 )\n ~-0.293\n > y = base.sqrt1pm1( -1.1 )\n NaN\n > y = base.sqrt1pm1( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.sqrtf":"\nbase.sqrtf( x )\n Computes the principal square root of a single-precision floating-point\n number.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrtf( 4.0 )\n 2.0\n > y = base.sqrtf( 9.0 )\n 3.0\n > y = base.sqrtf( 0.0 )\n 0.0\n > y = base.sqrtf( -4.0 )\n NaN\n > y = base.sqrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrtf, base.rsqrtf, base.sqrt\n","base.sqrtpi":"\nbase.sqrtpi( x )\n Computes the principal square root of the product of π and a positive\n double-precision floating-point number.\n\n For `x < 0`, the square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root of the product of π and the input value.\n\n Examples\n --------\n > var y = base.sqrtpi( 4.0 )\n ~3.5449\n > y = base.sqrtpi( 10.0 )\n ~5.60499\n > y = base.sqrtpi( 0.0 )\n 0.0\n > y = base.sqrtpi( -4.0 )\n NaN\n > y = base.sqrtpi( NaN )\n NaN\n\n See Also\n --------\n base.sqrt","base.startcase":"\nbase.startcase( str )\n Capitalizes the first letter of each word in an input string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = base.startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n base.capitalize, base.lowercase, base.uppercase\n","base.startsWith":"\nbase.startsWith( str, search, position )\n Tests if a string starts with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string starts with the characters of\n another string.\n\n Examples\n --------\n > var bool = base.startsWith( 'Beep', 'Be', 0 )\n true\n > bool = base.startsWith( 'Beep', 'ep', 0 )\n false\n > bool = base.startsWith( 'Beep', 'ee', 1 )\n true\n > bool = base.startsWith( 'Beep', 'ee', -3 )\n true\n > bool = base.startsWith( 'Beep', '', 0 )\n true\n\n See Also\n --------\n base.endsWith\n","base.stickycase":"\nbase.stickycase( str[, p] )\n Converts a string to sticky case.\n\n Parameters\n ----------\n str: string\n Input string.\n \n p: number\n Probability of capitalization.\n\n Returns\n -------\n out: string\n Sticky-cased string.\n\n Examples\n --------\n > var out = base.stickycase( 'Hello World!' )\n \n\n > out = base.stickycase( 'I am a tiny little teapot' )\n \n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase\n","base.strided.binary":"\nbase.strided.binary( arrays, shape, strides, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary( [ x, y, z ], shape, strides, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1, dtypes2, dtypes3[, options] )\n Generates a list of binary interface signatures from strided array data\n types.\n\n The function returns a strided array having a stride length of `3` (i.e.,\n every `3` elements define a binary interface signature).\n\n For each signature (i.e., set of three consecutive non-overlapping strided\n array elements), the first two elements are the input data types and the\n third element is the return data type.\n\n All signatures follow type promotion rules.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the first input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the second input argument.\n\n dtypes3: ArrayLike\n List of supported data types for the output value.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing binary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n [...]\n\n See Also\n --------\n base.strided.binarySignatureCallbacks\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table, signatures )\n Assigns callbacks to binary interfaces according to type promotion rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing binary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\n > var t = {\n ... 'default': base.add,\n ... 'complex64': base.caddf,\n ... 'complex128': base.cadd\n ... };\n > var out = base.strided.binarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.binaryDtypeSignatures\n","base.strided.ccopy":"\nbase.strided.ccopy( N, x, strideX, y, strideY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy( 2, x, -2, y, 1 )\n [ 5.0, 6.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0 ]\n\n // Using typed array views:\n > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.ccopy( 2, x1, -2, y1, 1 )\n [ 7.0, 8.0, 3.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.cswap\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.cswap","base.strided.cmap":"\nbase.strided.cmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\n > var v = y.get( 0 )\n [ 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > y = new Complex64Array( x.length );\n > base.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\n > v = y.get( 0 )\n [ 5.0, 6.0 ]\n\n // Using view offsets:\n > var x0 = new Complex64Array( xbuf );\n > var y0 = new Complex64Array( x0.length );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\n > v = y1.get( 0 )\n [ 7.0, 8.0 ]\n\n\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n > var v = y.get( 0 )\n [ 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( xbuf );\n > y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n > v = y.get( y.length-1 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.zmap, base.strided.unary\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n > var v = y.get( 0 )\n [ 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( xbuf );\n > y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n > v = y.get( y.length-1 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.zmap, base.strided.unary","base.strided.cswap":"\nbase.strided.cswap( N, x, strideX, y, strideY )\n Interchanges two complex single-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap( x.length, x, 1, y, 1 );\n > x\n [ 6.0, 7.0, 8.0, 9.0 ]\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap( 2, x, -2, y, 1 );\n > x\n [ 0.0, 0.0, 3.0, 4.0, 0.0, 0.0, 7.0, 8.0 ]\n > y\n [ 5.0, 6.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0 ]\n\n // Using typed array views:\n > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.cswap( 2, x1, -2, y1, 1 );\n > x0\n [ 1.0, 2.0, 0.0, 0.0, 5.0, 6.0, 0.0, 0.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > x\n [ 6.0, 7.0, 8.0, 9.0 ]\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > x\n [ 1.0, 2.0, 0.0, 0.0, 5.0, 6.0, 0.0, 0.0 ]\n > y\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.ccopy\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > x\n [ 6.0, 7.0, 8.0, 9.0 ]\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > x\n [ 1.0, 2.0, 0.0, 0.0, 5.0, 6.0, 0.0, 0.0 ]\n > y\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.ccopy","base.strided.cumax":"\nbase.strided.cumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of a strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.cumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumax\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumax","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.cumaxabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs","base.strided.cumin":"\nbase.strided.cumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of a strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumin( 3, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.cumin( 3, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumin\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumin","base.strided.cuminabs":"\nbase.strided.cuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.cuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs","base.strided.dabs":"\nbase.strided.dabs( N, x, strideX, y, strideY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs( N, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs","base.strided.dabs2":"\nbase.strided.dabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2","base.strided.dapx":"\nbase.strided.dapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx","base.strided.dapxsum":"\nbase.strided.dapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumkbn( 3, 5.0, x1, 2)\n 14.0\n\n\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation.\n\n The `N` and stride parameters determine which elements in\n the strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw","base.strided.dasum":"\nbase.strided.dasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.dasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.dasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum","base.strided.dasumpw":"\nbase.strided.dasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var stride = 2;\n > base.strided.dasumpw( 3, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.dasumpw( 3, x1, stride )\n 5.0\n\n\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw","base.strided.daxpy":"\nbase.strided.daxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.daxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.dasum, base.strided.gaxpy, base.strided.saxpy\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.dasum, base.strided.gaxpy, base.strided.saxpy","base.strided.dcbrt":"\nbase.strided.dcbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, base.strided.scbrt\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, base.strided.scbrt","base.strided.dceil":"\nbase.strided.dceil( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil( x.length, x, 1, y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil( N, x, 2, y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dceil( N, x1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil","base.strided.dcopy":"\nbase.strided.dcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy","base.strided.dcumax":"\nbase.strided.dcumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumaxabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs","base.strided.dcumin":"\nbase.strided.dcumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin( 3, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumin( 3, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs","base.strided.dcusum":"\nbase.strided.dcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2","base.strided.dcusumors":"\nbase.strided.dcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N, x, strideX, y, strideY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ddeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n strided.deg2rad, base.strided.sdeg2rad\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n strided.deg2rad, base.strided.sdeg2rad","base.strided.ddot":"\nbase.strided.ddot( N, x, strideX, y, strideY )\n Computes the dot product of two double-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.ddot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot","base.strided.dfill":"\nbase.strided.dfill( N, alpha, x, strideX )\n Fills a double-precision floating-point strided array with a specified\n scalar constant.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a double-precision floating-point strided array with a specified\n scalar constant using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill, base.strided.sfill\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a double-precision floating-point strided array with a specified\n scalar constant using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill, base.strided.sfill","base.strided.dfloor":"\nbase.strided.dfloor( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor( x.length, x, 1, y, 1 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor( N, x, 2, y, -1 )\n [ 3.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dfloor( N, x1, -2, y1, 1 )\n [ 4.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor","base.strided.dinv":"\nbase.strided.dinv( N, x, strideX, y, strideY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv( x.length, x, 1, y, 1 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv( N, x, 2, y, -1 )\n [ 0.5, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dinv( N, x1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n strided.inv, base.strided.sinv\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n strided.inv, base.strided.sinv","base.strided.dmap":"\nbase.strided.dmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap( x.length, x, 1, y, 1, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap( 2, x, 2, y, -1, base.identity )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmap( 2, x1, -2, y1, 1, base.identity )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.smap, base.strided.unary\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.smap, base.strided.unary","base.strided.dmap2":"\nbase.strided.dmap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays and assigns results to a double-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary","base.strided.dmax":"\nbase.strided.dmax( N, x, strideX )\n Computes the maximum value of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N, x, strideX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N, x, strideX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxabssorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxabssorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N, x, strideX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxsorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxsorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted","base.strided.dmean":"\nbase.strided.dmean( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeankbn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeankbn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeankbn2( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeankbn2( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2","base.strided.dmeanli":"\nbase.strided.dmeanli( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanli( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanli( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanlipw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanlipw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanlipw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanlipw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanlipw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw","base.strided.dmeanors":"\nbase.strided.dmeanors( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev( 3, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev( 3, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( 3, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( 3, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar( 3, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar( 3, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( 3, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( 3, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N, x, strideX )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted","base.strided.dmidrange":"\nbase.strided.dmidrange( N, x, strideX )\n Computes the mid-range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange","base.strided.dmin":"\nbase.strided.dmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmin( N, x1, stride )\n -2.0\n\n\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin","base.strided.dminabs":"\nbase.strided.dminabs( N, x, strideX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs","base.strided.dminsorted":"\nbase.strided.dminsorted( N, x, strideX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dminsorted( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dminsorted( 3, x1, 2 )\n -2.0\n\n\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted","base.strided.dmskabs":"\nbase.strided.dmskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N, x, sx, m, sm, y, sy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt","base.strided.dmskceil":"\nbase.strided.dmskceil( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N, x, sx, m, sm, y, sy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor","base.strided.dmskinv":"\nbase.strided.dmskinv( N, x, sx, m, sm, y, sy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\n [ 0.0, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.smskinv\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.smskinv","base.strided.dmskmap":"\nbase.strided.dmskmap( N, x, sx, m, sm, y, sy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n [ 0.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2","base.strided.dmskmax":"\nbase.strided.dmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax","base.strided.dmskmin":"\nbase.strided.dmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin","base.strided.dmskramp":"\nbase.strided.dmskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp","base.strided.dmskrange":"\nbase.strided.dmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc","base.strided.dnanasum":"\nbase.strided.dnanasum( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum( 4, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanasum( 4, x1, 2 )\n 5.0\n\n\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasumors( 4, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanasumors( 4, x1, 2 )\n 5.0\n\n\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasumors.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasumors.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum","base.strided.dnanmax":"\nbase.strided.dnanmax( N, x, strideX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs","base.strided.dnanmean":"\nbase.strided.dnanmean( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmean( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmean( 4, x1,2 )\n ~-0.3333\n\n\nbase.strided.dnanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanors( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpn( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanpn( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmeanpw( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanpw( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanwd( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanwd( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd","base.strided.dnanmin":"\nbase.strided.dnanmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N, x, strideX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange","base.strided.dnannsum":"\nbase.strided.dnannsum( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnansum, base.strided.dsum","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnansum, base.strided.dsum","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw","base.strided.dnanrange":"\nbase.strided.dnanrange( N, x, strideX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanrange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanrange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dnanstdev( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdev( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnanstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnanstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevch( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevch( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevch.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevch.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevpn( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevpn( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevpn.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevpn.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevtk( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevtk( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevtk.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevtk.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevwd( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevwd( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevwd.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevwd.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevyc( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevyc( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevyc.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevyc.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc","base.strided.dnansum":"\nbase.strided.dnansum( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumkbn( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumkbn2( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2","base.strided.dnansumors":"\nbase.strided.dnansumors( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariance( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariance( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariance.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariance.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, NaN, -2.0, 2.0 ] );\n > base.strided.dnanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancech( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariancech( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancech.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancech.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancepn( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariancepn( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancepn.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancepn.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancetk( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariancetk( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancetk.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancetk.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancewd( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariancewd( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancewd.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancewd.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvarianceyc( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvarianceyc( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvarianceyc.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvarianceyc.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc","base.strided.dnrm2":"\nbase.strided.dnrm2( N, x, stride )\n Computes the L2-norm of a double-precision floating-point vector.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2","base.strided.dramp":"\nbase.strided.dramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( x.length, x, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( N, x, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp","base.strided.drange":"\nbase.strided.drange( N, x, strideX )\n Computes the range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.drange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.drange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.drange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.drange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange","base.strided.drev":"\nbase.strided.drev( N, x, strideX )\n Reverses a double-precision floating-point strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.drev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev","base.strided.drsqrt":"\nbase.strided.drsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( x.length, x, 1, y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( N, x, 2, y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.drsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using extended accumulation and returning\n an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N, alpha, x, strideX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw","base.strided.dscal":"\nbase.strided.dscal( N, alpha, x, stride )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy","base.strided.dsdot":"\nbase.strided.dsdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation and result.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > dot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot","base.strided.dsem":"\nbase.strided.dsem( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsem( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsem( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsem.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsem.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsem.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev","base.strided.dsemch":"\nbase.strided.dsemch( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemch( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemch( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch","base.strided.dsempn":"\nbase.strided.dsempn( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsempn( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsempn( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsempn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsempn.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsempn.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn","base.strided.dsemtk":"\nbase.strided.dsemtk( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemtk( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemtk( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk","base.strided.dsemwd":"\nbase.strided.dsemwd( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemwd( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemwd( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd","base.strided.dsemyc":"\nbase.strided.dsemyc( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemyc( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemyc( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc","base.strided.dsmean":"\nbase.strided.dsmean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed.\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmean( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnanmean( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsnanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnanmeanors( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using a two-pass error correction algorithm\n with extended accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanpn( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnanmeanpn( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsnanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using Welford's algorithm with extended\n accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanwd( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnanmeanwd( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N, x, strideX, out, strideOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors","base.strided.dsnansum":"\nbase.strided.dsnansum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation,\n and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh","base.strided.dsorthp":"\nbase.strided.dsorthp( N, order, x, strideX )\n Sorts a double-precision floating-point strided array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsorthp( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.dsorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp","base.strided.dsortins":"\nbase.strided.dsortins( N, order, x, strideX )\n Sorts a double-precision floating-point strided array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsortins( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.dsortins.ndarray( N, order, x, strideX, offsetX )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N, order, x, strideX, offsetX )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins","base.strided.dsortsh":"\nbase.strided.dsortsh( N, order, x, stride )\n Sorts a double-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsortsh( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh","base.strided.dsqrt":"\nbase.strided.dsqrt( N, x, strideX, y, strideY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt( x.length, x, 1, y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt( N, x, 2, y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsqrt( N, x1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt","base.strided.dssum":"\nbase.strided.dssum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssum.ndarray(3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssum.ndarray(3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean","base.strided.dssumors":"\nbase.strided.dssumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and returning\n an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors","base.strided.dssumpw":"\nbase.strided.dssumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw","base.strided.dstdev":"\nbase.strided.dstdev( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdev( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdev( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev","base.strided.dstdevch":"\nbase.strided.dstdevch( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevch( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevch( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevpn( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevpn( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevtk( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevtk( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevwd( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevwd( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc( x.length, 1.0, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevyc( 3, 1.0, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevyc( 3, 1.0, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc","base.strided.dsum":"\nbase.strided.dsum( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2","base.strided.dsumors":"\nbase.strided.dsumors( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors","base.strided.dsumpw":"\nbase.strided.dsumpw( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw","base.strided.dsvariance":"\nbase.strided.dsvariance( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsvariance( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsvariance( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dsvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsvariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsvariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsvariancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsvariancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dsvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn","base.strided.dswap":"\nbase.strided.dswap( N, x, strideX, y, strideY )\n Interchanges two double-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped\n with values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap","base.strided.dtrunc":"\nbase.strided.dtrunc( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc( N, x, 2, y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dtrunc( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype )\n Returns the data type string associated with a strided array data type\n enumeration constant.\n\n Parameters\n ----------\n dtype: integer\n Data type enumeration constant.\n\n Returns\n -------\n out: string|null\n Data type string.\n\n Examples\n --------\n > var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n 'float64'\n\n See Also\n --------\n base.strided.dtypeStr2Enum\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype )\n Returns the enumeration constant associated with a supported strided array\n data type value.\n\n Downstream consumers of this function should *not* rely on specific integer\n values (e.g., `INT8 == 0`). Instead, the function should be used in an\n opaque manner.\n\n Parameters\n ----------\n dtype: any\n Data type value.\n\n Returns\n -------\n out: integer|null\n Enumeration constant.\n\n Examples\n --------\n > var out = base.strided.dtypeResolveEnum( 'float64' )\n \n > out = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n \n\n See Also\n --------\n base.strided.dtypeResolveStr\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype )\n Returns the data type string associated with a supported data type value.\n\n Parameters\n ----------\n dtype: any\n Data type value.\n\n Returns\n -------\n out: string|null\n Data type string.\n\n Examples\n --------\n > var out = base.strided.dtypeResolveStr( 'float64' )\n 'float64'\n > out = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n 'float64'\n\n See Also\n --------\n base.strided.dtypeResolveEnum\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype )\n Returns the enumeration constant associated with a strided array data type\n string.\n\n Downstream consumers of this function should *not* rely on specific integer\n values (e.g., `INT8 == 0`). Instead, the function should be used in an\n opaque manner.\n\n Parameters\n ----------\n dtype: string\n Data type string.\n\n Returns\n -------\n out: integer|null\n Enumeration constant.\n\n Examples\n --------\n > var out = base.strided.dtypeStr2Enum( 'float64' )\n \n\n See Also\n --------\n base.strided.dtypeEnum2Str\n","base.strided.dvariance":"\nbase.strided.dvariance( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariance( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariance( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance","base.strided.dvariancech":"\nbase.strided.dvariancech( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancech( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancech( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancetk( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancetk( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancewd( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancewd( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarianceyc( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarianceyc( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc","base.strided.dvarm":"\nbase.strided.dvarm( N, correction, mean, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm( x.length, 1, 1.0/3.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarm( 3, 1, 1.0/3.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarm( 3, 1, 1.0/3.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarm.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarm.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarm.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N, correction, mean, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn( x.length, 1, 1.0/3.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarmpn( 3, 1, 1.0/3.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarmpn( 3, 1, 1.0/3.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarmpn.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmpn.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmpn.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N, correction, mean, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk( x.length, 1, 1.0/3.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarmtk( 3, 1, 1.0/3.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarmtk( 3, 1, 1.0/3.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarmtk.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmtk.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmtk.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm","base.strided.gapx":"\nbase.strided.gapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 5.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gapx( 4, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, 0.0, 4.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.gapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx","base.strided.gapxsum":"\nbase.strided.gapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw","base.strided.gasum":"\nbase.strided.gasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > s = base.strided.gasum( 3, x, 2 )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.gasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum","base.strided.gasumpw":"\nbase.strided.gasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.gasumpw( 3, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gasumpw( 3, x1, 2 )\n 5.0\n\n\nbase.strided.gasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.gasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.gasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw","base.strided.gaxpy":"\nbase.strided.gaxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy","base.strided.gcopy":"\nbase.strided.gcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy","base.strided.gcusum":"\nbase.strided.gcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2","base.strided.gcusumors":"\nbase.strided.gcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw","base.strided.gdot":"\nbase.strided.gdot( N, x, strideX, y, strideY )\n Computes the dot product of two vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.gdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot","base.strided.gfill":"\nbase.strided.gfill( N, alpha, x, strideX )\n Fills a strided array with a specified scalar constant.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill","base.strided.gfillBy":"\nbase.strided.gfillBy( N, x, strideX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: current array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback return value is used as the fill value for the current array\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy( x.length, x, 1, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy( 3, x, 2, fill )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gfillBy( 3, x1, 2, fill )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfillBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn","base.strided.gnansum":"\nbase.strided.gnansum( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumkbn( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumkbn2( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2","base.strided.gnansumors":"\nbase.strided.gnansumors( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw","base.strided.gnrm2":"\nbase.strided.gnrm2( N, x, stride )\n Computes the L2-norm of a vector.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Stride length.\n\n Returns\n -------\n out: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2","base.strided.grev":"\nbase.strided.grev( N, x, strideX )\n Reverses a strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.grev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.grev.ndarray( N, x, strideX, offsetX )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.grev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N, x, strideX, offsetX )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.grev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev","base.strided.gscal":"\nbase.strided.gscal( N, alpha, x, strideX )\n Multiplies a vector by a scalar constant.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.gscal.ndarray( N, alpha, x, strideX, offsetX )\n Multiplies a vector by a scalar constant using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N, alpha, x, strideX, offsetX )\n Multiplies a vector by a scalar constant using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsort2hp( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsort2ins( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsort2sh( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.gsorthp":"\nbase.strided.gsorthp( N, order, x, strideX )\n Sorts a strided array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsorthp( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.gsorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.gsortins":"\nbase.strided.gsortins( N, order, x, strideX )\n Sorts a strided array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsortins( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.gsortins.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins","base.strided.gsortsh":"\nbase.strided.gsortsh( N, order, x, strideX )\n Sorts a strided array using Shellsort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsortsh( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.gsortsh.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.gsum":"\nbase.strided.gsum( N, x, strideX )\n Computes the sum of strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N, x, strideX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N, x, strideX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2","base.strided.gsumors":"\nbase.strided.gsumors( N, x, strideX )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors","base.strided.gsumpw":"\nbase.strided.gsumpw( N, x, strideX )\n Computes the sum of strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw","base.strided.gswap":"\nbase.strided.gswap( N, x, strideX, y, strideY )\n Interchanges vectors `x` and `y`.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap","base.strided.mapBy":"\nbase.strided.mapBy( N, x, sx, y, sy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary","base.strided.mapBy2":"\nbase.strided.mapBy2( N, x, sx, y, sy, z, sz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\n [ 8.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\n [ -4.0, 0.0 ]\n > z0\n [ 0.0, 0.0, -4.0, 0.0 ]\n\n\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 1.0, 1.0, 2.0, 2.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n [ 0.0, -4.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.binary\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 1.0, 1.0, 2.0, 2.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n [ 0.0, -4.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.binary","base.strided.max":"\nbase.strided.max( N, x, strideX )\n Computes the maximum value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.max( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.max( 3, x1, 2 )\n 2.0\n\n\nbase.strided.max.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.max.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.max.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax","base.strided.maxabs":"\nbase.strided.maxabs( N, x, strideX )\n Computes the maximum absolute value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.maxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.maxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.maxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.maxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.maxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs","base.strided.maxBy":"\nbase.strided.maxBy( N, x, strideX, clbk[, thisArg] )\n Computes the maximum value of a strided array via a callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `NaN`.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy( x.length, x, 1, accessor )\n 8.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy( 3, x, 2, accessor )\n 8.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.maxBy( 3, x1, 2, accessor )\n -4.0\n\n\nbase.strided.maxBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.maxBy.ndarray( 3, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.maxBy.ndarray( 3, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax","base.strided.maxsorted":"\nbase.strided.maxsorted( N, x, strideX )\n Computes the maximum value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.maxsorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.maxsorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.maxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.maxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.maxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N, stride, offset )\n Returns the maximum accessible index based on a set of provided strided\n array parameters.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n idx: integer\n Minimum accessible index.\n\n Examples\n --------\n > var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n 14\n\n","base.strided.mean":"\nbase.strided.mean( N, x, strideX )\n Computes the arithmetic mean of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.mean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.mean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.mean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.mean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.mean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.mean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.smean\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.mean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.mean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.smean","base.strided.meankbn":"\nbase.strided.meankbn( N, x, strideX )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meankbn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meankbn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn","base.strided.meankbn2":"\nbase.strided.meankbn2( N, x, strideX )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meankbn2( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meankbn2( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2","base.strided.meanors":"\nbase.strided.meanors( N, x, strideX )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors","base.strided.meanpn":"\nbase.strided.meanpn( N, x, strideX )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn","base.strided.meanpw":"\nbase.strided.meanpw( N, x, strideX )\n Computes the arithmetic mean of a strided array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw","base.strided.meanwd":"\nbase.strided.meanwd( N, x, strideX )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd","base.strided.mediansorted":"\nbase.strided.mediansorted( N, x, strideX )\n Computes the median value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.mediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.mediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.mediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.mediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.mediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta, dtypes, obj, bool )\n Defines non-enumerable read-only properties which expose strided array\n function meta data.\n\n Parameters\n ----------\n meta: Object\n Function meta data.\n\n meta.nargs: integer\n Total number of arguments (excluding offsets).\n\n meta.nin: integer\n Total number of input arrays.\n\n meta.nout: integer\n Total number of output arrays.\n\n dtypes: ArrayLikeObject\n List of strided array data types.\n\n obj: Object|Function\n Object on which to define properties.\n\n bool: boolean\n Boolean indicating whether the provided object should describe an\n \"ndarray\" function interface.\n\n Returns\n -------\n out: Object|Function\n Object on which properties were defined.\n\n Examples\n --------\n > var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\n > var dt = [ 'float64', 'float64' ];\n > var obj = {};\n > base.strided.metaDataProps( meta, dt, obj, false );\n > obj.nargs\n 7\n > obj.nin\n 1\n > obj.nout\n 1\n > obj.types\n [...]\n\n","base.strided.min":"\nbase.strided.min( N, x, strideX )\n Computes the minimum value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.min( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.min( 3, x1, 2 )\n -2.0\n\n\nbase.strided.min.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.min.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.min.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin","base.strided.minabs":"\nbase.strided.minabs( N, x, strideX )\n Computes the minimum absolute value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.minabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.minabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.minabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.minabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.minabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs","base.strided.minBy":"\nbase.strided.minBy( N, x, strideX, clbk[, thisArg] )\n Computes the minimum value of a strided array via a callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `NaN`.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy( x.length, x, 1, accessor )\n -10.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\n > base.strided.minBy( 3, x, 2, accessor )\n -4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.minBy( 3, x1, 2, accessor )\n -12.0\n\n\nbase.strided.minBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.minBy.ndarray( 3, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.minBy.ndarray( 3, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin","base.strided.minsorted":"\nbase.strided.minsorted( N, x, strideX )\n Computes the minimum value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.minsorted( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.minsorted( 3, x1, 2 )\n -2.0\n\n\nbase.strided.minsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.minsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.minsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N, stride, offset )\n Returns the minimum accessible index based on a set of provided strided\n array parameters.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n idx: integer\n Minimum accessible index.\n\n Examples\n --------\n > var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n 6\n\n See Also\n --------\n base.strided.offsetView\n","base.strided.mskmax":"\nbase.strided.mskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a strided array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.mskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax","base.strided.mskmin":"\nbase.strided.mskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a strided array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, -4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.mskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin","base.strided.mskrange":"\nbase.strided.mskrange( N, x, strideX, mask, strideMask )\n Computes the range of a strided array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.mskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange","base.strided.mskunary":"\nbase.strided.mskunary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array and assigns results to elements in a\n strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > base.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.smskmap, base.strided.unary\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.smskmap, base.strided.unary","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1, dtypes2[, options] )\n Generates a list of masked unary interface signatures from strided array\n data types.\n\n The function returns a strided array having a stride length of three (i.e.,\n every three elements define a masked unary interface signature).\n\n For each signature (i.e., set of three consecutive non-overlapping strided\n array elements), the first element is the input data type, the second\n element is the mask data type, and the last element is the return data type.\n\n All signatures follow type promotion rules.\n\n The mask array data type is always `uint8`.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the output argument.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing masked unary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.mskunaryDtypeSignatures( dt, dt )\n [...]\n\n See Also\n --------\n base.strided.mskunarySignatureCallbacks\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table, signatures )\n Assigns callbacks to masked unary interfaces according to type promotion\n rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing masked unary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\n > var t = {\n ... 'default': base.identity,\n ... 'complex64': base.cidentityf,\n ... 'complex128': base.cidentity\n ... };\n > var out = base.strided.mskunarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.mskunaryDtypeSignatures\n","base.strided.nanmax":"\nbase.strided.nanmax( N, x, strideX )\n Computes the maximum value of a strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanmax( 4, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmax( 4, x1, 2 )\n 2.0\n\n\nbase.strided.nanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmax.ndarray( 4, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmax.ndarray( 4, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanmaxabs( 4, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmaxabs( 4, x1, 2 )\n 2.0\n\n\nbase.strided.nanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmaxabs.ndarray( 4, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmaxabs.ndarray( 4, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N, x, strideX, clbk[, thisArg] )\n Computes the maximum value of strided array via a callback function,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `NaN`.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy( x.length, x, 1, accessor )\n 8.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.nanmaxBy( 3, x, 2, accessor )\n 8.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmaxBy( 3, x1, 2, accessor )\n -4.0\n\n\nbase.strided.nanmaxBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Computes the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanmaxBy.ndarray( 3, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Computes the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanmaxBy.ndarray( 3, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax","base.strided.nanmean":"\nbase.strided.nanmean( N, x, strideX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanmean( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmean( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.nanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.snanmean\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.snanmean","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N, x, strideX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmeanors( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.nanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N, x, strideX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanmeanpn( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmeanpn( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.nanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanmeanwd( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmeanwd( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.nanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd","base.strided.nanmin":"\nbase.strided.nanmin( N, x, strideX )\n Computes the minimum value of a strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanmin( 4, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmin( 4, x1, 2 )\n -2.0\n\n\nbase.strided.nanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmin.ndarray( 4, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmin.ndarray( 4, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin","base.strided.nanminabs":"\nbase.strided.nanminabs( N, x, strideX )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanminabs( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanminabs( 4, x1, 2 )\n 1.0\n\n\nbase.strided.nanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanminabs.ndarray( 4, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanminabs.ndarray( 4, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs","base.strided.nanminBy":"\nbase.strided.nanminBy( N, x, strideX, clbk[, thisArg] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `NaN`.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy( x.length, x, 1, accessor )\n -10.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\n > base.strided.nanminBy( 4, x, 2, accessor )\n -4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanminBy( 3, x1, 2, accessor )\n -12.0\n\n\nbase.strided.nanminBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanminBy.ndarray( 3, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanminBy.ndarray( 3, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a strided array according to a mask and\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskmax( 4, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmskmax( 4, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0, NaN, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmax.ndarray( 4, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0, NaN, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmax.ndarray( 4, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a strided array according to a mask and\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskmin( 4, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmskmin( 4, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0, NaN, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmin.ndarray( 4, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0, NaN, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmin.ndarray( 4, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a strided array according to a mask and ignoring `NaN`\n values.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskrange( 5, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskrange.ndarray( 5, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskrange.ndarray( 5, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange","base.strided.nanrange":"\nbase.strided.nanrange( N, x, strideX )\n Computes the range of a strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanrange( 4, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanrange( 4, x1, 2 )\n 4.0\n\n\nbase.strided.nanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanrange.ndarray( 4, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanrange.ndarray( 4, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N, x, strideX, clbk[, thisArg] )\n Computes the range of a strided array via a callback function, ignoring\n `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy( x.length, x, 1, accessor )\n 18.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\n > base.strided.nanrangeBy( 4, x, 2, accessor )\n 14.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanrangeBy( 3, x1, 2, accessor )\n 8.0\n\n\nbase.strided.nanrangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanrangeBy.ndarray( 3, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanrangeBy.ndarray( 3, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange","base.strided.nanstdev":"\nbase.strided.nanstdev( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdev( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0,NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdev( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdev.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdev.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevch( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevch( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevch.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevch.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevpn( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevpn( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevpn.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevpn.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevtk( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevtk( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevtk.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevtk.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevwd( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevwd( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevwd.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevwd.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevyc( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevyc( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevyc.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevyc.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc","base.strided.nanvariance":"\nbase.strided.nanvariance( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanvariance( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariance( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariance.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariance.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancech( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariancech( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancech.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancech.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.nanvariancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.nanvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.nanvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanvariancetk( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariancetk( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancetk.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancetk.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanvariancewd( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariancewd( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancewd.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancewd.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc( 4, 1.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.nanvarianceyc( 3, 1.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvarianceyc( 3, 1.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc.ndarray( 4, 1.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.nanvarianceyc.ndarray( 3, 1.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc.ndarray( 4, 1.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.nanvarianceyc.ndarray( 3, 1.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc","base.strided.nullary":"\nbase.strided.nullary( arrays, shape, strides, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n output array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary( [ x ], shape, strides, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting index (i.e., index offset) for\n the strided output array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1 ];\n > var offsets = [ 0 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting index (i.e., index offset) for\n the strided output array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1 ];\n > var offsets = [ 0 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.offsetView":"\nbase.strided.offsetView( x, offset )\n Returns a typed array view having the same data type as a provided input\n typed array and starting at a specified index offset.\n\n Parameters\n ----------\n x: TypedArray\n Input array.\n\n offset: integer\n Starting index of the view relative to the input array.\n\n Returns\n -------\n out: TypedArray\n Typed array view having the same data type as the input array.\n\n Examples\n --------\n > var x = new Float64Array( 10 );\n > var out = base.strided.offsetView( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.minViewBufferIndex\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays, shape, strides, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.quinary":"\nbase.strided.quinary( arrays, shape, strides, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary","base.strided.range":"\nbase.strided.range( N, x, strideX )\n Computes the range of a strided array.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a\n typed array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.range( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.range( 3, x1, 2 )\n 4.0\n\n\nbase.strided.range.ndarray( N, x, strideX, offsetX )\n Computes the range of a strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.range.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N, x, strideX, offsetX )\n Computes the range of a strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.range.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange","base.strided.rangeBy":"\nbase.strided.rangeBy( N, x, strideX, clbk[, thisArg] )\n Computes the range of a strided array via a callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy( x.length, x, 1, accessor )\n 18.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy( 3, x, 2, accessor )\n 12.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.rangeBy( 3, x1, 2, accessor )\n 8.0\n\n\nbase.strided.rangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.rangeBy.ndarray( 3, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.rangeBy.ndarray( 3, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x, offset )\n Returns a real-valued floating-point array view of a complex-valued\n floating-point array having the same precision.\n\n Parameters\n ----------\n x: Complex128Array|Complex64Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the input array.\n\n Returns\n -------\n out: Float64Array|Float32Array\n Real-valued floating-point array view.\n\n Examples\n --------\n > var x = new Complex128Array( 10 );\n > var out = base.strided.reinterpretComplex( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n > x = new Complex64Array( 10 );\n > out = base.strided.reinterpretComplex( x, 0 )\n \n > bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex128, base.strided.reinterpretComplex64\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x, offset )\n Returns a Float32Array view of a Complex64Array.\n\n Parameters\n ----------\n x: Complex64Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the Complex64Array.\n\n Returns\n -------\n out: Float32Array\n Float32Array view.\n\n Examples\n --------\n > var x = new Complex64Array( 10 );\n > var out = base.strided.reinterpretComplex64( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex, base.strided.reinterpretComplex128\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x, offset )\n Returns a Float64Array view of a Complex128Array.\n\n Parameters\n ----------\n x: Complex128Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the Complex128Array.\n\n Returns\n -------\n out: Float64Array\n Float64Array view.\n\n Examples\n --------\n > var x = new Complex128Array( 10 );\n > var out = base.strided.reinterpretComplex128( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex, base.strided.reinterpretComplex64\n","base.strided.sabs":"\nbase.strided.sabs( N, x, strideX, y, strideY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs( N, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2","base.strided.sabs2":"\nbase.strided.sabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs","base.strided.sapx":"\nbase.strided.sapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.sapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx","base.strided.sapxsum":"\nbase.strided.sapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw","base.strided.sasum":"\nbase.strided.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and stride parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.sasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.sasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum","base.strided.sasumpw":"\nbase.strided.sasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sasumpw( 3, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sasumpw( 3, x1, 2 )\n 5.0\n\n\nbase.strided.sasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw","base.strided.saxpy":"\nbase.strided.saxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.saxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy","base.strided.scbrt":"\nbase.strided.scbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt","base.strided.sceil":"\nbase.strided.sceil( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil( x.length, x, 1, y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil( N, x, 2, y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sceil( N, x1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc","base.strided.scopy":"\nbase.strided.scopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap","base.strided.scumax":"\nbase.strided.scumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumaxabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs","base.strided.scumin":"\nbase.strided.scumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin( 3, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumin( 3, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax","base.strided.scuminabs":"\nbase.strided.scuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin","base.strided.scusum":"\nbase.strided.scusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn","base.strided.scusumors":"\nbase.strided.scusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum","base.strided.scusumpw":"\nbase.strided.scusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N, x, strideX, y, strideY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sdeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad","base.strided.sdot":"\nbase.strided.sdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sdsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsdot":"\nbase.strided.sdsdot( N, scalar, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns the provided scalar constant.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot","base.strided.sdsmean":"\nbase.strided.sdsmean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsmean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsmean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.sdsmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.sdsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.sdsnanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsnanmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.sdsnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.sdsnanmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.sdsnanmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignore `NaN` values and using extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.sdsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.sdsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw","base.strided.sdssum":"\nbase.strided.sdssum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.sdssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.sdssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw","base.strided.sfill":"\nbase.strided.sfill( N, alpha, x, strideX )\n Fills a single-precision floating-point strided array with a specified\n scalar value.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.gfill\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.gfill","base.strided.sfloor":"\nbase.strided.sfloor( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor( x.length, x, 1, y, 1 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor( N, x, 2, y, -1 )\n [ 3.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sfloor( N, x1, -2, y1, 1 )\n [ 4.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc","base.strided.sinv":"\nbase.strided.sinv( N, x, strideX, y, strideY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv( x.length, x, 1, y, 1 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv( N, x, 2, y, -1 )\n [ 0.5, ~-0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sinv( N, x1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, strided.inv\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, strided.inv","base.strided.smap":"\nbase.strided.smap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap( x.length, x, 1, y, 1, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap( 2, x, 2, y, -1, base.identityf )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap( 2, x1, -2, y1, 1, base.identityf )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary","base.strided.smap2":"\nbase.strided.smap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary","base.strided.smax":"\nbase.strided.smax( N, x, strideX )\n Computes the maximum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax","base.strided.smaxabs":"\nbase.strided.smaxabs( N, x, strideX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N, x, strideX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxabssorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxabssorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N, x, strideX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxsorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxsorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted","base.strided.smean":"\nbase.strided.smean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean","base.strided.smeankbn":"\nbase.strided.smeankbn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeankbn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeankbn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeankbn2( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeankbn2( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean","base.strided.smeanli":"\nbase.strided.smeanli( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanli( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanli( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanlipw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanlipw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanlipw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanlipw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanlipw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli","base.strided.smeanors":"\nbase.strided.smeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors","base.strided.smeanpn":"\nbase.strided.smeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn","base.strided.smeanpw":"\nbase.strided.smeanpw( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean","base.strided.smeanwd":"\nbase.strided.smeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd","base.strided.smediansorted":"\nbase.strided.smediansorted( N, x, strideX )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean","base.strided.smidrange":"\nbase.strided.smidrange( N, x, strideX )\n Computes the mid-range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange","base.strided.smin":"\nbase.strided.smin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin","base.strided.sminabs":"\nbase.strided.sminabs( N, x, strideX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs","base.strided.sminsorted":"\nbase.strided.sminsorted( N, x, strideX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sminsorted( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sminsorted( 3, x1, 2 )\n -2.0\n\n\nbase.strided.sminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin","base.strided.smskabs":"\nbase.strided.smskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2","base.strided.smskabs2":"\nbase.strided.smskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N, x, sx, m, sm, y, sy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt","base.strided.smskceil":"\nbase.strided.smskceil( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N, x, sx, m, sm, y, sy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.dmskdeg2rad, base.strided.sdeg2rad\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.dmskdeg2rad, base.strided.sdeg2rad","base.strided.smskfloor":"\nbase.strided.smskfloor( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc","base.strided.smskinv":"\nbase.strided.smskinv( N, x, sx, m, sm, y, sy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv( 2, x, 2, m, 2, y, -1 )\n [ 0.0, ~-0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.dmskinv\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.dmskinv","base.strided.smskmap":"\nbase.strided.smskmap( N, x, sx, m, sm, y, sy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n [ 0.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2","base.strided.smskmap2":"\nbase.strided.smskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap","base.strided.smskmax":"\nbase.strided.smskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax","base.strided.smskmin":"\nbase.strided.smskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin","base.strided.smskramp":"\nbase.strided.smskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp","base.strided.smskrange":"\nbase.strided.smskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc","base.strided.snanmax":"\nbase.strided.snanmax( N, x, strideX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs","base.strided.snanmean":"\nbase.strided.snanmean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmean( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmean( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.snanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmeanors( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.snanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanpn( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmeanpn( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.snanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanwd( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmeanwd( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.snanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean","base.strided.snanmin":"\nbase.strided.snanmin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax","base.strided.snanminabs":"\nbase.strided.snanminabs( N, x, strideX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride lengt for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride lengt for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride lengt for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride lengt for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin","base.strided.snanrange":"\nbase.strided.snanrange( N, x, strideX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanrange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanrange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange","base.strided.snanstdev":"\nbase.strided.snanstdev( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc","base.strided.snansum":"\nbase.strided.snansum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansumkbn( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn2( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansumkbn2( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2","base.strided.snansumors":"\nbase.strided.snansumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var stride = 2;\n > base.strided.snansumors( 4, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.snansumors( 4, x1, stride )\n -1.0\n\n\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors","base.strided.snansumpw":"\nbase.strided.snansumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw","base.strided.snanvariance":"\nbase.strided.snanvariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariance( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancech( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancepn( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancetk( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancewd( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvarianceyc( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc","base.strided.snrm2":"\nbase.strided.snrm2( N, x, stride )\n Computes the L2-norm of a single-precision floating-point vector.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.snrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2","base.strided.sramp":"\nbase.strided.sramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( N, x, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp","base.strided.srange":"\nbase.strided.srange( N, x, strideX )\n Computes the range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.srange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.srange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.srange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range","base.strided.srev":"\nbase.strided.srev( N, x, strideX )\n Reverses a single-precision floating-point strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.srev.ndarray( N, x, strideX, offsetX )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N, x, strideX, offsetX )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev","base.strided.srsqrt":"\nbase.strided.srsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( x.length, x, 1, y, 1 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( N, x, 2, y, -1 )\n [ ~0.333, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.srsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt","base.strided.sscal":"\nbase.strided.sscal( N, alpha, x, stride )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves the strided arrays\n are unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.ssorthp":"\nbase.strided.ssorthp( N, order, x, stride )\n Sorts a single-precision floating-point strided array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns the strided\n array unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for the strided array.\n\n Returns\n -------\n x: Float32Array\n Input array the strided array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssorthp( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for the strided array.\n\n offset: integer\n Starting index of the strided array.\n\n Returns\n -------\n x: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for the strided array.\n\n offset: integer\n Starting index of the strided array.\n\n Returns\n -------\n x: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.ssortins":"\nbase.strided.ssortins( N, order, x, stride )\n Sorts a single-precision floating-point strided array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssortins( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins","base.strided.ssortsh":"\nbase.strided.ssortsh( N, order, x, stride )\n Sorts a single-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssortsh( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.ssqrt":"\nbase.strided.ssqrt( N, x, strideX, y, strideY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt( x.length, x, 1, y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt( N, x, 2, y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssqrt( N, x1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt","base.strided.sstdev":"\nbase.strided.sstdev( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdev( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdev( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance","base.strided.sstdevch":"\nbase.strided.sstdevch( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevch( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevch( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevpn( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevpn( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevtk( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevtk( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevwd( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevwd( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevyc( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevyc( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevyc.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevyc.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc","base.strided.ssum":"\nbase.strided.ssum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumors":"\nbase.strided.ssumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw","base.strided.ssumpw":"\nbase.strided.ssumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors","base.strided.sswap":"\nbase.strided.sswap( N, x, strideX, y, strideY )\n Interchanges two single-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped\n with values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.sswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap","base.strided.stdev":"\nbase.strided.stdev( N, correction, x, strideX )\n Computes the standard deviation of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdev( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdev( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance","base.strided.stdevch":"\nbase.strided.stdevch( N, correction, x, strideX )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevch( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevch( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech","base.strided.stdevpn":"\nbase.strided.stdevpn( N, correction, x, strideX )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevpn( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevpn( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn","base.strided.stdevtk":"\nbase.strided.stdevtk( N, correction, x, strideX )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevtk( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevtk( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk","base.strided.stdevwd":"\nbase.strided.stdevwd( N, correction, x, strideX )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevwd( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevwd( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd","base.strided.stdevyc":"\nbase.strided.stdevyc( N, correction, x, strideX )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevyc( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevyc( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevyc.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevyc.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc","base.strided.strunc":"\nbase.strided.strunc( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc( N, x, 2, y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.strunc( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc","base.strided.svariance":"\nbase.strided.svariance( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariance( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariance( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance","base.strided.svariancech":"\nbase.strided.svariancech( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancech( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancech( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech","base.strided.svariancepn":"\nbase.strided.svariancepn( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn","base.strided.svariancetk":"\nbase.strided.svariancetk( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancetk( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancetk( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk","base.strided.svariancewd":"\nbase.strided.svariancewd( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancewd( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancewd( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svarianceyc( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svarianceyc( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.ternary":"\nbase.strided.ternary( arrays, shape, strides, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary( [ x, y, z, w ], shape, strides, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary","base.strided.unary":"\nbase.strided.unary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > base.strided.unary( [ x, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays, shape, strides, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The shape and stride parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using shape and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n > y\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > sh = [ 2 ];\n > st = [ -2, 1 ];\n > base.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\n > y1\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > var o = [ 0, 0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > o = [ 1, y.length-1 ];\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.unary\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > var o = [ 0, 0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > o = [ 1, y.length-1 ];\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.unary","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1, dtypes2[, options] )\n Generates a list of unary interface signatures from strided array data\n types.\n\n The function returns a strided array having a stride length of two (i.e.,\n every two elements define a unary interface signature).\n\n For each signature (i.e., set of two consecutive non-overlapping strided\n array elements), the first element is the input data type and the second\n element is the return data type.\n\n All signatures follow type promotion rules.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the output argument.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing unary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.unaryDtypeSignatures( dt, dt )\n [...]\n\n See Also\n --------\n base.strided.unarySignatureCallbacks\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table, signatures )\n Assigns callbacks to unary interfaces according to type promotion rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing unary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.unaryDtypeSignatures( dt, dt );\n > var t = {\n ... 'default': base.identity,\n ... 'complex64': base.cidentityf,\n ... 'complex128': base.cidentity\n ... };\n > var out = base.strided.unarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.unaryDtypeSignatures\n","base.strided.variance":"\nbase.strided.variance( N, correction, x, strideX )\n Computes the variance of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variance( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variance( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance","base.strided.variancech":"\nbase.strided.variancech( N, correction, x, strideX )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variancech( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variancech( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance","base.strided.variancepn":"\nbase.strided.variancepn( N, correction, x, strideX )\n Computes the variance of a strided array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance","base.strided.variancetk":"\nbase.strided.variancetk( N, correction, x, strideX )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variancetk( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variancetk( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance","base.strided.variancewd":"\nbase.strided.variancewd( N, correction, x, strideX )\n Computes the variance of a strided array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variancewd( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variancewd( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance","base.strided.varianceyc":"\nbase.strided.varianceyc( N, correction, x, strideX )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc( x.length, 1.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.varianceyc( 3, 1.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.varianceyc( 3, 1.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.varianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.varianceyc.ndarray( 3, 1.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.varianceyc.ndarray( 3, 1.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance","base.strided.zmap":"\nbase.strided.zmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\n > var v = y.get( 0 )\n [ 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > y = new Complex128Array( x.length );\n > base.strided.zmap( 2, x, 2, y, -1, base.cidentity );\n > v = y.get( 0 )\n [ 5.0, 6.0 ]\n\n // Using view offsets:\n > var x0 = new Complex128Array( xbuf );\n > var y0 = new Complex128Array( x0.length );\n > var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\n > v = y1.get( 0 )\n [ 7.0, 8.0 ]\n\n\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n > var v = y.get( 0 )\n [ 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Complex128Array( xbuf );\n > y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n > v = y.get( y.length-1 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.cmap, base.strided.unary\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n > var v = y.get( 0 )\n [ 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Complex128Array( xbuf );\n > y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n > v = y.get( y.length-1 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.cmap, base.strided.unary","base.str2multislice":"\nbase.str2multislice( str )\n Parses a string-serialized MultiSlice object.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n s: MultiSlice|null\n MultiSlice instance (or null).\n\n Examples\n --------\n > var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\n > s.data\n [ null, null, null ]\n > s = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\n > s.data\n [ 10, , null ]\n\n See Also\n --------\n base.str2slice\n","base.str2slice":"\nbase.str2slice( str )\n Parses a string-serialized Slice object.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n s: Slice|null\n Slice instance (or null).\n\n Examples\n --------\n > var s = new base.str2slice( 'Slice(1,10,1)' );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new base.str2slice( 'Slice(2,5,2)' );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n base.str2multislice\n","base.sub":"\nbase.sub( x, y )\n Subtracts two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.sub( -1.0, 5.0 )\n -6.0\n > v = base.sub( 2.0, 5.0 )\n -3.0\n > v = base.sub( 0.0, 5.0 )\n -5.0\n > v = base.sub( -0.0, 0.0 )\n -0.0\n > v = base.sub( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.div, base.mul\n","base.subf":"\nbase.subf( x, y )\n Subtracts two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.subf( -1.0, 5.0 )\n -6.0\n > v = base.subf( 2.0, 5.0 )\n -3.0\n > v = base.subf( 0.0, 5.0 )\n -5.0\n > v = base.subf( -0.0, 0.0 )\n -0.0\n > v = base.subf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.divf, base.mulf, base.sub\n","base.sumSeries":"\nbase.sumSeries( generator[, options] )\n Sum the elements of the series given by the supplied function.\n\n Parameters\n ----------\n generator: Function\n Series function.\n\n options: Object (optional)\n Options.\n\n options.maxTerms: integer (optional)\n Maximum number of terms to be added. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n the current term times the tolerance. Default: `2.22e-16`.\n\n options.initialValue: number (optional)\n Initial value of the resulting sum. Default: `0`.\n\n Returns\n -------\n out: number\n Sum of series terms.\n\n Examples\n --------\n // Using an ES6 generator function:\n > function* geometricSeriesGenerator( x ) {\n ... var exponent = 0;\n ... while ( true ) {\n ... yield Math.pow( x, exponent );\n ... exponent += 1;\n ... }\n ... };\n > var gen = geometricSeriesGenerator( 0.9 );\n > var out = base.sumSeries( gen )\n 10\n\n // Using a closure:\n > function geometricSeriesClosure( x ) {\n ... var exponent = -1;\n ... return function() {\n ... exponent += 1;\n ... return Math.pow( x, exponent );\n ... };\n ... };\n > gen = geometricSeriesClosure( 0.9 );\n > out = base.sumSeries( gen )\n 10\n\n // Setting an initial value for the sum:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n 3\n // Changing the maximum number of terms to be summed:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n ~1.998 // Infinite sum is 2\n\n // Adjusting the used tolerance:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n ~1.998\n\n","base.tan":"\nbase.tan( x )\n Computes the tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tan( 0.0 )\n ~0.0\n > y = base.tan( -PI/4.0 )\n ~-1.0\n > y = base.tan( PI/4.0 )\n ~1.0\n > y = base.tan( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sin\n","base.tand":"\nbase.tand( x )\n Computes the tangent of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tand( 0.0 )\n 0.0\n > y = base.tand( 90.0 )\n Infinity\n > y = base.tand( 60.0 )\n ~1.73\n > y = base.tand( NaN )\n NaN\n\n See Also\n --------\n base.tan, base.cosd\n","base.tanh":"\nbase.tanh( x )\n Computes the hyperbolic tangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic tangent.\n\n Examples\n --------\n > var y = base.tanh( 0.0 )\n 0.0\n > var y = base.tanh( -0.0 )\n -0.0\n > y = base.tanh( 2.0 )\n ~0.964\n > y = base.tanh( -2.0 )\n ~-0.964\n > y = base.tanh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sinh, base.tan\n","base.toBinaryString":"\nbase.toBinaryString( x )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bstr: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryString( 4.0 )\n '0100000000010000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PI )\n '0100000000001001001000011111101101010100010001000010110100011000'\n > str = base.toBinaryString( -1.0e308 )\n '1111111111100001110011001111001110000101111010111100100010100000'\n > str = base.toBinaryString( -3.14e-320 )\n '1000000000000000000000000000000000000000000000000001100011010011'\n > str = base.toBinaryString( 5.0e-324 )\n '0000000000000000000000000000000000000000000000000000000000000001'\n > str = base.toBinaryString( 0.0 )\n '0000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( -0.0 )\n '1000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NaN )\n '0111111111111000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PINF )\n '0111111111110000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NINF )\n '1111111111110000000000000000000000000000000000000000000000000000'\n\n See Also\n --------\n base.fromBinaryString, base.toBinaryStringf\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\n '01000000100000000000000000000000'\n > str = base.toBinaryStringf( base.float64ToFloat32( PI ) )\n '01000000010010010000111111011011'\n > str = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\n '11111110100101100111011010011001'\n > str = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\n '10000000001000100011000100001011'\n > str = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringf( 0.0 )\n '00000000000000000000000000000000'\n > str = base.toBinaryStringf( -0.0 )\n '10000000000000000000000000000000'\n > str = base.toBinaryStringf( NaN )\n '01111111110000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_PINF )\n '01111111100000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_NINF )\n '11111111100000000000000000000000'\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 8-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 8-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned 8-bit\n integers. Accordingly, care should be taken to ensure that only nonnegative\n integer values less than `256` (`2^8`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint8Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint8( a[ 0 ] )\n '00000001'\n > str = base.toBinaryStringUint8( a[ 1 ] )\n '00000100'\n > str = base.toBinaryStringUint8( a[ 2 ] )\n '00001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 16-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 16-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 16-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `65536` (`2^16`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint16Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint16( a[ 0 ] )\n '0000000000000001'\n > str = base.toBinaryStringUint16( a[ 1 ] )\n '0000000000000100'\n > str = base.toBinaryStringUint16( a[ 2 ] )\n '0000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 32-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 32-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 32-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint32Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint32( a[ 0 ] )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringUint32( a[ 1 ] )\n '00000000000000000000000000000100'\n > str = base.toBinaryStringUint32( a[ 2 ] )\n '00000000000000000000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toWordf":"\nbase.toWordf( x )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var f32 = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n > var w = base.toWordf( f32 )\n 1068180177\n\n See Also\n --------\n base.fromWordf, base.toWords\n","base.toWords":"\nbase.toWords( x )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array\n Higher and lower order words.\n\n Examples\n --------\n > var w = base.toWords( 3.14e201 )\n [ 1774486211, 2479577218 ]\n\n\nbase.toWords.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var out = new Uint32Array( 2 );\n > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.toWords.assign":"\nbase.toWords.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var out = new Uint32Array( 2 );\n > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.transpose":"\nbase.transpose( x, writable )\n Transposes a matrix (or a stack of matrices).\n\n The returned ndarray is a *view* of the input ndarray. Accordingly, writing\n to the original ndarray will mutate the returned ndarray and vice versa.\n\n The `writable` parameter only applies to ndarray constructors supporting\n read-only instances.\n\n If provided an ndarray with fewer than two dimensions, the function raises\n an exception.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n writable: boolean\n Boolean indicating whether the returned ndarray should be writable.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ [ 1, 2, 3 ], [ 4, 5, 6 ] ]\n > var y = base.transpose( x, false )\n [ [ 1, 4 ], [ 2, 5 ], [ 3, 6 ] ]\n\n See Also\n --------\n ndarray\n","base.tribonacci":"\nbase.tribonacci( n )\n Computes the nth Tribonacci number.\n\n Tribonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2} + F_{n-3}\n\n with seed values F_0 = 0, F_1 = 0, and F_2 = 1.\n\n If `n` is greater than `63`, the function returns `NaN`, as larger\n Tribonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Tribonacci number.\n\n Examples\n --------\n > var y = base.tribonacci( 0 )\n 0\n > y = base.tribonacci( 1 )\n 0\n > y = base.tribonacci( 2 )\n 1\n > y = base.tribonacci( 3 )\n 1\n > y = base.tribonacci( 4 )\n 2\n > y = base.tribonacci( 64 )\n NaN\n > y = base.tribonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.trigamma":"\nbase.trigamma( x )\n Evaluates the trigamma function.\n\n If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n If provided `NaN`, the `function` returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.trigamma( -2.5 )\n ~9.539\n > y = base.trigamma( 1.0 )\n ~1.645\n > y = base.trigamma( 10.0 )\n ~0.105\n > y = base.trigamma( NaN )\n NaN\n > y = base.trigamma( -1.0 )\n NaN\n\n See Also\n --------\n base.digamma, base.gamma\n","base.trim":"\nbase.trim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n See Also\n --------\n base.leftTrim, base.rightTrim\n","base.trunc":"\nbase.trunc( x )\n Rounds a double-precision floating-point number toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc( 3.14 )\n 3.0\n > y = base.trunc( -4.2 )\n -4.0\n > y = base.trunc( -4.6 )\n -4.0\n > y = base.trunc( 9.5 )\n 9.0\n > y = base.trunc( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.round\n","base.trunc2":"\nbase.trunc2( x )\n Rounds a numeric value to the nearest power of two toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc2( 3.14 )\n 2.0\n > y = base.trunc2( -4.2 )\n -4.0\n > y = base.trunc2( -4.6 )\n -4.0\n > y = base.trunc2( 9.5 )\n 8.0\n > y = base.trunc2( 13.0 )\n 8.0\n > y = base.trunc2( -13.0 )\n -8.0\n > y = base.trunc2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round2, base.trunc, base.trunc10\n","base.trunc10":"\nbase.trunc10( x )\n Rounds a numeric value to the nearest power of ten toward zero.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc10( 3.14 )\n 1.0\n > y = base.trunc10( -4.2 )\n -1.0\n > y = base.trunc10( -4.6 )\n -1.0\n > y = base.trunc10( 9.5 )\n 1.0\n > y = base.trunc10( 13.0 )\n 10.0\n > y = base.trunc10( -13.0 )\n -10.0\n > y = base.trunc10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round10, base.trunc, base.trunc2\n","base.truncateMiddle":"\nbase.truncateMiddle( str, len, seq )\n Truncates the middle UTF-16 code units of a string to return a string\n having a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n seq: string\n Custom replacement sequence.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.truncateMiddle( str, 5, '...' )\n 'b...p'\n > out = base.truncateMiddle( str, 5, '|' )\n 'be|op'\n","base.truncb":"\nbase.truncb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.truncb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward zero:\n > y = base.truncb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.roundb, base.trunc, base.truncn\n","base.truncf":"\nbase.truncf( x )\n Rounds a single-precision floating-point number toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncf( 3.14 )\n 3.0\n > y = base.truncf( -4.2 )\n -4.0\n > y = base.truncf( -4.6 )\n -4.0\n > y = base.truncf( 9.5 )\n 9.0\n > y = base.truncf( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceilf, base.floorf, base.trunc\n","base.truncn":"\nbase.truncn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round behavior:\n > y = base.truncn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.truncn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.roundn, base.trunc, base.truncb\n","base.truncsd":"\nbase.truncsd( x, n, b )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncsd( 3.14159, 5, 10 )\n 3.1415\n > y = base.truncsd( 3.14159, 1, 10 )\n 3.0\n > y = base.truncsd( 12368.0, 2, 10 )\n 12000.0\n > y = base.truncsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.roundsd, base.trunc\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\n -1\n > y = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n 3\n\n","base.umul":"\nbase.umul( x, y )\n Multiples two unsigned 32-bit integers.\n\n The function performs C-like multiplication of two unsigned 32-bit integers,\n including wraparound semantics.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n y: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.umul( 10>>>0, 4>>>0 )\n 40\n\n See Also\n --------\n base.imul\n","base.umuldw":"\nbase.umuldw( a, b )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: Array\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.umuldw( 1, 10 )\n [ 0, 10 ]\n\n\nbase.umuldw.assign( a, b, out, stride, offset )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imuldw, base.umul\n","base.umuldw.assign":"\nbase.umuldw.assign( a, b, out, stride, offset )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imuldw, base.umul","base.uncapitalize":"\nbase.uncapitalize( str )\n Lowercases the first character of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = base.uncapitalize( 'Beep' )\n 'beep'\n > out = base.uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n base.capitalize\n","base.uppercase":"\nbase.uppercase( str )\n Converts a string to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = base.uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n base.lowercase\n","base.vercos":"\nbase.vercos( x )\n Computes the versed cosine.\n\n The versed cosine is defined as `1 + cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed cosine.\n\n Examples\n --------\n > var y = base.vercos( 3.14 )\n ~0.0\n > y = base.vercos( -4.2 )\n ~0.5097\n > y = base.vercos( -4.6 )\n ~0.8878\n > y = base.vercos( 9.5 )\n ~0.0028\n > y = base.vercos( -0.0 )\n 2.0\n\n See Also\n --------\n base.cos, base.versin\n","base.versin":"\nbase.versin( x )\n Computes the versed sine.\n\n The versed sine is defined as `1 - cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed sine.\n\n Examples\n --------\n > var y = base.versin( 3.14 )\n ~2.0\n > y = base.versin( -4.2 )\n ~1.490\n > y = base.versin( -4.6 )\n ~1.112\n > y = base.versin( 9.5 )\n ~1.997\n > y = base.versin( -0.0 )\n 0.0\n\n See Also\n --------\n base.cos, base.sin, base.vercos\n","base.wrap":"\nbase.wrap( v, min, max )\n Wraps a value to the half-open interval `[min,max)`.\n\n The function does not distinguish between positive and negative zero. Where\n appropriate, the function returns positive zero.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to wrap.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Wrapped value.\n\n Examples\n --------\n > var y = base.wrap( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.wrap( -3.14, 0.0, 5.0 )\n ~1.86\n > y = base.wrap( 3.14, 0.0, 3.0 )\n ~0.14\n > y = base.wrap( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.wrap( 0.0, -3.14, -0.0 )\n -3.14\n > y = base.wrap( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.xlog1py":"\nbase.xlog1py( x, y )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlog1py( 3.0, 2.0 )\n ~3.296\n > out = base.xlog1py( 1.5, 5.9 )\n ~2.897\n > out = base.xlog1py( 0.9, 1.0 )\n ~0.624\n > out = base.xlog1py( 1.0, 0.0 )\n 0.0\n > out = base.xlog1py( 0.0, -2.0 )\n 0.0\n > out = base.xlog1py( 1.5, NaN )\n NaN\n > out = base.xlog1py( 0.0, NaN )\n NaN\n > out = base.xlog1py( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.log1p, base.xlogy\n","base.xlogy":"\nbase.xlogy( x, y )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlogy( 3.0, 2.0 )\n ~2.079\n > out = base.xlogy( 1.5, 5.9 )\n ~2.662\n > out = base.xlogy( 0.9, 1.0 )\n 0.0\n > out = base.xlogy( 0.0, -2.0 )\n 0.0\n > out = base.xlogy( 1.5, NaN )\n NaN\n > out = base.xlogy( 0.0, NaN )\n NaN\n > out = base.xlogy( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.ln, base.xlog1py\n","base.zeta":"\nbase.zeta( s )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.zeta( 1.1 )\n ~10.584\n > y = base.zeta( -4.0 )\n 0.0\n > y = base.zeta( 70.0 )\n 1.0\n > y = base.zeta( 0.5 )\n ~-1.46\n > y = base.zeta( NaN )\n NaN\n\n // Evaluate at a pole:\n > y = base.zeta( 1.0 )\n NaN\n\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and other characteristics.\n\n Each array element has the following eleven fields:\n\n - education: number of years of education.\n - south: indicator variable for southern region (1 if a person lives in the\n South; 0 if a person does not live in the South).\n - gender: gender of the person.\n - experience: number of years of work experience.\n - union: indicator variable for union membership (1 if union member; 0 if\n not a union member).\n - wage: log-transformed wage (in dollars per hour).\n - age: age (in years).\n - race: ethnicity/race (white, hispanic, and other).\n - occupation: occupational category (management, sales, clerical, service,\n professional, and other).\n - sector: sector (other, manufacturing, or construction).\n - married: marital status (0 if unmarried; 1 if married).\n\n Based on residual plots, wages were log-transformed to stabilize the\n variance.\n\n Returns\n -------\n out: Array\n CPS data.\n\n Examples\n --------\n > var data = BERNDT_CPS_WAGES_1985()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n Longman Publishing Co.\n\n","bifurcate":"\nbifurcate( collection, [options,] filter )\n Splits values into two groups.\n\n If an element in `filter` is truthy, then the corresponding element in the\n input collection belongs to the first group; otherwise, the collection\n element belongs to the second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n filter: Array|TypedArray|Object\n A collection indicating which group an element in the input collection\n belongs to. If an element in `filter` is truthy, the corresponding\n element in `collection` belongs to the first group; otherwise, the\n collection element belongs to the second group. If provided an object,\n the object must be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var f = [ true, true, false, true ];\n > var out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n > f = [ 1, 1, 0, 1 ];\n > out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > f = [ true, true, false, true ];\n > var opts = { 'returns': 'indices' };\n > out = bifurcate( collection, opts, f )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = bifurcate( collection, opts, f )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n See Also\n --------\n bifurcateBy, bifurcateOwn, group\n","bifurcateBy":"\nbifurcateBy( collection, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If a predicate function returns a truthy value, a collection value is\n placed in the first group; otherwise, a collection value is placed in the\n second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = bifurcateBy( collection, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, groupBy\n","bifurcateByAsync":"\nbifurcateByAsync( collection, [options,] predicate, done )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an predicate function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If a predicate function calls the `next` callback with a truthy group value,\n a collection value is placed in the first group; otherwise, a collection\n value is placed in the second group.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n [ [ 1000, 3000 ], [ 2500 ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ 2, 0 ], [ 1 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n // Limit number of concurrent invocations:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n // Process sequentially:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync","bifurcateIn":"\nbifurcateIn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object with no prototype, the function returns an empty\n array.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var out = bifurcateIn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateOwn, groupIn\n","bifurcateOwn":"\nbifurcateOwn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object, the function returns an empty array.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = bifurcateOwn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateIn, groupOwn\n","BigInt":"\nBigInt( value )\n Returns a BigInt.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support BigInts.\n\n Parameters\n ----------\n value: integer|string\n Value of the BigInt.\n\n Returns\n -------\n out: BigInt\n BigInt.\n\n Examples\n --------\n > var v = ( BigInt ) ? BigInt( '1' ) : null\n\n\nTODO: document properties/methods\n\n","binomialTest":"\nbinomialTest( x[, n][, options] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: (number|Array)\n Number of successes or two-element array with successes and failures.\n\n n: Array (optional)\n Total number of observations.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.p: number (optional)\n Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Sample proportion.\n\n out.ci: Array\n 1-alpha confidence interval for the success probability.\n\n out.nullValue: number\n Assumed success probability under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var out = binomialTest( 682, 925 )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( [ 682, 925 - 682 ] )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( 21, 40, {\n ... 'p': 0.4,\n ... 'alternative': 'greater'\n ... })\n {\n 'pValue': ~0.074,\n 'statistic': 0.525\n // ...\n }\n\n","Boolean":"\nBoolean( value )\n Returns a boolean.\n\n When invoked without `new`,\n\n - if provided `false`, `null`, `undefined`, `-0`, `0`, `NaN`, or an empty\n string, the function returns `false`.\n - if provided any other value, including an empty object, an empty array,\n the string `'false'`, or a `Boolean` object (including a `Boolean` object\n whose value is `false`), the function returns `true`.\n\n When invoked with `new`, the constructor returns a `Boolean` object, which\n is an object wrapper for a primitive boolean value. The value of the\n returned `Boolean` object follows the same conversion semantics as when the\n constructor is invoked without `new`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: boolean|Boolean\n Boolean primitive or object.\n\n Examples\n --------\n > var b = new Boolean( null )\n \n > b = Boolean( null )\n false\n > b = Boolean( [] )\n true\n\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n\n Returns\n -------\n out: string\n String representation.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.toString()\n 'true'\n\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n\n Returns\n -------\n out: boolean\n Boolean primitive.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.valueOf()\n true\n\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n\n Returns\n -------\n out: string\n String representation.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.toString()\n 'true'","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n\n Returns\n -------\n out: boolean\n Boolean primitive.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.valueOf()\n true","BooleanArray":"\nBooleanArray()\n A Boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = new BooleanArray()\n \n\n\nBooleanArray( length )\n Creates a boolean array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10\n\n\nBooleanArray( booleanarray )\n Creates a boolean array from another boolean array.\n\n Parameters\n ----------\n booleanarray: BooleanArray\n Boolean array from which to generate another boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new BooleanArray( [ true, false, false, true ] )\n \n > var arr2 = new BooleanArray( arr1 )\n \n > var len = arr2.length\n 4\n\n\nBooleanArray( typedarray )\n Creates a boolean array from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var buf = new Uint8Array( [ 1, 0, 0, 1 ] )\n \n > var arr = new BooleanArray( buf )\n \n > var len = arr.length\n 4\n\n\nBooleanArray( obj )\n Creates a boolean array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new BooleanArray( [ true, false, false, true ] )\n \n > var len = arr1.length\n 4\n > var arr2 = new BooleanArray( [ {}, null, '', 4 ] );\n > len = arr2.length\n 4\n\n\nBooleanArray( buffer[, byteOffset[, length]] )\n Returns a boolean array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 240 );\n > var arr1 = new BooleanArray( buf )\n \n > var len = arr1.length\n 240\n > var arr2 = new BooleanArray( buf, 8 )\n \n > len = arr2.length\n 232\n > var arr3 = new BooleanArray( buf, 8, 20 )\n \n > len = arr3.length\n 20\n\n\nBooleanArray.from( src[, clbk[, thisArg]] )\n Creates a new boolean array from an array-like object or an iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > function map( v ) { return !v };\n > var src = [ true, false ];\n > var arr = BooleanArray.from( src, map )\n \n > var len = arr.length\n 2\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.of( element0[, element1[, ...elementN]] )\n Creates a new boolean array from a variable number of arguments.\n\n Parameters\n ----------\n element0: bool\n Array element.\n\n element1: bool (optional)\n Array element.\n\n elementN: ...bool (optional)\n Array elements.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = BooleanArray.of( true, false, false, true )\n \n > var len = arr.length\n 4\n\n\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n 1\n\n\nBooleanArray.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = BooleanArray.name\n 'BooleanArray'\n\n\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > var buf = arr.buffer\n \n\n\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var nbytes = arr.byteLength\n 10\n\n\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new BooleanArray( buf, 64 )\n \n > offset = arr.byteOffset\n 64\n\n\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 1\n\n\nBooleanArray.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10\n\n\nBooleanArray.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n An array element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > var v = arr.at( 1 )\n false\n > v = arr.at( -1 )\n true\n\n\nBooleanArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, true ]\n > v = it.next().value\n [ 1, false ]\n > v = it.next().value\n [ 2, true ]\n > var bool = it.next().done\n true\n\n\nBooleanArray.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, true, true ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nBooleanArray.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: boolean\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( 3 )\n \n > arr.fill( true );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n true\n\n\nBooleanArray.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( v === true ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.find( predicate )\n true\n\n\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.findLast( predicate )\n true\n\n\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findLastIndex( predicate )\n 2\n\n\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.forEach( clbk );\n > str\n '%true%false%false%true%'\n\n\nBooleanArray.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.set( true, 0 );\n > var v = arr.get( 0 )\n true\n\n\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var bool = arr.includes( true )\n true\n > bool = arr.includes( false, 3 )\n false\n\n\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var idx = arr.indexOf( true )\n 0\n > idx = arr.indexOf( false, 3 )\n -1\n\n\nBooleanArray.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.join()\n 'true,false,true'\n > str = arr.join( '|' )\n 'true|false|true'\n\n\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, true, true, false, true ] )\n \n > var idx = arr.lastIndexOf( false )\n 3\n > idx = arr.lastIndexOf( false, 2 )\n -1\n\n\nBooleanArray.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function invert( v ) { return !v; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.map( invert )\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false\n\n\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduce( reducer )\n false\n\n\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduceRight( reducer )\n false\n\n\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > arr.reverse();\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n false\n > v = arr.get( 2 )\n true\n\n\nBooleanArray.prototype.set( v[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n truthy and falsy values.\n\n Parameters\n ----------\n v: bool|BooleanArray|ArrayLikeObject\n Boolean value or Boolean value array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > arr.set( false );\n > var v = arr.get( 0 )\n false\n > arr.set( true, 1 );\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 4\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ false, true, false ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nBooleanArray.prototype.sort( [compareFunction] )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > arr.sort( compare );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n false\n\n\nBooleanArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array view.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toLocaleString()\n 'true,false,true'\n\n\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > var out = arr.toReversed()\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n false\n > v = out.get( 2 )\n true\n\n\nBooleanArray.prototype.toSorted( [compareFunction] )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.toSorted( compare );\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false\n\n\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n out: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toString()\n 'true,false,true'\n\n\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.values();\n > var v = it.next().value\n true\n > v = it.next().value\n false\n > var bool = it.next().done\n true\n\n\nBooleanArray.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: boolean\n Element value.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.with( 0, false )\n \n > var v = out.get( 0 )\n false\n\n\n See Also\n --------\n ArrayBuffer","BooleanArray.from":"\nBooleanArray.from( src[, clbk[, thisArg]] )\n Creates a new boolean array from an array-like object or an iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > function map( v ) { return !v };\n > var src = [ true, false ];\n > var arr = BooleanArray.from( src, map )\n \n > var len = arr.length\n 2\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true","BooleanArray.of":"\nBooleanArray.of( element0[, element1[, ...elementN]] )\n Creates a new boolean array from a variable number of arguments.\n\n Parameters\n ----------\n element0: bool\n Array element.\n\n element1: bool (optional)\n Array element.\n\n elementN: ...bool (optional)\n Array elements.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = BooleanArray.of( true, false, false, true )\n \n > var len = arr.length\n 4","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n 1","BooleanArray.name":"\nBooleanArray.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = BooleanArray.name\n 'BooleanArray'","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > var buf = arr.buffer\n ","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var nbytes = arr.byteLength\n 10","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new BooleanArray( buf, 64 )\n \n > offset = arr.byteOffset\n 64","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 1","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n An array element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > var v = arr.at( 1 )\n false\n > v = arr.at( -1 )\n true","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, true ]\n > v = it.next().value\n [ 1, false ]\n > v = it.next().value\n [ 2, true ]\n > var bool = it.next().done\n true","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, true, true ] )\n \n > var bool = arr.every( predicate )\n true","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: boolean\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( 3 )\n \n > arr.fill( true );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n true","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( v === true ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.find( predicate )\n true","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findIndex( predicate )\n 0","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.findLast( predicate )\n true","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findLastIndex( predicate )\n 2","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.forEach( clbk );\n > str\n '%true%false%false%true%'","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.set( true, 0 );\n > var v = arr.get( 0 )\n true","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var bool = arr.includes( true )\n true\n > bool = arr.includes( false, 3 )\n false","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var idx = arr.indexOf( true )\n 0\n > idx = arr.indexOf( false, 3 )\n -1","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.join()\n 'true,false,true'\n > str = arr.join( '|' )\n 'true|false|true'","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, true, true, false, true ] )\n \n > var idx = arr.lastIndexOf( false )\n 3\n > idx = arr.lastIndexOf( false, 2 )\n -1","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function invert( v ) { return !v; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.map( invert )\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduce( reducer )\n false","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduceRight( reducer )\n false","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > arr.reverse();\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n false\n > v = arr.get( 2 )\n true","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n truthy and falsy values.\n\n Parameters\n ----------\n v: bool|BooleanArray|ArrayLikeObject\n Boolean value or Boolean value array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > arr.set( false );\n > var v = arr.get( 0 )\n false\n > arr.set( true, 1 );\n > v = arr.get( 1 )\n true","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 4\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ false, true, false ] )\n \n > var bool = arr.some( predicate )\n true","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction] )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > arr.sort( compare );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n false","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array view.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toLocaleString()\n 'true,false,true'","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > var out = arr.toReversed()\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n false\n > v = out.get( 2 )\n true","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction] )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.toSorted( compare );\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n out: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toString()\n 'true,false,true'","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.values();\n > var v = it.next().value\n true\n > v = it.next().value\n false\n > var bool = it.next().done\n true","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: boolean\n Element value.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.with( 0, false )\n \n > var v = out.get( 0 )\n false\n\n\n See Also\n --------\n ArrayBuffer","broadcastArray":"\nbroadcastArray( x, shape )\n Broadcasts an ndarray to a specified shape.\n\n The returned array is a read-only view on the input array data buffer. The\n view is typically *not* contiguous. As more than one element of a returned\n view may refer to the same memory location, writing to the input array may\n affect multiple elements. If you need to write to the input array, copy the\n input array before broadcasting.\n\n The function throws an error if a provided ndarray is incompatible with a\n provided shape.\n\n The function always returns a new ndarray instance even if the input ndarray\n shape and the desired shape are the same.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n shape: ArrayLikeObject\n Desired shape.\n\n Returns\n -------\n out: ndarray\n Broadcasted array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = broadcastArray( x, [ 3, 2, 2 ] )\n \n > sh = y.shape\n [ 3, 2, 2 ]\n > var v = y.get( 0, 0, 0 )\n 1\n > v = y.get( 0, 0, 1 )\n 2\n > v = y.get( 0, 1, 0 )\n 3\n > v = y.get( 0, 1, 1 )\n 4\n > v = y.get( 1, 0, 0 )\n 1\n > v = y.get( 1, 1, 0 )\n 3\n > v = y.get( 2, 0, 0 )\n 1\n > v = y.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, broadcastArrays, ndarray, maybeBroadcastArray\n","broadcastArrays":"\nbroadcastArrays( ...arrays )\n Broadcasts ndarrays to a common shape.\n\n The function supports two (mutually exclusive) means of providing ndarray\n arguments:\n\n 1. Providing a single array containing ndarray arguments.\n 2. Providing ndarray arguments as separate arguments.\n\n The returned arrays are read-only views on their respective underlying\n array data buffers. The views are typically **not** contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to a view may affect multiple elements. If you need to write to an\n input array, copy the array before broadcasting.\n\n The function throws an error if provided broadcast-incompatible ndarrays.\n\n The function always returns new ndarray instances even if an input ndarray\n and the broadcasted shape are the same.\n\n Parameters\n ----------\n arrays: ...ndarray|ArrayLikeObject\n Array arguments.\n\n Returns\n -------\n out: Array\n Broadcasted arrays.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = ndzeros( [ 3, 2, 2 ] )\n \n > var out = broadcastArrays( [ x, y ] )\n [ , ]\n\n // Retrieve the broadcasted \"x\" array:\n > var bx = out[ 0 ]\n \n > sh = bx.shape\n [ 3, 2, 2 ]\n\n // Retrieve broadcasted elements...\n > var v = bx.get( 0, 0, 0 )\n 1\n > v = bx.get( 0, 0, 1 )\n 2\n > v = bx.get( 0, 1, 0 )\n 3\n > v = bx.get( 0, 1, 1 )\n 4\n > v = bx.get( 1, 0, 0 )\n 1\n > v = bx.get( 1, 1, 0 )\n 3\n > v = bx.get( 2, 0, 0 )\n 1\n > v = bx.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, broadcastArray, ndarray, maybeBroadcastArrays\n","Buffer":"\nBuffer\n Buffer constructor.\n\n\nBuffer( size )\n Allocates a buffer having a specified number of bytes.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 4 )\n \n\n\nBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n > var b2 = new Buffer( b1 )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n Allocates a buffer using an array of octets.\n\n Parameters\n ----------\n array: Array\n Array of octets.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 'beep boop' )\n \n\n\nTODO: add methods and properties\n\n\n See Also\n --------\n ArrayBuffer\n","buffer2json":"\nbuffer2json( buffer )\n Returns a JSON representation of a buffer.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n out.type: string\n Value type. The assigned value is always \"Buffer\".\n\n out.data: Array\n Buffer data.\n\n Examples\n --------\n > var buf = new allocUnsafe( 2 );\n > buf[ 0 ] = 1;\n > buf[ 1 ] = 2;\n > var json = buffer2json( buf )\n { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n See Also\n --------\n typedarray2json, reviveBuffer\n","BYTE_ORDER":"\nBYTE_ORDER\n Platform byte order.\n\n Possible values:\n\n - 'little-endian'\n - 'big-endian'\n - 'mixed-endian'\n - 'unknown'\n\n Examples\n --------\n > BYTE_ORDER\n \n\n See Also\n --------\n IS_BIG_ENDIAN, IS_LITTLE_ENDIAN\n","camelcase":"\ncamelcase( str )\n Converts a string to camel case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Camel-cased string.\n\n Examples\n --------\n > var out = camelcase( 'Hello World!' )\n 'helloWorld'\n > out = camelcase( 'beep boop' )\n 'beepBoop'\n\n See Also\n --------\n constantcase, kebabcase, pascalcase, snakecase","capitalize":"\ncapitalize( str )\n Capitalizes the first character in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = capitalize( 'beep' )\n 'Beep'\n > out = capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n uncapitalize, uppercase\n","capitalizeKeys":"\ncapitalizeKeys( obj )\n Converts the first letter of each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'aa': 1, 'bb': 2 };\n > var out = capitalizeKeys( obj )\n { 'Aa': 1, 'Bb': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","CATALAN":"\nCATALAN\n Catalan's constant.\n\n Examples\n --------\n > CATALAN\n 0.915965594177219\n\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n\n Examples\n --------\n > CBRT_EPS\n 0.0000060554544523933395\n\n See Also\n --------\n EPS, SQRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n Returns US birth data from 1969 to 1988, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_BIRTHS_1969_1988()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1994_2003, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n Returns US birth data from 1994 to 2003, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_BIRTHS_1994_2003()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1969_1988, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n the Center for Disease Control and Prevention's National Center for Health\n Statistics.\n\n All birth data by race before 1980 are based on race of the child. Starting\n in 1980, birth data by race are based on race of the mother. Birth data are\n used to calculate infant mortality rate.\n\n Returns\n -------\n out: Object\n Infant mortality data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n { 'black': [...], 'white': [...] }\n\n","chdir":"\nchdir( path )\n Changes the current working directory.\n\n If unable to set the current working directory (e.g., due to a non-existent\n path), the function returns an error; otherwise, the function returns\n `null`.\n\n Parameters\n ----------\n path: string\n Desired working directory.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = chdir( '/path/to/current/working/directory' )\n\n See Also\n --------\n cwd\n","chi2gof":"\nchi2gof( x, y[, ...args][, options] )\n Performs a chi-square goodness-of-fit test.\n\n A chi-square goodness-of-fit test is computed for the null hypothesis that\n the values of `x` come from the discrete probability distribution specified\n by `y`.\n\n The second argument can either be expected frequencies, population\n probabilities summing to one, or a discrete probability distribution name to\n test against.\n\n When providing a discrete probability distribution name, distribution\n parameters *must* be supplied as additional arguments.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n By default, the p-value is computed using a chi-square distribution with\n `k-1` degrees of freedom, where `k` is the length of `x`.\n\n If provided distribution arguments are estimated (e.g., via maximum\n likelihood estimation), the degrees of freedom should be corrected. Set the\n `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n freedom adjustment.\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five.\n\n Instead of relying on chi-square approximation to calculate the p-value, one\n can use Monte Carlo simulation. When the `simulate` option is `true`, the\n simulation is performed by re-sampling from the discrete probability\n distribution specified by `y`.\n\n Parameters\n ----------\n x: ndarray|Array|TypedArray\n Observation frequencies.\n\n y: ndarray|Array|TypedArray|string\n Expected frequencies, population probabilities, or a discrete\n probability distribution name.\n\n args: ...number (optional)\n Distribution parameters. Distribution parameters will be passed to a\n probability mass function (PMF) as arguments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.ddof: number (optional)\n Delta degrees of freedom adjustment. Default: 0.\n\n options.simulate: boolean (optional)\n Boolean indicating whether to calculate p-values by Monte Carlo\n simulation. The simulation is performed by re-sampling from the discrete\n distribution specified by `y`. Default: false.\n\n options.iterations: number (optional)\n Number of Monte Carlo iterations. Default: 500.\n\n Returns\n -------\n out: Object\n Test results object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number|null\n Degrees of freedom.\n\n out.method: string\n Test name.\n\n out.toString: Function\n Serializes results as formatted output.\n\n out.toJSON: Function\n Serializes results as JSON.\n\n Examples\n --------\n // Provide expected probabilities...\n > var x = [ 89, 37, 30, 28, 2 ];\n > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > var out = chi2gof( x, p );\n > var o = out.toJSON()\n { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n > out.toString()\n\n // Set significance level...\n > var opts = { 'alpha': 0.01 };\n > out = chi2gof( x, p, opts );\n > out.toString()\n\n // Calculate the test p-value via Monte Carlo simulation...\n > x = [ 89, 37, 30, 28, 2 ];\n > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > opts = { 'simulate': true, 'iterations': 1000 };\n > out = chi2gof( x, p, opts );\n > out.toString()\n\n // Verify that data comes from Poisson distribution...\n > var lambda = 3.0;\n > var rpois = base.random.poisson.factory( lambda );\n > var len = 400;\n > x = [];\n > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n // Generate a frequency table...\n > var freqs = new Int32Array( len );\n > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n > out = chi2gof( freqs, 'poisson', lambda );\n > out.toString()\n\n","chi2test":"\nchi2test( x[, options] )\n Performs a chi-square independence test.\n\n For a two-way contingency table, the function computes a chi-square\n independence test for the null hypothesis that the joint distribution of the\n cell counts is the product of the row and column marginals (i.e. that the\n row and column variables are independent).\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five. The Yates' continuity correction is enabled\n by default for 2x2 tables to account for this, although it tends to\n over-correct.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n Parameters\n ----------\n x: ndarray|Array>\n Two-way table of observed frequencies.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.correct: boolean (optional)\n Boolean indicating whether to use Yates' continuity correction when\n provided a 2x2 contingency table. Default: true.\n\n Returns\n -------\n out: Object\n Test results object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number\n Degrees of freedom.\n\n out.expected: ndarray\n Expected frequencies.\n\n out.method: string\n Test name.\n\n out.toString: Function\n Serializes results as formatted output.\n\n out.toJSON: Function\n Serializes results as JSON.\n\n Examples\n --------\n > var x = [ [ 20, 30 ], [ 30, 20 ] ];\n > var out = chi2test( x );\n > var o = out.toJSON()\n { 'rejected': false, 'pValue': ~0.072, 'statistic': 3.24, ... }\n > out.toString()\n\n // Set significance level...\n > var opts = { 'alpha': 0.1 };\n > out = chi2test( x, opts );\n > o = out.toJSON()\n { 'rejected': true, 'pValue': ~0.072, 'statistic': 3.24, ... }\n > out.toString()\n\n // Disable Yates' continuity correction (primarily used with small counts):\n > opts = { 'correct': false };\n > out = chi2test( x, opts );\n > out.toString()\n\n","circarray2iterator":"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, an iterator iterates over elements\n from right-to-left. Default: 1.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n array2iterator, stridedarray2iterator\n","circularArrayStream":"\ncircularArrayStream( src[, options] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream","CircularBuffer":"\nCircularBuffer( buffer )\n Circular buffer constructor.\n\n Parameters\n ----------\n buffer: integer|ArrayLike\n Buffer size or an array-like object to use as the underlying buffer.\n\n Returns\n -------\n buf: Object\n Circular buffer data structure.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.length\n 3\n > b.count\n 3\n > b.push( 'boop' )\n 'foo'\n\n\nCircularBuffer.prototype.clear()\n Clears a buffer.\n\n Returns\n -------\n out: Object\n Circular buffer instance.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.count\n 3\n > b.clear();\n > b.count\n 0\n\n\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n\n Returns\n -------\n out: integer\n Number of elements currently in the buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.count\n 0\n > b.push( 'foo' );\n > b.count\n 1\n > b.push( 'bar' );\n > b.count\n 2\n\n\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a circular buffer is full.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.full\n false\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.full\n true\n\n\nCircularBuffer.prototype.iterator( [niters] )\n Returns an iterator for iterating over a circular buffer.\n\n A returned iterator does not iterate over partially full buffers.\n\n Parameters\n ----------\n niters: integer (optional)\n Number of iterations. Default: infinity.\n\n Returns\n -------\n out: Iterator\n Iterator.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var it = b.iterator( b.length );\n > var v = it.next().value\n 'bar'\n > v = it.next().value\n 'beep'\n > v = it.next().value\n 'boop'\n > var bool = it.next().done\n true\n\n\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n\n Returns\n -------\n out: integer\n Buffer length.\n\n Examples\n --------\n > var b = CircularBuffer( [ 0, 0, 0 ] );\n > var len = b.length\n 3\n\n\nCircularBuffer.prototype.push( value )\n Adds a value to a circular buffer.\n\n Parameters\n ----------\n value: any\n Value to add.\n\n Returns\n -------\n out: any\n Removed element (or undefined).\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' )\n undefined\n > b.push( 'bar' )\n undefined\n > b.push( 'beep' )\n undefined\n > b.push( 'boop' )\n 'foo'\n\n\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n\n Returns\n -------\n out: Array\n Circular buffer values.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var vals = b.toArray()\n [ 'bar', 'beep', 'boop' ]\n\n\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n\n Returns\n -------\n out: Object\n Serialized circular buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var o = b.toJSON()\n {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n See Also\n --------\n FIFO, Stack\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n Clears a buffer.\n\n Returns\n -------\n out: Object\n Circular buffer instance.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.count\n 3\n > b.clear();\n > b.count\n 0","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n\n Returns\n -------\n out: integer\n Number of elements currently in the buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.count\n 0\n > b.push( 'foo' );\n > b.count\n 1\n > b.push( 'bar' );\n > b.count\n 2","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a circular buffer is full.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.full\n false\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.full\n true","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters] )\n Returns an iterator for iterating over a circular buffer.\n\n A returned iterator does not iterate over partially full buffers.\n\n Parameters\n ----------\n niters: integer (optional)\n Number of iterations. Default: infinity.\n\n Returns\n -------\n out: Iterator\n Iterator.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var it = b.iterator( b.length );\n > var v = it.next().value\n 'bar'\n > v = it.next().value\n 'beep'\n > v = it.next().value\n 'boop'\n > var bool = it.next().done\n true","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n\n Returns\n -------\n out: integer\n Buffer length.\n\n Examples\n --------\n > var b = CircularBuffer( [ 0, 0, 0 ] );\n > var len = b.length\n 3","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value )\n Adds a value to a circular buffer.\n\n Parameters\n ----------\n value: any\n Value to add.\n\n Returns\n -------\n out: any\n Removed element (or undefined).\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' )\n undefined\n > b.push( 'bar' )\n undefined\n > b.push( 'beep' )\n undefined\n > b.push( 'boop' )\n 'foo'","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n\n Returns\n -------\n out: Array\n Circular buffer values.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var vals = b.toArray()\n [ 'bar', 'beep', 'boop' ]","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n\n Returns\n -------\n out: Object\n Serialized circular buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var o = b.toJSON()\n {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n See Also\n --------\n FIFO, Stack","close":"\nclose( fd, clbk )\n Asynchronously closes a file descriptor, so that the file descriptor no\n longer refers to any file and may be reused.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n clbk: Function\n Callback to invoke upon closing a file descriptor.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close( fd, done ); };\n\n\nclose.sync( fd )\n Synchronously closes a file descriptor.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n Returns\n -------\n out: Error|void\n If an error occurs, an error object; otherwise, undefined.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n exists, open, readFile\n","close.sync":"\nclose.sync( fd )\n Synchronously closes a file descriptor.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n Returns\n -------\n out: Error|void\n If an error occurs, an error object; otherwise, undefined.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n exists, open, readFile","CMUDICT":"\nCMUDICT( [options] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n Data includes the following:\n\n - dict: the main pronouncing dictionary.\n - phones: manners of articulation for each sound.\n - symbols: complete list of ARPABET symbols used by the dictionary.\n - vp: verbal pronunciations of punctuation marks.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n CMUdict dataset.\n\n Examples\n --------\n > var data = CMUDICT();\n > var dict = data.dict\n {...}\n > var phones = data.phones\n {...}\n > var symbols = data.symbols\n [...]\n > var vp = data.vp\n {...}\n\n","codePointAt":"\ncodePointAt( str, idx[, backward] )\n Returns a Unicode code point from a string at a specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n idx: integer\n Position. If less than `0`, the string position is determined relative\n to the end of the input string.\n\n backward: boolean (optional)\n Backward iteration for low surrogates. Default: false.\n\n Returns\n -------\n out: integer\n Unicode code point.\n\n Examples\n --------\n > var out = codePointAt( 'last man standing', 4 )\n 32\n > out = codePointAt( 'presidential election', 8, true )\n 116\n > out = codePointAt( 'अनुच्छेद', 2 )\n 2369\n > out = codePointAt( '🌷', 1, true )\n 127799\n\n See Also\n --------\n fromCodePoint","commonKeys":"\ncommonKeys( obj1, obj2[, ...obj] )\n Returns the common own property names of two or more objects.\n\n Parameters\n ----------\n obj1: any\n First object.\n\n obj2: any\n Second object.\n\n obj: ...any (optional)\n Additional objects.\n\n Returns\n -------\n out: Array\n Common keys of objects.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > var keys = commonKeys( obj1, obj2 )\n [ 'a', 'b' ]\n\n See Also\n --------\n commonKeysIn, objectKeys","commonKeysIn":"\ncommonKeysIn( obj1, obj2[, ...obj] )\n Returns the common own and inherited property names of two or more objects.\n\n Parameters\n ----------\n obj1: any\n First object.\n\n obj2: any\n Second object.\n\n obj: ...any (optional)\n Additional objects.\n\n Returns\n -------\n out: Array\n Common keys.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > var keys = commonKeysIn( obj1, obj2 )\n [ 'a', 'b' ]\n\n See Also\n --------\n commonKeys, keysIn","complex":"\ncomplex( real, imag[, dtype] )\n Creates a complex number.\n\n The function supports the following data types:\n\n - float64\n - float32\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n z: Complex\n Complex number.\n\n Examples\n --------\n > var z = complex( 5.0, 3.0, 'float64' )\n \n > z = complex( 5.0, 3.0, 'float32' )\n \n\n See Also\n --------\n Complex128, Complex64\n","Complex64":"\nComplex64( real, imag )\n 64-bit complex number constructor.\n\n Both the real and imaginary components are stored as single-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex64\n 64-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n\nComplex64.name\n Constructor name.\n\n Examples\n --------\n > var str = Complex64.name\n 'Complex64'\n\n\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex64.BYTES_PER_ELEMENT\n 4\n\n\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 4\n\n\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.byteLength\n 8\n\n See Also\n --------\n complex, Complex128\n","Complex64.name":"\nComplex64.name\n Constructor name.\n\n Examples\n --------\n > var str = Complex64.name\n 'Complex64'","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex64.BYTES_PER_ELEMENT\n 4","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 4","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.byteLength\n 8\n\n See Also\n --------\n complex, Complex128","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n Canonical single-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX64_NAN\n \n\n See Also\n --------\n COMPLEX128_NAN\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n\n Examples\n --------\n > COMPLEX64_NUM_BYTES\n 8\n\n See Also\n --------\n COMPLEX128_NUM_BYTES, FLOAT32_NUM_BYTES\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n Single-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX64_ZERO\n \n\n See Also\n --------\n COMPLEX128_ZERO\n","Complex64Array":"\nComplex64Array()\n A 64-bit complex number array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex64Array()\n \n\n\nComplex64Array( length )\n Creates a 64-bit complex number array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex64Array( complexarray )\n Creates a 64-bit complex number array from another complex number array.\n\n Parameters\n ----------\n complexarray: Complex64Array\n Complex array from which to generate another complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr2 = new Complex64Array( arr1 )\n \n > var len = arr2.length\n 2\n\n\nComplex64Array( typedarray )\n Creates a 64-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr = new Complex64Array( buf )\n \n > var len = arr.length\n 2\n\n\nComplex64Array( obj )\n Creates a 64-bit complex number array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var len = arr1.length\n 2\n > var buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\n > var arr2 = new Complex64Array( buf )\n \n > len = arr2.length\n 2\n\n\nComplex64Array( buffer[, byteOffset[, length]] )\n Returns a 64-bit complex number array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 240 );\n > var arr1 = new Complex64Array( buf )\n \n > var len = arr1.length\n 30\n > var arr2 = new Complex64Array( buf, 8 )\n \n > len = arr2.length\n 29\n > var arr3 = new Complex64Array( buf, 8, 20 )\n \n > len = arr3.length\n 20\n\n\nComplex64Array.from( src[, clbk[, thisArg]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n \n Returns\n -------\n out: Complex64Array\n A typed array.\n \n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n\n\nComplex64Array.of( element0[, element1[, ...elementN]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex64( 1.0, -1.0 );\n > var z2 = new Complex64( 2.0, -2.0 );\n > arr = Complex64Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n\n\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n 8\n\n\nComplex64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex64Array.name\n 'Complex64Array'\n\n\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > var buf = arr.buffer\n \n\n\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var nbytes = arr.byteLength\n 80\n\n\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 5 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new Complex64Array( buf, 64 )\n \n > offset = arr.byteOffset\n 64\n\n\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 8\n\n\nComplex64Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex64Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex64|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n\n\nComplex64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, ]\n > var re = realf( v[ 1 ] )\n 1.0\n > var im = imagf( v[ 1 ] )\n -1.0\n > v = it.next().value\n [ 1, ]\n > re = realf( v[ 1 ] )\n 2.0\n > im = imagf( v[ 1 ] )\n -2.0\n > v = it.next().value\n [ 2, ]\n > re = realf( v[ 1 ] )\n 3.0\n > im = imagf( v[ 1 ] )\n -3.0\n > var bool = it.next().done\n true\n\n\nComplex64Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nComplex64Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex64\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex64Array( 3 )\n \n > arr.fill( new Complex64( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 1.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0\n\n\nComplex64Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n 2.0\n\n\nComplex64Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 1.0\n\n\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context. \n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n 2.0\n\n\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1\n\n\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'\n\n\nComplex64Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n\n\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n false\n\n\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n -1\n\n\nComplex64Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n \n Returns\n -------\n out: string\n Array serialized as a string.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'\n\n\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n 0\n\n\nComplex64Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n \n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n\n\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element. \n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.caddf )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.caddf )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n -1.0\n\n\nComplex64Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex64|Complex64Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > arr.set( new Complex64( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n\n\nComplex64Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n \n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n \n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nComplex64Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n \n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'\n\n\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n 3.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n 2.0\n > z = out.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0\n\n\nComplex64Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n \n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = out.get( 2 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = realf( v )\n 1.0\n > var im = imagf( v )\n -1.0\n > v = it.next().value\n \n > re = realf( v )\n 2.0\n > im = imagf( v )\n -2.0\n > var bool = it.next().done\n true\n\n\nComplex64Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: Complex64\n Element value. \n\n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\n See Also\n --------\n Complex128Array, complex, Complex64","Complex64Array.from":"\nComplex64Array.from( src[, clbk[, thisArg]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n \n Returns\n -------\n out: Complex64Array\n A typed array.\n \n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0","Complex64Array.of":"\nComplex64Array.of( element0[, element1[, ...elementN]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex64( 1.0, -1.0 );\n > var z2 = new Complex64( 2.0, -2.0 );\n > arr = Complex64Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n 8","Complex64Array.name":"\nComplex64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex64Array.name\n 'Complex64Array'","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > var buf = arr.buffer\n ","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var nbytes = arr.byteLength\n 80","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 5 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new Complex64Array( buf, 64 )\n \n > offset = arr.byteOffset\n 64","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 8","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex64|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, ]\n > var re = realf( v[ 1 ] )\n 1.0\n > var im = imagf( v[ 1 ] )\n -1.0\n > v = it.next().value\n [ 1, ]\n > re = realf( v[ 1 ] )\n 2.0\n > im = imagf( v[ 1 ] )\n -2.0\n > v = it.next().value\n [ 2, ]\n > re = realf( v[ 1 ] )\n 3.0\n > im = imagf( v[ 1 ] )\n -3.0\n > var bool = it.next().done\n true","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex64\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex64Array( 3 )\n \n > arr.fill( new Complex64( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 1.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n 2.0","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 1.0","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context. \n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n 2.0","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n false","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n -1","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n \n Returns\n -------\n out: string\n Array serialized as a string.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n 0","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n \n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element. \n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.caddf )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.caddf )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n -1.0","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex64|Complex64Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > arr.set( new Complex64( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n \n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n \n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n \n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n 3.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n 2.0\n > z = out.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n \n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = out.get( 2 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = realf( v )\n 1.0\n > var im = imagf( v )\n -1.0\n > v = it.next().value\n \n > re = realf( v )\n 2.0\n > im = imagf( v )\n -2.0\n > var bool = it.next().done\n true","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: Complex64\n Element value. \n\n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\n See Also\n --------\n Complex128Array, complex, Complex64","Complex128":"\nComplex128( real, imag )\n 128-bit complex number constructor.\n\n Both the real and imaginary components are stored as double-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex128\n 128-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n\nComplex128.name\n Constructor name.\n\n Examples\n --------\n > var str = Complex128.name\n 'Complex128'\n\n\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex128.BYTES_PER_ELEMENT\n 8\n\n\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 8\n\n\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.byteLength\n 16\n\n See Also\n --------\n complex, Complex64\n","Complex128.name":"\nComplex128.name\n Constructor name.\n\n Examples\n --------\n > var str = Complex128.name\n 'Complex128'","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex128.BYTES_PER_ELEMENT\n 8","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 8","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.byteLength\n 16\n\n See Also\n --------\n complex, Complex64","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX128_NAN\n \n\n See Also\n --------\n COMPLEX64_NAN\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n\n Examples\n --------\n > COMPLEX128_NUM_BYTES\n 16\n\n See Also\n --------\n COMPLEX64_NUM_BYTES, FLOAT64_NUM_BYTES\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX128_ZERO\n \n\n See Also\n --------\n COMPLEX64_ZERO\n","Complex128Array":"\nComplex128Array()\n A 128-bit complex number array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex128Array()\n \n\n\nComplex128Array( length )\n Creates a 128-bit complex number array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex128Array( complexarray )\n Creates a 64-bit complex number array from another complex number array.\n\n Parameters\n ----------\n complexarray: Complex128Array\n Complex array from which to generate another complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr2 = new Complex128Array( arr1 )\n \n > var len = arr2.length\n 2\n\n\nComplex128Array( typedarray )\n Creates a 128-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr = new Complex128Array( buf )\n \n > var len = arr.length\n 2\n\n\nComplex128Array( obj )\n Creates a 128-bit complex number array from an array-like object or \n iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var len = arr1.length\n 2\n > var buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\n > var arr2 = new Complex128Array( buf )\n \n > len = arr2.length\n 2\n\n\nComplex128Array( buffer[, byteOffset[, length]] )\n Returns a 128-bit complex number array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 480 );\n > var arr1 = new Complex128Array( buf )\n \n > var len = arr1.length\n 30\n > var arr2 = new Complex128Array( buf, 16 )\n \n > len = arr2.length\n 29\n > var arr3 = new Complex128Array( buf, 16, 20 )\n \n > len = arr3.length\n 20\n\n\nComplex128Array.from( src[, clbk[, thisArg]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n \n Returns\n -------\n out: Complex128Array\n A typed array.\n \n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n\n\nComplex128Array.of( element0[, element1[, ...elementN]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number|ComplexLike\n Array element.\n\n element1: number |ComplexLike(optional)\n Array element.\n\n elementN: ...number|ComplexLike (optional)\n Array elements.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex128( 1.0, -1.0 );\n > var z2 = new Complex128( 2.0, -2.0 );\n > arr = Complex128Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n\n\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n 16\n\n\nComplex128Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex128Array.name\n 'Complex128Array'\n\n\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > var buf = arr.buffer\n \n\n\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var nbytes = arr.byteLength\n 160\n\n\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 480 );\n > arr = new Complex128Array( buf, 128 )\n \n > offset = arr.byteOffset\n 128\n\n\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 16\n\n\nComplex128Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex128Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n\n\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, ]\n > var re = real( v[ 1 ] )\n 1.0\n > var im = imag( v[ 1 ] )\n -1.0\n > v = it.next().value\n [ 1, ]\n > re = real( v[ 1 ] )\n 2.0\n > im = imag( v[ 1 ] )\n -2.0\n > v = it.next().value\n [ 2, ]\n > re = real( v[ 1 ] )\n 3.0\n > im = imag( v[ 1 ] )\n -3.0\n > var bool = it.next().done\n true\n\n\nComplex128Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) > 0.0 ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nComplex128Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex128\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex128Array( 3 )\n \n > arr.fill( new Complex128( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n 1.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n\n\nComplex128Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n 2.0\n\n\nComplex128Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n 1.0\n\n\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context. \n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n 2.0\n\n\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1\n\n\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'\n\n\nComplex128Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n\n\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n false\n\n\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n -1\n\n\nComplex128Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n \n Returns\n -------\n out: string\n Array serialized as a string.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'\n\n\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n 0\n\n\nComplex128Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n \n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n\n\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element. \n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.cadd )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.cadd )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n -1.0\n\n\nComplex128Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex128|Complex128Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > arr.set( new Complex128( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n\n\nComplex128Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n \n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n \n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nComplex128Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n \n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'\n\n\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n 3.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n 2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n\n\nComplex128Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n \n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n -1.0\n > v = it.next().value\n \n > re = real( v )\n 2.0\n > im = imag( v )\n -2.0\n > var bool = it.next().done\n true\n\n\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: Complex128\n Element value. \n\n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\n See Also\n --------\n Complex64Array, complex, Complex128","Complex128Array.from":"\nComplex128Array.from( src[, clbk[, thisArg]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n \n Returns\n -------\n out: Complex128Array\n A typed array.\n \n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0","Complex128Array.of":"\nComplex128Array.of( element0[, element1[, ...elementN]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number|ComplexLike\n Array element.\n\n element1: number |ComplexLike(optional)\n Array element.\n\n elementN: ...number|ComplexLike (optional)\n Array elements.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex128( 1.0, -1.0 );\n > var z2 = new Complex128( 2.0, -2.0 );\n > arr = Complex128Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n 16","Complex128Array.name":"\nComplex128Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex128Array.name\n 'Complex128Array'","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > var buf = arr.buffer\n ","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var nbytes = arr.byteLength\n 160","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 480 );\n > arr = new Complex128Array( buf, 128 )\n \n > offset = arr.byteOffset\n 128","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 16","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, ]\n > var re = real( v[ 1 ] )\n 1.0\n > var im = imag( v[ 1 ] )\n -1.0\n > v = it.next().value\n [ 1, ]\n > re = real( v[ 1 ] )\n 2.0\n > im = imag( v[ 1 ] )\n -2.0\n > v = it.next().value\n [ 2, ]\n > re = real( v[ 1 ] )\n 3.0\n > im = imag( v[ 1 ] )\n -3.0\n > var bool = it.next().done\n true","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) > 0.0 ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex128\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex128Array( 3 )\n \n > arr.fill( new Complex128( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n 1.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n 2.0","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n 1.0","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context. \n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n 2.0","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n false","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n -1","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n \n Returns\n -------\n out: string\n Array serialized as a string.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n 0","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n \n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element. \n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.cadd )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.cadd )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n -1.0","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex128|Complex128Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > arr.set( new Complex128( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n \n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n \n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n \n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n 3.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n 2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n \n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n -1.0\n > v = it.next().value\n \n > re = real( v )\n 2.0\n > im = imag( v )\n -2.0\n > var bool = it.next().done\n true","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: Complex128\n Element value. \n\n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\n See Also\n --------\n Complex64Array, complex, Complex128","complexarray":"\ncomplexarray( [dtype] )\n Creates a complex typed array.\n\n The function supports the following data types:\n\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n\n The default typed array data type is `complex128`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray()\n \n > arr = complexarray( 'complex64' )\n \n\n\ncomplexarray( length[, dtype] )\n Returns a complex number typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray( 5 )\n \n > arr = complexarray( 5, 'complex64' )\n \n\n\ncomplexarray( complexarray[, dtype] )\n Creates a complex number typed array from another complex number typed\n array.\n\n Parameters\n ----------\n complexarray: ComplexArray\n Complex number typed array from which to generate another complex number\n typed array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( obj[, dtype] )\n Creates a complex number typed array from an array-like object or iterable.\n\n If an array-like object contains interleaved real and imaginary components,\n the array-like object must have a length which is a multiple of two.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a complex number typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first array element.\n Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = complexarray( buf, 0, 8, 'complex64' )\n \n\n See Also\n --------\n typedarray, realarray\n","complexarrayCtors":"\ncomplexarrayCtors( dtype )\n Returns a complex typed array constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Complex typed array constructor.\n\n Examples\n --------\n > var ctor = complexarrayCtors( 'complex64' )\n \n > ctor = complexarrayCtors( 'float32' )\n null\n\n See Also\n --------\n arrayCtors, typedarrayCtors, realarrayCtors\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n\n Returns\n -------\n out: Array\n List of complex typed array data types.\n\n Examples\n --------\n > var out = complexarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, typedarrayDataTypes, realarrayDataTypes, ndarrayDataTypes\n","complexCtors":"\ncomplexCtors( dtype )\n Returns a complex number constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = complexCtors( 'complex128' )\n \n > ctor = complexCtors( 'complex' )\n null\n\n See Also\n --------\n complexarrayCtors\n","complexDataType":"\ncomplexDataType( value )\n Returns the data type of a complex number object.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var v = new Complex128( 1.0, 2.0 );\n > var dt = complexDataType( v )\n 'complex128'\n > dt = complexDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataType\n","complexDataTypes":"\ncomplexDataTypes()\n Returns a list of complex number data types.\n\n The output array contains the following data types:\n\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n\n Returns\n -------\n out: Array\n List of complex number data types.\n\n Examples\n --------\n > var out = complexDataTypes()\n \n\n See Also\n --------\n complexarrayDataTypes\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1, dtype2] )\n Returns the complex number data type with the smallest size and closest\n \"kind\" to which data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n Data type.\n\n dtype2: string (optional)\n Data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = complexPromotionRules( 'complex128', 'complex64' )\n 'complex128'\n\n See Also\n --------\n arrayPromotionRules, ndarrayPromotionRules\n","compose":"\ncompose( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as an argument\n to the next function. The result of the leftmost function is the result\n of the whole.\n\n Notes:\n\n - Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n - The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x ) {\n ... return 2 * x;\n ... }\n > function b( x ) {\n ... return x + 3;\n ... }\n > function c( x ) {\n ... return x / 5;\n ... }\n > var f = compose( c, b, a );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n composeAsync\n","composeAsync":"\ncomposeAsync( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as the first argument\n of the next function. The result of the leftmost function is the result\n of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - error: error argument.\n - result: function result.\n\n If a composed function calls the `next` callback with a truthy `error`\n argument, the composite function suspends execution and immediately calls\n the `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = composeAsync( c, b, a );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n compose\n","configdir":"\nconfigdir( [p] )\n Returns a directory for user-specific configuration files.\n\n On Windows platforms, the function first checks for a `LOCALAPPDATA`\n environment variable before checking for an `APPDATA` environment variable.\n This means that machine specific user configuration files have precedence\n over roaming user configuration files.\n\n On non-Windows platforms, if the function is unable to locate the current\n user's `home` directory, the function returns `null`. Similarly, on Windows\n platforms, if the function is unable to locate an application data\n directory, the function also returns `null`.\n\n Parameters\n ----------\n p: string (optional)\n Path to append to a base directory.\n\n Returns\n -------\n out: string|null\n Directory.\n\n Examples\n --------\n > var dir = configdir()\n e.g., '/Users//Library/Preferences'\n > dir = configdir( 'appname/config' )\n e.g., '/Users//Library/Preferences/appname/config'\n\n See Also\n --------\n homedir, tmpdir\n","conj":"\nconj( z )\n Returns the complex conjugate of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conj( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n imag, real, reim\n","conjf":"\nconjf( z )\n Returns the complex conjugate of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conjf( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n conj, imagf, realf, reimf\n","constantcase":"\nconstantcase( str )\n Converts a string to constant case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Constant-cased string.\n\n Examples\n --------\n > var out = constantcase( 'Hello World!' )\n 'HELLO_WORLD'\n > out = constantcase( 'I am a tiny little teapot' )\n 'I_AM_A_TINY_LITTLE_TEAPOT'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","constantFunction":"\nconstantFunction( val )\n Creates a function which always returns the same value.\n\n Notes:\n\n - When provided an object reference, the returned `function` always returns\n the same reference.\n\n Parameters\n ----------\n val: any\n Value to always return.\n\n Returns\n -------\n out: Function\n Constant function.\n\n Examples\n --------\n > var fcn = constantFunction( 3.14 );\n > var v = fcn()\n 3.14\n > v = fcn()\n 3.14\n > v = fcn()\n 3.14\n\n See Also\n --------\n argumentFunction, identity\n","constantStream":"\nconstantStream( value[, options] )\n Returns a readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream( 'beep', opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream\n","constantStream.factory":"\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );","constantStream.objectMode":"\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream","constructorName":"\nconstructorName( val )\n Determines the name of a value's constructor.\n\n Parameters\n ----------\n val: any\n Input value.\n\n Returns\n -------\n out: string\n Name of a value's constructor.\n\n Examples\n --------\n > var v = constructorName( 'a' )\n 'String'\n > v = constructorName( {} )\n 'Object'\n > v = constructorName( true )\n 'Boolean'\n\n See Also\n --------\n functionName\n","contains":"\ncontains( value, searchValue[, position] )\n Tests if an array-like value contains a search value.\n\n When `value` is a string, the function checks whether the characters of the\n search string are found in the input string. The search is case-sensitive.\n\n When `value` is an array-like object, the function checks whether the input\n array contains an element strictly equal to the specified search value.\n\n For strings, this function is modeled after `String.prototype.includes`,\n part of the ECMAScript 6 specification. This function is different from a\n call to `String.prototype.includes.call` insofar as type-checking is\n performed for all arguments.\n\n The function does distinguish between positive and negative zero.\n\n If `position < 0`, the search is performed for the entire input array or\n string.\n\n\n Parameters\n ----------\n value: ArrayLike\n Input value.\n\n searchValue: any\n Value to search for.\n\n position: integer (optional)\n Position at which to start searching for `searchValue`. Default: `0`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input value contains another value.\n\n Examples\n --------\n > var bool = contains( 'Hello World', 'World' )\n true\n > bool = contains( 'Hello World', 'world' )\n false\n > bool = contains( [ 1, 2, 3, 4 ], 2 )\n true\n > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n true\n\n // Supply a position:\n > bool = contains( 'Hello World', 'Hello', 6 )\n false\n > bool = contains( [ true, NaN, false ], true, 1 )\n false\n\n","convertArray":"\nconvertArray( arr, dtype )\n Converts an input array to an array of a different data type.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Array to convert.\n\n dtype: string\n Output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n > var out = convertArray( arr, 'float32' )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArraySame\n","convertArraySame":"\nconvertArraySame( x, y )\n Converts an input array to the same data type as a second input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Array to convert.\n\n y: Array|TypedArray\n Array having desired output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = new Float32Array( 0 );\n > var out = convertArraySame( x, y )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArray\n","convertPath":"\nconvertPath( from, to )\n Converts between POSIX and Windows paths.\n\n Parameters\n ----------\n from: string\n Input path.\n\n to: string\n Output path convention: 'win32', 'mixed', or 'posix'.\n\n Returns\n -------\n out: string\n Converted path.\n\n Examples\n --------\n > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n 'c:\\foo\\bar\\beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n 'c:/foo/bar/beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\n 'C:\\\\foo\\bar\\beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\n 'C:/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n\n","copy":"\ncopy( value[, level] )\n Copy or deep clone a value to an arbitrary depth.\n\n The implementation can handle circular references.\n\n If a `Number`, `String`, or `Boolean` object is encountered, the value is\n cloned as a primitive. This behavior is intentional.\n\n For objects, the implementation only copies enumerable keys and their\n associated property descriptors.\n\n The implementation only checks whether basic `Objects`, `Arrays`, and class\n instances are extensible, sealed, and/or frozen.\n\n Functions are not cloned; their reference is copied.\n\n The implementation supports custom error types which are `Error` instances\n (e.g., ES2015 subclasses).\n\n Support for copying class instances is inherently fragile. Any instances\n with privileged access to variables (e.g., within closures) cannot be\n cloned. This stated, basic copying of class instances is supported. Provided\n an environment which supports ES5, the implementation is greedy and performs\n a deep clone of any arbitrary class instance and its properties. The\n implementation assumes that the concept of `level` applies only to the class\n instance reference, but not to its internal state.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n level: integer (optional)\n Copy depth. Default: Infinity.\n\n Returns\n -------\n out: any\n Value copy.\n\n Examples\n --------\n > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > var out = copy( value )\n [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n > var bool = ( value[ 0 ].c === out[ 0 ].c )\n false\n\n // Set the `level` option to limit the copy depth:\n > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > out = copy( value, 1 );\n > bool = ( value[ 0 ] === out[ 0 ] )\n true\n > bool = ( value[ 0 ].c === out[ 0 ].c )\n true\n\n\n See Also\n --------\n merge\n","copyBuffer":"\ncopyBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = array2buffer( [ 1, 2, 3, 4 ] );\n > var b2 = copyBuffer( b1 )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n allocUnsafe, Buffer\n","countBy":"\ncountBy( collection, [options,] indicator )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = countBy( collection, indicator )\n { 'b': 3, 'other': 1 }\n\n See Also\n --------\n group, groupBy\n","countByAsync":"\ncountByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"even\": 2, \"odd\": 1 }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync\n","countByAsync.factory":"\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync","currentYear":"\ncurrentYear()\n Returns the current year.\n\n Returns\n -------\n out: integer\n Current year.\n\n Examples\n --------\n > var y = currentYear()\n \n\n See Also\n --------\n isCurrentYear\n","curry":"\ncurry( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curry( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curry( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curry( obj.greet, obj );\n > var str = f( 'Hello' )( 'there' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curryRight, uncurry, uncurryRight\n","curryRight":"\ncurryRight( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n This function applies arguments starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curryRight( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curryRight( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curryRight( obj.greet, obj );\n > var str = f( 'there' )( 'Hello' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curry, uncurry, uncurryRight\n","cwd":"\ncwd()\n Returns the current working directory.\n\n Returns\n -------\n path: string\n Current working directory of the process.\n\n Examples\n --------\n > var dir = cwd()\n '/path/to/current/working/directory'\n\n See Also\n --------\n chdir\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar American-English words.\n\n Returns\n -------\n out: Array\n List of familiar American-English words.\n\n Examples\n --------\n > var list = DALE_CHALL_NEW()\n [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n References\n ----------\n - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n the new Dale-Chall readability formula*. Brookline Books.\n .\n\n","datasets":"\ndatasets( name[, options] )\n Returns a dataset.\n\n The function forwards provided options to the dataset interface specified\n by `name`.\n\n Parameters\n ----------\n name: string\n Dataset name.\n\n options: Object (optional)\n Function options.\n\n Returns\n -------\n out: any\n Dataset.\n\n Examples\n --------\n > var out = datasets( 'MONTH_NAMES_EN' )\n [ 'January', 'February', ... ]\n > var opts = { 'data': 'cities' };\n > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n [ {...}, {...}, ... ]\n\n","DataType":"\nDataType( value[, options] )\n Data type constructor.\n\n Parameters\n ----------\n value: any\n Data type value.\n\n options: Object (optional)\n Constructor options.\n\n options.description: string (optional)\n Data type description.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteLength\n 8\n\n\nDataType.name\n Constructor name.\n\n Returns\n -------\n out: string\n Constructor name.\n\n Examples\n --------\n > DataType.name\n 'DataType'\n\n\nDataType.prototype.alignment\n Alignment (in bytes) for the data type.\n\n If a data type does not have a known alignment, the returned value is -1.\n\n Returns\n -------\n out: integer\n Alignment (in bytes).\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.alignment\n 8\n\n\nDataType.prototype.byteLength\n Size (in bytes) of the data type.\n\n If a data type does not have a known size, the returned value is -1.\n\n Returns\n -------\n out: integer\n Byte length (in bytes).\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteLength\n 8\n\n\nDataType.prototype.byteOrder\n Data type byte order.\n\n May be one of the following values:\n\n - host: host platform byte order.\n - little-endian: little-endian byte order.\n - big-endian: big-endian byte order.\n\n Returns\n -------\n out: string\n Byte order.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteOrder\n 'host'\n\n\nDataType.prototype.char\n Single letter character abbreviation for the data type.\n\n If a data type does not have a corresponding single letter character\n abbreviation, the returned value is an empty string.\n\n Returns\n -------\n out: string\n Single letter character abbreviation.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.char\n 'd'\n\n\nDataType.prototype.description\n Data type description.\n\n If a data type does not have an associated description, the returned value\n is an empty string.\n\n Returns\n -------\n out: string\n Description.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.description\n '...'\n\n\nDataType.prototype.enum\n Enumeration constant for the data type.\n\n If a data type does not have a corresponding known enumeration constant, the\n returned value is -1.\n\n Returns\n -------\n out: integer\n Enumeration constant.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.enum\n \n\n\nDataType.prototype.value\n Raw (original) data type value.\n\n Returns\n -------\n out: any\n Data type value.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.value\n 'float64'\n\n\nDataType.prototype.toJSON()\n Serializes a data type instance as a JSON object.\n\n Returns\n -------\n out: Object\n JSON object.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.toJSON()\n {...}\n\n\nDataType.prototype.toString()\n Serializes a data type instance to a string.\n\n Returns\n -------\n out: string\n Serialized string.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.toString()\n 'float64'\n\n\nDataType.prototype.valueOf()\n Converts a data type instance to a primitive.\n\n This method returns the same value as `#.toString()`.\n\n Returns\n -------\n out: string\n Primitive value.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.valueOf()\n 'float64'\n\n See Also\n --------\n ndarray, ndarrayDataType\n\n","DataType.name":"\nDataType.name\n Constructor name.\n\n Returns\n -------\n out: string\n Constructor name.\n\n Examples\n --------\n > DataType.name\n 'DataType'","DataType.prototype.alignment":"\nDataType.prototype.alignment\n Alignment (in bytes) for the data type.\n\n If a data type does not have a known alignment, the returned value is -1.\n\n Returns\n -------\n out: integer\n Alignment (in bytes).\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.alignment\n 8","DataType.prototype.byteLength":"\nDataType.prototype.byteLength\n Size (in bytes) of the data type.\n\n If a data type does not have a known size, the returned value is -1.\n\n Returns\n -------\n out: integer\n Byte length (in bytes).\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteLength\n 8","DataType.prototype.byteOrder":"\nDataType.prototype.byteOrder\n Data type byte order.\n\n May be one of the following values:\n\n - host: host platform byte order.\n - little-endian: little-endian byte order.\n - big-endian: big-endian byte order.\n\n Returns\n -------\n out: string\n Byte order.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteOrder\n 'host'","DataType.prototype.char":"\nDataType.prototype.char\n Single letter character abbreviation for the data type.\n\n If a data type does not have a corresponding single letter character\n abbreviation, the returned value is an empty string.\n\n Returns\n -------\n out: string\n Single letter character abbreviation.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.char\n 'd'","DataType.prototype.description":"\nDataType.prototype.description\n Data type description.\n\n If a data type does not have an associated description, the returned value\n is an empty string.\n\n Returns\n -------\n out: string\n Description.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.description\n '...'","DataType.prototype.enum":"\nDataType.prototype.enum\n Enumeration constant for the data type.\n\n If a data type does not have a corresponding known enumeration constant, the\n returned value is -1.\n\n Returns\n -------\n out: integer\n Enumeration constant.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.enum\n ","DataType.prototype.value":"\nDataType.prototype.value\n Raw (original) data type value.\n\n Returns\n -------\n out: any\n Data type value.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.value\n 'float64'","DataType.prototype.toJSON":"\nDataType.prototype.toJSON()\n Serializes a data type instance as a JSON object.\n\n Returns\n -------\n out: Object\n JSON object.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.toJSON()\n {...}","DataType.prototype.toString":"\nDataType.prototype.toString()\n Serializes a data type instance to a string.\n\n Returns\n -------\n out: string\n Serialized string.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.toString()\n 'float64'","DataType.prototype.valueOf":"\nDataType.prototype.valueOf()\n Converts a data type instance to a primitive.\n\n This method returns the same value as `#.toString()`.\n\n Returns\n -------\n out: string\n Primitive value.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.valueOf()\n 'float64'\n\n See Also\n --------\n ndarray, ndarrayDataType","DataView":"\nDataView( buffer[, byteOffset[, byteLength]] )\n Returns a data view representing a provided array buffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer|SharedArrayBuffer\n Array buffer.\n\n byteOffset: integer (optional)\n Offset (in bytes) to the first byte in the array buffer for the new view\n to reference. Default: 0.\n\n byteLength: integer (optional)\n Number of elements in the byte array. If not provided, the view's length\n will equal the buffer's length.\n\n Returns\n -------\n out: DataView\n A data view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n > var dv = new DataView( buf )\n \n\n\nDataView.prototype.buffer\n Read-only property which returns the underlying array buffer.\n\n Examples\n --------\n > var buf1 = new ArrayBuffer( 5 );\n > var dv = new DataView( buf1 );\n > var buf2 = dv.buffer\n \n > var b = ( buf1 === buf2 )\n true\n\n\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf );\n > dv.byteLength\n 5\n\n\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf, 2 );\n > dv.byteLength\n 3\n > dv.byteOffset\n 2\n\n\nTODO: document properties/methods\n\n\n See Also\n --------\n ArrayBuffer, typedarray\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n Read-only property which returns the underlying array buffer.\n\n Examples\n --------\n > var buf1 = new ArrayBuffer( 5 );\n > var dv = new DataView( buf1 );\n > var buf2 = dv.buffer\n \n > var b = ( buf1 === buf2 )\n true","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf );\n > dv.byteLength\n 5","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf, 2 );\n > dv.byteLength\n 3\n > dv.byteOffset\n 2","datespace":"\ndatespace( start, stop[, length][ , options] )\n Generates an array of linearly spaced dates.\n\n Parameters\n ----------\n start: number\n Start time as either a `Date` object, Unix timestamp, JavaScript\n timestamp, or date string.\n\n stop: number\n Stop time as either a `Date` object, Unix timestamp, JavaScript\n timestamp, or date string.\n\n length: integer (optional)\n Length of output array. Default: `100`.\n\n options: Object (optional)\n Options.\n\n options.round: string (optional)\n Specifies how sub-millisecond times should be rounded:\n [ 'floor', 'ceil', 'round' ]. Default: 'floor'.\n\n Returns\n -------\n arr: Array\n Array of dates.\n\n Examples\n --------\n > var stop = '2014-12-02T07:00:54.973Z';\n > var start = new Date( stop ) - 60000;\n > var arr = datespace( start, stop, 6 )\n [...]\n\n // Equivalent of Math.ceil():\n > var opts = { 'round': 'ceil' };\n > arr = datespace( 1417503655000, 1417503655001, 3, opts )\n [...]\n\n See Also\n --------\n linspace, logspace\n","dayOfQuarter":"\ndayOfQuarter( [month[, day, year]] )\n Returns the day of the quarter.\n\n By default, the function returns the day of the quarter for the current date\n (according to local time). To determine the day of the quarter for a\n particular day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the quarter.\n\n Examples\n --------\n > var day = dayOfQuarter()\n \n > day = dayOfQuarter( new Date() )\n \n > day = dayOfQuarter( 12, 31, 2017 )\n 92\n\n // Other ways to supply month:\n > day = dayOfQuarter( 'dec', 31, 2017 )\n 92\n > day = dayOfQuarter( 'december', 31, 2017 )\n 92\n\n See Also\n --------\n dayOfYear\n","dayOfYear":"\ndayOfYear( [month[, day, year]] )\n Returns the day of the year.\n\n By default, the function returns the day of the year for the current date\n (according to local time). To determine the day of the year for a particular\n day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the year.\n\n Examples\n --------\n > var day = dayOfYear()\n \n > day = dayOfYear( new Date() )\n \n > day = dayOfYear( 12, 31, 2016 )\n 366\n\n // Other ways to supply month:\n > day = dayOfYear( 'dec', 31, 2016 )\n 366\n > day = dayOfYear( 'december', 31, 2016 )\n 366\n\n See Also\n --------\n dayOfQuarter\n","daysInMonth":"\ndaysInMonth( [month[, year]] )\n Returns the number of days in a month.\n\n By default, the function returns the number of days in the current month\n of the current year (according to local time). To determine the number of\n days for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Days in a month.\n\n Examples\n --------\n > var num = daysInMonth()\n \n > num = daysInMonth( 2 )\n \n > num = daysInMonth( 2, 2016 )\n 29\n > num = daysInMonth( 2, 2017 )\n 28\n\n // Other ways to supply month:\n > num = daysInMonth( 'feb', 2016 )\n 29\n > num = daysInMonth( 'february', 2016 )\n 29\n\n See Also\n --------\n daysInYear\n","daysInYear":"\ndaysInYear( [value] )\n Returns the number of days in a year according to the Gregorian calendar.\n\n By default, the function returns the number of days in the current year\n (according to local time). To determine the number of days for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of days in a year.\n\n Examples\n --------\n > var num = daysInYear()\n \n > num = daysInYear( 2016 )\n 366\n > num = daysInYear( 2017 )\n 365\n\n See Also\n --------\n daysInMonth\n","ddot":"\nddot( x, y[, dim] )\n Computes the dot product of two double-precision floating-point vectors.\n\n If provided at least one input array having more than one dimension, the\n input arrays are broadcasted to a common shape.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function computes the dot product for each pair\n of vectors in `x` and `y` according to the specified dimension index.\n\n The size of the contracted dimension must be the same for both input arrays.\n\n The function resolves the dimension index for which to compute the dot\n product *before* broadcasting.\n\n If provided empty vectors, the dot product is `0`.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float64' data type. Must have at least\n one dimension and be broadcast-compatible with the second input array.\n\n y: ndarray\n Second input array. Must have a 'float64' data type. Must have at least\n one dimension and be broadcast-compatible with the first input array.\n\n dim: integer (optional)\n Dimension index for which to compute the dot product. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n out: ndarray\n The dot product. The output array has the same data type as the input\n arrays and has a shape which is determined by broadcasting and excludes\n the contracted dimension.\n\n Examples\n --------\n > var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var x = array( xbuf );\n > var ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var y = array( ybuf );\n > var z = ddot( x, y )\n [ -5.0 ]\n\n See Also\n --------\n base.strided.ddot, gdot, sdot\n","debugSinkStream":"\ndebugSinkStream( [options,] [clbk] )\n Returns a writable stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > var s = debugSinkStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream","debugStream":"\ndebugStream( [options,] [clbk] )\n Returns a transform stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = debugStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","debugStream.factory":"\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );","debugStream.objectMode":"\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream","decorateAfter":"\ndecorateAfter( fcn, arity, after[, thisArg] )\n Decorates a provided function such that the function's return value is\n provided as an argument to another function.\n\n Decorators are intended to be transparent, meaning that, when interfacing\n with an API, the decorated API should have the same signature (i.e., number\n of parameters) as the decorated function.\n\n Thus, a typical value for `arity` is `fcn.length`. This function does not\n require equality, however, and the `arity` argument is allowed to diverge\n from that of the decorated function. Specifying a differing `arity` does\n *not* affect function evaluation behavior, as the returned function passes\n all provided arguments to the decorated function.\n\n If the `after` function returns `undefined`, the returned decorator returns\n the return value of the decorated function `fcn`; otherwise, the returned\n decorator returns the return value of `after`.\n\n The returned decorator supports an `arity` less than or equal to `10` (i.e.,\n the maximum arity of the returned function is `10`). For an arity greater\n than `10`, the returned function has an arity equal to `0`. While this\n violates strict notions of a decorator, for all practical purposes, this is\n unlikely to be an issue, as the vast majority of functions have fewer than\n `10` parameters and the need for explicitly checking function length is\n relatively uncommon.\n\n Common use cases for decorating a function with additional actions *after*\n invocation include logging, capturing invocation statistics, and validating\n return values.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5\n\n\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n\n Code generation may be problematic in browser contexts enforcing a strict\n content security policy] (CSP). If running in or targeting an environment\n with a CSP, avoid using code generation.\n\n For non-native functions, the function supports returning a decorator whose\n API exactly matches the API of the decorated function, including function\n length and parameter names.\n\n For native functions, due to how native functions serialize to strings, the\n function generates placeholder parameter names, which are unlikely to match\n the canonical parameter names. Using placeholder parameter names ensures\n that the length of the decorator (i.e., number of parameters) matches the\n decorated function and, except in scenarios involving function source code\n inspection, will not affect runtime behavior.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter.factory( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5\n\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n\n Code generation may be problematic in browser contexts enforcing a strict\n content security policy] (CSP). If running in or targeting an environment\n with a CSP, avoid using code generation.\n\n For non-native functions, the function supports returning a decorator whose\n API exactly matches the API of the decorated function, including function\n length and parameter names.\n\n For native functions, due to how native functions serialize to strings, the\n function generates placeholder parameter names, which are unlikely to match\n the canonical parameter names. Using placeholder parameter names ensures\n that the length of the decorator (i.e., number of parameters) matches the\n decorated function and, except in scenarios involving function source code\n inspection, will not affect runtime behavior.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter.factory( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5","deepEqual":"\ndeepEqual( a, b )\n Tests for deep equality between two values.\n\n Parameters\n ----------\n a: any\n First comparison value.\n\n b: any\n Second comparison value.\n\n Returns\n -------\n out: boolean\n Boolean indicating if `a` is deep equal to `b`.\n\n Examples\n --------\n > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n true\n\n > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n false\n\n > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n false\n\n See Also\n --------\n isStrictEqual, isSameValue\n","deepGet":"\ndeepGet( obj, path[, options] )\n Returns a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: any\n Nested property value.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a.b.c' )\n 'd'\n\n // Specify a custom separator via the `sep` option:\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n 'd'\n\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet\n","deepGet.factory":"\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet","deepHasOwnProp":"\ndeepHasOwnProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path.\n\n The function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepHasOwnProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet","deepHasProp":"\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasProp.factory":"\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet","deepPluck":"\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n See Also\n --------\n deepGet, deepSet\n","deepSet":"\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj1 = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj1, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > var obj2 = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj2, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj2\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > var obj3 = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj3, 'a.e.c', 'boop', { 'create': true } );\n > obj3\n { 'a': { 'b': { 'c': 'd' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep set function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck\n","deepSet.factory":"\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep set function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck","defineMemoizedProperty":"\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n See Also\n --------\n setMemoizedReadOnly, defineProperty\n","defineProperties":"\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default: undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n See Also\n --------\n defineProperty, setReadOnly\n","defineProperty":"\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n defineProperties, setReadOnly\n","dirname":"\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n See Also\n --------\n extname\n","dotcase":"\ndotcase( str )\n Converts a string to dot case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Dot-cased string.\n\n Examples\n --------\n > var out = dotcase( 'Hello World!' )\n 'hello.world'\n > out = dotcase( 'beep boop' )\n 'beep.boop'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n\n Returns\n -------\n list: Object\n Doubly linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the first list node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node. For its third argument, the\n method accepts a location: 'before' or 'after'. Default: 'after'.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation. For its sole argument, the method accepts a\n direction: 'forward' or 'reverse'. Default: 'forward'.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = DoublyLinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n LinkedList, Stack\n","doUntil":"\ndoUntil( fcn, predicate[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doUntil( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntilAsync, doUntilEach, doWhile, until, whilst\n","doUntilAsync":"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from one).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is falsy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doUntilAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, untilAsync, whileAsync\n","doUntilEach":"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doUntilEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, untilEach\n","doUntilEachRight":"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doUntilEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, untilEachRight\n","doWhile":"\ndoWhile( fcn, predicate[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doWhile( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, doWhileEach, until, whilst\n","doWhileAsync":"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from one).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is truthy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doWhileAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhile, untilAsync, whileAsync\n","doWhileEach":"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doWhileEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, whileEach\n","doWhileEachRight":"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doWhileEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, whileEachRight\n","dswap":"\ndswap( x, y[, dim] )\n Interchanges two double-precision floating-point vectors.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function interchanges each pair of vectors in `x`\n and `y` according to the specified dimension index.\n\n Both input arrays must have the same shape.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float64' data type. Must have at least\n one dimension and must have the same shape as the second input array.\n\n y: ndarray\n Second input array. Must have a 'float64' data type. Must have at least\n one dimension and must have the same shape as the first input array.\n\n dim: integer (optional)\n Dimension index along which to interchange vectors. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > dswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dswap, gswap, sswap\n","E":"\nE\n Euler's number.\n\n Examples\n --------\n > E\n 2.718281828459045\n\n","EMOJI":"\nEMOJI()\n Returns an emoji database.\n\n Returns\n -------\n out: Array\n Emoji database.\n\n Examples\n --------\n > var data = EMOJI()\n [ {...}, ... ]\n\n See Also\n --------\n EMOJI_CODE_PICTO, EMOJI_PICTO_CODE\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n Returns an object mapping emoji codes to pictographs.\n\n Returns\n -------\n out: Object\n An object mapping emoji codes to pictographs.\n\n Examples\n --------\n > var out = EMOJI_CODE_PICTO()\n\n See Also\n --------\n EMOJI, EMOJI_PICTO_CODE\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n Returns an object mapping emoji pictographs to codes.\n\n Returns\n -------\n out: Object\n An object mapping emoji pictographs to codes.\n\n Examples\n --------\n > var out = EMOJI_PICTO_CODE()\n\n See Also\n --------\n EMOJI, EMOJI_CODE_PICTO\n","emptyStream":"\nemptyStream( [options] )\n Returns an \"empty\" readable stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = emptyStream();\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream\n","emptyStream.factory":"\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );","emptyStream.objectMode":"\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream","endsWith":"\nendsWith( str, search[, len] )\n Tests if a string ends with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer (optional)\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, returning\n the same output as `str.length + len`. Default: `str.length`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string ends with the characters of another\n string.\n\n Examples\n --------\n > var bool = endsWith( 'beep', 'ep' )\n true\n > bool = endsWith( 'Beep', 'op' )\n false\n > bool = endsWith( 'Beep', 'ee', 3 )\n true\n > bool = endsWith( 'Beep', 'ee', -1 )\n true\n > bool = endsWith( 'beep', '' )\n true\n\n See Also\n --------\n startsWith\n","enumerableProperties":"\nenumerableProperties( value )\n Returns an array of an object's own enumerable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = enumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerablePropertiesIn, enumerablePropertySymbols, inheritedEnumerableProperties, objectKeys, nonEnumerableProperties, properties\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = enumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbolsIn, inheritedEnumerableProperties, keysIn, nonEnumerablePropertiesIn, propertiesIn\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value )\n Returns an array of an object's own enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedEnumerablePropertySymbols, objectKeys, nonEnumerablePropertySymbols, propertySymbols\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedEnumerablePropertySymbols, keysIn, nonEnumerablePropertySymbolsIn, propertySymbolsIn\n","ENV":"\nENV\n An object containing the user environment.\n\n Examples\n --------\n > var user = ENV.USER\n \n\n See Also\n --------\n ARGV\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n\n Examples\n --------\n > EPS\n 2.220446049250313e-16\n\n See Also\n --------\n FLOAT32_EPS\n","error2json":"\nerror2json( error )\n Returns a JSON representation of an error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n The JSON object is guaranteed to have the following properties:\n\n - type: error type.\n - message: error message.\n\n The only standardized cross-platform property is `message`. Depending on the\n platform, the following properties *may* be present:\n\n - name: error name.\n - stack: stack trace.\n - code: error code (Node.js system errors).\n - errno: error code string (Node.js system errors).\n - syscall: string representing the failed system call (Node.js system\n errors).\n\n The function also serializes all enumerable properties.\n\n The implementation supports custom error types and sets the `type` field to\n the closest built-in error type.\n\n Parameters\n ----------\n error: Error\n Error to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var err = new Error( 'beep' );\n > var json = error2json( err )\n \n\n See Also\n --------\n reviveError\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n\n Examples\n --------\n > EULERGAMMA\n 0.5772156649015329\n\n","every":"\nevery( collection )\n Tests whether all elements in a collection are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 1, 1, 1, 1, 1 ];\n > var bool = every( arr )\n true\n\n See Also\n --------\n any, everyBy, forEach, none, some\n","everyBy":"\neveryBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyBy( arr, positive )\n true\n\n See Also\n --------\n anyBy, everyByRight, forEach, noneBy, someBy\n","everyByAsync":"\neveryByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync\n","everyByAsync.factory":"\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync","everyByRight":"\neveryByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyByRight( arr, positive )\n true\n\n See Also\n --------\n anyBy, every, everyBy, forEachRight, noneByRight, someByRight\n","everyByRightAsync":"\neveryByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync","everyInBy":"\neveryInBy( object, predicate[, thisArg ] )\n Test whether all properties (own and inherited) of an object pass a\n test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - object: the input object.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var o = {a: 1, b: 2, c: 3};\n > var bool = everyInBy( o, positive )\n true\n\n See Also\n --------\n anyInBy, noneInBy, someInBy, everyOwnBy\n","everyOwnBy":"\neveryOwnBy( object, predicate[, thisArg ] )\n Tests whether every own property of an object pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > var bool = everyOwnBy( obj, positive )\n true\n\n See Also\n --------\n anyOwnBy, everyInBy, noneOwnBy, someOwnBy, everyBy\n","evil":"\nevil( str )\n Alias for `eval` global.\n\n A reference to `eval` is treated differently by the compiler. For example,\n when evaluating code containing block-scoped declarations (e.g., `let`,\n `const`, `function`, `class`), the compiler may throw an `error` complaining\n that block-scoped declarations are not yet supported outside of\n `strict mode`. One possible workaround is to include `\"use strict\";` in the\n evaluated code.\n\n Parameters\n ----------\n str: string\n Code to evaluate.\n\n Returns\n -------\n out: any\n Returned value if applicable.\n\n Examples\n --------\n > var v = evil( '5*4*3*2*1' )\n 120\n\n","EXEC_PATH":"\nEXEC_PATH\n Absolute pathname of the executable which started the current Node.js\n process.\n\n Examples\n --------\n > EXEC_PATH\n \n\n","exists":"\nexists( path, clbk )\n Asynchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n clbk: Function\n Callback to invoke after testing for path existence. A callback may\n accept a single argument, a boolean indicating whether a path exists, or\n two arguments, an error argument and a boolean, matching the error-first\n callback convention used in most asynchronous Node.js APIs.\n\n Examples\n --------\n > function done( error, bool ) { console.log( bool ); };\n > exists( './beep/boop', done );\n\n\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir\n","exists.sync":"\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir","expandAcronyms":"\nexpandAcronyms( str )\n Expands acronyms in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded acronyms.\n\n Examples\n --------\n > var str = 'LOL, this is fun. I am ROFL.';\n > var out = expandAcronyms( str )\n 'laughing out loud, this is fun. I am rolling on the floor laughing.'\n\n > str = 'brb, I need to check my mail. thx!';\n > out = expandAcronyms( str )\n 'be right back, I need to check my mail. thanks!'\n\n See Also\n --------\n expandContractions\n","expandContractions":"\nexpandContractions( str )\n Expands all contractions to their formal equivalents.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded contractions.\n\n Examples\n --------\n > var str = 'I won\\'t be able to get y\\'all out of this one.';\n > var out = expandContractions( str )\n 'I will not be able to get you all out of this one.'\n\n > str = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\n > out = expandContractions( str )\n 'It ought not to be my fault, because, you know, I did not know'\n\n","extname":"\nextname( filename )\n Returns a filename extension.\n\n Parameters\n ----------\n filename: string\n Filename.\n\n Returns\n -------\n ext: string\n Filename extension.\n\n Examples\n --------\n > var ext = extname( 'index.js' )\n '.js'\n\n See Also\n --------\n dirname\n","FancyArray":"\nFancyArray( dtype, buffer, shape, strides, offset, order[, options] )\n Returns a FancyArray instance.\n\n A FancyArray is an ndarray which supports slicing via indexing expressions.\n\n A FancyArray is an ndarray instance and supports all ndarray options,\n attributes, and methods. A FancyArray can be consumed by any API which\n supports ndarray instances.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on ndarray views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use and\n scripting. For performance critical applications, prefer equivalent\n functional APIs supporting ndarray instances.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n ndarray: FancyArray\n FancyArray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nFancyArray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nFancyArray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nFancyArray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nFancyArray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nFancyArray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nFancyArray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nFancyArray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nFancyArray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","FancyArray.prototype.data":"\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","FancyArray.prototype.length":"\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","FancyArray.prototype.order":"\nFancyArray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray","fastmath.abs":"\nfastmath.abs( x )\n Computes an absolute value.\n\n This implementation is not IEEE 754 compliant. If provided `-0`, the\n function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Absolute value.\n\n Examples\n --------\n > var v = fastmath.abs( -1.0 )\n 1.0\n > v = fastmath.abs( 2.0 )\n 2.0\n > v = fastmath.abs( 0.0 )\n 0.0\n > v = fastmath.abs( -0.0 )\n -0.0\n > v = fastmath.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs\n","fastmath.acosh":"\nfastmath.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n will return `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var v = fastmath.acosh( 1.0 )\n 0.0\n > v = fastmath.acosh( 2.0 )\n ~1.317\n > v = fastmath.acosh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.acosh( 1.0e308 )\n Infinity\n\n See Also\n --------\n base.acosh\n","fastmath.ampbm":"\nfastmath.ampbm( x, y )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n The algorithm computes only an approximation.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.ampbm( 5.0, 12.0 )\n ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot","fastmath.asinh":"\nfastmath.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var v = fastmath.asinh( 0.0 )\n 0.0\n > v = fastmath.asinh( 2.0 )\n ~1.444\n > v = fastmath.asinh( -2.0 )\n ~-1.444\n > v = fastmath.asinh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.asinh( 1.0e200 )\n Infinity\n\n // The function underflows for small `x`:\n > v = fastmath.asinh( 1.0e-50 )\n 0.0\n\n See Also\n --------\n base.asinh\n","fastmath.atanh":"\nfastmath.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var v = fastmath.atanh( 0.0 )\n 0.0\n > v = fastmath.atanh( 0.9 )\n ~1.472\n > v = fastmath.atanh( 1.0 )\n Infinity\n > v = fastmath.atanh( -1.0 )\n -Infinity\n > v = fastmath.atanh( NaN )\n NaN\n\n // The function underflows for small `x`:\n > v = fastmath.atanh( 1.0e-17 )\n 0.0\n\n See Also\n --------\n base.atanh\n","fastmath.hypot":"\nfastmath.hypot( x, y )\n Computes the hypotenuse.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.hypot( -5.0, 12.0 )\n 13.0\n\n // For a sufficiently large `x` and/or `y`, the function overflows:\n > h = fastmath.hypot( 1.0e154, 1.0e154 )\n Infinity\n\n // For sufficiently small `x` and/or `y`, the function underflows:\n > h = fastmath.hypot( 1e-200, 1.0e-200 )\n 0.0\n\n See Also\n --------\n base.hypot\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n\n This function provides a performance boost when requiring only approximate\n computations for integer arguments.\n\n For high-precision applications, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer binary logarithm (base two).\n\n Examples\n --------\n > var v = fastmath.log2Uint32( 4 >>> 0 )\n 2\n > v = fastmath.log2Uint32( 8 >>> 0 )\n 3\n > v = fastmath.log2Uint32( 9 >>> 0 )\n 3\n\n See Also\n --------\n base.log2\n","fastmath.max":"\nfastmath.max( x, y )\n Returns the maximum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = fastmath.max( 3.14, 4.2 )\n 4.2\n > v = fastmath.max( 3.14, NaN )\n NaN\n > v = fastmath.max( NaN, 3.14 )\n 3.14\n > v = fastmath.max( -0.0, +0.0 )\n +0.0\n > v = fastmath.max( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max\n","fastmath.min":"\nfastmath.min( x, y )\n Returns the minimum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = fastmath.min( 3.14, 4.2 )\n 3.14\n > v = fastmath.min( 3.14, NaN )\n NaN\n > v = fastmath.min( NaN, 3.14 )\n 3.14\n > v = fastmath.min( -0.0, +0.0 )\n +0.0\n > v = fastmath.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.min\n","fastmath.powint":"\nfastmath.powint( x, y )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n\n This function is not recommended for high-precision applications due to\n error accumulation.\n\n If provided a negative exponent, the function first computes the reciprocal\n of the base and then evaluates the exponential function. This can introduce\n significant error.\n\n Parameters\n ----------\n x: number\n Base.\n\n y: integer\n Signed 32-bit integer exponent.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = fastmath.powint( 2.0, 3 )\n 8.0\n > v = fastmath.powint( 3.14, 0 )\n 1.0\n > v = fastmath.powint( 2.0, -2 )\n 0.25\n > v = fastmath.powint( 0.0, 0 )\n 1.0\n > v = fastmath.powint( -3.14, 1 )\n -3.14\n > v = fastmath.powint( NaN, 0 )\n NaN\n\n See Also\n --------\n base.pow\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n Prefer hardware `sqrt` over a software implementation.\n\n When using a software `sqrt`, this function provides a performance boost\n when an application requires only approximate computations for integer\n arguments.\n\n For applications requiring high-precision, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer square root.\n\n Examples\n --------\n > var v = fastmath.sqrtUint32( 9 >>> 0 )\n 3\n > v = fastmath.sqrtUint32( 2 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 3 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 0 >>> 0 )\n 0\n\n See Also\n --------\n base.sqrt\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common female first names.\n\n Examples\n --------\n > var list = FEMALE_FIRST_NAMES_EN()\n [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. \"Moby Word II.\" .\n\n See Also\n --------\n MALE_FIRST_NAMES_EN\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n\n Returns\n -------\n queue: Object\n First-in-first-out queue.\n\n queue.clear: Function\n Clears the queue.\n\n queue.first: Function\n Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.iterator: Function\n Returns an iterator for iterating over a queue. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from queue mutation during\n iteration, a returned iterator **always** iterates over a queue\n \"snapshot\", which is defined as the list of queue elements at the time\n of the method's invocation.\n\n queue.last: Function\n Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.length: integer\n Queue length.\n\n queue.pop: Function\n Removes and returns the current \"first-out\" value from the queue. If the\n queue is empty, the returned value is `undefined`.\n\n queue.push: Function\n Adds a value to the queue.\n\n queue.toArray: Function\n Returns an array of queue values.\n\n queue.toJSON: Function\n Serializes a queue as JSON.\n\n Examples\n --------\n > var q = FIFO();\n > q.push( 'foo' ).push( 'bar' );\n > q.length\n 2\n > q.pop()\n 'foo'\n > q.length\n 1\n > q.pop()\n 'bar'\n > q.length\n 0\n\n See Also\n --------\n Stack\n","filledarray":"\nfilledarray( [dtype] )\n Creates a filled array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarray()\n \n > arr = filledarray( 'float32' )\n \n\n\nfilledarray( value, length[, dtype] )\n Returns a filled array having a specified length.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarray( 1.0, 5 )\n [ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n > arr = filledarray( 1, 5, 'int32' )\n [ 1, 1, 1, 1, 1 ]\n\n\nfilledarray( value, array[, dtype] )\n Creates a filled array from another array (or array-like object).\n\n Parameters\n ----------\n value: any\n Fill value.\n\n array: ArrayLikeObject\n Array from which to generate another array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\n [ 2.0, 2.0, 2.0 ]\n > var arr2 = filledarray( 1.0, arr1, 'float32' )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, iterable[, dtype] )\n Creates a filled array from an iterable.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n iterable: Iterable\n Iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = iterConstant( 3.0, {'iter': 3} );\n > var arr2 = filledarray( 1.0, arr1, 'float32' )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, buffer[, byteOffset[, length]][, dtype] )\n Returns a filled typed array view of an ArrayBuffer.\n\n The 'generic' array data type is *not* supported.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n [ 1.0, 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n filledarrayBy, typedarray\n","filledarrayBy":"\nfilledarrayBy( [dtype] )\n Creates a filled array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarrayBy()\n \n > arr = filledarrayBy( 'float32' )\n \n\n\nfilledarrayBy( length[, dtype], clbk[, thisArg] )\n Returns a filled array according to a provided callback function and having\n a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var arr = filledarrayBy( 5, clbk )\n [ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n > arr = filledarrayBy( 5, 'int32', clbk )\n [ 1, 1, 1, 1, 1 ]\n\n\nfilledarrayBy( array[, dtype], clbk[, thisArg] )\n Creates a filled array from another array (or array-like object) according\n to a provided callback function.\n\n Parameters\n ----------\n array: ArrayLikeObject\n Array from which to generate another array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\n [ 2.0, 2.0, 2.0 ]\n > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( iterable[, dtype], clbk[, thisArg] )\n Creates a filled array from an iterable according to a provided callback\n function.\n\n Parameters\n ----------\n iterable: Iterable\n Iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = iterConstant( 3.0, {'iter': 3} );\n > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( buffer[, byteOffset[, length]][, dtype], clbk[, thisArg] )\n Returns a filled typed array view of an ArrayBuffer according to a provided\n callback function.\n\n The 'generic' array data type is *not* supported.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n filledarray, typedarray\n","filterArguments":"\nfilterArguments( fcn, predicate[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n\n Only those arguments in which the predicate function returns a truthy value\n are applied to a provided function.\n\n The predicate function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > function predicate( v ) { return ( v !== 2 ); };\n > var bar = filterArguments( foo, predicate );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n maskArguments, rejectArguments, reorderArguments, reverseArguments\n","find":"\nfind( arr, [options,] clbk )\n Finds elements in an array-like object that satisfy a test condition.\n\n Parameters\n ----------\n arr: Array|TypedArray|string\n Object from which elements will be tested.\n\n options: Object (optional)\n Options.\n\n options.k: integer (optional)\n Limits the number of returned elements. The sign determines the\n direction in which to search. If set to a negative integer, the function\n searches from last element to first element. Default: arr.length.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'indices'.\n\n clbk: Function\n Function invoked for each array element. If the return value is truthy,\n the value is considered to have satisfied the test condition.\n\n Returns\n -------\n out: Array\n Array of indices, element values, or arrays of index-value pairs.\n\n Examples\n --------\n > var data = [ 30, 20, 50, 60, 10 ];\n > function condition( val ) { return val > 20; };\n > var vals = find( data, condition )\n [ 0, 2, 3 ]\n\n // Limit number of results:\n > data = [ 30, 20, 50, 60, 10 ];\n > var opts = { 'k': 2, 'returns': 'values' };\n > vals = find( data, opts, condition )\n [ 30, 50 ]\n\n // Return both indices and values as index-value pairs:\n > data = [ 30, 20, 50, 60, 10 ];\n > opts = { 'k': -2, 'returns': '*' };\n > vals = find( data, opts, condition )\n [ [ 3, 60 ], [ 2, 50 ] ]\n\n","firstChar":"\nfirstChar( str[, n][, options] )\n Returns the first character(s) of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to return. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = firstChar( 'beep' )\n 'b'\n > out = firstChar( 'Boop', 1 )\n 'B'\n > out = firstChar( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n removeFirst, last\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n Returns FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n\n Returns\n -------\n out: Array\n FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n\n Examples\n --------\n > var data = FIVETHIRTYEIGHT_FFQ()\n [ {...}, ... ]\n\n References\n ----------\n - Aschwanden, Christie. 2016. \"You Can't Trust What You Read About\n Nutrition.\" .\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n","flattenArray":"\nflattenArray( arr[, options] )\n Flattens an array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > var out = flattenArray( arr )\n [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Set the maximum depth:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2 } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n true\n\n // Deep copy:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n false\n\n\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: ArrayLike\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject\n","flattenArray.factory":"\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: ArrayLike\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject","flattenObject":"\nflattenObject( obj[, options] )\n Flattens an object.\n\n Parameters\n ----------\n obj: ObjectLike\n Object to flatten.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n out: ObjectLike\n Flattened object.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flattenObject( obj )\n { 'a.b.c': 'd' }\n\n // Set the `depth` option to flatten to a specified depth:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'depth': 1 } )\n { 'a.b': { 'c': 'd' } }\n > var bool = ( obj.a.b === out[ 'a.b' ] )\n true\n\n // Set the `delimiter` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'delimiter': '-|-' } )\n { 'a-|-b-|-c': 'd' }\n\n // Flatten arrays:\n > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n > out = flattenObject( obj, { 'flattenArrays': true } )\n { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray\n","flattenObject.factory":"\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray","flignerTest":"\nflignerTest( ...x[, options] )\n Computes the Fligner-Killeen test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = flignerTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = flignerTest( arr, { 'groups': groups } )\n\n See Also\n --------\n bartlettTest\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n Platform float word order.\n\n Possible values:\n\n - 'little-endian'\n - 'big-endian'\n - 'unknown'\n\n Examples\n --------\n > FLOAT_WORD_ORDER\n \n\n See Also\n --------\n BYTE_ORDER\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_CBRT_EPS\n 0.09921256574801247\n\n See Also\n --------\n FLOAT16_EPS, FLOAT16_SQRT_EPS, FLOAT32_CBRT_EPS, CBRT_EPS\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_EPS\n 0.0009765625\n\n See Also\n --------\n FLOAT32_EPS, EPS\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT16_EXPONENT_BIAS\n 15\n\n See Also\n --------\n FLOAT32_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_MAX\n 65504.0\n\n See Also\n --------\n FLOAT32_MAX, FLOAT64_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n\n The maximum safe half-precision floating-point integer is given by\n `2^11 - 1`.\n\n Examples\n --------\n > FLOAT16_MAX_SAFE_INTEGER\n 2047\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n\n The minimum safe half-precision floating-point integer is given by\n `-(2^11 - 1)`.\n\n Examples\n --------\n > FLOAT16_MIN_SAFE_INTEGER\n -2047\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT16_NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_PINF, FLOAT32_NINF, NINF\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_NUM_BYTES\n 2\n\n See Also\n --------\n FLOAT32_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT16_PINF\n Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_PINF, PINF\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n\n The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT16_PRECISION\n 11\n\n See Also\n --------\n FLOAT32_PRECISION, FLOAT64_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_NORMAL\n 6.103515625e-5\n\n See Also\n --------\n FLOAT16_SMALLEST_SUBNORMAL, FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_SUBNORMAL\n 5.960464477539063e-8\n\n See Also\n --------\n FLOAT16_SMALLEST_NORMAL, FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_SQRT_EPS\n 0.03125\n\n See Also\n --------\n FLOAT16_EPS, FLOAT32_SQRT_EPS, SQRT_EPS\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n Mask for excluding the sign bit of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_ABS_MASK\n 2147483647\n > base.toBinaryStringUint32( FLOAT32_ABS_MASK )\n '01111111111111111111111111111111'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_CBRT_EPS\n 0.004921566694974899\n\n See Also\n --------\n FLOAT32_EPS, FLOAT32_SQRT_EPS, CBRT_EPS\n","FLOAT32_E":"\nFLOAT32_E\n Euler's number.\n\n Examples\n --------\n > FLOAT32_E\n 2.7182817459106445\n\n See Also\n --------\n E\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EPS\n 1.1920928955078125e-7\n\n See Also\n --------\n EPS\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT32_EXPONENT_BIAS\n 127\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n Mask for the exponent of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EXPONENT_MASK\n 2139095040\n > base.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n '01111111100000000000000000000000'\n\n See Also\n --------\n FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_FOURTH_PI\n 7.853981852531433e-1\n\n See Also\n --------\n FLOAT32_HALF_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n One half times the natural logarithm of 2 as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_HALF_LN_TWO\n 0.3465735912322998\n\n See Also\n --------\n HALF_LN2\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_HALF_PI\n 1.5707963705062866\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n Natural logarithm of `1/2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_HALF\n -0.6931471824645996\n\n See Also\n --------\n LN_HALF\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n Natural logarithm of the mathematical constant `π` as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_PI\n 1.1447298526763916\n\n See Also\n --------\n FLOAT32_PI, LN_PI\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n Natural logarithm of `10` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_TEN\n 2.3025851249694824\n\n See Also\n --------\n FLOAT32_LN_TWO, LN10\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n Natural logarithm of `2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_TWO\n 0.6931471824645996\n\n See Also\n --------\n FLOAT32_LN_TEN, LN2\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX\n 3.4028234663852886e+38\n\n See Also\n --------\n FLOAT16_MAX, FLOAT64_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a single-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE2_EXPONENT\n 127\n\n See Also\n --------\n FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n -127\n\n See Also\n --------\n FLOAT32_MAX_BASE2_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE10_EXPONENT\n 38\n\n See Also\n --------\n FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal single-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n -38\n\n See Also\n --------\n FLOAT32_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in single-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_FIBONACCI\n 14930352\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n\n The maximum safe single-precision floating-point integer is given by\n `2^24 - 1`.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_INTEGER\n 16777215\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n Maximum safe nth factorial when stored in single-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_FACTORIAL\n 10\n\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in single-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_FIBONACCI\n 36\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in single-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_LUCAS\n 34\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE2_EXPONENT\n -126\n\n See Also\n --------\n FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n -149\n\n See Also\n --------\n FLOAT32_MIN_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normal single-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE10_EXPONENT\n -37\n\n See Also\n --------\n FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal single-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n -45\n\n See Also\n --------\n FLOAT32_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n\n The minimum safe single-precision floating-point integer is given by\n `-(2^24 - 1)`.\n\n Examples\n --------\n > FLOAT32_MIN_SAFE_INTEGER\n -16777215\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"\nFLOAT32_NAN\n Single-precision floating-point NaN.\n\n Examples\n --------\n > FLOAT32_NAN\n NaN\n\n See Also\n --------\n NAN\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT32_NINF\n -Infinity\n\n See Also\n --------\n FLOAT32_PINF, NINF\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_NUM_BYTES\n 4\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT32_PHI":"\nFLOAT32_PHI\n Golden ratio.\n\n Examples\n --------\n > FLOAT32_PHI\n 1.6180340051651\n\n See Also\n --------\n PHI\n","FLOAT32_PI":"\nFLOAT32_PI\n The mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_PI\n 3.1415927410125732\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_TWO_PI\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT32_PINF\n Infinity\n\n See Also\n --------\n FLOAT32_NINF, PINF\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n\n The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT32_PRECISION\n 24\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT64_PRECISION\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n Mask for the sign bit of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SIGN_MASK\n 2147483648\n > base.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n '10000000000000000000000000000000'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n Mask for the significand of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SIGNIFICAND_MASK\n 8388607\n > base.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n '00000000011111111111111111111111'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_NORMAL\n 1.1754943508222875e-38\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_SUBNORMAL\n 1.401298464324817e-45\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_SQRT_EPS\n 0.0003452669770922512\n\n See Also\n --------\n FLOAT32_EPS, SQRT_EPS\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n Square root of `1/2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_HALF\n 0.7071067690849304\n\n See Also\n --------\n SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n Square root of `π` divided by `2` as a single-precision \n floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_HALF_PI\n 1.2533141374588013\n\n See Also\n --------\n SQRT_HALF_PI","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n Square root of the golden ratio as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_PHI\n 1.272019624710083\n\n See Also\n --------\n SQRT_PHI\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n Square root of the mathematical constant `π` as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_PI\n 1.7724539041519165\n\n See Also\n --------\n FLOAT32_PI, SQRT_PI\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n Square root of `3` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_THREE\n 1.7320507764816284\n\n See Also\n --------\n FLOAT32_SQRT_TWO, SQRT_THREE\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n Square root of `2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_TWO\n 1.4142135381698608\n\n See Also\n --------\n FLOAT32_SQRT_THREE, SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n Square root of the mathematical constant `π` times `2` as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_TWO_PI\n 2.5066282749176025\n\n See Also\n --------\n FLOAT32_PI, FLOAT32_TWO_PI, SQRT_TWO_PI\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > FLOAT32_TWO_PI\n 6.2831854820251465\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_PI\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array()\n \n\n\nFloat32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Float32Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'\n\n\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n \n\n\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20\n\n\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float32Array.from":"\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]","Float32Array.of":"\nFloat32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4","Float32Array.name":"\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n ","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT64_EXPONENT_BIAS\n 1023\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT32_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n High word mask for excluding the sign bit of a double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_ABS_MASK\n 2147483647\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n '01111111111111111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_EXPONENT_MASK\n 2146435072\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n '01111111111100000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n High word mask for the sign bit of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGN_MASK\n 2147483648\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n '10000000000000000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n 1048575\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n '00000000000011111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX\n 1.7976931348623157e+308\n\n See Also\n --------\n FLOAT16_MAX, FLOAT32_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT\n 1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n -1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT\n 308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_LN\n 709.782712893384\n\n See Also\n --------\n FLOAT64_MIN_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_FIBONACCI\n 8944394323791464\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n\n The maximum safe double-precision floating-point integer is given by\n `2^53 - 1`.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_INTEGER\n 9007199254740991\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_LUCAS\n 7639424778862807\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI, FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n 78\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_LUCAS\n 76\n\n See Also\n --------\n FLOAT64_MAX_SAFE_LUCAS, FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT\n -1022\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n -1074\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n -324\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MIN_LN\n -708.3964185322641\n\n See Also\n --------\n FLOAT64_MAX_LN\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n\n The minimum safe double-precision floating-point integer is given by\n `-(2^53 - 1)`.\n\n Examples\n --------\n > FLOAT64_MIN_SAFE_INTEGER\n -9007199254740991\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_NUM_BYTES\n 8\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT32_NUM_BYTES\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n\n The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT64_PRECISION\n 53\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT32_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_NORMAL\n 2.2250738585072014e-308\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_SUBNORMAL\n 4.940656458412465e-324\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array()\n \n\n\nFloat64Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = new Float64Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'\n\n\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n \n\n\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40\n\n\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float64Array.from":"\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]","Float64Array.of":"\nFloat64Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8","Float64Array.name":"\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n ","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","forEach":"\nforEach( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEach( arr, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachAsync":"\nforEachAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachAsync.factory":"\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync","forEachChar":"\nforEachChar( str, [options,] clbk[, thisArg] )\n Invokes a function for each character in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: starting character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters over which to iterate. The following modes are\n supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n clbk: Function\n The function to invoke for each character in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > forEachChar( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n forEach\n","forEachRight":"\nforEachRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEachRight( arr, logger )\n 3: 4\n 2: 3\n 1: 2\n 0: 1\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachRightAsync":"\nforEachRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight","forIn":"\nforIn( obj, fcn[, thisArg] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n\n When invoked, the function is provided three arguments:\n\n - value: object property value.\n - key: object property.\n - obj: the input object.\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > function Foo() { return this; };\n > Foo.prototype.beep = 'boop';\n > var obj = new Foo();\n > forIn( obj, logger )\n beep: boop\n\n See Also\n --------\n forEach, forOwn\n","format":"\nformat( str, ...args )\n Insert supplied variable values into a format string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n args: ...any\n Variable values.\n\n Returns\n -------\n out: string\n Formatted string.\n\n Examples\n --------\n > var out = format( 'Hello, %s!', 'World' )\n 'Hello, World!'\n\n > out = format( '%s %s', 'Hello', 'World' )\n 'Hello World'\n\n > out = format( 'Pi: %.2f', PI )\n 'Pi: 3.14'\n\n","forOwn":"\nforOwn( obj, fcn[, thisArg] )\n Invokes a function for each own enumerable property of an object.\n\n When invoked, the function is provided three arguments:\n\n - value: object property value.\n - key: object property.\n - obj: the input object.\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n The function determines the list of own enumerable properties *before*\n invoking the provided function. Hence, any modifications made to the input\n object *after* calling this function (such as adding and removing\n properties) will *not* affect the list of visited properties.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > forOwn( obj, logger )\n a: 1\n b: 2\n c: 3\n d: 4\n\n See Also\n --------\n forEach, forIn\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FOURTH_PI\n 7.85398163397448309616e-1\n\n See Also\n --------\n PI\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n\n Examples\n --------\n > FOURTH_ROOT_EPS\n 0.0001220703125\n\n See Also\n --------\n EPS\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n\n Each array element has the following fields:\n\n - date: collection date (month/day/year; e.g., 01/01/1980).\n - all_workers: wage rates for hourly and non-hourly workers.\n - hourly_workers: wage rates for hourly workers.\n - non_hourly_workers: wage rates for non-hourly workers.\n - less_than_high_school: wage rates for workers with less than a high school\n education.\n - high_school: wage rates for workers with a high school education.\n - some_college: wage rates for workers with some college education.\n - college: wage rates for workers with a college education.\n - construction: wage rates for workers in the construction industry.\n - finance: wage rates for workers in the finance industry.\n - manufacturing: wage rates for workers in the manufacturing industry.\n\n Returns\n -------\n out: Array\n Wage rates.\n\n Examples\n --------\n > var data = FRB_SF_WAGE_RIGIDITY()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" .\n\n","fromCodePoint":"\nfromCodePoint( ...pt )\n Creates a string from a sequence of Unicode code points.\n\n In addition to multiple arguments, the function also supports providing an\n array-like object as a single argument containing a sequence of Unicode code\n points.\n\n Parameters\n ----------\n pt: ...integer\n Sequence of Unicode code points.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = fromCodePoint( 9731 )\n '☃'\n > out = fromCodePoint( [ 9731 ] )\n '☃'\n > out = fromCodePoint( 97, 98, 99 )\n 'abc'\n > out = fromCodePoint( [ 97, 98, 99 ] )\n 'abc'\n\n See Also\n --------\n codePointAt\n","Function":"\nFunction( [...argNames,] body )\n Returns a Function object.\n\n Argument names must be strings corresponding to valid JavaScript parameters\n (i.e., a plain identifier, or, in environments supporting such parameters, a\n rest parameter or destructured parameter, optionally with a default).\n\n Parameters\n ----------\n argNames: ...any (optional)\n Parameter names.\n\n body: string\n Function body.\n\n Returns\n -------\n fcn: Function\n Function object.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f( 1, 2 )\n 3\n\n\nFunction.prototype.apply( thisArg, args )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: Array\n Array of arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.apply( null, [ 1, 2 ] )\n 3\n\nFunction.prototype.call( thisArg, ...args )\n Calls a function with a given `this` value and arguments provided\n individually.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.call( null, 1, 2 )\n 3\n\nFunction.prototype.bind( thisArg, ...args )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n fcn: Function\n Bound function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > var g = f.bind( null, 1 );\n > g( 2 )\n 3\n\nFunction.prototype.toString()\n Returns a string representation of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.toString()\n 'function anonymous( x, y ) { return x + y; }'\n\nFunction.prototype.length\n The number of arguments expected by the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.length\n 2\n\nFunction.prototype.name\n The name of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name\n 'anonymous'\n\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name = 'add';\n > f.name\n 'add'\n\nFunction.prototype.prototype\n The prototype of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.prototype\n {}\n\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg, args )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: Array\n Array of arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.apply( null, [ 1, 2 ] )\n 3","Function.prototype.call":"\nFunction.prototype.call( thisArg, ...args )\n Calls a function with a given `this` value and arguments provided\n individually.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.call( null, 1, 2 )\n 3","Function.prototype.bind":"\nFunction.prototype.bind( thisArg, ...args )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n fcn: Function\n Bound function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > var g = f.bind( null, 1 );\n > g( 2 )\n 3","Function.prototype.toString":"\nFunction.prototype.toString()\n Returns a string representation of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.toString()\n 'function anonymous( x, y ) { return x + y; }'","Function.prototype.length":"\nFunction.prototype.length\n The number of arguments expected by the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.length\n 2","Function.prototype.name":"\nFunction.prototype.name\n The name of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name\n 'anonymous'\n\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name = 'add';\n > f.name\n 'add'","Function.prototype.prototype":"\nFunction.prototype.prototype\n The prototype of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.prototype\n {}","function2string":"\nfunction2string( fcn )\n Returns a string representing the source code of a provided function.\n\n If called on built-in functions, functions created by `Function#bind()`, or\n other non-JavaScript functions, the function returns a \"native\" function\n string similar to the following:\n\n \"function foo() { [native code] }\"\n\n For intrinsic object methods and functions, `foo` is the initial name of the\n function.\n\n If called on a function created by the `Function` constructor, the function\n returns the source code of a synthesized function declaration having the\n name \"anonymous\" and using the provided parameters and function body.\n\n Starting in ES2018, the ECMAScript specification requires that the returned\n string contain the exact same source code as it was declared, including any\n whitespace and/or comments. If the host is unable to access the source code,\n the specification requires that the returned string be the native function\n string.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n String representing the function's source code.\n\n Examples\n --------\n > function2string( base.erf )\n \n\n See Also\n --------\n Function\n","functionName":"\nfunctionName( fcn )\n Returns the name of a function.\n\n If provided an anonymous function, the function returns an empty `string` or\n the string `\"anonymous\"`.\n\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n Function name.\n\n Examples\n --------\n > var v = functionName( String )\n 'String'\n > v = functionName( function foo(){} )\n 'foo'\n > v = functionName( function(){} )\n '' || 'anonymous'\n\n See Also\n --------\n constructorName\n","functionSequence":"\nfunctionSequence( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as an argument to the next function. The result of the\n rightmost function is the result of the whole.\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x ) { return 2 * x; };\n > function b( x ) { return x + 3; };\n > function c( x ) { return x / 5; };\n > var f = functionSequence( a, b, c );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n compose, functionSequenceAsync\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as the first argument of the next function. The result of\n the rightmost function is the result of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - error: error argument.\n - result: function result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the pipeline function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = functionSequenceAsync( a, b, c );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n composeAsync, functionSequence\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n Examples\n --------\n > GAMMA_LANCZOS_G\n 10.900511\n\n","gdot":"\ngdot( x, y )\n Computes the dot product of two vectors.\n\n In general, for best performance, especially for large vectors, provide\n 1-dimensional ndarrays whose underlying data type is either 'float64' or\n 'float32'.\n\n If provided empty vectors, the function returns `0.0`.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n First input array.\n\n y: ndarray|ArrayLikeObject\n Second input array.\n\n Returns\n -------\n dot: number\n The dot product.\n\n Examples\n --------\n // Using ndarrays...\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > gdot( x, y )\n -5.0\n\n // Using array-like objects...\n > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > gdot( x, y )\n -5.0\n\n See Also\n --------\n base.strided.gdot, ddot, sdot\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n\n The function only returns an effective group identity on POSIX platforms.\n For all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric group identity.\n\n Examples\n --------\n > var gid = getegid()\n\n See Also\n --------\n geteuid, getgid, getuid\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n\n The function only returns an effective user identity on POSIX platforms. For\n all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric user identity.\n\n Examples\n --------\n > var uid = geteuid()\n\n See Also\n --------\n getegid, getgid, getuid\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n\n The function only returns a group identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric group identity.\n\n Examples\n --------\n > var gid = getgid()\n\n See Also\n --------\n getegid, geteuid, getuid\n","getGlobal":"\ngetGlobal( [codegen] )\n Returns the global object.\n\n Parameters\n ----------\n codegen: boolean (optional)\n Boolean indicating whether to use code generation to resolve the global\n object. Code generation is the *most* reliable means for resolving the\n global object; however, using code generation may violate content\n security policies (CSPs). Default: false.\n\n Returns\n -------\n global: Object\n Global object.\n\n Examples\n --------\n > var g = getGlobal()\n {...}\n\n","getPrototypeOf":"\ngetPrototypeOf( value )\n Returns the prototype of a provided object.\n\n In contrast to the native `Object.getPrototypeOf`, this function does not\n throw when provided `null` or `undefined`. Instead, similar to when provided\n any value with *no* inherited properties, the function returns `null`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object|null\n Prototype.\n\n Examples\n --------\n > var proto = getPrototypeOf( {} )\n {}\n\n See Also\n --------\n isPrototypeOf\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n\n The function only returns a user identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric user identity.\n\n Examples\n --------\n > var uid = getuid()\n\n See Also\n --------\n getegid, geteuid, getgid\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n\n Examples\n --------\n > GLAISHER\n 1.2824271291006226\n\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over each grapheme cluster in a string.\n\n When invoked, an input function is provided three arguments:\n\n - value: grapheme cluster.\n - index: iterated value index.\n - src: source string.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke a string's `@@iterator` method, regardless of whether this method is\n defined. To convert a string to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: string\n String from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = graphemeClusters2iterator( '🌷🍕' );\n > var v = it.next().value\n '🌷'\n > v = it.next().value\n '🍕'\n > var bool = it.next().done\n true\n\n See Also\n --------\n array2iterator, graphemeClusters2iteratorRight\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over each grapheme\n cluster in a string.\n\n When invoked, an input function is provided three arguments:\n\n - value: grapheme cluster.\n - index: iterated value index.\n - src: source string.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke a string's `@@iterator` method, regardless of whether this method is\n defined. To convert a string to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: string\n String from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = graphemeClusters2iteratorRight( '🌷🍕' );\n > var v = it.next().value\n '🍕'\n > v = it.next().value\n '🌷'\n > var bool = it.next().done\n true\n\n See Also\n --------\n array2iteratorRight, graphemeClusters2iterator\n","group":"\ngroup( collection, [options,] groups )\n Groups values as arrays associated with distinct keys.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n groups: Array|TypedArray|Object\n A collection defining which group an element in the input collection\n belongs to. Each value in `groups` should resolve to a value which can\n be serialized as an object key. If provided an object, the object must\n be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var groups = [ 'b', 'b', 'f', 'b' ];\n > var out = group( collection, groups )\n { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n > groups = [ 1, 1, 2, 1 ];\n > out = group( collection, groups )\n { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n // Output group results as indices:\n > groups = [ 'b', 'b', 'f', 'b' ];\n > var opts = { 'returns': 'indices' };\n > out = group( collection, opts, groups )\n { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = group( collection, opts, groups )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n See Also\n --------\n bifurcate, countBy, groupBy\n","groupBy":"\ngroupBy( collection, [options,] indicator )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = groupBy( collection, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n See Also\n --------\n bifurcateBy, countBy, group\n","groupByAsync":"\ngroupByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy\n","groupByAsync.factory":"\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy","groupIn":"\ngroupIn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object with no prototype, the function returns an empty\n object.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > var out = groupIn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateIn, groupBy, groupOwn\n","groupOwn":"\ngroupOwn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object, the function returns an empty object.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = groupOwn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateOwn, group, groupBy\n","gswap":"\ngswap( x, y )\n Interchanges two vectors.\n\n In general, for best performance, especially for large vectors, provide\n 1-dimensional ndarrays whose underlying data type is either 'float64' or\n 'float32'.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n First input array.\n\n y: ndarray|ArrayLikeObject\n Second input array.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n // Using ndarrays...\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > gswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n // Using array-like objects...\n > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > gswap( x, y );\n > x\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gswap, dswap, sswap\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n\n Examples\n --------\n > HALF_LN2\n 3.46573590279972654709e-01\n\n See Also\n --------\n LN2\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > HALF_PI\n 1.5707963267948966\n\n See Also\n --------\n PI\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 14 attributes:\n\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n - lstat: percent lower status of the population.\n - medv: median value of owner-occupied homes in $1000's.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n Additionally, as documented by Gilley and Pace (1996), the dataset contains\n eight miscoded median values.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES_CORRECTED, PACE_BOSTON_HOUSE_PRICES\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 15 attributes:\n\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population.\n - medv: median value of owner-occupied homes in $1000's.\n - cmedv: corrected median value of owner-occupied homes in $1000's.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, PACE_BOSTON_HOUSE_PRICES\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `ArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasArrayBufferSupport()\n \n\n See Also\n --------\n hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasSharedArrayBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n Tests whether an environment supports native arrow functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support arrow functions.\n\n Examples\n --------\n > var bool = hasArrowFunctionSupport()\n \n\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `async`/`await` support.\n\n Examples\n --------\n > var bool = hasAsyncAwaitSupport()\n \n\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.asyncIterator`\n support.\n\n Examples\n --------\n > var bool = hasAsyncIteratorSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport, hasSymbolSupport\n","hasAtobSupport":"\nhasAtobSupport()\n Tests for native `atob` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `atob` support.\n\n Examples\n --------\n > var bool = hasAtobSupport()\n \n\n See Also\n --------\n hasBtoaSupport\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n Tests for native `BigInt64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `BigInt64Array` support.\n\n Examples\n --------\n > var bool = hasBigInt64ArraySupport()\n \n\n See Also\n --------\n hasBigIntSupport, hasBigUint64ArraySupport\n","hasBigIntSupport":"\nhasBigIntSupport()\n Tests for native `BigInt` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `BigInt` support.\n\n Examples\n --------\n > var bool = hasBigIntSupport()\n \n\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n Tests for native `BigUint64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `BigUint64Array` support.\n\n Examples\n --------\n > var bool = hasBigUint64ArraySupport()\n \n\n See Also\n --------\n hasBigIntSupport, hasBigInt64ArraySupport\n","hasBtoaSupport":"\nhasBtoaSupport()\n Tests for native `btoa` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `btoa` support.\n\n Examples\n --------\n > var bool = hasBtoaSupport()\n \n\n See Also\n --------\n hasAtobSupport\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `class` support.\n\n Examples\n --------\n > var bool = hasClassSupport()\n \n\n","hasDataViewSupport":"\nhasDataViewSupport()\n Tests for native `DataView` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `DataView` support.\n\n Examples\n --------\n > var bool = hasDataViewSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperties`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertiesSupport()\n \n\n See Also\n --------\n hasDefinePropertySupport\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperty`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertySupport()\n \n\n See Also\n --------\n hasDefinePropertiesSupport\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float32Array` support.\n\n Examples\n --------\n > var bool = hasFloat32ArraySupport()\n \n\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float64Array` support.\n\n Examples\n --------\n > var bool = hasFloat64ArraySupport()\n \n\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has function `name` support.\n\n Examples\n --------\n > var bool = hasFunctionNameSupport()\n \n\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support generator functions.\n\n Examples\n --------\n > var bool = hasGeneratorSupport()\n \n\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n Tests for `globalThis` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `globalThis` support.\n\n Examples\n --------\n > var bool = hasGlobalThisSupport()\n \n\n See Also\n --------\n getGlobal\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int8Array` support.\n\n Examples\n --------\n > var bool = hasInt8ArraySupport()\n \n\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int16Array` support.\n\n Examples\n --------\n > var bool = hasInt16ArraySupport()\n \n\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int32Array` support.\n\n Examples\n --------\n > var bool = hasInt32ArraySupport()\n \n\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.iterator`\n support.\n\n Examples\n --------\n > var bool = hasIteratorSymbolSupport()\n \n\n See Also\n --------\n hasAsyncIteratorSymbolSupport, hasSymbolSupport\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Map` support.\n\n Examples\n --------\n > var bool = hasMapSupport()\n \n\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Buffer` support.\n\n Examples\n --------\n > var bool = hasNodeBufferSupport()\n \n\n","hasOwnProp":"\nhasOwnProp( value, property )\n Tests if an object has a specified property.\n\n In contrast to the native `Object.prototype.hasOwnProperty`, this function\n does not throw when provided `null` or `undefined`. Instead, the function\n returns `false`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasOwnProp( beep, 'boop' )\n true\n > bool = hasOwnProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp\n","hasProp":"\nhasProp( value, property )\n Tests if an object has a specified property, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasProp( beep, 'boop' )\n true\n > bool = hasProp( beep, 'toString' )\n true\n > bool = hasProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Proxy` support.\n\n Examples\n --------\n > var bool = hasProxySupport()\n \n\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Set` support.\n\n Examples\n --------\n > var bool = hasSetSupport()\n \n\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasSharedArrayBufferSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport, hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol` support.\n\n Examples\n --------\n > var bool = hasSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `Symbol.toStringTag` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Symbol.toStringTag` support.\n\n Examples\n --------\n > var bool = hasToStringTagSupport()\n \n\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8Array` support.\n\n Examples\n --------\n > var bool = hasUint8ArraySupport()\n \n\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n Examples\n --------\n > var bool = hasUint8ClampedArraySupport()\n \n\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint16Array` support.\n\n Examples\n --------\n > var bool = hasUint16ArraySupport()\n \n\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint32Array` support.\n\n Examples\n --------\n > var bool = hasUint32ArraySupport()\n \n\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str, pos )\n Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n\n Parameters\n ----------\n str: string\n Input string.\n\n pos: integer\n Position.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether surrogate pair exists at specified position.\n\n Examples\n --------\n > var out = hasUTF16SurrogatePairAt( '🌷', 0 )\n true\n > out = hasUTF16SurrogatePairAt( '🌷', 1 )\n false\n\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakMap` support.\n\n Examples\n --------\n > var bool = hasWeakMapSupport()\n \n\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakSet` support.\n\n Examples\n --------\n > var bool = hasWeakSetSupport()\n \n\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native WebAssembly support.\n\n Examples\n --------\n > var bool = hasWebAssemblySupport()\n \n\n","headercase":"\nheadercase( str )\n Converts a string to HTTP header case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n HTTP header-cased string.\n\n Examples\n --------\n > var out = headercase( 'Hello World!' )\n 'Hello-World'\n > out = headercase( 'beep boop' )\n 'Beep-Boop'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n\n This dataset is a classic dataset commonly used in examples demonstrating\n outlier detection.\n\n Returns\n -------\n out: Array\n Observations.\n\n Examples\n --------\n > var d = HERNDON_VENUS_SEMIDIAMETERS()\n [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n References\n ----------\n - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n 5th ed. Vol. 5. London, England: Trübner & Co.\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n\n If unable to locate a home directory, the function returns `null`.\n\n Returns\n -------\n out: string|null\n Home directory.\n\n Examples\n --------\n > var home = homedir()\n e.g., '/Users/'\n\n See Also\n --------\n configdir, tmpdir\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var hrs = days * HOURS_IN_DAY\n 75.36\n\n See Also\n --------\n HOURS_IN_WEEK\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var hrs = wks * HOURS_IN_WEEK\n 527.52\n\n See Also\n --------\n HOURS_IN_DAY\n","hoursInMonth":"\nhoursInMonth( [month[, year]] )\n Returns the number of hours in a month.\n\n By default, the function returns the number of hours in the current month of\n the current year (according to local time). To determine the number of hours\n for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Hours in a month.\n\n Examples\n --------\n > var num = hoursInMonth()\n \n > num = hoursInMonth( 2 )\n \n > num = hoursInMonth( 2, 2016 )\n 696\n > num = hoursInMonth( 2, 2017 )\n 672\n\n // Other ways to supply month:\n > num = hoursInMonth( 'feb', 2016 )\n 696\n > num = hoursInMonth( 'february', 2016 )\n 696\n\n See Also\n --------\n hoursInYear\n","hoursInYear":"\nhoursInYear( [value] )\n Returns the number of hours in a year according to the Gregorian calendar.\n\n By default, the function returns the number of hours in the current year\n (according to local time). To determine the number of hours for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of hours in a year.\n\n Examples\n --------\n > var num = hoursInYear()\n \n > num = hoursInYear( 2016 )\n 8784\n > num = hoursInYear( 2017 )\n 8760\n\n See Also\n --------\n hoursInMonth\n","httpServerFactory":"\nhttpServerFactory( [options,] [requestListener] )\n Returns a function to create an HTTP server.\n\n In addition to options documented below, the function supports any options\n supported by `http.createServer`. Which server options are supported depends\n on the Node.js version. Older Node.js versions (e.g., <= v8.12.0) do not\n support an options object when calling `http.createServer`, and, for those\n versions, any options supported by `http.createServer` in later Node.js\n versions are ignored.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.port: integer (optional)\n Server port. Default: `0` (i.e., randomly assigned).\n\n options.maxport: integer (optional)\n Max server port when port hunting. Default: `maxport = port`.\n\n options.hostname: string (optional)\n Server hostname.\n\n options.address: string (optional)\n Server address. Default: `'127.0.0.1'`.\n\n requestListener: Function (optional)\n Request callback.\n\n Returns\n -------\n httpServer: Function\n Function to create an HTTP server.\n\n Examples\n --------\n // Basic usage:\n > var boot = httpServerFactory()\n \n\n // Provide a request callback:\n > function onRequest( request, response ) {\n ... console.log( request.url );\n ... response.end( 'OK' );\n ... };\n > boot = httpServerFactory( onRequest )\n \n\n // Specify a specific port:\n > var opts = { 'port': 7331 };\n > boot = httpServerFactory( opts )\n \n\n\nboot( done )\n Creates an HTTP server.\n\n Parameters\n ----------\n done: Function\n Callback to invoke after creating a server.\n\n Examples\n --------\n > function done( error, server ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Success!' );\n ... server.close();\n ... };\n > var boot = httpServerFactory();\n > boot( done );\n\n","identity":"\nidentity( x )\n Identity function.\n\n Parameters\n ----------\n x: any\n Input value.\n\n Returns\n -------\n out: any\n Input value.\n\n Examples\n --------\n > var v = identity( 3.14 )\n 3.14\n\n See Also\n --------\n constantFunction\n","ifelse":"\nifelse( bool, x, y )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n Returns\n -------\n z: any\n Either `x` or `y`.\n\n Examples\n --------\n > var z = ifelse( true, 1.0, -1.0 )\n 1.0\n > z = ifelse( false, 1.0, -1.0 )\n -1.0\n\n See Also\n --------\n ifelseAsync, ifthen\n","ifelseAsync":"\nifelseAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n\n A predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate completion.\n\n The callback function accepts two arguments:\n\n - error: error object.\n - bool: condition used to determine whether to invoke `x` or `y`.\n\n The `done` callback is invoked upon function completion and is provided at\n most two arguments:\n\n - error: error object.\n - result: either `x` or `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, true );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifelseAsync( predicate, 'beep', 'boop', done )\n 'beep'\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthen":"\nifthen( bool, x, y )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n Returns\n -------\n z: any\n Return value of either `x` or `y`.\n\n Examples\n --------\n > function x() { return 1.0; };\n > function y() { return -1.0; };\n > var z = ifthen( true, x, y )\n 1.0\n > z = ifthen( false, x, y )\n -1.0\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthenAsync":"\nifthenAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n\n The predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate function completion.\n\n The predicate function callback accepts two arguments:\n\n - error: error object.\n - bool: condition used to determine whether to invoke `x` or `y`.\n\n Both `x` and `y` are provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the `done` callback is invoked with only an\n error argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, false );\n ... }\n ... };\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'beep' );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifthenAsync( predicate, x, y, done )\n 'boop'\n\n See Also\n --------\n ifelseAsync, ifthen\n","imag":"\nimag( z )\n Returns the imaginary component of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var im = imag( z )\n 3.0\n\n See Also\n --------\n real, reim\n","imagf":"\nimagf( z )\n Returns the imaginary component of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var im = imagf( z )\n 3.0\n\n See Also\n --------\n imag, realf, reimf\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ACANTHUS_MOLLIS()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Acanthus mollis*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ALLIUM_OREOPHILUM\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_AIRPLANE_FROM_ABOVE()\n \n\n References\n ----------\n - Azari, Fédèle. 1929. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium oreophilum*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ALLIUM_OREOPHILUM()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Allium oreophilum*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ACANTHUS_MOLLIS\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_BLACK_CANYON()\n \n\n References\n ----------\n - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n Looking Above*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_DUST_BOWL_HOME()\n \n\n References\n ----------\n - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n \n\n References\n ----------\n - Braun, Adolphe. 1870. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_HOUSE_CAT()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_NUDE_MALE\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_NUDE_MALE()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_HOUSE_CAT\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_MARCH_PASTORAL()\n \n\n References\n ----------\n - Emerson, Peter Henry. 1888. *A March Pastoral*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_NAGASAKI_BOATS()\n \n\n References\n ----------\n - Beato, Felice. 1865. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","incrapcorr":"\nincrapcorr( [mx, my] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrapcorr();\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator()\n ~1.0\n\n See Also\n --------\n incrmapcorr, incrpcorr, incrpcorr2\n","incrBinaryClassification":"\nincrBinaryClassification( N[, options] )\n Returns an accumulator function which incrementally performs binary\n classification using stochastic gradient descent (SGD).\n\n If provided a feature vector and response value, the accumulator function\n updates a binary classification model and returns updated model\n coefficients.\n\n If not provided a feature vector and response value, the accumulator\n function returns the current model coefficients.\n\n Stochastic gradient descent is sensitive to the scaling of the features. One\n is advised to either scale each feature to `[0,1]` or `[-1,1]` or to\n transform the features into z-scores with zero mean and unit variance. One\n should keep in mind that the same scaling has to be applied to training data\n in order to obtain accurate predictions.\n\n In general, the more data provided to an accumulator, the more reliable the\n model predictions.\n\n Parameters\n ----------\n N: integer\n Number of features.\n\n options: Object (optional)\n Function options.\n\n options.intercept: boolean (optional)\n Boolean indicating whether to include an intercept. Default: true.\n\n options.lambda: number (optional)\n Regularization parameter. Default: 1.0e-4.\n\n options.learningRate: ArrayLike (optional)\n Learning rate function and associated (optional) parameters. The first\n array element specifies the learning rate function and must be one of\n the following:\n\n - ['constant', ...]: constant learning rate function. To set the\n learning rate, provide a second array element. By default, when the\n learn rate function is 'constant', the learning rate is set to 0.02.\n\n - ['basic']: basic learning rate function according to the formula\n `10/(10+t)` where `t` is the current iteration.\n\n - ['invscaling', ...]: inverse scaling learning rate function according\n to the formula `eta0/pow(t, power_t)` where `eta0` is the initial\n learning rate and `power_t` is the exponent controlling how quickly the\n learning rate decreases. To set the initial learning rate, provide a\n second array element. By default, the initial learning rate is 0.02. To\n set the exponent, provide a third array element. By default, the\n exponent is 0.5.\n\n - ['pegasos']: Pegasos learning rate function according to the formula\n `1/(lambda*t)` where `t` is the current iteration and `lambda` is the\n regularization parameter.\n\n Default: ['basic'].\n\n options.loss: string (optional)\n Loss function. Must be one of the following:\n\n - hinge: hinge loss function. Corresponds to a soft-margin linear\n Support Vector Machine (SVM), which can handle non-linearly separable\n data.\n\n - log: logistic loss function. Corresponds to Logistic Regression.\n\n - modifiedHuber: Huber loss function variant for classification.\n\n - perceptron: hinge loss function without a margin. Corresponds to the\n original Perceptron by Rosenblatt.\n\n - squaredHinge: squared hinge loss function SVM (L2-SVM).\n\n Default: 'log'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts response values for one ore more observation vectors. Provide a\n second argument to specify the prediction type. Must be one of the\n following: 'label', 'probability', or 'linear'. Default: 'label'.\n\n Note that the probability prediction type is only compatible with 'log'\n and 'modifiedHuber' loss functions.\n\n Examples\n --------\n // Create an accumulator:\n > var opts = {};\n > opts.intercept = true;\n > opts.lambda = 1.0e-5;\n > var acc = incrBinaryClassification( 3, opts );\n\n // Update the model:\n > var buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\n > var x = array( buf );\n > var coefs = acc( x, 1 )\n \n\n // Create a new observation vector:\n > buf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\n > x = array( buf );\n\n // Predict the response value:\n > var yhat = acc.predict( x )\n \n\n See Also\n --------\n incrSGDRegression\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrmean, incrsum, incrsummary\n","incrcovariance":"\nincrcovariance( [mx, my] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n\n If provided values, the accumulator function returns an updated unbiased\n sample covariance. If not provided values, the accumulator function returns\n the current unbiased sample covariance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovariance();\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator()\n ~-7.49\n\n See Also\n --------\n incrmcovariance, incrpcorr, incrvariance\n","incrcovmat":"\nincrcovmat( out[, means] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n unbiased sample covariance matrix. If not provided a data vector, the\n accumulator function returns the current unbiased sample covariance matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the covariance matrix or a square 2-dimensional ndarray for\n storing the covariance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovariance, incrpcorrmat\n","incrcv":"\nincrcv( [mean] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcv();\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator()\n ~0.47\n\n See Also\n --------\n incrmean, incrmcv, incrstdev, incrvmr\n","increwmean":"\nincrewmean( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwmean( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -1.5\n > v = accumulator()\n -1.5\n\n See Also\n --------\n increwvariance, incrmean, incrmmean, incrwmean\n","increwstdev":"\nincrewstdev( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n\n If provided a value, the accumulator function returns an updated standard\n deviation. If not provided a value, the accumulator function returns the\n current standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwstdev( 0.5 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n 3.5\n > s = accumulator()\n 3.5\n\n See Also\n --------\n increwvariance, incrmstdev, incrstdev\n","increwvariance":"\nincrewvariance( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n\n If provided a value, the accumulator function returns an updated variance.\n If not provided a value, the accumulator function returns the current\n variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwvariance( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 0.0\n > v = accumulator( -5.0 )\n 12.25\n > v = accumulator()\n 12.25\n\n See Also\n --------\n increwmean, increwstdev, incrvariance, incrmvariance\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n\n If provided a value, the accumulator function returns an updated geometric\n mean. If not provided a value, the accumulator function returns the current\n geometric mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n If provided a negative value, the accumulated value is `NaN` for all future\n invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrgmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator()\n ~3.16\n\n See Also\n --------\n incrhmean, incrmean, incrmgmean, incrsummary\n","incrgrubbs":"\nincrgrubbs( [options] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the test statistic is `NaN` for all future invocations.\n\n The accumulator must be provided *at least* three data points before\n performing Grubbs' test. Until at least three data points are provided, the\n accumulator returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n options.init: integer (optional)\n Number of data points the accumulator should use to compute initial\n statistics *before* testing for an outlier. Until the accumulator is\n provided the number of data points specified by this option, the\n accumulator returns `null`. Default: 100.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrgrubbs();\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrmgrubbs\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n\n If provided a value, the accumulator function returns an updated harmonic\n mean. If not provided a value, the accumulator function returns the current\n harmonic mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrhmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator()\n ~2.86\n\n See Also\n --------\n incrgmean, incrmean, incrmhmean, incrsummary\n","incrkmeans":"\nincrkmeans( k[, ndims][, options] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n\n If not provided initial centroids, the accumulator caches data vectors for\n subsequent centroid initialization. Until an accumulator computes initial\n centroids, an accumulator returns `null`.\n\n Once an accumulator has initial centroids (either provided or computed), if\n provided a data vector, the accumulator function returns updated cluster\n results. If not provided a data vector, the accumulator function returns the\n current cluster results.\n\n Cluster results are comprised of the following:\n\n - centroids: a `k x ndims` matrix containing centroid locations. Each\n centroid is the component-wise mean of the data points assigned to a\n centroid's corresponding cluster.\n - stats: a `k x 4` matrix containing cluster statistics.\n\n Cluster statistics consists of the following columns:\n\n - 0: number of data points assigned to a cluster.\n - 1: total within-cluster sum of squared distances.\n - 2: arithmetic mean of squared distances.\n - 3: corrected sample standard deviation of squared distances.\n\n Because an accumulator incrementally partitions data, one should *not*\n expect cluster statistics to match similar statistics had provided data been\n analyzed via a batch algorithm. In an incremental context, data points which\n would not be considered part of a particular cluster when analyzed via a\n batch algorithm may contribute to that cluster's statistics when analyzed\n incrementally.\n\n In general, the more data provided to an accumulator, the more reliable the\n cluster statistics.\n\n Parameters\n ----------\n k: integer|ndarray\n Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n ndims: integer (optional)\n Number of dimensions. This argument must accompany an integer-valued\n first argument.\n\n options: Object (optional)\n Function options.\n\n options.metric: string (optional)\n Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n 'correlation'. Default: 'euclidean'.\n\n options.init: ArrayLike (optional)\n Centroid initialization method and associated (optional) parameters. The\n first array element specifies the initialization method and must be one\n of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n element specifies the number of data points to use when calculating\n initial centroids. When performing kmeans++ initialization, the third\n array element specifies the number of trials to perform when randomly\n selecting candidate centroids. Typically, more trials is correlated with\n initial centroids which lead to better clustering; however, a greater\n number of trials increases computational overhead. Default: ['kmeans++',\n k, 2+⌊ln(k)⌋ ].\n\n options.normalize: boolean (optional)\n Boolean indicating whether to normalize incoming data. This option is\n only relevant for non-Euclidean distance metrics. If set to `true`, an\n accumulator partitioning data based on cosine distance normalizes\n provided data to unit Euclidean length. If set to `true`, an accumulator\n partitioning data based on correlation distance first centers provided\n data and then normalizes data dimensions to have zero mean and unit\n variance. If this option is set to `false` and the metric is either\n cosine or correlation distance, then incoming data *must* already be\n normalized. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy incoming data to prevent mutation\n during normalization. Default: true.\n\n options.seed: any (optional)\n PRNG seed. Setting this option is useful when wanting reproducible\n initial centroids.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts centroid assignment for each data point in a provided matrix.\n To specify an output vector, provide a 1-dimensional ndarray as the\n first argument. Each element in the returned vector corresponds to a\n predicted cluster index for a respective data point.\n\n Examples\n --------\n > var accumulator = incrkmeans( 5, 2 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v );\n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v );\n\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n\n If provided a value, the accumulator function returns an updated corrected\n sample excess kurtosis. If not provided a value, the accumulator function\n returns the current corrected sample excess kurtosis.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrkurtosis();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( 2.0 )\n null\n > v = accumulator( -4.0 )\n null\n > v = accumulator( -4.0 )\n -6.0\n\n See Also\n --------\n incrmean, incrskewness, incrstdev, incrsummary, incrvariance\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n\n If provided input values, the accumulator function returns an updated mean\n arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current mean arctangent absolute percentage\n error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.3218\n > m = accumulator( 5.0, 2.0 )\n ~0.6523\n > m = accumulator()\n ~0.6523\n\n See Also\n --------\n incrmae, incrmape, incrmean, incrmmaape\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute error. If not provided input values, the accumulator function\n returns the current mean absolute error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmae();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmape, incrme, incrmean, incrmmae\n","incrmapcorr":"\nincrmapcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample absolute correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample absolute correlation coefficient. If not provided values, the\n accumulator function returns the current moving sample absolute correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmapcorr( 3 );\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator( 3.0, -1.0 )\n ~0.925\n > ar = accumulator( 5.0, -9.5 )\n ~0.863\n > ar = accumulator()\n ~0.863\n\n See Also\n --------\n incrapcorr, incrmpcorr, incrmpcorr2\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute percentage error. If not provided input values, the accumulator\n function returns the current mean absolute percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator()\n ~91.67\n\n See Also\n --------\n incrmaape, incrmae, incrmean, incrmmape\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n\n If provided a value, the accumulator function returns an updated maximum\n value. If not provided a value, the accumulator function returns the current\n maximum value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmax();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmidrange, incrmin, incrmmax, incrrange, incrsummary\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n\n If provided a value, the accumulator function returns an updated maximum\n absolute value. If not provided a value, the accumulator function returns\n the current maximum absolute value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaxabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmax, incrminabs, incrmmaxabs\n","incrmcovariance":"\nincrmcovariance( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample covariance.\n\n If provided values, the accumulator function returns an updated moving\n unbiased sample covariance. If not provided values, the accumulator function\n returns the current moving unbiased sample covariance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcovariance( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator( 3.0, -1.0 )\n -8.35\n > v = accumulator( 5.0, -9.5 )\n -29.42\n > v = accumulator()\n -29.42\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrmvariance\n","incrmcv":"\nincrmcv( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n\n The `W` parameter defines the number of values over which to compute the\n moving coefficient of variation.\n\n If provided a value, the accumulator function returns an updated moving\n coefficient of variation. If not provided a value, the accumulator function\n returns the current moving coefficient of variation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcv( 3 );\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator( 3.0 )\n 0.5\n > cv = accumulator( 7.0 )\n ~0.83\n > cv = accumulator()\n ~0.83\n\n See Also\n --------\n incrcv, incrmmean, incrmstdev, incrmvmr\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n\n If provided input values, the accumulator function returns an updated mean\n directional accuracy. If not provided input values, the accumulator function\n returns the current mean directional accuracy.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmda();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 4.0 )\n 0.5\n > m = accumulator()\n 0.5\n\n See Also\n --------\n incrmape, incrmmda\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n\n If provided input values, the accumulator function returns an updated mean\n error. If not provided input values, the accumulator function returns the\n current mean error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrme();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmae, incrmean, incrmme\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator()\n -1.5\n\n See Also\n --------\n incrmidrange, incrmmean, incrstdev, incrsum, incrsummary, incrvariance\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator()\n 3.5\n\n See Also\n --------\n incrmean, incrmmeanabs, incrsumabs\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs2();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 4.0\n > mu = accumulator( -5.0 )\n 14.5\n > mu = accumulator()\n 14.5\n\n See Also\n --------\n incrmean, incrmeanabs, incrmmeanabs2, incrsumabs2\n","incrmeanstdev":"\nincrmeanstdev( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanstdev();\n > var ms = accumulator()\n null\n > ms = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > ms = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > ms = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > ms = accumulator( 5.0 )\n [ 1.25, ~4.35 ]\n > ms = accumulator()\n [ 1.25, ~4.35 ]\n\n See Also\n --------\n incrmean, incrmeanvar, incrmmeanstdev, incrstdev\n","incrmeanvar":"\nincrmeanvar( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanvar();\n > var mv = accumulator()\n null\n > mv = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > mv = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > mv = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > mv = accumulator( 5.0 )\n [ 1.25, ~18.92 ]\n > mv = accumulator()\n [ 1.25, ~18.92 ]\n\n See Also\n --------\n incrmean, incrmeanstdev, incrmmeanvar, incrvariance\n","incrmgmean":"\nincrmgmean( W )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving geometric mean.\n\n If provided a value, the accumulator function returns an updated moving\n geometric mean. If not provided a value, the accumulator function returns\n the current moving geometric mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmgmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator( 3.0 )\n ~3.11\n > v = accumulator( 5.0 )\n ~4.22\n > v = accumulator()\n ~4.22\n\n See Also\n --------\n incrgmean, incrmhmean, incrmmean\n","incrmgrubbs":"\nincrmgrubbs( W[, options] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n The `W` parameter defines the number of values over which to perform Grubbs'\n test. The minimum window size is 3.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n Until provided `W` values, the accumulator function returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrmgrubbs( 20 );\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrgrubbs\n","incrmhmean":"\nincrmhmean( W )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving harmonic mean.\n\n If provided a value, the accumulator function returns an updated moving\n harmonic mean. If not provided a value, the accumulator function returns the\n current moving harmonic mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmhmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator( 3.0 )\n ~2.90\n > v = accumulator( 5.0 )\n ~4.09\n > v = accumulator()\n ~4.09\n\n See Also\n --------\n incrhmean, incrmgmean, incrmmean\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If provided a value, the accumulator function returns an updated mid-range.\n If not provided a value, the accumulator function returns the current mid-\n range.\n\n If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmidrange();\n > var v = accumulator()\n null\n > v = accumulator( 3.14 )\n 3.14\n > v = accumulator( -5.0 )\n ~-0.93\n > v = accumulator( 10.1 )\n 2.55\n > v = accumulator()\n 2.55\n\n See Also\n --------\n incrmean, incrmax, incrmin, incrrange, incrsummary\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n\n If provided a value, the accumulator function returns an updated minimum\n value. If not provided a value, the accumulator function returns the current\n minimum value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmin();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 10.1 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmax, incrmidrange, incrmmin, incrrange, incrsummary\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n\n If provided a value, the accumulator function returns an updated minimum\n absolute value. If not provided a value, the accumulator function returns\n the current minimum absolute value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 3.14\n > m = accumulator()\n 3.14\n\n See Also\n --------\n incrmaxabs, incrmin, incrmminabs\n","incrminmax":"\nincrminmax( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmax();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmminmax, incrrange\n","incrminmaxabs":"\nincrminmaxabs( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmaxabs();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator()\n [ 2.0, 5.0 ]\n\n See Also\n --------\n incrmaxabs, incrminabs, incrminmax, incrmminmaxabs\n","incrmmaape":"\nincrmmaape( W )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean arctangent absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean arctangent absolute\n percentage error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.32\n > m = accumulator( 5.0, 2.0 )\n ~0.65\n > m = accumulator( 3.0, 2.0 )\n ~0.59\n > m = accumulator( 2.0, 5.0 )\n ~0.66\n > m = accumulator()\n ~0.66\n\n See Also\n --------\n incrmaape, incrmmape, incrmmpe, incrmmean\n","incrmmae":"\nincrmmae( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute error.\n\n If provided a value, the accumulator function returns an updated moving\n mean absolute error. If not provided a value, the accumulator function\n returns the current moving mean absolute error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmae( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n 3.0\n > m = accumulator( 5.0, -2.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmae, incrmme, incrmmean\n","incrmmape":"\nincrmmape( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean absolute percentage\n error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator( 3.0, 2.0 )\n ~77.78\n > m = accumulator( 2.0, 5.0 )\n ~86.67\n > m = accumulator()\n ~86.67\n\n See Also\n --------\n incrmape, incrmmaape, incrmmpe, incrmmean\n","incrmmax":"\nincrmmax( W )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum.\n\n If provided a value, the accumulator function returns an updated moving\n maximum. If not provided a value, the accumulator function returns the\n current moving maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmax( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 3.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmmidrange, incrmmin, incrmrange, incrmsummary\n","incrmmaxabs":"\nincrmmaxabs( W )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n maximum absolute value. If not provided a value, the accumulator function\n returns the current moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaxabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 3.0 )\n 5.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmaxabs, incrmmax, incrmminabs\n","incrmmda":"\nincrmmda( W )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean directional accuracy.\n\n If provided input values, the accumulator function returns an updated moving\n mean directional accuracy. If not provided input values, the accumulator\n function returns the current moving mean directional accuracy.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmda( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( 5.0, 2.0 )\n 0.5\n > m = accumulator( 3.0, 2.0 )\n ~0.33\n > m = accumulator( 4.0, 5.0 )\n ~0.33\n > m = accumulator()\n ~0.33\n\n See Also\n --------\n incrmda, incrmmape\n","incrmme":"\nincrmme( W )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean error.\n\n If provided a value, the accumulator function returns an updated moving\n mean error. If not provided a value, the accumulator function returns the\n current moving mean error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmme( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n ~2.33\n > m = accumulator( 5.0, -2.0 )\n ~-0.33\n > m = accumulator()\n ~-0.33\n\n See Also\n --------\n incrme, incrmmae, incrmmean\n","incrmmean":"\nincrmmean( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmean( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator( 3.0 )\n 0.0\n > mu = accumulator( 5.0 )\n 1.0\n > mu = accumulator()\n 1.0\n\n See Also\n --------\n incrmean, incrmsum, incrmstdev, incrmsummary, incrmvariance\n","incrmmeanabs":"\nincrmmeanabs( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator( 3.0 )\n ~3.33\n > mu = accumulator( 5.0 )\n ~4.33\n > mu = accumulator()\n ~4.33\n\n See Also\n --------\n incrmeanabs, incrmmean, incrmsumabs\n","incrmmeanabs2":"\nincrmmeanabs2( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs2( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 4.0\n > m = accumulator( -5.0 )\n 14.5\n > m = accumulator( 3.0 )\n ~12.67\n > m = accumulator( 5.0 )\n ~19.67\n > m = accumulator()\n ~19.67\n\n See Also\n --------\n incrmeanabs2, incrmmeanabs, incrmsumabs2\n","incrmmeanstdev":"\nincrmmeanstdev( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanstdev( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > v = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > v = accumulator( 5.0 )\n [ 1.0, ~5.29 ]\n > v = accumulator()\n [ 1.0, ~5.29 ]\n\n See Also\n --------\n incrmeanstdev, incrmmean, incrmmeanvar, incrmstdev\n","incrmmeanvar":"\nincrmmeanvar( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanvar( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > v = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > v = accumulator( 5.0 )\n [ 1.0, 28.0 ]\n > v = accumulator()\n [ 1.0, 28.0 ]\n\n See Also\n --------\n incrmeanvar, incrmmean, incrmmeanstdev, incrmvariance\n","incrmmidrange":"\nincrmmidrange( W )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of values over which to compute\n the moving mid-range.\n\n If provided a value, the accumulator function returns an updated moving mid-\n range. If not provided a value, the accumulator function returns the current\n moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmidrange( 3 );\n > var mr = accumulator()\n null\n > mr = accumulator( 2.0 )\n 2.0\n > mr = accumulator( -5.0 )\n -1.5\n > mr = accumulator( 3.0 )\n -1.0\n > mr = accumulator( 5.0 )\n 0.0\n > mr = accumulator()\n 0.0\n\n See Also\n --------\n incrmmean, incrmmax, incrmmin, incrmrange\n","incrmmin":"\nincrmmin( W )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum. If not provided a value, the accumulator function returns the\n current moving minimum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmin( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 3.0 )\n -5.0\n > m = accumulator( 5.0 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmin, incrmmax, incrmmidrange, incrmrange, incrmsummary\n","incrmminabs":"\nincrmminabs( W )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n minimum absolute value. If not provided a value, the accumulator function\n returns the current moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 2.0\n > m = accumulator( 5.0 )\n 3.0\n > m = accumulator()\n 3.0\n\n See Also\n --------\n incrminabs, incrmmaxabs, incrmmin\n","incrmminmax":"\nincrmminmax( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum and maximum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmax( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmmax, incrminmax, incrmmin, incrmrange\n","incrmminmaxabs":"\nincrmminmaxabs( [out,] W )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n\n The `W` parameter defines the number of values over which to compute moving\n minimum and maximum absolute values.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmaxabs( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 3.0, 5.0 ]\n > mm = accumulator()\n [ 3.0, 5.0 ]\n\n See Also\n --------\n incrminmaxabs, incrmmax, incrmmaxabs, incrmmin, incrmminabs, incrmminmax\n","incrmmpe":"\nincrmmpe( W )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean percentage error. If not provided input values, the accumulator\n function returns the current moving mean percentage error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmpe( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator( 3.0, 2.0 )\n ~-55.56\n > m = accumulator( 2.0, 5.0 )\n ~-46.67\n > m = accumulator()\n ~-46.67\n\n See Also\n --------\n incrmmape, incrmme, incrmpe\n","incrmmse":"\nincrmmse( W )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean squared error.\n\n If provided a value, the accumulator function returns an updated moving mean\n squared error. If not provided a value, the accumulator function returns the\n current moving mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmse( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator( 3.0, 2.0 )\n 17.0\n > m = accumulator( 5.0, -2.0 )\n 33.0\n > m = accumulator()\n 33.0\n\n See Also\n --------\n incrmrmse, incrmrss, incrmse\n","incrmpcorr":"\nincrmpcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation coefficient. If not provided values, the accumulator\n function returns the current moving sample correlation coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator( 3.0, -1.0 )\n ~-0.925\n > r = accumulator( 5.0, -9.5 )\n ~-0.863\n > r = accumulator()\n ~-0.863\n\n See Also\n --------\n incrmcovariance, incrmpcorrdist, incrpcorr\n","incrmpcorr2":"\nincrmpcorr2( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving squared sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n squared sample correlation coefficient. If not provided values, the\n accumulator function returns the current moving squared sample correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr2( 3 );\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator( 3.0, -1.0 )\n ~0.86\n > r2 = accumulator( 5.0, -9.5 )\n ~0.74\n > r2 = accumulator()\n ~0.74\n\n See Also\n --------\n incrmapcorr, incrmpcorr, incrpcorr2\n","incrmpcorrdist":"\nincrmpcorrdist( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n However, due to limitations inherent in representing numeric values using\n floating-point format (i.e., the inability to represent numeric values with\n infinite precision), the correlation distance between perfectly correlated\n random variables may *not* be `0` or `2`. In fact, the correlation distance\n is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n distance should, however, be within floating-point roundoff error.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation distance.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation distance. If not provided values, the accumulator\n function returns the current moving sample correlation distance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorrdist( 3 );\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator( 3.0, -1.0 )\n ~1.925\n > d = accumulator( 5.0, -9.5 )\n ~1.863\n > d = accumulator()\n ~1.863\n\n See Also\n --------\n incrmpcorr, incrpcorrdist\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n\n If provided input values, the accumulator function returns an updated mean\n percentage error. If not provided input values, the accumulator function\n returns the current mean percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpe();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator()\n ~-58.33\n\n See Also\n --------\n incrmape, incrme, incrmmpe\n","incrmprod":"\nincrmprod( W )\n Returns an accumulator function which incrementally computes a moving\n product.\n\n The `W` parameter defines the number of values over which to compute the\n moving product.\n\n If provided a value, the accumulator function returns an updated moving\n product. If not provided a value, the accumulator function returns the\n current moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n For accumulations over large windows or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmprod( 3 );\n > var p = accumulator()\n null\n > p = accumulator( 2.0 )\n 2.0\n > p = accumulator( -5.0 )\n -10.0\n > p = accumulator( 3.0 )\n -30.0\n > p = accumulator( 5.0 )\n -75.0\n > p = accumulator()\n -75.0\n\n See Also\n --------\n incrmsum, incrprod\n","incrmrange":"\nincrmrange( W )\n Returns an accumulator function which incrementally computes a moving range.\n\n The `W` parameter defines the number of values over which to compute the\n moving range.\n\n If provided a value, the accumulator function returns an updated moving\n range. If not provided a value, the accumulator function returns the current\n moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrange( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0 )\n 0.0\n > r = accumulator( -5.0 )\n 7.0\n > r = accumulator( 3.0 )\n 8.0\n > r = accumulator( 5.0 )\n 10.0\n > r = accumulator()\n 10.0\n\n See Also\n --------\n incrmmax, incrmmean, incrmmin, incrmsummary, incrrange\n","incrmrmse":"\nincrmrmse( W )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving root mean squared error.\n\n If provided a value, the accumulator function returns an updated moving root\n mean squared error. If not provided a value, the accumulator function\n returns the current moving root mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrmse( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator( 3.0, 2.0 )\n ~4.12\n > r = accumulator( 5.0, -2.0 )\n ~5.74\n > r = accumulator()\n ~5.74\n\n See Also\n --------\n incrmmse, incrmrss, incrrmse\n","incrmrss":"\nincrmrss( W )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n\n The `W` parameter defines the number of values over which to compute the\n moving residual sum of squares.\n\n If provided a value, the accumulator function returns an updated moving\n residual sum of squares. If not provided a value, the accumulator function\n returns the current moving residual sum of squares.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrss( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator( 3.0, 2.0 )\n 51.0\n > r = accumulator( 5.0, -2.0 )\n 99.0\n > r = accumulator()\n 99.0\n\n See Also\n --------\n incrrss, incrmmse, incrmrmse\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n\n If provided input values, the accumulator function returns an updated mean\n squared error. If not provided input values, the accumulator function\n returns the current mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmse();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator()\n 25.0\n\n See Also\n --------\n incrmmse, incrrmse, incrrss\n","incrmstdev":"\nincrmstdev( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving corrected sample standard deviation.\n\n If provided a value, the accumulator function returns an updated moving\n corrected sample standard deviation. If not provided a value, the\n accumulator function returns the current moving corrected sample standard\n deviation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmstdev( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator( 3.0 )\n ~4.36\n > s = accumulator( 5.0 )\n ~5.29\n > s = accumulator()\n ~5.29\n\n See Also\n --------\n incrmmean, incrmsummary, incrmvariance, incrstdev\n","incrmsum":"\nincrmsum( W )\n Returns an accumulator function which incrementally computes a moving sum.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsum( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator( 3.0 )\n 0.0\n > s = accumulator( 5.0 )\n 3.0\n > s = accumulator()\n 3.0\n\n See Also\n --------\n incrmmean, incrmsummary, incrsum\n","incrmsumabs":"\nincrmsumabs( W )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator( 3.0 )\n 10.0\n > s = accumulator( -5.0 )\n 13.0\n > s = accumulator()\n 13.0\n\n See Also\n --------\n incrmmeanabs, incrmsum, incrsum, incrsumabs\n","incrmsumabs2":"\nincrmsumabs2( W )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs2( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator( 3.0 )\n 38.0\n > s = accumulator( -5.0 )\n 59.0\n > s = accumulator()\n 59.0\n\n See Also\n --------\n incrmmeanabs2, incrmsumabs, incrsumabs, incrsumabs2\n","incrmsummary":"\nincrmsummary( W )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n\n The `W` parameter defines the number of values over which to compute the\n moving statistical summary.\n\n If provided a value, the accumulator function returns an updated moving\n statistical summary. If not provided a value, the accumulator function\n returns the current moving statistical summary.\n\n The returned summary is an object containing the following fields:\n\n - window: window size.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - range: range.\n - midrange: arithmetic mean of the minimum and maximum values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n summaries are calculated from smaller sample sizes. Until the window is\n full, each returned summary is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsummary( 3 );\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsum, incrmvariance, incrsummary\n","incrmsumprod":"\nincrmsumprod( W )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n\n The `W` parameter defines the number of (x,y) pairs over which to compute\n the moving sum of products.\n\n If provided input values, the accumulator function returns an updated moving\n sum. If not provided input values, the accumulator function returns the\n current moving sum.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumprod( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator( 3.0, -2.0 )\n -10.0\n > s = accumulator( 5.0, 3.0 )\n -1.0\n > s = accumulator()\n -1.0\n\n See Also\n --------\n incrmprod, incrmsum, incrsumprod\n","incrmvariance":"\nincrmvariance( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample variance.\n\n If provided a value, the accumulator function returns an updated moving\n unbiased sample variance. If not provided a value, the accumulator function\n returns the current moving unbiased sample variance.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvariance( 3 );\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator( 3.0 )\n 19.0\n > s2 = accumulator( 5.0 )\n 28.0\n > s2 = accumulator()\n 28.0\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsummary, incrvariance\n","incrmvmr":"\nincrmvmr( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n\n The `W` parameter defines the number of values over which to compute the\n moving variance-to-mean ratio.\n\n If provided a value, the accumulator function returns an updated moving\n variance-to-mean ratio. If not provided a value, the accumulator function\n returns the current moving variance-to-mean ratio.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvmr( 3 );\n > var F = accumulator()\n null\n > F = accumulator( 2.0 )\n 0.0\n > F = accumulator( 1.0 )\n ~0.33\n > F = accumulator( 3.0 )\n 0.5\n > F = accumulator( 7.0 )\n ~2.55\n > F = accumulator()\n ~2.55\n\n See Also\n --------\n incrmmean, incrmvariance, incrvmr\n","incrnancount":"\nincrnancount()\n Returns an accumulator function which incrementally updates a count,\n ignoring `NaN` values.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnancount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrnansum\n","incrnansum":"\nincrnansum()\n Returns an accumulator function which incrementally computes a sum, ignoring\n `NaN` values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( NaN )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrnansumabs, incrsum\n","incrnansumabs":"\nincrnansumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values, ignoring NaN values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( NaN )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrnansum, incrnansumabs2, incrsumabs\n","incrnansumabs2":"\nincrnansumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values, ignoring NaN values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( NaN )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrnansum, incrnansumabs, incrsumabs2\n","incrpcorr":"\nincrpcorr( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated sample\n correlation coefficient. If not provided values, the accumulator function\n returns the current sample correlation coefficient.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator()\n ~-1.0\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrsummary\n","incrpcorr2":"\nincrpcorr2( [mx, my] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr2();\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator()\n ~1.0\n\n See Also\n --------\n incrapcorr, incrmpcorr2, incrpcorr\n","incrpcorrdist":"\nincrpcorrdist( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n If provided values, the accumulator function returns an updated sample\n correlation distance. If not provided values, the accumulator function\n returns the current sample correlation distance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdist();\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator()\n ~2.0\n\n See Also\n --------\n incrcovariance, incrpcorr, incrsummary\n","incrpcorrdistmat":"\nincrpcorrdistmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation distance matrix. If not provided a data vector, the\n accumulator function returns the current sample correlation distance matrix.\n\n Due to limitations inherent in representing numeric values using floating-\n point format (i.e., the inability to represent numeric values with infinite\n precision), the correlation distance between perfectly correlated random\n variables may *not* be `0` or `2`. In fact, the correlation distance is\n *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n should, however, be within floating-point roundoff error.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation distance matrix or a square 2-dimensional\n ndarray for storing the correlation distance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdistmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrpcorrdist, incrpcorrmat\n","incrpcorrmat":"\nincrpcorrmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation matrix. If not provided a data vector, the accumulator\n function returns the current sample correlation matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation matrix or a square 2-dimensional ndarray for\n storing the correlation matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovmat, incrpcorr, incrpcorrdistmat\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n\n If provided a value, the accumulator function returns an updated product. If\n not provided a value, the accumulator function returns the current product.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrprod();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -10.0\n > v = accumulator()\n -10.0\n\n See Also\n --------\n incrmprod, incrsum, incrsummary\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n\n If provided a value, the accumulator function returns an updated range. If\n not provided a value, the accumulator function returns the current range.\n\n If provided `NaN`, the range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrange();\n > var v = accumulator()\n null\n > v = accumulator( -2.0 )\n 0.0\n > v = accumulator( 1.0 )\n 3.0\n > v = accumulator( 3.0 )\n 5.0\n > v = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmean, incrmin, incrmrange, incrsummary\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n\n If provided input values, the accumulator function returns an updated root\n mean squared error. If not provided input values, the accumulator function\n returns the current root mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrmse();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator()\n 5.0\n\n See Also\n --------\n incrmrmse, incrmse, incrrss\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n\n If provided input values, the accumulator function returns an updated\n residual sum of squares. If not provided input values, the accumulator\n function returns the current residual sum of squares.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrss();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator()\n 50.0\n\n See Also\n --------\n incrmrss, incrmse, incrrmse\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n\n If provided a value, the accumulator function returns an updated corrected\n sample skewness. If not provided a value, the accumulator function returns\n the current corrected sample skewness.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrskewness();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( -5.0 )\n null\n > v = accumulator( -10.0 )\n ~0.492\n > v = accumulator()\n ~0.492\n\n See Also\n --------\n incrkurtosis, incrmean, incrstdev, incrsummary, incrvariance\n","incrspace":"\nincrspace( start, stop[, increment] )\n Generates a linearly spaced numeric array using a provided increment.\n\n If an `increment` is not provided, the default `increment` is `1`.\n\n The output array is guaranteed to include the `start` value but does not\n include the `stop` value.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Array element bound.\n\n increment: number (optional)\n Increment. Default: `1`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = incrspace( 0, 11, 2 )\n [ 0, 2, 4, 6, 8, 10 ]\n\n See Also\n --------\n linspace, logspace\n","incrstdev":"\nincrstdev( [mean] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n\n If provided a value, the accumulator function returns an updated corrected\n sample standard deviation. If not provided a value, the accumulator function\n returns the current corrected sample standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrstdev();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator()\n ~4.95\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrsummary, incrvariance\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrcount, incrmean, incrmsum, incrprod, incrsummary\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrmeanabs, incrmsumabs, incrsum\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrmeanabs2, incrmsumabs2, incrsumabs\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n\n If provided a value, the accumulator function returns an updated summary. If\n not provided a value, the accumulator function returns the current summary.\n\n The returned summary is an object containing the following fields:\n\n - count: count.\n - max: maximum value.\n - min: minimum value.\n - range: range.\n - midrange: mid-range.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - skewness: corrected sample skewness.\n - kurtosis: corrected sample excess kurtosis.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsummary();\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrcount, incrkurtosis, incrmax, incrmean, incrmidrange, incrmin, incrmsummary, incrrange, incrskewness, incrstdev, incrsum, incrvariance\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n\n If provided input values, the accumulator function returns an updated sum.\n If not provided input values, the accumulator function returns the current\n sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumprod();\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator()\n -4.0\n\n See Also\n --------\n incrmsumprod, incrprod, incrsum\n","incrvariance":"\nincrvariance( [mean] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n\n If provided a value, the accumulator function returns an updated unbiased\n sample variance. If not provided a value, the accumulator function returns\n the current unbiased sample variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvariance();\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator()\n 24.5\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrstdev, incrsummary\n","incrvmr":"\nincrvmr( [mean] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvmr();\n > var D = accumulator()\n null\n > D = accumulator( 2.0 )\n 0.0\n > D = accumulator( 1.0 )\n ~0.33\n > D = accumulator()\n ~0.33\n\n See Also\n --------\n incrmean, incrmvmr, incrvariance\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n\n If provided arguments, the accumulator function returns an updated weighted\n mean. If not provided arguments, the accumulator function returns the\n current weighted mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n The accumulator function accepts two arguments:\n\n - x: value.\n - w: weight.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrwmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0, 1.0 )\n 2.0\n > mu = accumulator( 2.0, 0.5 )\n 2.0\n > mu = accumulator( 3.0, 1.5 )\n 2.5\n > mu = accumulator()\n 2.5\n\n See Also\n --------\n increwmean, incrmean, incrmmean\n","ind2sub":"\nind2sub( shape, idx[, options] )\n Converts a linear index to an array of subscripts.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n Returns\n -------\n out: Array\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var s = ind2sub( d, 17 )\n [ 1, 2, 2 ]\n\n\nind2sub.assign( shape, idx[, options], out )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n out: Array|TypedArray|Object\n Output array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var out = [ 0, 0, 0 ];\n > var s = ind2sub.assign( d, 17, out )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind\n","ind2sub.assign":"\nind2sub.assign( shape, idx[, options], out )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n out: Array|TypedArray|Object\n Output array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var out = [ 0, 0, 0 ];\n > var s = ind2sub.assign( d, 17, out )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind","indexOf":"\nindexOf( arr, searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n Search is performed using *strict equality* comparison.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object.\n\n searchElement: any\n Element to find.\n\n fromIndex: integer (optional)\n Starting index (if negative, the start index is determined relative to\n last element).\n\n Returns\n -------\n out: integer\n Index or -1.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ 4, 3, 2, 1 ];\n > var idx = indexOf( arr, 3 )\n 1\n > arr = [ 4, 3, 2, 1 ];\n > idx = indexOf( arr, 5 )\n -1\n\n // Using a `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, 3 )\n 5\n\n // `fromIndex` which exceeds `array` length:\n > arr = [ 1, 2, 3, 4, 2, 5 ];\n > idx = indexOf( arr, 2, 10 )\n -1\n\n // Negative `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n > idx = indexOf( arr, 2, -4 )\n 5\n > idx = indexOf( arr, 2, -1 )\n 7\n\n // Negative `fromIndex` exceeding input `array` length:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, -10 )\n 1\n\n // Array-like objects:\n > var str = 'bebop';\n > idx = indexOf( str, 'o' )\n 3\n\n","inherit":"\ninherit( ctor, superCtor )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n\n This function is not designed to work with ES2015/ES6 classes. For\n ES2015/ES6 classes, use `class` with `extends`.\n\n Parameters\n ----------\n ctor: Object|Function\n Constructor which will inherit.\n\n superCtor: Object|Function\n Super (parent) constructor.\n\n Returns\n -------\n out: Object|Function\n Child constructor.\n\n Examples\n --------\n // Create a parent constructor:\n > function Foo() { return this; };\n > Foo.prototype.beep = function beep() { return 'boop'; };\n\n // Create a child constructor:\n > function Bar() { Foo.call( this ); return this; };\n\n // Setup inheritance:\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var v = bar.beep()\n 'boop'\n\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value[, level] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited enumerable properties.\n\n Examples\n --------\n > var props = inheritedEnumerableProperties( {} )\n\n See Also\n --------\n enumerableProperties, enumerablePropertiesIn, inheritedEnumerablePropertySymbols, inheritedKeys, inheritedNonEnumerableProperties, inheritedProperties\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbols, inheritedKeys, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedKeys":"\ninheritedKeys( value[, level] )\n Returns an array of an object's inherited enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable property names.\n\n Examples\n --------\n > var keys = inheritedKeys( {} )\n\n See Also\n --------\n objectKeys, keysIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value[, level] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited non-enumerable properties.\n\n Examples\n --------\n > var props = inheritedNonEnumerableProperties( {} )\n\n See Also\n --------\n inheritedEnumerableProperties, inheritedNonEnumerablePropertyNames, inheritedNonEnumerablePropertySymbols, inheritedKeys, nonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value[, level] )\n Returns an array of an object's inherited non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited non-enumerable property names.\n\n Examples\n --------\n > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertySymbols, objectKeys, nonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertyNames, nonEnumerableProperties, nonEnumerablePropertyNames, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedProperties":"\ninheritedProperties( value[, level] )\n Returns an array of an object's inherited property names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited property names and symbols.\n\n Examples\n --------\n > var symbols = inheritedProperties( [] )\n\n See Also\n --------\n properties, propertiesIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value, property[, level] )\n Returns a property descriptor for an object's inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n {...}\n\n See Also\n --------\n propertyDescriptor, propertyDescriptorIn, inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value[, level] )\n Returns an object's inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object\n An object's inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = inheritedPropertyDescriptors( obj )\n { 'foo': {...}, ... }\n\n See Also\n --------\n propertyDescriptors, propertyDescriptorsIn, inheritedKeys, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyNames":"\ninheritedPropertyNames( value[, level] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable and non-enumerable property\n names.\n\n Examples\n --------\n > var keys = inheritedPropertyNames( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertySymbols, propertyNames, propertyNamesIn\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value[, level] )\n Returns an array of an object's inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited symbol properties.\n\n Examples\n --------\n > var symbols = inheritedPropertySymbols( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, propertySymbols, propertySymbolsIn\n","inheritedWritableProperties":"\ninheritedWritableProperties( value[, level] )\n Returns an array of an object's inherited writable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited writable properties.\n\n Examples\n --------\n > var props = inheritedWritableProperties( {} )\n\n See Also\n --------\n inheritedWritablePropertyNames, inheritedWritablePropertySymbols, writableProperties, writablePropertiesIn, properties\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value[, level] )\n Returns an array of an object's inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited writable property names.\n\n Examples\n --------\n > var keys = inheritedWritablePropertyNames( {} )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertyNames, writablePropertyNamesIn, properties\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value[, level] )\n Returns an array of an object's inherited writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited writable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedWritablePropertySymbols( [] )\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertySymbols, writablePropertySymbolsIn, properties\n","inmap":"\ninmap( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmap( arr, foo )\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEach, inmapRight, map\n","inmapAsync":"\ninmapAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: value used to update the collection.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 2000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 2000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap\n","inmapAsync.factory":"\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap","inmapRight":"\ninmapRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmapRight( arr, foo )\n 2: 3.0\n 1: 2.0\n 0: 1.0\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEachRight, inmap, mapRight\n","inmapRightAsync":"\ninmapRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: value used to update the collection.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 6000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 6000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight","inspectSinkStream":"\ninspectSinkStream( [options,] clbk )\n Returns a writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream","inspectStream":"\ninspectStream( [options,] clbk )\n Returns a transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream\n","inspectStream.factory":"\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","inspectStream.objectMode":"\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream","instanceOf":"\ninstanceOf( value, constructor )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n\n While the prototype of an `object` created using object literal notion is\n `undefined`, the function returns `true` when provided an `object` literal\n and the `Object` constructor. This maintains consistent behavior with the\n `instanceof` operator.\n\n Parameters\n ----------\n value: any\n Input value.\n\n constructor: Function\n Constructor.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an instance of a provided constructor.\n\n Examples\n --------\n > var bool = instanceOf( [], Array )\n true\n > bool = instanceOf( {}, Object )\n true\n > bool = instanceOf( null, Object )\n false\n\n See Also\n --------\n isPrototypeOf, constructorName, inherit, typeOf\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n\n The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n Examples\n --------\n > INT8_MAX\n 127\n\n See Also\n --------\n INT8_MIN\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n\n The minimum signed 8-bit integer is given by `-(2^7)`.\n\n Examples\n --------\n > INT8_MIN\n -128\n\n See Also\n --------\n INT8_MAX\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n\n Examples\n --------\n > INT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT16_NUM_BYTES, INT32_NUM_BYTES, UINT8_NUM_BYTES\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array()\n \n\n\nInt8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Int8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'\n\n\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n \n\n\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5\n\n\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int8Array.from":"\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int8Array.of":"\nInt8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1","Int8Array.name":"\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n ","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Int8Array.prototype.length":"\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n\n The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n Examples\n --------\n > INT16_MAX\n 32767\n\n See Also\n --------\n INT16_MIN\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n\n The minimum signed 16-bit integer is given by `-(2^15)`.\n\n Examples\n --------\n > INT16_MIN\n -32768\n\n See Also\n --------\n INT16_MAX\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n\n Examples\n --------\n > INT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT32_NUM_BYTES, INT8_NUM_BYTES, UINT16_NUM_BYTES\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array()\n \n\n\nInt16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Int16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'\n\n\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n \n\n\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10\n\n\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int16Array.from":"\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int16Array.of":"\nInt16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2","Int16Array.name":"\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n ","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2","Int16Array.prototype.length":"\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n\n The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n Examples\n --------\n > INT32_MAX\n 2147483647\n\n See Also\n --------\n INT32_MIN\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n\n The minimum signed 32-bit integer is given by `-(2^31)`.\n\n Examples\n --------\n > INT32_MIN\n -2147483648\n\n See Also\n --------\n INT32_MAX\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n\n Examples\n --------\n > INT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT16_NUM_BYTES, INT8_NUM_BYTES, UINT32_NUM_BYTES\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array()\n \n\n\nInt32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 5, 5, 5 ] );\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Int32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'\n\n\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n \n\n\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20\n\n\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int32Array.from":"\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int32Array.of":"\nInt32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4","Int32Array.name":"\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n ","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Int32Array.prototype.length":"\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n\n Examples\n --------\n > IS_BIG_ENDIAN\n \n\n See Also\n --------\n IS_LITTLE_ENDIAN\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n\n Examples\n --------\n > IS_BROWSER\n \n\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n\n Examples\n --------\n > IS_DARWIN\n \n\n","IS_DOCKER":"\nIS_DOCKER\n Boolean indicating if the process is running in a Docker container.\n\n Examples\n --------\n > IS_DOCKER\n \n\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n\n Examples\n --------\n > IS_ELECTRON\n \n\n See Also\n --------\n IS_ELECTRON_MAIN, IS_ELECTRON_RENDERER\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n\n Examples\n --------\n > IS_ELECTRON_MAIN\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_RENDERER\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n\n Examples\n --------\n > IS_ELECTRON_RENDERER\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_MAIN\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n\n Examples\n --------\n > IS_LITTLE_ENDIAN\n \n\n See Also\n --------\n IS_BIG_ENDIAN\n","IS_MOBILE":"\nIS_MOBILE\n Boolean indicating if the current environment is a mobile device.\n\n Examples\n --------\n > IS_MOBILE\n \n\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n\n Examples\n --------\n > IS_NODE\n \n\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n Boolean indicating if the current environment is a touch device.\n\n Examples\n --------\n > IS_TOUCH_DEVICE\n \n\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n\n Examples\n --------\n > IS_WEB_WORKER\n \n\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n\n Examples\n --------\n > IS_WINDOWS\n \n\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value )\n Tests whether a value is an absolute HTTP(S) URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is an absolute HTTP(S) URI.\n\n Examples\n --------\n > var bool = isAbsoluteHttpURI( 'http://example.com/' )\n true\n > bool = isAbsoluteHttpURI( 'example.com' )\n false\n > bool = isAbsoluteHttpURI( 'foo@bar.com' )\n false\n\n See Also\n --------\n isAbsoluteURI","isAbsolutePath":"\nisAbsolutePath( value )\n Tests if a value is an absolute path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an absolute path.\n\n Examples\n --------\n // Windows environment:\n > var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n\n // POSIX environment:\n > bool = isAbsolutePath( '/foo/bar/baz' )\n true\n\n\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false\n\n\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false","isAbsolutePath.win32":"\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath","isAbsoluteURI":"\nisAbsoluteURI( value )\n Tests whether a value is an absolute URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is an absolute URI.\n\n Examples\n --------\n > var bool = isAbsoluteURI( 'http://example.com/' )\n true\n > bool = isAbsoluteURI( 'example.com' )\n false\n > bool = isAbsoluteURI( 'foo@bar.com' )\n false\n\n See Also\n --------\n isRelativeURI","isAccessorArray":"\nisAccessorArray( value )\n Tests if a value is an array-like object supporting the accessor (get/set)\n protocol.\n\n An accessor array is defined as an array, typed array, or an array-like\n object (excluding strings and functions) having `get` and `set` methods for\n accessing array elements.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an accessor array.\n\n Examples\n --------\n > var bool = isAccessorArray( new Complex64Array( 10 ) )\n true\n > bool = isAccessorArray( [] )\n false\n > bool = isAccessorArray( { 'length': 0 } )\n false\n > bool = isAccessorArray( {} )\n false\n\n See Also\n --------\n isArrayLike, isArrayLikeObject, isCollection\n","isAccessorProperty":"\nisAccessorProperty( value, property )\n Tests if an object's own property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has an accessor\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorProperty( obj, 'boop' )\n false\n > bool = isAccessorProperty( obj, 'beep' )\n true\n\n See Also\n --------\n hasOwnProp, isAccessorPropertyIn, isDataProperty\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value, property )\n Tests if an object's own or inherited property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has an\n accessor descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorPropertyIn( obj, 'boop' )\n false\n > bool = isAccessorPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n hasProp, isAccessorProperty, isDataPropertyIn\n","isAlphagram":"\nisAlphagram( value )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n\n The function first checks that an input value is a string before validating\n that the value is an alphagram. For non-string values, the function returns\n `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an alphagram.\n\n Examples\n --------\n > var out = isAlphagram( 'beep' )\n true\n > out = isAlphagram( 'zba' )\n false\n > out = isAlphagram( '' )\n false\n\n See Also\n --------\n isAnagram\n","isAlphaNumeric":"\nisAlphaNumeric( str )\n Tests whether a string contains only alphanumeric characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only alphanumeric\n characters.\n\n Examples\n --------\n > var bool = isAlphaNumeric( 'abc0123456789' )\n true\n > bool = isAlphaNumeric( 'abcdef' )\n true\n > bool = isAlphaNumeric( '0xff' )\n true\n > bool = isAlphaNumeric( '' )\n false\n\n See Also\n --------\n isDigitString\n","isAnagram":"\nisAnagram( str, value )\n Tests if a value is an anagram.\n\n Parameters\n ----------\n str: string\n Comparison string.\n\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an anagram.\n\n Examples\n --------\n > var str1 = 'I am a weakish speller';\n > var str2 = 'William Shakespeare';\n > var bool = isAnagram( str1, str2 )\n true\n > bool = isAnagram( 'bat', 'tabba' )\n false\n\n See Also\n --------\n isAlphagram\n","isArguments":"\nisArguments( value )\n Tests if a value is an arguments object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arguments object.\n\n Examples\n --------\n > function foo() { return arguments; };\n > var bool = isArguments( foo() )\n true\n > bool = isArguments( [] )\n false\n\n","isArray":"\nisArray( value )\n Tests if a value is an array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array.\n\n Examples\n --------\n > var bool = isArray( [] )\n true\n > bool = isArray( {} )\n false\n\n See Also\n --------\n isArrayLike\n","isArrayArray":"\nisArrayArray( value )\n Tests if a value is an array of arrays.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of arrays.\n\n Examples\n --------\n > var bool = isArrayArray( [ [], [] ] )\n true\n > bool = isArrayArray( [ {}, {} ] )\n false\n > bool = isArrayArray( [] )\n false\n\n","isArrayBuffer":"\nisArrayBuffer( value )\n Tests if a value is an ArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an ArrayBuffer.\n\n Examples\n --------\n > var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\n true\n > bool = isArrayBuffer( [] )\n false\n\n See Also\n --------\n isSharedArrayBuffer, isTypedArray\n","isArrayBufferView":"\nisArrayBufferView( value )\n Tests if a value is a `ArrayBuffer` view.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `ArrayBuffer` view.\n\n Examples\n --------\n > var bool = isArrayBufferView( new Int8Array() )\n true\n > bool = isArrayBufferView( [] )\n false\n\n See Also\n --------\n isDataView, isTypedArray\n","isArrayLength":"\nisArrayLength( value )\n Tests if a value is a valid array length.\n\n A valid length property for an Array instance is any integer value on the\n interval [0, 2^32-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a valid array length.\n\n Examples\n --------\n > var bool = isArrayLength( 5 )\n true\n > bool = isArrayLength( 2.0e200 )\n false\n > bool = isArrayLength( -3.14 )\n false\n > bool = isArrayLength( null )\n false\n\n See Also\n --------\n isArray\n","isArrayLike":"\nisArrayLike( value )\n Tests if a value is array-like.\n\n If provided a string, the function returns `true`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is array-like.\n\n Examples\n --------\n > var bool = isArrayLike( [] )\n true\n > bool = isArrayLike( { 'length': 10 } )\n true\n > bool = isArrayLike( 'beep' )\n true\n > bool = isArrayLike( null )\n false\n\n See Also\n --------\n isArray, isArrayLikeObject, isCollection\n","isArrayLikeObject":"\nisArrayLikeObject( value )\n Tests if a value is an array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object.\n\n Examples\n --------\n > var bool = isArrayLikeObject( [] )\n true\n > bool = isArrayLikeObject( { 'length': 10 } )\n true\n > bool = isArrayLikeObject( 'beep' )\n false\n\n See Also\n --------\n isArray, isArrayLike, isCollection\n","isArrowFunction":"\nisArrowFunction( value )\n Tests if a value is an arrow function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arrow function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isArrowFunction( beep )\n false\n > bool = isArrowFunction( {} )\n false\n\n","isASCII":"\nisASCII( str )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string has all ASCII characters.\n\n Examples\n --------\n > var str = 'beep boop';\n > var bool = isASCII( str )\n true\n > bool = isASCII( fromCodePoint( 130 ) )\n false\n\n See Also\n --------\n isString\n","isBetween":"\nisBetween( value, a, b[, left, right] )\n Tests if a value is between two values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is between two values.\n\n Examples\n --------\n > var bool = isBetween( 3.14, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.0, 4.0 )\n true\n > bool = isBetween( 4.0, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.14, 4.0 )\n false\n > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n false\n > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetweenArray\n","isBetweenArray":"\nisBetweenArray( value, a, b[, left, right] )\n Tests if a value is an array-like object where every element is between two\n values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object where every\n element is between two values.\n\n Examples\n --------\n > var arr = [ 3.0, 3.14, 4.0 ];\n > var bool = isBetweenArray( arr, 3.0, 4.0 )\n true\n > bool = isBetweenArray( arr, 3.14, 4.0 )\n false\n > bool = isBetweenArray( arr, 3.0, 3.14 )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetween\n","isBigInt":"\nisBigInt( value )\n Tests if a value is a BigInt.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a BigInt.\n\n Examples\n --------\n > var bool = isBigInt( BigInt( '1' ) )\n true\n > bool = isBigInt( Object( BigInt( '1' ) ) )\n true\n > bool = isBigInt( {} )\n false\n > bool = isBigInt( null )\n false\n > bool = isBigInt( true )\n false\n\n","isBigInt64Array":"\nisBigInt64Array( value )\n Tests if a value is a BigInt64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a BigInt64Array.\n\n Examples\n --------\n > var bool = isBigInt64Array( new BigInt64Array( 10 ) )\n true\n > bool = isBigInt64Array( [] )\n false\n\n See Also\n --------\n isBigUint64Array\n","isBigUint64Array":"\nisBigUint64Array( value )\n Tests if a value is a BigUint64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a BigUint64Array.\n\n Examples\n --------\n > var bool = isBigUint64Array( new BigUint64Array( 10 ) )\n true\n > bool = isBigUint64Array( [] )\n false\n\n See Also\n --------\n isBigInt64Array\n","isBinaryString":"\nisBinaryString( value )\n Tests if a value is a binary string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a binary string.\n\n Examples\n --------\n > var bool = isBinaryString( '1000101' )\n true\n > bool = isBinaryString( 'beep' )\n false\n > bool = isBinaryString( '' )\n false\n\n See Also\n --------\n isString\n","isBlankString":"\nisBlankString( value )\n Tests if a value is a blank string (i.e., an empty string or a string\n consisting only of whitespace characters).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a blank string.\n\n Examples\n --------\n > var bool = isBlankString( ' ' )\n true\n > bool = isBlankString( 'beep' )\n false\n > bool = isBlankString( null )\n false\n\n See Also\n --------\n isString, isEmptyString\n","isBoolean":"\nisBoolean( value )\n Tests if a value is a boolean.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean.\n\n Examples\n --------\n > var bool = isBoolean( false )\n true\n > bool = isBoolean( new Boolean( false ) )\n true\n\n\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false\n\n\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true\n\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false","isBoolean.isObject":"\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true","isBooleanArray":"\nisBooleanArray( value )\n Tests if a value is an array-like object of booleans.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object of booleans.\n\n Examples\n --------\n > var bool = isBooleanArray( [ true, false, true ] )\n true\n > bool = isBooleanArray( [ true, 'abc', false ] )\n false\n\n\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false\n\n\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true\n\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false","isBooleanArray.objects":"\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true","isBoxedPrimitive":"\nisBoxedPrimitive( value )\n Tests if a value is a JavaScript boxed primitive.\n\n Boxed primitive objects can be created with one of the following:\n\n - new Boolean()\n - new Number()\n - new String()\n - Object( Symbol() ) (ES6/ES2015)\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a JavaScript boxed primitive.\n\n Examples\n --------\n > var bool = isBoxedPrimitive( new Boolean( false ) )\n true\n > bool = isBoxedPrimitive( true )\n false\n\n See Also\n --------\n isPrimitive\n","isBuffer":"\nisBuffer( value )\n Tests if a value is a Buffer instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Buffer instance.\n\n Examples\n --------\n > var bool = isBuffer( new Buffer( 'beep' ) )\n true\n > bool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\n true\n > bool = isBuffer( {} )\n false\n > bool = isBuffer( [] )\n false\n\n","isCamelcase":"\nisCamelcase( value )\n Tests if a value is a camelcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a camelcase string.\n\n Examples\n --------\n > var bool = isCamelcase( 'helloWorld' )\n true\n > bool = isCamelcase( 'hello world' )\n false\n\n See Also\n --------\n isString, isConstantcase","isCapitalized":"\nisCapitalized( value )\n Tests if a value is a string having an uppercase first character.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string with an uppercase first\n character.\n\n Examples\n --------\n > var bool = isCapitalized( 'Hello' )\n true\n > bool = isCapitalized( 'world' )\n false\n\n See Also\n --------\n isString\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value )\n Tests if a value is a matrix which is symmetric about its center.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a centrosymmetric matrix.\n\n Examples\n --------\n > var buf = [ 2, 1, 1, 2 ];\n > var M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isCentrosymmetricMatrix( M )\n true\n > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isCentrosymmetricMatrix( 3.14 )\n false\n > bool = isCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isCircular":"\nisCircular( value )\n Tests if an object-like value contains a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an object-like value contains a circular\n reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircular( obj )\n true\n > bool = isCircular( {} )\n false\n > bool = isCircular( null )\n false\n\n See Also\n --------\n isCircularArray, isCircularPlainObject\n","isCircularArray":"\nisCircularArray( value )\n Tests if a value is an array containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing a\n circular reference.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > arr.push( arr );\n > var bool = isCircularArray( arr )\n true\n > bool = isCircularArray( [] )\n false\n > bool = isCircularArray( null )\n false\n\n See Also\n --------\n isCircular, isCircularPlainObject\n","isCircularPlainObject":"\nisCircularPlainObject( value )\n Tests if a value is a plain object containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object containing a\n circular reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircularPlainObject( obj )\n true\n > bool = isCircularPlainObject( {} )\n false\n > bool = isCircularPlainObject( null )\n false\n\n See Also\n --------\n isCircular, isCircularArray\n","isClass":"\nisClass( value )\n Tests if a value is a class.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a class.\n\n Examples\n --------\n > var bool = isClass( class Person {} )\n true\n > bool = isClass( function Person() {} )\n false\n > bool = isClass( {} )\n false\n > bool = isClass( null )\n false\n > bool = isClass( true )\n false\n","isCollection":"\nisCollection( value )\n Tests if a value is a collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a collection.\n\n Examples\n --------\n > var bool = isCollection( [] )\n true\n > bool = isCollection( { 'length': 0 } )\n true\n > bool = isCollection( {} )\n false\n\n See Also\n --------\n isArrayLike, isArrayLikeObject\n","isComplex":"\nisComplex( value )\n Tests if a value is a 64-bit or 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit or 128-bit complex\n number.\n\n Examples\n --------\n > var bool = isComplex( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex( 3.14 )\n false\n > bool = isComplex( {} )\n false\n\n See Also\n --------\n isComplex64, isComplex128\n","isComplex64":"\nisComplex64( value )\n Tests if a value is a 64-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit complex number.\n\n Examples\n --------\n > var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex64( new Complex128( 3.0, 1.0 ) )\n false\n > bool = isComplex64( 3.14 )\n false\n > bool = isComplex64( {} )\n false\n\n See Also\n --------\n isComplex, isComplex128\n","isComplex64Array":"\nisComplex64Array( value )\n Tests if a value is a Complex64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex64Array.\n\n Examples\n --------\n > var bool = isComplex64Array( new Complex64Array( 10 ) )\n true\n > bool = isComplex64Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128Array, isComplexTypedArray\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64MatrixLike( M )\n true\n > bool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64MatrixLike( 3.14 )\n false\n > bool = isComplex64MatrixLike( {} )\n false\n\n See Also\n --------\n isComplex128MatrixLike, isndarrayLike, isMatrixLike\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value )\n Tests if a value is an ndarray-like object containing single-precision\n complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64ndarrayLike( M )\n true\n > bool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64ndarrayLike( 3.14 )\n false\n > bool = isComplex64ndarrayLike( {} )\n false\n\n See Also\n --------\n isComplex128ndarrayLike, isndarrayLike\n","isComplex64VectorLike":"\nisComplex64VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64VectorLike( M )\n true\n > bool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64VectorLike( 3.14 )\n false\n > bool = isComplex64VectorLike( {} )\n false\n\n See Also\n --------\n isComplex128VectorLike, isndarrayLike, isVectorLike\n","isComplex128":"\nisComplex128( value )\n Tests if a value is a 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 128-bit complex number.\n\n Examples\n --------\n > var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex128( new Complex64( 2.0, 2.0 ) )\n false\n > bool = isComplex128( 3.14 )\n false\n > bool = isComplex128( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64\n","isComplex128Array":"\nisComplex128Array( value )\n Tests if a value is a Complex128Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex128Array.\n\n Examples\n --------\n > var bool = isComplex128Array( new Complex128Array( 10 ) )\n true\n > bool = isComplex128Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex128, isComplex64Array, isComplexTypedArray\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128MatrixLike( M )\n true\n > bool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128MatrixLike( 3.14 )\n false\n > bool = isComplex128MatrixLike( {} )\n false\n\n See Also\n --------\n isComplex64MatrixLike, isndarrayLike, isMatrixLike\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value )\n Tests if a value is an ndarray-like object containing double-precision\n complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128ndarrayLike( M )\n true\n > bool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128ndarrayLike( 3.14 )\n false\n > bool = isComplex128ndarrayLike( {} )\n false\n\n See Also\n --------\n isComplex64ndarrayLike, isndarrayLike\n","isComplex128VectorLike":"\nisComplex128VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128VectorLike( M )\n true\n > bool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128VectorLike( 3.14 )\n false\n > bool = isComplex128VectorLike( {} )\n false\n\n See Also\n --------\n isComplex64VectorLike, isndarrayLike, isVectorLike\n","isComplexLike":"\nisComplexLike( value )\n Tests if a value is a complex number-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a complex number-like object.\n\n Examples\n --------\n > var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplexLike( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplexLike( 3.14 )\n false\n > bool = isComplexLike( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128\n","isComplexTypedArray":"\nisComplexTypedArray( value )\n Tests if a value is a complex typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a complex typed array.\n\n Examples\n --------\n > var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n true\n\n See Also\n --------\n isComplex, isComplex64Array, isComplex128Array\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value )\n Tests if a value is complex-typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is complex-typed-array-like.\n\n Examples\n --------\n > var bool = isComplexTypedArrayLike( new Complex128Array() )\n true\n > bool = isComplexTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4,\n ... 'get': function get() {},\n ... 'set': function set() {}\n ... })\n true\n\n See Also\n --------\n isComplexLike, isComplexTypedArray, isComplex64Array, isComplex128Array\n","isComposite":"\nisComposite( value )\n Tests if a value is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a composite number.\n\n Examples\n --------\n > var bool = isComposite( 4.0 )\n true\n > bool = isComposite( new Number( 4.0 ) )\n true\n > bool = isComposite( 3.14 )\n false\n > bool = isComposite( -4.0 )\n false\n > bool = isComposite( null )\n false\n\n\nisComposite.isPrimitive( value )\n Tests if a value is a number primitive which is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n composite number.\n\n Examples\n --------\n > var bool = isComposite.isPrimitive( 4.0 )\n true\n > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n false\n\n\nisComposite.isObject( value )\n Tests if a value is a number object having a value which is a composite\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a composite number.\n\n Examples\n --------\n > var bool = isComposite.isObject( 4.0 )\n false\n > bool = isComposite.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isPrime\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value )\n Tests if a value is a number primitive which is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n composite number.\n\n Examples\n --------\n > var bool = isComposite.isPrimitive( 4.0 )\n true\n > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n false","isComposite.isObject":"\nisComposite.isObject( value )\n Tests if a value is a number object having a value which is a composite\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a composite number.\n\n Examples\n --------\n > var bool = isComposite.isObject( 4.0 )\n false\n > bool = isComposite.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isPrime","isConfigurableProperty":"\nisConfigurableProperty( value, property )\n Tests if an object's own property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurableProperty( obj, 'boop' )\n true\n > bool = isConfigurableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isReadableProperty, isWritableProperty\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurablePropertyIn( obj, 'boop' )\n true\n > bool = isConfigurablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isConstantcase":"\nisConstantcase( value )\n Tests if a value is a constantcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a constantcase string.\n\n Examples\n --------\n > var bool = isConstantcase( 'BEEP_BOOP' )\n true\n > bool = isConstantcase( 'BEEP and BOOP' )\n false\n\n See Also\n --------\n isString, isCamelcase","isCubeNumber":"\nisCubeNumber( value )\n Tests if a value is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber( 8.0 )\n true\n > bool = isCubeNumber( new Number( 8.0 ) )\n true\n > bool = isCubeNumber( 3.14 )\n false\n > bool = isCubeNumber( -5.0 )\n false\n > bool = isCubeNumber( null )\n false\n\n\nisCubeNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a cube\n number.\n\n Examples\n --------\n > var bool = isCubeNumber.isPrimitive( 8.0 )\n true\n > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n false\n\n\nisCubeNumber.isObject( value )\n Tests if a value is a number object having a value which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber.isObject( 8.0 )\n false\n > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a cube\n number.\n\n Examples\n --------\n > var bool = isCubeNumber.isPrimitive( 8.0 )\n true\n > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n false","isCubeNumber.isObject":"\nisCubeNumber.isObject( value )\n Tests if a value is a number object having a value which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber.isObject( 8.0 )\n false\n > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber","isCurrentYear":"\nisCurrentYear( value )\n Tests if a value is the current year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is the current year.\n\n Examples\n --------\n > var bool = isCurrentYear( new Date() )\n true\n > bool = isCurrentYear( currentYear() )\n true\n > bool = isCurrentYear( 2021 )\n false\n > bool = isCurrentYear( null )\n false\n\n","isDataProperty":"\nisDataProperty( value, property )\n Tests if an object's own property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has a data descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataProperty( obj, 'boop' )\n true\n > bool = isDataProperty( obj, 'beep' )\n false\n\n See Also\n --------\n hasOwnProp, isAccessorProperty, isDataPropertyIn\n","isDataPropertyIn":"\nisDataPropertyIn( value, property )\n Tests if an object's own or inherited property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has a data\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataPropertyIn( obj, 'boop' )\n true\n > bool = isDataPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n hasProp, isAccessorPropertyIn, isDataProperty\n","isDataView":"\nisDataView( value )\n Tests if a value is a DataView.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a DataView.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 10 );\n > var bool = isDataView( new DataView( buf ) )\n true\n > bool = isDataView( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isDateObject":"\nisDateObject( value )\n Tests if a value is a Date object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Date object.\n\n Examples\n --------\n > var bool = isDateObject( new Date() )\n true\n > bool = isDateObject( '2017-01-01' )\n false\n\n","isDateObjectArray":"\nisDateObjectArray( value )\n Tests if a value is an array-like object containing only Date objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if value is an array-like object containing only Date\n objects.\n\n Examples\n --------\n > var bool = isDateObjectArray( [ new Date(), new Date() ] )\n true\n > bool = isDateObjectArray( [ {}, {} ] )\n false\n > bool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\n false\n > bool = isDateObjectArray( [] )\n false\n\n See Also\n --------\n isDateObject\n","isDigitString":"\nisDigitString( str )\n Tests whether a string contains only numeric digits.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only numeric digits.\n\n Examples\n --------\n > var bool = isDigitString( '0123456789' )\n true\n > bool = isDigitString( 'abcdef' )\n false\n > bool = isDigitString( '0xff' )\n false\n > bool = isDigitString( '' )\n false\n\n See Also\n --------\n isHexString, isString\n","isDomainName":"\nisDomainName( value )\n Tests if a value is a domain name.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a domain name.\n\n Examples\n --------\n > var bool = isDomainName( 'example.com' )\n true\n > bool = isDomainName( 'foo@bar.com' )\n false\n","isDurationString":"\nisDurationString( value )\n Tests if a value is a duration string.\n\n The function validates that a value is a string. For all other types, the\n function returns `false`.\n\n A duration string is a string containing a sequence of time units. A time\n unit is a nonnegative integer followed by a unit identifier. The following\n unit identifiers are supported:\n\n - d: days.\n - h: hours.\n - m: minutes.\n - s: seconds.\n - ms: milliseconds.\n\n For example, the string `1m3s10ms` is a duration string containing three\n time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n The string `60m` is a duration string containing a single time unit: `60m`\n (60 minutes). Time units must be supplied in descending order of magnitude\n (i.e., days, hours, minutes, seconds, milliseconds).\n\n Duration strings are case insensitive. For example, the string `1M3S10MS` is\n equivalent to `1m3s10ms`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a duration string.\n\n Examples\n --------\n > var bool = isDurationString( '1d' )\n true\n > bool = isDurationString( '1h' )\n true\n > bool = isDurationString( 'beep' )\n false\n","isEmailAddress":"\nisEmailAddress( value )\n Tests if a value is an email address.\n\n Validation is not rigorous. *9* RFCs relate to email addresses, and\n accounting for all of them is a fool's errand. The function performs the\n simplest validation; i.e., requiring at least one `@` symbol.\n\n For rigorous validation, send a confirmation email. If the email bounces,\n consider the email invalid.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an email address.\n\n Examples\n --------\n > var bool = isEmailAddress( 'beep@boop.com' )\n true\n > bool = isEmailAddress( 'beep' )\n false\n > bool = isEmailAddress( null )\n false\n\n","isEmptyArray":"\nisEmptyArray( value )\n Tests if a value is an empty array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty array.\n\n Examples\n --------\n > var bool = isEmptyArray( [] )\n true\n > bool = isEmptyArray( [ 1, 2, 3 ] )\n false\n > bool = isEmptyArray( {} )\n false\n\n See Also\n --------\n isArray, isEmptyArrayLikeObject, isEmptyCollection\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value )\n Tests if a value is an empty array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an empty array-like object.\n\n Examples\n --------\n > var bool = isEmptyArrayLikeObject( [] )\n true\n > bool = isEmptyArrayLikeObject( { 'length': 0 } )\n true\n > bool = isEmptyArrayLikeObject( '' )\n false\n\n See Also\n --------\n isArrayLikeObject, isEmptyArray, isEmptyCollection\n","isEmptyCollection":"\nisEmptyCollection( value )\n Tests if a value is an empty collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty collection.\n\n Examples\n --------\n > var bool = isEmptyCollection( [] )\n true\n > bool = isEmptyCollection( { 'length': 0 } )\n true\n > bool = isEmptyCollection( [ 1, 2, 3 ] )\n false\n > bool = isEmptyCollection( {} )\n false\n\n See Also\n --------\n isCollection, isEmptyArray, isEmptyArrayLikeObject\n","isEmptyObject":"\nisEmptyObject( value )\n Tests if a value is an empty object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty object.\n\n Examples\n --------\n > var bool = isEmptyObject( {} )\n true\n > bool = isEmptyObject( { 'beep': 'boop' } )\n false\n > bool = isEmptyObject( [] )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isEmptyString":"\nisEmptyString( value )\n Tests if a value is an empty string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty string.\n\n Examples\n --------\n > var bool = isEmptyString( '' )\n true\n > bool = isEmptyString( new String( '' ) )\n true\n > bool = isEmptyString( 'beep' )\n false\n > bool = isEmptyString( [] )\n false\n\n\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false\n\n\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false","isEmptyString.isObject":"\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString","isEnumerableProperty":"\nisEnumerableProperty( value, property )\n Tests if an object's own property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is enumerable.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isEnumerableProperty( beep, 'boop' )\n true\n > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isEnumerablePropertyIn( obj, 'boop' )\n true\n > bool = isEnumerablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isEqualArray":"\nisEqualArray( v1, v2 )\n Tests if two arguments are both generic arrays and have equal values.\n\n The function performs strict equality comparison; thus, the function treats\n `-0` and `+0` as equal and `NaNs` as distinct.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are equal.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isEqualArray( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isEqualArray( x, y )\n false\n\n See Also\n --------\n isArray, isSameArray\n","isEqualDateObject":"\nisEqualDateObject( d1, d2 )\n Tests if two values are both Date objects corresponding to the same date\n and time.\n\n Parameters\n ----------\n d1: any\n First input value.\n d2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether both values are Date objects corresponding to\n the same date and time.\n\n Examples\n --------\n > var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > var d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > var bool = isEqualDateObject( d1, d2 )\n true\n > d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > d2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\n > bool = isEqualDateObject( d1, d2 )\n false\n\n See Also\n --------\n isDateObject, isSameValue\n","isError":"\nisError( value )\n Tests if a value is an Error object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Error object.\n\n Examples\n --------\n > var bool = isError( new Error( 'beep' ) )\n true\n > bool = isError( {} )\n false\n\n","isEvalError":"\nisEvalError( value )\n Tests if a value is an EvalError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided an EvalError (or a descendant) object,\n false positives may occur due to the fact that the EvalError constructor\n inherits from Error and has no internal class of its own. Hence, EvalError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an EvalError object.\n\n Examples\n --------\n > var bool = isEvalError( new EvalError( 'beep' ) )\n true\n > bool = isEvalError( {} )\n false\n\n See Also\n --------\n isError\n","isEven":"\nisEven( value )\n Tests if a value is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an even number.\n\n Examples\n --------\n > var bool = isEven( 4.0 )\n true\n > bool = isEven( new Number( 4.0 ) )\n true\n > bool = isEven( 3.0 )\n false\n > bool = isEven( -3.14 )\n false\n > bool = isEven( null )\n false\n\n\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false\n\n\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd\n","isEven.isPrimitive":"\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false","isEven.isObject":"\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd","isFalsy":"\nisFalsy( value )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is falsy.\n\n Examples\n --------\n > var bool = isFalsy( false )\n true\n > bool = isFalsy( '' )\n true\n > bool = isFalsy( 0 )\n true\n > bool = isFalsy( null )\n true\n > bool = isFalsy( void 0 )\n true\n > bool = isFalsy( NaN )\n true\n > bool = isFalsy( {} )\n false\n > bool = isFalsy( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isFalsyArray":"\nisFalsyArray( value )\n Tests if a value is an array-like object containing only falsy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only falsy values.\n\n Examples\n --------\n > var bool = isFalsyArray( [ null, '' ] )\n true\n > bool = isFalsyArray( [ {}, [] ] )\n false\n > bool = isFalsyArray( [] )\n false\n\n See Also\n --------\n isFalsy, isTruthyArray\n","isFinite":"\nisFinite( value )\n Tests if a value is a finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite number.\n\n Examples\n --------\n > var bool = isFinite( 5.0 )\n true\n > bool = isFinite( new Number( 5.0 ) )\n true\n > bool = isFinite( 1.0/0.0 )\n false\n > bool = isFinite( null )\n false\n\n\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false","isFinite.isObject":"\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite","isFiniteArray":"\nisFiniteArray( value )\n Tests if a value is an array-like object of finite numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of finite\n numbers.\n\n Examples\n --------\n > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n false\n\n\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isFiniteArray.objects":"\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite","isFloat32Array":"\nisFloat32Array( value )\n Tests if a value is a Float32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float32Array.\n\n Examples\n --------\n > var bool = isFloat32Array( new Float32Array( 10 ) )\n true\n > bool = isFloat32Array( [] )\n false\n\n See Also\n --------\n isFloat64Array\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32MatrixLike( M )\n true\n > bool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32MatrixLike( 3.14 )\n false\n > bool = isFloat32MatrixLike( {} )\n false\n\n See Also\n --------\n isFloat64MatrixLike, isndarrayLike, isMatrixLike\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value )\n Tests if a value is an ndarray-like object containing single-precision\n floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32ndarrayLike( M )\n true\n > bool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32ndarrayLike( 3.14 )\n false\n > bool = isFloat32ndarrayLike( {} )\n false\n\n See Also\n --------\n isFloat64ndarrayLike, isndarrayLike\n","isFloat32VectorLike":"\nisFloat32VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32VectorLike( M )\n true\n > bool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32VectorLike( 3.14 )\n false\n > bool = isFloat32VectorLike( {} )\n false\n\n See Also\n --------\n isFloat64VectorLike, isndarrayLike, isVectorLike\n","isFloat64Array":"\nisFloat64Array( value )\n Tests if a value is a Float64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float64Array.\n\n Examples\n --------\n > var bool = isFloat64Array( new Float64Array( 10 ) )\n true\n > bool = isFloat64Array( [] )\n false\n\n See Also\n --------\n isFloat32Array\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64MatrixLike( M )\n true\n > bool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64MatrixLike( 3.14 )\n false\n > bool = isFloat64MatrixLike( {} )\n false\n\n See Also\n --------\n isFloat32MatrixLike, isndarrayLike, isMatrixLike\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value )\n Tests if a value is an ndarray-like object containing double-precision\n floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64ndarrayLike( M )\n true\n > bool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64ndarrayLike( 3.14 )\n false\n > bool = isFloat64ndarrayLike( {} )\n false\n\n See Also\n --------\n isFloat32ndarrayLike, isndarrayLike\n","isFloat64VectorLike":"\nisFloat64VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64VectorLike( M )\n true\n > bool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64VectorLike( 3.14 )\n false\n > bool = isFloat64VectorLike( {} )\n false\n\n See Also\n --------\n isFloat32VectorLike, isndarrayLike, isVectorLike\n","isFunction":"\nisFunction( value )\n Tests if a value is a function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isFunction( beep )\n true\n > bool = isFunction( {} )\n false\n\n","isFunctionArray":"\nisFunctionArray( value )\n Tests if a value is an array-like object containing only functions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n functions.\n\n Examples\n --------\n > function beep() {};\n > function boop() {};\n > var bool = isFunctionArray( [ beep, boop ] )\n true\n > bool = isFunctionArray( [ {}, beep ] )\n false\n > bool = isFunctionArray( [] )\n false\n\n See Also\n --------\n isArray\n","isGeneratorObject":"\nisGeneratorObject( value )\n Tests if a value is a generator object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a generator object.\n\n Examples\n --------\n > function* generateID() {\n ... var idx = 0;\n ... while ( idx < idx+1 ) {\n ... yield idx;\n ... idx += 1;\n ... }\n ... };\n > var bool = isGeneratorObject( generateID() )\n true\n > bool = isGeneratorObject( generateID )\n false\n > bool = isGeneratorObject( {} )\n false\n > bool = isGeneratorObject( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObjectLike\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value )\n Tests if a value is generator object-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is generator object-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {},\n ... 'return': function noop() {},\n ... 'throw': function noop() {}\n ... };\n > var bool = isGeneratorObjectLike( obj )\n true\n > bool = isGeneratorObjectLike( {} )\n false\n > bool = isGeneratorObjectLike( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObject\n","isgzipBuffer":"\nisgzipBuffer( value )\n Tests if a value is a gzip buffer.\n\n A gzip buffer is defined as either a Node.js Buffer or Uint8Array which\n contains a 10-byte header, a body containing the compressed payload, and an\n 8-byte footer containing a CRC-32 checksum and the length of the original\n uncompressed data, modulo 2^32.\n\n This function only examines the 10-byte header to ensure the header includes\n the expected magic number and compression method. The function does not\n perform an integrity check.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a gzip buffer.\n\n Examples\n --------\n > var buf = new Uint8Array( 20 );\n > buf[ 0 ] = 31; // 0x1f => magic number\n > buf[ 1 ] = 139; // 0x8b\n > buf[ 2 ] = 8; // 0x08 => compression method\n > var bool = isgzipBuffer( buf )\n true\n > bool = isgzipBuffer( [] )\n false\n\n See Also\n --------\n isBuffer, isUint8Array\n","isHexString":"\nisHexString( str )\n Tests whether a string contains only hexadecimal digits.\n\n The function does not recognize `x` (as in the standard `0x` prefix).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only hexadecimal digits.\n\n Examples\n --------\n > var bool = isHexString( '0123456789abcdefABCDEF' )\n true\n > bool = isHexString( '0xffffff' )\n false\n > bool = isHexString( 'x' )\n false\n > bool = isHexString( '' )\n false\n\n See Also\n --------\n isString\n","isInfinite":"\nisInfinite( value )\n Tests if a value is an infinite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an infinite number.\n\n Examples\n --------\n > var bool = isInfinite( 1.0/0.0 )\n true\n > bool = isInfinite( new Number( -1.0/0.0 ) )\n true\n > bool = isInfinite( 5.0 )\n false\n > bool = isInfinite( '1.0/0.0' )\n false\n\n\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false","isInfinite.isObject":"\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite","isInheritedProperty":"\nisInheritedProperty( value, property )\n Tests if an object has an inherited property.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has an inherited property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isInheritedProperty( beep, 'boop' )\n false\n > bool = isInheritedProperty( beep, 'toString' )\n true\n > bool = isInheritedProperty( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp, hasProp\n","isInt8Array":"\nisInt8Array( value )\n Tests if a value is an Int8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int8Array.\n\n Examples\n --------\n > var bool = isInt8Array( new Int8Array( 10 ) )\n true\n > bool = isInt8Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt32Array\n","isInt16Array":"\nisInt16Array( value )\n Tests if a value is an Int16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int16Array.\n\n Examples\n --------\n > var bool = isInt16Array( new Int16Array( 10 ) )\n true\n > bool = isInt16Array( [] )\n false\n\n See Also\n --------\n isInt32Array, isInt8Array\n","isInt32Array":"\nisInt32Array( value )\n Tests if a value is an Int32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int32Array.\n\n Examples\n --------\n > var bool = isInt32Array( new Int32Array( 10 ) )\n true\n > bool = isInt32Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt8Array\n","isInteger":"\nisInteger( value )\n Tests if a value is an integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an integer.\n\n Examples\n --------\n > var bool = isInteger( 5.0 )\n true\n > bool = isInteger( new Number( 5.0 ) )\n true\n > bool = isInteger( -3.14 )\n false\n > bool = isInteger( null )\n false\n\n\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false","isInteger.isObject":"\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber","isIntegerArray":"\nisIntegerArray( value )\n Tests if a value is an array-like object of integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of integer\n values.\n\n Examples\n --------\n > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isIntegerArray( [ -3.0, '3.0' ] )\n false\n\n\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isIntegerArray.objects":"\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isIterableLike":"\nisIterableLike( value )\n Tests if a value is iterable-like.\n\n In order to be iterable, an object must implement the @@iterator method,\n which, when called, returns an iterator protocol-compliant object.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n In environments lacking Symbol.iterator support, this function always\n returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterable-like.\n\n Examples\n --------\n > var bool = isIterableLike( [ 1, 2, 3 ] )\n \n > bool = isIterableLike( {} )\n false\n > bool = isIterableLike( null )\n false\n\n See Also\n --------\n isIteratorLike\n","isIteratorLike":"\nisIteratorLike( value )\n Tests if a value is iterator-like.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterator-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {}\n ... };\n > var bool = isIteratorLike( obj )\n true\n > bool = isIteratorLike( {} )\n false\n > bool = isIteratorLike( null )\n false\n\n See Also\n --------\n isIterableLike\n","isJSON":"\nisJSON( value )\n Tests if a value is a parseable JSON string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a parseable JSON string.\n\n Examples\n --------\n > var bool = isJSON( '{\"a\":5}' )\n true\n > bool = isJSON( '{a\":5}' )\n false\n\n","isKebabcase":"\nisKebabcase( value )\n Tests if a value is a string in kebab case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in kebab case.\n\n Examples\n --------\n > var bool = isKebabcase( 'beep-boop' )\n true\n > bool = isKebabcase( 'BEEP_BOOP' )\n false\n\n See Also\n --------\n isString","isLeapYear":"\nisLeapYear( value )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n A leap year is defined as any year which is exactly divisible by 4, except\n for years which are exactly divisible by 100 and not by 400. In this\n definition, 100 corresponds to years marking a new century, and 400\n corresponds to the length of the *leap cycle*.\n\n If not provided any arguments, the function returns a boolean indicating\n if the current year (according to local time) is a leap year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value corresponds to a leap year.\n\n Examples\n --------\n > var bool = isLeapYear( new Date() )\n \n > bool = isLeapYear( 1996 )\n true\n > bool = isLeapYear( 2001 )\n false\n\n","isLocalhost":"\nisLocalhost( value )\n Tests whether a value is a localhost hostname.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a localhost hostname.\n\n Examples\n --------\n > var bool = isLocalhost( 'localhost' )\n true\n > bool = isLocalhost( '127.0.0.1' )\n true\n > bool = isLocalhost( 'stdlib.io' )\n false\n","isLowercase":"\nisLowercase( value )\n Tests if a value is a lowercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a lowercase string.\n\n Examples\n --------\n > var bool = isLowercase( 'hello' )\n true\n > bool = isLowercase( 'World' )\n false\n\n See Also\n --------\n isString, isUppercase\n","isMatrixLike":"\nisMatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isMatrixLike( M )\n true\n > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isMatrixLike( 3.14 )\n false\n > bool = isMatrixLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isndarrayLike, isTypedArrayLike, isVectorLike\n","isMethod":"\nisMethod( value, property )\n Tests if an object has a specified method name.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n The function only searches own properties.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': function beep() { return 'beep'; } };\n > var bool = isMethod( beep, 'boop' )\n true\n > bool = isMethod( beep, 'toString' )\n false\n\n See Also\n --------\n hasOwnProp, isFunction, isMethodIn\n","isMethodIn":"\nisMethodIn( value, property )\n Tests if an object has a specified method name, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isMethodIn( beep, 'toString' )\n true\n > bool = isMethodIn( beep, 'boop' )\n false\n > bool = isMethodIn( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp, isFunction, isMethod\n","isMultiSlice":"\nisMultiSlice( value )\n Tests if a value is a MultiSlice object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a MultiSlice object.\n\n Examples\n --------\n > var bool = isMultiSlice( new MultiSlice() )\n true\n > bool = isMultiSlice( 3.14 )\n false\n > bool = isMultiSlice( {} )\n false\n\n See Also\n --------\n isSlice, MultiSlice\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value )\n Tests if a value is named typed tuple-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is named typed tuple-like.\n\n Examples\n --------\n > var Point = namedtypedtuple( [ 'x', 'y' ] );\n > var p = new Point();\n > var bool = isNamedTypedTupleLike( p )\n true\n > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isNamedTypedTupleLike( 3.14 )\n false\n > bool = isNamedTypedTupleLike( {} )\n false\n\n See Also\n --------\n namedtypedtuple\n","isnan":"\nisnan( value )\n Tests if a value is NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is NaN.\n\n Examples\n --------\n > var bool = isnan( NaN )\n true\n > bool = isnan( new Number( NaN ) )\n true\n > bool = isnan( 3.14 )\n false\n > bool = isnan( null )\n false\n\n\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false\n\n\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber\n","isnan.isPrimitive":"\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false","isnan.isObject":"\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber","isNaNArray":"\nisNaNArray( value )\n Tests if a value is an array-like object containing only NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n NaN values.\n\n Examples\n --------\n > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n true\n > bool = isNaNArray( [ NaN, 2 ] )\n false\n\n\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true\n\n\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan\n","isNaNArray.primitives":"\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true","isNaNArray.objects":"\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan","isNativeFunction":"\nisNativeFunction( value )\n Tests if a value is a native function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a native function.\n\n Examples\n --------\n > var bool = isNativeFunction( Date )\n true\n > function beep() {};\n > bool = isNativeFunction( beep )\n false\n > bool = isNativeFunction( {} )\n false\n\n See Also\n --------\n isFunction\n","isndarrayLike":"\nisndarrayLike( value )\n Tests if a value is ndarray-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is ndarray-like.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLike( M )\n true\n > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isndarrayLike( 3.14 )\n false\n > bool = isndarrayLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isTypedArrayLike, isVectorLike\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value, dtype )\n Tests if a value is an ndarray-like object having a specified data type.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n dtype: any\n Data type value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object having a\n specified data type.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLikeWithDataType( M, 'generic' )\n true\n > bool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\n false\n > bool = isndarrayLikeWithDataType( 3.14, 'generic' )\n false\n > bool = isndarrayLikeWithDataType( {}, 'generic' )\n false\n\n See Also\n --------\n isndarrayLike\n","isNegativeFinite":"\nisNegativeFinite( value )\n Tests if a value is a finite negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite negative number.\n\n Examples\n --------\n > var bool = isNegativeFinite( -5.0 )\n true\n > bool = isNegativeFinite( new Number( -5.0 ) )\n true\n > bool = isNegativeFinite( -3.14 )\n true\n > bool = isNegativeFinite( 5.0 )\n false\n > bool = isNegativeFinite( null )\n false\n > bool = isNegativeFinite( -1.0/0.0 )\n false\n > bool = isNegativeFinite( new Number( -1.0/0.0 ) )\n false\n\n\nisNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isPrimitive( -3.0 )\n true\n > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n false\n > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisNegativeFinite.isObject( value )\n Tests if a value is a number object having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isObject( -3.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n true\n > bool = isNegativeFinite.isObject( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n false\n\n See Also\n --------\n isFinite, isNegativeNumber, isPositiveFinite\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isPrimitive( -3.0 )\n true\n > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n false\n > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n false","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value )\n Tests if a value is a number object having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isObject( -3.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n true\n > bool = isNegativeFinite.isObject( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n false\n\n See Also\n --------\n isFinite, isNegativeNumber, isPositiveFinite","isNegativeInteger":"\nisNegativeInteger( value )\n Tests if a value is a negative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative integer.\n\n Examples\n --------\n > var bool = isNegativeInteger( -5.0 )\n true\n > bool = isNegativeInteger( new Number( -5.0 ) )\n true\n > bool = isNegativeInteger( 5.0 )\n false\n > bool = isNegativeInteger( -3.14 )\n false\n > bool = isNegativeInteger( null )\n false\n\n\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isNegativeIntegerArray":"\nisNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only negative integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative integers.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNegativeNumber":"\nisNegativeNumber( value )\n Tests if a value is a negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative number.\n\n Examples\n --------\n > var bool = isNegativeNumber( -5.0 )\n true\n > bool = isNegativeNumber( new Number( -5.0 ) )\n true\n > bool = isNegativeNumber( -3.14 )\n true\n > bool = isNegativeNumber( 5.0 )\n false\n > bool = isNegativeNumber( null )\n false\n\n\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber","isNegativeNumberArray":"\nisNegativeNumberArray( value )\n Tests if a value is an array-like object containing only negative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNegativeZero":"\nisNegativeZero( value )\n Tests if a value is negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero( -0.0 )\n true\n > bool = isNegativeZero( new Number( -0.0 ) )\n true\n > bool = isNegativeZero( -3.14 )\n false\n > bool = isNegativeZero( 0.0 )\n false\n > bool = isNegativeZero( null )\n false\n\n\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false\n\n\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false","isNegativeZero.isObject":"\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero","isNodeBuiltin":"\nisNodeBuiltin( str )\n Tests whether a string matches a Node.js built-in module name.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string matches a Node.js built-in module\n name.\n\n Examples\n --------\n > var bool = isNodeBuiltin( 'cluster' )\n true\n > bool = isNodeBuiltin( 'crypto' )\n true\n > bool = isNodeBuiltin( 'fs-extra' )\n false\n > bool = isNodeBuiltin( '' )\n false\n\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value )\n Tests if a value is Node duplex stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node duplex stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Duplex;\n > s = new Stream();\n > var bool = isNodeDuplexStreamLike( s )\n true\n > bool = isNodeDuplexStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value )\n Tests if a value is Node readable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node readable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Readable;\n > s = new Stream();\n > var bool = isNodeReadableStreamLike( s )\n true\n > bool = isNodeReadableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if running in a Node.js REPL environment.\n\n Examples\n --------\n > var bool = isNodeREPL()\n \n\n","isNodeStreamLike":"\nisNodeStreamLike( value )\n Tests if a value is Node stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Stream;\n > s = new Stream();\n > var bool = isNodeStreamLike( s )\n true\n > bool = isNodeStreamLike( {} )\n false\n\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value )\n Tests if a value is Node transform stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node transform stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Transform;\n > s = new Stream();\n > var bool = isNodeTransformStreamLike( s )\n true\n > bool = isNodeTransformStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value )\n Tests if a value is Node writable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node writable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Writable;\n > s = new Stream();\n > var bool = isNodeWritableStreamLike( s )\n true\n > bool = isNodeWritableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value, property )\n Tests if an object's own property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurableProperty( obj, 'boop' )\n false\n > bool = isNonConfigurableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n false\n > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value, property )\n Tests if an object's own property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerableProperty( obj, 'boop' )\n false\n > bool = isNonEnumerableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadableProperty, isWritableProperty\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n false\n > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadablePropertyIn, isWritablePropertyIn\n","isNonNegativeFinite":"\nisNonNegativeFinite( value )\n Tests if a value is a nonnegative finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative finite number.\n\n Examples\n --------\n > var bool = isNonNegativeFinite( 5.0 )\n true\n > bool = isNonNegativeFinite( new Number( 5.0 ) )\n true\n > bool = isNonNegativeFinite( 3.14 )\n true\n > bool = isNonNegativeFinite( -5.0 )\n false\n > bool = isNonNegativeFinite( null )\n false\n > bool = isNonNegativeFinite( PINF )\n false\n\n\nisNonNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeFinite.isObject( value )\n Tests if a value is a number object having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a \n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isObject( 3.0 )\n false\n > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonNegativeNumber, isNumber\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value )\n Tests if a value is a number object having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a \n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isObject( 3.0 )\n false\n > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonNegativeNumber, isNumber","isNonNegativeInteger":"\nisNonNegativeInteger( value )\n Tests if a value is a nonnegative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative integer.\n\n Examples\n --------\n > var bool = isNonNegativeInteger( 5.0 )\n true\n > bool = isNonNegativeInteger( new Number( 5.0 ) )\n true\n > bool = isNonNegativeInteger( 3.14 )\n false\n > bool = isNonNegativeInteger( -5.0 )\n false\n > bool = isNonNegativeInteger( null )\n false\n\n\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNonNegativeNumber, isNumber\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNonNegativeNumber, isNumber","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative integers.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonNegativeNumber":"\nisNonNegativeNumber( value )\n Tests if a value is a nonnegative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative number.\n\n Examples\n --------\n > var bool = isNonNegativeNumber( 5.0 )\n true\n > bool = isNonNegativeNumber( new Number( 5.0 ) )\n true\n > bool = isNonNegativeNumber( 3.14 )\n true\n > bool = isNonNegativeNumber( -5.0 )\n false\n > bool = isNonNegativeNumber( null )\n false\n\n\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNonNegativeFinite, isNonNegativeInteger, isNumber\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNonNegativeFinite, isNonNegativeInteger, isNumber","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonPositiveFinite":"\nisNonPositiveFinite( value )\n Tests if a value is a nonpositive finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive finite number.\n\n Examples\n --------\n > var bool = isNonPositiveFinite( -5.0 )\n true\n > bool = isNonPositiveFinite( new Number( -5.0 ) )\n true\n > bool = isNonPositiveFinite( -3.14 )\n true\n > bool = isNonPositiveFinite( 5.0 )\n false\n > bool = isNonPositiveFinite( null )\n false\n\n\nisNonPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveFinite.isObject( value )\n Tests if a value is a number object having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isObject( -3.0 )\n false\n > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonPositiveNumber\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value )\n Tests if a value is a number object having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isObject( -3.0 )\n false\n > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonPositiveNumber","isNonPositiveInteger":"\nisNonPositiveInteger( value )\n Tests if a value is a nonpositive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive integer.\n\n Examples\n --------\n > var bool = isNonPositiveInteger( -5.0 )\n true\n > bool = isNonPositiveInteger( new Number( -5.0 ) )\n true\n > bool = isNonPositiveInteger( 5.0 )\n false\n > bool = isNonPositiveInteger( -3.14 )\n false\n > bool = isNonPositiveInteger( null )\n false\n\n\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive integers.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonPositiveNumber":"\nisNonPositiveNumber( value )\n Tests if a value is a nonpositive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive number.\n\n Examples\n --------\n > var bool = isNonPositiveNumber( -5.0 )\n true\n > bool = isNonPositiveNumber( new Number( -5.0 ) )\n true\n > bool = isNonPositiveNumber( -3.14 )\n true\n > bool = isNonPositiveNumber( 5.0 )\n false\n > bool = isNonPositiveNumber( null )\n false\n\n\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value )\n Tests if a value is a non-symmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a non-symmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 2, 3, 4 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isNonSymmetricMatrix( M )\n true\n > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isNonSymmetricMatrix( 3.14 )\n false\n > bool = isNonSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isNull":"\nisNull( value )\n Tests if a value is null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is null.\n\n Examples\n --------\n > var bool = isNull( null )\n true\n > bool = isNull( true )\n false\n\n See Also\n --------\n isUndefined, isUndefinedOrNull\n","isNullArray":"\nisNullArray( value )\n Tests if a value is an array-like object containing only null values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n null values.\n\n Examples\n --------\n > var bool = isNullArray( [ null, null, null ] )\n true\n > bool = isNullArray( [ NaN, 2, null ] )\n false\n\n See Also\n --------\n isArray, isNull\n","isNumber":"\nisNumber( value )\n Tests if a value is a number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number.\n\n Examples\n --------\n > var bool = isNumber( 3.14 )\n true\n > bool = isNumber( new Number( 3.14 ) )\n true\n > bool = isNumber( NaN )\n true\n > bool = isNumber( null )\n false\n\n\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false\n\n\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true\n\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false","isNumber.isObject":"\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true","isNumberArray":"\nisNumberArray( value )\n Tests if a value is an array-like object containing only numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n numbers.\n\n Examples\n --------\n > var bool = isNumberArray( [ 1, 2, 3 ] )\n true\n > bool = isNumberArray( [ '1', 2, 3 ] )\n false\n\n\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false\n\n\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray\n","isNumberArray.primitives":"\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false","isNumberArray.objects":"\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray","isNumericArray":"\nisNumericArray( value )\n Tests if a value is a numeric array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a numeric array.\n\n Examples\n --------\n > var bool = isNumericArray( new Int8Array( 10 ) )\n true\n > bool = isNumericArray( [ 1, 2, 3 ] )\n true\n > bool = isNumericArray( [ '1', '2', '3' ] )\n false\n\n See Also\n --------\n isArray, isNumberArray, isTypedArray\n\n","isObject":"\nisObject( value )\n Tests if a value is an object; e.g., `{}`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an object.\n\n Examples\n --------\n > var bool = isObject( {} )\n true\n > bool = isObject( true )\n false\n\n See Also\n --------\n isObjectLike, isPlainObject\n","isObjectArray":"\nisObjectArray( value )\n Tests if a value is an array-like object containing only objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n objects.\n\n Examples\n --------\n > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n true\n > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isObject\n","isObjectLike":"\nisObjectLike( value )\n Tests if a value is object-like.\n\n Return values are the same as would be obtained using the built-in `typeof`\n operator except that `null` is not considered an object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is object-like.\n\n Examples\n --------\n > var bool = isObjectLike( {} )\n true\n > bool = isObjectLike( [] )\n true\n > bool = isObjectLike( null )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isOdd":"\nisOdd( value )\n Tests if a value is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an odd number.\n\n Examples\n --------\n > var bool = isOdd( 5.0 )\n true\n > bool = isOdd( new Number( 5.0 ) )\n true\n > bool = isOdd( 4.0 )\n false\n > bool = isOdd( new Number( 4.0 ) )\n false\n > bool = isOdd( -3.14 )\n false\n > bool = isOdd( null )\n false\n\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false\n\n\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false","isOdd.isObject":"\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven","isoWeeksInYear":"\nisoWeeksInYear( [year] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n\n By default, the function returns the number of ISO weeks in the current year\n (according to local time). To determine the number of ISO weeks for a\n particular year, provide either a year or a `Date` object.\n\n Parameters\n ----------\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Number of ISO weeks in a year.\n\n Examples\n --------\n > var num = isoWeeksInYear()\n \n > num = isoWeeksInYear( 2015 )\n 53\n > num = isoWeeksInYear( 2017 )\n 52\n\n","isPascalcase":"\nisPascalcase( value )\n Tests if a value is a string in Pascal case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in Pascal case.\n\n Examples\n --------\n > var bool = isPascalcase( 'HelloWorld' )\n true\n > bool = isPascalcase( 'hello-world' )\n false\n\n See Also\n --------\n isString","isPersymmetricMatrix":"\nisPersymmetricMatrix( value )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a persymmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 2, 3, 1 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isPersymmetricMatrix( M )\n true\n > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isPersymmetricMatrix( 3.14 )\n false\n > bool = isPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isPlainObject":"\nisPlainObject( value )\n Tests if a value is a plain object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object.\n\n Examples\n --------\n > var bool = isPlainObject( {} )\n true\n > bool = isPlainObject( null )\n false\n\n See Also\n --------\n isObject\n","isPlainObjectArray":"\nisPlainObjectArray( value )\n Tests if a value is an array-like object containing only plain objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n plain objects.\n\n Examples\n --------\n > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n false\n > bool = isPlainObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPlainObject\n","isPositiveFinite":"\nisPositiveFinite( value )\n Tests if a value is a positive finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a positive finite number.\n\n Examples\n --------\n > var bool = isPositiveFinite( 5.0 )\n true\n > bool = isPositiveFinite( new Number( 5.0 ) )\n true\n > bool = isPositiveFinite( 3.14 )\n true\n > bool = isPositiveFinite( -5.0 )\n false\n > var bool = isPositiveFinite( 1.0/0.0 )\n false\n > bool = isPositiveFinite( new Number( 1.0/0.0 ) )\n false\n > bool = isPositiveFinite( null )\n false\n\n\nisPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a number primitive having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isPrimitive( 3.0 )\n true\n > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n false\n > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveFinite.isObject( value )\n Tests if a value is a number object having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isObject( 3.0 )\n false\n > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n true\n > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n false\n\n\n See Also\n --------\n isFinite, isPositiveNumber\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a number primitive having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isPrimitive( 3.0 )\n true\n > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n false\n > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n false","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value )\n Tests if a value is a number object having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isObject( 3.0 )\n false\n > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n true\n > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n false\n\n\n See Also\n --------\n isFinite, isPositiveNumber","isPositiveInteger":"\nisPositiveInteger( value )\n Tests if a value is a positive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive integer.\n\n Examples\n --------\n > var bool = isPositiveInteger( 5.0 )\n true\n > bool = isPositiveInteger( new Number( 5.0 ) )\n true\n > bool = isPositiveInteger( 3.14 )\n false\n > bool = isPositiveInteger( -5.0 )\n false\n > bool = isPositiveInteger( null )\n false\n\n\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isPositiveIntegerArray":"\nisPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only positive integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive integers.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger","isPositiveNumber":"\nisPositiveNumber( value )\n Tests if a value is a positive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive number.\n\n Examples\n --------\n > var bool = isPositiveNumber( 5.0 )\n true\n > bool = isPositiveNumber( new Number( 5.0 ) )\n true\n > bool = isPositiveNumber( 3.14 )\n true\n > bool = isPositiveNumber( -5.0 )\n false\n > bool = isPositiveNumber( null )\n false\n\n\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber","isPositiveNumberArray":"\nisPositiveNumberArray( value )\n Tests if a value is an array-like object containing only positive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive numbers.\n\n Examples\n --------\n > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber","isPositiveZero":"\nisPositiveZero( value )\n Tests if a value is positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero( 0.0 )\n true\n > bool = isPositiveZero( new Number( 0.0 ) )\n true\n > bool = isPositiveZero( -3.14 )\n false\n > bool = isPositiveZero( -0.0 )\n false\n > bool = isPositiveZero( null )\n false\n\n\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false\n\n\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false","isPositiveZero.isObject":"\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero","isPrime":"\nisPrime( value )\n Tests if a value is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a prime number.\n\n Examples\n --------\n > var bool = isPrime( 5.0 )\n true\n > bool = isPrime( new Number( 5.0 ) )\n true\n > bool = isPrime( 3.14 )\n false\n > bool = isPrime( -5.0 )\n false\n > bool = isPrime( null )\n false\n\n\nisPrime.isPrimitive( value )\n Tests if a value is a number primitive which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a prime\n number.\n\n Examples\n --------\n > var bool = isPrime.isPrimitive( 5.0 )\n true\n > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n false\n\n\nisPrime.isObject( value )\n Tests if a value is a number object having a value which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a prime number.\n\n Examples\n --------\n > var bool = isPrime.isObject( 5.0 )\n false\n > bool = isPrime.isObject( new Number( 5.0 ) )\n true\n\n\n See Also\n --------\n isComposite, isInteger, isNumber\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value )\n Tests if a value is a number primitive which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a prime\n number.\n\n Examples\n --------\n > var bool = isPrime.isPrimitive( 5.0 )\n true\n > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n false","isPrime.isObject":"\nisPrime.isObject( value )\n Tests if a value is a number object having a value which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a prime number.\n\n Examples\n --------\n > var bool = isPrime.isObject( 5.0 )\n false\n > bool = isPrime.isObject( new Number( 5.0 ) )\n true\n\n\n See Also\n --------\n isComposite, isInteger, isNumber","isPrimitive":"\nisPrimitive( value )\n Tests if a value is a JavaScript primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a JavaScript primitive.\n\n Examples\n --------\n > var bool = isPrimitive( true )\n true\n > bool = isPrimitive( {} )\n false\n\n See Also\n --------\n isBoxedPrimitive\n","isPrimitiveArray":"\nisPrimitiveArray( value )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n JavaScript primitives.\n\n Examples\n --------\n > var bool = isPrimitiveArray( [ '3', 2, null ] )\n true\n > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n false\n > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPrimitive\n","isPRNGLike":"\nisPRNGLike( value )\n Tests if a value is PRNG-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is PRNG-like.\n\n Examples\n --------\n > var bool = isPRNGLike( base.random.randu )\n true\n > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isPRNGLike( 3.14 )\n false\n > bool = isPRNGLike( {} )\n false\n\n","isProbability":"\nisProbability( value )\n Tests if a value is a probability.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a probability.\n\n Examples\n --------\n > var bool = isProbability( 0.5 )\n true\n > bool = isProbability( new Number( 0.5 ) )\n true\n > bool = isProbability( 3.14 )\n false\n > bool = isProbability( -5.0 )\n false\n > bool = isProbability( null )\n false\n\n\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false\n\n\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false","isProbability.isObject":"\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber","isProbabilityArray":"\nisProbabilityArray( value )\n Tests if a value is an array-like object containing only probabilities.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n true\n > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n false\n > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n false\n\n\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false\n\n\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false","isProbabilityArray.objects":"\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability","isPropertyKey":"\nisPropertyKey( value )\n Tests whether a value is a property key.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether value is a property key.\n\n Examples\n --------\n > var out = isPropertyKey( 'foo' )\n true\n > out = isPropertyKey( 1 )\n true\n > out = isPropertyKey( true )\n false\n\n See Also\n --------\n isString, isSymbol, isNonNegativeInteger, hasOwnProp, hasProp","isPrototypeOf":"\nisPrototypeOf( value, proto )\n Tests if an object's prototype chain contains a provided prototype.\n\n The function returns `false` if provided a primitive value.\n\n This function is generally more robust than the `instanceof` operator (e.g.,\n where inheritance is performed without using constructors).\n\n Parameters\n ----------\n value: any\n Input value.\n\n proto: Object|Function\n Prototype.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a provided prototype exists in a prototype chain.\n\n Examples\n --------\n > function Foo() { return this; };\n > function Bar() { return this; };\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var bool = isPrototypeOf( bar, Foo.prototype )\n true\n\n See Also\n --------\n getPrototypeOf\n","isRaggedNestedArray":"\nisRaggedNestedArray( value )\n Tests if a value is a ragged nested array. \n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a ragged nested array.\n\n Examples\n --------\n > var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\n true\n > bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n false\n > bool = isRaggedNestedArray( 'beep' )\n false\n\n","isRangeError":"\nisRangeError( value )\n Tests if a value is a RangeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a RangeError (or a descendant) object,\n false positives may occur due to the fact that the RangeError constructor\n inherits from Error and has no internal class of its own. Hence, RangeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a RangeError object.\n\n Examples\n --------\n > var bool = isRangeError( new RangeError( 'beep' ) )\n true\n > bool = isRangeError( {} )\n false\n\n See Also\n --------\n isError\n","isReadableProperty":"\nisReadableProperty( value, property )\n Tests if an object's own property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadableProperty( obj, 'boop' )\n true\n > bool = isReadableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isReadablePropertyIn, isWritableProperty\n","isReadablePropertyIn":"\nisReadablePropertyIn( value, property )\n Tests if an object's own or inherited property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadablePropertyIn( obj, 'boop' )\n true\n > bool = isReadablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isReadableProperty, isWritablePropertyIn\n","isReadOnlyProperty":"\nisReadOnlyProperty( value, property )\n Tests if an object's own property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is read-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyProperty( obj, 'boop' )\n true\n > bool = isReadOnlyProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadableProperty, isWritableProperty\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is read-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n true\n > bool = isReadOnlyPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isReadWriteProperty":"\nisReadWriteProperty( value, property )\n Tests if an object's own property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWriteProperty( obj, 'boop' )\n true\n > bool = isReadWriteProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadableProperty, isWritableProperty\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value, property )\n Tests if an object's own or inherited property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable\n and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWritePropertyIn( obj, 'boop' )\n true\n > bool = isReadWritePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadablePropertyIn, isWritablePropertyIn\n","isReferenceError":"\nisReferenceError( value )\n Tests if a value is a ReferenceError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a ReferenceError (or a descendant)\n object, false positives may occur due to the fact that the ReferenceError\n constructor inherits from Error and has no internal class of its own.\n Hence, ReferenceError impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a ReferenceError object.\n\n Examples\n --------\n > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n true\n > bool = isReferenceError( {} )\n false\n\n See Also\n --------\n isError\n","isRegExp":"\nisRegExp( value )\n Tests if a value is a regular expression.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression.\n\n Examples\n --------\n > var bool = isRegExp( /\\.+/ )\n true\n > bool = isRegExp( {} )\n false\n\n","isRegExpString":"\nisRegExpString( value )\n Tests if a value is a regular expression string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression string.\n\n Examples\n --------\n > var bool = isRegExpString( '/beep/' )\n true\n > bool = isRegExpString( 'beep' )\n false\n > bool = isRegExpString( '' )\n false\n > bool = isRegExpString( null )\n false\n\n See Also\n --------\n isRegExp\n","isRelativePath":"\nisRelativePath( value )\n Tests if a value is a relative path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a relative path.\n\n Examples\n --------\n // Windows environments:\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n\n // POSIX environments:\n > bool = isRelativePath( './foo/bar/baz' )\n true\n\n\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false\n\n\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath\n","isRelativePath.posix":"\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false","isRelativePath.win32":"\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath","isRelativeURI":"\nisRelativeURI( value )\n Tests whether a value is a relative URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is a relative URI.\n\n Examples\n --------\n > var bool = isRelativeURI( '/images/example.png' )\n true\n > bool = isRelativeURI( 'http://www.example.com' )\n false\n > bool = isRelativeURI( null )\n false\n\n See Also\n --------\n isURI","isSafeInteger":"\nisSafeInteger( value )\n Tests if a value is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a safe integer.\n\n Examples\n --------\n > var bool = isSafeInteger( 5.0 )\n true\n > bool = isSafeInteger( new Number( 5.0 ) )\n true\n > bool = isSafeInteger( 2.0e200 )\n false\n > bool = isSafeInteger( -3.14 )\n false\n > bool = isSafeInteger( null )\n false\n\n\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false","isSafeInteger.isObject":"\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber","isSafeIntegerArray":"\nisSafeIntegerArray( value )\n Tests if a value is an array-like object containing only safe integers.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing\n only safe integers.\n\n Examples\n --------\n > var arr = [ -3.0, new Number(0.0), 2.0 ];\n > var bool = isSafeIntegerArray( arr )\n true\n > arr = [ -3.0, '3.0' ];\n > bool = isSafeIntegerArray( arr )\n false\n\n\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false\n\n\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger","isSameArray":"\nisSameArray( v1, v2 )\n Tests if two arguments are both generic arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isSameArray( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isSameArray( x, y )\n true\n\n See Also\n --------\n isArray, isEqualArray, isSameArrayLike, isSameValue\n","isSameArrayLike":"\nisSameArrayLike( v1, v2 )\n Tests if two arguments are both array-like and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isSameArrayLike( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isSameArrayLike( x, y )\n true\n\n See Also\n --------\n isArrayLike, isSameArray, isSameValue\n","isSameComplex64":"\nisSameComplex64( v1, v2 )\n Tests if two arguments are both single-precision complex floating-point\n numbers and have the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex64( 1.0, 2.0 );\n > var y = new Complex64( 1.0, 2.0 );\n > var bool = isSameComplex64( x, y )\n true\n\n > x = new Complex64( NaN, NaN );\n > y = new Complex64( NaN, NaN );\n > bool = isSameComplex64( x, y )\n true\n\n See Also\n --------\n isComplex64, isSameComplex128, isSameValue\n","isSameComplex64Array":"\nisSameComplex64Array( v1, v2 )\n Tests if two arguments are both Complex64Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var bool = isSameComplex64Array( x, y )\n true\n\n > x = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n > y = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n > bool = isSameComplex64Array( x, y )\n true\n\n See Also\n --------\n isComplex64Array, isSameComplex128Array, isSameFloat32Array, isSameValue\n","isSameComplex128":"\nisSameComplex128( v1, v2 )\n Tests if two arguments are both double-precision complex floating-point\n numbers and have the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex128( 1.0, 2.0 );\n > var y = new Complex128( 1.0, 2.0 );\n > var bool = isSameComplex128( x, y )\n true\n\n > x = new Complex128( NaN, NaN );\n > y = new Complex128( NaN, NaN );\n > bool = isSameComplex128( x, y )\n true\n\n See Also\n --------\n isComplex128, isSameComplex64, isSameValue\n","isSameComplex128Array":"\nisSameComplex128Array( v1, v2 )\n Tests if two arguments are both Complex128Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var bool = isSameComplex128Array( x, y )\n true\n\n > x = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n > y = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n > bool = isSameComplex128Array( x, y )\n true\n\n See Also\n --------\n isComplex128Array, isSameComplex64Array, isSameFloat64Array, isSameValue\n","isSameFloat32Array":"\nisSameFloat32Array( v1, v2 )\n Tests if two arguments are both Float32Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > var bool = isSameFloat32Array( x, y )\n true\n\n > x = new Float32Array( [ NaN, NaN, NaN ] );\n > y = new Float32Array( [ NaN, NaN, NaN ] );\n > bool = isSameFloat32Array( x, y )\n true\n\n See Also\n --------\n isSameFloat64Array, isSameValue\n","isSameFloat64Array":"\nisSameFloat64Array( v1, v2 )\n Tests if two arguments are both Float64Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > var bool = isSameFloat64Array( x, y )\n true\n\n > x = new Float64Array( [ NaN, NaN, NaN ] );\n > y = new Float64Array( [ NaN, NaN, NaN ] );\n > bool = isSameFloat64Array( x, y )\n true\n\n See Also\n --------\n isSameFloat32Array, isSameValue\n","isSameNativeClass":"\nisSameNativeClass( a, b )\n Tests if two arguments have the same native class.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments have the same native class.\n\n Examples\n --------\n > var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\n true\n > bool = isSameNativeClass( 'beep', 'boop' )\n true\n > bool = isSameNativeClass( {}, [] )\n false\n\n See Also\n --------\n isSameType, isSameValue, isStrictEqual\n","isSameType":"\nisSameType( a, b )\n Tests if two arguments have the same type.\n\n The function uses the `typeof` operator to test for the same type.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments have the same type.\n\n Examples\n --------\n > var bool = isSameType( true, true )\n true\n > bool = isSameType( {}, [] )\n true\n > bool = isSameType( 3.12, -3.12 )\n true\n > bool = isSameType( 0.0, '0.0' )\n false\n\n See Also\n --------\n isSameNativeClass, isSameValue, isStrictEqual\n","isSameValue":"\nisSameValue( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValue( true, true )\n true\n > bool = isSameValue( {}, {} )\n false\n > bool = isSameValue( -0.0, -0.0 )\n true\n > bool = isSameValue( -0.0, 0.0 )\n false\n > bool = isSameValue( NaN, NaN )\n true\n\n See Also\n --------\n isSameValueZero, isStrictEqual\n","isSameValueZero":"\nisSameValueZero( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValueZero( true, true )\n true\n > bool = isSameValueZero( {}, {} )\n false\n > bool = isSameValueZero( -0.0, -0.0 )\n true\n > bool = isSameValueZero( -0.0, 0.0 )\n true\n > bool = isSameValueZero( NaN, NaN )\n true\n\n See Also\n --------\n isSameValue, isStrictEqual\n","isSemVer":"\nisSemVer( value )\n Tests if a value is a semantic version string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a provided value is a semantic version\n string.\n\n Examples\n --------\n > var bool = isSemVer( '1.0.0' )\n true\n > bool = isSemVer( '1.0.0-alpha.1' )\n true\n > bool = isSemVer( '0.1' )\n false\n > bool = isSemVer( null )\n false\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value )\n Tests if a value is a SharedArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SharedArrayBuffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffer...\n > var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\n true\n > bool = isSharedArrayBuffer( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value )\n Tests if a value is a skew-centrosymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n Examples\n --------\n > var buf = [ 2, 1, -1, -2 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewCentrosymmetricMatrix( M )\n true\n > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewCentrosymmetricMatrix( 3.14 )\n false\n > bool = isSkewCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isCentrosymmetricMatrix, isMatrixLike, isSkewSymmetricMatrix\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value )\n Tests if a value is a skew-persymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-persymmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 0, 0, -1 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewPersymmetricMatrix( M )\n true\n > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewPersymmetricMatrix( 3.14 )\n false\n > bool = isSkewPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isPersymmetricMatrix, isSkewSymmetricMatrix\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-symmetric matrix.\n\n Examples\n --------\n > var buf = [ 0, -1, 1, 0 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewSymmetricMatrix( M )\n true\n > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewSymmetricMatrix( 3.14 )\n false\n > bool = isSkewSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix\n","isSlice":"\nisSlice( value )\n Tests if a value is a Slice object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a Slice object.\n\n Examples\n --------\n > var bool = isSlice( new Slice( 10 ) )\n true\n > bool = isSlice( 3.14 )\n false\n > bool = isSlice( {} )\n false\n\n See Also\n --------\n isMultiSlice, Slice\n","isSnakecase":"\nisSnakecase( value )\n Tests if a value is a string in snake case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in snake case.\n\n Examples\n --------\n > var bool = isSnakecase( 'hello_world' )\n true\n > bool = isSnakecase( 'Hello World' )\n false\n\n See Also\n --------\n isString","isSquareMatrix":"\nisSquareMatrix( value )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object having equal dimensions.\n\n Examples\n --------\n > var buf = [ 0, 0, 0, 0 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSquareMatrix( M )\n true\n > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSquareMatrix( 3.14 )\n false\n > bool = isSquareMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSymmetricMatrix\n","isSquareNumber":"\nisSquareNumber( value )\n Tests if a value is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber( 4.0 )\n true\n > bool = isSquareNumber( new Number( 4.0 ) )\n true\n > bool = isSquareNumber( 3.14 )\n false\n > bool = isSquareNumber( -5.0 )\n false\n > bool = isSquareNumber( null )\n false\n\n\nisSquareNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isPrimitive( 4.0 )\n true\n > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n false\n\n\nisSquareNumber.isObject( value )\n Tests if a value is a number object having a value which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isObject( 4.0 )\n false\n > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isCubeNumber, isInteger, isNumber, isTriangularNumber\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isPrimitive( 4.0 )\n true\n > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n false","isSquareNumber.isObject":"\nisSquareNumber.isObject( value )\n Tests if a value is a number object having a value which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isObject( 4.0 )\n false\n > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isCubeNumber, isInteger, isNumber, isTriangularNumber","isSquareTriangularNumber":"\nisSquareTriangularNumber( value )\n Tests if a value is a square triangular number.\n\n Return values are not reliable for numbers greater than 1125899906842624.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber( 36.0 )\n true\n > bool = isSquareTriangularNumber( new Number( 36.0 ) )\n true\n > bool = isSquareTriangularNumber( 3.14 )\n false\n > bool = isSquareTriangularNumber( -5.0 )\n false\n > bool = isSquareTriangularNumber( null )\n false\n\n\nisSquareTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false\n\n\nisSquareTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a square\n triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isObject( 36.0 )\n false\n > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isTriangularNumber\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a square\n triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isObject( 36.0 )\n false\n > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isTriangularNumber","isStartcase":"\nisStartcase( value )\n Tests if a value is a startcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if value is a startcase string.\n\n Examples\n --------\n > var bool = isStartcase( 'Beep Boop' )\n true\n > bool = isStartcase( 'Beep and Boop' )\n false\n\n See Also\n --------\n isString","isStrictEqual":"\nisStrictEqual( a, b )\n Tests if two arguments are strictly equal.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are strictly equal.\n\n Examples\n --------\n > var bool = isStrictEqual( true, true )\n true\n > bool = isStrictEqual( {}, {} )\n false\n > bool = isStrictEqual( -0.0, -0.0 )\n true\n > bool = isStrictEqual( -0.0, 0.0 )\n false\n > bool = isStrictEqual( NaN, NaN )\n false\n\n See Also\n --------\n isSameValue\n","isString":"\nisString( value )\n Tests if a value is a string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string.\n\n Examples\n --------\n > var bool = isString( 'beep' )\n true\n > bool = isString( new String( 'beep' ) )\n true\n > bool = isString( 5 )\n false\n\n\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false\n\n\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false\n\n","isString.isPrimitive":"\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false","isString.isObject":"\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false","isStringArray":"\nisStringArray( value )\n Tests if a value is an array of strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of strings.\n\n Examples\n --------\n > var bool = isStringArray( [ 'abc', 'def' ] )\n true\n > bool = isStringArray( [ 'abc', 123 ] )\n false\n\n\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false\n\n\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString\n","isStringArray.primitives":"\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false","isStringArray.objects":"\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString","isStruct":"\nisStruct( value )\n Tests if a value is a `struct` instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a `struct` instance.\n\n Examples\n --------\n > var schema = [ { 'name': 'foo', 'type': 'float64' } ];\n > var S = structFactory( schema );\n > var bool = isStruct( new S() )\n true\n > bool = isStruct( [ 1, 2, 3, 4 ] )\n false\n > bool = isStruct( 3.14 )\n false\n > bool = isStruct( {} )\n false\n\n See Also\n --------\n isStructConstructorLike, structFactory\n","isStructConstructorLike":"\nisStructConstructorLike( value )\n Tests if a value is struct constructor-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is struct constructor-like.\n\n Examples\n --------\n > var schema = [ { 'name': 'foo', 'type': 'float64' } ];\n > var S = structFactory( schema );\n > var bool = isStructConstructorLike( S )\n true\n > bool = isStructConstructorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isStructConstructorLike( 3.14 )\n false\n > bool = isStructConstructorLike( {} )\n false\n\n See Also\n --------\n isStruct, structFactory\n","isSymbol":"\nisSymbol( value )\n Tests if a value is a symbol.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symbol.\n\n Examples\n --------\n > var bool = isSymbol( Symbol( 'beep' ) )\n true\n > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n true\n > bool = isSymbol( {} )\n false\n > bool = isSymbol( null )\n false\n > bool = isSymbol( true )\n false\n\n","isSymbolArray":"\nisSymbolArray( value )\n Tests if a value is an array-like object containing only symbols.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only symbols.\n\n Examples\n --------\n > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n true\n > bool = isSymbolArray( Symbol( 'beep' ) )\n false\n > bool = isSymbolArray( [] )\n false\n > bool = isSymbolArray( {} )\n false\n > bool = isSymbolArray( null )\n false\n > bool = isSymbolArray( true )\n false\n\n\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false\n\n\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false","isSymbolArray.objects":"\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol","isSymmetricMatrix":"\nisSymmetricMatrix( value )\n Tests if a value is a square matrix which equals its transpose.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symmetric matrix.\n\n Examples\n --------\n > var buf = [ 0, 1, 1, 2 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSymmetricMatrix( M )\n true\n > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSymmetricMatrix( 3.14 )\n false\n > bool = isSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isNonSymmetricMatrix, isSquareMatrix\n","isSyntaxError":"\nisSyntaxError( value )\n Tests if a value is a SyntaxError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a SyntaxError (or a descendant) object,\n false positives may occur due to the fact that the SyntaxError constructor\n inherits from Error and has no internal class of its own. Hence, SyntaxError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SyntaxError object.\n\n Examples\n --------\n > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n true\n > bool = isSyntaxError( {} )\n false\n\n See Also\n --------\n isError\n","isTriangularNumber":"\nisTriangularNumber( value )\n Tests if a value is a triangular number.\n\n Return values are not reliable for numbers greater than 1125899906842624.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber( 36.0 )\n true\n > bool = isTriangularNumber( new Number( 36.0 ) )\n true\n > bool = isTriangularNumber( 3.14 )\n false\n > bool = isTriangularNumber( -5.0 )\n false\n > bool = isTriangularNumber( null )\n false\n\n\nisTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false\n\n\nisTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a triangular\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isObject( 36.0 )\n false\n > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isSquareTriangularNumber\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a triangular\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isObject( 36.0 )\n false\n > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isSquareTriangularNumber","isTruthy":"\nisTruthy( value )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is truthy.\n\n Examples\n --------\n > var bool = isTruthy( true )\n true\n > bool = isTruthy( {} )\n true\n > bool = isTruthy( [] )\n true\n > bool = isTruthy( false )\n false\n > bool = isTruthy( '' )\n false\n > bool = isTruthy( 0 )\n false\n > bool = isTruthy( null )\n false\n > bool = isTruthy( void 0 )\n false\n > bool = isTruthy( NaN )\n false\n\n See Also\n --------\n isFalsy\n","isTruthyArray":"\nisTruthyArray( value )\n Tests if a value is an array-like object containing only truthy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only truthy values.\n\n Examples\n --------\n > var bool = isTruthyArray( [ {}, [] ] )\n true\n > bool = isTruthyArray( [ null, '' ] )\n false\n > bool = isTruthyArray( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isTypedArray":"\nisTypedArray( value )\n Tests if a value is a typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a typed array.\n\n Examples\n --------\n > var bool = isTypedArray( new Int8Array( 10 ) )\n true\n\n See Also\n --------\n isArray, isTypedArrayLike\n","isTypedArrayLength":"\nisTypedArrayLength( value )\n Tests if a value is a valid typed array length.\n\n A valid length property for a typed array instance is any integer value on\n the interval [0, 2^53-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a valid typed array length.\n\n Examples\n --------\n > var bool = isTypedArrayLength( 5 )\n true\n > bool = isTypedArrayLength( 2.0e200 )\n false\n > bool = isTypedArrayLength( -3.14 )\n false\n > bool = isTypedArrayLength( null )\n false\n\n See Also\n --------\n isArrayLength, isTypedArray\n","isTypedArrayLike":"\nisTypedArrayLike( value )\n Tests if a value is typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is typed-array-like.\n\n Examples\n --------\n > var bool = isTypedArrayLike( new Int16Array() )\n true\n > bool = isTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4\n ... })\n true\n\n See Also\n --------\n isTypedArray\n","isTypeError":"\nisTypeError( value )\n Tests if a value is a TypeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a TypeError (or a descendant) object,\n false positives may occur due to the fact that the TypeError constructor\n inherits from Error and has no internal class of its own. Hence, TypeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a TypeError object.\n\n Examples\n --------\n > var bool = isTypeError( new TypeError( 'beep' ) )\n true\n > bool = isTypeError( {} )\n false\n\n See Also\n --------\n isError\n","isUint8Array":"\nisUint8Array( value )\n Tests if a value is a Uint8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8Array.\n\n Examples\n --------\n > var bool = isUint8Array( new Uint8Array( 10 ) )\n true\n > bool = isUint8Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint32Array\n","isUint8ClampedArray":"\nisUint8ClampedArray( value )\n Tests if a value is a Uint8ClampedArray.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8ClampedArray.\n\n Examples\n --------\n > var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\n true\n > bool = isUint8ClampedArray( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint8Array\n","isUint16Array":"\nisUint16Array( value )\n Tests if a value is a Uint16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint16Array.\n\n Examples\n --------\n > var bool = isUint16Array( new Uint16Array( 10 ) )\n true\n > bool = isUint16Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint32Array, isUint8Array\n","isUint32Array":"\nisUint32Array( value )\n Tests if a value is a Uint32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint32Array.\n\n Examples\n --------\n > var bool = isUint32Array( new Uint32Array( 10 ) )\n true\n > bool = isUint32Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint8Array\n","isUNCPath":"\nisUNCPath( value )\n Tests if a value is a UNC path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a UNC path.\n\n Examples\n --------\n > var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isUNCPath( '/foo/bar/baz' )\n false\n\n","isUndefined":"\nisUndefined( value )\n Tests if a value is undefined.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined.\n\n Examples\n --------\n > var bool = isUndefined( void 0 )\n true\n > bool = isUndefined( null )\n false\n\n See Also\n --------\n isNull, isUndefinedOrNull\n","isUndefinedOrNull":"\nisUndefinedOrNull( value )\n Tests if a value is undefined or null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined or null.\n\n Examples\n --------\n > var bool = isUndefinedOrNull( void 0 )\n true\n > bool = isUndefinedOrNull( null )\n true\n > bool = isUndefinedOrNull( false )\n false\n\n See Also\n --------\n isNull, isUndefined\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value )\n Tests if a value is an array of probabilities that sum to one.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of probabilities that sum\n to one.\n\n Examples\n --------\n > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n true\n > bool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\n true\n > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n false\n > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n false\n\n See Also\n --------\n isProbability, isProbabilityArray\n","isUppercase":"\nisUppercase( value )\n Tests if a value is an uppercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an uppercase string.\n\n Examples\n --------\n > var bool = isUppercase( 'HELLO' )\n true\n > bool = isUppercase( 'World' )\n false\n\n See Also\n --------\n isLowercase, isString\n","isURI":"\nisURI( value )\n Tests if a value is a URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URI.\n\n Examples\n --------\n > var bool = isURI( 'http://google.com' )\n true\n > bool = isURI( 'http://localhost/' )\n true\n > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n true\n > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n true\n\n // No scheme:\n > bool = isURI( '' )\n false\n > bool = isURI( 'foo@bar' )\n false\n > bool = isURI( '://foo/' )\n false\n\n // Illegal characters:\n > bool = isURI( 'http://' )\n false\n\n // Invalid path:\n > bool = isURI( 'http:////foo.html' )\n false\n\n // Incomplete hex escapes:\n > bool = isURI( 'http://example.w3.org/%a' )\n false\n\n","isURIError":"\nisURIError( value )\n Tests if a value is a URIError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a URIError (or a descendant) object,\n false positives may occur due to the fact that the URIError constructor\n inherits from Error and has no internal class of its own. Hence, URIError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URIError object.\n\n Examples\n --------\n > var bool = isURIError( new URIError( 'beep' ) )\n true\n > bool = isURIError( {} )\n false\n\n See Also\n --------\n isError\n","isVectorLike":"\nisVectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isVectorLike( M )\n true\n > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isVectorLike( 3.14 )\n false\n > bool = isVectorLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isndarrayLike, isTypedArrayLike\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value )\n Tests if a value is a WebAssembly memory instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a WebAssembly memory instance.\n\n Examples\n --------\n > var bool = isWebAssemblyMemory( {} )\n false\n\n See Also\n --------\n hasWebAssemblySupport\n","isWellFormedString":"\nisWellFormedString( str )\n Tests if a string is well-formed.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is well-formed.\n\n Examples\n --------\n > var bool = isWellFormedString( '' )\n true\n\n > bool = isWellFormedString( new String( '' ) )\n true\n\n > bool = isWellFormedString( '\\uDBFF' )\n false\n\n > bool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\n false\n\n > bool = isWellFormedString( [] )\n false\n\n > bool = isWellFormedString( '-5' )\n true\n\n > bool = isWellFormedString( null )\n false\n\n\nisWellFormedString.isPrimitive( str )\n Tests if a string is a well-formed string primitive.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string primitive.\n\n Examples\n --------\n > var bool = isWellFormedString.isPrimitive( '' )\n true\n > bool = isWellFormedString.isPrimitive( new String( '' ) )\n false\n\n\nisWellFormedString.isObject( str )\n Tests if a string is a well-formed string object.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string object.\n\n Examples\n --------\n > var bool = isWellFormedString.isObject( '' )\n false\n > bool = isWellFormedString.isObject( new String( '' ) )\n true\n\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str )\n Tests if a string is a well-formed string primitive.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string primitive.\n\n Examples\n --------\n > var bool = isWellFormedString.isPrimitive( '' )\n true\n > bool = isWellFormedString.isPrimitive( new String( '' ) )\n false","isWellFormedString.isObject":"\nisWellFormedString.isObject( str )\n Tests if a string is a well-formed string object.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string object.\n\n Examples\n --------\n > var bool = isWellFormedString.isObject( '' )\n false\n > bool = isWellFormedString.isObject( new String( '' ) )\n true","isWhitespace":"\nisWhitespace( str )\n Tests whether a string contains only white space characters.\n\n A white space character is defined as one of the 25 characters defined as a\n white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n database, as well as one related white space character without the Unicode\n character property \"WSpace=Y\" (zero width non-breaking space which was\n deprecated as of Unicode 3.2).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only white space\n characters.\n\n Examples\n --------\n > var bool = isWhitespace( ' ' )\n true\n > bool = isWhitespace( 'abcdef' )\n false\n > bool = isWhitespace( '' )\n false\n\n See Also\n --------\n reWhitespace\n","isWritableProperty":"\nisWritableProperty( value, property )\n Tests if an object's own property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritableProperty( obj, 'boop' )\n true\n > bool = isWritableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadableProperty, isReadWriteProperty, isWritablePropertyIn, isWriteOnlyProperty\n","isWritablePropertyIn":"\nisWritablePropertyIn( value, property )\n Tests if an object's own or inherited property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritablePropertyIn( obj, 'boop' )\n true\n > bool = isWritablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadablePropertyIn, isReadWritePropertyIn, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value, property )\n Tests if an object's own property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is write-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyProperty( obj, 'boop' )\n false\n > bool = isWriteOnlyProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is write-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n false\n > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isWritablePropertyIn, isWriteOnlyProperty\n","iterAbs":"\niterAbs( iterator )\n Returns an iterator which iteratively computes the absolute value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAbs( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.abs, iterAbs2\n","iterAbs2":"\niterAbs2( iterator )\n Returns an iterator which iteratively computes the squared absolute value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAbs2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.abs2, iterAbs\n","iterAcos":"\niterAcos( iterator )\n Returns an iterator which iteratively computes the arccosine.\n\n The domain of arccosine is restricted to [-1,1]. If an iterated value is\n outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acos, iterAcosh, iterAsin, iterAtan\n","iterAcosh":"\niterAcosh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arccosine.\n\n The domain of the hyperbolic arccosine is restricted to [1,+infinity). If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acosh, iterAcos, iterAsinh, iterAtanh\n","iterAcot":"\niterAcot( iterator )\n Returns an iterator which iteratively computes the inverse cotangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acot, iterAcos, iterAcoth, iterAsin, iterAtan\n","iterAcoth":"\niterAcoth( iterator )\n Returns an iterator which iteratively computes the inverse hyperbolic\n cotangent.\n\n The domain of the inverse hyperbolic cotangent is restricted to (-inf,-1]\n and [1,inf). If an iterated value is outside of the domain, the returned\n iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acoth, iterAcosh, iterAcot, iterAsinh, iterAtanh\n","iterAcovercos":"\niterAcovercos( iterator )\n Returns an iterator which iteratively computes the inverse coversed cosine.\n\n The domain of inverse coversed cosine is restricted to [0,2]. If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcovercos( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acovercos, iterAcoversin, iterAvercos, iterCovercos, iterVercos\n","iterAcoversin":"\niterAcoversin( iterator )\n Returns an iterator which iteratively computes the inverse coversed sine.\n\n The domain of inverse coversed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acoversin, iterAcovercos, iterAversin, iterCoversin, iterVersin\n","iterAdd":"\niterAdd( iter0, ...iterator )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to add.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterAdd( it1, it2 );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide, iterMultiply, iterSubtract\n","iterAdvance":"\niterAdvance( iterator[, n] )\n Advances an entire iterator.\n\n The function *eagerly* advances an input iterator `n` iterations or until\n the input iterator finishes, whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Input iterator to advance.\n\n n: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Input iterator.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var it = iterAdvance( arr, 4 );\n > var v = it.next().value\n 1\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterHead, iterSlice\n","iterAhavercos":"\niterAhavercos( iterator )\n Returns an iterator which iteratively computes the inverse half-value versed\n cosine.\n\n The domain of inverse half-value versed cosine is restricted to [0,1]. If\n an iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ahavercos, iterAhaversin, iterHavercos, iterVercos\n","iterAhaversin":"\niterAhaversin( iterator )\n Returns an iterator which iteratively computes the inverse half-value versed\n sine.\n\n The domain of inverse half-value versed sine is restricted to [-2,0]. If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ahaversin, iterAhavercos, iterHaversin, iterVersin\n","iterAny":"\niterAny( iterator )\n Tests whether at least one iterated value is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a value is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterAny( arr )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNone, iterSome\n","iterAnyBy":"\niterAnyBy( iterator, predicate[, thisArg ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for any iterated value. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > function fcn( v ) { return ( v === 1 ); };\n > var bool = iterAnyBy( arr, fcn )\n true\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNoneBy, iterSomeBy\n","iterAsin":"\niterAsin( iterator )\n Returns an iterator which iteratively computes the arcsine.\n\n The domain of arcsine is restricted to [-1,1]. If an iterated value is\n outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.asin, iterAcos, iterAsinh, iterAtan\n","iterAsinh":"\niterAsinh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arcsine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.asinh, iterAcosh, iterAsin, iterAtanh\n","iterAtan":"\niterAtan( iterator )\n Returns an iterator which iteratively computes the arctangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atan, iterAcos, iterAsin, iterAtanh\n","iterAtan2":"\niterAtan2( y, x )\n Returns an iterator which iteratively computes the angle in the plane (in\n radians) between the positive x-axis and the ray from (0,0) to the point\n (x,y).\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n y: Object|number\n Input iterator.\n\n x: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( -2.0, 2.0 );\n > var y = random.iterators.uniform( -2.0, 2.0 );\n > var it = iterAtan2( y, x );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atan2, iterAtan\n","iterAtanh":"\niterAtanh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arctangent.\n\n The domain of hyperbolic arctangent is restricted to [-1,1]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atanh, iterAcosh, iterAsinh, iterAtan\n","iterator2array":"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n Creates (or fills) an array from an iterator.\n\n When invoked, an input function is provided two arguments:\n\n - value: iterated value.\n - index: iterated value index (zero-based).\n\n If provided an output array, the function fills the output array with\n iterated values.\n\n Iteration stops when an output array is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n out: ArrayLikeObject (optional)\n Output array-like object.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var opts = { 'iter': 10 };\n > var arr = iterator2array( random.iterators.randu( opts ) )\n\n See Also\n --------\n array2iterator, iterator2arrayview\n","iterator2arrayview":"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view with values returned from an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: destination index (zero-based).\n - n: iteration index (zero-based).\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayview( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iterator, iterator2arrayviewRight\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: destination index (zero-based).\n - n: iteration index (zero-based).\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iteratorRight, iterator2arrayview\n","iteratorStream":"\niteratorStream( iterator[, options] )\n Creates a readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n In binary mode, if an iterator generates `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n explicitly map `undefined` values to a different value by wrapping the\n provided iterator with another iterator.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream( it );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","iteratorStream.factory":"\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n\n See Also\n --------\n Symbol\n","iterAvercos":"\niterAvercos( iterator )\n Returns an iterator which iteratively computes the inverse versed cosine.\n\n The domain of inverse versed cosine is restricted to [-2,0]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.avercos, iterAversin, iterVersin\n","iterAversin":"\niterAversin( iterator )\n Returns an iterator which iteratively computes the inverse versed sine.\n\n The domain of inverse versed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.aversin, iterAvercos, iterVercos\n","iterawgn":"\niterawgn( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n drawn from a standard normal distribution. If provided, the `state` and\n `seed` options are ignored. In order to seed the returned iterator, one\n must seed the provided `prng` (assuming the provided `prng` is\n seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function|null\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawgn( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawln, iterawun\n","iterawln":"\niterawln( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawln( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawun\n","iterawun":"\niterawun( iterator, sigma[, options] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawun( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawln\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettPulse, iterHannPulse, iterPulse, iterTriangleWave\n","iterBartlettPulse":"\niterBartlettPulse( [options] )\n Returns an iterator which generates a Bartlett pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterTriangleWave\n","iterBesselj0":"\niterBesselj0( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBesselj0( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.besselj0, iterBesselj1, iterBessely0, iterBessely1\n","iterBesselj1":"\niterBesselj1( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order one.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBesselj1( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.besselj1, iterBesselj0, iterBessely0, iterBessely1\n","iterBessely0":"\niterBessely0( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBessely0( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.bessely0, iterBesselj0, iterBesselj1, iterBessely1\n","iterBessely1":"\niterBessely1( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order one.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBessely1( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.bessely1, iterBesselj0, iterBesselj1, iterBessely0\n","iterBeta":"\niterBeta( x, y )\n Returns an iterator which iteratively evaluates the beta function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n y: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( 0.0, 2.0 );\n > var it = iterBeta( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.beta, iterBetaln\n","iterBetaln":"\niterBetaln( x, y )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n beta function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n y: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( 0.0, 2.0 );\n > var it = iterBetaln( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.betaln, iterBeta\n","iterBinet":"\niterBinet( iterator )\n Returns an iterator which iteratively evaluates Binet's formula extended to\n real numbers.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBinet( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.binet\n","iterCbrt":"\niterCbrt( iterator )\n Returns an iterator which iteratively computes the cube root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCbrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cbrt, iterPow, iterSqrt\n","iterCeil":"\niterCeil( iterator )\n Returns an iterator which rounds each iterated value toward positive\n infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil, iterFloor, iterRound\n","iterCeil2":"\niterCeil2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward positive infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil2, iterCeil, iterCeil10, iterFloor2, iterRound2\n","iterCeil10":"\niterCeil10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward positive infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil10, iterCeil, iterCeil2, iterFloor10, iterRound10\n","iterCompositesSeq":"\niterCompositesSeq( [options] )\n Returns an iterator which generates a sequence of composite numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCompositesSeq();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n > v = it.next().value\n 8\n\n See Also\n --------\n iterIntegersSeq, iterPositiveIntegersSeq, iterPrimesSeq\n","iterConcat":"\niterConcat( iter0, ...iterator )\n Returns an iterator which iterates over the values of two or more iterators.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to concatenate.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = array2iterator( [ 3, 4 ] );\n > var it = iterConcat( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n","iterConstant":"\niterConstant( value[, options] )\n Returns an iterator which always returns the same value.\n\n When provided an object reference, the returned iterator always returns the\n same reference.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n value: any\n Value to return.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterConstant( 3.14 );\n > var v = it.next().value\n 3.14\n > v = it.next().value\n 3.14\n\n See Also\n --------\n constantFunction\n","iterContinuedFraction":"\niterContinuedFraction( iterator[, options] )\n Evaluates the terms of a continued fraction.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Maximum number of iterations. Default: 1e308.\n\n options.tol: number (optional)\n Tolerance at which to terminate further evaluation of the continued\n fraction. Default: floating-point epsilon.\n\n Returns\n -------\n out: number|null\n Result.\n\n Examples\n --------\n > var terms = array2iterator( [ 3, 4, 12, 4 ] );\n > var v = iterContinuedFraction( terms )\n ~3.245\n\n See Also\n --------\n iterContinuedFractionSeq\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x[, options] )\n Returns an iterator which generates a list of all continued fraction terms\n which can be obtained given the precision of `x`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x: number\n Input value.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Maximum number of iterations. Default: 1e308.\n\n options.tol: number (optional)\n Tolerance at which to terminate further evaluation of the continued\n fraction. Default: floating-point epsilon.\n\n options.returns: string (optional)\n Specifies the type of result to return. Must be one of\n\n - terms: return continued fraction terms\n - convergents: return continued fraction convergents\n - *: return both continued fraction terms and their associated\n convergents as a two-element array.\n\n Default: 'terms'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n // Return continued fraction terms...\n > var it = iterContinuedFractionSeq( 3.245 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 4\n > v = it.next().value\n 12\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n // Return continued fraction convergents...\n > it = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\n > v = it.next().value\n 3.0\n > v = it.next().value\n 3.25\n > v = it.next().value\n ~3.2449\n > v = it.next().value\n 3.245\n > bool = it.next().done\n true\n\n See Also\n --------\n iterContinuedFraction\n","iterCos":"\niterCos( iterator )\n Returns an iterator which iteratively computes the cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCos( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cos, iterCospi, iterSin, iterTan\n","iterCosh":"\niterCosh( iterator )\n Returns an iterator which iteratively computes the hyperbolic cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterCosh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.cosh, iterCos, iterSinh, iterTanh\n","iterCosineWave":"\niterCosineWave( [options] )\n Returns an iterator which generates a cosine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a cosine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCosineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterCosm1":"\niterCosm1( iterator )\n Returns an iterator which iteratively computes `cos(x) - 1`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCosm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.cosm1, iterCos\n","iterCospi":"\niterCospi( iterator )\n Returns an iterator which computes the cosine of each iterated value times\n π.\n\n Computes cos(πx) more accurately than cos(pi*x), especially for large x.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCospi( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cospi, iterCos\n","iterCounter":"\niterCounter( iterator )\n Returns an iterator which iteratively computes the number of iterated\n values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCounter( random.iterators.randu() );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterLength\n","iterCovercos":"\niterCovercos( iterator )\n Returns an iterator which iteratively computes the coversed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCovercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.covercos, iterCoversin, iterVercos\n","iterCoversin":"\niterCoversin( iterator )\n Returns an iterator which iteratively computes the coversed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCoversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.coversin, iterCovercos, iterVersin\n","iterCubesSeq":"\niterCubesSeq( [options] )\n Returns an iterator which generates a sequence of cubes.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 208063.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCubesSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 8\n\n See Also\n --------\n iterFourthPowersSeq, iterSquaresSeq\n","itercugmean":"\nitercugmean( iterator )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n\n If provided a negative value, the iterated value is `NaN` for all future\n invocations.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercugmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~3.16\n > v = it.next().value\n ~3.11\n > v = it.next().value\n ~3.50\n\n See Also\n --------\n itercuhmean, itercumean\n","itercuhmean":"\nitercuhmean( iterator )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercuhmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~2.86\n > v = it.next().value\n ~2.90\n > v = it.next().value\n ~3.24\n\n See Also\n --------\n itercugmean, itercumean\n","itercumax":"\nitercumax( iterator )\n Returns an iterator which iteratively computes a cumulative maximum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumax( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumidrange, itercumin, itercurange, itermax\n","itercumaxabs":"\nitercumaxabs( iterator )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumaxabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumax, itercuminabs, itermaxabs\n","itercumean":"\nitercumean( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumean( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.25\n\n See Also\n --------\n itercumidrange, itercusum, itermean\n","itercumeanabs":"\nitercumeanabs( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n 3.75\n\n See Also\n --------\n itercumean, itercumeanabs2, itercusumabs, itermeanabs\n","itercumeanabs2":"\nitercumeanabs2( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs2( arr );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n 15.75\n\n See Also\n --------\n itercumean, itercumeanabs, itercusumabs2, itermeanabs2\n","itercumidrange":"\nitercumidrange( iterator )\n Returns an iterator which iteratively computes a cumulative mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumidrange( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itercumean, itercumax, itercumin, itercurange, itermidrange\n","itercumin":"\nitercumin( iterator )\n Returns an iterator which iteratively computes a cumulative minimum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumin( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itercumax, itercumidrange, itercurange, itermin\n","itercuminabs":"\nitercuminabs( iterator )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuminabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n\n See Also\n --------\n itercumaxabs, itercumin, iterminabs\n","itercuprod":"\nitercuprod( iterator )\n Returns an iterator which iteratively computes a cumulative product.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuprod( arr );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -150.0\n\n See Also\n --------\n itercusum, iterprod\n","itercurange":"\nitercurange( iterator )\n Returns an iterator which iteratively computes a cumulative range.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercurange( arr );\n > var r = it.next().value\n 0.0\n > r = it.next().value\n 7.0\n > r = it.next().value\n 8.0\n > r = it.next().value\n 10.0\n\n See Also\n --------\n itercumax, itercumean, itercumin, iterrange\n","itercusum":"\nitercusum( iterator )\n Returns an iterator which iteratively computes a cumulative sum.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusum( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 5.0\n\n See Also\n --------\n itercumean, itersum, itercuprod\n","itercusumabs":"\nitercusumabs( iterator )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 15.0\n\n See Also\n --------\n itercumeanabs, itercusum, itersumabs\n","itercusumabs2":"\nitercusumabs2( iterator )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs2( arr );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 63.0\n\n See Also\n --------\n itercumeanabs2, itercusumabs, itersumabs2\n","iterDatespace":"\niterDatespace( start, stop[, N][, options] )\n Returns an iterator which returns evenly spaced dates over a specified\n interval.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: integer|string|Date\n Starting date either as a `Date` object, JavaScript timestamp, or a date\n string (inclusive).\n\n stop: integer|string|Date\n Stopping value either as a `Date` object, JavaScript timestamp, or a\n date string (inclusive).\n\n N: integer (optional)\n Number of values. Default: 100.\n\n options: Object (optional)\n Function options.\n\n options.round: string (optional)\n Specifies how sub-millisecond times should be rounded. Must be one of\n the following: 'floor', 'ceil', or 'round'. Default: 'floor'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var t1 = new Date();\n > var it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterator2array, iterIncrspace, iterLinspace, iterLogspace, iterStep\n","iterDedupe":"\niterDedupe( iterator[, limit] )\n Returns an iterator which removes consecutive duplicated values.\n\n `NaN` values are considered distinct.\n\n Uniqueness is determined according to strict equality. Accordingly, objects\n are *not* checked for deep equality.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > var it = iterDedupe( arr );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupeBy, iterUnique\n","iterDedupeBy":"\niterDedupeBy( iterator, [limit,] fcn )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n\n The provided function is provided five arguments:\n\n - curr: current source iterated value.\n - sprev: previous source iterated value.\n - dprev: previous downstream iterated value.\n - index: source iteration index (zero-based).\n - acc: previous resolved value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n fcn: Function\n Function indicating whether an iterated value is a \"duplicate\".\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > function fcn( v ) { return v; };\n > var it = iterDedupeBy( arr, fcn );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupe, iterUnique\n","iterDeg2rad":"\niterDeg2rad( iterator )\n Returns an iterator which iteratively converts an angle from degrees to\n radians.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -360.0, 360.0 );\n > var it = iterDeg2rad( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.deg2rad, iterRad2deg\n","iterDigamma":"\niterDigamma( iterator )\n Returns an iterator which iteratively evaluates the digamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.01, 5.0 );\n > var it = iterDigamma( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.digamma, iterGamma, iterTrigamma\n","iterDiracComb":"\niterDiracComb( [options] )\n Returns an iterator which generates a Dirac comb.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracComb();\n > var v = it.next().value\n Infinity\n > v = it.next().value\n 0.0\n\n See Also\n --------\n iterPulse\n","iterDiracDelta":"\niterDiracDelta( iterator )\n Returns an iterator which iteratively evaluates the Dirac delta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracDelta( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.diracDelta\n","iterDivide":"\niterDivide( iter0, ...iterator )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterDivide( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 0.5\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n","iterDoUntilEach":"\niterDoUntilEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v !== v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterDoUntilEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterDoWhileEach, iterUntilEach, iterWhileEach\n","iterDoWhileEach":"\niterDoWhileEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v === v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterDoWhileEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterDoUntilEach, iterUntilEach, iterWhileEach\n","iterEllipe":"\niterEllipe( iterator )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the second kind.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.0, 1.0 );\n > var it = iterEllipe( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.ellipe, iterEllipk\n","iterEllipk":"\niterEllipk( iterator )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the first kind.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.0, 1.0 );\n > var it = iterEllipk( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.ellipk, iterEllipe\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEmpty();\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterConstant\n","iterErf":"\niterErf( iterator )\n Returns an iterator which iteratively evaluates the error function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErf( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erf, iterErfc, iterErfinv, iterErfcinv\n","iterErfc":"\niterErfc( iterator )\n Returns an iterator which iteratively evaluates the complementary error\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfc( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfc, iterErf, iterErfinv, iterErfcinv\n","iterErfcinv":"\niterErfcinv( iterator )\n Returns an iterator which iteratively evaluates the inverse complementary\n error function.\n\n The domain of inverse complementary error function is restricted to [0,2].\n If an iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfcinv, iterErf, iterErfc, iterErfinv\n","iterErfinv":"\niterErfinv( iterator )\n Returns an iterator which iteratively evaluates the inverse error function.\n\n The domain of inverse error function is restricted to [-1,1]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfinv, iterErf, iterErfc, iterErfcinv\n","iterEta":"\niterEta( iterator )\n Returns an iterator which iteratively evaluates the Dirichlet eta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEta( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.eta\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options] )\n Returns an iterator which generates an interleaved sequence of even\n integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n > v = it.next().value\n -2\n\n See Also\n --------\n iterIntegersSeq, iterOddIntegersSeq\n","iterEvery":"\niterEvery( iterator )\n Tests whether all iterated values are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is falsy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\n > var bool = iterEvery( arr )\n false\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNone, iterSome\n","iterEveryBy":"\niterEveryBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a falsy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterEveryBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNoneBy, iterSomeBy\n","iterExp":"\niterExp( iterator )\n Returns an iterator which iteratively evaluates the natural exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterExp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.exp, iterExp10, iterExp2, iterExpm1, iterLn\n","iterExp2":"\niterExp2( iterator )\n Returns an iterator which iteratively evaluates the base `2` exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExp2( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.exp2, iterExp, iterExp10, iterLog2\n","iterExp10":"\niterExp10( iterator )\n Returns an iterator which iteratively evaluates the base `10` exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExp10( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.exp10, iterExp, iterExp2, iterLog10\n","iterExpit":"\niterExpit( iterator )\n Returns an iterator which iteratively evaluates the standard logistic\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 1.0 );\n > var it = iterExpit( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expit, iterExp, iterLogit\n","iterExpm1":"\niterExpm1( iterator )\n Returns an iterator which iteratively computes `exp(x) - 1`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterExpm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expm1, iterExp, iterExpm1rel\n","iterExpm1rel":"\niterExpm1rel( iterator )\n Returns an iterator which iteratively evaluates the relative error\n exponential.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExpm1rel( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expm1rel, iterExp, iterExpm1\n","iterFactorial":"\niterFactorial( iterator )\n Returns an iterator which iteratively evaluates the factorial function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorial( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.factorial, iterFactorialln\n","iterFactorialln":"\niterFactorialln( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n factorial function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorialln( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.factorialln, iterFactorial\n","iterFactorialsSeq":"\niterFactorialsSeq( [options] )\n Returns an iterator which generates a sequence of factorials.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorialsSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterFactorial\n","iterFibonacciSeq":"\niterFibonacciSeq( [options] )\n Returns an iterator which generates a Fibonacci sequence.\n\n The returned iterator can only generate the first 79 Fibonacci numbers, as\n larger Fibonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFibonacciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.fibonacci, iterLucasSeq, iterNegaFibonacciSeq, iterNonFibonacciSeq\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options] )\n Returns an iterator which generates a sequence of fifth powers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1552.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFifthPowersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 32\n\n See Also\n --------\n iterCubesSeq, iterFourthPowersSeq, iterSquaresSeq\n","iterFill":"\niterFill( iterator, value[, begin[, end]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n replaces the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n value: any\n Static value.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\n > var r = it.next().value\n 3.14\n > r = it.next().value\n 3.14\n > r = it.next().value\n \n\n","iterFilter":"\niterFilter( iterator, predicate[, thisArg] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilter( it1, f );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterFilterMap, iterMap, iterReject\n","iterFilterMap":"\niterFilterMap( iterator, fcn[, thisArg] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n\n When invoked, the callback function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If the callback returns `undefined`, the iterator invokes the function for\n the next value of the provided iterator; otherwise, the iterator returns\n the callback's return value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Callback function which both filters and maps.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilterMap( it1, f );\n > var v = it2.next().value\n 30\n > v = it2.next().value\n 40\n\n See Also\n --------\n iterFilter, iterMap\n","iterFirst":"\niterFirst( iterator )\n Returns the first iterated value.\n\n The function does *not* consume an entire iterator before returning.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The first iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\n > var v = iterFirst( arr )\n 1\n\n See Also\n --------\n iterHead, iterLast, iterNth\n","iterFlatTopPulse":"\niterFlatTopPulse( [options] )\n Returns an iterator which generates a flat top pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFlatTopPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse\n","iterFloor":"\niterFloor( iterator )\n Returns an iterator which rounds each iterated value toward negative\n infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor, iterCeil, iterRound\n","iterFloor2":"\niterFloor2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward negative infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor2, iterCeil2, iterFloor, iterFloor10, iterRound2\n","iterFloor10":"\niterFloor10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward negative infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor10, iterCeil10, iterFloor, iterFloor2, iterRound10\n","iterFlow":"\niterFlow( methods )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n\n The methods argument should be an object which maps constructor method names\n to iterator functions.\n\n Each iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n When a fluent interface iterator method is invoked, the method invokes the\n corresponding iterator function with an iterator and provided method\n arguments.\n\n If an iterator function returns an iterator, the corresponding fluent\n interface method returns a new fluent interface instance; otherwise, the\n corresponding fluent interface method returns the iterator function result.\n\n The iterator function evaluation context is always `null`.\n\n Iterator functions which return iterators are expected to return iterator\n protocol-compliant objects (i.e., an object having a `next` method which\n returns the next iterated value (if one exists) assigned to a `value`\n property and a `done` property having a boolean value indicating whether the\n iterator is finished).\n\n If an environment supports `Symbol.iterator`, the returned constructor\n returns iterators which are iterable.\n\n Parameters\n ----------\n methods: Object\n An object mapping method names to iterator functions.\n\n Returns\n -------\n FluentIterator: Function\n Fluent interface iterator constructor.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n Returns a new fluent interface iterator from a source iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n Returns\n -------\n iterator: Object\n Fluent interface iterator.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var bool = it.head( 3 ).some( 2 )\n false\n\n\nFluentIterator.prototype.next()\n Returns the next iterated value.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > v = it2.next().value\n 0\n > v = it2.next().value\n 1\n\n\nFluentIterator.prototype.return( [value] )\n Finishes an iterator and returns a provided value.\n\n Parameters\n ----------\n value: any (optional)\n Value to return.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > var bool = it2.return().done\n true\n > v = it2.next().value\n undefined\n\n See Also\n --------\n iterPipeline\n","iterForEach":"\niterForEach( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterForEach( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterMap\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options] )\n Returns an iterator which generates a sequence of fourth powers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9741.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFourthPowersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 16\n\n See Also\n --------\n iterCubesSeq, iterFifthPowersSeq, iterSquaresSeq\n","iterFresnelc":"\niterFresnelc( iterator )\n Returns an iterator which iteratively computes the Fresnel integral C(x).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterFresnelc( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.fresnelc, iterFresnels\n","iterFresnels":"\niterFresnels( iterator )\n Returns an iterator which iteratively computes the Fresnel integral S(x).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterFresnels( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.fresnels, iterFresnelc\n","iterGamma":"\niterGamma( iterator )\n Returns an iterator which iteratively evaluates the gamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterGamma( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.gamma, iterGamma1pm1, iterGammaln\n","iterGamma1pm1":"\niterGamma1pm1( iterator )\n Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n cancellation errors for small `x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterGamma1pm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.gamma1pm1, iterGamma\n","iterGammaln":"\niterGammaln( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n gamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterGammaln( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.gammaln, iterGamma\n","iterHacovercos":"\niterHacovercos( iterator )\n Returns an iterator which iteratively computes the half-value coversed\n cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHacovercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.hacovercos, iterCovercos, iterHacoversin\n","iterHacoversin":"\niterHacoversin( iterator )\n Returns an iterator which iteratively computes the half-value coversed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHacoversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.hacoversin, iterCoversin, iterHacovercos\n","iterHannPulse":"\niterHannPulse( [options] )\n Returns an iterator which generates a Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterSineWave\n","iterHavercos":"\niterHavercos( iterator )\n Returns an iterator which iteratively computes the half-value versed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHavercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.havercos, iterHaversin, iterVercos\n","iterHaversin":"\niterHaversin( iterator )\n Returns an iterator which iteratively computes the half-value versed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHaversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.haversin, iterHavercos, iterVersin\n","iterHead":"\niterHead( iterator, n )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n\n If a provided iterator only generates `m` values and `m` is less than `n`,\n the returned iterator only returns `m` values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of values.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHead( random.iterators.randu(), 5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterSlice\n","iterIncrspace":"\niterIncrspace( start, stop[, increment] )\n Returns an iterator which returns evenly spaced numbers according to a\n specified increment.\n\n Beware that values which follow the starting value are subject to floating-\n point rounding errors.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number\n Stopping value (exclusive).\n\n increment: number (optional)\n Increment. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterIncrspace( 0, 101, 2 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, iterDatespace, iterLinspace, iterLogspace, iterStep, iterUnitspace\n","iterIntegersSeq":"\niterIntegersSeq( [options] )\n Returns an iterator which generates an interleaved integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 18014398509481984.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n -1\n\n See Also\n --------\n iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterIntersection":"\niterIntersection( iter0, ...iterator )\n Returns an iterator which returns the intersection of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterIntersection( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersectionByHash, iterUnion, iterUnique\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n A returned iterator internally buffers unique hashes, along with the *first*\n iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > function f( v ) { return v.toString(); };\n > var it = iterIntersectionByHash( it1, it2, f );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUniqueByHash\n","iterInv":"\niterInv( iterator )\n Returns an iterator which iteratively computes the multiplicative inverse.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterInv( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.inv, iterPow\n","iterLanczosPulse":"\niterLanczosPulse( [options] )\n Returns an iterator which generates a Lanczos pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLanczosPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterPeriodicSinc\n","iterLast":"\niterLast( iterator )\n Consumes an entire iterator and returns the last iterated value.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The last iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var v = iterLast( arr )\n 1\n\n See Also\n --------\n iterFirst, iterNth\n","iterLength":"\niterLength( iterator )\n Consumes an entire iterator and returns the number of iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n len: integer\n Iterator length.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var len = iterLength( arr )\n 5\n\n See Also\n --------\n iterCounter\n","iterLinspace":"\niterLinspace( start, stop[, N] )\n Returns an iterator which returns evenly spaced numbers over a specified\n interval.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number\n Stopping value (inclusive).\n\n N: integer (optional)\n Number of values. Default: 100.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLinspace( 0, 99, 100 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLogspace, iterStep, iterUnitspace\n","iterLn":"\niterLn( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLn( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ln, iterExp, iterLog10, iterLog1p, iterLog2\n","iterLog":"\niterLog( x, b )\n Returns an iterator which iteratively computes the base `b` logarithm.\n\n For negative `b` or `x` iterated values, the returned iterator returns\n `NaN`.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n b: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 100.0 );\n > var y = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterLog( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log, iterLog10, iterLog1p, iterLog2, iterPow\n","iterLog1mexp":"\niterLog1mexp( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1-exp(-|x|)`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1mexp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1mexp, iterLog, iterLog1p, iterLog1pexp, iterPow\n","iterLog1p":"\niterLog1p( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1p( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1p, iterLog, iterLog10, iterLog2, iterPow\n","iterLog1pexp":"\niterLog1pexp( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+exp(x)`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1pexp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1pexp, iterLog, iterLog1p, iterLog1mexp, iterPow\n","iterLog2":"\niterLog2( iterator )\n Returns an iterator which iteratively evaluates the binary logarithm.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log2, iterLog, iterLog10, iterLog1p, iterPow\n","iterLog10":"\niterLog10( iterator )\n Returns an iterator which iteratively evaluates the common logarithm\n (logarithm with base 10).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog10( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log10, iterLog, iterLog1p, iterLog2, iterPow\n","iterLogit":"\niterLogit( iterator )\n Returns an iterator which iteratively evaluates the logit function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 1.0 );\n > var it = iterLogit( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.logit\n","iterLogspace":"\niterLogspace( start, stop[, N][, options] )\n Returns an iterator which returns evenly spaced numbers on a log scale.\n\n In linear space, the sequence starts at `base` raised to the power of\n `start` and ends with `base` raised to the power of `stop`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Exponent of starting value.\n\n stop: number\n Exponent of stopping value.\n\n N: integer (optional)\n Number of values. Default: 100.\n\n options: Object (optional)\n Function options.\n\n options.base: number (optional)\n Base of log space. Default: 10.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLogspace( 0, 3, 4 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 10\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterStep\n","iterLucasSeq":"\niterLucasSeq( [options] )\n Returns an iterator which generates a Lucas sequence.\n\n The returned iterator can only generate the first 77 Lucas numbers, as\n larger Lucas numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 77.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLucasSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 1\n\n See Also\n --------\n base.lucas, iterFibonacciSeq, iterNegaLucasSeq\n","iterMap":"\niterMap( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return v * 10.0; };\n > var it = iterMap( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFilter, iterFilterMap, iterForEach, iterReject\n","iterMapN":"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n\n When invoked, the callback function is provided `N+1` arguments, where `N`\n is the number of provided iterators and the last argument is the iteration\n index:\n\n - ...value: iterated values.\n - index: iteration index (zero-based).\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators.\n\n fcn: Function\n Function to invoke with iterated values.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > function fcn( x, y ) { return x + y; };\n > var it = iterMapN( it1, it2, fcn );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterMap\n","itermax":"\nitermax( iterator )\n Computes the maximum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermax( arr )\n 3.0\n\n See Also\n --------\n itermidrange, itermin, itermmax, iterrange\n","itermaxabs":"\nitermaxabs( iterator )\n Computes the maximum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermaxabs( arr )\n 4.0\n\n See Also\n --------\n itermax, iterminabs, itermmaxabs\n","itermean":"\nitermean( iterator )\n Computes an arithmetic mean over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = itermean( arr )\n 2.5\n\n See Also\n --------\n itermidrange, itermmean, iterstdev, itersum, itervariance\n","itermeanabs":"\nitermeanabs( iterator )\n Computes an arithmetic mean of absolute values for all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs( arr )\n 2.5\n\n See Also\n --------\n itermean, itermmeanabs, itersumabs\n","itermeanabs2":"\nitermeanabs2( iterator )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs2( arr )\n 7.5\n\n See Also\n --------\n itermean, itermeanabs, itermmeanabs2, itersumabs2\n","itermidrange":"\nitermidrange( iterator )\n Computes the mid-range of all iterated values.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Mid-range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = itermidrange( arr )\n -0.5\n\n See Also\n --------\n itermean, itermax, itermin, iterrange\n","itermin":"\nitermin( iterator )\n Computes the minimum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermin( arr )\n -3.0\n\n See Also\n --------\n itermax, itermidrange, itermmin, iterrange\n","iterminabs":"\niterminabs( iterator )\n Computes the minimum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = iterminabs( arr )\n 1.0\n\n See Also\n --------\n itermaxabs, itermin, itermminabs\n","itermmax":"\nitermmax( iterator, W )\n Returns an iterator which iteratively computes a moving maximum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmax( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermax, itermmidrange, itermmin, itermrange\n","itermmaxabs":"\nitermmaxabs( iterator, W )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmaxabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermaxabs, itermmax, itermminabs\n","itermmean":"\nitermmean( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmean( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.0\n\n See Also\n --------\n itermean, itermsum\n","itermmeanabs":"\nitermmeanabs( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n ~4.33\n\n See Also\n --------\n itermeanabs, itermmean, itermsumabs\n","itermmeanabs2":"\nitermmeanabs2( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of squared absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs2( arr, 3 );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n ~19.67\n\n See Also\n --------\n itermeanabs2, itermmeanabs, itermsumabs2\n","itermmidrange":"\nitermmidrange( iterator, W )\n Returns an iterator which iteratively computes a moving mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmidrange( arr, 3 );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itermidrange, itermmean, itermmax, itermmin, itermrange\n","itermmin":"\nitermmin( iterator, W )\n Returns an iterator which iteratively computes a moving minimum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmin( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itermin, itermmax, itermmidrange, itermrange\n","itermminabs":"\nitermminabs( iterator, W )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermminabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n\n See Also\n --------\n iterminabs, itermmaxabs, itermmin\n","iterMod":"\niterMod( iter0, ...iterator )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterMod( it1, it2 );\n > var v = it.next().value\n 0.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide\n","itermprod":"\nitermprod( iterator, W )\n Returns an iterator which iteratively computes a moving product.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermprod( arr, 3 );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -75.0\n\n See Also\n --------\n itermsum, iterprod\n","itermrange":"\nitermrange( iterator, W )\n Returns an iterator which iteratively computes a moving range.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermrange( arr, 3 );\n > var m = it.next().value\n 0.0\n > m = it.next().value\n 7.0\n > m = it.next().value\n 8.0\n > m = it.next().value\n 10.0\n\n See Also\n --------\n itermmax, itermmean, itermmin, iterrange\n","itermsum":"\nitermsum( iterator, W )\n Returns an iterator which iteratively computes a moving sum.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsum( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 3.0\n\n See Also\n --------\n itermmean, itersum\n","itermsumabs":"\nitermsumabs( iterator, W )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 13.0\n\n See Also\n --------\n itermmeanabs, itermsum, itersum, itersumabs\n","itermsumabs2":"\nitermsumabs2( iterator, W )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs2( arr, 3 );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 59.0\n\n See Also\n --------\n itermmeanabs2, itermsumabs, itersumabs, itersumabs2\n","iterMultiply":"\niterMultiply( iter0, ...iterator )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to multiply.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterMultiply( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 8.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterSubtract\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options] )\n Returns an iterator which generates a negaFibonacci sequence.\n\n The returned iterator can only generate the first 79 negaFibonacci numbers,\n as larger negaFibonacci numbers cannot be safely represented in double-\n precision floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegaFibonacciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.negafibonacci, iterFibonacciSeq, iterNonFibonacciSeq\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options] )\n Returns an iterator which generates a negaLucas sequence.\n\n The returned iterator can only generate the first 77 negaLucas numbers, as\n larger negaLucas numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 77.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegaLucasSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n -1\n\n See Also\n --------\n base.negalucas, iterLucasSeq, iterNegaFibonacciSeq\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of negative even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeEvenIntegersSeq();\n > var v = it.next().value\n -2\n > v = it.next().value\n -4\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterNonPositiveEvenIntegersSeq\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options] )\n Returns an iterator which generates a negative integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740991.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeIntegersSeq();\n > var v = it.next().value\n -1\n > v = it.next().value\n -2\n\n See Also\n --------\n iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options] )\n Returns an iterator which generates a sequence of negative odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeOddIntegersSeq();\n > var v = it.next().value\n -1\n > v = it.next().value\n -3\n\n See Also\n --------\n iterOddIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeEvenIntegersSeq, iterPositiveOddIntegersSeq\n","iterNone":"\niterNone( iterator )\n Tests whether all iterated values are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is truthy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterNone( arr )\n false\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNoneBy, iterSome\n","iterNoneBy":"\niterNoneBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a falsy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v <= 0 ); };\n > var bool = iterNoneBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNone, iterSomeBy\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonFibonacciSeq();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n\n See Also\n --------\n base.nonfibonacci, iterFibonacciSeq\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of nonnegative even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370497.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonNegativeEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveEvenIntegersSeq, iterPositiveEvenIntegersSeq\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options] )\n Returns an iterator which generates a nonnegative integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonNegativeIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterIntegersSeq, iterNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of nonpositive even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370497.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonPositiveEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n -2\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeEvenIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeEvenIntegersSeq\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options] )\n Returns an iterator which generates a nonpositive integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonPositiveIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n -1\n\n See Also\n --------\n iterIntegersSeq, iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterPositiveIntegersSeq\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options] )\n Returns an iterator which generates a sequence of nonsquares.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199349647256.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonSquaresSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 5\n\n See Also\n --------\n iterCubesSeq, iterSquaresSeq\n","iterNth":"\niterNth( iterator, n )\n Returns the nth iterated value.\n\n If `n` exceeds the total number of iterations, the function returns\n `undefined`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Iteration number.\n\n Returns\n -------\n v: any\n The nth iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\n > var v = iterNth( arr, 3 )\n 1\n\n See Also\n --------\n iterFirst, iterLast\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options] )\n Returns an iterator which generates an interleaved sequence of odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterOddIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n -1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq\n","iterPeriodicSinc":"\niterPeriodicSinc( n[, options] )\n Returns an iterator which generates a periodic sinc waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Order.\n\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 100.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPeriodicSinc( 7 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterSineWave\n","iterPipeline":"\niterPipeline( iterFcn[, ...iterFcn] )\n Returns an iterator pipeline.\n\n Parameters\n ----------\n iterFcn: Function|Array\n Iterator function or an array of iterator functions.\n\n iterFcn: ...Function (optional)\n Iterator functions.\n\n Returns\n -------\n fcn( src ): Function\n Iterator pipeline which accepts a single argument, a source iterator.\n\n Examples\n --------\n > var it1 = iterThunk( iterHead, 100 );\n > function f( r ) { return ( r > 0.95 ); };\n > var it2 = iterThunk( iterSomeBy, 5, f );\n > var p = iterPipeline( it1, it2 );\n > var bool = p( random.iterators.randu() )\n \n\n See Also\n --------\n iterFlow, iterThunk\n","iterPop":"\niterPop( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the last value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPop( it1 );\n > var v = it2.next().value\n 1\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPush, iterShift, iterSlice\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of positive even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveEvenIntegersSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 4\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNegativeEvenIntegersSeq, iterNonNegativeEvenIntegersSeq, iterPositiveIntegersSeq, iterPositiveOddIntegersSeq\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options] )\n Returns an iterator which generates a positive integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740991.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeIntegersSeq\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options] )\n Returns an iterator which generates a sequence of positive odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveOddIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterOddIntegersSeq, iterIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterPositiveIntegersSeq\n","iterPow":"\niterPow( base, exponent )\n Returns an iterator which iteratively evaluates the exponential function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n base: Object|number\n Input iterator.\n\n exponent: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( -2.0, 2.0 );\n > var it = iterPow( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.pow, iterExp, iterLog\n","iterPrimesSeq":"\niterPrimesSeq( [options] )\n Returns an iterator which generates a sequence of prime numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 245181918813464.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPrimesSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 5\n\n See Also\n --------\n iterCompositesSeq, iterIntegersSeq, iterPositiveIntegersSeq\n","iterprod":"\niterprod( iterator )\n Computes the product of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Product.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = iterprod( arr )\n 24.0\n\n See Also\n --------\n itermprod, itersum\n","iterPulse":"\niterPulse( [options] )\n Returns an iterator which generates a pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 10.\n\n options.duration: integer (optional)\n Pulse duration (i.e., the number of consecutive iterations of maximum\n amplitude during one period). Default: floor(options.period/2).\n\n options.min: number (optional)\n Minimum amplitude. Default: 0.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPulse();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterPush":"\niterPush( iterator, ...items )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to append.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPush( it1, 3, 4 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterUnshift\n","iterRad2deg":"\niterRad2deg( iterator )\n Returns an iterator which iteratively converts an angle from radians to\n degrees.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterRad2deg( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.rad2deg, iterDeg2rad\n","iterRamp":"\niterRamp( iterator )\n Returns an iterator which iteratively evaluates the ramp function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRamp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ramp\n","iterrange":"\niterrange( iterator )\n Computes the range of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = iterrange( arr )\n 7.0\n\n See Also\n --------\n itermax, itermean, itermin, itermrange\n","iterReject":"\niterReject( iterator, predicate[, thisArg] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterReject( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterFilter, iterMap\n","iterReplicate":"\niterReplicate( iterator, n )\n Returns an iterator which replicates each iterated value `n` times.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of times each iterated value is replicated.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > var it2 = iterReplicate( it1, 2 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterReplicateBy\n","iterReplicateBy":"\niterReplicateBy( iterator, fcn[, thisArg] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n\n The callback function is provided three arguments:\n\n - value: iterated value.\n - index: source iteration index (zero-based).\n - n: iteration index (zero-based).\n\n The callback function is invoked *once* per iterated value of the provided\n iterator.\n\n The callback function *must* return an integer value. If the return value is\n less than or equal to zero, the returned iterator skips an iterated value\n and invokes the callback for the next iterated value of the provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function which returns the number of times an iterated value should be\n replicated.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > function f( v, i ) { return i + 1; };\n > var it2 = iterReplicateBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterReplicate\n","iterRound":"\niterRound( iterator )\n Returns an iterator which rounds each iterated value to the nearest integer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round, iterCeil, iterFloor, iterTrunc\n","iterRound2":"\niterRound2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two on a linear scale.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round2, iterCeil2, iterFloor2, iterRound, iterRound10, iterTrunc2\n","iterRound10":"\niterRound10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 on a linear scale.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round10, iterCeil10, iterFloor10, iterRound, iterRound2, iterTrunc10\n","iterRsqrt":"\niterRsqrt( iterator )\n Returns an iterator which iteratively computes the reciprocal (inverse)\n square root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRsqrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.rsqrt, iterSqrt\n","iterSawtoothWave":"\niterSawtoothWave( [options] )\n Returns an iterator which generates a sawtooth wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSawtoothWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSineWave, iterSquareWave, iterTriangleWave\n","iterShift":"\niterShift( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the first value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterShift( it1 );\n > var v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPop, iterSlice, iterUnshift\n","iterSignum":"\niterSignum( iterator )\n Returns an iterator which iteratively evaluates the signum function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSignum( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.signum\n","iterSin":"\niterSin( iterator )\n Returns an iterator which iteratively computes the sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSin( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sin, iterCos, iterSinpi, iterTan\n","iterSinc":"\niterSinc( iterator )\n Returns an iterator which iteratively computes the normalized cardinal sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterSinc( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sinc, iterSin\n","iterSineWave":"\niterSineWave( [options] )\n Returns an iterator which generates a sine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a sine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterCosineWave, iterPulse, iterSawtoothWave, iterSquareWave, iterTriangleWave\n","iterSinh":"\niterSinh( iterator )\n Returns an iterator which iteratively evaluates the hyperbolic sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterSinh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sinh, iterCosh, iterTanh\n","iterSinpi":"\niterSinpi( iterator )\n Returns an iterator which computes the sine of each iterated value times π.\n\n Computes sin(πx) more accurately than sin(pi*x), especially for large x.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSinpi( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sinpi, iterSin\n","iterSlice":"\niterSlice( iterator[, begin[, end]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n returns the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSlice( random.iterators.randu(), 5, 10 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterHead\n","iterSome":"\niterSome( iterator, n )\n Tests whether at least `n` iterated values are truthy.\n\n The function immediately returns upon finding `n` truthy values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an iterator returns at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = iterSome( arr, 3 )\n true\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNone, iterSomeBy\n","iterSomeBy":"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering `n` truthy return values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Minimum number of successful values.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for at least `n` iterated values. Otherwise, the function returns\n `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterSomeBy( arr, 3, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNoneBy, iterSome\n","iterSpence":"\niterSpence( iterator )\n Returns an iterator which iteratively evaluates Spence's function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 100.0 );\n > var it = iterSpence( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.spence\n","iterSqrt":"\niterSqrt( iterator )\n Returns an iterator which iteratively computes the principal square root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSqrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sqrt, iterCbrt, iterRsqrt\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator )\n Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n accurately for small `x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 100.0 );\n > var it = iterSqrt1pm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sqrt1pm1, iterSqrt\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options] )\n Returns an iterator which generates a sequence of squared triangular\n numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 11585.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquaredTriangularSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 9\n\n See Also\n --------\n iterTriangularSeq\n","iterSquaresSeq":"\niterSquaresSeq( [options] )\n Returns an iterator which generates a sequence of squares.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 94906265.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquaresSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 4\n\n See Also\n --------\n iterCubesSeq, iterNonSquaresSeq\n","iterSquareWave":"\niterSquareWave( [options] )\n Returns an iterator which generates a square wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a square wave repeats).\n This must be an even integer in order to ensure a 50% duty cycle.\n Default: 10.\n\n options.min: number (optional)\n Minimum amplitude. Default: -1.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquareWave();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterTriangleWave\n","iterstdev":"\niterstdev( iterator[, mean] )\n Computes a correct sample standard deviation over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Corrected sample standard deviation.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var m = iterstdev( arr )\n ~4.95\n\n See Also\n --------\n itermean, itervariance\n","iterStep":"\niterStep( start, increment[, N] )\n Returns an iterator which returns a sequence of numbers according to a\n specified increment.\n\n Beware that values which follow the starting value are subject to floating-\n point rounding errors.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n increment: number\n Increment.\n\n N: number (optional)\n Number of values. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterStep( 0, 2, 10 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterLogspace, iterUnitspace\n","iterStrided":"\niterStrided( iterator, stride[, offset[, eager]] )\n Returns an iterator which steps by a specified amount.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n stride: integer\n Stride (i.e., step amount).\n\n offset: integer (optional)\n Index of the first iterated value. Default: 0.\n\n eager: boolean (optional)\n Boolean indicating whether to eagerly advance the input iterator when\n provided a non-zero offset. Default: false.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n > var it = iterStrided( arr, 2, 1 );\n > var r = it.next().value\n 1\n > r = it.next().value\n 3\n\n See Also\n --------\n iterAdvance, iterNth, iterStridedBy\n","iterStridedBy":"\niterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )\n Returns an iterator which steps according to a provided callback function.\n\n When invoked, the input function is provided four arguments:\n\n - value: iterated value.\n - i: input iteration index (zero-based).\n - n: output (strided) iteration index (zero-based).\n - curr: current stride.\n\n The return value of the input function specifies the next stride.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Stride function (i.e., a function which returns the step amount).\n\n offset: integer (optional)\n Index of the first iterated value. Default: 0.\n\n eager: boolean (optional)\n Boolean indicating whether to eagerly advance the input iterator when\n provided a non-zero offset. Default: false.\n\n thisArg: any (optional)\n Stride function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n > function stride( v, i ) { return (i % 10)+1; };\n > var it = iterStridedBy( arr, stride );\n > var r = it.next().value\n 0\n > r = it.next().value\n 1\n > r = it.next().value\n 3\n\n See Also\n --------\n iterAdvance, iterNth, iterStrided\n","iterSubtract":"\niterSubtract( iter0, ...iterator )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to subtract.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 5.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterSubtract( it1, it2 );\n > var v = it.next().value\n -2.0\n > v = it.next().value\n 1.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n","itersum":"\nitersum( iterator )\n Computes the sum of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = itersum( arr )\n 10.0\n\n See Also\n --------\n itermean, itermsum, iterprod\n","itersumabs":"\nitersumabs( iterator )\n Computes the sum of absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs( arr )\n 10.0\n\n See Also\n --------\n itermeanabs, itermsumabs, itersum\n","itersumabs2":"\nitersumabs2( iterator )\n Computes the sum of squared absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs2( arr )\n 30.0\n\n See Also\n --------\n itermeanabs2, itermsumabs2, itersumabs\n","iterTan":"\niterTan( iterator )\n Returns an iterator which iteratively evaluates the tangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.57, 1.57 );\n > var it = iterTan( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.tan, iterCos, iterSin\n","iterTanh":"\niterTanh( iterator )\n Returns an iterator which iteratively evaluates the hyperbolic tangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -4.0, 4.0 );\n > var it = iterTanh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.tanh, iterCosh, iterSinh, iterTan\n","iterThunk":"\niterThunk( iterFcn[, ...args] )\n Returns an iterator \"thunk\".\n\n A provided iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n The returned function expects a single argument, an iterator.\n\n This function is useful within the context of iterator pipelines as a means\n to defer execution until a pipeline is ready for data flow.\n\n Parameters\n ----------\n iterFcn: Function\n Iterator function.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n fcn( iter ): Function\n Function which accepts a single argument, an iterator, and invokes a\n previously provided iterator function with the provided iterator and any\n previously provided arguments.\n\n Examples\n --------\n > var fcn = iterThunk( iterSome, 3 );\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = fcn( arr )\n true\n\n See Also\n --------\n iterPipeline\n","iterTriangleWave":"\niterTriangleWave( [options] )\n Returns an iterator which generates a triangle wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangleWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave\n","iterTriangularSeq":"\niterTriangularSeq( [options] )\n Returns an iterator which generates a sequence of triangular numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 134217727.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangularSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterSquaredTriangularSeq\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options] )\n Returns an iterator which generates a Tribonacci sequence.\n \n The returned iterator can only generate the first 64 Tribonacci numbers, as\n larger Tribonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 64.\n\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant\n object has the next\n iterated value (if one exists) and a\n boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n\n Examples\n --------\n > var it = iterTribonnaciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 0\n\n See Also\n --------\n base.tribonacci, base.fibonacci, iterLucasSeq\n","iterTrigamma":"\niterTrigamma( iterator )\n Returns an iterator which iteratively evaluates the trigamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.01, 50.0 );\n > var it = iterTrigamma( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.trigamma, iterDigamma, iterGamma\n","iterTrunc":"\niterTrunc( iterator )\n Returns an iterator which rounds each iterated value toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc, iterCeil, iterFloor, iterRound\n","iterTrunc2":"\niterTrunc2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc2, iterCeil2, iterFloor2, iterRound2, iterTrunc\n","iterTrunc10":"\niterTrunc10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc10, iterCeil10, iterFloor10, iterRound10, iterTrunc\n","iterUnion":"\niterUnion( iter0, ...iterator )\n Returns an iterator which returns the union of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the total number of source iterator\n values.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterUnion( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 4\n > v = it.next().value\n 5\n > v = it.next().value\n 3\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUnique\n","iterUnique":"\niterUnique( iterator )\n Returns an iterator which returns unique values.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = iterUnique( it1 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUniqueBy, iterUniqueByHash\n","iterUniqueBy":"\niterUniqueBy( iterator, predicate[, thisArg] )\n Returns an iterator which returns unique values according to a predicate\n function.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n A predicate function is invoked for each iterated value against each value\n in an internal buffer consisting of previously identified unique values.\n Thus, as the number of unique values grows, so, too, does the number of\n predicate function invocations per iterated value.\n\n An iterated value is considered \"unique\" if the predicate function returns\n truthy values for all comparisons of the iterated value with each value in\n the internal buffer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n A binary function with parameters `a` and `b` corresponding to iterated\n values. If the values are the same, the function should return `false`\n (i.e., non-unique); otherwise, if the values are distinct, the function\n should return `true` (i.e., unique).\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( a, b ) { return ( a !== b ); };\n > var it2 = iterUniqueBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueByHash\n","iterUniqueByHash":"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n Returns an iterator which returns unique values according to a hash\n function.\n\n A returned iterator internally buffers unique hashes and, thus, has O(N)\n memory requirements.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( v ) { return v.toString(); };\n > var it2 = iterUniqueByHash( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueBy\n","iterUnitspace":"\niterUnitspace( start[, stop] )\n Returns an iterator which returns numbers incremented by one.\n\n The iterator stops once the `stop` value is exceeded.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number (optional)\n Stopping value. Default: +infinity.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterUnitspace( 0, 99 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterator2array, iterIncrspace, iterLinspace, iterStep\n","iterUnshift":"\niterUnshift( iterator, ...items )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to prepend.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterUnshift( it1, 3, 4 );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterPush, iterShift\n","iterUntilEach":"\niterUntilEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v !== v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterUntilEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterWhileEach\n","itervariance":"\nitervariance( iterator[, mean] )\n Computes an unbiased sample variance over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Unbiased sample variance.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var s2 = itervariance( arr )\n 24.5\n\n See Also\n --------\n itermean, iterstdev\n","iterVercos":"\niterVercos( iterator )\n Returns an iterator which iteratively computes the versed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterVercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.vercos, iterCos, iterSin, iterVersin\n","iterVersin":"\niterVersin( iterator )\n Returns an iterator which iteratively computes the versed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterVersin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.versin, iterCos, iterSin, iterVercos\n","iterWhileEach":"\niterWhileEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v === v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterWhileEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterUntilEach\n","iterZeta":"\niterZeta( iterator )\n Returns an iterator which iteratively evaluates the Riemann zeta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 1.1, 50.0 );\n > var it = iterZeta( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.zeta\n","joinStream":"\njoinStream( [options] )\n Returns a transform stream which joins streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = joinStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream\n","joinStream.factory":"\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","joinStream.objectMode":"\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream","kde2d":"\nkde2d( x, y[, options] )\n Two-dimensional kernel density estimation.\n\n Parameters\n ----------\n x: Array\n Array of x values.\n\n y: Array\n Array of y values.\n\n options: Object (optional)\n Function options.\n\n options.h: number (optional)\n Array of length two containing the bandwidth values for x and y.\n\n options.n: number (optional)\n Number of partitions on the x- and y-axes. Default: `25`.\n\n options.xMin: number (optional)\n Lower limit of x.\n\n options.xMax: number (optional)\n Upper limit of x.\n\n options.yMin: number (optional)\n Lower limit of y.\n\n options.yMax: number (optional)\n Upper limit of y.\n\n options.kernel: string|Function\n A string or function to specifying the used kernel function. Default:\n `'gaussian'`.\n\n Returns\n -------\n out: Object\n Object containing the density estimates (`z`) along grid points (`x` and\n `y` values).\n\n Examples\n --------\n > var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\n > var y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\n > var out = kde2d( x, y )\n { 'x': [1, ... ], 'y': [0.05, ...], 'z': ndarray{Float64Array[0.031, ...] }\n\n","kebabcase":"\nkebabcase( str )\n Converts a string to kebab case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Kebab-cased string.\n\n Examples\n --------\n > var out = kebabcase( 'Hello World!' )\n 'hello-world'\n > out = kebabcase( 'I am a tiny little teapot' )\n 'i-am-a-tiny-little-teapot'\n\n See Also\n --------\n camelcase, constantcase, pascalcase, snakecase","keyBy":"\nkeyBy( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n\n When invoked, the input function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyBy( arr, toKey )\n { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n See Also\n --------\n forEach\n","keyByRight":"\nkeyByRight( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n\n When invoked, the input function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyByRight( arr, toKey )\n { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n See Also\n --------\n forEachRight, keyBy\n","keysIn":"\nkeysIn( obj )\n Returns an array of an object's own and inherited enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = keysIn( obj )\n e.g., [ 'beep', 'foo' ]\n\n See Also\n --------\n objectEntriesIn, objectKeys, objectValuesIn\n","kruskalTest":"\nkruskalTest( ...x[, options] )\n Computes the Kruskal-Wallis test for equal medians.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = kruskalTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = kruskalTest( arr, { 'groups': groups } )\n\n","kstest":"\nkstest( x, y[, ...params][, options] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n is computed for the null hypothesis that the values of `x` come from the\n distribution specified by `y`. `y` can be either a string with the name of\n the distribution to test against, or a function.\n\n In the latter case, `y` is expected to be the cumulative distribution\n function (CDF) of the distribution to test against, with its first parameter\n being the value at which to evaluate the CDF and the remaining parameters\n constituting the parameters of the distribution. The parameters of the\n distribution are passed as additional arguments after `y` from `kstest` to\n the chosen CDF. The function returns an object holding the calculated test\n statistic `statistic` and the `pValue` of the test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the hypothesis test results.\n\n Parameters\n ----------\n x: Array\n Input array holding numeric values.\n\n y: Function|string\n Either a CDF function or a string denoting the name of a distribution.\n\n params: ...number (optional)\n Distribution parameters passed to reference CDF.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array is already in sorted order.\n Default: `false`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that the true distribution of `x` is not equal\n to the reference distribution specified by `y` (`two-sided`), whether it\n is `less` than the reference distribution or `greater` than the\n reference distribution. Default: `'two-sided'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.alternative: string\n Used test alternative. Either `two-sided`, `less` or `greater`.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Verify that data is drawn from a normal distribution:\n > var rnorm = base.random.normal.factory({ 'seed': 4839 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n // Test against N(0,1)\n > var out = kstest( x, 'normal', 0.0, 1.0 )\n { pValue: 0.0, statistic: 0.847, ... }\n\n // Test against N(3,1)\n > out = kstest( x, 'normal', 3.0, 1.0 )\n { pValue: 0.6282, statistic: 0.0733, ... }\n\n // Verify that data is drawn from a uniform distribution:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0 )\n { pValue: ~0.703, statistic: ~0.069, ... }\n\n // Print output:\n > out.print()\n Kolmogorov-Smirnov goodness-of-fit test.\n\n Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n pValue: 0.7039\n statistic: 0.0689\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Set custom significance level:\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\n { pValue: ~0.7039, statistic: ~0.069, ... }\n\n // Carry out one-sided hypothesis tests:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\n { pValue: ~0.358, statistic: ~0.07, ... }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\n { pValue: ~0.907, statistic: ~0.02, ... }\n\n // Set `sorted` option to true when data is in increasing order:\n > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n { pValue: ~1, statistic: 0.1, ... }\n\n","last":"\nlast( str[, n][, options] )\n Returns the last character(s) of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to return. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = last( 'beep' )\n 'p'\n > out = last( 'Boop', 2 )\n 'op'\n > out = last( 'foo bar', 3 )\n 'bar'\n\n See Also\n --------\n firstChar\n","leveneTest":"\nleveneTest( x[, ...y[, options]] )\n Computes Levene's test for equal variances.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n y: ...Array (optional)\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Array\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = leveneTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = leveneTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, bartlettTest\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n\n Returns\n -------\n list: Object\n Linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the last node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = LinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n DoublyLinkedList, Stack\n","linspace":"\nlinspace( start, stop, length[, options] )\n Generates a linearly spaced array over a specified interval.\n\n If the specified length is zero, the function returns an empty array.\n\n If the specified length is one, the function returns an array containing\n `stop`, but not `start`, when `endpoint` is true; otherwise, the function\n returns an array containing `start`, but not `stop`.\n\n For real-valued `start` and `stop`, if `start` is less than `stop`, the\n output array will contain ascending values, and, if `start` is greater than\n `stop`, the output array will contain descending values.\n\n When the output array length is greater than one and `endpoint` is true, the\n output array is guaranteed to include the `start` and `stop` values. Beware,\n however, that values between `start` and `stop` are subject to floating-\n point rounding errors.\n\n If both `start` and `stop` are real-valued, the output array data type may\n be any floating-point data type or 'generic'. However, if either `start` or\n `stop` are complex numbers, the output array type must be a complex\n floating-point data type or 'generic'.\n\n When writing to a complex floating-point output array, real-valued `start`\n and `stop` values are treated as complex numbers having a real component\n equaling the provided value and having an imaginary component equaling zero.\n\n When generating linearly spaced complex floating-point numbers, the real and\n imaginary components are generated separately.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n length: integer\n Length of output array.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Must be a floating-point data type or 'generic'.\n If both `start` and `stop` are the same type (either 'float64',\n 'complex64', or 'complex128'), the default output array data type is\n the same type as the input values (either 'float64', 'complex64', or\n 'complex128', respectively). Otherwise, the default output array data\n type is 'complex128'.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `length + 1` linearly spaced\n values over the interval `[start, stop]` and only writes `length` values\n to the output array, thus excluding `stop` from the output array.\n Accordingly, for a fixed `length`, the spacing between adjacent values\n in the output array changes depending on the value of `endpoint`.\n Default: true.\n\n Returns\n -------\n arr: Array\n Linearly spaced array.\n\n Examples\n --------\n > var arr = linspace( 0.0, 100.0, 6 )\n [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n > arr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\n [ 0.0, 20.0, 40.0, 60.0, 80.0 ]\n > arr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n\n\nlinspace.assign( start, stop, out[, options] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n\n If the provided output array is empty, the function returns the provided\n output array unchanged.\n\n If the provided output array contains a single element, the function writes\n the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n function writes the `start` value, but not `stop`.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n out: ArrayLikeObject\n Output array.\n\n options: Object (optional)\n Options.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `N+1` linearly spaced values\n (where `N` is the length of the provided output array) over the interval\n `[start, stop]` and only writes `N` values to the output array, thus\n excluding `stop` from the output array. Accordingly, for a fixed `N`,\n the spacing between adjacent values in the output array changes\n depending on the value of `endpoint`. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0, 0 ];\n > var out = linspace.assign( 0, 100, arr )\n [ 0, 20, 40, 60, 80, 100 ]\n > var bool = ( arr === out )\n true\n > arr = [ 0, 0, 0, 0, 0 ];\n > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n [ 0, 20, 40, 60, 80 ]\n\n See Also\n --------\n incrspace, logspace\n","linspace.assign":"\nlinspace.assign( start, stop, out[, options] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n\n If the provided output array is empty, the function returns the provided\n output array unchanged.\n\n If the provided output array contains a single element, the function writes\n the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n function writes the `start` value, but not `stop`.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n out: ArrayLikeObject\n Output array.\n\n options: Object (optional)\n Options.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `N+1` linearly spaced values\n (where `N` is the length of the provided output array) over the interval\n `[start, stop]` and only writes `N` values to the output array, thus\n excluding `stop` from the output array. Accordingly, for a fixed `N`,\n the spacing between adjacent values in the output array changes\n depending on the value of `endpoint`. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0, 0 ];\n > var out = linspace.assign( 0, 100, arr )\n [ 0, 20, 40, 60, 80, 100 ]\n > var bool = ( arr === out )\n true\n > arr = [ 0, 0, 0, 0, 0 ];\n > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n [ 0, 20, 40, 60, 80 ]\n\n See Also\n --------\n incrspace, logspace","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of negative opinion words.\n\n Examples\n --------\n > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_POSITIVE_OPINION_WORDS_EN\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of positive opinion words.\n\n Examples\n --------\n > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_NEGATIVE_OPINION_WORDS_EN\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n\n Examples\n --------\n > LN_HALF\n -0.6931471805599453\n\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n\n Examples\n --------\n > LN_PI\n 1.1447298858494002\n\n See Also\n --------\n PI\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n\n Examples\n --------\n > LN_SQRT_TWO_PI\n 0.9189385332046728\n\n See Also\n --------\n PI\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n\n Examples\n --------\n > LN_TWO_PI\n 1.8378770664093456\n\n See Also\n --------\n TWO_PI\n","LN2":"\nLN2\n Natural logarithm of `2`.\n\n Examples\n --------\n > LN2\n 0.6931471805599453\n\n See Also\n --------\n LN10\n","LN10":"\nLN10\n Natural logarithm of `10`.\n\n Examples\n --------\n > LN10\n 2.302585092994046\n\n See Also\n --------\n LN2\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n\n Examples\n --------\n > LOG2E\n 1.4426950408889634\n\n See Also\n --------\n E, LOG10E\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n\n Examples\n --------\n > LOG10E\n 0.4342944819032518\n\n See Also\n --------\n E, LOG2E\n","logspace":"\nlogspace( a, b[, length] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n If a `length` is not provided, the default output array length is `10`.\n\n The output array includes the values `10^a` and `10^b`.\n\n Parameters\n ----------\n a: number\n Exponent of start value.\n\n b: number\n Exponent of end value.\n\n length: integer (optional)\n Length of output array. Default: `10`.\n\n Returns\n -------\n arr: Array\n Logarithmically spaced numeric array.\n\n Examples\n --------\n > var arr = logspace( 0, 2, 6 )\n [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n See Also\n --------\n incrspace, linspace\n","lowercase":"\nlowercase( str )\n Converts a string to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n uncapitalize, uppercase\n","lowercaseKeys":"\nlowercaseKeys( obj )\n Converts each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'A': 1, 'B': 2 };\n > var out = lowercaseKeys( obj )\n { 'a': 1, 'b': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","lowess":"\nlowess( x, y[, options] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n\n Parameters\n ----------\n x: Array\n x-axis values (abscissa values).\n\n y: Array\n Corresponding y-axis values (ordinate values).\n\n options: Object (optional)\n Function options.\n\n options.f: number (optional)\n Positive number specifying the smoothing span, i.e., the proportion of\n points which influence smoothing at each value. Larger values\n correspond to more smoothing. Default: `2/3`.\n\n options.nsteps: number (optional)\n Number of iterations in the robust fit (fewer iterations translates to\n faster function execution). If set to zero, the nonrobust fit is\n returned. Default: `3`.\n\n options.delta: number (optional)\n Nonnegative number which may be used to reduce the number of\n computations. Default: 1/100th of the range of `x`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n Returns\n -------\n out: Object\n Object with ordered x-values and fitted values.\n\n Examples\n --------\n > var x = new Float64Array( 100 );\n > var y = new Float64Array( x.length );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = i;\n ... y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n ... }\n > var out = lowess( x, y );\n > var yhat = out.y;\n\n > var h = Plot( [ x, x ], [ y, yhat ] );\n > h.lineStyle = [ 'none', '-' ];\n > h.symbols = [ 'closed-circle', 'none' ];\n\n > h.view( 'window' );\n\n","lpad":"\nlpad( str, len[, pad] )\n Left pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = lpad( 'a', 5 )\n ' a'\n > out = lpad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = lpad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n pad, rpad\n","ltrim":"\nltrim( str )\n Trims whitespace from the beginning of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n See Also\n --------\n trim, rtrim\n","ltrimN":"\nltrimN( str, n[, chars] )\n Trims `n` characters from the beginning of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of characters to trim.\n\n chars: Array|string (optional)\n Characters to trim. Default: whitespace characters.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrimN( ' abc ', 2 )\n 'abc '\n > var out = ltrimN( '!!!abc!!!', 2, '!' )\n '!abc!!!'\n\n See Also\n --------\n rtrimN, trim","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common male first names.\n\n Examples\n --------\n > var list = MALE_FIRST_NAMES_EN()\n [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. 'Moby Word II.' .\n\n See Also\n --------\n FEMALE_FIRST_NAMES_EN\n","map":"\nmap( arr, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = map( arr, f )\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = map( arr, f );\n > var v = out.get( 1, 1 )\n 5\n\n\nmap.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n mapRight, reduce\n","map.assign":"\nmap.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n mapRight, reduce","map2":"\nmap2( x, y, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to a new array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Input arrays must be either both array-like objects or both ndarray-like\n objects.\n\n If input arrays are array-like objects, the arrays must have the same number\n of elements.\n\n If input arrays are ndarray-like objects, the arrays must be broadcast\n compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = map2( x, y, f )\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > x = array( x, { 'shape': [ 2, 3 ] } );\n > y = array( y, { 'shape': [ 2, 3 ] } );\n > out = map2( x, y, f );\n > var v = out.get( 1, 1 )\n 6\n\n\nmap2.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n map\n","map2.assign":"\nmap2.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n map","map2d":"\nmap2d( arr, fcn[, thisArg] )\n Applies a function to each nested element in an array of arrays and assigns\n the result to a nested element in a new array of arrays.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array of arrays.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\n > var out = map2d( arr, f );\n > out[ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map3d, map4d, map5d, reduce2d\n","map2Right":"\nmap2Right( x, y, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to a new array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Input arrays must be either both array-like objects or both ndarray-like\n objects.\n\n If input arrays are array-like objects, the arrays must have the same number\n of elements.\n\n If input arrays are ndarray-like objects, the arrays must be broadcast\n compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = map2Right( x, y, f )\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > x = array( x, { 'shape': [ 2, 3 ] } );\n > y = array( y, { 'shape': [ 2, 3 ] } );\n > out = map2Right( x, y, f );\n > var v = out.get( 1, 1 )\n 6\n\n\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2Right.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2Right.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n mapRight, map2\n","map2Right.assign":"\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2Right.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2Right.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n mapRight, map2","map3d":"\nmap3d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a three-dimensional nested\n array and assigns the result to a nested element in a new three-dimensional\n nested array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject>\n Input three-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>\n Three-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\n > var out = map3d( arr, f );\n > out[ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map4d, map5d\n","map4d":"\nmap4d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a four-dimensional nested array\n and assigns the result to a nested element in a new four-dimensional nested\n array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input four-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>>\n Four-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\n > var out = map4d( arr, f );\n > out[ 0 ][ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map3d, map5d\n","map5d":"\nmap5d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a five-dimensional nested array\n and assigns the result to a nested element in a new five-dimensional nested\n array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input five-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>>>\n Five-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\n > var out = map5d( arr, f );\n > out[ 0 ][ 0 ][ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ][ 0 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map3d, map4d\n","mapArguments":"\nmapArguments( fcn, clbk[, thisArg] )\n Returns a function that applies arguments to a provided function after\n transforming arguments according to a callback function.\n\n The callback function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > function clbk( v ) { return v * 2; };\n > var bar = mapArguments( foo, clbk );\n > var out = bar( 1, 2, 3 )\n [ 2, 4, 6 ]\n\n See Also\n --------\n filterArguments\n","mapFun":"\nmapFun( fcn, n[, thisArg] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n The invoked function is provided a single argument: the invocation index\n (zero-based).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n thisArg: any (optional)\n Function execution context.\n\n Returns\n -------\n out: Array\n Array of accumulated function return values.\n\n Examples\n --------\n > function fcn( i ) { return i; };\n > var arr = mapFun( fcn, 5 )\n [ 0, 1, 2, 3, 4 ]\n\n See Also\n --------\n mapFunAsync\n","mapFunAsync":"\nmapFunAsync( fcn, n, [options,] done )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n For each iteration, the provided function is invoked with two arguments:\n\n - index: invocation index (starting from zero).\n - next: callback to be invoked upon function completion.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: function result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n done: Function\n A callback invoked upon executing a provided function `n` times or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > mapFunAsync( fcn, 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Limit number of concurrent invocations:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'limit': 2 };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Sequential invocation:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'series': true };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun","mapKeys":"\nmapKeys( obj, transform )\n Maps keys from one object to a new object having the same values.\n\n The transform function is provided three arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n\n The value returned by a transform function should be a value which can be\n serialized as an object key.\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values specify the keys of the output object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapKeys( obj, transform )\n { 'a1': 1, 'b2': 2 }\n\n See Also\n --------\n mapValues\n","mapKeysAsync":"\nmapKeysAsync( obj, [options,] transform, done )\n Maps keys from one object to a new object having the same values.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n - next: a callback to be invoked after processing an object `key`.\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - key\n - next\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - key\n - value\n - next\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - key: transformed key.\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The key returned by a transform function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapKeysAsync( obj, transform, done )\n { 'a:1': 1, 'b:2': 2 }\n\n // Limit number of concurrent invocations:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n // Process sequentially:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync","mapReduce":"\nmapReduce( arr, initial, mapper, reducer[, thisArg] )\n Performs a map-reduce operation for each element in an array and returns the\n accumulated result.\n\n When invoked, the mapping function is provided three arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n When invoked, the reducing function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: result after applying the mapping function to the current array\n element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a single-pass map-reduce\n operation over the entire input ndarray (i.e., higher-order ndarray\n dimensions are flattened to a single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n mapper: Function\n Mapping function.\n\n reducer: Function\n Reducing function.\n\n thisArg: any (optional)\n Execution context for the reducing function.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f1 = naryFunction( base.abs, 1 );\n > var f2 = naryFunction( base.add, 2 );\n > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n > var out = mapReduce( arr, 0.0, f1, f2 )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapReduce( arr, 0.0, f1, f2 )\n 21.0\n\n See Also\n --------\n map, mapReduceRight, reduce\n","mapReduceRight":"\nmapReduceRight( arr, initial, mapper, reducer[, thisArg] )\n Performs a map-reduce operation for each element in an array while iterating\n from right to left and returns the accumulated result.\n\n When invoked, the mapping function is provided three arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n When invoked, the reducing function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: result after applying the mapping function to the current array\n element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a single-pass map-reduce\n operation over the entire input ndarray (i.e., higher-order ndarray\n dimensions are flattened to a single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n mapper: Function\n Mapping function.\n\n reducer: Function\n Reducing function.\n\n thisArg: any (optional)\n Execution context for the reducing function.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f1 = naryFunction( base.abs, 1 );\n > var f2 = naryFunction( base.add, 2 );\n > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n > var out = mapReduceRight( arr, 0.0, f1, f2 )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapReduceRight( arr, 0.0, f1, f2 )\n 21.0\n\n See Also\n --------\n mapRight, mapReduce, reduceRight\n","mapRight":"\nmapRight( arr, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = mapRight( arr, f )\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapRight( arr, f );\n > var v = out.get( 1, 1 )\n 5\n\n\nmapRight.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > mapRight.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > mapRight.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n map, reduce\n","mapRight.assign":"\nmapRight.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > mapRight.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > mapRight.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n map, reduce","mapValues":"\nmapValues( obj, transform )\n Maps values from one object to a new object having the same keys.\n\n The transform function is provided three arguments:\n\n - value: object value corresponding to `key`.\n - key: object key.\n - obj: the input object.\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( value, key ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapValues( obj, transform )\n { 'a': 'a1', 'b': 'b2' }\n\n See Also\n --------\n mapKeys, omitBy, pickBy\n","mapValuesAsync":"\nmapValuesAsync( obj, [options,] transform, done )\n Maps values from one object to a new object having the same keys.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - value: object value corresponding to `key`.\n - key: object key.\n - obj: the input object.\n - next: a callback to be invoked after processing an object `value`.\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - value\n - next\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - value\n - key\n - next\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - value: transformed value.\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapValuesAsync( obj, transform, done )\n { 'a': 'a:1', 'b': 'b:2' }\n\n // Limit number of concurrent invocations:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n // Process sequentially:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues","maskArguments":"\nmaskArguments( fcn, mask[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a specified mask.\n\n Only those arguments having a truthy mask value are applied to a provided\n function.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n mask: ArrayLikeObject\n Mask array.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > var bar = maskArguments( foo, [ 1, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n filterArguments, rejectArguments, reorderArguments, reverseArguments\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n\n Examples\n --------\n > MAX_ARRAY_LENGTH\n 4294967295\n\n See Also\n --------\n MAX_TYPED_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n\n Examples\n --------\n > MAX_TYPED_ARRAY_LENGTH\n 9007199254740991\n\n See Also\n --------\n MAX_ARRAY_LENGTH\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x, shape )\n Broadcasts an ndarray to a specified shape if and only if the specified\n shape differs from the provided ndarray's shape.\n\n If a provided ndarray has the same shape as the specified shape, the\n function returns the provided ndarray.\n\n If a provided ndarray has a different (broadcast compatible) shape than the\n specified shape, the function returns a new *read-only* ndarray view of the\n provided ndarray's data. The view is typically *not* contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to the input ndarray may affect multiple elements. If you need to\n write to the input ndarray, copy the input ndarray before broadcasting.\n\n The function throws an error if a provided ndarray is incompatible with a\n provided shape.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n shape: ArrayLikeObject\n Desired shape.\n\n Returns\n -------\n out: ndarray\n Broadcasted array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\n \n > sh = y.shape\n [ 3, 2, 2 ]\n > var v = y.get( 0, 0, 0 )\n 1\n > v = y.get( 0, 0, 1 )\n 2\n > v = y.get( 0, 1, 0 )\n 3\n > v = y.get( 0, 1, 1 )\n 4\n > v = y.get( 1, 0, 0 )\n 1\n > v = y.get( 1, 1, 0 )\n 3\n > v = y.get( 2, 0, 0 )\n 1\n > v = y.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, ndarray, broadcastArray, maybeBroadcastArrays\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays )\n Broadcasts ndarrays to a common shape.\n\n The function supports two (mutually exclusive) means of providing ndarray\n arguments:\n\n 1. Providing a single array containing ndarray arguments.\n 2. Providing ndarray arguments as separate arguments.\n\n If a provided ndarray has a shape matching the common shape, the function\n returns the provided ndarray.\n\n If a provided ndarray has a different (broadcast compatible) shape than the\n common shape, the function returns a new *read-only* ndarray view of the\n provided ndarray's data. The view is typically *not* contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to a view may affect multiple elements. If you need to write to an\n input ndarray, copy the input ndarray before broadcasting.\n\n The function throws an error if a provided broadcast-incompatible ndarrays.\n\n Parameters\n ----------\n arrays: ...ndarray|ArrayLikeObject\n Array arguments.\n\n Returns\n -------\n out: Array\n Broadcasted arrays.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = ndzeros( [ 3, 2, 2 ] )\n \n > var out = maybeBroadcastArrays( [ x, y ] )\n [ , ]\n\n // Retrieve the broadcasted \"x\" array:\n > var bx = out[ 0 ]\n \n > sh = bx.shape\n [ 3, 2, 2 ]\n\n // Retrieve broadcasted elements...\n > var v = bx.get( 0, 0, 0 )\n 1\n > v = bx.get( 0, 0, 1 )\n 2\n > v = bx.get( 0, 1, 0 )\n 3\n > v = bx.get( 0, 1, 1 )\n 4\n > v = bx.get( 1, 0, 0 )\n 1\n > v = bx.get( 1, 1, 0 )\n 3\n > v = bx.get( 2, 0, 0 )\n 1\n > v = bx.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, ndarray, broadcastArrays, maybeBroadcastArray\n","memoize":"\nmemoize( fcn[, hashFunction] )\n Returns a memoized function.\n\n The function does not set the `length` property of the returned function.\n Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n The function serializes provided arguments as a string and stores results\n using the string as an identifier. To use a custom hash function, provide a\n hash function argument.\n\n Parameters\n ----------\n fcn: Function\n Function to memoize.\n\n hashFunction: Function (optional)\n Function to map a set of arguments to a single value identifying that\n set.\n\n Returns\n -------\n out: Function\n Memoized function.\n\n Examples\n --------\n > function factorial( n ) {\n ... var prod;\n ... var i;\n ... prod = 1;\n ... for ( i = n; i > 1; i-- ) {\n ... prod *= i;\n ... }\n ... return prod;\n ... };\n > var memoized = memoize( factorial );\n > var v = memoized( 5 )\n 120\n > v = memoized( 5 )\n 120\n\n","merge":"\nmerge( target, ...source )\n Merges objects into a target object.\n\n The target object is mutated.\n\n Only plain objects are merged and extended. Other values/types are either\n deep copied or assigned.\n\n Support for deep merging class instances is inherently fragile.\n\n `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n Functions are not deep copied.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n source: ...Object\n Source objects (i.e., objects to be merged into the target object).\n\n Returns\n -------\n out: Object\n Merged (target) object.\n\n Examples\n --------\n > var target = { 'a': 'beep' };\n > var source = { 'a': 'boop', 'b': 'bap' };\n > var out = merge( target, source )\n { 'a': 'boop', 'b': 'bap' }\n > var bool = ( out === target )\n true\n\n\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy\n","merge.factory":"\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var ms = days * MILLISECONDS_IN_DAY\n 271296000\n\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var ms = hrs * MILLISECONDS_IN_HOUR\n 11304000\n\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var ms = mins * MILLISECONDS_IN_MINUTE\n 188400\n\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var secs = 3.14;\n > var ms = secs * MILLISECONDS_IN_SECOND\n 3140\n\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var weeks = 3.14;\n > var ms = weeks * MILLISECONDS_IN_WEEK\n 1899072000\n\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n\n Data includes the following:\n\n - army: army size.\n - cities: cities.\n - labels: map labels.\n - temperature: temperature during the army's return from Russia.\n - rivers: river data.\n\n Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n to convert to Celsius.\n\n River data is formatted as GeoJSON.\n\n River data is incomplete, with portions of rivers missing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n Minard's data.\n\n Examples\n --------\n > var data = MINARD_NAPOLEONS_MARCH();\n > var army = data.army\n [...]\n > var cities = data.cities\n [...]\n > var labels = data.labels\n [...]\n > var rivers = data.rivers\n {...}\n > var t = data.temperature\n [...]\n\n References\n ----------\n - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n Ecole nationale des ponts et chaussées.\n - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n York. doi:10.1007/0-387-28695-0.\n\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var mins = days * MINUTES_IN_DAY\n 4521.6\n\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var mins = hrs * MINUTES_IN_HOUR\n 188.4\n\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var mins = wks * MINUTES_IN_WEEK\n 31651.2\n\n","minutesInMonth":"\nminutesInMonth( [month[, year]] )\n Returns the number of minutes in a month.\n\n By default, the function returns the number of minutes in the current month\n of the current year (according to local time). To determine the number of\n minutes for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Minutes in a month.\n\n Examples\n --------\n > var num = minutesInMonth()\n \n > num = minutesInMonth( 2 )\n \n > num = minutesInMonth( 2, 2016 )\n 41760\n > num = minutesInMonth( 2, 2017 )\n 40320\n\n // Other ways to supply month:\n > num = minutesInMonth( 'feb', 2016 )\n 41760\n > num = minutesInMonth( 'february', 2016 )\n 41760\n\n See Also\n --------\n minutesInYear\n","minutesInYear":"\nminutesInYear( [value] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n\n By default, the function returns the number of minutes in the current year\n (according to local time). To determine the number of minutes for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of minutes in a year.\n\n Examples\n --------\n > var num = minutesInYear()\n \n > num = minutesInYear( 2016 )\n 527040\n > num = minutesInYear( 2017 )\n 525600\n\n See Also\n --------\n minutesInMonth\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n\n Each array element has the following fields:\n\n - chapter: book chapter (number or identifier).\n - title: chapter title (if available; otherwise, empty).\n - text: chapter text.\n\n Returns\n -------\n out: Array\n Book text.\n\n Examples\n --------\n > var data = MOBY_DICK()\n [ {...}, {...}, ... ]\n\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n\n Returns\n -------\n out: Array\n List of month names.\n\n Examples\n --------\n > var list = MONTH_NAMES_EN()\n [ 'January', 'February', 'March', 'April', ... ]\n\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var yrs = 3.14;\n > var mons = yrs * MONTHS_IN_YEAR\n 37.68\n\n","moveProperty":"\nmoveProperty( source, prop, target )\n Moves a property from one object to another object.\n\n The property is deleted from the source object and the property's descriptor\n is preserved during transfer.\n\n If a source property is not configurable, the function throws an error, as\n the property cannot be deleted from the source object.\n\n Parameters\n ----------\n source: Object\n Source object.\n\n prop: string\n Property to move.\n\n target: Object\n Target object.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether operation was successful.\n\n Examples\n --------\n > var obj1 = { 'a': 'b' };\n > var obj2 = {};\n > var bool = moveProperty( obj1, 'a', obj2 )\n true\n > bool = moveProperty( obj1, 'c', obj2 )\n false\n\n","MultiSlice":"\nMultiSlice( ...slice )\n Returns a multi-slice.\n\n Parameters\n ----------\n ...slice: Slice|integer|null|undefined\n Slice arguments.\n\n Returns\n -------\n s: MultiSlice\n MultiSlice instance.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n\n\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n\n Returns\n -------\n ndims: integer\n Number of slice dimensions.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.ndims\n 3\n\n\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n\n Returns\n -------\n data: Array\n Slice data.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.data\n [ 2, , 1 ]\n\n\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n\n Returns\n -------\n str: string\n Serialized multi-slice string.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.toString()\n 'MultiSlice(2,Slice(2,10,null),1)'\n\n\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 2, 10, 1 );\n > var ms = new MultiSlice( 2, s );\n > ms.toJSON()\n {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n See Also\n --------\n ndarray, Slice\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n\n Returns\n -------\n ndims: integer\n Number of slice dimensions.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.ndims\n 3","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n\n Returns\n -------\n data: Array\n Slice data.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.data\n [ 2, , 1 ]","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n\n Returns\n -------\n str: string\n Serialized multi-slice string.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.toString()\n 'MultiSlice(2,Slice(2,10,null),1)'","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 2, 10, 1 );\n > var ms = new MultiSlice( 2, s );\n > ms.toJSON()\n {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n See Also\n --------\n ndarray, Slice","namedtypedtuple":"\nnamedtypedtuple( fields[, options] )\n Returns a named typed tuple factory.\n\n Named tuples assign a property name, and thus a meaning, to each position in\n a tuple and allow for more readable, self-documenting code.\n\n Named typed tuples can be used wherever typed arrays are used, with the\n added benefit that they allow accessing fields by both field name and\n position index.\n\n Named typed tuples may be one the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n fields: Array\n Field (property) names.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Default tuple data type. If a data type is not provided to a named typed\n tuple factory, this option specifies the underlying tuple data type.\n Default: 'float64'.\n\n options.name: string (optional)\n Tuple name. Default: 'tuple'.\n\n Returns\n -------\n factory: Function\n Named typed tuple factory.\n\n Examples\n --------\n > var opts = {};\n > opts.name = 'Point';\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var tuple = factory();\n\n\nfactory()\n Returns a named typed tuple of the default data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory();\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory( dtype )\n Returns a named typed tuple of the specified data type.\n\n Parameters\n ----------\n dtype: string\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( 'int32' );\n > p.x\n 0\n > p.y\n 0\n > p[ 0 ]\n 0\n > p[ 1 ]\n 0\n\n\nfactory( typedarray[, dtype] )\n Creates a named typed tuple from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a named typed tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var f = namedtypedtuple( [ 'x', 'y' ] );\n > var p = f( new Float64Array( [ 1.0, -1.0 ] ) );\n > p.x\n 1.0\n > p.y\n -1.0\n > p[ 0 ]\n 1.0\n > p[ 1 ]\n -1.0\n\n\nfactory( obj[, dtype] )\n Creates a named typed tuple from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a named typed\n tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( [ 1, -1 ], 'int32' );\n > p.x\n 1\n > p.y\n -1\n > p[ 0 ]\n 1\n > p[ 1 ]\n -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n Returns a named typed tuple view of an ArrayBuffer.\n\n The view length equals the number of tuple fields.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first tuple element.\n Default: 0.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var buf = new ArrayBuffer( 16 );\n > var p = factory( buf, 4, 'float32' );\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n Creates a new named typed tuple from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n - field: tuple field.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of tuple elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > function mapFcn( v ) { return v * 2.0; };\n > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n Creates a new named typed tuple from an object containing tuple fields.\n\n A callback is provided the following arguments:\n\n - value: source object tuple field value.\n - field: source object tuple field name.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n map: Function (optional)\n Callback to invoke for each source object tuple field.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.of( element0[, element1[, ...elementN]] )\n Creates a new named typed tuple from a variable number of arguments.\n\n The number of arguments *must* equal the number of tuple fields.\n\n Parameters\n ----------\n element0: number\n Tuple element.\n\n element1: number (optional)\n Tuple element.\n\n elementN: ...number (optional)\n Tuple elements.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.of( 2.0, -2.0 );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n Size (in bytes) of each tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.BYTES_PER_ELEMENT\n 8\n\n\ntuple.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.buffer\n \n\n\ntuple.byteLength\n Length (in bytes) of the tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteLength\n 16\n\n\ntuple.byteOffset\n Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteOffset\n 0\n\n\ntuple.length\n Tuple length (i.e., number of elements).\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.length\n 2\n\n\ntuple.name\n Tuple name.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.name\n 'Point'\n\n\ntuple.fields\n Returns the list of tuple fields.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fields\n [ 'x', 'y' ]\n\n\ntuple.orderedFields\n Returns the list of tuple fields in index order.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.sort();\n > p[ 0 ]\n -1.0\n > p.fields\n [ 'x', 'y' ]\n > p.orderedFields\n [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n Copies a sequence of elements within the tuple starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > p.copyWithin( 3, 0, 2 );\n > p.w\n 2.0\n > p.v\n -2.0\n\n\ntuple.entries()\n Returns an iterator for iterating over tuple key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple key-value pairs.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.entries();\n > it.next().value\n [ 0, 'x', 1.0 ]\n > it.next().value\n [ 1, 'y', -1.0 ]\n > it.next().done\n true\n\n\ntuple.every( predicate[, thisArg] )\n Tests whether all tuple elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all tuple elements pass.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > p.every( predicate )\n false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n Returns the field of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var f = p.fieldOf( 2.0 )\n undefined\n > f = p.fieldOf( -1.0 )\n 'z'\n\n\ntuple.fill( value[, start[, end]] )\n Fills a tuple from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last tuple element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fill( 2.0 );\n > p.x\n 2.0\n > p.y\n 2.0\n\n\ntuple.filter( predicate[, thisArg] )\n Creates a new tuple which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n If a predicate function does not return a truthy value for any tuple\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters tuple elements. If a predicate function\n returns a truthy value, a tuple element is included in the output tuple;\n otherwise, a tuple element is not included in the output tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var p2 = p1.filter( predicate );\n > p2.fields\n [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n Returns the first tuple element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = p.find( predicate )\n -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n Returns the field of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var f = p.findField( predicate )\n 'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n Returns the index of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = p.findIndex( predicate )\n 2\n\n\ntuple.forEach( fcn[, thisArg] )\n Invokes a callback for each tuple element.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each tuple element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > var str = ' ';\n > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n > p.forEach( fcn );\n > str\n ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether a tuple includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a tuple includes a search element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var bool = p.includes( 2.0 )\n false\n > bool = p.includes( -1.0 )\n true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n Returns the index of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var idx = p.indexOf( 2.0 )\n -1\n > idx = p.indexOf( -1.0 )\n 2\n\n\ntuple.ind2key( ind )\n Converts a tuple index to a field name.\n\n If provided an out-of-bounds index, the method returns `undefined`.\n\n Parameters\n ----------\n ind: integer\n Tuple index. If less than zero, the method resolves the index relative\n to the last tuple element.\n\n Returns\n -------\n field: string|undefined\n Field name.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.ind2key( 1 )\n 'y'\n > p.ind2key( 100 )\n undefined\n\n\ntuple.join( [separator] )\n Serializes a tuple by joining all tuple elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating tuple elements. Default: ','.\n\n Returns\n -------\n str: string\n Tuple serialized as a string.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > p.join( '|' )\n '1|0|-1'\n\n\ntuple.keys()\n Returns an iterator for iterating over tuple keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple keys.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.keys();\n > it.next().value\n [ 0, 'x' ]\n > it.next().value\n [ 1, 'y' ]\n > it.next().done\n true\n\n\ntuple.key2ind( field )\n Converts a field name to a tuple index.\n\n If provided an unknown field name, the method returns `-1`.\n\n Parameters\n ----------\n field: string\n Tuple field name.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.key2ind( 'y' )\n 1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n Returns the field of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var f = p.lastFieldOf( 2.0 )\n undefined\n > f = p.lastFieldOf( 0.0 )\n 'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = p.lastIndexOf( 2.0 )\n -1\n > idx = p.lastIndexOf( 0.0 )\n 3\n\n\ntuple.map( fcn[, thisArg] )\n Maps each tuple element to an element in a new tuple.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n Parameters\n ----------\n fcn: Function\n Function which maps tuple elements to elements in the new tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var p2 = p1.map( fcn );\n > p2.x\n 2.0\n > p2.y\n 0.0\n > p2.z\n -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first tuple element as the first argument and the second tuple\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduce( fcn, 0.0 )\n 2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last tuple element as the first argument and the second-to-last\n tuple element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduceRight( fcn, 0.0 )\n 2.0\n\n\ntuple.reverse()\n Reverses a tuple *in-place*.\n\n This method mutates the tuple on which the method is invoked.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.x\n 1.0\n > p.reverse();\n > p[ 0 ]\n -1.0\n > p.x\n 1.0\n\n\ntuple.set( arr[, offset] )\n Sets tuple elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing tuple values to set.\n\n offset: integer (optional)\n Tuple index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 1 ]\n 0.0\n > p.y\n 0.0\n > p.set( [ -2.0, 2.0 ], 1 );\n > p[ 1 ]\n -2.0\n > p.y\n -2.0\n > p[ 2 ]\n 2.0\n > p.z\n 2.0\n\n\ntuple.slice( [begin[, end]] )\n Copies tuple elements to a new tuple with the same underlying data type as\n the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > p1.fields\n [ 'x', 'y', 'z' ]\n > var p2 = p1.slice( 1 );\n > p2.fields\n [ 'y', 'z' ]\n > p2.y\n 0.0\n > p2.z\n -1.0\n\n\ntuple.some( predicate[, thisArg] )\n Tests whether at least one tuple element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one tuple element passes.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > p.some( predicate )\n true\n\n\ntuple.sort( [compareFunction] )\n Sorts a tuple *in-place*.\n\n Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n before and after sorting will always return the same tuple element. However,\n this behavior is generally not true when accessing tuple elements according\n to tuple index. In summary, sorting affects index order but not field\n assignments.\n\n The comparison function is provided two tuple elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the tuple on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > p.sort();\n > p.orderedFields\n [ 'v', 'y', 'z', 'x', 'w' ]\n > p[ 0 ]\n -2.0\n > p[ 1 ]\n -1.0\n > p.y\n -1.0\n > p.key2ind( 'x' )\n 3\n > p[ 3 ]\n 1.0\n\n\ntuple.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n arr: TypedArray\n A new typed array view.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr = p.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n > arr.length\n 3\n\n\ntuple.subtuple( [begin[, end]] )\n Creates a new named typed tuple over the same underlying ArrayBuffer and\n with the same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var p2 = p1.subtuple( 2 );\n > p2.fields\n [ 'z', 'w', 'v' ]\n > p2[ 0 ]\n 0.0\n > p2.z\n 0.0\n > p2[ 1 ]\n 2.0\n > p2.w\n 2.0\n > p2[ 2 ]\n -2.0\n > p2.v\n -2.0\n > p2.length\n 3\n\n\ntuple.toJSON()\n Serializes a tuple as JSON.\n\n Returns\n -------\n obj: Object\n A tuple JSON representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toJSON()\n { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n Serializes a tuple as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n > p.toLocaleString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.toString()\n Serializes a tuple as a string.\n\n Returns\n -------\n str: string\n A tuple string representation.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n Returns an iterator for iterating over tuple elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple elements.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n See Also\n --------\n typedarray\n","NAN":"\nNAN\n Double-precision floating-point NaN.\n\n Examples\n --------\n > NAN\n NaN\n\n See Also\n --------\n FLOAT32_NAN\n","naryFunction":"\nnaryFunction( fcn, arity[, thisArg] )\n Returns a function that applies a specified number of arguments to a\n provided function.\n\n The returned function *always* invokes the wrapped function with a specified\n number of arguments, even when the returned function is provided fewer\n arguments.\n\n The value for the missing arguments is equal to `undefined`.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n arity: integer\n Number of arguments.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = naryFunction( foo, 2 );\n > var out = bar( 1, 2, 3 )\n [ 1, 2, undefined ]\n\n See Also\n --------\n maskArguments, pickArguments\n","nativeClass":"\nnativeClass( value )\n Returns a string value indicating a specification defined classification of\n an object.\n\n The function is *not* robust for ES2015+ environments. In ES2015+,\n `Symbol.toStringTag` allows overriding the default description of an object.\n While measures are taken to uncover the default description, such measures\n can be thwarted. While this function remains useful for type-checking, be\n aware that value impersonation is possible. Where possible, prefer functions\n tailored to checking for particular value types, as specialized functions\n are better equipped to address `Symbol.toStringTag`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n String value indicating a specification defined classification of the\n input value.\n\n Examples\n --------\n > var str = nativeClass( 'a' )\n '[object String]'\n > str = nativeClass( 5 )\n '[object Number]'\n > function Beep(){};\n > str = nativeClass( new Beep() )\n '[object Object]'\n\n See Also\n --------\n constructorName, typeOf\n","ndarray":"\nndarray( dtype, buffer, shape, strides, offset, order[, options] )\n Returns an ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n ndarray: ndarray\n ndarray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nndarray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, FancyArray\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","ndarray.prototype.data":"\nndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","ndarray.prototype.flags":"\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","ndarray.prototype.length":"\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","ndarray.prototype.offset":"\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","ndarray.prototype.order":"\nndarray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","ndarray.prototype.shape":"\nndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","ndarray.prototype.strides":"\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","ndarray.prototype.get":"\nndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","ndarray.prototype.iget":"\nndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","ndarray.prototype.set":"\nndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","ndarray.prototype.iset":"\nndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","ndarray.prototype.toString":"\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, FancyArray","ndarray2array":"\nndarray2array( x )\n Converts an ndarray to a generic array.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: Array|Array\n Generic array (which may include nested arrays).\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarray2array( arr )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n array, ndarray, ndarray2json\n","ndarray2fancy":"\nndarray2fancy( x[, options] )\n Converts an ndarray to an object supporting fancy indexing.\n\n An ndarray supporting fancy indexing is an ndarray which supports slicing\n via indexing expressions for both retrieval and assignment.\n\n A fancy ndarray can be consumed by any API which supports ndarray instances.\n\n A fancy ndarray shares the *same* data as the provided input ndarray. Hence,\n any mutations to the returned ndarray will affect the underlying input\n ndarray and vice versa.\n\n A fancy ndarray supports indexing using positive and negative integers (both\n numeric literals and strings), Slice and MultiSlice instances, subsequence\n expressions, mask ndarrays, boolean ndarrays, and integer ndarrays.\n\n A fancy ndarray supports all properties and methods of the input ndarray,\n and, thus, a fancy ndarray can be consumed by any API which supports\n ndarray-like objects.\n\n For operations returning a new ndarray (e.g., when slicing or invoking an\n instance method), a fancy ndarray returns a new fancy ndarray having the\n same configuration as specified by provided options.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on ndarray views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use and\n scripting. For performance critical applications, prefer equivalent\n functional APIs supporting ndarray instances.\n\n Fancy ndarrays support broadcasting in which assigned scalars and ndarrays\n are repeated (without additional memory allocation) to match the dimensions\n of a target ndarray instance.\n\n When assigning ndarrays to slices, the ndarray on the right-hand-side must\n be broadcast-compatible with dimensions implied by the slice.\n\n Fancy ndarrays support (mostly) safe casts (i.e., any cast which can be\n performed without overflow or loss of precision, with the exception of\n floating-point ndarrays which are also allowed to downcast from higher\n precision to lower precision).\n\n When attempting to perform an unsafe cast, fancy ndarrays will raise an\n exception.\n\n When assigning a real-valued scalar to a complex number ndarray, a fancy\n ndarray will cast the real-valued scalar to a complex number argument having\n an imaginary component equal to zero.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n out: ndarray\n Output ndarray supporting fancy indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Convert to a fancy ndarray:\n > var arr = ndarray2fancy( x );\n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nndarray2fancy.factory( [options] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an ndarray to an object supporting fancy\n indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Create a function for converting ndarrays to fancy ndarrays:\n > var f = ndarray2fancy.factory();\n\n // Convert the normal ndarray to a fancy ndarray:\n > var y = f( x );\n\n\nndarray2fancy.idx( x[, options] )\n Wraps a provided ndarray as an ndarray index object.\n\n For documentation and usage, see `ndindex`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndarrayIndex\n ndarray index instance.\n\n Examples\n --------\n > var opts = { 'dtype': 'int32' };\n > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n > var arr = array( buf, opts );\n > var idx = ndarray2fancy.idx( arr );\n\n See Also\n --------\n array2fancy, array, ndarray, FancyArray\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an ndarray to an object supporting fancy\n indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Create a function for converting ndarrays to fancy ndarrays:\n > var f = ndarray2fancy.factory();\n\n // Convert the normal ndarray to a fancy ndarray:\n > var y = f( x );","ndarray2fancy.idx":"\nndarray2fancy.idx( x[, options] )\n Wraps a provided ndarray as an ndarray index object.\n\n For documentation and usage, see `ndindex`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndarrayIndex\n ndarray index instance.\n\n Examples\n --------\n > var opts = { 'dtype': 'int32' };\n > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n > var arr = array( buf, opts );\n > var idx = ndarray2fancy.idx( arr );\n\n See Also\n --------\n array2fancy, array, ndarray, FancyArray","ndarray2json":"\nndarray2json( x )\n Serializes an ndarray as a JSON object.\n\n This function does *not* serialize data outside of the buffer region defined\n by the ndarray view.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Object\n JSON object.\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarray2json( arr )\n {...}\n\n See Also\n --------\n array, ndarray, ndarray2array\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n\n The output array contains the following modes:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'mostly-safe': allow \"safe\" casts and, for floating-point data types,\n downcasts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers and\n floats).\n\n Returns\n -------\n out: Array\n List of ndarray casting modes.\n\n Examples\n --------\n > var out = ndarrayCastingModes()\n [ 'none', 'equiv', 'safe', 'mostly-safe', 'same-kind', 'unsafe' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x )\n Returns the underlying data buffer of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: ArrayLikeObject\n Underlying data buffer.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n \n\n See Also\n --------\n array, ndarray, ndarrayDataType\n","ndarrayDataType":"\nndarrayDataType( x )\n Returns the data type of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n dt: string\n Data type.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n 'float64'\n\n See Also\n --------\n array, ndarray, ndarrayDataTypes\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind] )\n Returns a list of ndarray data types.\n\n When not provided a data type \"kind\", the function returns an array\n containing the following data types:\n\n - float16: half-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex32: half-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int8: signed 8-bit integers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - binary: binary.\n\n The function supports the following data type \"kinds\":\n\n - floating_point: floating-point data types.\n - real_floating_point: real-valued floating-point data types.\n - complex_floating_point: complex-valued floating-point data types.\n - boolean: boolean data types.\n - integer: integer data types.\n - signed_integer: signed integer data types.\n - unsigned_integer: unsigned integer data types.\n - real: real-valued data types.\n - numeric: numeric data types.\n - typed: typed data types.\n - integer_index: integer index data types.\n - boolean_index: boolean index data types.\n - mask_index: mask index data types.\n - typed_index: typed index data types.\n - index: index data types.\n - all: all data types.\n\n Additionally, the function supports extending the \"kinds\" listed above by\n appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n Parameters\n ----------\n kind: string (optional)\n Data type kind.\n\n Returns\n -------\n out: Array\n List of ndarray data types.\n\n Examples\n --------\n > var out = ndarrayDataTypes()\n [...]\n > out = ndarrayDataTypes( 'floating_point' )\n [...]\n > out = ndarrayDataTypes( 'floating_point_and_generic' )\n [...]\n\n\nndarrayDataTypes.binary\n Read-only property returning a data type instance representing a binary data\n type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.binary\n \n\n\nndarrayDataTypes.boolean\n Read-only property returning a data type instance representing a boolean\n data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.boolean\n \n\n\nndarrayDataTypes.complex32\n Read-only property returning a data type instance representing a half-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex32\n \n\n\nndarrayDataTypes.complex64\n Read-only property returning a data type instance representing a single-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex64\n \n\n\nndarrayDataTypes.complex128\n Read-only property returning a data type instance representing a double-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex128\n \n\n\nndarrayDataTypes.float16\n Read-only property returning a data type instance representing a half-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float16\n \n\n\nndarrayDataTypes.float32\n Read-only property returning a data type instance representing a single-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float32\n \n\n\nndarrayDataTypes.float64\n Read-only property returning a data type instance representing a double-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float64\n \n\n\nndarrayDataTypes.generic\n Read-only property returning a data type instance representing a \"generic\"\n data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.generic\n \n\n\nndarrayDataTypes.int8\n Read-only property returning a data type instance representing a signed\n 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int8\n \n\n\nndarrayDataTypes.int16\n Read-only property returning a data type instance representing a signed\n 16-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int16\n \n\n\nndarrayDataTypes.int32\n Read-only property returning a data type instance representing a signed\n 32-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int32\n \n\n\nndarrayDataTypes.uint8\n Read-only property returning a data type instance representing an unsigned\n 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint8\n \n\n\nndarrayDataTypes.uint8c\n Read-only property returning a data type instance representing an unsigned\n clamped 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint8c\n \n\n\nndarrayDataTypes.uint16\n Read-only property returning a data type instance representing an unsigned\n 16-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint16\n \n\n\nndarrayDataTypes.uint32\n Read-only property returning a data type instance representing an unsigned\n 32-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint32\n \n\n See Also\n --------\n arrayDataTypes, array, ndarray, typedarrayDataTypes\n","ndarrayDataTypes.binary":"\nndarrayDataTypes.binary\n Read-only property returning a data type instance representing a binary data\n type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.binary\n ","ndarrayDataTypes.boolean":"\nndarrayDataTypes.boolean\n Read-only property returning a data type instance representing a boolean\n data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.boolean\n ","ndarrayDataTypes.complex32":"\nndarrayDataTypes.complex32\n Read-only property returning a data type instance representing a half-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex32\n ","ndarrayDataTypes.complex64":"\nndarrayDataTypes.complex64\n Read-only property returning a data type instance representing a single-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex64\n ","ndarrayDataTypes.complex128":"\nndarrayDataTypes.complex128\n Read-only property returning a data type instance representing a double-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex128\n ","ndarrayDataTypes.float16":"\nndarrayDataTypes.float16\n Read-only property returning a data type instance representing a half-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float16\n ","ndarrayDataTypes.float32":"\nndarrayDataTypes.float32\n Read-only property returning a data type instance representing a single-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float32\n ","ndarrayDataTypes.float64":"\nndarrayDataTypes.float64\n Read-only property returning a data type instance representing a double-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float64\n ","ndarrayDataTypes.generic":"\nndarrayDataTypes.generic\n Read-only property returning a data type instance representing a \"generic\"\n data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.generic\n ","ndarrayDataTypes.int8":"\nndarrayDataTypes.int8\n Read-only property returning a data type instance representing a signed\n 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int8\n ","ndarrayDataTypes.int16":"\nndarrayDataTypes.int16\n Read-only property returning a data type instance representing a signed\n 16-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int16\n ","ndarrayDataTypes.int32":"\nndarrayDataTypes.int32\n Read-only property returning a data type instance representing a signed\n 32-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int32\n ","ndarrayDataTypes.uint8":"\nndarrayDataTypes.uint8\n Read-only property returning a data type instance representing an unsigned\n 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint8\n ","ndarrayDataTypes.uint8c":"\nndarrayDataTypes.uint8c\n Read-only property returning a data type instance representing an unsigned\n clamped 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint8c\n ","ndarrayDataTypes.uint16":"\nndarrayDataTypes.uint16\n Read-only property returning a data type instance representing an unsigned\n 16-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint16\n ","ndarrayDataTypes.uint32":"\nndarrayDataTypes.uint32\n Read-only property returning a data type instance representing an unsigned\n 32-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint32\n \n\n See Also\n --------\n arrayDataTypes, array, ndarray, typedarrayDataTypes","ndarrayDispatch":"\nndarrayDispatch( fcns, types, data, nargs, nin, nout )\n Returns an ndarray function interface which performs multiple dispatch.\n\n An ndarray function interface has the following signature:\n\n f( x, y, ... )\n\n where\n\n - x: ndarray.\n - y: ndarray.\n - ...: additional ndarrays.\n\n The number of parameters is derived from `nargs`, the number of input\n ndarrays is derived from `nin`, and the number of output ndarrays is derived\n from `nout`.\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of ndarray functions. An ndarray function should have the following\n signature:\n\n f( arrays, data )\n\n where\n\n - arrays: array containing input and output ndarrays.\n - data: ndarray function data (e.g., a callback).\n\n For convenience, a single ndarray function may be provided which will be\n invoked whenever the ndarray argument data types match a sequence of\n types in `types`. Providing a single ndarray function is particularly\n convenient for the case where, regardless of array data types,\n traversing arrays remains the same, but the ndarray function `data`\n differs (e.g., callbacks which differ based on the array data types).\n\n types: ArrayLikeObject\n One-dimensional list of ndarray argument data types.\n\n data: ArrayLikeObject|null\n ndarray function data (e.g., callbacks). If `null`, a returned ndarray\n function interface does **not** provide a `data` argument to an invoked\n ndarray function.\n\n nargs: integer\n Total number of ndarray function interface arguments.\n\n nin: integer\n Number of input ndarrays.\n\n nout: integer\n Number of output ndarrays.\n\n Returns\n -------\n fcn: Function\n ndarray function interface.\n\n Examples\n --------\n // Define ndarray argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of ndarray function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create an ndarray function interface for applying unary callbacks:\n > var f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\n\n // Create an input ndarray:\n > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n // Create an output ndarray:\n > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n // Compute the element-wise absolute value:\n > f( x, y );\n > ybuf\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n array, ndarray\n","ndarrayFlag":"\nndarrayFlag( x, name )\n Returns a specified flag for a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n name: string|symbol\n Flag name.\n\n Returns\n -------\n out: any\n Flag value.\n\n Examples\n --------\n > var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n \n\n See Also\n --------\n array, ndarray, ndarrayFlags\n","ndarrayFlags":"\nndarrayFlags( x )\n Returns the flags of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Object\n Flags.\n\n Examples\n --------\n > var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n {...}\n\n See Also\n --------\n array, ndarray, ndarrayFlag\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n\n The output array contains the following modes:\n\n - throw: specifies that a function should throw an error when an index is\n outside a restricted interval.\n - normalize: specifies that a function should normalize negative indices and\n throw an error when an index is outside a restricted interval.\n - wrap: specifies that a function should wrap around an index using modulo\n arithmetic.\n - clamp: specifies that a function should set an index less than zero to\n zero (minimum index) and set an index greater than a maximum index value to\n the maximum possible index.\n\n Returns\n -------\n out: Array\n List of ndarray index modes.\n\n Examples\n --------\n > var out = ndarrayIndexModes()\n [ 'throw', 'normalize', 'clamp', 'wrap' ]\n\n See Also\n --------\n array, ndarray\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x[, options] )\n Converts an ndarray-like object to an ndarray.\n\n If provided a read-only ndarray, the function returns a read-only ndarray.\n\n Parameters\n ----------\n x: ndarrayLike\n Input ndarray-like object.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarraylike2ndarray( arr )\n \n\n See Also\n --------\n array, ndarray, ndemptyLike, ndzerosLike\n","ndarrayMinDataType":"\nndarrayMinDataType( value )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n ndarray data type.\n\n Examples\n --------\n > var dt = ndarrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = ndarrayMinDataType( 3 )\n 'uint8'\n > dt = ndarrayMinDataType( -3 )\n 'int8'\n > dt = ndarrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast and, for floating-point data types, can be downcast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be cast.\n\n Examples\n --------\n > var out = ndarrayMostlySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts, ndarraySameKindCasts\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype] )\n Returns the next larger ndarray data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = ndarrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayOffset":"\nndarrayOffset( x )\n Returns the index offset specifying the underlying buffer index of the first\n iterated ndarray element.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Index offset.\n\n Examples\n --------\n > var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n 0\n\n See Also\n --------\n array, ndarray, ndarrayShape, ndarrayStrides\n","ndarrayOrder":"\nndarrayOrder( x )\n Returns the layout order of a provided ndarray.\n\n If unable to resolve a layout order, the function returns `null`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: string|null\n Layout order.\n\n Examples\n --------\n > var opts = { 'order': 'row-major' };\n > var dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n 'row-major'\n\n See Also\n --------\n array, ndarray, ndarrayOrders, ndarrayShape, ndarrayStrides\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n\n The output array contains the following orders:\n\n - row-major: row-major (C-style) order.\n - column-major: column-major (Fortran-style) order.\n\n Returns\n -------\n out: Array\n List of ndarray orders.\n\n Examples\n --------\n > var out = ndarrayOrders()\n [ 'row-major', 'column-major' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1, dtype2] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: any (optional)\n ndarray data type value.\n\n dtype2: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = ndarrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = ndarraySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySameKindCasts\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast or cast\n within the same \"kind\".\n\n Examples\n --------\n > var out = ndarraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarrayShape":"\nndarrayShape( x )\n Returns the shape of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Array\n Shape.\n\n Examples\n --------\n > var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n [ 3, 3, 3 ]\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayStrides\n","ndarrayStride":"\nndarrayStride( x, dim )\n Returns the stride along a specified dimension for a provided ndarray.\n\n A \"stride\" is the linear distance (i.e., number of elements) between\n adjacent elements along a specified dimension.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n Returns\n -------\n out: integer\n Stride.\n\n Examples\n --------\n > var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n 9\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape, ndarrayStrides\n","ndarrayStrides":"\nndarrayStrides( x )\n Returns the strides of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Array\n Strides.\n\n Examples\n --------\n > var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n [ 9, 3, 1 ]\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape\n","ndat":"\nndat( x[, ...indices] )\n Returns an ndarray element.\n\n Negative indices are resolved relative to the last element along the\n respective dimension, with the last element corresponding to `-1`.\n\n If provided out-of-bounds indices, the function always returns `undefined`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n indices: ...integer (optional)\n Index arguments. The number of index arguments must equal the number of\n dimensions.\n\n Returns\n -------\n out: any\n Element value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > ndat( x, 0, 1 )\n 2\n > ndat( x, 1, 0 )\n 3\n\n See Also\n --------\n array, ndslice\n","ndempty":"\nndempty( shape[, options] )\n Returns an uninitialized ndarray having a specified shape and data type.\n\n In browser environments, the function always returns zero-filled ndarrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n For returned ndarrays whose underlying memory is *not* initialized, memory\n contents are unknown and may contain *sensitive* data.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Underlying data type. Default: 'float64'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = ndempty( [ 2, 2 ] )\n \n\n See Also\n --------\n ndemptyLike, ndzeros\n","ndemptyLike":"\nndemptyLike( x[, options] )\n Returns an uninitialized ndarray having the same shape and data type as a\n provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n In browser environments, the function always returns zero-filled ndarrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n For returned ndarrays whose underlying memory is *not* initialized, memory\n contents are unknown and may contain *sensitive* data.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string|DataType (optional)\n Array data type. Overrides the input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = ndzeros( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n > var y = ndemptyLike( x )\n \n\n See Also\n --------\n ndempty, ndzerosLike\n","ndfill":"\nndfill( x, value )\n Fills an input ndarray with a specified value.\n\n If `value` is a number and `x` has a complex data type, the function fills\n an input ndarray with a complex number whose real component equals the\n provided scalar `value` and whose imaginary component is zero.\n\n The function *mutates* the input ndarray.\n\n Parameters\n ----------\n x: ndarrayLike\n Input ndarray.\n\n value: any\n Scalar value. Must be able to safely cast to the input ndarray data\n type. Scalar values having floating-point data types (both real and\n complex) are allowed to downcast to a lower precision data type of the\n same kind (e.g., a scalar double-precision floating-point number can be\n used to fill a 'float32' input ndarray).\n\n Returns\n -------\n out: ndarrayLike\n Input ndarray.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var x = ndzeros( [ 2, 2 ], opts );\n > x.get( 0, 0 )\n 0.0\n > ndfill( x, 10.0 );\n > x.get( 0, 0 )\n 10.0\n\n See Also\n --------\n ndfillBy, ndmap, ndzeros\n","ndfillBy":"\nndfillBy( x, fcn[, thisArg] )\n Fills an input ndarray according to a callback function.\n\n The function *mutates* the input ndarray.\n\n The function assumes that each element in the underlying input ndarray data\n buffer has one, and only one, corresponding element in input ndarray view\n (i.e., a provided ndarray is not a broadcasted ndarray view).\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarrayLike\n Input ndarray.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n out: ndarrayLike\n Input ndarray.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var x = ndzeros( [ 2, 2 ], opts );\n > x.get( 0, 0 )\n 0.0\n > function fcn() { return 10.0; };\n > ndfillBy( x, fcn );\n > x.get( 0, 0 )\n 10.0\n > x.get( 0, 1 )\n 10.0\n > x.get( 1, 0 )\n 10.0\n > x.get( 1, 1 )\n 10.0\n\n See Also\n --------\n ndfill, ndmap, ndzeros\n","ndfilter":"\nndfilter( x[, options], predicate[, thisArg] )\n Returns a shallow copy of an ndarray containing only those elements which\n pass a test implemented by a predicate function.\n\n The predicate function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Predicate function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v > 2.0; };\n > var y = ndfilter( x, f )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n ndfilterMap, ndmap, ndreject, ndslice","ndfilterMap":"\nndfilterMap( x[, options], fcn[, thisArg] )\n Filters and maps elements in an input ndarray to elements in a new output\n ndarray according to a callback function.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n If a provided callback function returns `undefined`, the function skips the\n respective ndarray element. If the callback function returns a value other\n than `undefined`, the function stores the callback's return value in the\n output ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\n > var y = ndfilterMap( x, f )\n [ 30.0, 40.0 ]\n\n See Also\n --------\n ndfilter, ndmap, ndreject, ndslice","ndforEach":"\nndforEach( x, fcn[, thisArg] )\n Invokes a callback function once for each ndarray element.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\n > ndforEach( x, f );\n\n See Also\n --------\n ndmap","ndims":"\nndims( x )\n Returns the number of ndarray dimensions.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Number of dimensions.\n\n Examples\n --------\n > var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n 3\n\n See Also\n --------\n array, ndarray, numel, ndarrayShape\n","ndindex":"\nndindex( x[, options] )\n Wraps a provided array as an ndarray index object.\n\n ndarray index instances have no explicit functionality; however, they are\n used by \"fancy\" ndarrays for element retrieval and assignment.\n\n By default, an instance is invalidated and removed from an internal cache\n immediately after a consumer resolves the underlying data associated with an\n instance using the `get` static method. Immediate invalidation and cache\n removal ensures that references to the underlying ndarray are not the source\n of memory leaks.\n\n Because instances leverage an internal cache implementing the Singleton\n pattern, one must be sure to use the same constructor as consumers. If one\n uses a different constructor, the consumer will *not* be able to resolve the\n original wrapped ndarray, as the consumer will attempt to resolve an\n instance in the wrong internal cache.\n\n Because non-persisted instances are freed after first use, in order to avoid\n holding onto memory and to allow garbage collection, one should avoid\n scenarios in which an instance is never used.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n\n\nndindex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.free( idx.id )\n \n\n\nndindex.get( id )\n Returns the ndarray associated with the instance having a provided\n identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing ndarray data.\n\n out.data: ndarray\n The underlying ndarray associated with the provided identifier.\n\n out.type: string\n The type of ndarray index.\n\n out.dtype: string\n The data type of the underlying ndarray.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.get( idx.id )\n {...}\n\n\nndindex.cartesianIndex( x[, options] )\n Returns an ndarray index containing Cartesian indices.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'cartesian'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = ndindex.cartesianIndex( x );\n\n\nndindex.linearIndex( x[, options] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'linear'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n > var idx = ndindex.linearIndex( x );\n\n\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n\n Returns\n -------\n out: ndarray\n Array data.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.data\n \n\n\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.dtype\n 'int32'\n\n\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.id\n \n\n\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an ndarray index is actively cached.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.isCached\n true\n\n\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n\n Returns\n -------\n out: string\n Index kind.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n > idx.kind\n 'cartesian'\n\n\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n\n Returns\n -------\n out: string\n Index type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.type\n \n\n\nndindex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toString()\n \n\n\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toJSON()\n { 'type': 'ndindex', ... }\n\n See Also\n --------\n array, ndarray, FancyArray, ndslice, ndarray2fancy\n","ndindex.free":"\nndindex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.free( idx.id )\n ","ndindex.get":"\nndindex.get( id )\n Returns the ndarray associated with the instance having a provided\n identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing ndarray data.\n\n out.data: ndarray\n The underlying ndarray associated with the provided identifier.\n\n out.type: string\n The type of ndarray index.\n\n out.dtype: string\n The data type of the underlying ndarray.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.get( idx.id )\n {...}","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x[, options] )\n Returns an ndarray index containing Cartesian indices.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'cartesian'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = ndindex.cartesianIndex( x );","ndindex.linearIndex":"\nndindex.linearIndex( x[, options] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'linear'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n > var idx = ndindex.linearIndex( x );","ndindex.prototype.data":"\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n\n Returns\n -------\n out: ndarray\n Array data.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.data\n ","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.dtype\n 'int32'","ndindex.prototype.id":"\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.id\n ","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an ndarray index is actively cached.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.isCached\n true","ndindex.prototype.kind":"\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n\n Returns\n -------\n out: string\n Index kind.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n > idx.kind\n 'cartesian'","ndindex.prototype.type":"\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n\n Returns\n -------\n out: string\n Index type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.type\n ","ndindex.prototype.toString":"\nndindex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toString()\n ","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toJSON()\n { 'type': 'ndindex', ... }\n\n See Also\n --------\n array, ndarray, FancyArray, ndslice, ndarray2fancy","nditer2arrayEach":"\nnditer2arrayEach( iterator )\n Returns an iterator which converts each iterated ndarray to a generic array.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditer2arrayEach( nditerRows( x ) );\n > var v = it.next().value\n [ 1, 2 ]\n > v = it.next().value\n [ 3, 4 ]\n\n See Also\n --------\n ndarray, ndarray2array\n","nditerColumnEntries":"\nnditerColumnEntries( x[, options] )\n Returns an iterator which returns [index, column] pairs for each column in a\n matrix (or stack of matrices).\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerColumnEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ null, 0 ]\n > ndarray2array( v[ 1 ] )\n [ 1, 3 ]\n > v = it.next().value;\n > v[ 0 ]\n [ null, 1 ]\n > ndarray2array( v[ 1 ] )\n [ 2, 4 ]\n\n See Also\n --------\n nditerColumns, nditerEntries, nditerRowEntries, ndslice\n","nditerColumns":"\nnditerColumns( x[, options] )\n Returns an iterator which iterates over each column in a matrix (or stack of\n matrices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerColumns( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ 1, 3 ]\n > v = it.next().value;\n > ndarray2array( v )\n [ 2, 4 ]\n\n See Also\n --------\n nditerColumnEntries, nditerRows, ndslice\n","nditerEntries":"\nnditerEntries( x[, options] )\n Returns an iterator which returns [index, value] pairs for each element in a\n provided ndarray.\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator returns values\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerEntries( x );\n > var v = it.next().value\n [ [ 0, 0 ], 1 ]\n > v = it.next().value\n [ [ 0, 1 ], 2 ]\n\n See Also\n --------\n ndarray, nditerIndices, nditerValues\n","nditerIndices":"\nnditerIndices( shape[, options] )\n Returns an iterator which returns indices for use indexing into an ndarray\n having a specified shape.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n shape: Array\n Input shape.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator iterates over\n the last dimensions first, thus corresponding to iteration over\n contiguous data stored in row-major order. Must be either 'row-major'\n or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerIndices( x.shape );\n > var v = it.next().value\n [ 0, 0 ]\n > v = it.next().value\n [ 0, 1 ]\n\n See Also\n --------\n ndarray, nditerEntries, nditerValues\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr, ndims )\n Returns an iterator which iterates over interleaved subarrays.\n\n For input ndarrays supporting read-only views, the function returns\n *read-only* views of interleaved subarrays. As input ndarrays may be\n broadcasted, a view is typically *not* contiguous. As more than one element\n of a returned view may refer to the same memory location, writing to a view\n may affect multiple elements. If you need to write to a subarray, copy the\n subarray before attempting mutation.\n\n The function throws an error if a provided broadcast-incompatible ndarrays.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n arr: ArrayLike\n Input ndarrays. All ndarrays must be broadcast-compatible. After\n broadcasting, each broadcasted input ndarray must have at least\n `ndims+1` dimensions.\n\n ndims: integer\n Number of dimensions to stack after broadcasting.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerInterleaveSubarrays( [ x, x ], 2 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerSubarrays, ndslice\n","nditerMatrices":"\nnditerMatrices( x[, options] )\n Returns an iterator which iterates over each matrix in a stack of matrices.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerMatrices( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrixEntries, nditerRows, ndslice\n","nditerMatrixEntries":"\nnditerMatrixEntries( x[, options] )\n Returns an iterator which returns [index, matrix] pairs for each matrix in a\n stack of matrices.\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerMatrixEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ 0, null, null ]\n > ndarray2array( v[ 1 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumnEntries, nditerEntries, nditerMatrices, nditerRowEntries, ndslice\n","nditerRowEntries":"\nnditerRowEntries( x[, options] )\n Returns an iterator which returns [index, row] pairs for each row in a\n matrix (or stack of matrices).\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerRowEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ 0, null ]\n > ndarray2array( v[ 1 ] )\n [ 1, 2 ]\n > v = it.next().value;\n > v[ 0 ]\n [ 1, null ]\n > ndarray2array( v[ 1 ] )\n [ 3, 4 ]\n\n See Also\n --------\n nditerColumnEntries, nditerEntries, nditerRows, ndslice\n","nditerRows":"\nnditerRows( x[, options] )\n Returns an iterator which iterates over each row in a matrix (or stack of\n matrices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerRows( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ 1, 2 ]\n > v = it.next().value;\n > ndarray2array( v )\n [ 3, 4 ]\n\n See Also\n --------\n nditerColumns, nditerRowEntries, ndslice\n","nditerSelectDimension":"\nnditerSelectDimension( x, dim[, options] )\n Returns an iterator which iterates over each view along a specified\n dimension.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n options.keepdim: boolean (optional)\n Boolean indicating whether returned views should include the selected\n dimension as a singleton dimension. Including the selected dimension as\n a singleton dimension can be useful when wanting to ensure that returned\n views remain broadcast compatible with the input ndarray. Default:\n false.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerSelectDimension( x, 0 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, ndslice\n","nditerStacks":"\nnditerStacks( x, dims[, options] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays according to a list of specified stack dimensions.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator. Must have at least\n `dims.length+1` dimensions.\n\n dims: Array\n Indices of dimensions to stack. If a dimension index is less than zero,\n the index is resolved relative to the last dimension, with the last\n dimension corresponding to the value `-1`. The list of indices must be\n unique and resolve to dimension indices sorted in ascending order.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerStacks( x, [ 1, 2 ] );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, nditerSubarrays, ndslice\n","nditerSubarrays":"\nnditerSubarrays( x, ndims[, options] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator. Must have at least\n `ndims+1` dimensions.\n\n ndims: integer\n Number of dimensions to stack.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerSubarrays( x, 2 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, nditerStacks, ndslice\n","nditerValues":"\nnditerValues( x[, options] )\n Returns an iterator which returns individual elements from a provided\n ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator returns values\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerValues( x );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n ndarray, nditerEntries, nditerIndices\n","ndmap":"\nndmap( x[, options], fcn[, thisArg] )\n Applies a callback function to elements in an input ndarray and assigns\n results to elements in a new output ndarray.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v*10.0; };\n > var y = ndmap( x, f )\n [ [ 10.0, 20.0 ], [ 30.0, 40.0 ] ]\n\n See Also\n --------\n ndfilter, ndfilterMap, ndforEach, ndslice","ndreject":"\nndreject( x[, options], predicate[, thisArg] )\n Returns a shallow copy of an ndarray containing only those elements which\n fail a test implemented by a predicate function.\n\n The predicate function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Predicate function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v <= 2.0; };\n > var y = ndreject( x, f );\n > ndarray2array( y )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n ndfilter, ndfilterMap, ndmap, ndslice","ndslice":"\nndslice( x, ...s[, options] )\n Returns a read-only view of an input ndarray.\n\n The function supports three (mutually exclusive) means of providing slice\n arguments:\n\n 1. Providing a single MultiSlice object.\n 2. Providing a single array containing slice arguments.\n 3. Providing slice arguments as separate arguments.\n\n An individual slice argument must be either a Slice, an integer, null, or\n undefined.\n\n In all cases, the number of slice dimensions must match the number of array\n dimensions.\n\n If providing a MultiSlice object or an array of slice arguments, no other\n slice arguments should be provided.\n\n Mixing function invocation styles (e.g., providing multiple MultiSlice\n objects or providing an array of slice arguments followed by additional\n slice arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n Slice arguments.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var s = new MultiSlice( null, 1 )\n \n > var y = ndslice( x, s )\n \n > y.shape\n [ 2 ]\n > ndarray2array( y )\n [ 2, 4 ]\n\n See Also\n --------\n array, ndat, ndarray, ndsliceAssign, ndsliceDimension\n","ndsliceAssign":"\nndsliceAssign( x, y, ...s[, options] )\n Assigns element values from a broadcasted input ndarray to corresponding\n elements in an output ndarray view.\n\n The function supports three (mutually exclusive) means of providing slice\n arguments:\n\n 1. Providing a single MultiSlice object.\n 2. Providing a single array containing slice arguments.\n 3. Providing slice arguments as separate arguments.\n\n An individual slice argument must be either a Slice, an integer, null, or\n undefined.\n\n In all cases, the number of slice dimensions must match the number of output\n array dimensions.\n\n If providing a MultiSlice object or an array of slice arguments, no other\n slice arguments should be provided.\n\n Mixing function invocation styles (e.g., providing multiple MultiSlice\n objects or providing an array of slice arguments followed by additional\n slice arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array. The input array must be broadcast compatible with the\n output array view and must have a data type which can be safely cast to\n the output array data type. Floating-point data types (both real and\n complex) are allowed to downcast to a lower precision data type of the\n same kind (e.g., element values from a 'float64' input array can be\n assigned to corresponding elements in a 'float32' output array).\n\n y: ndarray\n Output array. The output array must be writable.\n\n s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n Slice arguments.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n true.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var y = ndzeros( [ 2, 2 ] )\n \n > var x = scalar2ndarray( 3.0 )\n \n > var s = new MultiSlice( null, 1 )\n \n > var out = ndsliceAssign( x, y, s )\n \n > var bool = ( out === y )\n true\n > ndarray2array( y )\n [ [ 0.0, 3.0 ], [ 0.0, 3.0 ] ]\n\n See Also\n --------\n array, ndarray, ndslice\n","ndsliceDimension":"\nndsliceDimension( x, dim, slice[, options] )\n Returns a read-only view of an input ndarray when sliced along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n slice: Slice|integer|null|undefined\n Slice object or an integer. If provided `null` or `undefined`, the\n returned view includes all elements along a specified dimension. If\n provided an integer less than zero, the corresponding element along the\n specified dimension is resolved relative to the last element along that\n dimension. For negative integers, the last element corresponds to the\n value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimension( x, 1, 1 )\n \n > y.shape\n [ 2 ]\n > ndarray2array( y )\n [ 2, 4 ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceDimensionTo\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x, dim, start[, options] )\n Returns a read-only shifted view of an input ndarray along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n start: integer\n Starting index (inclusive). If less than zero, the corresponding element\n along the specified dimension is resolved relative to the last element\n along that dimension. For negative integers, the last element\n corresponds to the value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimensionFrom( x, 1, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 2 ], [ 4 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionTo, ndsliceFrom\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x, dim, stop[, options] )\n Returns a read-only truncated view of an input ndarray along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n stop: integer\n Ending index (exclusive). If less than zero, the corresponding element\n along the specified dimension is resolved relative to the last element\n along that dimension. For negative integers, the last element\n corresponds to the value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimensionTo( x, 1, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 1 ], [ 3 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionFrom, ndsliceTo\n","ndsliceFrom":"\nndsliceFrom( x, ...start[, options] )\n Returns a read-only shifted view of an input ndarray.\n\n The function supports two (mutually exclusive) means of providing starting\n indices:\n\n 1. Providing a single array containing start arguments.\n 2. Providing start arguments as separate arguments.\n\n An individual start argument must be either an integer, null, or undefined.\n\n In all cases, the number of start indices must match the number of array\n dimensions.\n\n If providing an array of start arguments, no other start arguments should be\n provided.\n\n Mixing function invocation styles (e.g., providing an array of start\n arguments followed by additional start arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n start: ...null|void|integer\n Starting indices (inclusive). If an element is either `null` or\n `undefined`, the function returns a view containing all elements along\n that dimension. A negative integer indicates to resolve a starting index\n relative to the last element along a corresponding dimension, with the\n last element having index `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceFrom( x, 0, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 2 ], [ 4 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceTo\n","ndsliceTo":"\nndsliceTo( x, ...stop[, options] )\n Returns a read-only truncated view of an input ndarray.\n\n The function supports two (mutually exclusive) means of providing ending\n indices:\n\n 1. Providing a single array containing stop arguments.\n 2. Providing stop arguments as separate arguments.\n\n An individual stop argument must be either an integer, null, or undefined.\n\n In all cases, the number of stop indices must match the number of array\n dimensions.\n\n If providing an array of stop arguments, no other stop arguments should be\n provided.\n\n Mixing function invocation styles (e.g., providing an array of stop\n arguments followed by additional stop arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n stop: ...null|void|integer\n Ending indices (exclusive). If an ending index is either `null` or\n `undefined`, the function returns a view containing all elements along\n that dimension. A negative integer indicates to resolve an ending index\n relative to the last element along a corresponding dimension, with the\n last element having index `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceTo( x, 1, 1 )\n \n > y.shape\n [ 1, 1 ]\n > ndarray2array( y )\n [ [ 1 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionTo, ndsliceFrom\n","ndzeros":"\nndzeros( shape[, options] )\n Returns a zero-filled ndarray having a specified shape and data type.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Underlying data type. Must be a numeric or \"generic\" data type. Default:\n 'float64'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = ndzeros( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n ndempty, ndzerosLike\n","ndzerosLike":"\nndzerosLike( x[, options] )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a numeric or \"generic\" data type. Overrides the\n input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = ndzeros( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n > var y = ndzerosLike( x )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n ndemptyLike, ndzeros\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str[, fromIndex] )\n Returns the next extended grapheme cluster break in a string after a\n specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n fromIndex: integer (optional)\n Position. Default: 0.\n\n Returns\n -------\n out: integer\n Next extended grapheme cluster break position.\n\n Examples\n --------\n > var out = nextGraphemeClusterBreak( 'last man standing', 4 )\n 5\n > out = nextGraphemeClusterBreak( 'presidential election', 8 )\n 9\n > out = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\n 3\n > out = nextGraphemeClusterBreak( '🌷' )\n -1\n\n See Also\n --------\n numGraphemeClusters, prevGraphemeClusterBreak","nextTick":"\nnextTick( clbk[, ...args] )\n Adds a callback to the \"next tick queue\".\n\n The queue is fully drained after the current operation on the JavaScript\n stack runs to completion and before the event loop is allowed to continue.\n\n Parameters\n ----------\n clbk: Function\n Callback to invoke.\n\n ...args: any (optional)\n Arguments to provide to the callback upon invocation.\n\n Examples\n --------\n > function f() { console.log( 'beep' ); };\n > nextTick( f )\n\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n\n Returns\n -------\n out: Array\n Nightingale's data.\n\n Examples\n --------\n > var data = NIGHTINGALES_ROSE()\n [{...}, {...}, ...]\n\n References\n ----------\n - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n the British army during the late war with Russia*. London, United Kingdom:\n John W. Parker and Son..\n\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n\n Examples\n --------\n > NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_NINF, PINF\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n\n Examples\n --------\n > NODE_VERSION\n \n\n","none":"\nnone( collection )\n Tests whether all elements in a collection are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are falsy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0 ];\n > var bool = none( arr )\n true\n\n See Also\n --------\n any, every, forEach, noneBy, some\n","noneBy":"\nnoneBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = noneBy( arr, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, none, noneByRight, someBy\n","noneByAsync":"\nnoneByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync\n","noneByAsync.factory":"\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync","noneByRight":"\nnoneByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ -1, -2, -3, -4 ];\n > var bool = noneByRight( arr, positive )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, none, noneBy, someByRight\n","noneByRightAsync":"\nnoneByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync","noneInBy":"\nnoneInBy( object, predicate[, thisArg ] )\n Tests whether every property in an object fails a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 4 };\n > var bool = noneInBy( obj, negative )\n true\n\n See Also\n --------\n anyInBy, everyInBy, noneBy, someInBy\n","nonEnumerableProperties":"\nnonEnumerableProperties( value )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own non-enumerable properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var props = nonEnumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerableProperties, inheritedNonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited non-enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = nonEnumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerablePropertiesIn, inheritedNonEnumerableProperties, nonEnumerableProperties, propertiesIn\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value )\n Returns an array of an object's own non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNames( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n objectKeys, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNamesIn( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n keysIn, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNames, propertyNamesIn\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value )\n Returns an array of an object's own non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNames, nonEnumerablePropertySymbolsIn, propertySymbols\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertySymbolsIn\n","noneOwnBy":"\nnoneOwnBy( object, predicate[, thisArg ] )\n Tests whether every own property of an object fails a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all own properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function isUnderage( v ) { return ( v < 18 ); };\n > var obj = { 'a': 11, 'b': 12, 'c': 22 };\n > var bool = noneOwnBy( obj, isUnderage )\n false\n\n See Also\n --------\n anyOwnBy, everyOwnBy, noneBy, someOwnBy\n","nonIndexKeys":"\nnonIndexKeys( obj )\n Returns an array of an object's own enumerable property names which are not\n integer indices.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = nonIndexKeys( obj )\n e.g., [ 'beep' ]\n\n See Also\n --------\n objectEntries, objectKeys, objectValues\n","noop":"\nnoop()\n A function which does nothing.\n\n Examples\n --------\n > noop();\n\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n\n The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n Returns\n -------\n out: integer\n Time in seconds since the epoch.\n\n Examples\n --------\n > var ts = now()\n \n\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n\n In browser environments, the number of CPUs is determined by querying the\n hardware concurrency API.\n\n In Node.js environments, the number of CPUs is determined via the `os`\n module.\n\n Examples\n --------\n > NUM_CPUS\n \n\n","num2words":"\nnum2words( value[, options] )\n Converts a number to a word representation.\n\n Parameters\n ----------\n value: integer\n Input value.\n\n options: Object (optional)\n Options.\n\n options.lang: string (optional)\n Language code. Supported languages:\n\n - en: English.\n - de: German.\n\n Default: `'en'`.\n\n Returns\n -------\n out: string\n Word representation of number.\n\n Examples\n --------\n > var out = num2words( 123 )\n 'one hundred twenty-three'\n\n > out = num2words( 16.31 )\n 'sixteen point three one'\n\n > out = num2words( 123, { 'lang': 'de' } )\n 'einhundertdreiundzwanzig'\n\n","Number":"\nNumber( value )\n Returns a Number object.\n\n This constructor should be used sparingly. Always prefer number primitives.\n\n Parameters\n ----------\n value: number\n Value to wrap in a Number object.\n\n Returns\n -------\n out: Number\n Number object.\n\n Examples\n --------\n > var v = new Number( 5 )\n \n\n","numel":"\nnumel( x )\n Returns the number of elements in an ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Number of elements.\n\n Examples\n --------\n > var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n 27\n\n See Also\n --------\n array, ndarray, numelDimension\n","numelDimension":"\nnumelDimension( x, dim )\n Returns the size (i.e., number of elements) of a specified dimension for a\n provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n Returns\n -------\n out: integer\n Dimension size.\n\n Examples\n --------\n > var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n 4\n\n See Also\n --------\n array, ndarray, numel\n","numGraphemeClusters":"\nnumGraphemeClusters( str )\n Returns the number of grapheme clusters in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Number of grapheme clusters.\n\n Examples\n --------\n > var out = numGraphemeClusters( 'beep' )\n 4\n > out = numGraphemeClusters( '🌷' )\n 1\n\n See Also\n --------\n nextGraphemeClusterBreak\n","Object":"\nObject( value )\n Returns an object.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n If provided an existing object, the function returns the input value\n unchanged.\n\n Otherwise, if provided any other value (e.g., a number, string, etc), the\n function will return an object of the corresponding type.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > var o = new Object( null )\n {}\n > o = new Object( 5.0 )\n \n > o = new Object( 'beep' )\n \n\nObject.assign( target, ...sources )\n Assigns enumerable and own properties from source objects to a target\n object.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n sources: ...Object\n Source objects.\n\n Returns\n -------\n out: Object\n Target object.\n\n Examples\n --------\n > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n { 'a': 1, 'b': 2 }\n\nObject.create( prototype, properties )\n Creates a new object with a specified prototype object and properties.\n\n Parameters\n ----------\n prototype: Object\n Prototype object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }\n\nObject.defineProperties( obj, properties )\n Defines properties for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }\n\nObject.defineProperty( obj, key, descriptor )\n Defines a property for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n descriptor: Object\n Property descriptor.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperty( {}, 'a', {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': false\n })\n { 'a': 1 }\n\nObject.entries( obj )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of [key, value] pairs.\n\n Examples\n --------\n > var o = Object.entries( { 'a': 1, 'b': 2 } )\n [ [ 'a', 1 ], [ 'b', 2 ] ]\n\nObject.freeze( obj )\n Freezes an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.freeze( { 'a': 1 } )\n { 'a': 1 }\n\nObject.getOwnPropertyDescriptor( obj, key )\n Returns an object's own property descriptor.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n Returns\n -------\n out: Object\n Property descriptor.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }\n\nObject.getOwnPropertyDescriptors( obj )\n Returns an object's own property descriptors.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Property descriptors.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n {\n 'a': {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n },\n 'b': {\n 'value': 2,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n }\n }\n\nObject.getOwnPropertyNames( obj )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]\n\nObject.getOwnPropertySymbols( obj )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of symbol property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n []\n\nObject.getPrototypeOf( obj )\n Returns an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Prototype.\n\n Examples\n --------\n > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n \n\nObject.hasOwn( obj, p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n true\n\nObject.is( value1, value2 )\n Returns a boolean indicating whether two values are the same value.\n\n Parameters\n ----------\n value1: any\n First value.\n\n value2: any\n Second value.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether two values are the same value.\n\n Examples\n --------\n > var o = Object.is( 1, 1 )\n true\n > var o = Object.is( 1, '1' )\n false\n\nObject.isExtensible( obj )\n Returns a boolean indicating whether an object is extensible.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is extensible.\n\n Examples\n --------\n > var o = Object.isExtensible( { 'a': 1 } )\n true\n\nObject.isFrozen( obj )\n Returns a boolean indicating whether an object is frozen.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is frozen.\n\n Examples\n --------\n > var o = Object.isFrozen( { 'a': 1 } )\n false\n > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n true\n\nObject.isSealed( obj )\n Returns a boolean indicating whether an object is sealed.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is sealed.\n\n Examples\n --------\n > var o = Object.isSealed( { 'a': 1 } )\n false\n > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n true\n\nObject.keys( obj )\n Returns an array of an object's own enumerable string-keyed property\n names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.keys( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]\n\nObject.preventExtensions( obj )\n Prevents the addition of new properties to an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.preventExtensions( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n\nObject.seal( obj )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.seal( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n > delete o.a;\n > o\n { 'a': 1 }\n\nObject.setPrototypeOf( obj, proto )\n Sets an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n proto: Object\n Prototype.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n { 'a': 1 }\n > o.b\n 2\n\nObject.values( obj )\n Returns an array of an object's own enumerable property values.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property values.\n\n Examples\n --------\n > var o = Object.values( { 'a': 1, 'b': 2 } )\n [ 1, 2 ]\n\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n \n\nObject.prototype.toString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n \n\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n\n Returns\n -------\n out: any\n Primitive value of the object.\n\n Examples\n --------\n > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n {}\n\nObject.prototype.hasOwnProperty( p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n true\n\nObject.prototype.isPrototypeOf( obj )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object exists in another object's\n prototype chain.\n\n Examples\n --------\n > var p = { 'a': 1 };\n > var o = { '__proto__': p };\n > var b = o.isPrototypeOf( p );\n true\n\nObject.prototype.propertyIsEnumerable( p )\n Returns a boolean indicating whether an object's property is enumerable.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object's property is enumerable.\n\n Examples\n --------\n > var o = { 'a': 1, 'b': 2 };\n > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n true\n\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n\n Examples\n --------\n > var o = new Object( null );\n > var ctr = o.constructor;\n \n\n","Object.assign":"\nObject.assign( target, ...sources )\n Assigns enumerable and own properties from source objects to a target\n object.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n sources: ...Object\n Source objects.\n\n Returns\n -------\n out: Object\n Target object.\n\n Examples\n --------\n > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n { 'a': 1, 'b': 2 }","Object.create":"\nObject.create( prototype, properties )\n Creates a new object with a specified prototype object and properties.\n\n Parameters\n ----------\n prototype: Object\n Prototype object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }","Object.defineProperties":"\nObject.defineProperties( obj, properties )\n Defines properties for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }","Object.defineProperty":"\nObject.defineProperty( obj, key, descriptor )\n Defines a property for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n descriptor: Object\n Property descriptor.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperty( {}, 'a', {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': false\n })\n { 'a': 1 }","Object.entries":"\nObject.entries( obj )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of [key, value] pairs.\n\n Examples\n --------\n > var o = Object.entries( { 'a': 1, 'b': 2 } )\n [ [ 'a', 1 ], [ 'b', 2 ] ]","Object.freeze":"\nObject.freeze( obj )\n Freezes an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.freeze( { 'a': 1 } )\n { 'a': 1 }","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj, key )\n Returns an object's own property descriptor.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n Returns\n -------\n out: Object\n Property descriptor.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj )\n Returns an object's own property descriptors.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Property descriptors.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n {\n 'a': {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n },\n 'b': {\n 'value': 2,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n }\n }","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of symbol property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n []","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj )\n Returns an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Prototype.\n\n Examples\n --------\n > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n ","Object.hasOwn":"\nObject.hasOwn( obj, p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n true","Object.is":"\nObject.is( value1, value2 )\n Returns a boolean indicating whether two values are the same value.\n\n Parameters\n ----------\n value1: any\n First value.\n\n value2: any\n Second value.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether two values are the same value.\n\n Examples\n --------\n > var o = Object.is( 1, 1 )\n true\n > var o = Object.is( 1, '1' )\n false","Object.isExtensible":"\nObject.isExtensible( obj )\n Returns a boolean indicating whether an object is extensible.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is extensible.\n\n Examples\n --------\n > var o = Object.isExtensible( { 'a': 1 } )\n true","Object.isFrozen":"\nObject.isFrozen( obj )\n Returns a boolean indicating whether an object is frozen.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is frozen.\n\n Examples\n --------\n > var o = Object.isFrozen( { 'a': 1 } )\n false\n > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n true","Object.isSealed":"\nObject.isSealed( obj )\n Returns a boolean indicating whether an object is sealed.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is sealed.\n\n Examples\n --------\n > var o = Object.isSealed( { 'a': 1 } )\n false\n > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n true","Object.keys":"\nObject.keys( obj )\n Returns an array of an object's own enumerable string-keyed property\n names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.keys( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]","Object.preventExtensions":"\nObject.preventExtensions( obj )\n Prevents the addition of new properties to an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.preventExtensions( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }","Object.seal":"\nObject.seal( obj )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.seal( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n > delete o.a;\n > o\n { 'a': 1 }","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj, proto )\n Sets an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n proto: Object\n Prototype.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n { 'a': 1 }\n > o.b\n 2","Object.values":"\nObject.values( obj )\n Returns an array of an object's own enumerable property values.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property values.\n\n Examples\n --------\n > var o = Object.values( { 'a': 1, 'b': 2 } )\n [ 1, 2 ]","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n ","Object.prototype.toString":"\nObject.prototype.toString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n ","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n\n Returns\n -------\n out: any\n Primitive value of the object.\n\n Examples\n --------\n > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n {}","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n true","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object exists in another object's\n prototype chain.\n\n Examples\n --------\n > var p = { 'a': 1 };\n > var o = { '__proto__': p };\n > var b = o.isPrototypeOf( p );\n true","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p )\n Returns a boolean indicating whether an object's property is enumerable.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object's property is enumerable.\n\n Examples\n --------\n > var o = { 'a': 1, 'b': 2 };\n > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n true","Object.prototype.constructor":"\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n\n Examples\n --------\n > var o = new Object( null );\n > var ctr = o.constructor;\n ","objectEntries":"\nobjectEntries( obj )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var entries = objectEntries( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntriesIn, objectFromEntries, objectKeys, objectValues\n","objectEntriesIn":"\nobjectEntriesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var entries = objectEntriesIn( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntries, objectFromEntries, keysIn, objectValuesIn\n","objectFromEntries":"\nobjectFromEntries( entries )\n Creates an object from an array of key-value pairs.\n\n Parameters\n ----------\n entries: Array\n Input object.\n\n Returns\n -------\n out: Object\n Object created from `[key, value]` pairs.\n\n Examples\n --------\n > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n > var obj = objectFromEntries( entries )\n { 'beep': 'boop', 'foo': 'bar' }\n\n See Also\n --------\n objectEntries\n","objectInverse":"\nobjectInverse( obj[, options] )\n Inverts an object, such that keys become values and values become keys.\n\n Beware when providing objects having values which are themselves objects.\n The function relies on native object serialization (`#toString`) when\n converting values to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverse( obj )\n { 'beep': 'a', 'boop': 'b' }\n\n // Duplicate values:\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverse( obj )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverse( obj, { 'duplicates': false } )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverseBy\n","objectInverseBy":"\nobjectInverseBy( obj, [options,] transform )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n\n The transform function is provided three arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n\n The value returned by a transform function should be a value which can be\n serialized as an object key. Hence, beware when providing objects having\n values which are themselves objects. The function relies on native object\n serialization (`#toString`) when converting transform function return values\n to keys.\n\n In older JavaScript engines, insertion order is not guaranteed, as object\n key enumeration was not specified according to the ECMAScript specification\n in earlier editions. In practice, however, most older engines use insertion\n order to sort an object's keys, thus allowing for deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n transform: Function\n Transform function.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverseBy( obj, transform )\n { 'abeep': 'a', 'bboop': 'b' }\n\n // Duplicate values:\n > function transform( key, value ) { return value; };\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverseBy( obj, transform )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverse\n","objectKeys":"\nobjectKeys( value )\n Returns an array of an object's own enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = objectKeys( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectEntries, keysIn, nonIndexKeys, objectValues\n","objectValues":"\nobjectValues( obj )\n Returns an array of an object's own enumerable property values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var vals = objectValues( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntries, objectKeys\n","objectValuesIn":"\nobjectValuesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var values = objectValuesIn( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntriesIn, keysIn, objectValues\n","omit":"\nomit( obj, keys )\n Returns a partial object copy excluding specified keys.\n\n The function returns a shallow copy.\n\n The function ignores non-existent keys.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to exclude.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omit( obj1, 'b' )\n { 'a': 1 }\n\n See Also\n --------\n omitBy\n","omitBy":"\nomitBy( obj, predicate )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n\n The function returns a shallow copy.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) { return ( value > 1 ); };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omitBy( obj1, predicate )\n { 'a': 1 }\n\n See Also\n --------\n omit\n","open":"\nopen( path[, flags[, mode]], clbk )\n Asynchronously opens a file.\n\n Some characters, such as <>:\"/\\|?*, are reserved under Windows.\n Under NTFS, if the path contains a colon, Node.js will open a file system\n stream.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon opening a file.\n\n Examples\n --------\n > function onOpen( error, fd ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... close.sync( fd );\n ... }\n ... };\n > open( './beep/boop.txt', onOpen );\n\n\nopen.sync( path[, flags[, mode]] )\n Synchronously opens a file.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n Returns\n -------\n fd: Error|integer\n File descriptor.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.txt' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n close, exists, readFile\n","open.sync":"\nopen.sync( path[, flags[, mode]] )\n Synchronously opens a file.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n Returns\n -------\n fd: Error|integer\n File descriptor.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.txt' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n close, exists, readFile","openURL":"\nopenURL( url )\n Opens a URL in a user's default browser.\n\n In a non-browser environment, the function returns an unreferenced child\n process. In a browser environment, the function returns a reference to a\n `window` object.\n\n Parameters\n ----------\n url: string\n URL to open.\n\n Returns\n -------\n out: process|Window\n Child process or `window` object.\n\n Examples\n --------\n > var out = openURL( 'https://google.com' );\n\n","ordinalize":"\nordinalize( value[, options] )\n Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n\n Parameters\n ----------\n value: string|integer\n Input value.\n\n options: Object (optional)\n Options.\n\n options.lang: string (optional)\n Language code. Supported languages:\n\n - en: English.\n - es: Spanish.\n - fin: Finnish.\n - fr: French.\n - de: Dutch.\n - it: Italian.\n - pt: Portuguese.\n - swe: Swedish.\n\n Default: `'en'`.\n\n options.suffixOnly: boolean (optional)\n Boolean indicating whether to return only the suffix. Default: `false`.\n\n options.gender: string (optional)\n Grammatical gender (used if applicable); must be either 'masculine' or\n 'feminine'. Default: `'masculine'`.\n\n Returns\n -------\n out: string\n Ordinal string or suffix.\n\n Examples\n --------\n > var out = ordinalize( '1' )\n '1st'\n > out = ordinalize( 2, { 'suffixOnly': true } )\n 'nd'\n > out = ordinalize( '3', { 'lang': 'es' } )\n '3º'\n\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 21 attributes:\n\n - obs: observation number.\n - town: town name.\n - town_id: town identifier.\n - tract: tract identifier.\n - lon: longitude.\n - lat: latitude.\n - medv: median value of owner-occupied homes in $1000's.\n - cmedv: corrected median value of owner-occupied homes in $1000's.\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n - lstat: percent lower status of the population.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n by including geo-referencing and spatial estimation for each observation.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = PACE_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n Configuration of the Data to Improve Estimation.\" _The Journal of Real\n Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, HARRISON_BOSTON_HOUSE_PRICES_CORRECTED\n","pad":"\npad( str, len[, options] )\n Pads a `string` such that the padded `string` has length `len`.\n\n Any padding which does not evenly divide available space is trimmed such\n that the returned string length is always `len`.\n\n If `len < str.length`, the input string is trimmed.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n options: Object (optional)\n Options.\n\n options.lpad: string (optional)\n String used to left pad.\n\n options.rpad: string (optional)\n String used to right pad.\n\n options.centerRight: boolean (optional)\n Boolean indicating whether to center right in the event of a tie.\n Default: `false` (i.e., center left).\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n // Standard usage:\n > var out = pad( 'a', 5 )\n 'a '\n\n // Left pad:\n > out = pad( 'a', 10, { 'lpad': 'b' } )\n 'bbbbbbbbba'\n\n // Right pad:\n > out = pad( 'a', 12, { 'rpad': 'b' } )\n 'abbbbbbbbbbb'\n\n // Center an input string:\n > var opts = { 'lpad': 'a', 'rpad': 'c' };\n > out = pad( 'b', 11, opts )\n 'aaaaabccccc'\n\n // Left center:\n > opts.centerRight = false;\n > out = pad( 'b', 10, opts )\n 'aaaabccccc'\n\n // Right center:\n > opts.centerRight = true;\n > out = pad( 'b', 10, opts )\n 'aaaaabcccc'\n\n // Output string always length `len`:\n > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n > out = pad( 'beep', 10, opts )\n 'boobeepwoo'\n\n // Pad right, trim right:\n > out = pad( 'beep', 2 )\n 'be'\n\n // Pad left, trim left:\n > opts = { 'lpad': 'b' };\n > out = pad( 'beep', 2, opts )\n 'ep'\n\n // Pad both, trim both:\n > opts = { 'lpad': '@', 'rpad': '!' };\n > out = pad( 'beep', 2, opts )\n 'ee'\n\n // Pad both, trim both starting from left:\n > out = pad( 'abcdef', 3, opts )\n 'cde'\n\n // Pad both, trim both starting from right:\n > opts.centerRight = true;\n > out = pad( 'abcdef', 3, opts )\n 'bcd'\n\n See Also\n --------\n lpad, rpad\n","padjust":"\npadjust( pvals, method[, comparisons] )\n Adjusts supplied p-values for multiple comparisons via a specified method.\n\n The `method` parameter can be one of the following values:\n\n - bh: Benjamini-Hochberg procedure controlling the False Discovery\n Rate (FDR).\n - bonferroni: Bonferroni correction fixing the family-wise error rate\n by multiplying the p-values with the number of comparisons. The Bonferroni\n correction is usually a too conservative adjustment compared to the others.\n - by: Procedure by Benjamini & Yekutieli for controlling the False\n Discovery Rate (FDR) under dependence.\n - holm: Hommel's method controlling family-wise error rate. It is\n uniformly more powerful than the Bonferroni correction.\n - hommel: Hommel's method, which is valid when hypothesis tests are\n independent. It is more expensive to compute than the other methods.\n\n By default, the number of comparisons for which the p-values should be\n corrected is equal to the number of provided p-values. Alternatively, it is\n possible to set `comparisons` to a number greater than the length of\n `pvals`. In that case, the methods assume `comparisons - pvals.length`\n unobserved p-values that are greater than all observed p-values (for Holm's\n method and the Bonferroni correction) or equal to `1` for the remaining\n methods.\n\n Parameters\n ----------\n pvals: Array\n P-values to be adjusted.\n\n method: string\n Correction method.\n\n comparisons: integer (optional)\n Number of comparisons. Default value: `pvals.length`.\n\n Returns\n -------\n out: Array\n Array containing the corrected p-values.\n\n Examples\n --------\n > var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\n > var out = padjust( pvalues, 'bh' )\n [ 0.04, 0.075, ~0.205, 0.6, 0.25 ]\n\n > out = padjust( pvalues, 'bonferroni' )\n [ 0.04, 0.15, 0.615, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'by' )\n [ ~0.457, ~0.856, 1.0, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'holm' )\n [ 0.2, 0.6, 1.0, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'hommel' )\n [ 0.16, 0.6, 1.0, 1.0, 1.0 ]\n\n","papply":"\npapply( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var add2 = papply( add, 2 );\n > var sum = add2( 3 )\n 5\n\n See Also\n --------\n papplyRight\n","papplyRight":"\npapplyRight( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function say( text, name ) { return text + ', ' + name + '.'; };\n > var toGrace = papplyRight( say, 'Grace Hopper' );\n > var str = toGrace( 'Hello' )\n 'Hello, Grace Hopper.'\n > str = toGrace( 'Thank you' )\n 'Thank you, Grace Hopper.'\n\n See Also\n --------\n papply\n","parallel":"\nparallel( files, [options,] clbk )\n Executes scripts in parallel.\n\n Relative file paths are resolved relative to the current working directory.\n\n Ordered script output does not imply that scripts are executed in order. To\n preserve script order, execute the scripts sequentially via some other\n means.\n\n Parameters\n ----------\n files: Array\n Script file paths.\n\n options: Object (optional)\n Options.\n\n options.cmd: string (optional)\n Executable file/command. Default: `'node'`.\n\n options.concurrency: integer (optional)\n Number of scripts to execute concurrently. Script concurrency cannot\n exceed the number of scripts. By specifying a concurrency greater than\n the number of workers, a worker may be executing more than `1` script at\n any one time. While not likely to be advantageous for synchronous\n scripts, setting a higher concurrency may be advantageous for scripts\n performing asynchronous tasks. If the script concurrency is less than\n the number of workers, the number of workers is reduced to match the\n specified concurrency. Default: `options.workers`.\n\n options.workers: integer (optional)\n Number of workers. Default: number of CPUs minus `1`.\n\n options.ordered: boolean (optional)\n Boolean indicating whether to preserve the order of script output. By\n default, the `stdio` output for each script is interleaved; i.e., the\n `stdio` output from one script may be interleaved with the `stdio`\n output from one or more other scripts. To preserve the `stdio` output\n order for each script, set the `ordered` option to `true`. Default:\n `false`.\n\n options.uid: integer (optional)\n Process user identity.\n\n options.gid: integer (optional)\n Process group identity.\n\n options.maxBuffer: integer (optional)\n Max child process `stdio` buffer size. This option is only applied when\n `options.ordered = true`. Default: `200*1024*1024`.\n\n clbk: Function\n Callback to invoke after executing all scripts.\n\n","parseJSON":"\nparseJSON( str[, reviver] )\n Attempts to parse a string as JSON.\n\n Function behavior differs from `JSON.parse()` as follows:\n\n - throws a `TypeError` if provided any value which is not a string.\n - throws a `TypeError` if provided a `reviver` argument which is not a\n function.\n - returns, rather than throws, a `SyntaxError` if unable to parse a string\n as JSON.\n\n Parameters\n ----------\n str: string\n String to parse.\n\n reviver: Function (optional)\n Transformation function.\n\n Returns\n -------\n out: any|Error\n Parsed value or an error.\n\n Examples\n --------\n > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n { 'beep': 'boop' }\n\n // Provide a reviver:\n > function reviver( key, value ) {\n ... if ( key === '' ) { return value; }\n ... if ( key === 'beep' ) { return value; }\n ... };\n > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n > var out = parseJSON( str, reviver )\n { 'beep': 'boop' }\n\n","pascalcase":"\npascalcase( str )\n Converts a string to Pascal case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Pascal-cased string.\n\n Examples\n --------\n > var out = pascalcase( 'Hello World!' )\n 'HelloWorld'\n > out = pascalcase( 'beep boop' )\n 'BeepBoop'\n\n See Also\n --------\n camelcase, constantcase, kebabcase, snakecase","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER\n \n\n // POSIX environment:\n > var path = '/usr/bin:/bin:/usr/sbin';\n > var parts = path.split( PATH_DELIMITER )\n [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n // Windows environment:\n > path = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\n > parts = path.split( PATH_DELIMITER )\n [ 'C:\\\\Windows\\system32', 'C:\\\\Windows' ]\n\n See Also\n --------\n PATH_DELIMITER_POSIX, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_POSIX\n ':'\n > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n > var paths = PATH.split( PATH_DELIMITER_POSIX )\n [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_WIN32\n ';'\n > var PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\n > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n [ 'C:\\\\Windows\\\\system32', 'C:\\\\Windows', 'C:\\\\Program Files\\\\node\\\\' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_POSIX\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n\n Examples\n --------\n > PATH_SEP\n \n\n // Windows environment:\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n // POSIX environment:\n > parts = 'foo/bar/baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP_POSIX, PATH_SEP_WIN32\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n\n Examples\n --------\n > PATH_SEP_POSIX\n '/'\n > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_WIN32\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n\n Examples\n --------\n > PATH_SEP_WIN32\n '\\\\'\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_POSIX\n","pcorrtest":"\npcorrtest( x, y[, options] )\n Computes a Pearson product-moment correlation test between paired samples.\n\n By default, the function performs a t-test for the null hypothesis that the\n data in arrays or typed arrays `x` and `y` is not correlated. A test against\n a different population correlation can be carried out by supplying the `rho`\n option. In this case, a test using the Fisher's z transform is conducted.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Nnumber in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.rho: number (optional)\n Number denoting the correlation under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the Pearson product-moment correlation\n coefficient. The confidence interval is calculated using Fisher's\n z-transform.\n\n out.nullValue: number\n Assumed correlation under H0 (equal to the supplied `rho` option).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var rho = 0.5;\n > var x = new Array( 300 );\n > var y = new Array( 300 );\n > for ( var i = 0; i < 300; i++ ) {\n ... x[ i ] = base.random.normal( 0.0, 1.0 );\n ... y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n ... base.sqrt( 1.0 - (rho*rho) ) );\n ... }\n > var out = pcorrtest( x, y )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 10.115805615994121,\n ci: [ 0.4161679018930295, 0.5853122968949995 ],\n alternative: 'two-sided',\n method: 't-test for Pearson correlation coefficient',\n nullValue: 0,\n pcorr: 0.505582072355616,\n }\n\n // Print output:\n > var table = out.print()\n t-test for Pearson correlation coefficient\n\n Alternative hypothesis: True correlation coefficient is not equal to 0\n\n pValue: 0\n statistic: 9.2106\n 95% confidence interval: [0.3776,0.5544]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n","percentEncode":"\npercentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = percentEncode( '☃' )\n '%E2%98%83'\n\n","PHI":"\nPHI\n Golden ratio.\n\n Examples\n --------\n > PHI\n 1.618033988749895\n\n","PI":"\nPI\n The mathematical constant `π`.\n\n Examples\n --------\n > PI\n 3.141592653589793\n\n See Also\n --------\n TWO_PI\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n\n Examples\n --------\n > PI_SQUARED\n 9.869604401089358\n\n See Also\n --------\n PI\n","pick":"\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n See Also\n --------\n pickBy\n","pickArguments":"\npickArguments( fcn, indices[, thisArg] )\n Returns a function that applies specified arguments to a provided function.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > var bar = pickArguments( foo, [ 0, 2 ] );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n reorderArguments, reverseArguments\n","pickBy":"\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n See Also\n --------\n pick\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n See Also\n --------\n NINF\n","pkg2alias":"\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n The function supports both internal and standalone package names.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n \n > v = pkg2alias( '@stdlib/math-base-special-sin' )\n \n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","pkg2related":"\npkg2related( pkg )\n Returns package names related to a specified package name.\n\n The function supports both internal and standalone package names.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: Array|null\n Related package names.\n\n Examples\n --------\n > var v = pkg2related( '@stdlib/math/base/special/sin' )\n [...]\n > v = pkg2related( '@stdlib/math-base-special-sin' )\n [...]\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","pkg2standalone":"\npkg2standalone( pkg )\n Returns the standalone package name associated with a provided internal\n package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Standalone package name.\n\n Examples\n --------\n > var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n '@stdlib/math-base-special-sin'\n\n See Also\n --------\n alias2pkg, alias2standalone, aliases, pkg2alias, pkg2related\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n See Also\n --------\n ARCH\n","plot":"\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n See Also\n --------\n Plot\n","Plot":"\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n See Also\n --------\n plot\n","pluck":"\npluck( arr, prop[, options] )\n Extracts a property value from each element of an object array.\n\n The function skips `null` and `undefined` array elements.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n prop: string\n Property to access.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. To mutate the\n input data structure (e.g., when input values can be discarded or when\n optimizing memory usage), set the `copy` option to `false`. Default:\n true.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > var out = pluck( arr, 'a' )\n [ 1, 0.5 ]\n\n > arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > out = pluck( arr, 'a', { 'copy': false } )\n [ 1, 0.5 ]\n > var bool = ( arr[ 0 ] === out[ 0 ] )\n true\n\n See Also\n --------\n deepPluck, pick\n","pop":"\npop( collection )\n Removes and returns the last element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = pop( arr )\n [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = pop( arr )\n [ [ 1.0 ], 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = pop( arr )\n [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n See Also\n --------\n push, shift, unshift\n","porterStemmer":"\nporterStemmer( word )\n Extracts the stem of a given word.\n\n Parameters\n ----------\n word: string\n Input word.\n\n Returns\n -------\n out: string\n Word stem.\n\n Examples\n --------\n > var out = porterStemmer( 'walking' )\n 'walk'\n > out = porterStemmer( 'walked' )\n 'walk'\n > out = porterStemmer( 'walks' )\n 'walk'\n > out = porterStemmer( '' )\n ''\n\n","prepend":"\nprepend( collection1, collection2 )\n Adds the elements of one collection to the beginning of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = prepend( arr, [ 6.0, 7.0 ] )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = prepend( arr, [ 3.0, 4.0 ] )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = prepend( arr, [ 2.0, 3.0 ] )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n append, unshift\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str[, fromIndex] )\n Returns the previous extended grapheme cluster break in a string before a\n specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n fromIndex: integer (optional)\n Position. Default: str.length-1.\n\n Returns\n -------\n out: integer\n Previous extended grapheme cluster break position.\n\n Examples\n --------\n > var out = prevGraphemeClusterBreak( 'last man standing', 4 )\n 3\n > out = prevGraphemeClusterBreak( 'presidential election', 8 )\n 7\n > out = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\n 0\n > out = prevGraphemeClusterBreak( '🌷', 1 )\n -1\n\n See Also\n --------\n numGraphemeClusters, nextGraphemeClusterBreak","PRIMES_100K":"\nPRIMES_100K()\n Returns an array containing the first 100,000 prime numbers.\n\n Returns\n -------\n out: Array\n List of primes.\n\n Examples\n --------\n > var list = PRIMES_100K()\n [ 2, 3, 5, ... ]\n\n See Also\n --------\n iterPrimesSeq\n","properties":"\nproperties( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable and non-enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = properties( obj )\n [ 'beep' ]\n\n See Also\n --------\n defineProperties, inheritedProperties, propertiesIn, propertyNames, propertySymbols\n","propertiesIn":"\npropertiesIn( value )\n Returns an array of an object's own and inherited property names and\n symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited property names and symbols.\n\n Examples\n --------\n > var props = propertiesIn( [] )\n\n See Also\n --------\n defineProperties, inheritedProperties, properties, propertyNamesIn, propertySymbolsIn\n","propertyDescriptor":"\npropertyDescriptor( value, property )\n Returns a property descriptor for an object's own property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptor( obj, 'a' )\n {...}\n\n See Also\n --------\n hasOwnProp, defineProperty, propertyDescriptorIn, propertyDescriptors\n","propertyDescriptorIn":"\npropertyDescriptorIn( value, property )\n Returns a property descriptor for an object's own or inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptorIn( obj, 'a' )\n {...}\n\n See Also\n --------\n hasProp, defineProperty, propertyDescriptor, propertyDescriptorsIn\n","propertyDescriptors":"\npropertyDescriptors( value )\n Returns an object's own property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n Property descriptors.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptors( obj )\n { 'a': {...} }\n\n See Also\n --------\n defineProperty, defineProperties, propertyDescriptor, propertyDescriptorsIn, propertyNames, propertySymbols\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value )\n Returns an object's own and inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n An object's own and inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = propertyDescriptorsIn( obj )\n { 'beep': {...}, 'foo': {...}, ... }\n\n See Also\n --------\n defineProperties, propertyDescriptorIn, propertyDescriptors, propertyNamesIn, propertySymbolsIn\n","propertyNames":"\npropertyNames( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable and non-enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNames( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNames, propertyNamesIn, propertySymbols\n","propertyNamesIn":"\npropertyNamesIn( value )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable and non-enumerable\n property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNamesIn( obj )\n e.g., [ 'beep', 'foo', ... ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNamesIn, propertyNames, propertySymbolsIn\n","propertySymbols":"\npropertySymbols( value )\n Returns an array of an object's own symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own symbol properties.\n\n Examples\n --------\n > var s = propertySymbols( {} )\n\n See Also\n --------\n propertyNames, propertySymbolsIn\n","propertySymbolsIn":"\npropertySymbolsIn( value )\n Returns an array of an object's own and inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited symbol properties.\n\n Examples\n --------\n > var s = propertySymbolsIn( [] )\n\n See Also\n --------\n propertyNamesIn, propertySymbols\n","Proxy":"\nProxy( target, handlers )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n\n The following \"traps\" are supported:\n\n - getPrototypeOf( target )\n Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n `instanceof` operator. The method must return an object or `null`.\n\n - setPrototypeOf( target, prototype )\n Trap for `Object.setPrototypeOf()`. The method must return a boolean\n indicating if the prototype was successfully set.\n\n - isExtensible( target )\n Trap for `Object.isExtensible()`. The method must return a boolean.\n\n - preventExtensions( target )\n Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n - getOwnPropertyDescriptor( target, property )\n Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n object or `undefined`.\n\n - defineProperty( target, property, descriptor )\n Trap for `Object.defineProperty()`. The method must return a boolean\n indicating whether the operation succeeded.\n\n - has( target, property )\n Trap for the `in` operator. The method must return a boolean.\n\n - get( target, property, receiver )\n Trap for retrieving property values. The method can return any value.\n\n - set( target, property, value, receiver )\n Trap for setting property values. The method should return a boolean\n indicating whether assignment succeeded.\n\n - deleteProperty( target, property )\n Trap for the `delete` operator. The method must return a boolean\n indicating whether operation succeeded.\n\n - ownKeys( target )\n Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n `Object.getOwnPropertySymbols()`. The method must return an enumerable\n object.\n\n - apply( target, thisArg, argumentsList )\n Trap for a function call. The method can return any value.\n\n - construct( target, argumentsList, newTarget )\n Trap for the `new` operator. The method must return an object.\n\n All traps are optional. If a trap is not defined, the default behavior is to\n forward the operation to the target.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Proxy object.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = new Proxy( {}, h );\n > p.a = 3.14;\n > p.a\n 6.28\n\n\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();\n\n","Proxy.revocable":"\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();","push":"\npush( collection, ...items )\n Adds one or more elements to the end of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = push( arr, 6.0, 7.0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = push( arr, 3.0, 4.0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = push( arr, 1.0, 2.0 )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n pop, shift, unshift\n","quarterOfYear":"\nquarterOfYear( [month] )\n Returns the quarter of the year.\n\n By default, the function returns the quarter of the year for the current\n month in the current year (according to local time). To determine the\n quarter for a particular month, provide either a month or a `Date`\n object.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n Parameters\n ----------\n month: integer|string|Date (optional)\n Month (or `Date`).\n\n Returns\n -------\n out: integer\n Quarter of the year.\n\n Examples\n --------\n > var q = quarterOfYear( new Date() )\n \n > q = quarterOfYear( 4 )\n 2\n > q = quarterOfYear( 'June' )\n 2\n\n // Other ways to supply month:\n > q = quarterOfYear( 'April' )\n 2\n > q = quarterOfYear( 'apr' )\n 2\n\n See Also\n --------\n dayOfYear\n","random.array.arcsine":"\nrandom.array.arcsine( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from an arcsine\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.arcsine.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.arcsine.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.arcsine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.arcsine.PRNG;\n\n\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.arcsine.seed;\n\n\nrandom.array.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.arcsine.seedLength;\n\n\nrandom.array.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.arcsine.state\n \n\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.arcsine.stateLength;\n\n\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.arcsine.byteLength;\n\n See Also\n --------\n base.random.arcsine, random.strided.arcsine\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.arcsine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.arcsine.PRNG;","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.arcsine.seed;","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.arcsine.seedLength;","random.array.arcsine.state":"\nrandom.array.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.arcsine.state\n \n\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n ","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.arcsine.stateLength;","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.arcsine.byteLength;\n\n See Also\n --------\n base.random.arcsine, random.strided.arcsine","random.array.bernoulli":"\nrandom.array.bernoulli( len, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n\nrandom.array.bernoulli.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.bernoulli.assign( 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.bernoulli.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.bernoulli.factory();\n > var out = fcn( 3, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.bernoulli.factory( 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.bernoulli.PRNG;\n\n\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.bernoulli.seed;\n\n\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.bernoulli.seedLength;\n\n\nrandom.array.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.bernoulli.state\n \n\n > out = random.array.bernoulli( 3, 0.5 )\n \n > out = random.array.bernoulli( 3, 0.5 )\n \n\n // Set the state:\n > random.array.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.array.bernoulli( 3, 0.5 )\n \n\n\nrandom.array.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.bernoulli.stateLength;\n\n\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.strided.bernoulli\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.bernoulli.assign( 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.bernoulli.factory();\n > var out = fcn( 3, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.bernoulli.factory( 0.5 );\n > out = fcn( 3 )\n ","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.bernoulli.PRNG;","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.bernoulli.seed;","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.bernoulli.seedLength;","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.bernoulli.state\n \n\n > out = random.array.bernoulli( 3, 0.5 )\n \n > out = random.array.bernoulli( 3, 0.5 )\n \n\n // Set the state:\n > random.array.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.array.bernoulli( 3, 0.5 )\n ","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.bernoulli.stateLength;","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.strided.bernoulli","random.array.beta":"\nrandom.array.beta( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a beta\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n\nrandom.array.beta.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.beta.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.beta.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.beta.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.beta.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.beta.PRNG;\n\n\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.beta.seed;\n\n\nrandom.array.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.beta.seedLength;\n\n\nrandom.array.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.beta.state\n \n\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n\nrandom.array.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.beta.stateLength;\n\n\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.strided.beta\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.beta.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.beta.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.beta.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.beta.PRNG;","random.array.beta.seed":"\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.beta.seed;","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.beta.seedLength;","random.array.beta.state":"\nrandom.array.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.beta.state\n \n\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.array.beta( 3, 2.0, 5.0 )\n ","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.beta.stateLength;","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.strided.beta","random.array.betaprime":"\nrandom.array.betaprime( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n\nrandom.array.betaprime.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.betaprime.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.betaprime.PRNG;\n\n\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.betaprime.seed;\n\n\nrandom.array.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.betaprime.seedLength;\n\n\nrandom.array.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.betaprime.state\n \n\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n\nrandom.array.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.betaprime.stateLength;\n\n\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.strided.betaprime\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.betaprime.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.betaprime.PRNG;","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.betaprime.seed;","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.betaprime.seedLength;","random.array.betaprime.state":"\nrandom.array.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.betaprime.state\n \n\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n ","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.betaprime.stateLength;","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.strided.betaprime","random.array.binomial":"\nrandom.array.binomial( len, n, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a binomial\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n\nrandom.array.binomial.assign( n, p, out )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n Parameters\n ----------\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.binomial.assign( 17, 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.binomial.factory( [n, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n n: number (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.binomial.factory();\n > var out = fcn( 3, 17, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.binomial.factory( 17, 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.binomial.PRNG;\n\n\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.binomial.seed;\n\n\nrandom.array.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.binomial.seedLength;\n\n\nrandom.array.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.binomial.state\n \n\n > out = random.array.binomial( 3, 17, 0.5 )\n \n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Set the state:\n > random.array.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n\nrandom.array.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.binomial.stateLength;\n\n\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.binomial.byteLength;\n\n See Also\n --------\n random.array.negativeBinomial, base.random.binomial\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n, p, out )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n Parameters\n ----------\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.binomial.assign( 17, 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n n: number (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.binomial.factory();\n > var out = fcn( 3, 17, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.binomial.factory( 17, 0.5 );\n > out = fcn( 3 )\n ","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.binomial.PRNG;","random.array.binomial.seed":"\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.binomial.seed;","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.binomial.seedLength;","random.array.binomial.state":"\nrandom.array.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.binomial.state\n \n\n > out = random.array.binomial( 3, 17, 0.5 )\n \n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Set the state:\n > random.array.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.binomial( 3, 17, 0.5 )\n ","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.binomial.stateLength;","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.binomial.byteLength;\n\n See Also\n --------\n random.array.negativeBinomial, base.random.binomial","random.array.cauchy":"\nrandom.array.cauchy( len, x0, gamma[, options] )\n Returns an array containing pseudorandom numbers drawn from a Cauchy\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cauchy.assign( x0, gamma, out )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n gamma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cauchy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cauchy.PRNG;\n\n\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cauchy.seed;\n\n\nrandom.array.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cauchy.seedLength;\n\n\nrandom.array.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cauchy.state\n \n\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cauchy.stateLength;\n\n\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cauchy.byteLength;\n\n See Also\n --------\n base.random.cauchy\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0, gamma, out )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n gamma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cauchy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cauchy.PRNG;","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cauchy.seed;","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cauchy.seedLength;","random.array.cauchy.state":"\nrandom.array.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cauchy.state\n \n\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n ","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cauchy.stateLength;","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cauchy.byteLength;\n\n See Also\n --------\n base.random.cauchy","random.array.chi":"\nrandom.array.chi( len, k[, options] )\n Returns an array containing pseudorandom numbers drawn from a chi\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n\nrandom.array.chi.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chi.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.chi.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chi.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chi.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chi.PRNG;\n\n\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chi.seed;\n\n\nrandom.array.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chi.seedLength;\n\n\nrandom.array.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chi.state\n \n\n > out = random.array.chi( 3, 2.0 )\n \n > out = random.array.chi( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chi( 3, 2.0 )\n \n\n\nrandom.array.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chi.stateLength;\n\n\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.strided.chi\n","random.array.chi.assign":"\nrandom.array.chi.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chi.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.chi.factory":"\nrandom.array.chi.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chi.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chi.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chi.PRNG;","random.array.chi.seed":"\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chi.seed;","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chi.seedLength;","random.array.chi.state":"\nrandom.array.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chi.state\n \n\n > out = random.array.chi( 3, 2.0 )\n \n > out = random.array.chi( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chi( 3, 2.0 )\n ","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chi.stateLength;","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.strided.chi","random.array.chisquare":"\nrandom.array.chisquare( len, k[, options] )\n Returns an array containing pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n\nrandom.array.chisquare.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chisquare.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.chisquare.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chisquare.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chisquare.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chisquare.PRNG;\n\n\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chisquare.seed;\n\n\nrandom.array.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chisquare.seedLength;\n\n\nrandom.array.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chisquare.state\n \n\n > out = random.array.chisquare( 3, 2.0 )\n \n > out = random.array.chisquare( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chisquare( 3, 2.0 )\n \n\n\nrandom.array.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chisquare.stateLength;\n\n\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.strided.chisquare\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chisquare.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chisquare.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chisquare.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chisquare.PRNG;","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chisquare.seed;","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chisquare.seedLength;","random.array.chisquare.state":"\nrandom.array.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chisquare.state\n \n\n > out = random.array.chisquare( 3, 2.0 )\n \n > out = random.array.chisquare( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chisquare( 3, 2.0 )\n ","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chisquare.stateLength;","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.strided.chisquare","random.array.cosine":"\nrandom.array.cosine( len, mu, s[, options] )\n Returns an array containing pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cosine.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cosine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.cosine.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cosine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cosine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cosine.PRNG;\n\n\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cosine.seed;\n\n\nrandom.array.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cosine.seedLength;\n\n\nrandom.array.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cosine.state\n \n\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cosine.stateLength;\n\n\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cosine.byteLength;\n\n See Also\n --------\n base.random.cosine, random.strided.cosine\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cosine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cosine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cosine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cosine.PRNG;","random.array.cosine.seed":"\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cosine.seed;","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cosine.seedLength;","random.array.cosine.state":"\nrandom.array.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cosine.state\n \n\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cosine( 3, 2.0, 5.0 )\n ","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cosine.stateLength;","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cosine.byteLength;\n\n See Also\n --------\n base.random.cosine, random.strided.cosine","random.array.discreteUniform":"\nrandom.array.discreteUniform( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n\nrandom.array.discreteUniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.discreteUniform.assign( -10, 10, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.discreteUniform.factory();\n > var out = fcn( 3, -10, 10 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.discreteUniform.factory( -10, 10 );\n > out = fcn( 3 )\n \n\n\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.discreteUniform.PRNG;\n\n\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.discreteUniform.seed;\n\n\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.discreteUniform.seedLength;\n\n\nrandom.array.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.array.discreteUniform.state\n \n\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Set the state:\n > random.array.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.discreteUniform.stateLength;\n\n\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.discreteUniform.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.discreteUniform.assign( -10, 10, x )\n \n > var bool = ( out === x )\n true","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.discreteUniform.factory();\n > var out = fcn( 3, -10, 10 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.discreteUniform.factory( -10, 10 );\n > out = fcn( 3 )\n ","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.discreteUniform.PRNG;","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.discreteUniform.seed;","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.discreteUniform.seedLength;","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.array.discreteUniform.state\n \n\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Set the state:\n > random.array.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.discreteUniform( 3, -10, 10 )\n ","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.discreteUniform.stateLength;","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.discreteUniform.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform","random.array.erlang":"\nrandom.array.erlang( len, k, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from an Erlang\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n\nrandom.array.erlang.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.erlang.assign( 2, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.erlang.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.erlang.factory();\n > var out = fcn( 3, 2, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.erlang.factory( 2, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.erlang.PRNG;\n\n\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.erlang.seed;\n\n\nrandom.array.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.erlang.seedLength;\n\n\nrandom.array.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.erlang.state\n \n\n > out = random.array.erlang( 3, 2, 5.0 )\n \n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Set the state:\n > random.array.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n\nrandom.array.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.erlang.stateLength;\n\n\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.erlang.byteLength;\n\n See Also\n --------\n base.random.erlang\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.erlang.assign( 2, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.erlang.factory();\n > var out = fcn( 3, 2, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.erlang.factory( 2, 5.0 );\n > out = fcn( 3 )\n ","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.erlang.PRNG;","random.array.erlang.seed":"\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.erlang.seed;","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.erlang.seedLength;","random.array.erlang.state":"\nrandom.array.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.erlang.state\n \n\n > out = random.array.erlang( 3, 2, 5.0 )\n \n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Set the state:\n > random.array.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.array.erlang( 3, 2, 5.0 )\n ","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.erlang.stateLength;","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.erlang.byteLength;\n\n See Also\n --------\n base.random.erlang","random.array.exponential":"\nrandom.array.exponential( len, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n lambda: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n\nrandom.array.exponential.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.exponential.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.exponential.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.exponential.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.exponential.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.exponential.PRNG;\n\n\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.exponential.seed;\n\n\nrandom.array.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.exponential.seedLength;\n\n\nrandom.array.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.exponential.state\n \n\n > out = random.array.exponential( 3, 2.0 )\n \n > out = random.array.exponential( 3, 2.0 )\n \n\n // Set the state:\n > random.array.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.array.exponential( 3, 2.0 )\n \n\n\nrandom.array.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.exponential.stateLength;\n\n\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.strided.exponential\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.exponential.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.exponential.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.exponential.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.exponential.PRNG;","random.array.exponential.seed":"\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.exponential.seed;","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.exponential.seedLength;","random.array.exponential.state":"\nrandom.array.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.exponential.state\n \n\n > out = random.array.exponential( 3, 2.0 )\n \n > out = random.array.exponential( 3, 2.0 )\n \n\n // Set the state:\n > random.array.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.array.exponential( 3, 2.0 )\n ","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.exponential.stateLength;","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.strided.exponential","random.array.f":"\nrandom.array.f( len, d1, d2[, options] )\n Returns an array containing pseudorandom numbers drawn from an F\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n\nrandom.array.f.assign( d1, d2, out )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.f.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.f.factory( [d1, d2, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.f.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.f.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.f.PRNG;\n\n\nrandom.array.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.f.seed;\n\n\nrandom.array.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.f.seedLength;\n\n\nrandom.array.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.f.state\n \n\n > out = random.array.f( 3, 2.0, 5.0 )\n \n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.f.state = state;\n\n // Regenerate a previous array:\n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n\nrandom.array.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.f.stateLength;\n\n\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.f.byteLength;\n\n See Also\n --------\n base.random.f\n","random.array.f.assign":"\nrandom.array.f.assign( d1, d2, out )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.f.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.f.factory":"\nrandom.array.f.factory( [d1, d2, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.f.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.f.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.f.PRNG":"\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.f.PRNG;","random.array.f.seed":"\nrandom.array.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.f.seed;","random.array.f.seedLength":"\nrandom.array.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.f.seedLength;","random.array.f.state":"\nrandom.array.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.f.state\n \n\n > out = random.array.f( 3, 2.0, 5.0 )\n \n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.f.state = state;\n\n // Regenerate a previous array:\n > out = random.array.f( 3, 2.0, 5.0 )\n ","random.array.f.stateLength":"\nrandom.array.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.f.stateLength;","random.array.f.byteLength":"\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.f.byteLength;\n\n See Also\n --------\n base.random.f","random.array.frechet":"\nrandom.array.frechet( len, alpha, s, m[, options] )\n Returns an array containing pseudorandom numbers drawn from a Fréchet\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.frechet.assign( alpha, s, m, out )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.frechet.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.frechet.PRNG;\n\n\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.frechet.seed;\n\n\nrandom.array.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.frechet.seedLength;\n\n\nrandom.array.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.frechet.state\n \n\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.frechet.stateLength;\n\n\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha, s, m, out )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.frechet.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n ","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.frechet.PRNG;","random.array.frechet.seed":"\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.frechet.seed;","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.frechet.seedLength;","random.array.frechet.state":"\nrandom.array.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.frechet.state\n \n\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n ","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.frechet.stateLength;","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet","random.array.gamma":"\nrandom.array.gamma( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a gamma\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gamma.PRNG;\n\n\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gamma.seed;\n\n\nrandom.array.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gamma.seedLength;\n\n\nrandom.array.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gamma.state\n \n\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gamma.stateLength;\n\n\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gamma.byteLength;\n\n See Also\n --------\n base.random.gamma, random.strided.gamma\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gamma.PRNG;","random.array.gamma.seed":"\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gamma.seed;","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gamma.seedLength;","random.array.gamma.state":"\nrandom.array.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gamma.state\n \n\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gamma( 3, 2.0, 5.0 )\n ","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gamma.stateLength;","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gamma.byteLength;\n\n See Also\n --------\n base.random.gamma, random.strided.gamma","random.array.geometric":"\nrandom.array.geometric( len, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n\nrandom.array.geometric.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.geometric.assign( 0.01, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.geometric.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.geometric.factory();\n > var out = fcn( 3, 0.01 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.geometric.factory( 0.01 );\n > out = fcn( 3 )\n \n\n\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.geometric.PRNG;\n\n\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.geometric.seed;\n\n\nrandom.array.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.geometric.seedLength;\n\n\nrandom.array.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.array.geometric.state\n \n\n > out = random.array.geometric( 3, 0.01 )\n \n > out = random.array.geometric( 3, 0.01 )\n \n\n // Set the state:\n > random.array.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.geometric( 3, 0.01 )\n \n\n\nrandom.array.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.geometric.stateLength;\n\n\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.strided.geometric\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.geometric.assign( 0.01, x )\n \n > var bool = ( out === x )\n true","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.geometric.factory();\n > var out = fcn( 3, 0.01 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.geometric.factory( 0.01 );\n > out = fcn( 3 )\n ","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.geometric.PRNG;","random.array.geometric.seed":"\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.geometric.seed;","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.geometric.seedLength;","random.array.geometric.state":"\nrandom.array.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.array.geometric.state\n \n\n > out = random.array.geometric( 3, 0.01 )\n \n > out = random.array.geometric( 3, 0.01 )\n \n\n // Set the state:\n > random.array.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.geometric( 3, 0.01 )\n ","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.geometric.stateLength;","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.strided.geometric","random.array.gumbel":"\nrandom.array.gumbel( len, mu, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a Gumbel\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gumbel.assign( mu, beta, out )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gumbel.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gumbel.PRNG;\n\n\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gumbel.seed;\n\n\nrandom.array.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gumbel.seedLength;\n\n\nrandom.array.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gumbel.state\n \n\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gumbel.stateLength;\n\n\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gumbel.byteLength;\n\n See Also\n --------\n base.random.gumbel\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu, beta, out )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gumbel.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gumbel.PRNG;","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gumbel.seed;","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gumbel.seedLength;","random.array.gumbel.state":"\nrandom.array.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gumbel.state\n \n\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n ","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gumbel.stateLength;","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gumbel.byteLength;\n\n See Also\n --------\n base.random.gumbel","random.array.hypergeometric":"\nrandom.array.hypergeometric( len, N, K, n[, options] )\n Returns an array containing pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n\nrandom.array.hypergeometric.assign( N, K, n, out )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n N: number (optional)\n Population size.\n\n K: number (optional)\n Subpopulation size.\n\n n: number (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.hypergeometric.factory();\n > var out = fcn( 3, 20, 10, 7 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n > out = fcn( 3 )\n \n\n\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.hypergeometric.PRNG;\n\n\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.hypergeometric.seed;\n\n\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.hypergeometric.seedLength;\n\n\nrandom.array.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.array.hypergeometric.state\n \n\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Set the state:\n > random.array.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.hypergeometric.stateLength;\n\n\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N, K, n, out )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n \n > var bool = ( out === x )\n true","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n N: number (optional)\n Population size.\n\n K: number (optional)\n Subpopulation size.\n\n n: number (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.hypergeometric.factory();\n > var out = fcn( 3, 20, 10, 7 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n > out = fcn( 3 )\n ","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.hypergeometric.PRNG;","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.hypergeometric.seed;","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.hypergeometric.seedLength;","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.array.hypergeometric.state\n \n\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Set the state:\n > random.array.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n ","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.hypergeometric.stateLength;","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric","random.array.invgamma":"\nrandom.array.invgamma( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.invgamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.invgamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.invgamma.PRNG;\n\n\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.invgamma.seed;\n\n\nrandom.array.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.invgamma.seedLength;\n\n\nrandom.array.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.invgamma.state\n \n\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.invgamma.stateLength;\n\n\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.invgamma.byteLength;\n\n See Also\n --------\n base.random.invgamma, random.strided.invgamma\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.invgamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.invgamma.PRNG;","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.invgamma.seed;","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.invgamma.seedLength;","random.array.invgamma.state":"\nrandom.array.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.invgamma.state\n \n\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n ","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.invgamma.stateLength;","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.invgamma.byteLength;\n\n See Also\n --------\n base.random.invgamma, random.strided.invgamma","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n double bounded distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.kumaraswamy.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.kumaraswamy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.kumaraswamy.PRNG;\n\n\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.kumaraswamy.seed;\n\n\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.seedLength;\n\n\nrandom.array.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.kumaraswamy.state\n \n\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.stateLength;\n\n\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.kumaraswamy.byteLength;\n\n See Also\n --------\n base.random.kumaraswamy\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.kumaraswamy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.kumaraswamy.PRNG;","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.kumaraswamy.seed;","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.seedLength;","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.kumaraswamy.state\n \n\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n ","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.stateLength;","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.kumaraswamy.byteLength;\n\n See Also\n --------\n base.random.kumaraswamy","random.array.laplace":"\nrandom.array.laplace( len, mu, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n\nrandom.array.laplace.assign( mu, b, out )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.laplace.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.laplace.factory( [mu, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.laplace.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.laplace.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.laplace.PRNG;\n\n\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.laplace.seed;\n\n\nrandom.array.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.laplace.seedLength;\n\n\nrandom.array.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.laplace.state\n \n\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n\nrandom.array.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.laplace.stateLength;\n\n\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.laplace.byteLength;\n\n See Also\n --------\n base.random.laplace\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu, b, out )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.laplace.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.laplace.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.laplace.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.laplace.PRNG;","random.array.laplace.seed":"\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.laplace.seed;","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.laplace.seedLength;","random.array.laplace.state":"\nrandom.array.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.laplace.state\n \n\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.array.laplace( 3, 2.0, 5.0 )\n ","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.laplace.stateLength;","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.laplace.byteLength;\n\n See Also\n --------\n base.random.laplace","random.array.levy":"\nrandom.array.levy( len, mu, c[, options] )\n Returns an array containing pseudorandom numbers drawn from a Lévy\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.levy.assign( mu, c, out )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.levy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.levy.factory( [mu, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.levy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.levy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.levy.PRNG;\n\n\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.levy.seed;\n\n\nrandom.array.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.levy.seedLength;\n\n\nrandom.array.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.levy.state\n \n\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.levy.stateLength;\n\n\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.levy.byteLength;\n\n See Also\n --------\n base.random.levy\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu, c, out )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.levy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.levy.factory":"\nrandom.array.levy.factory( [mu, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.levy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.levy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.levy.PRNG;","random.array.levy.seed":"\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.levy.seed;","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.levy.seedLength;","random.array.levy.state":"\nrandom.array.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.levy.state\n \n\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.levy( 3, 2.0, 5.0 )\n ","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.levy.stateLength;","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.levy.byteLength;\n\n See Also\n --------\n base.random.levy","random.array.logistic":"\nrandom.array.logistic( len, mu, s[, options] )\n Returns an array containing pseudorandom numbers drawn from a logistic\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n\nrandom.array.logistic.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n Parameters\n ----------\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.logistic.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.logistic.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.logistic.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.logistic.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.logistic.PRNG;\n\n\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.logistic.seed;\n\n\nrandom.array.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.logistic.seedLength;\n\n\nrandom.array.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.logistic.state\n \n\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n\nrandom.array.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.logistic.stateLength;\n\n\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.logistic.byteLength;\n\n See Also\n --------\n base.random.logistic\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n Parameters\n ----------\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.logistic.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.logistic.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.logistic.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.logistic.PRNG;","random.array.logistic.seed":"\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.logistic.seed;","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.logistic.seedLength;","random.array.logistic.state":"\nrandom.array.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.logistic.state\n \n\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.array.logistic( 3, 2.0, 5.0 )\n ","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.logistic.stateLength;","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.logistic.byteLength;\n\n See Also\n --------\n base.random.logistic","random.array.lognormal":"\nrandom.array.lognormal( len, mu, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.lognormal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.lognormal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.lognormal.PRNG;\n\n\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.lognormal.seed;\n\n\nrandom.array.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.lognormal.seedLength;\n\n\nrandom.array.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.lognormal.state\n \n\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.lognormal.stateLength;\n\n\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.lognormal.byteLength;\n\n See Also\n --------\n base.random.lognormal, random.strided.lognormal\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.lognormal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.lognormal.PRNG;","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.lognormal.seed;","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.lognormal.seedLength;","random.array.lognormal.state":"\nrandom.array.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.lognormal.state\n \n\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n ","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.lognormal.stateLength;","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.lognormal.byteLength;\n\n See Also\n --------\n base.random.lognormal, random.strided.lognormal","random.array.minstd":"\nrandom.array.minstd( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n\nrandom.array.minstd.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd.normalized( 3 )\n \n\n\nrandom.array.minstd.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstd.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstd.PRNG;\n\n\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstd.seed;\n\n\nrandom.array.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstd.seedLength;\n\n\nrandom.array.minstd.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstd.state;\n\n > out = random.array.minstd( 3 )\n \n > out = random.array.minstd( 3 )\n \n\n // Set the state:\n > random.array.minstd.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstd( 3 )\n \n\n\nrandom.array.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstd.stateLength;\n\n\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstd.byteLength;\n\n See Also\n --------\n random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd.normalized( 3 )\n ","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstd.factory();\n > var out = fcn( 3 )\n ","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstd.PRNG;","random.array.minstd.seed":"\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstd.seed;","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstd.seedLength;","random.array.minstd.state":"\nrandom.array.minstd.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstd.state;\n\n > out = random.array.minstd( 3 )\n \n > out = random.array.minstd( 3 )\n \n\n // Set the state:\n > random.array.minstd.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstd( 3 )\n ","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstd.stateLength;","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstd.byteLength;\n\n See Also\n --------\n random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n\nrandom.array.minstdShuffle.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle.normalized( 3 )\n \n\n\nrandom.array.minstdShuffle.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstdShuffle.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstdShuffle.PRNG;\n\n\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstdShuffle.seed;\n\n\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.seedLength;\n\n\nrandom.array.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstdShuffle.state;\n\n > out = random.array.minstdShuffle( 3 )\n \n > out = random.array.minstdShuffle( 3 )\n \n\n // Set the state:\n > random.array.minstdShuffle.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstdShuffle( 3 )\n \n\n\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.stateLength;\n\n\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstdShuffle.byteLength;\n\n See Also\n --------\n random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle.normalized( 3 )\n ","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstdShuffle.factory();\n > var out = fcn( 3 )\n ","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstdShuffle.PRNG;","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstdShuffle.seed;","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.seedLength;","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstdShuffle.state;\n\n > out = random.array.minstdShuffle( 3 )\n \n > out = random.array.minstdShuffle( 3 )\n \n\n // Set the state:\n > random.array.minstdShuffle.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstdShuffle( 3 )\n ","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.stateLength;","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstdShuffle.byteLength;\n\n See Also\n --------\n random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle","random.array.mt19937":"\nrandom.array.mt19937( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[0, 4294967295]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n\nrandom.array.mt19937.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937.normalized( 3 )\n \n\n\nrandom.array.mt19937.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.mt19937.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.mt19937.PRNG;\n\n\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.mt19937.seed;\n\n\nrandom.array.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.mt19937.seedLength;\n\n\nrandom.array.mt19937.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.mt19937.state;\n\n > out = random.array.mt19937( 3 )\n \n > out = random.array.mt19937( 3 )\n \n\n // Set the state:\n > random.array.mt19937.state = state;\n\n // Regenerate a previous array:\n > out = random.array.mt19937( 3 )\n \n\n\nrandom.array.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.mt19937.stateLength;\n\n\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.mt19937.byteLength;\n\n See Also\n --------\n random.array.randu, base.random.mt19937, random.strided.mt19937\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937.normalized( 3 )\n ","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.mt19937.factory();\n > var out = fcn( 3 )\n ","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.mt19937.PRNG;","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.mt19937.seed;","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.mt19937.seedLength;","random.array.mt19937.state":"\nrandom.array.mt19937.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.mt19937.state;\n\n > out = random.array.mt19937( 3 )\n \n > out = random.array.mt19937( 3 )\n \n\n // Set the state:\n > random.array.mt19937.state = state;\n\n // Regenerate a previous array:\n > out = random.array.mt19937( 3 )\n ","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.mt19937.stateLength;","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.mt19937.byteLength;\n\n See Also\n --------\n random.array.randu, base.random.mt19937, random.strided.mt19937","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len, r, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a negative\n binomial distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n\nrandom.array.negativeBinomial.assign( r, p, out )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.negativeBinomial.factory();\n > var out = fcn( 3, 10, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.negativeBinomial.PRNG;\n\n\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.negativeBinomial.seed;\n\n\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.seedLength;\n\n\nrandom.array.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.negativeBinomial.state\n \n\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Set the state:\n > random.array.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.stateLength;\n\n\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.negativeBinomial.byteLength;\n\n See Also\n --------\n random.array.binomial, base.random.negativeBinomial\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r, p, out )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.negativeBinomial.factory();\n > var out = fcn( 3, 10, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n > out = fcn( 3 )\n ","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.negativeBinomial.PRNG;","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.negativeBinomial.seed;","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.seedLength;","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.negativeBinomial.state\n \n\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Set the state:\n > random.array.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n ","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.stateLength;","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.negativeBinomial.byteLength;\n\n See Also\n --------\n random.array.binomial, base.random.negativeBinomial","random.array.normal":"\nrandom.array.normal( len, mu, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a normal\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.normal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.normal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.normal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n sigma: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.normal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.normal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.normal.PRNG;\n\n\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.normal.seed;\n\n\nrandom.array.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.normal.seedLength;\n\n\nrandom.array.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.normal.state\n \n\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.normal.stateLength;\n\n\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.normal.byteLength;\n\n See Also\n --------\n base.random.normal, random.strided.normal\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.normal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.normal.factory":"\nrandom.array.normal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n sigma: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.normal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.normal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.normal.PRNG;","random.array.normal.seed":"\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.normal.seed;","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.normal.seedLength;","random.array.normal.state":"\nrandom.array.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.normal.state\n \n\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.normal( 3, 2.0, 5.0 )\n ","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.normal.stateLength;","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.normal.byteLength;\n\n See Also\n --------\n base.random.normal, random.strided.normal","random.array.pareto1":"\nrandom.array.pareto1( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n\nrandom.array.pareto1.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.pareto1.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.pareto1.PRNG;\n\n\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.pareto1.seed;\n\n\nrandom.array.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.pareto1.seedLength;\n\n\nrandom.array.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.pareto1.state\n \n\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n\nrandom.array.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.pareto1.stateLength;\n\n\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.pareto1.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.pareto1.PRNG;","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.pareto1.seed;","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.pareto1.seedLength;","random.array.pareto1.state":"\nrandom.array.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.pareto1.state\n \n\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n ","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.pareto1.stateLength;","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1","random.array.poisson":"\nrandom.array.poisson( len, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from a Poisson\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n lambda: number\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n\nrandom.array.poisson.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n Parameters\n ----------\n lambda: number\n Mean parameter.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.poisson.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.poisson.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.poisson.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.poisson.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.poisson.PRNG;\n\n\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.poisson.seed;\n\n\nrandom.array.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.poisson.seedLength;\n\n\nrandom.array.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.poisson.state\n \n\n > out = random.array.poisson( 3, 2.0 )\n \n > out = random.array.poisson( 3, 2.0 )\n \n\n // Set the state:\n > random.array.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.array.poisson( 3, 2.0 )\n \n\n\nrandom.array.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.poisson.stateLength;\n\n\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.strided.poisson\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n Parameters\n ----------\n lambda: number\n Mean parameter.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.poisson.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.poisson.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.poisson.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.poisson.PRNG;","random.array.poisson.seed":"\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.poisson.seed;","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.poisson.seedLength;","random.array.poisson.state":"\nrandom.array.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.poisson.state\n \n\n > out = random.array.poisson( 3, 2.0 )\n \n > out = random.array.poisson( 3, 2.0 )\n \n\n // Set the state:\n > random.array.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.array.poisson( 3, 2.0 )\n ","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.poisson.stateLength;","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.strided.poisson","random.array.randu":"\nrandom.array.randu( len[, options] )\n Returns an array containing uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n\nrandom.array.randu.factory( [options] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.randu.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.randu.PRNG;\n\n\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.randu.seed;\n\n\nrandom.array.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.randu.seedLength;\n\n\nrandom.array.randu.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.randu.state;\n\n > out = random.array.randu( 3 )\n \n > out = random.array.randu( 3 )\n \n\n // Set the state:\n > random.array.randu.state = state;\n\n // Regenerate a previous array:\n > out = random.array.randu( 3 )\n \n\n\nrandom.array.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.randu.stateLength;\n\n\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.randu.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.randu, random.strided.randu\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.randu.factory();\n > var out = fcn( 3 )\n ","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.randu.PRNG;","random.array.randu.seed":"\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.randu.seed;","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.randu.seedLength;","random.array.randu.state":"\nrandom.array.randu.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.randu.state;\n\n > out = random.array.randu( 3 )\n \n > out = random.array.randu( 3 )\n \n\n // Set the state:\n > random.array.randu.state = state;\n\n // Regenerate a previous array:\n > out = random.array.randu( 3 )\n ","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.randu.stateLength;","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.randu.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.randu, random.strided.randu","random.array.rayleigh":"\nrandom.array.rayleigh( len, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n sigma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n\nrandom.array.rayleigh.assign( sigma, out )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.rayleigh.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.rayleigh.factory( [sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.rayleigh.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.rayleigh.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.rayleigh.PRNG;\n\n\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.rayleigh.seed;\n\n\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.rayleigh.seedLength;\n\n\nrandom.array.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.rayleigh.state\n \n\n > out = random.array.rayleigh( 3, 2.0 )\n \n > out = random.array.rayleigh( 3, 2.0 )\n \n\n // Set the state:\n > random.array.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.array.rayleigh( 3, 2.0 )\n \n\n\nrandom.array.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.rayleigh.stateLength;\n\n\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.strided.rayleigh\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma, out )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.rayleigh.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.rayleigh.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.rayleigh.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.rayleigh.PRNG;","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.rayleigh.seed;","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.rayleigh.seedLength;","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.rayleigh.state\n \n\n > out = random.array.rayleigh( 3, 2.0 )\n \n > out = random.array.rayleigh( 3, 2.0 )\n \n\n // Set the state:\n > random.array.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.array.rayleigh( 3, 2.0 )\n ","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.rayleigh.stateLength;","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.strided.rayleigh","random.array.t":"\nrandom.array.t( len, v[, options] )\n Returns an array containing pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n\nrandom.array.t.assign( v, out )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.t.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.t.factory( [v, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.t.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.t.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.t.PRNG;\n\n\nrandom.array.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.t.seed;\n\n\nrandom.array.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.t.seedLength;\n\n\nrandom.array.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.t.state\n \n\n > out = random.array.t( 3, 2.0 )\n \n > out = random.array.t( 3, 2.0 )\n \n\n // Set the state:\n > random.array.t.state = state;\n\n // Regenerate a previous array:\n > out = random.array.t( 3, 2.0 )\n \n\n\nrandom.array.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.t.stateLength;\n\n\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.t.byteLength;\n\n See Also\n --------\n base.random.t, random.strided.t\n","random.array.t.assign":"\nrandom.array.t.assign( v, out )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.t.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.t.factory":"\nrandom.array.t.factory( [v, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.t.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.t.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.t.PRNG":"\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.t.PRNG;","random.array.t.seed":"\nrandom.array.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.t.seed;","random.array.t.seedLength":"\nrandom.array.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.t.seedLength;","random.array.t.state":"\nrandom.array.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.t.state\n \n\n > out = random.array.t( 3, 2.0 )\n \n > out = random.array.t( 3, 2.0 )\n \n\n // Set the state:\n > random.array.t.state = state;\n\n // Regenerate a previous array:\n > out = random.array.t( 3, 2.0 )\n ","random.array.t.stateLength":"\nrandom.array.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.t.stateLength;","random.array.t.byteLength":"\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.t.byteLength;\n\n See Also\n --------\n base.random.t, random.strided.t","random.array.triangular":"\nrandom.array.triangular( len, a, b, c[, options] )\n Returns an array containing pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.triangular.assign( a, b, c, out )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.triangular.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.triangular.PRNG;\n\n\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.triangular.seed;\n\n\nrandom.array.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.triangular.seedLength;\n\n\nrandom.array.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.triangular.state\n \n\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.triangular.stateLength;\n\n\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a, b, c, out )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.triangular.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n ","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.triangular.PRNG;","random.array.triangular.seed":"\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.triangular.seed;","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.triangular.seedLength;","random.array.triangular.state":"\nrandom.array.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.triangular.state\n \n\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n ","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.triangular.stateLength;","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular","random.array.uniform":"\nrandom.array.uniform( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n\nrandom.array.uniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.uniform.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.uniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.uniform.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.uniform.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.uniform.PRNG;\n\n\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.uniform.seed;\n\n\nrandom.array.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.uniform.seedLength;\n\n\nrandom.array.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.uniform.state\n \n\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n\nrandom.array.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.uniform.stateLength;\n\n\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.uniform.byteLength;\n\n See Also\n --------\n random.array.discreteUniform, base.random.uniform, random.strided.uniform\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.uniform.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.uniform.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.uniform.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.uniform.PRNG;","random.array.uniform.seed":"\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.uniform.seed;","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.uniform.seedLength;","random.array.uniform.state":"\nrandom.array.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.uniform.state\n \n\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.uniform( 3, 2.0, 5.0 )\n ","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.uniform.stateLength;","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.uniform.byteLength;\n\n See Also\n --------\n random.array.discreteUniform, base.random.uniform, random.strided.uniform","random.array.weibull":"\nrandom.array.weibull( len, k, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from a Weibull\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n\nrandom.array.weibull.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.weibull.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.weibull.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n lambda: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.weibull.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.weibull.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.weibull.PRNG;\n\n\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.weibull.seed;\n\n\nrandom.array.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.weibull.seedLength;\n\n\nrandom.array.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.weibull.state\n \n\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n\nrandom.array.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.weibull.stateLength;\n\n\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull, random.strided.weibull\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.weibull.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n lambda: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.weibull.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.weibull.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.weibull.PRNG;","random.array.weibull.seed":"\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.weibull.seed;","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.weibull.seedLength;","random.array.weibull.state":"\nrandom.array.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.weibull.state\n \n\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.array.weibull( 3, 2.0, 5.0 )\n ","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.weibull.stateLength;","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull, random.strided.weibull","random.iterators.arcsine":"\nrandom.iterators.arcsine( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.arcsine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.arcsine\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.bernoulli( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.bernoulli\n","random.iterators.beta":"\nrandom.iterators.beta( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.beta( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.beta\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.betaprime( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.betaprime\n","random.iterators.binomial":"\nrandom.iterators.binomial( n, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.binomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.binomial\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.boxMuller();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.boxMuller\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cauchy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cauchy\n","random.iterators.chi":"\nrandom.iterators.chi( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chi( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chi\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chisquare( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chisquare\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cosine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cosine\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned iterator, one must\n seed the provided `prng` (assuming the provided `prng` is seedable). The\n provided PRNG must have `MIN` and `MAX` properties specifying the\n minimum and maximum possible pseudorandom integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.discreteUniform( 0, 3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.discreteUniform\n","random.iterators.erlang":"\nrandom.iterators.erlang( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.erlang( 1, 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.erlang\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.exponential( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.exponential\n","random.iterators.f":"\nrandom.iterators.f( d1, d2[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.f( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.f\n","random.iterators.frechet":"\nrandom.iterators.frechet( α, s, m[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `s <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.frechet\n","random.iterators.gamma":"\nrandom.iterators.gamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gamma\n","random.iterators.geometric":"\nrandom.iterators.geometric( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.geometric( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.geometric\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gumbel( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gumbel\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n throws an error.\n\n If `n > N` or `K > N`, the function throws an error.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.hypergeometric( 20, 10, 7 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.hypergeometric\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.improvedZiggurat();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.improvedZiggurat\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.invgamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.invgamma\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `a <= 0` or `b <= 0`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.kumaraswamy\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.laplace( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.laplace\n","random.iterators.levy":"\nrandom.iterators.levy( μ, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.levy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.levy\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.logistic( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.logistic\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.lognormal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.lognormal\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstd();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstd, random.iterators.minstdShuffle, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstdShuffle();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstd, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Uint32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Uint32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.mt19937();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.mt19937, random.iterators.minstd, random.iterators.minstdShuffle, random.iterators.randi, random.iterators.randu\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.negativeBinomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.negativeBinomial\n","random.iterators.normal":"\nrandom.iterators.normal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.normal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.normal\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.pareto1( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.pareto1\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.poisson( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.poisson\n","random.iterators.randi":"\nrandom.iterators.randi( [options] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randi();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randi, random.iterators.randu\n","random.iterators.randn":"\nrandom.iterators.randn( [options] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: `'improved-ziggurat'`.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randn();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randn\n","random.iterators.randu":"\nrandom.iterators.randu( [options] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randu();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randu, random.iterators.randi\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.rayleigh( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.rayleigh\n","random.iterators.t":"\nrandom.iterators.t( v[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.t( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.t\n","random.iterators.triangular":"\nrandom.iterators.triangular( a, b, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.triangular\n","random.iterators.uniform":"\nrandom.iterators.uniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.uniform( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.uniform\n","random.iterators.weibull":"\nrandom.iterators.weibull( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `k <= 0` or `λ <= 0`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.weibull( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.weibull\n","random.streams.arcsine":"\nrandom.streams.arcsine( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine","random.streams.bernoulli":"\nrandom.streams.bernoulli( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli","random.streams.beta":"\nrandom.streams.beta( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta","random.streams.betaprime":"\nrandom.streams.betaprime( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime","random.streams.binomial":"\nrandom.streams.binomial( n, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial( 20, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn","random.streams.cauchy":"\nrandom.streams.cauchy( x0, γ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy","random.streams.chi":"\nrandom.streams.chi( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi","random.streams.chisquare":"\nrandom.streams.chisquare( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare","random.streams.cosine":"\nrandom.streams.cosine( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform( 2, 5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform","random.streams.erlang":"\nrandom.streams.erlang( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang( 2, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang","random.streams.exponential":"\nrandom.streams.exponential( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential","random.streams.f":"\nrandom.streams.f( d1, d2[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f","random.streams.frechet":"\nrandom.streams.frechet( α, s, m[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Fréchet distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.frechet.factory( [α, s, m,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.frechet.factory( opts );\n\n\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.frechet, random.iterators.frechet\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α, s, m,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.frechet.factory( opts );","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.frechet, random.iterators.frechet","random.streams.gamma":"\nrandom.streams.gamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma","random.streams.geometric":"\nrandom.streams.geometric( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric","random.streams.gumbel":"\nrandom.streams.gumbel( μ, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N, K, n[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric( 5, 3, 2, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.hypergeometric.factory( opts );\n\n\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.hypergeometric, random.iterators.hypergeometric\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.hypergeometric.factory( opts );","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.hypergeometric, random.iterators.hypergeometric","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn","random.streams.invgamma":"\nrandom.streams.invgamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy","random.streams.laplace":"\nrandom.streams.laplace( μ, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace","random.streams.levy":"\nrandom.streams.levy( μ, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy","random.streams.logistic":"\nrandom.streams.logistic( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic","random.streams.lognormal":"\nrandom.streams.lognormal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal","random.streams.minstd":"\nrandom.streams.minstd( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.mt19937":"\nrandom.streams.mt19937( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n Twister pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial","random.streams.normal":"\nrandom.streams.normal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal","random.streams.pareto1":"\nrandom.streams.pareto1( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1","random.streams.poisson":"\nrandom.streams.poisson( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson","random.streams.randi":"\nrandom.streams.randi( [options] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu","random.streams.randn":"\nrandom.streams.randn( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat","random.streams.randu":"\nrandom.streams.randu( [options] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh","random.streams.t":"\nrandom.streams.t( v[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t","random.streams.triangular":"\nrandom.streams.triangular( a, b, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.triangular.factory( opts );\n\n\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.triangular, random.iterators.triangular\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.triangular.factory( opts );","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.triangular, random.iterators.triangular","random.streams.uniform":"\nrandom.streams.uniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform","random.streams.weibull":"\nrandom.streams.weibull( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull","random.strided.arcsine":"\nrandom.strided.arcsine( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.arcsine, random.array.arcsine\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.arcsine, random.array.arcsine","random.strided.bernoulli":"\nrandom.strided.bernoulli( N, p, sp, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.bernoulli.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.bernoulli.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.bernoulli.PRNG;\n\n\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.bernoulli.seed;\n\n\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.bernoulli.seedLength;\n\n\nrandom.strided.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.bernoulli.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.bernoulli.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.bernoulli.stateLength;\n\n\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.array.bernoulli\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n [...]","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.bernoulli.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.5 ], 0, out, 1 )\n [...]","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.bernoulli.PRNG;","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.bernoulli.seed;","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.bernoulli.seedLength;","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.bernoulli.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.bernoulli.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.bernoulli.stateLength;","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.array.bernoulli","random.strided.beta":"\nrandom.strided.beta( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.beta, random.array.beta\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.beta, random.array.beta","random.strided.betaprime":"\nrandom.strided.betaprime( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime","random.strided.chi":"\nrandom.strided.chi( N, k, sk, out, so )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.chi.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chi.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chi.PRNG;\n\n\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chi.seed;\n\n\nrandom.strided.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chi.seedLength;\n\n\nrandom.strided.chi.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chi.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chi.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chi.stateLength;\n\n\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.array.chi\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chi.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chi.PRNG;","random.strided.chi.seed":"\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chi.seed;","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chi.seedLength;","random.strided.chi.state":"\nrandom.strided.chi.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chi.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chi.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chi.stateLength;","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.array.chi","random.strided.chisquare":"\nrandom.strided.chisquare( N, k, sk, out, so )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.chisquare.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chisquare.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chisquare.PRNG;\n\n\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chisquare.seed;\n\n\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chisquare.seedLength;\n\n\nrandom.strided.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chisquare.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chisquare.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chisquare.stateLength;\n\n\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.array.chisquare\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chisquare.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chisquare.PRNG;","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chisquare.seed;","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chisquare.seedLength;","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chisquare.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chisquare.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chisquare.stateLength;","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.array.chisquare","random.strided.cosine":"\nrandom.strided.cosine( N, mu, sm, s, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n [...]\n\n\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n os: integer\n Starting index for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.cosine, random.array.cosine\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n os: integer\n Starting index for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.cosine, random.array.cosine","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform","random.strided.exponential":"\nrandom.strided.exponential( N, lambda, sl, out, so )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.exponential.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.exponential.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.exponential.PRNG;\n\n\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.exponential.seed;\n\n\nrandom.strided.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.exponential.seedLength;\n\n\nrandom.strided.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.exponential.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.exponential.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.exponential.stateLength;\n\n\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.array.exponential\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.exponential.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.exponential.PRNG;","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.exponential.seed;","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.exponential.seedLength;","random.strided.exponential.state":"\nrandom.strided.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.exponential.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.exponential.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.exponential.stateLength;","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.array.exponential","random.strided.gamma":"\nrandom.strided.gamma( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.gamma, random.array.gamma\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.gamma, random.array.gamma","random.strided.geometric":"\nrandom.strided.geometric( N, p, sp, out, so )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.geometric.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.geometric.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.geometric.PRNG;\n\n\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.geometric.seed;\n\n\nrandom.strided.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.geometric.seedLength;\n\n\nrandom.strided.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.geometric.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.geometric.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.geometric.stateLength;\n\n\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.array.geometric\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n [...]","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.geometric.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.01 ], 0, out, 1 )\n [...]","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.geometric.PRNG;","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.geometric.seed;","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.geometric.seedLength;","random.strided.geometric.state":"\nrandom.strided.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.geometric.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.geometric.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.geometric.stateLength;","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.array.geometric","random.strided.invgamma":"\nrandom.strided.invgamma( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.invgamma, random.array.invgamma\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.invgamma, random.array.invgamma","random.strided.lognormal":"\nrandom.strided.lognormal( N, mu, sm, sigma, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n [...]\n\n\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.lognormal, random.array.lognormal\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.lognormal, random.array.lognormal","random.strided.minstd":"\nrandom.strided.minstd( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.minstd.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized( out.length, out, 1 )\n [...]","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n [...]","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu","random.strided.mt19937":"\nrandom.strided.mt19937( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937( out.length, out, 1 )\n [...]\n\n\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.mt19937, random.array.mt19937, random.strided.randu\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized( out.length, out, 1 )\n [...]","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.mt19937, random.array.mt19937, random.strided.randu","random.strided.normal":"\nrandom.strided.normal( N, mu, sm, sigma, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n [...]\n\n\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.normal, random.array.normal\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.normal, random.array.normal","random.strided.poisson":"\nrandom.strided.poisson( N, lambda, sl, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.poisson.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.poisson.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.poisson.PRNG;\n\n\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.poisson.seed;\n\n\nrandom.strided.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.poisson.seedLength;\n\n\nrandom.strided.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.poisson.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.poisson.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.poisson.stateLength;\n\n\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.array.poisson\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.poisson.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.poisson.PRNG;","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.poisson.seed;","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.poisson.seedLength;","random.strided.poisson.state":"\nrandom.strided.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.poisson.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.poisson.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.poisson.stateLength;","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.array.poisson","random.strided.randu":"\nrandom.strided.randu( N, out, so[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu( out.length, out, 1 )\n [...]\n\n\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.randu, random.array.randu, random.strided.uniform\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.randu, random.array.randu, random.strided.uniform","random.strided.rayleigh":"\nrandom.strided.rayleigh( N, sigma, ss, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.rayleigh.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.rayleigh.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.rayleigh.PRNG;\n\n\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.rayleigh.seed;\n\n\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.rayleigh.seedLength;\n\n\nrandom.strided.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.rayleigh.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.rayleigh.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.rayleigh.stateLength;\n\n\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.array.rayleigh\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.rayleigh.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.rayleigh.PRNG;","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.rayleigh.seed;","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.rayleigh.seedLength;","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.rayleigh.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.rayleigh.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.rayleigh.stateLength;","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.array.rayleigh","random.strided.t":"\nrandom.strided.t( N, v, sv, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n ov: integer\n Starting index for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.t.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.t.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.t.PRNG;\n\n\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.t.seed;\n\n\nrandom.strided.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.t.seedLength;\n\n\nrandom.strided.t.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.t.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.t.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.t.stateLength;\n\n\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.t.byteLength;\n\n See Also\n --------\n base.random.t, random.array.t\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n ov: integer\n Starting index for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.t.factory":"\nrandom.strided.t.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.t.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.t.PRNG;","random.strided.t.seed":"\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.t.seed;","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.t.seedLength;","random.strided.t.state":"\nrandom.strided.t.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.t.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.t.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.t.stateLength;","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.t.byteLength;\n\n See Also\n --------\n base.random.t, random.array.t","random.strided.uniform":"\nrandom.strided.uniform( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.uniform, random.array.uniform, random.strided.discreteUniform\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.uniform, random.array.uniform, random.strided.discreteUniform","random.strided.weibull":"\nrandom.strided.weibull( N, k, sk, lambda, sl, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.weibull, random.array.weibull\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.weibull, random.array.weibull","ranks":"\nranks( arr[, options] )\n Computes the sample ranks for the values of an array-like object.\n\n When all elements of the `array` are different, the ranks are uniquely\n determined. When there are equal elements (called *ties*), the `method`\n option determines how they are handled. The default, `'average'`, replaces\n the ranks of the ties by their mean. Other possible options are `'min'` and\n `'max'`, which replace the ranks of the ties by their minimum and maximum,\n respectively. `'dense'` works like `'min'`, with the difference that the\n next highest element after a tie is assigned the next smallest integer.\n Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n the position they appear in.\n\n The `missing` option is used to specify how to handle missing data.\n By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n that missing values are placed last, `'first'` that the are assigned the\n lowest ranks and `'remove'` means that they are removed from the array\n before the ranks are calculated.\n\n Parameters\n ----------\n arr: Array\n Input values.\n\n options: Object (optional)\n Function options.\n\n options.method (optional)\n Method name determining how ties are treated (`average`, `min`, `max`,\n `dense`, or `ordinal`). Default: `'average'`.\n\n options.missing (optional)\n Determines where missing values go (`first`, `last`, or `remove`).\n Default: `'last'`.\n\n options.encoding (optional)\n Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n Returns\n -------\n out: Array\n Array containing the computed ranks for the elements of the input array.\n\n Examples\n --------\n > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n > var out = ranks( arr )\n [ 2, 3, 5, 1, 4 ]\n\n // Ties are averaged:\n > arr = [ 2, 2, 1, 4, 3 ];\n > out = ranks( arr )\n [ 2.5, 2.5, 1, 5, 4 ]\n\n // Missing values are placed last:\n > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n > out = ranks( arr )\n [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n","readDir":"\nreadDir( path, clbk )\n Asynchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n clbk: Function\n Callback to invoke after reading directory contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile\n","readDir.sync":"\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile","readFile":"\nreadFile( file[, options], clbk )\n Asynchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, open, readDir, readJSON, writeFile\n","readFile.sync":"\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, open, readDir, readJSON, writeFile","readFileList":"\nreadFileList( filepaths[, options], clbk )\n Asynchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Each file is represented by an object with the following fields:\n\n - file: file path.\n - data: file contents as either a Buffer or string.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );\n\n","readFileList.sync":"\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );","readJSON":"\nreadJSON( file[, options], clbk )\n Asynchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile\n","readJSON.sync":"\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile","readWASM":"\nreadWASM( file[, options], clbk )\n Asynchronously reads a file as WebAssembly.\n\n The function returns file contents as a Uint8Array.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile\n","readWASM.sync":"\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile","real":"\nreal( z )\n Returns the real component of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var re = real( z )\n 5.0\n\n See Also\n --------\n imag, reim\n","realarray":"\nrealarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = realarray()\n \n > arr = realarray( 'float32' )\n \n\n\nrealarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = realarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = realarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\nrealarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = realarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\nrealarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = realarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\nrealarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = realarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","realarrayCtors":"\nrealarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = realarrayCtors( 'float64' )\n \n > ctor = realarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors, complexarrayCtors\n","realarrayDataTypes":"\nrealarrayDataTypes()\n Returns a list of typed array real-valued data types.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = realarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, complexarrayDataTypes\n","realf":"\nrealf( z )\n Returns the real component of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var re = realf( z )\n 5.0\n\n See Also\n --------\n imagf, real, reimf\n","realmax":"\nrealmax( dtype )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum finite value.\n\n Examples\n --------\n > var m = realmax( 'float16' )\n 65504.0\n > m = realmax( 'float32' )\n 3.4028234663852886e+38\n\n See Also\n --------\n realmin, typemax\n","realmin":"\nrealmin( dtype )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Smallest finite normal value.\n\n Examples\n --------\n > var m = realmin( 'float16' )\n 0.00006103515625\n > m = realmin( 'float32' )\n 1.1754943508222875e-38\n\n See Also\n --------\n realmax, typemin\n","reBasename":"\nreBasename( [platform] )\n Returns a regular expression to capture the last part of a path.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reBasename()\n \n > var RE_POSIX = reBasename( 'posix' );\n > var RE_WIN32 = reBasename( 'win32' );\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var RE = reBasename.REGEXP\n \n\n\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasenamePosix, reBasenameWindows\n","reBasename.REGEXP":"\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var RE = reBasename.REGEXP\n ","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasenamePosix, reBasenameWindows","reBasenamePosix":"\nreBasenamePosix()\n Returns a regular expression to capture the last part of a POSIX path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_BASENAME_POSIX = reBasenamePosix();\n > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n ''\n\n\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasename, reBasenameWindows\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasename, reBasenameWindows","reBasenameWindows":"\nreBasenameWindows()\n Returns a regular expression to capture the last part of a Windows path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_BASENAME_WINDOWS = reBasenameWindows();\n > var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n\n See Also\n --------\n reBasename, reBasenamePosix\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n\n See Also\n --------\n reBasename, reBasenamePosix","reColorHexadecimal":"\nreColorHexadecimal( [mode] )\n Returns a regular expression to match a hexadecimal color.\n\n Parameters\n ----------\n mode: string (optional)\n Color format (`full`, `shorthand`, or `either`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reColorHexadecimal();\n > var bool = RE.test( 'ffffff' )\n true\n > bool = RE.test( '000' )\n false\n > bool = RE.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP.test( '000' )\n false\n > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n false\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n false\n\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP.test( '000' )\n false\n > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n false","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n false\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n false","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n false","reDecimalNumber":"\nreDecimalNumber( [options] )\n Returns a regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to create a capture group for the match.\n Default: false.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDecimalNumber();\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true\n > bool = RE.test( '0.0' )\n true\n > bool = RE.test( '.0' )\n true\n > bool = RE.test( '0' )\n false\n > bool = RE.test( 'beep' )\n false\n\n // Create a RegExp to capture all decimal numbers:\n > var re = reDecimalNumber({ 'flags': 'g' });\n > var str = '1.234 5.6, 7.8';\n > var out = str.match( re )\n [ '1.234', '5.6', '7.8' ]\n\n\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP;\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true\n\n\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP_CAPTURE;\n > var str = '1.02';\n > var out = replace( str, RE, '$1 x $1' )\n '1.02 x 1.02'\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP;\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP_CAPTURE;\n > var str = '1.02';\n > var out = replace( str, RE, '$1 x $1' )\n '1.02 x 1.02'","reDirname":"\nreDirname( [platform] )\n Returns a regular expression to capture a path dirname.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirname()\n \n > var RE_POSIX = reDirname( 'posix' );\n > var dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > var RE_WIN32 = reDirname( 'win32' );\n > dir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n\n Examples\n --------\n > var RE = reDirname.REGEXP\n \n\n\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n reDirnamePosix, reDirnameWindows, dirname\n","reDirname.REGEXP":"\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n\n Examples\n --------\n > var RE = reDirname.REGEXP\n ","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n reDirnamePosix, reDirnameWindows, dirname","reDirnamePosix":"\nreDirnamePosix()\n Returns a regular expression to capture a POSIX path dirname.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirnamePosix();\n > var dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > dir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n './foo/bar'\n > dir = RE.exec( 'foo/file.pdf' )[ 1 ]\n 'foo'\n > dir = RE.exec( '/foo/bar/file' )[ 1 ]\n '/foo/bar'\n > dir = RE.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE.exec( '.' )[ 1 ]\n '.'\n > dir = RE.exec( './' )[ 1 ]\n '.'\n > dir = RE.exec( '' )[ 1 ]\n ''\n\n\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n See Also\n --------\n reDirname, reDirnameWindows, dirname\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n See Also\n --------\n reDirname, reDirnameWindows, dirname","reDirnameWindows":"\nreDirnameWindows()\n Returns a regular expression to capture a Windows path dirname.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirnameWindows();\n > var dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n > dir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n 'C:\\foo\\bar'\n > dir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'foo'\n > dir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n '\\foo\\bar'\n > dir = RE.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE.exec( '' )[ 1 ]\n ''\n\n\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n\n See Also\n --------\n reDirname, reDirnamePosix, dirname\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n\n See Also\n --------\n reDirname, reDirnamePosix, dirname","reduce":"\nreduce( arr, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a reduction over the entire\n input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input array.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var out = reduce( arr, 0.0, f )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = reduce( arr, 0.0, f )\n 21.0\n\n See Also\n --------\n forEach, map, reduceAsync, reduceRight\n","reduce2d":"\nreduce2d( arr, initial, reducer[, thisArg] )\n Reduces the number of dimensions by one of a two-dimensional nested array by\n applying a function against an accumulator and each element along the\n innermost dimension and returning the accumulation results as a one-\n dimensional array.\n\n The applied function is provided the following arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array of arrays.\n\n initial: ArrayLikeObject\n Initial values. Must have a length equal to the size of the outermost\n input array dimension.\n\n reducer: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array\n Accumulation results.\n\n Examples\n --------\n > var f = naryFunction( base.add, 2 );\n > var arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\n > var out = reduce2d( arr, [ 0, 0 ], f )\n [ 6, 15 ]\n\n See Also\n --------\n map2d, reduce\n","reduceAsync":"\nreduceAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - accumulator: accumulated value.\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - accumulator\n - value\n - next\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - accumulator\n - value\n - index\n - next\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - accumulator: accumulated value.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync\n","reduceAsync.factory":"\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync","reduceRight":"\nreduceRight( arr, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in an array while\n iterating from right to left and returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a reduction over the entire\n input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input array.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var out = reduceRight( arr, 0.0, f )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = reduceRight( arr, 0.0, f )\n 21.0\n\n See Also\n --------\n forEachRight, mapRight, reduce, reduceRightAsync\n","reduceRightAsync":"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - accumulator: accumulated value.\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - accumulator\n - value\n - next\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - accumulator\n - value\n - index\n - next\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - accumulator: accumulated value.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight","reDurationString":"\nreDurationString()\n Returns a regular expression to match a duration string.\n\n A duration string is a string containing a sequence of time units. A time\n unit is a nonnegative integer followed by a unit identifier. The following\n unit identifiers are supported:\n\n - d: days.\n - h: hours.\n - m: minutes.\n - s: seconds.\n - ms: milliseconds.\n\n For example, the string `1m3s10ms` is a duration string containing three\n time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n The string `60m` is a duration string containing a single time unit: `60m`\n (60 minutes). Time units must be supplied in descending order of magnitude\n (i.e., days, hours, minutes, seconds, milliseconds).\n\n Duration strings are case insensitive. For example, the string `1M3S10MS` is\n equivalent to `1m3s10ms`.\n\n The regular expression captures the following groups:\n\n 1. The days component.\n 2. The hours component.\n 3. The minutes component.\n 4. The seconds component.\n 5. The milliseconds component.\n\n Returns\n -------\n re: RegExp: Regular expression\n Regular expression to match a duration string.\n\n Examples\n --------\n > var RE = reDurationString();\n > var parts = RE.exec( '3d2ms' )\n [...]\n > parts = RE.exec( '4h3m20s' )\n [...]\n\n\nreDurationString.REGEXP\n Regular expression to match a duration string.\n\n Examples\n --------\n > var bool = reDurationString.REGEXP.test( '3d2ms' )\n true\n > bool = reDurationString.REGEXP.test( 'foo' )\n false\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n Regular expression to match a duration string.\n\n Examples\n --------\n > var bool = reDurationString.REGEXP.test( '3d2ms' )\n true\n > bool = reDurationString.REGEXP.test( 'foo' )\n false","reEOL":"\nreEOL( [options] )\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to create a capture group for the match.\n Default: false.\n\n Returns\n -------\n regexp: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_EOL = reEOL();\n > var bool = RE_EOL.test( '\\n' )\n true\n > bool = RE_EOL.test( '\\r\\n' )\n true\n > bool = RE_EOL.test( '\\\\r\\\\n' )\n false\n\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = reEOL.REGEXP.test( 'abc' )\n false\n\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n [ '\\n', '\\n' ]\n\n","reEOL.REGEXP":"\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = reEOL.REGEXP.test( 'abc' )\n false","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n [ '\\n', '\\n' ]","reExtendedLengthPath":"\nreExtendedLengthPath()\n Returns a regular expression to test if a string is an extended-length path.\n\n Extended-length paths are Windows paths which begin with `\\\\?\\`.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtendedLengthPath();\n > var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\n > var bool = RE.test( path )\n true\n > path = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\n > bool = RE.test( path )\n true\n > path = 'C:\\\\foo\\\\bar';\n > bool = RE.test( path )\n false\n > path = '/c/foo/bar';\n > bool = RE.test( path )\n false\n > path = '/foo/bar';\n > bool = RE.test( path )\n false\n\n\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n\n Examples\n --------\n > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n false\n\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n\n Examples\n --------\n > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n false","reExtname":"\nreExtname( [platform] )\n Returns a regular expression to capture a filename extension.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtname()\n \n > var RE_POSIX = reExtname( 'posix' );\n > var ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > var RE_WIN32 = reExtname( 'win32' );\n > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n\n Examples\n --------\n > var RE = reExtname.REGEXP\n \n\n\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtnamePosix, reExtnameWindows, extname\n","reExtname.REGEXP":"\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n\n Examples\n --------\n > var RE = reExtname.REGEXP\n ","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtnamePosix, reExtnameWindows, extname","reExtnamePosix":"\nreExtnamePosix\n Returns a regular expression to capture a POSIX filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtnamePosix();\n > var ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n ''\n > ext = RE.exec( 'foo/file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE.exec( '/foo/bar/file' )[ 1 ]\n ''\n > ext = RE.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( '.' )[ 1 ]\n ''\n > ext = RE.exec( './' )[ 1 ]\n ''\n > ext = RE.exec( '' )[ 1 ]\n ''\n\n\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnameWindows, extname\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnameWindows, extname","reExtnameWindows":"\nreExtnameWindows\n Returns a regular expression to capture a Windows filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtnameWindows();\n > var ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n ''\n > ext = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n ''\n > ext = RE.exec( 'beep\\\\boop.' )[ 1 ]\n '.'\n > ext = RE.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( '' )[ 1 ]\n ''\n\n\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnamePosix, extname\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnamePosix, extname","reFilename":"\nreFilename( [platform] )\n Regular expression to split a filename.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilename()\n \n > var RE_POSIX = reFilename( 'posix' );\n > var parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\n \n > var RE_WIN32 = reFilename( 'win32' );\n > parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n \n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreFilename.REGEXP\n Regular expression to split a filename.\n\n Examples\n --------\n > var RE = reFilename.REGEXP\n \n\n\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilenamePosix, reFilenameWindows\n","reFilename.REGEXP":"\nreFilename.REGEXP\n Regular expression to split a filename.\n\n Examples\n --------\n > var RE = reFilename.REGEXP\n ","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilenamePosix, reFilenameWindows","reFilenamePosix":"\nreFilenamePosix()\n Returns a regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilenamePosix();\n > var parts = RE.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n > parts = RE.exec( './foo/bar/.gitignore' ).slice()\n [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n > parts = RE.exec( 'foo/file.pdf' ).slice()\n [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n > parts = RE.exec( '/foo/bar/file' ).slice()\n [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n > parts = RE.exec( 'index.js' ).slice()\n [ 'index.js', '', '', 'index.js', '.js' ]\n > parts = RE.exec( '.' ).slice()\n [ '.', '', '', '.', '' ]\n > parts = RE.exec( './' ).slice()\n [ './', '', ..., '.', '' ]\n > parts = RE.exec( '' ).slice()\n [ '', '', '', '', '' ]\n\n\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n\n Examples\n --------\n > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenameWindows\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n\n Examples\n --------\n > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenameWindows","reFilenameWindows":"\nreFilenameWindows()\n Returns a regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilenameWindows();\n > var parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n > parts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\n [ '\\\\foo\\\\bar\\\\.gitignore', '', '\\\\', 'foo\\\\bar\\\\', '.gitignore', '' ]\n > parts = RE.exec( 'foo\\\\file.pdf' ).slice()\n [ 'foo\\\\file.pdf', '', '', 'foo\\\\', 'file.pdf', '.pdf' ]\n > parts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\n [ '\\\\foo\\\\bar\\\\file', '', '\\\\', 'foo\\\\bar\\\\', 'file', '' ]\n > parts = RE.exec( 'index.js' ).slice()\n [ 'index.js', '', '', '', 'index.js', '.js' ]\n > parts = RE.exec( '.' ).slice()\n [ '.', '', '', '', '.', '' ]\n > parts = RE.exec( './' ).slice()\n [ './', '', ..., '.', '' ]\n > parts = RE.exec( '' ).slice()\n [ '', '', '', '', '', '' ]\n\n\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n\n Examples\n --------\n > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenamePosix","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n\n Examples\n --------\n > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenamePosix","reFromString":"\nreFromString( str )\n Parses a regular expression string and returns a new regular expression.\n\n Provided strings should be properly escaped.\n\n If unable to parse a string as a regular expression, the function returns\n `null`.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: RegExp|null\n Regular expression or null.\n\n Examples\n --------\n > var re = reFromString( '/beep/' )\n /beep/\n > re = reFromString( '/beep' )\n null\n\n","reFunctionName":"\nreFunctionName()\n Return a regular expression to capture a function name.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_FUNCTION_NAME = reFunctionName();\n > function beep() { return 'boop'; };\n > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n 'beep'\n > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n ''\n\n\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n\n Examples\n --------\n > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n 'sqrt'\n\n See Also\n --------\n functionName\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n\n Examples\n --------\n > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n 'sqrt'\n\n See Also\n --------\n functionName","regexp2json":"\nregexp2json( re )\n Returns a JSON representation of a regular expression.\n\n Parameters\n ----------\n re: RegExp\n Regular expression to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n \n out.type: string\n Value type. The assigned value is always 'RegExp'.\n \n out.pattern: string\n Regular expression pattern.\n \n out.flags: string\n Regular expression flags.\n\n Examples\n --------\n > var json = regexp2json( /ab+c/ )\n {...}\n\n See Also\n --------\n reviveRegExp \n","reim":"\nreim( z )\n Returns the real and imaginary components of a double-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Float64Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var out = reim( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imag, real\n","reimf":"\nreimf( z )\n Returns the real and imaginary components of a single-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Float32Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var out = reimf( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imagf, realf, reim\n","rejectArguments":"\nrejectArguments( fcn, predicate[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n\n Only those arguments in which the predicate function returns a falsy value\n are applied to a provided function.\n\n The predicate function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > function predicate( v ) { return ( v === 2 ); };\n > var bar = rejectArguments( foo, predicate );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n filterArguments, maskArguments\n","removeFirst":"\nremoveFirst( str[, n][, options] )\n Removes the first character(s) of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to remove. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeFirst( 'beep' )\n 'eep'\n > out = removeFirst( 'Boop' )\n 'oop'\n > out = removeFirst( 'foo bar', 4 )\n 'bar'\n\n See Also\n --------\n removeLast\n","removeLast":"\nremoveLast( str[, n][, options] )\n Removes the last character(s) of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to remove. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to remove. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeLast( 'beep' )\n 'bee'\n > out = removeLast( 'Boop' )\n 'Boo'\n > out = removeLast( 'foo bar', 4 )\n 'foo'\n\n See Also\n --------\n removeFirst\n","removePunctuation":"\nremovePunctuation( str )\n Removes punctuation characters from a `string`.\n\n The function removes the following characters:\n\n - Apostrophe: `\n - Braces : { }\n - Brackets: [ ]\n - Colon: :\n - Comma: ,\n - Exclamation Mark: !\n - Fraction Slash: /\n - Guillemets: < >\n - Parentheses: ( )\n - Period: .\n - Semicolon: ;\n - Tilde: ~\n - Vertical Bar: |\n - Question Mark: ?\n - Quotation Marks: ' \"\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with punctuation characters removed.\n\n Examples\n --------\n > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n > var out = removePunctuation( str )\n 'Sun Tzu said A leader leads by example not by force'\n\n > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\n > out = removePunctuation( str )\n 'This function removes these characters '\n\n","removeUTF8BOM":"\nremoveUTF8BOM( str )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with BOM removed.\n\n Examples\n --------\n > var out = removeUTF8BOM( '\\ufeffbeep' )\n 'beep'\n\n","removeWords":"\nremoveWords( str, words[, ignoreCase] )\n Removes all occurrences of the given words from a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n words: Array\n Array of words to be removed.\n\n ignoreCase: boolean (optional)\n Boolean indicating whether to perform a case-insensitive operation.\n Default: `false`.\n\n Returns\n -------\n out: string\n String with words removed.\n\n Examples\n --------\n > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n 'beep Foo bar'\n\n // Case-insensitive:\n > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n 'beep bar'\n\n","rename":"\nrename( oldPath, newPath, clbk )\n Asynchronously renames a file.\n\n The old path can specify a directory. In this case, the new path must either\n not exist, or it must specify an empty directory.\n\n The old pathname should not name an ancestor directory of the new pathname.\n\n If the old path points to the pathname of a file that is not a directory,\n the new path should not point to the pathname of a directory.\n\n Write access permission is required for both the directory containing the\n old path and the directory containing the new path.\n\n If the link named by the new path exists, the new path is removed and the\n old path is renamed to the new path. The link named by the new path will\n remain visible to other threads throughout the renaming operation and refer\n to either the file referred to by the new path or to the file referred to by\n the old path before the operation began.\n\n If the old path and the new path resolve to either the same existing\n directory entry or to different directory entries for the same existing\n file, no action is taken, and no error is returned.\n\n If the old path points to a pathname of a symbolic link, the symbolic link\n is renamed. If the new path points to a pathname of a symbolic link, the\n symbolic link is removed.\n\n If a link named by the new path exists and the file's link count becomes 0\n when it is removed and no process has the file open, the space occupied by\n the file is freed and the file is no longer accessible. If one or more\n processes have the file open when the last link is removed, the link is\n removed before the function returns, but the removal of file contents is\n postponed until all references to the file are closed.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n clbk: Function\n Callback to invoke upon renaming a file.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink\n","rename.sync":"\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink","reNativeFunction":"\nreNativeFunction()\n Returns a regular expression to match a native function.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reNativeFunction();\n > var bool = RE.test( Date.toString() )\n true\n > bool = RE.test( (function noop() {}).toString() )\n false\n\n\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n true\n > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n reFunctionName, functionName\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n true\n > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n reFunctionName, functionName","reorderArguments":"\nreorderArguments( fcn, indices[, thisArg] )\n Returns a function that invokes a provided function with reordered\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reordered arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 3, 1, 2 ]\n\n See Also\n --------\n maskArguments, reverseArguments\n","repeat":"\nrepeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = repeat( 'a', 5 )\n 'aaaaa'\n > out = repeat( '', 100 )\n ''\n > out = repeat( 'beep', 0 )\n ''\n\n See Also\n --------\n pad\n","replace":"\nreplace( str, search, newval )\n Replaces search occurrences with a replacement string.\n\n When provided a string as the search value, the function replaces *all*\n occurrences. To remove only the first match, use a regular expression.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string|RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n // Standard usage:\n > var out = replace( 'beep', 'e', 'o' )\n 'boop'\n\n // Replacer function:\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > out = replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = replace( 'beep', /e/, 'o' )\n 'boep'\n\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n Replaces the substring before the first occurrence of a specified search\n string. \n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n \n replacement: string\n Replacement string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = replaceBefore( str, ' ', 'foo' )\n 'foo boop'\n > out = replaceBefore( str, 'o', 'foo' )\n 'foooop'\n\n","reRegExp":"\nreRegExp()\n Returns a regular expression to parse a regular expression string.\n\n Regular expression strings should be escaped.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reRegExp();\n > var bool = RE.test( '/^beep$/' )\n true\n > bool = RE.test( '/boop' )\n false\n\n // Escape regular expression strings:\n > bool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n false\n > bool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n true\n\n\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n\n Examples\n --------\n > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n true\n > bool = reRegExp.REGEXP.test( '/boop' )\n false\n\n See Also\n --------\n reFromString\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n\n Examples\n --------\n > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n true\n > bool = reRegExp.REGEXP.test( '/boop' )\n false\n\n See Also\n --------\n reFromString","rescape":"\nrescape( str )\n Escapes a regular expression string.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: string\n Escaped string.\n\n Examples\n --------\n > var str = rescape( '[A-Z]*' )\n '\\[A\\-Z\\]\\*'\n\n","reSemVer":"\nreSemVer()\n Returns a regular expression to match a semantic version string.\n\n Returns\n -------\n out: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_SEMVER = reSemVer()\n \n > var bool = RE_SEMVER.test( '1.0.0' )\n true\n > bool = RE_SEMVER.test( '1.0.0-alpha.1' )\n true\n > bool = RE_SEMVER.test( 'abc' )\n false\n > bool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n true\n\n\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n\n Examples\n --------\n > var bool = reSemVer.REGEXP.test( '1.0.0' )\n true\n > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n false\n\n\n See Also\n --------\n isSemVer","reSemVer.REGEXP":"\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n\n Examples\n --------\n > var bool = reSemVer.REGEXP.test( '1.0.0' )\n true\n > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n false\n\n\n See Also\n --------\n isSemVer","resolveParentPath":"\nresolveParentPath( path[, options], clbk )\n Asynchronously resolves a path by walking parent directories.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n See Also\n --------\n resolveParentPathBy\n","resolveParentPath.sync":"\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n See Also\n --------\n resolveParentPathBy","resolveParentPathBy":"\nresolveParentPathBy( path[, options], predicate, clbk )\n Asynchronously resolves a path according to a predicate function by walking\n parent directories.\n\n When invoked, the predicate function is provided two arguments:\n\n - path: a resolved path.\n - next: a callback to be invoked after processing a resolved path.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided predicate function calls the `next` callback with a truthy\n `error` argument, the function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n the resolved path as the second argument.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function predicate( path, next ) {\n ... setTimeout( onTimeout, path );\n ... function onTimeout() {\n ... console.log( path );\n ... next( null, false );\n ... }\n ... };\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPathBy( 'package.json', predicate, onPath );\n\n\nresolveParentPathBy.sync( path[, options], predicate )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n\n The predicate function is provided one argument:\n\n - path: a resolved path.\n\n The function immediately returns upon encountering a truthy return value.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > function predicate() { return false; };\n > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n See Also\n --------\n resolveParentPath\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path[, options], predicate )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n\n The predicate function is provided one argument:\n\n - path: a resolved path.\n\n The function immediately returns upon encountering a truthy return value.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > function predicate() { return false; };\n > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n See Also\n --------\n resolveParentPath","reUncPath":"\nreUncPath()\n Return a regular expression to parse a UNC path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUncPath();\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\\\\\share';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\\\\\\\\\server\\\\share';\n > bool = RE.test( path )\n false\n > path = 'beep boop \\\\\\\\server\\\\share';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server';\n > bool = RE.test( path )\n false\n > path = '\\\\';\n > bool = RE.test( path )\n false\n > path = '';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\n > bool = RE.test( path )\n false\n > path = '//server/share';\n > bool = RE.test( path )\n false\n > path = '/foo/bar';\n > bool = RE.test( path )\n false\n > path = 'foo/bar';\n > bool = RE.test( path )\n false\n > path = './foo/bar';\n > bool = RE.test( path )\n false\n > path = '/foo/../bar';\n > bool = RE.test( path )\n false\n\n\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = reUncPath.REGEXP.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = reUncPath.REGEXP.test( path )\n true\n\n See Also\n --------\n isUNCPath\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = reUncPath.REGEXP.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = reUncPath.REGEXP.test( path )\n true\n\n See Also\n --------\n isUNCPath","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n Returns a regular expression to match a UTF-16 surrogate pair.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair();\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair.REGEXP;\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n See Also\n --------\n reUtf16UnpairedSurrogate","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair.REGEXP;\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n See Also\n --------\n reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n Returns a regular expression to match an unpaired UTF-16 surrogate.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate();\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate.REGEXP;\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n See Also\n --------\n reUtf16SurrogatePair","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate.REGEXP;\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n See Also\n --------\n reUtf16SurrogatePair","reverseArguments":"\nreverseArguments( fcn[, thisArg] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reversed arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reverseArguments( foo );\n > var out = bar( 1, 2, 3 )\n [ 3, 2, 1 ]\n\n See Also\n --------\n maskArguments, reorderArguments\n","reverseString":"\nreverseString( str[, options] )\n Reverses a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to reverse. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Reversed string.\n\n Examples\n --------\n > var out = reverseString( 'foo' )\n 'oof'\n > out = reverseString( 'abcdef' )\n 'fedcba'\n\n","reviveBasePRNG":"\nreviveBasePRNG( key, value )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or PRNG.\n\n Examples\n --------\n > var str = JSON.stringify( base.random.mt19937 );\n > var r = parseJSON( str, reviveBasePRNG )\n \n\n","reviveBuffer":"\nreviveBuffer( key, value )\n Revives a JSON-serialized Buffer.\n\n The serialization format for a Buffer is an object having the following\n fields:\n\n - type: value type (Buffer).\n - data: buffer data as an array of integers.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or Buffer.\n\n Examples\n --------\n > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n > var buf = parseJSON( str, reviveBuffer )\n [ 5, 3 ]\n\n See Also\n --------\n buffer2json\n","reviveComplex":"\nreviveComplex( key, value )\n Revives a JSON-serialized complex number.\n\n The serialization format for complex numbers is an object having the\n following fields:\n\n - type: complex number type (e.g., \"Complex128\", \"Complex64\").\n - re: real component (number).\n - im: imaginary component (number).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex )\n \n\n See Also\n --------\n Complex128, Complex64, reviveComplex128, reviveComplex64\n","reviveComplex64":"\nreviveComplex64( key, value )\n Revives a JSON-serialized 64-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex64 )\n \n\n See Also\n --------\n Complex64, reviveComplex128, reviveComplex\n","reviveComplex128":"\nreviveComplex128( key, value )\n Revives a JSON-serialized 128-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex128 )\n \n\n See Also\n --------\n Complex128, reviveComplex64, reviveComplex\n","reviveError":"\nreviveError( key, value )\n Revives a JSON-serialized error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or error object.\n\n Examples\n --------\n > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n > var err = JSON.parse( str, reviveError )\n \n\n See Also\n --------\n error2json\n","reviveRegExp":"\nreviveRegExp( key, value )\n Revives a JSON-serialized regular expression.\n\n The serialization format for a regular expression is an object having the\n following fields:\n\n - type: value type (RegExp).\n - pattern: regular expression pattern.\n - flags: regular expression flags.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or regular expression.\n\n Examples\n --------\n > var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\n > var v = parseJSON( str, reviveRegExp )\n \n\n See Also\n --------\n regexp2json","reviveTypedArray":"\nreviveTypedArray( key, value )\n Revives a JSON-serialized typed array.\n\n The serialization format for typed array is an object having the following\n fields:\n\n - type: typed array type (e.g., \"Float64Array\", \"Int8Array\").\n - data: typed array data as an array of numbers.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or typed array.\n\n Examples\n --------\n > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n > var arr = parseJSON( str, reviveTypedArray )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n typedarray2json\n","reWhitespace":"\nreWhitespace( [options] )\n Returns a regular expression to match a white space character.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to wrap a regular expression matching a white\n space character with a capture group. Default: false.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reWhitespace();\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false\n\n\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP;\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false\n\n\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP_CAPTURE;\n > var str = 'Duplicate capture';\n > var out = replace( str, RE, '$1$1' )\n 'Duplicate capture'\n\n See Also\n --------\n isWhitespace","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP;\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP_CAPTURE;\n > var str = 'Duplicate capture';\n > var out = replace( str, RE, '$1$1' )\n 'Duplicate capture'\n\n See Also\n --------\n isWhitespace","rpad":"\nrpad( str, len[, pad] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = rpad( 'a', 5 )\n 'a '\n > out = rpad( 'beep', 10, 'p' )\n 'beeppppppp'\n > out = rpad( 'beep', 12, 'boop' )\n 'beepboopboop'\n\n See Also\n --------\n lpad, pad\n","rtrim":"\nrtrim( str )\n Trims whitespace from the end of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n See Also\n --------\n ltrim, trim\n","rtrimN":"\nrtrimN( str, n[, chars] )\n Trims `n` characters from the end of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of characters to trim.\n\n chars: Array|string (optional)\n Characters to trim. Default: whitespace characters.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrimN( ' abc ', 2 )\n ' abc'\n > var out = rtrimN( '!!!abc!!!', 2, '!' )\n '!!!abc!'\n\n See Also\n --------\n ltrimN, trim","safeintmax":"\nsafeintmax( dtype )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: integer\n Maximum safe integer.\n\n Examples\n --------\n > var m = safeintmax( 'float16' )\n 2047\n > m = safeintmax( 'float32' )\n 16777215\n\n See Also\n --------\n safeintmin, realmax, typemax\n","safeintmin":"\nsafeintmin( dtype )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: integer\n Minimum safe integer.\n\n Examples\n --------\n > var m = safeintmin( 'float16' )\n -2047\n > m = safeintmin( 'float32' )\n -16777215\n\n See Also\n --------\n safeintmax, realmin, typemin\n","sample":"\nsample( x[, options] )\n Samples elements from an array-like object.\n\n Parameters\n ----------\n x: ArrayLike\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.size: integer (optional)\n Sample size. By default, the function returns an array having the same\n length as `x`. Specify the `size` option to generate a sample of a\n different size.\n\n options.probs: Array (optional)\n Element probabilities. By default, the probability of sampling an\n element is the same for all elements. To assign elements different\n probabilities, set the `probs` option. The `probs` option must be a\n numeric array consisting of nonnegative values which sum to one. When\n sampling without replacement, note that the `probs` option denotes the\n initial element probabilities which are then updated after each draw.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. If the `replace`\n option is set to `false`, the `size` option cannot be an integer larger\n than the number of elements in `x`. Default: `true`.\n\n Returns\n -------\n out: Array\n Sample.\n\n Examples\n --------\n > var out = sample( 'abc' )\n e.g., [ 'a', 'a', 'b' ]\n > out = sample( [ 3, 6, 9 ] )\n e.g., [ 3, 9, 6 ]\n > var bool = ( out.length === 3 )\n true\n\n > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n e.g., [ 3, 'abc', null, 3, null ]\n\n // Set sample size:\n > out = sample( [ 3, 6, 9 ], { 'size': 10 } )\n e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n > out = sample( [ 0, 1 ], { 'size': 20 } )\n e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n // Draw without replacement:\n > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\n e.g., [ 6, 1, 5 ]\n > out = sample( [ 0, 1 ], { 'replace': false } )\n e.g., [ 0, 1 ]\n\n // Assigning non-uniform element probabilities:\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n > out = sample( x, { 'probs': probs } )\n e.g., [ 5, 6, 6, 5, 6, 4 ]\n > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 } );\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]\n\n","sample.factory":"\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 } );\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FIN()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FR()\n [ 'a', 'à', 'â', 'abord', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_GER()\n [ 'a', 'ab', 'aber', 'ach', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_IT()\n [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_POR()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SP()\n [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SWE()\n [ 'aderton', 'adertonde', 'adjö', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","scalar2array":"\nscalar2array( value[, dtype] )\n Returns a single-element array containing a provided scalar value.\n\n If `value` is a number and `dtype` is a complex number data type, the\n function returns a complex number array containing a complex number whose\n real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n dtype: string (optional)\n Data type. If not provided and `value`\n\n - is a number, the default data type is the default real-valued\n floating-point data type.\n - is a boolean, the default data type is the default boolean data type.\n - is a complex number object of a known complex data type, the data type\n is the same as the provided value.\n - is a complex number object of an unknown data type, the default data\n type is the default complex-valued floating-point data type.\n - is any other value type, the default data type is 'generic'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = scalar2array( 1.0 )\n [ 1.0 ]\n\n See Also\n --------\n iterator2array\n","scalar2ndarray":"\nscalar2ndarray( value[, options] )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n\n If `value` is a number and `options.dtype` is a complex number data type,\n the function returns a zero-dimensional ndarray containing a complex number\n whose real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Data type. If not provided and `value`\n\n - is a number, the default data type is the default real-valued\n floating-point data type.\n - is a boolean, the default data type is the default boolean data type.\n - is a complex number object of a known complex data type, the data type\n is the same as the provided value.\n - is a complex number object of an unknown data type, the default data\n type is the default complex-valued floating-point data type.\n - is any other value type, the default data type is 'generic'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = scalar2ndarray( 1.0 )\n \n > var sh = x.shape\n []\n > var dt = x.dtype\n 'float64'\n > var v = x.get()\n 1.0\n\n See Also\n --------\n array, ndarray\n","sdot":"\nsdot( x, y[, dim] )\n Computes the dot product of two single-precision floating-point vectors.\n\n If provided at least one input array having more than one dimension, the\n input arrays are broadcasted to a common shape.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function computes the dot product for each pair\n of vectors in `x` and `y` according to the specified dimension index.\n\n The size of the contracted dimension must be the same for both input arrays.\n\n The function resolves the dimension index for which to compute the dot\n product *before* broadcasting.\n\n If provided empty vectors, the dot product is `0`.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float32' data type. Must have at least\n one dimension and be broadcast-compatible with the second input array.\n\n y: ndarray\n Second input array. Must have a 'float32' data type. Must have at least\n one dimension and be broadcast-compatible with the first input array.\n\n dim: integer (optional)\n Dimension index for which to compute the dot product. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n out: ndarray\n The dot product. The output array has the same data type as the input\n arrays and has a shape which is determined by broadcasting and excludes\n the contracted dimension.\n\n Examples\n --------\n > var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var x = array( xbuf );\n > var ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var y = array( ybuf );\n > var z = sdot( x, y )\n \n > z.get()\n -5.0\n\n See Also\n --------\n base.strided.sdot, ddot, gdot\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var secs = days * SECONDS_IN_DAY\n 271296\n\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var secs = hrs * SECONDS_IN_HOUR\n 11304\n\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var secs = mins * SECONDS_IN_MINUTE\n 188.4\n\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n","secondsInMonth":"\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n See Also\n --------\n secondsInYear\n","secondsInYear":"\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n See Also\n --------\n secondsInMonth\n","sentencize":"\nsentencize( str )\n Splits a string into an array of sentences.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: Array\n Array of sentences.\n\n Examples\n --------\n > var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello Mrs. Maple, could you call me back?' ]\n\n > out = sentencize( 'Hello World! How are you?' )\n [ 'Hello World!', 'How are you?' ]\n\n See Also\n --------\n tokenize\n","seq2slice":"\nseq2slice( str, len, strict )\n Converts a subsequence string to a Slice object.\n\n A subsequence string has the following format:\n\n ::\n\n If an increment is not specified, the default increment is one. An increment\n of zero is not allowed.\n\n The start index is inclusive.\n\n The stop index is exclusive.\n\n Both start and stop indices are optional. If not provided, the start and\n stop indices default to index extremes. Which extremes correspond to which\n index depends on whether the increment is positive or negative.\n\n Both start and stop indices can be negative; in which case, the\n corresponding index is resolved by subtracting the respective value from the\n provided length.\n\n Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n 'end-3:', etc), which supports basic subtraction and division.\n\n The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n exception is when performing a division operation when the increment is less\n than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n user expectations when 'end/d' equals a whole number and slicing from right-\n to-left. The result from a division operation is rounded down to the nearest\n integer value.\n\n In non-strict mode, the resolved slice start is clamped to the slice index\n bounds [0, len).\n\n In non-strict mode, Tte resolved slice end is upper bound clamped to the\n provided length (i.e., one greater than the last possible index).\n\n When the increment is negative, the resolved slice end value may be `null`,\n thus indicating that a non-empty slice should include the first index.\n\n The function ensures that results satisfy the convention that ':n' combined\n with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n When the provided length is zero, the function always returns a slice object\n equivalent to '0:0:'.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new seq2slice( '1:10', 10, false );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new seq2slice( '2:5:2', 10, false );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n Slice\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setReadOnly\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj, prop, fcn )\n Defines a configurable memoized read-only object property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedConfigurableReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setMemoizedReadOnly, setReadOnly\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj, prop, fcn )\n Defines a memoized read-only object property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n defineMemoizedProperty, setReadOnly\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > objectKeys( obj )\n []\n\n See Also\n --------\n setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n Defines a non-enumerable property having read-write accessors.\n\n Non-enumerable read-write accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableWriteOnlyAccessor, setReadWriteAccessor\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n Defines a non-enumerable write-only accessor.\n\n Non-enumerable write-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnly":"\nsetReadOnly( obj, prop, value )\n Defines a read-only property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setReadOnlyAccessor, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj, prop, getter )\n Defines a read-only accessor.\n\n Read-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj, prop, getter, setter )\n Defines a property having read-write accessors.\n\n Read-write accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setWriteOnlyAccessor\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj, prop, setter )\n Defines a write-only accessor.\n\n Write-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setReadWriteAccessor\n","SharedArrayBuffer":"\nSharedArrayBuffer( size )\n Returns a shared array buffer having a specified number of bytes.\n\n A shared array buffer behaves similarly to a non-shared array buffer, except\n that a shared array buffer allows creating views of memory shared between\n threads.\n\n Buffer contents are initialized to 0.\n\n If an environment does not support shared array buffers, the function throws\n an error.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: SharedArrayBuffer\n A shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 )\n \n\n\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1\n\n\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","shift":"\nshift( collection )\n Removes and returns the first element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = shift( arr )\n [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = shift( arr )\n [ [ 2.0 ], 1.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = shift( arr )\n [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n See Also\n --------\n pop, push, unshift\n","shuffle":"\nshuffle( arr[, options] )\n Shuffles elements of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object to shuffle.\n\n options: Object (optional)\n Options.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n out: ArrayLike\n Shuffled array-like object.\n\n Examples\n --------\n > var data = [ 1, 2, 3 ];\n > var out = shuffle( data )\n e.g., [ 3, 1, 2 ]\n > out = shuffle( data, { 'copy': 'none' } );\n > var bool = ( data === out )\n true\n\n\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' } );\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample\n","shuffle.factory":"\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' } );\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample","sizeOf":"\nsizeOf( dtype )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - complex128: 128-bit complex numbers.\n - complex64: 64-bit complex numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Size (in bytes).\n\n Examples\n --------\n > var s = sizeOf( 'int8' )\n 1\n > s = sizeOf( 'uint32' )\n 4\n\n See Also\n --------\n realmax, typemax\n","Slice":"\nSlice( [stop] )\n Returns a Slice.\n\n Parameters\n ----------\n stop: integer|null|undefined (optional)\n Ending index (exclusive).\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new Slice();\n > s = new Slice( 10 );\n\n\nSlice( start, stop[, step] )\n Returns a Slice.\n\n Parameters\n ----------\n start: integer|null|undefined\n Starting index (inclusive).\n\n stop: integer|null|undefined\n Ending index (exclusive).\n\n step: integer|null|undefined (optional)\n Index increment. A numeric index increment argument should be a non-zero\n integer value. Default: null.\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > s = new Slice( 2, 10, 1 );\n\n\nSlice.prototype.start\n Read-only property returning the starting slice index.\n\n Returns\n -------\n start: integer|null\n Starting index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.start\n null\n > s = new Slice( 2, 10 );\n > s.start\n 2\n\n\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n\n Returns\n -------\n stop: integer|null\n Ending index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.stop\n 10\n > s = new Slice( 2, 10 );\n > s.stop\n 10\n\n\nSlice.prototype.step\n Read-only property returning the index increment.\n\n Returns\n -------\n step: integer|null\n Index increment.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.step\n null\n > s = new Slice( 2, 10 );\n > s.step\n null\n > s = new Slice( 2, 10, 1 );\n > s.step\n 1\n\n\nSlice.prototype.toString()\n Serializes a Slice as a string.\n\n Returns\n -------\n str: string\n Serialized Slice string.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toString()\n 'Slice(null,10,null)'\n > s = new Slice( 2, 10, 1 );\n > s.toString()\n 'Slice(2,10,1)'\n\n\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ null, 10, null ] }\n > s = new Slice( 2, 10, 1 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n See Also\n --------\n ndarray, MultiSlice\n","Slice.prototype.start":"\nSlice.prototype.start\n Read-only property returning the starting slice index.\n\n Returns\n -------\n start: integer|null\n Starting index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.start\n null\n > s = new Slice( 2, 10 );\n > s.start\n 2","Slice.prototype.stop":"\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n\n Returns\n -------\n stop: integer|null\n Ending index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.stop\n 10\n > s = new Slice( 2, 10 );\n > s.stop\n 10","Slice.prototype.step":"\nSlice.prototype.step\n Read-only property returning the index increment.\n\n Returns\n -------\n step: integer|null\n Index increment.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.step\n null\n > s = new Slice( 2, 10 );\n > s.step\n null\n > s = new Slice( 2, 10, 1 );\n > s.step\n 1","Slice.prototype.toString":"\nSlice.prototype.toString()\n Serializes a Slice as a string.\n\n Returns\n -------\n str: string\n Serialized Slice string.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toString()\n 'Slice(null,10,null)'\n > s = new Slice( 2, 10, 1 );\n > s.toString()\n 'Slice(2,10,1)'","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ null, 10, null ] }\n > s = new Slice( 2, 10, 1 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n See Also\n --------\n ndarray, MultiSlice","snakecase":"\nsnakecase( str )\n Converts a string to snake case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Snake-cased string.\n\n Examples\n --------\n > var out = snakecase( 'Hello World!' )\n 'hello_world'\n > out = snakecase( 'I am a tiny little teapot' )\n 'i_am_a_tiny_little_teapot'\n\n See Also\n --------\n camelcase, constantcase, kebabcase, pascalcase","some":"\nsome( collection, n )\n Tests whether at least `n` elements in a collection are truthy.\n\n The function immediately returns upon finding `n` truthy elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 1, 2, 3 ];\n > var bool = some( arr, 3 )\n true\n\n See Also\n --------\n any, every, forEach, none, someBy\n","someBy":"\nsomeBy( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, -3, 4, -1 ];\n > var bool = someBy( arr, 2, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, noneBy, someByAsync, someByRight\n","someByAsync":"\nsomeByAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync\n","someByAsync.factory":"\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync","someByRight":"\nsomeByRight( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, -2, 3, 4 ];\n > var bool = someByRight( arr, 2, negative )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, noneByRight, someBy, someByRightAsync\n","someByRightAsync":"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection value.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight","someInBy":"\nsomeInBy( obj, n, predicate[, thisArg ] )\n Tests whether an object contains at least `n` properties\n (own and inherited) which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - obj: the input object.\n\n The function immediately returns upon finding `n` successful properties.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n obj: Object\n Input object over which to iterate.\n\n n: number\n Minimum number of successful properties.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an object contains at least `n`\n successful properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\n > var bool = someInBy( obj, 2, negative )\n true\n\n See Also\n --------\n anyInBy, everyInBy, someBy, someOwnBy","someOwnBy":"\nsomeOwnBy( obj, n, predicate[, thisArg ] )\n Tests whether some `own` properties of a provided object\n satisfy a predicate function for at least `n` properties.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - obj: the input object.\n\n The function immediately returns upon finding `n` successful properties.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n obj: Object\n Input object over which to iterate.\n\n n: number\n Minimum number of successful properties.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an object's own properties satisfy a\n predicate for at least `n` properties; otherwise, the function\n returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\n > var bool = someOwnBy( obj, 2, negative )\n true\n\n See Also\n --------\n anyOwnBy, everyOwnBy, someBy, someInBy","SOTU":"\nSOTU( [options] )\n Returns State of the Union (SOTU) addresses.\n\n Each State of the Union address is represented by an object with the\n following fields:\n\n - year: speech year.\n - name: President name.\n - party: the President's political party.\n - text: speech text.\n\n The following political parties are recognized:\n\n - Democratic\n - Republican\n - Democratic-Republican\n - Federalist\n - National Union\n - Whig\n - Whig & Democratic\n - none\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.name: String|Array (optional)\n President name(s).\n\n options.party: String|Array (optional)\n Political party (or parties).\n\n options.year: integer|Array (optional)\n Year(s).\n\n options.range: Array (optional)\n Two-element array specifying a year range.\n\n Returns\n -------\n out: Array\n State of the Union addresses.\n\n Examples\n --------\n > var out = SOTU()\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more Presidents...\n > var opts = { 'name': 'Barack Obama' };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more political parties...\n > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses from one or more years...\n > opts = { 'year': [ 2008, 2009, 2011 ] };\n > out = SOTU( opts )\n [ {...}, {...}, {...} ]\n\n // Retrieve addresses from a range of consecutive years...\n > opts = { 'range': [ 2008, 2016 ] }\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n\n Returns\n -------\n out: Array\n List of simple American-English words.\n\n Examples\n --------\n > var list = SPACHE_REVISED()\n [ 'a', 'able', 'about', 'above', ... ]\n\n References\n ----------\n - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n 458513.\n - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n .\n - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n School Journal* 57 (1). University of Chicago Press: 36–41.\n .\n - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n .\n\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n\n Each array element has the following fields:\n\n - id: message id (relative to message group).\n - group: message group.\n - checksum: object containing checksum info.\n - text: message text (including headers).\n\n The message group may be one of the following:\n\n - easy-ham-1: easier to detect non-spam e-mails (2500 messages).\n - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n (1400 messages).\n - hard-ham-1: harder to detect non-spam e-mails (250 messages).\n - spam-1: spam e-mails (500 messages).\n - spam-2: spam e-mails collected at a later date (1396 messages).\n\n The checksum object contains the following fields:\n\n - type: checksum type (e.g., MD5).\n - value: checksum value.\n\n Returns\n -------\n out: Array\n Corpus.\n\n Examples\n --------\n > var data = SPAM_ASSASSIN()\n [ {...}, {...}, ... ]\n\n","SparklineBase":"\nSparklineBase( [data,] [options] )\n Returns a Sparkline instance.\n\n This constructor is a base Sparkline constructor from which constructors\n tailored to generating particular types of Sparkline graphics should be\n derived.\n\n At a minimum, descendants should implement a private `_render()` method\n which will be automatically invoked by the public `render()` method.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options.description: string (optional)\n Sparkline description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n sparkline: Sparkline\n Sparkline instance.\n\n sparkline.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n sparkline.bufferSize\n Data buffer size.\n\n sparkline.description\n Sparkline description.\n\n sparkline.data\n Sparkline data.\n\n sparkline.label\n Data label.\n\n sparkline.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n sparkline.render()\n Renders a sparkline. This method calls `_render()` which must be\n implemented by instances and child classes. The default behavior is\n throw an error.\n\n Examples\n --------\n > var sparkline = new SparklineBase()\n \n\n // Provide sparkline data at instantiation:\n > var data = [ 1, 2, 3 ];\n > sparkline = new SparklineBase( data )\n \n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","sparsearray2iterator":"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, sparsearray2iteratorRight\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, sparsearray2iterator\n","splitStream":"\nsplitStream( [options] )\n Returns a transform stream which splits streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream.Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = splitStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream\n","splitStream.factory":"\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();","splitStream.objectMode":"\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n\n Examples\n --------\n > SQRT_EPS\n 0.14901161193847656e-7\n\n See Also\n --------\n EPS\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n\n Examples\n --------\n > SQRT_HALF\n 0.7071067811865476\n\n See Also\n --------\n LN_HALF\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n\n Examples\n --------\n > SQRT_HALF_PI\n 1.2533141373155003\n\n See Also\n --------\n PI\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n\n Examples\n --------\n > SQRT_PHI\n 1.272019649514069\n\n See Also\n --------\n PHI\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n\n Examples\n --------\n > SQRT_PI\n 1.7724538509055160\n\n See Also\n --------\n PI\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n\n Examples\n --------\n > SQRT_THREE\n 1.7320508075688772\n\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n\n Examples\n --------\n > SQRT_TWO\n 1.4142135623730951\n\n See Also\n --------\n LN2\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n\n Examples\n --------\n > SQRT_TWO_PI\n 2.5066282746310007\n\n See Also\n --------\n TWO_PI\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n Returns US birth data from 2000 to 2014, as provided by the Social Security\n Administration.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = SSA_US_BIRTHS_2000_2014()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1969_1988, CDC_NCHS_US_BIRTHS_1994_2003\n","sswap":"\nsswap( x, y[, dim] )\n Interchanges two single-precision floating-point vectors.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function interchanges each pair of vectors in `x`\n and `y` according to the specified dimension index.\n\n Both input arrays must have the same shape.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float32' data type. Must have at least\n one dimension and must have the same shape as the second input array.\n\n y: ndarray\n Second input array. Must have a 'float32' data type. Must have at least\n one dimension and must have the same shape as the first input array.\n\n dim: integer (optional)\n Dimension index along which to interchange vectors. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n > var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > sswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.sswap, dswap, gswap\n","Stack":"\nStack()\n Stack constructor.\n\n A stack is also referred to as a \"last-in-first-out\" queue.\n\n Returns\n -------\n stack: Object\n Stack data structure.\n\n stack.clear: Function\n Clears the stack.\n\n stack.first: Function\n Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.iterator: Function\n Returns an iterator for iterating over a stack. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from stack mutation during\n iteration, a returned iterator **always** iterates over a stack\n \"snapshot\", which is defined as the list of stack elements at the time\n of the method's invocation.\n\n stack.last: Function\n Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.length: integer\n Stack length.\n\n stack.pop: Function\n Removes and returns the current \"first-out\" value from the stack. If the\n stack is empty, the returned value is `undefined`.\n\n stack.push: Function\n Adds a value to the stack.\n\n stack.toArray: Function\n Returns an array of stack values.\n\n stack.toJSON: Function\n Serializes a stack as JSON.\n\n Examples\n --------\n > var s = Stack();\n > s.push( 'foo' ).push( 'bar' );\n > s.length\n 2\n > s.pop()\n 'bar'\n > s.length\n 1\n > s.pop()\n 'foo'\n > s.length\n 0\n\n See Also\n --------\n FIFO\n","standalone2pkg":"\nstandalone2pkg( pkg )\n Returns the internal package name associated with a provided standalone\n package name.\n\n Parameters\n ----------\n pkg: string\n Standalone package name.\n\n Returns\n -------\n out: string|null\n Internal package name.\n\n Examples\n --------\n > var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2standalone, pkg2alias, pkg2standalone\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n Returns a string array containing two or three letter abbreviations for each\n card in a standard 52-card deck.\n\n Abbreviation format: \n\n Cards: A, 2, 3, 4, 5, 6, 7, 8, 9, 10, J, Q, K, where\n\n - A: ace\n - J: jack\n - Q: queen\n - K: king\n\n Suit abbreviations:\n\n - C: clubs\n - D: diamonds\n - H: hearts\n - S: spades\n\n Returns\n -------\n out: Array\n List of cards.\n\n Examples\n --------\n > var list = STANDARD_CARD_DECK()\n [ 'AC', '2C', '3C', ... ]\n\n","startcase":"\nstartcase( str )\n Capitalizes the first letter of each word in an input string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n lowercase, uppercase\n","startsWith":"\nstartsWith( str, search[, position] )\n Tests if a string starts with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer (optional)\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string starts with the characters of\n another string.\n\n Examples\n --------\n > var bool = startsWith( 'Beep', 'Be' )\n true\n > bool = startsWith( 'Beep', 'ep' )\n false\n > bool = startsWith( 'Beep', 'ee', 1 )\n true\n > bool = startsWith( 'Beep', 'ee', -3 )\n true\n > bool = startsWith( 'Beep', '' )\n true\n\n See Also\n --------\n endsWith\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = STOPWORDS_EN()\n [ 'a', 'about', 'above', 'across', ... ]\n\n","strided.abs":"\nstrided.abs( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs( 2, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs","strided.abs2":"\nstrided.abs2( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 9.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs2\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs2","strided.abs2By":"\nstrided.abs2By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By( x.length, x, 1, y, 1, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By( 2, x, 2, y, -1, clbk )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs2By( 2, x1, -2, y1, 1, clbk )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = [ -1.0, -2.0, -3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.absBy, strided.abs2\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = [ -1.0, -2.0, -3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.absBy, strided.abs2","strided.absBy":"\nstrided.absBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy( x.length, x, 1, y, 1, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy( 2, x, 2, y, -1, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.absBy( 2, x1, -2, y1, 1, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n strided.abs, strided.abs2By\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n strided.abs, strided.abs2By","strided.acosBy":"\nstrided.acosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy( 2, x, 2, y, -1, clbk )\n [ ~0.524, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acosBy( 2, x1, -2, y1, 1, clbk )\n [ ~2.356, ~0.786 ]\n > y0\n [ 0.0, 0.0, ~2.356, ~0.786 ]\n\n\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Advanced indexing:\n > x = [ 1.0, 0.707, 0.866, -0.707 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.356, ~0.786 ]\n\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Advanced indexing:\n > x = [ 1.0, 0.707, 0.866, -0.707 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.356, ~0.786 ]","strided.acoshBy":"\nstrided.acoshBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy( 2, x, 2, y, -1, clbk )\n [ ~1.317, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acoshBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.567, ~0.962 ]\n > y0\n [ 0.0, 0.0, ~1.567, ~0.962 ]\n\n\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Advanced indexing:\n > x = [ 1.0, 1.5, 2.0, 2.5 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.567, ~0.962 ]\n\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Advanced indexing:\n > x = [ 1.0, 1.5, 2.0, 2.5 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.567, ~0.962 ]","strided.acotBy":"\nstrided.acotBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy( x.length, x, 1, y, 1, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy( 2, x, 2, y, -1, clbk )\n [ ~-1.107, ~-0.381, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acotBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~-0.588 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Advanced indexing:\n > x = [ -2.5, -1.5, -0.5, 0.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Advanced indexing:\n > x = [ -2.5, -1.5, -0.5, 0.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~-0.588 ]","strided.acothBy":"\nstrided.acothBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy( x.length, x, 1, y, 1, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy( 2, x, 2, y, -1, clbk )\n [ ~-0.347, ~-0.203, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acothBy( 2, x1, -2, y1, 1, clbk )\n [ -Infinity, ~-0.255 ]\n > y0\n [ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Advanced indexing:\n > x = [ -5.0, -4.0, -3.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Advanced indexing:\n > x = [ -5.0, -4.0, -3.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, -Infinity, ~-0.255 ]","strided.acovercosBy":"\nstrided.acovercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy( x.length, x, 1, y, 1, clbk )\n [ ~-1.571, ~0.607, ~-0.524, 0.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy( 2, x, 2, y, -1, clbk )\n [ ~-0.524, ~-1.571, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acovercosBy( 2, x1, -2, y1, 1, clbk )\n [ 0.0, ~0.607 ]\n > y0\n [ 0.0, 0.0, 0.0, ~0.607 ]\n\n\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-1.571, ~0.607, ~-0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~0.607 ]\n\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-1.571, ~0.607, ~-0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~0.607 ]","strided.acoversinBy":"\nstrided.acoversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy( x.length, x, 1, y, 1, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy( 2, x, 2, y, -1, clbk )\n [ ~0.524, ~1.571, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acoversinBy( 2, x1, -2, y1, 1, clbk )\n [ 0.0, ~-0.607 ]\n > y0\n [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~-0.607 ]","strided.add":"\nstrided.add( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ 1.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -2.0, 5.0 ]\n > z0\n [ 0.0, 0.0, -2.0, 5.0 ]\n\n\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 5.0, -2.0, 0.0 ]\n\n See Also\n --------\n strided.mul, strided.sub\n","strided.add.ndarray":"\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 5.0, -2.0, 0.0 ]\n\n See Also\n --------\n strided.mul, strided.sub","strided.addBy":"\nstrided.addBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.addBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 13.0, 14.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 17.0, 16.0 ]\n > z0\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n See Also\n --------\n strided.add, strided.mulBy, strided.subBy\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n See Also\n --------\n strided.add, strided.mulBy, strided.subBy","strided.ahavercosBy":"\nstrided.ahavercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy( x.length, x, 1, y, 1, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy( 2, x, 2, y, -1, clbk )\n [ 0.0, ~3.142, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\n [ ~2.094, ~1.571 ]\n > y0\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n See Also\n --------\n strided.ahaversinBy\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n See Also\n --------\n strided.ahaversinBy","strided.ahaversinBy":"\nstrided.ahaversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy( 2, x, 2, y, -1, clbk )\n [ ~3.142, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.047, ~1.571 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n See Also\n --------\n strided.ahavercosBy\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n See Also\n --------\n strided.ahavercosBy","strided.asinBy":"\nstrided.asinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy( 2, x, 2, y, -1, clbk )\n [ ~1.571, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.asinBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.253, ~-0.524 ]\n > y0\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n See Also\n --------\n strided.asinhBy\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n See Also\n --------\n strided.asinhBy","strided.asinhBy":"\nstrided.asinhBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy( 2, x, 2, y, -1, clbk )\n [ ~1.444, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.asinhBy( 2, x1, -2, y1, 1, clbk )\n [ ~-1.444, 0.0 ]\n > y0\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.0, 2.0, -2.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n See Also\n --------\n strided.asinBy\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.0, 2.0, -2.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n See Also\n --------\n strided.asinBy","strided.atanBy":"\nstrided.atanBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy( 2, x, 2, y, -1, clbk )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.atanBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.896, ~-0.464 ]\n > y0\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -1.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n See Also\n --------\n strided.atanhBy\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -1.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n See Also\n --------\n strided.atanhBy","strided.atanhBy":"\nstrided.atanhBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy( 2, x, 2, y, -1, clbk )\n [ Infinity, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.atanhBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.255, ~-0.549 ]\n > y0\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n See Also\n --------\n strided.atanBy\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n See Also\n --------\n strided.atanBy","strided.avercosBy":"\nstrided.avercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy( 2, x, 2, y, -1, clbk )\n [ ~1.047, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.avercosBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~2.177 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, -1.57, -0.5, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, -1.57, -0.5, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.aversinBy":"\nstrided.aversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy( 2, x, 2, y, -1, clbk )\n [ ~1.047, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.aversinBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~2.177 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.besselj0By":"\nstrided.besselj0By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By( 2, x, 2, y, -1, clbk )\n [ ~0.998, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.besselj0By( 2, x1, -2, y1, 1, clbk )\n [ ~0.984, ~0.765 ]\n > y0\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n See Also\n --------\n strided.besselj1By, strided.bessely0By, strided.bessely1By\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n See Also\n --------\n strided.besselj1By, strided.bessely0By, strided.bessely1By","strided.besselj1By":"\nstrided.besselj1By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By( 2, x, 2, y, -1, clbk )\n [ ~0.05, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.besselj1By( 2, x1, -2, y1, 1, clbk )\n [ ~0.124, ~0.44 ]\n > y0\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n See Also\n --------\n strided.besselj0By, strided.bessely0By, strided.bessely1By\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n See Also\n --------\n strided.besselj0By, strided.bessely0By, strided.bessely1By","strided.bessely0By":"\nstrided.bessely0By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By( x.length, x, 1, y, 1, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By( 2, x, 2, y, -1, clbk )\n [ ~-1.534, -Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.bessely0By( 2, x1, -2, y1, 1, clbk )\n [ ~-0.932, ~0.088 ]\n > y0\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely1By\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely1By","strided.bessely1By":"\nstrided.bessely1By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By( x.length, x, 1, y, 1, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By( 2, x, 2, y, -1, clbk )\n [ ~-6.459, -Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.bessely1By( 2, x1, -2, y1, 1, clbk )\n [ ~-2.704, ~-0.781 ]\n > y0\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely0By\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely0By","strided.binetBy":"\nstrided.binetBy( N, x, sx, y, sy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy( 2, x, 2, y, -1, clbk )\n [ 1.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.binetBy( 2, x1, -2, y1, 1, clbk )\n [ 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 2.0, 1.0 ]\n\n\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 2.0, 3.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 2.0, 1.0 ]\n\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 2.0, 3.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 2.0, 1.0 ]","strided.cbrt":"\nstrided.cbrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.scbrt, strided.sqrt\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.scbrt, strided.sqrt","strided.cbrtBy":"\nstrided.cbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy( 2, x, 2, y, -1, clbk )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cbrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~4.327, ~2.08 ]\n > y0\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = [ 1.0, 9.0, -27.0, 81.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = [ 1.0, 9.0, -27.0, 81.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt","strided.ceil":"\nstrided.ceil( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil","strided.cosBy":"\nstrided.cosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy( 2, x, 2, y, -1, clbk )\n [ ~-1.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cosBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.839, ~-1.0 ]\n > y0\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]","strided.deg2rad":"\nstrided.deg2rad( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~1.571, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.sdeg2rad\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.sdeg2rad","strided.dataTypes":"\nstrided.dataTypes()\n Returns a list of strided array data types.\n\n The output array contains the following data types:\n\n - binary: binary.\n - bool: boolean values.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of strided array data types.\n\n Examples\n --------\n > var out = strided.dataTypes()\n \n\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy( 2, x, 2, y, -1, clbk )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~4.327, ~2.08 ]\n > y0\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt","strided.dispatch":"\nstrided.dispatch( fcns, types, data, nargs, nin, nout )\n Returns a strided array function interface which performs multiple dispatch.\n\n Without offsets, a strided array function interface has the following\n signature:\n\n f( N, dtypeX, x, strideX, dtypeY, y, strideY, ... )\n\n where\n\n - N: number of indexed elements.\n - dtypeX: data type for `x`.\n - x: strided array.\n - strideX: index increment for `x`.\n - dtypeY: data type for `y`.\n - y: strided array.\n - strideY: index increment for `y`.\n - ...: additional strided arrays, data types, and associated strides.\n\n The number of parameters is derived from `nargs`, the number of input\n strided arrays is derived from `nin`, and the number of output strided\n arrays is derived from `nout`.\n\n Without offsets, the number of parameters must obey the following relation:\n\n nargs = 3*(nout+nin) + 1\n\n With offsets, the number of parameters must obey the following relation:\n\n nargs = 4*(nout+nin) + 1\n\n With offsets, a strided array function interface has the following\n signature:\n\n f( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY, ... )\n\n where\n\n - N: number of indexed elements.\n - dtypeX: data type for `x`.\n - x: strided array.\n - strideX: index increment for `x`.\n - offsetX: starting index for `x`.\n - dtypeY: data type for `y`.\n - y: strided array.\n - strideY: index increment for `y`.\n - offsetY: starting index for `y`.\n - ...: additional strided arrays and associated data types, strides, and\n offsets.\n\n The choice of which strided array function interface to return depends on\n the use case. The former is suitable for typed array views; while the latter\n affords alternative indexing semantics more suitable for n-dimensional\n arrays (ndarrays).\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of strided array functions. Without offsets, a strided array\n function should have the following signature:\n\n f( arrays, shape, strides, data )\n\n where\n\n - arrays: array containing strided input and output arrays.\n - shape: array containing a single element, the number of indexed\n elements.\n - strides: array containing the stride lengths for the strided input and\n output arrays.\n - data: strided array function data (e.g., a callback).\n\n With offsets, a strided array function should have the following\n signature:\n\n f( arrays, shape, strides, offsets, data )\n\n where\n\n - offsets: array containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n For convenience, a single strided array function may be provided which\n will be invoked whenever the strided array argument data types match a\n sequence of types in `types`. Providing a single strided array function\n is particularly convenient for the case where, regardless of array data\n types, traversing arrays remains the same, but the strided array\n function `data` differs (e.g., callbacks which differ based on the array\n data types).\n\n types: ArrayLikeObject\n One-dimensional list of strided array argument data types.\n\n data: ArrayLikeObject|null\n Strided array function data (e.g., callbacks). If `null`, a returned\n strided array function interface does **not** provide a `data` argument\n to an invoked strided array function.\n\n nargs: integer\n Total number of strided array function interface arguments (including\n data types, strides, and offsets).\n\n nin: integer\n Number of input strided arrays.\n\n nout: integer\n Number of output strided arrays.\n\n Returns\n -------\n fcn: Function\n Strided array function interface.\n\n Examples\n --------\n // Define strided array argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of strided array function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create a strided array function interface for applying unary callbacks:\n > var f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\n\n // Create an input strided array:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value:\n > f( x.length, 'float64', x, 1, 'float64', y, 1 );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Create a strided array function interface supporting offsets:\n > f = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\n\n // Create an input strided array:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value starting from the third element:\n > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\n > y\n [ 0.0, 0.0, 3.0, 4.0 ]\n\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns, types, data, nargs, nin, nout )\n Returns a strided array function interface which accepts a callback function\n and performs multiple dispatch.\n\n Without offsets, a strided array function interface has the following\n signature:\n\n f( N, dx, x, sx, dy, y, sy, ..., clbk[, thisArg] )\n\n where\n\n - N: number of indexed elements.\n - dx: data type for `x`.\n - x: strided array.\n - sx: index increment for `x`.\n - dy: data type for `y`.\n - y: strided array.\n - sy: index increment for `y`.\n - ...: additional strided arrays, data types, and associated strides.\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n The number of parameters is derived from `nargs`, the number of input\n strided arrays is derived from `nin`, and the number of output strided\n arrays is derived from `nout`.\n\n Without offsets, the number of parameters must obey the following relation:\n\n nargs = 3*(nout+nin) + 2\n\n With offsets, the number of parameters must obey the following relation:\n\n nargs = 4*(nout+nin) + 2\n\n With offsets, a strided array function interface has the following\n signature:\n\n f( N, dx, x, sx, ox, dy, y, sy, oy, ..., clbk[, thisArg] )\n\n where\n\n - N: number of indexed elements.\n - dx: data type for `x`.\n - x: strided array.\n - sx: index increment for `x`.\n - ox: starting index for `x`.\n - dy: data type for `y`.\n - y: strided array.\n - sy: index increment for `y`.\n - oy: starting index for `y`.\n - ...: additional strided arrays and associated data types, strides, and\n offsets.\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n The choice of which strided array function interface to return depends on\n the use case. The former is suitable for typed array views; while the latter\n affords alternative indexing semantics more suitable for n-dimensional\n arrays (ndarrays).\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of strided array functions. Without offsets, a strided array\n function should have the following signature:\n\n f( arrays, shape, strides, data, clbk, thisArg )\n\n where\n\n - arrays: array containing strided input and output arrays.\n - shape: array containing a single element, the number of indexed\n elements.\n - strides: array containing the stride lengths for the strided input and\n output arrays.\n - data: strided array function data (e.g., a callback).\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n With offsets, a strided array function should have the following\n signature:\n\n f( arrays, shape, strides, offsets, data, clbk, thisArg )\n\n where\n\n - offsets: array containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n For convenience, a single strided array function may be provided which\n will be invoked whenever the strided array argument data types match a\n sequence of types in `types`. Providing a single strided array function\n is particularly convenient for the case where, regardless of array data\n types, traversing arrays remains the same, but the strided array\n function `data` differs (e.g., callbacks which differ based on the array\n data types).\n\n types: ArrayLikeObject\n One-dimensional list of strided array argument data types.\n\n data: ArrayLikeObject|null\n Strided array function data (e.g., callbacks). If `null`, a returned\n strided array function interface does **not** provide a `data` argument\n to an invoked strided array function.\n\n nargs: integer\n Total number of strided array function interface arguments (including\n data types, strides, offsets, and the callback function).\n\n nin: integer\n Number of input strided arrays.\n\n nout: integer\n Number of output strided arrays.\n\n Returns\n -------\n fcn: Function\n Strided array function interface.\n\n Examples\n --------\n // Define strided array argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of strided array function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create a strided array function interface for applying unary callbacks:\n > var f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\n\n // Create an input strided array:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value:\n > f( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Create a strided array function interface supporting offsets:\n > f = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\n\n // Create an input strided array:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value starting from the third element:\n > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\n > y\n [ 0.0, 0.0, 3.0, 4.0 ]\n\n See Also\n --------\n strided.dispatch\n","strided.floor":"\nstrided.floor( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -4.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor","strided.inv":"\nstrided.inv( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 0.5, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.sinv\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.sinv","strided.mul":"\nstrided.mul( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ -6.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -15.0, 4.0 ]\n > z0\n [ 0.0, 0.0, -15.0, 4.0 ]\n\n\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 4.0, -15.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.sub\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 4.0, -15.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.sub","strided.mulBy":"\nstrided.mulBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 12.0, 33.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 52.0, 28.0 ]\n > z0\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n See Also\n --------\n strided.mul, strided.addBy, strided.subBy\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n See Also\n --------\n strided.mul, strided.addBy, strided.subBy","strided.ramp":"\nstrided.ramp( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.sramp\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.sramp","strided.rsqrt":"\nstrided.rsqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.sqrt, base.strided.srsqrt\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.sqrt, base.strided.srsqrt","strided.sinBy":"\nstrided.sinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy( 2, x, 2, y, -1, clbk )\n [ ~-0.002, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sinBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.544, ~0.002 ]\n > y0\n [ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.544, ~0.002 ]","strided.sqrt":"\nstrided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt","strided.sqrtBy":"\nstrided.sqrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy( 2, x, 2, y, -1, clbk )\n [ ~11.045, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sqrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~7.071, 1.0 ]\n > y0\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 122.0, 50.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n See Also\n --------\n strided.sqrt\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 122.0, 50.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n See Also\n --------\n strided.sqrt","strided.sub":"\nstrided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ -5.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -8.0, -3.0 ]\n > z0\n [ 0.0, 0.0, -8.0, -3.0 ]\n\n\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, -3.0, -8.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.mul\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, -3.0, -8.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.mul","strided.subBy":"\nstrided.subBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.subBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 4.0, 5.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 8.0, 7.0 ]\n > z0\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Advanced indexing:\n > x = [ 11.0, 12.0, 13.0, 14.0 ];\n > y = [ 8.0, 7.0, 6.0, 5.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n See Also\n --------\n strided.sub, strided.addBy, strided.mulBy\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Advanced indexing:\n > x = [ 11.0, 12.0, 13.0, 14.0 ];\n > y = [ 8.0, 7.0, 6.0, 5.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n See Also\n --------\n strided.sub, strided.addBy, strided.mulBy","strided.trunc":"\nstrided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc","stridedarray2iterator":"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n N: integer\n Number of values to iterate.\n\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iterator\n","stridedArrayStream":"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n Creates a readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream","string2buffer":"\nstring2buffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = string2buffer( 'beep boop' )\n \n > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n > b.toString()\n 'this is a tést'\n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer\n","sub2ind":"\nsub2ind( shape, ...subscript[, options] )\n Converts subscripts to a linear index.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n subscript: ...integer\n Subscripts.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string|Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If\n equal to 'throw', the function throws an error when a subscript exceeds\n array dimensions. If equal to 'normalize', the function normalizes\n negative subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', the function wraps around subscripts\n exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', the function sets subscripts exceeding array dimensions to\n either `0` (minimum index) or the maximum index along a particular\n dimension. If provided a mode array, each array element specifies the\n mode for a corresponding array dimension. If provided fewer modes than\n dimensions, the function recycles modes using modulo arithmetic.\n Default: [ 'throw' ].\n\n Returns\n -------\n idx: integer\n Linear index.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var idx = sub2ind( d, 1, 2, 2 )\n 17\n\n See Also\n --------\n array, ndarray, ind2sub\n","substringAfter":"\nsubstringAfter( str, search[, fromIndex] )\n Returns the part of a string after a specified substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n fromIndex: integer (optional)\n Index from which to start the search. Default: `0`.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var out = substringAfter( 'Hello World!', 'World' )\n '!'\n > out = substringAfter( 'Hello World!', 'Hello ' )\n 'World!'\n > out = substringAfter( 'Hello World!', 'l', 5 )\n 'd!'\n\n See Also\n --------\n substringBefore, substringBeforeLast, substringAfterLast","substringAfterLast":"\nsubstringAfterLast( str, search[, fromIndex] )\n Returns the part of a string after the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n fromIndex: integer (optional)\n Index of last character to be considered beginning of a match.\n Default: `str.length`.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var out = substringAfterLast( 'beep boop beep baz', 'beep' )\n ' baz'\n > out = substringAfterLast( 'Hello World!', 'Hello ' )\n 'World!'\n > out = substringAfterLast( 'Hello World!', 'o', 5 )\n ' World!'\n\n See Also\n --------\n substringBefore, substringBeforeLast, substringAfter","substringBefore":"\nsubstringBefore( str, search )\n Returns the part of a string before a specified substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = substringBefore( str, ' ' )\n 'beep'\n > out = substringBefore( str, 'o' )\n 'beep b'\n\n See Also\n --------\n substringBeforeLast, substringAfter, substringAfterLast","substringBeforeLast":"\nsubstringBeforeLast( str, search )\n Returns the part of a string before the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'Beep Boop Beep';\n > var out = substringBeforeLast( str, 'Beep' )\n 'Beep Boop '\n > out = substringBeforeLast( str, 'Boop' )\n 'Beep '\n\n See Also\n --------\n substringBefore, substringAfter, substringAfterLast","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on July 10, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on May 9, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK\n","Symbol":"\nSymbol( [description] )\n Returns a symbol.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support symbols.\n\n Parameters\n ----------\n description: string (optional)\n Symbol description which can be used for debugging but not to access the\n symbol itself.\n\n Returns\n -------\n out: symbol\n Symbol.\n\n Examples\n --------\n > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n","tabulate":"\ntabulate( collection )\n Generates a frequency table.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulate( collection )\n [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulateBy\n","tabulateBy":"\ntabulateBy( collection, [options,] indicator )\n Generates a frequency table according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > function indicator( value ) { return value[ 0 ]; };\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulateBy( collection, indicator )\n [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulate\n","tabulateByAsync":"\ntabulateByAsync( collection, [options,] indicator, done )\n Generates a frequency table according to an indicator function.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, indicator, done )\n 750\n 1000\n 2500\n 3000\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n 750\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy","thunk":"\nthunk( fcn[, ...args] )\n Returns a thunk.\n\n Parameters\n ----------\n fcn: Function\n Function to convert to a thunk.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n out: Function\n Thunk.\n\n Examples\n --------\n > var fcn = thunk( base.add, 2, 3 );\n > var v = fcn()\n 5\n > v = fcn()\n 5\n\n","tic":"\ntic()\n Returns a high-resolution time.\n\n The returned array has the following format: `[seconds, nanoseconds]`.\n\n Returns\n -------\n out: Array\n High resolution time.\n\n Examples\n --------\n > var t = tic()\n [ , ]\n\n See Also\n --------\n toc\n","timeit":"\ntimeit( code, [options,] clbk )\n Times a snippet.\n\n If the `asynchronous` option is set to `true`, the implementation assumes\n that `before`, `after`, and `code` snippets are all asynchronous.\n Accordingly, these snippets should invoke a `next( [error] )` callback\n once complete. The implementation wraps the snippet within a function\n accepting two arguments: `state` and `next`.\n\n The `state` parameter is simply an empty object which allows the `before`,\n `after`, and `code` snippets to share state.\n\n Notes:\n\n - Snippets always run in strict mode.\n - Always verify results. Doing so prevents the compiler from performing dead\n code elimination and other optimization techniques, which would render\n timing results meaningless.\n - Executed code is not sandboxed and has access to the global state. You are\n strongly advised against timing untrusted code. To time untrusted code,\n do so in an isolated environment (e.g., a separate process with restricted\n access to both global state and the host environment).\n - Wrapping asynchronous code does add overhead, but, in most cases, the\n overhead should be negligible compared to the execution cost of the timed\n snippet.\n - When the `asynchronous` option is `true`, ensure that the main `code`\n snippet is actually asynchronous. If a snippet releases the zalgo, an\n error complaining about exceeding the maximum call stack size is highly\n likely.\n - While many benchmark frameworks calculate various statistics over raw\n timing results (e.g., mean and standard deviation), do not do this.\n Instead, consider the fastest time an approximate lower bound for how fast\n an environment can execute a snippet. Slower times are more likely\n attributable to other processes interfering with timing accuracy rather\n than attributable to variability in JavaScript's speed. In which case, the\n minimum time is most likely the only result of interest. When considering\n all raw timing results, apply common sense rather than statistics.\n\n Parameters\n ----------\n code: string\n Snippet to time.\n\n options: Object (optional)\n Options.\n\n options.before: string (optional)\n Setup code. Default: `''`.\n\n options.after: string (optional)\n Cleanup code. Default: `''`.\n\n options.iterations: integer|null (optional)\n Number of iterations. If `null`, the number of iterations is determined\n by trying successive powers of `10` until the total time is at least\n `0.1` seconds. Default: `1e6`.\n\n options.repeats: integer (optional)\n Number of repeats. Default: `3`.\n\n options.asynchronous: boolean (optional)\n Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n clbk: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > var code = 'var x = Math.pow( Math.random(), 3 );';\n > code += 'if ( x !== x ) {';\n > code += 'throw new Error( \\'Something went wrong.\\' );';\n > code += '}';\n > function done( error, results ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.dir( results );\n ... };\n > timeit( code, done )\n e.g.,\n {\n \"iterations\": 1000000,\n \"repeats\": 3,\n \"min\": [ 0, 135734733 ], // [seconds,nanoseconds]\n \"elapsed\": 0.135734733, // seconds\n \"rate\": 7367311.062526641, // iterations/second\n \"times\": [ // raw timing results\n [ 0, 145641393 ],\n [ 0, 135734733 ],\n [ 0, 140462721 ]\n ]\n }\n\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n\n Returns\n -------\n dir: string\n Directory for temporary files.\n\n Examples\n --------\n > var dir = tmpdir()\n e.g., '/path/to/temporary/files/directory'\n\n See Also\n --------\n configdir, homedir\n","toc":"\ntoc( time )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n\n Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n Parameters\n ----------\n time: Array\n High-resolution time.\n\n Returns\n -------\n out: Array\n High resolution time difference.\n\n Examples\n --------\n > var start = tic();\n > var delta = toc( start )\n [ , ]\n\n See Also\n --------\n tic\n","tokenize":"\ntokenize( str[, keepWhitespace] )\n Tokenizes a string.\n\n To include whitespace characters (spaces, tabs, line breaks) in the output\n array, set `keepWhitespace` to `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n keepWhitespace: boolean (optional)\n Boolean indicating whether whitespace characters should be returned as\n part of the token array. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of tokens.\n\n Examples\n --------\n > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n > out = tokenize( 'Hello World!', true )\n [ 'Hello', ' ', 'World', '!' ]\n\n","transformStream":"\ntransformStream( [options] )\n Returns a transform stream.\n\n If a transform function is not provided, the returned stream will be a\n simple pass through stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = transformStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n","transformStream.factory":"\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","transformStream.objectMode":"\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();","transformStream.ctor":"\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","trim":"\ntrim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n See Also\n --------\n ltrim, pad, rtrim\n","truncate":"\ntruncate( str, len[, ending] )\n Truncates a string to a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n ending: string (optional)\n Custom ending. Default: '...'.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = truncate( str, 5 )\n 'be...'\n\n > out = truncate( str, 5, '|' )\n 'beep|'\n\n See Also\n --------\n truncateMiddle","truncateMiddle":"\ntruncateMiddle( str, len[, seq] )\n Truncates a string in the middle to a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n seq: string (optional)\n Custom replacement sequence. Default: '...'.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = truncateMiddle( str, 5 )\n 'b...p'\n\n > out = truncateMiddle( str, 5, '|' )\n 'be|op'\n\n See Also\n --------\n truncate","trycatch":"\ntrycatch( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: any\n Value to return if a function throws an error.\n\n Returns\n -------\n z: any\n Either the return value of `x` or the provided argument `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > var z = trycatch( x, -1.0 )\n \n\n See Also\n --------\n trycatchAsync, trythen\n","trycatchAsync":"\ntrycatchAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts two arguments:\n\n - error: error object.\n - result: function result.\n\n The `done` callback is invoked upon function completion and is provided two\n arguments:\n\n - error: error object.\n - result: either the result of `x` or the provided argument `y`.\n\n If `x` invokes `clbk` with an error argument, the function invokes the\n `done` callback with both the error and the argument `y`.\n\n If `x` does not invoke `clbk` with an error argument, the function invokes\n the `done` callback with a first argument equal to `null` and the function\n `result`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: any\n Value to return if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... // process error...\n ... }\n ... console.log( result );\n ... };\n > trycatchAsync( x, 'boop', done )\n 'boop'\n\n See Also\n --------\n trycatch, trythenAsync\n","tryFunction":"\ntryFunction( fcn[, thisArg] )\n Wraps a function in a try/catch block.\n\n If provided an asynchronous function, the returned function only traps\n errors which occur during the current event loop tick.\n\n If a function throws a literal, the literal is serialized as a string and\n returned as an `Error` object.\n\n Parameters\n ----------\n fcn: Function\n Function to wrap.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Wrapped function.\n\n Examples\n --------\n > function fcn() { throw new Error( 'beep boop' ); };\n > var f = tryFunction( fcn );\n > var out = f();\n > out.message\n 'beep boop'\n\n","tryRequire":"\ntryRequire( id )\n Wraps `require` in a `try/catch` block.\n\n This function traps and returns any errors encountered when attempting to\n require a module.\n\n Use caution when attempting to resolve a relative path or a local module.\n This function attempts to resolve a module from its current path. Thus, the\n function is unable to resolve anything which is not along its search path.\n For local requires, use an absolute file path.\n\n Parameters\n ----------\n id: string\n Module id.\n\n Returns\n -------\n out: any|Error\n Resolved module or an `Error`.\n\n Examples\n --------\n > var out = tryRequire( '_unknown_module_id_' )\n \n\n","trythen":"\ntrythen( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n\n The function `y` is provided a single argument:\n\n - error: the error thrown by `x`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: Function\n Function to invoke if an initial function throws an error.\n\n Returns\n -------\n z: any\n The return value of either `x` or `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > function y() {\n ... return -1.0;\n ... };\n > var z = trythen( x, y )\n \n\n See Also\n --------\n trycatch, trythenAsync\n","trythenAsync":"\ntrythenAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the function invokes a `done` callback with\n its first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the function invokes a function `y`. The\n number of arguments provided to `y` depends on the function's length. If `y`\n is a unary function, `y` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n Otherwise, `y` is provided two arguments:\n\n - error: the error from `x`.\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument equal to `null` and all other arguments provided by `y`.\n\n If the error argument is truthy, the `done` callback is invoked with only\n the error argument provided by `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: Function\n Function to invoke if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > trythenAsync( x, y, done )\n 'boop'\n\n See Also\n --------\n trycatchAsync, trythen\n","ttest":"\nttest( x[, y][, options] )\n Computes a one-sample or paired Student's t test.\n\n When no `y` is supplied, the function performs a one-sample t-test for the\n null hypothesis that the data in array or typed array `x` is drawn from a\n normal distribution with mean zero and unknown variance.\n\n When array or typed array `y` is supplied, the function tests whether the\n differences `x - y` come from a normal distribution with mean zero and\n unknown variance via the paired t-test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n y: Array (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed mean under H0 (or difference in means when `y` is supplied).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.mean: number\n Sample mean of `x` or `x - y`, respectively.\n\n out.sd: number\n Standard error of the mean.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample t-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ttest( x )\n {\n rejected: false,\n pValue: ~0.722,\n statistic: ~0.357,\n ci: [~-0.333,~0.479],\n // ...\n }\n\n // Paired t-test:\n > rnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\n > x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... y[ i ] = rnorm();\n ... }\n > out = ttest( x, y )\n {\n rejected: false,\n pValue: ~0.191,\n statistic: ~1.315,\n ci: [ ~-0.196, ~0.964 ],\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.1916\n statistic: 1.3148\n df: 99\n 95% confidence interval: [-0.1955,0.9635]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose custom significance level:\n > var arr = [ 2, 4, 3, 1, 0 ];\n > out = ttest( arr, { 'alpha': 0.01 } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0474\n statistic: 2.8284\n df: 4\n 99% confidence interval: [-1.2556,5.2556]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n // Test for a mean equal to five:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'mu': 5 } )\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~3.758, ~6.242 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'alternative': 'less' } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is less than 0\n\n pValue: 0.9998\n statistic: 11.1803\n df: 4\n 95% confidence interval: [-Infinity,5.9534]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n > out = ttest( arr, { 'alternative': 'greater' } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is greater than 0\n\n pValue: 0.0002\n statistic: 11.1803\n df: 4\n 95% confidence interval: [4.0466,Infinity]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest2\n","ttest2":"\nttest2( x, y[, options] )\n Computes a two-sample Student's t test.\n\n By default, the function performs a two-sample t-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n options.variance: string (optional)\n String indicating if the test should be conducted under the assumption\n that the unknown variances of the normal distributions are `equal` or\n `unequal`. As a default choice, the function carries out the Welch test\n (using the Satterthwaite approximation for the degrees of freedom),\n which does not have the requirement that the variances of the underlying\n distributions are equal. If the equal variances assumption seems\n warranted, set the option to `equal`. Default: `unequal`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Student's sleep data:\n > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n > var out = ttest2( x, y )\n {\n rejected: false,\n pValue: ~0.079,\n statistic: ~-1.861,\n ci: [ ~-3.365, ~0.205 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 95% confidence interval: [-3.3655,0.2055]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ttest2( x, y, { 'alpha': 0.1 } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 90% confidence interval: [-3.0534,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 10% significance level\n\n // Perform one-sided tests:\n > out = ttest2( x, y, { 'alternative': 'less' } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.0397\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-Infinity,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n > out = ttest2( x, y, { 'alternative': 'greater' } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.9603\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-3.0534,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Run tests with equal variances assumption:\n > x = [ 2, 3, 1, 4 ];\n > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n > out = ttest2( x, y, { 'variance': 'equal' } );\n > table = out.print()\n Two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.8848\n statistic: -0.1486\n df: 10\n 95% confidence interval: [-1.9996,1.7496]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 3.0 );\n ... }\n > y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 1.0, 3.0 );\n ... }\n > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n {\n rejected: false,\n pValue: ~0.642,\n statistic: ~-0.466,\n ci: [ ~-0.0455, ~1.646 ],\n // ...\n }\n\n See Also\n --------\n ttest\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > TWO_PI\n 6.283185307179586\n\n See Also\n --------\n PI\n","typedarray":"\ntypedarray( [dtype] )\n Creates a typed array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray()\n \n > arr = typedarray( 'float32' )\n \n\n\ntypedarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = typedarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Complex128Array, Complex64Array, Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","typedarray2json":"\ntypedarray2json( arr )\n Returns a JSON representation of a typed array.\n\n The following typed array types are supported:\n\n - Float64Array\n - Float32Array\n - Int32Array\n - Uint32Array\n - Int16Array\n - Uint16Array\n - Int8Array\n - Uint8Array\n - Uint8ClampedArray\n - Complex64Array\n - Complex128Array\n - BooleanArray\n\n The returned JSON object has the following properties:\n\n - type: typed array type.\n - data: typed array data as a generic array.\n\n The implementation supports custom typed arrays and sets the `type` field to\n the closest known typed array type.\n\n Parameters\n ----------\n arr: TypedArray\n Typed array to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var arr = new Float64Array( 2 );\n > arr[ 0 ] = 5.0;\n > arr[ 1 ] = 3.0;\n > var json = typedarray2json( arr )\n { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n See Also\n --------\n reviveTypedArray\n","typedarrayCtors":"\ntypedarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayCtors( 'float64' )\n \n > ctor = typedarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = typedarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, ndarrayDataTypes\n","typedarraypool":"\ntypedarraypool( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n Memory is **uninitialized**, which means that the contents of a returned\n typed array may contain sensitive contents.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool()\n []\n > arr = typedarraypool( 'float32' )\n []\n\n\ntypedarraypool( length[, dtype] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > arr = typedarraypool( 5, 'int32' )\n \n\n\ntypedarraypool( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n \n\n\ntypedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n \n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []\n\n\ntypedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n\n\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear();\n\n\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n \n\n\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n \n\n\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n typedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n typedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]typedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []typedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]","typedarraypool.free":"\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );","typedarraypool.clear":"\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear();","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n ","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n ","typedarraypool.factory":"\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray","typemax":"\ntypemax( dtype )\n Returns the maximum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var m = typemax( 'int8' )\n 127\n > m = typemax( 'uint32' )\n 4294967295\n\n See Also\n --------\n realmax, typemin\n","typemin":"\ntypemin( dtype )\n Returns the minimum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var m = typemin( 'int8' )\n -128\n > m = typemin( 'uint32' )\n 0\n\n See Also\n --------\n realmin, typemax\n","typeOf":"\ntypeOf( value )\n Determines a value's type.\n\n The following values are not natively provided in older JavaScript engines:\n\n - Map\n - Set\n - WeakMap\n - WeakSet\n - Symbol\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n The value's type.\n\n Examples\n --------\n // Built-ins:\n > var t = typeOf( 'a' )\n 'string'\n > t = typeOf( 5 )\n 'number'\n > t = typeOf( NaN )\n 'number'\n > t = typeOf( true )\n 'boolean'\n > t = typeOf( false )\n 'boolean'\n > t = typeOf( null )\n 'null'\n > t = typeOf( undefined )\n 'undefined'\n > t = typeOf( [] )\n 'array'\n > t = typeOf( {} )\n 'object'\n > t = typeOf( function noop() {} )\n 'function'\n > t = typeOf( Symbol( 'beep' ) )\n 'symbol'\n > t = typeOf( /.+/ )\n 'regexp'\n > t = typeOf( new String( 'beep' ) )\n 'string'\n > t = typeOf( new Number( 5 ) )\n 'number'\n > t = typeOf( new Boolean( false ) )\n 'boolean'\n > t = typeOf( new Array() )\n 'array'\n > t = typeOf( new Object() )\n 'object'\n > t = typeOf( new Int8Array( 10 ) )\n 'int8array'\n > t = typeOf( new Uint8Array( 10 ) )\n 'uint8array'\n > t = typeOf( new Uint8ClampedArray( 10 ) )\n 'uint8clampedarray'\n > t = typeOf( new Int16Array( 10 ) )\n 'int16array'\n > t = typeOf( new Uint16Array( 10 ) )\n 'uint16array'\n > t = typeOf( new Int32Array( 10 ) )\n 'int32array'\n > t = typeOf( new Uint32Array( 10 ) )\n 'uint32array'\n > t = typeOf( new Float32Array( 10 ) )\n 'float32array'\n > t = typeOf( new Float64Array( 10 ) )\n 'float64array'\n > t = typeOf( new ArrayBuffer( 10 ) )\n 'arraybuffer'\n > t = typeOf( new Date() )\n 'date'\n > t = typeOf( new RegExp( '.+' ) )\n 'regexp'\n > t = typeOf( new Map() )\n 'map'\n > t = typeOf( new Set() )\n 'set'\n > t = typeOf( new WeakMap() )\n 'weakmap'\n > t = typeOf( new WeakSet() )\n 'weakset'\n > t = typeOf( new Error( 'beep' ) )\n 'error'\n > t = typeOf( new TypeError( 'beep' ) )\n 'typeerror'\n > t = typeOf( new SyntaxError( 'beep' ) )\n 'syntaxerror'\n > t = typeOf( new ReferenceError( 'beep' ) )\n 'referenceerror'\n > t = typeOf( new URIError( 'beep' ) )\n 'urierror'\n > t = typeOf( new RangeError( 'beep' ) )\n 'rangeerror'\n > t = typeOf( new EvalError( 'beep' ) )\n 'evalerror'\n > t = typeOf( Math )\n 'math'\n > t = typeOf( JSON )\n 'json'\n\n // Arguments object:\n > function beep() { return arguments; };\n > t = typeOf( beep() )\n 'arguments'\n\n // Node.js Buffer object:\n > t = typeOf( new Buffer( 10 ) )\n 'buffer'\n\n // Custom constructor:\n > function Person() { return this };\n > t = typeOf( new Person() )\n 'person'\n\n // Anonymous constructor:\n > var Foo = function () { return this; };\n > t = typeOf( new Foo() )\n '' || 'foo'\n\n See Also\n --------\n constructorName, nativeClass\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n\n The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n Examples\n --------\n > UINT8_MAX\n 255\n\n See Also\n --------\n INT8_MAX\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n\n Examples\n --------\n > UINT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT8_NUM_BYTES, UINT16_NUM_BYTES, UINT32_NUM_BYTES\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array()\n \n\n\nUint8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'\n\n\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n \n\n\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5\n\n\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray\n","Uint8Array.from":"\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint8Array.of":"\nUint8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1","Uint8Array.name":"\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n ","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray()\n \n\n\nUint8ClampedArray( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8ClampedArray( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n \n\n\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5\n\n\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns an empty array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n ","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns an empty array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n\n The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n Examples\n --------\n > UINT16_MAX\n 65535\n\n See Also\n --------\n INT16_MAX\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n\n Examples\n --------\n > UINT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT16_NUM_BYTES, UINT32_NUM_BYTES, UINT8_NUM_BYTES\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array()\n \n\n\nUint16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Uint16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'\n\n\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n \n\n\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10\n\n\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Uint16Array.from":"\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint16Array.of":"\nUint16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2","Uint16Array.name":"\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n ","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n\n The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n Examples\n --------\n > UINT32_MAX\n 4294967295\n\n See Also\n --------\n INT32_MAX\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n\n Examples\n --------\n > UINT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT32_NUM_BYTES, UINT16_NUM_BYTES, UINT8_NUM_BYTES\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array()\n \n\n\nUint32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Uint32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'\n\n\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n \n\n\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20\n\n\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray\n","Uint32Array.from":"\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint32Array.of":"\nUint32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4","Uint32Array.name":"\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n ","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray","umask":"\numask( [mask,] [options] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n\n A mask is a set of bits, each of which restricts how its corresponding\n permission is set for newly created files.\n\n On POSIX platforms, each file has a set of attributes that control who can\n read, write, or execute that file. Upon creating a file, file permissions\n must be set to an initial setting. The process mask restricts those\n permission settings.\n\n If the mask contains a bit set to \"1\", the corresponding initial file\n permission is disabled. If the mask contains a bit set to \"0\", the\n corresponding permission is left to be determined by the requesting process\n and the system.\n\n The process mask is thus a filter that removes permissions as a file is\n created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n In octal representation, a mask is a four digit number, e.g., 0077,\n comprised as follows:\n\n - 0: special permissions (setuid, setgid, sticky bit)\n - 0: (u)ser/owner permissions\n - 7: (g)roup permissions\n - 7: (o)thers/non-group permissions\n\n Octal codes correspond to the following permissions:\n\n - 0: read, write, execute\n - 1: read, write\n - 2: read, execute\n - 3: read\n - 4: write, execute\n - 5: write\n - 6: execute\n - 7: no permissions\n\n If provided fewer than four digits, the mask is left-padded with zeros.\n\n Note, however, that only the last three digits (i.e., the file permissions\n digits) of the mask are actually used when the mask is applied.\n\n Permissions can be represented using the following symbolic form:\n\n u=rwx,g=rwx,o=rwx\n\n where\n\n - u: user permissions\n - g: group permissions\n - o: other/non-group permissions\n - r: read\n - w: write\n - x: execute\n\n When setting permissions using symbolic notation, the function accepts a\n mask expression of the form:\n\n []\n\n where \"classes\" may be a combination of\n\n - u: user\n - g: group\n - o: other/non-group\n - a: all\n\n \"symbols\" may be a combination of\n\n - r: read\n - w: write\n - x: execute\n - X: special execute\n - s: setuid/gid on execution\n - t: sticky\n\n and \"operator\" may be one of\n\n - +: enable\n - -: disable\n - =: enable specified and disable unspecified permissions\n\n For example,\n\n - u-w: disable user write permissions\n - u+w: enable user write permissions\n - u=w: enable user write permissions and disable user read and execute\n\n To specify multiple changes, provide a comma-separated list of mask\n expressions. For example,\n\n u+rwx,g-x,o=r\n\n would enable user read, write, and execute permissions, disable group\n execute permissions, enable other read permissions, and disable other\n write and execute permissions.\n\n The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n is the default class if a class is omitted when specifying permissions. For\n example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n Parameters\n ----------\n mask: integer|string (optional)\n Mask or mask expression. If the mask is a string, the mask is assumed to\n be in symbolic notation.\n\n options: Object (optional)\n Options.\n\n options.symbolic: boolean (optional)\n Boolean indicating whether to return the mask using symbolic notation.\n\n Returns\n -------\n mask: integer|string\n Process mask. If provided a mask, the returned value is the previous\n mask; otherwise, the returned value is the current process mask.\n\n Examples\n --------\n > var mask = umask()\n \n > mask = umask( { 'symbolic': true } )\n \n\n","uncapitalize":"\nuncapitalize( str )\n Lowercases the first character of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = uncapitalize( 'Beep' )\n 'beep'\n > out = uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n capitalize, lowercase\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj )\n Converts the first letter of each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'AA': 1, 'BB': 2 };\n > var out = uncapitalizeKeys( obj )\n { 'aA': 1, 'bB': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","uncurry":"\nuncurry( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurry( addX );\n > var sum = fcn( 2, 3 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( x ) {\n ... return function add( y ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurry( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addX( x ) {\n ... this.x = x;\n ... return addY;\n ... };\n > function addY( y ) {\n ... return this.x + y;\n ... };\n > fcn = uncurry( addX, {} );\n > sum = fcn( 2, 3 )\n 5\n\n See Also\n --------\n curry, uncurryRight\n","uncurryRight":"\nuncurryRight( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Provided arguments are applied starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurryRight( addX );\n > var sum = fcn( 3, 2 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( y ) {\n ... return function add( x ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurryRight( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addY( y ) {\n ... this.y = y;\n ... return addX;\n ... };\n > function addX( x ) {\n ... return x + this.y;\n ... };\n > fcn = uncurryRight( addY, {} );\n > sum = fcn( 3, 2 )\n 5\n\n See Also\n --------\n curry, curryRight, uncurry\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n\n Examples\n --------\n > UNICODE_MAX\n 1114111\n\n See Also\n --------\n UNICODE_MAX_BMP\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n Examples\n --------\n > UNICODE_MAX_BMP\n 65535\n\n See Also\n --------\n UNICODE_MAX\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data,] [options] )\n Returns a sparkline column chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeColumnChartSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data,] [options] )\n Returns a sparkline line chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: LineChart\n Line chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a line chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeLineChartSparkline( data );\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeSparkline":"\nUnicodeSparkline( [data,] [options] )\n Returns a Unicode sparkline instance.\n\n The following chart types are supported:\n\n - column: column chart (e.g., ▃▆▂▄▁▅▅).\n - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.type: string (optional)\n Chart type. Default: 'column'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.type\n Chart type.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n > chart.type = 'line';\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data,] [options] )\n Returns a sparkline tristate chart instance.\n\n In a tristate chart, negative values are encoded as lower blocks, positive\n values are encoded as upper blocks, and values equal to zero are encoded as\n middle lines.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: TristateChart\n Tristate chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a tristate chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n > var chart = new UnicodeTristateChartSparkline( data );\n > chart.render()\n '▄▀──▀▄▄▀'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data,] [options] )\n Returns a sparkline up/down chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ↑ |\n | -1 | ↓ |\n\n If provided any other value other than 1 or -1, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: UpDownChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1 or -1.\n\n chart.render()\n Renders an up/down chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n > var chart = new UnicodeUpDownChartSparkline( data );\n > chart.render()\n '↓↑↑↑↑↓↓↑'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data,] [options] )\n Returns a sparkline win/loss chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ╵ |\n | -1 | ╷ |\n | 2 | └ |\n | -2 | ┌ |\n\n If a `2` or `-2` is preceded by a `2` or `-2`,\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 2 | ┴ |\n | -2 | ┬ |\n\n Based on the win/loss analogy,\n\n - 1: win away\n - 2: win at home\n - -1: loss away\n - -2: loss at home\n\n If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: WinLossChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n chart.render()\n Renders a win/loss chart sparkline.\n\n Examples\n --------\n > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n > var chart = new UnicodeWinLossChartSparkline( data );\n > chart.render()\n '┌╵└┴╵╷╷╵'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline\n","unlink":"\nunlink( path, clbk )\n Asynchronously removes a directory entry.\n\n If a provided path is a symbolic link, the function removes the symbolic\n link named by the path and does not affect any file or directory named by\n the contents of the symbolic link.\n\n Otherwise, the function removes the link named by the provided path and\n decrements the link count of the file referenced by the link.\n\n When a file's link count becomes 0 and no process has the file open, the\n space occupied by the file is freed and the file is no longer accessible.\n\n If one or more processes have the file open when the last link is removed,\n the link is removed before the function returns; however, the removal of\n file contents is postponed until all references to the file are closed.\n\n If the path refers to a socket, FIFO, or device, processes which have the\n object open may continue to use it.\n\n The path argument should *not* be a directory. To remove a directory, use\n rmdir().\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n clbk: Function\n Callback to invoke upon removing an entry.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists\n","unlink.sync":"\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists","unshift":"\nunshift( collection, ...items )\n Adds one or more elements to the beginning of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = unshift( arr, 6.0, 7.0 )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = unshift( arr, 3.0, 4.0 )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = unshift( arr, 2.0, 3.0 )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n pop, push, shift\n","until":"\nuntil( predicate, fcn[, thisArg] )\n Invokes a function until a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > until( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, untilAsync, untilEach, whilst\n","untilAsync":"\nuntilAsync( predicate, fcn, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from zero).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is falsy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > untilAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, until, whileAsync\n","untilEach":"\nuntilEach( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > untilEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEachRight, whileEach\n","untilEachRight":"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > untilEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n untilEach, whileEachRight\n","unzip":"\nunzip( arr[, idx] )\n Unzips a zipped array (i.e., a nested array of tuples).\n\n Parameters\n ----------\n arr: Array\n Zipped array.\n\n idx: Array (optional)\n Array of indices specifying which tuple elements to unzip.\n\n Returns\n -------\n out: Array\n Array of unzipped arrays.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > var out = unzip( arr )\n [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n // Provide indices:\n > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > out = unzip( arr, [ 0, 2 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n zip\n","uppercase":"\nuppercase( str )\n Converts a string to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n capitalize, lowercase\n","uppercaseKeys":"\nuppercaseKeys( obj )\n Converts each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'a': 1, 'b': 2 };\n > var out = uppercaseKeys( obj )\n { 'A': 1, 'B': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n\n Returns\n -------\n out: Array\n List of US state two-letter abbreviations.\n\n Examples\n --------\n > var list = US_STATES_ABBR()\n [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n\n Returns\n -------\n out: Array\n List of US state capitals.\n\n Examples\n --------\n > var list = US_STATES_CAPITALS()\n [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS_NAMES, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n\n Returns\n -------\n out: Object\n An object mapping US state capitals to state names.\n\n Examples\n --------\n > var out = US_STATES_CAPITALS_NAMES()\n { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n\n Returns\n -------\n out: Array\n List of US state names.\n\n Examples\n --------\n > var list = US_STATES_NAMES()\n [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS, US_STATES_CAPITALS_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n\n Returns\n -------\n out: Object\n An object mapping US state names to state capitals.\n\n Examples\n --------\n > var out = US_STATES_NAMES_CAPITALS()\n { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n\n The following byte sequences are used to represent a character. The sequence\n depends on the code point:\n\n 0x00000000 - 0x0000007F:\n 0xxxxxxx\n\n 0x00000080 - 0x000007FF:\n 110xxxxx 10xxxxxx\n\n 0x00000800 - 0x0000FFFF:\n 1110xxxx 10xxxxxx 10xxxxxx\n\n 0x00010000 - 0x001FFFFF:\n 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n The `x` bit positions correspond to code point bits.\n\n Only the shortest possible multi-byte sequence which can represent a code\n point is used.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: Array\n Array of integers.\n\n Examples\n --------\n > var str = '☃';\n > var out = utf16ToUTF8Array( str )\n [ 226, 152, 131 ]\n\n","vartest":"\nvartest( x, y[, options] )\n Computes a two-sample F-test for equal variances.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`.\n\n options.ratio: number (optional)\n Positive number denoting the ratio of the two population variances under\n the null hypothesis. Default: `1`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the ratio of variances.\n\n out.nullValue: number\n Assumed ratio of variances under H0.\n\n out.xvar: number\n Sample variance of `x`.\n\n out.yvar: number\n Sample variance of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.dfX: number\n Numerator degrees of freedom.\n\n out.dfY: number\n Denominator degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [ 610, 610, 550, 590, 565, 570 ];\n > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n > var out = vartest( x, y )\n {\n rejected: false,\n pValue: ~0.399,\n statistic: ~1.976,\n ci: [ ~0.374, ~13.542 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n F test for comparing two variances\n\n Alternative hypothesis: True ratio in variances is not equal to 1\n\n pValue: 0.3992\n statistic: 1.976\n variance of x: 617.5 (df of x: 5)\n variance of y: 312.5 (df of y: 7)\n 95% confidence interval: [0.3739,13.5417]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n See Also\n --------\n bartlettTest\n","waterfall":"\nwaterfall( fcns, clbk[, thisArg] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n\n The last argument applied to each waterfall function is a callback. The\n callback should be invoked upon a series function completion. The first\n argument is reserved as an error argument (which can be `null`). Any results\n which should be passed to the next function in the series should be provided\n beginning with the second argument.\n\n If any function calls the provided callback with a truthy `error` argument,\n the waterfall suspends execution and immediately calls the completion\n callback for subsequent error handling.\n\n Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n the completion callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();\n\n","waterfall.factory":"\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor )\n WebAssembly memory constructor.\n\n Parameters\n ----------\n descriptor: Object\n Memory descriptor object.\n\n descriptor.initial: integer\n Initial memory size in units of WebAssembly pages (i.e., 64KiB).\n\n descriptor.maximum: integer (optional)\n Maximum memory size in units of WebAssembly pages (i.e., 64KiB).\n\n descriptor.shared: boolean (optional)\n Boolean indicating whether the memory is shared. Default: false.\n\n Returns\n -------\n out: Memory\n WebAssembly memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } )\n \n\n\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.buffer\n \n\n\nWebAssemblyMemory.prototype.grow( delta )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n\n Upon increasing the size, the previous ArrayBuffer is detached, thus\n invalidating any typed arrays which were views over the previous\n ArrayBuffer.\n\n Detachment means that the previous ArrayBuffer byte length becomes zero, and\n it no longer has bytes accessible to JavaScript.\n\n ArrayBuffer detachment applies even when `delta` is zero.\n\n Detachment only applies for non-shared memory instances. For a shared memory\n instance, the initial buffer (which is a SharedArrayBuffer) will not become\n detached and, instead, its length will not be updated.\n\n Accesses to the `buffer` property after growing a SharedArrayBuffer will\n yield a larger SharedArrayBuffer which may access a larger span of memory\n than the buffer before growing memory.\n\n Every SharedArrayBuffer accessed via the `buffer` property will always refer\n to the start of the same memory address range and thus manipulate the same\n data.\n\n Parameters\n ----------\n delta: integer\n Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n underlying memory.\n\n Returns\n -------\n out: integer\n Size of the previous memory (in units of pages).\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.grow( 1 )\n \n\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.buffer\n ","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n\n Upon increasing the size, the previous ArrayBuffer is detached, thus\n invalidating any typed arrays which were views over the previous\n ArrayBuffer.\n\n Detachment means that the previous ArrayBuffer byte length becomes zero, and\n it no longer has bytes accessible to JavaScript.\n\n ArrayBuffer detachment applies even when `delta` is zero.\n\n Detachment only applies for non-shared memory instances. For a shared memory\n instance, the initial buffer (which is a SharedArrayBuffer) will not become\n detached and, instead, its length will not be updated.\n\n Accesses to the `buffer` property after growing a SharedArrayBuffer will\n yield a larger SharedArrayBuffer which may access a larger span of memory\n than the buffer before growing memory.\n\n Every SharedArrayBuffer accessed via the `buffer` property will always refer\n to the start of the same memory address range and thus manipulate the same\n data.\n\n Parameters\n ----------\n delta: integer\n Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n underlying memory.\n\n Returns\n -------\n out: integer\n Size of the previous memory (in units of pages).\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.grow( 1 )\n ","whileAsync":"\nwhileAsync( predicate, fcn, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from zero).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is truthy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > whileAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, untilAsync, whilst\n","whileEach":"\nwhileEach( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > whileEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEach, whileEachRight\n","whileEachRight":"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > whileEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n whileEach, untilEachRight\n","whilst":"\nwhilst( predicate, fcn[, thisArg] )\n Invokes a function while a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > whilst( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, until, whileAsync, whileEach\n","wilcoxon":"\nwilcoxon( x[, y][, options] )\n Computes a one-sample or paired Wilcoxon signed rank test.\n\n When no `y` is supplied, the function performs a one-sample Wilcoxon signed\n rank test for the null hypothesis that the data is drawn from a symmetric\n distribution around zero.\n\n When `y` is supplied, the function tests whether the\n differences `x - y` come from a symmetric distribution around zero.\n\n If `x` has less than fifty elements, an exact p-value is computed if there\n are no zero values or ties. Otherwise, a normal approximation is used.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array|TypedArray\n Data array.\n\n y: Array|TypedArray (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`), or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.correction: boolean (optional)\n Determines whether to apply continuity correction adjusting the Wilcoxon\n rank statistic by 0.5 towards the mean when using the normal\n approximation. Default: `true`.\n\n options.exact: boolean (optional)\n Determines whether to force use of the exact distribution instead of a\n normal approximation when there are more than fifty data points.\n Default: `false`.\n\n options.mu: number (optional)\n Hypothesized true location under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n options.zeroMethod: string (optional)\n Method governing how zero-differences are handled (`pratt`, `wilcox`, or\n `zsplit`). When set to `pratt`, differences of zero are used to\n calculate ranks but their ranks are then dropped. When set to `wilcox`,\n all zero-differences are discarded. When set to `zsplit`, differences of\n zero are used to rank and their ranks are then split between positive\n and negative ones. Default: `'wilcox'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.nullValue: number\n Assumed location parameter under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample test:\n > var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\n > var out = wilcoxon( x )\n {\n 'rejected': true,\n 'alpha': 0.05,\n 'pValue': 0.04125976562499978,\n 'statistic': 96\n // ...\n }\n\n // Paired test:\n > runif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\n > var x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = runif();\n ... y[ i ] = runif();\n ... }\n > out = wilcoxon( x, y )\n {\n 'rejected': false,\n 'alpha': 0.05,\n 'pValue': 0.21759090963694638,\n 'statistic': 2702.5,\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired Wilcoxon signed rank test\n\n Alternative hypothesis: Median of the difference `x - y` is not equal to 0\n\n pValue: 0.2176\n statistic: 2702.5\n\n Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n // Choose custom significance level:\n > out = wilcoxon( arr, { 'alpha': 0.01 });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is not equal to 0\n\n pValue: 0.0413\n statistic: 96\n\n Test Decision: Fail to reject null in favor of alternative at 1% significance level\n\n\n // Test for a median equal to ten:\n > out = wilcoxon( arr, { 'mu': 10 })\n {\n 'rejected': false,\n 'alpha': 0.05,\n 'pValue': 0.11169650413134602,\n 'statistic': 88.5,\n 'nullValue': 10,\n // ...\n }\n\n // Perform one-sided tests:\n > out = wilcoxon( arr, { 'alternative': 'less' });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is less than 0\n\n pValue: 0.9823\n statistic: 96\n\n Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n > out = wilcoxon( arr, { 'alternative': 'greater' });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is greater than 0\n\n pValue: 0.0206\n statistic: 96\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest, ztest\n","writableProperties":"\nwritableProperties( value )\n Returns an array of an object's own writable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own writable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = writableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n inheritedWritableProperties, writablePropertiesIn, properties\n","writablePropertiesIn":"\nwritablePropertiesIn( value )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited writable property names and\n symbols.\n\n Examples\n --------\n > var props = writablePropertiesIn( [] )\n\n See Also\n --------\n inheritedWritableProperties, writableProperties, propertiesIn\n","writablePropertyNames":"\nwritablePropertyNames( value )\n Returns an array of an object's own writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNames( obj )\n [ 'a' ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writableProperties, writablePropertyNamesIn, writablePropertySymbols, propertyNames\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value )\n Returns an array of an object's own and inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNamesIn( obj )\n e.g., [ 'a', ... ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertiesIn, writablePropertyNames, writablePropertySymbolsIn, propertyNamesIn\n","writablePropertySymbols":"\nwritablePropertySymbols( value )\n Returns an array of an object's own writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbols( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writableProperties, writablePropertyNames, writablePropertySymbolsIn, propertySymbols\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited writable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbolsIn( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertiesIn, writablePropertyNamesIn, writablePropertySymbols, propertySymbolsIn\n","writeFile":"\nwriteFile( file, data[, options], clbk )\n Asynchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon writing data to a file.\n\n Examples\n --------\n > function onWrite( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile\n","writeFile.sync":"\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile","zip":"\nzip( ...arr[, options] )\n Generates array tuples from input arrays.\n\n Parameters\n ----------\n arr: ...Array\n Input arrays to be zipped.\n\n options: Object (optional)\n Options.\n\n options.trunc: boolean (optional)\n Boolean indicating whether to truncate arrays longer than the shortest\n input array. Default: `true`.\n\n options.fill: any (optional)\n Fill value used for arrays of unequal length. Default: `null`.\n\n options.arrays: boolean (optional)\n Boolean indicating whether an input array should be interpreted as an\n array of arrays to be zipped. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n // Basic usage:\n > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n // Turn off truncation:\n > var opts = { 'trunc': false };\n > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n See Also\n --------\n unzip\n","ztest":"\nztest( x, sigma[, options] )\n Computes a one-sample z-test.\n\n The function performs a one-sample z-test for the null hypothesis that the\n data in array or typed array `x` is drawn from a normal distribution with\n mean zero and standard deviation `sigma`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n sigma: number\n Known standard deviation.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for mean.\n\n out.nullValue: number\n Assumed mean value under H0.\n\n out.sd: number\n Standard error.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test (`One-Sample z-test`).\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample z-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ztest( x, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.180,\n statistic: ~-1.34,\n ci: [ ~-0.66, ~0.124 ],\n ...\n }\n\n // Choose custom significance level and print output:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ztest( arr, 2.0, { 'alpha': 0.01 } );\n > table = out.print()\n One-sample z-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0253\n statistic: 2.2361\n 99% confidence interval: [-0.3039,4.3039]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'mu': 5 } )\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~4.123, ~5.877 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'alternative': 'less' } )\n {\n alpha: 0.05,\n rejected: false,\n pValue: 1,\n statistic: 11.180339887498949,\n ci: [ -Infinity, 5.735600904580115 ],\n // ...\n }\n > out = ztest( arr, 1.0, { 'alternative': 'greater' } )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 11.180339887498949,\n ci: [ 4.264399095419885, Infinity ],\n //...\n }\n\n See Also\n --------\n ztest2\n","ztest2":"\nztest2( x, y, sigmax, sigmay[, options] )\n Computes a two-sample z-test.\n\n By default, the function performs a two-sample z-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means and known\n standard deviations `sigmax` and `sigmay`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n sigmax: number\n Known standard deviation of first group.\n\n sigmay: number\n Known standard deviation of second group.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Drawn from Normal(0,2):\n > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n // Drawn from Normal(1,2):\n > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n > var out = ztest2( x, y, 2.0, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.398,\n statistic: ~-0.844\n ci: [ ~-2.508, ~0.988 ],\n alternative: 'two-sided',\n method: 'Two-sample z-test',\n nullValue: 0,\n xmean: ~0.573,\n ymean: ~1.328\n }\n\n // Print table output:\n > var table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 95% confidence interval: [-2.508,0.998]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 60% confidence interval: [-1.5078,-0.0022]\n\n Test Decision: Reject null in favor of alternative at 40% significance level\n\n // Perform one-sided tests:\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.1993\n statistic: -0.8441\n 95% confidence interval: [-Infinity,0.7162]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.8007\n statistic: -0.8441\n 95% confidence interval: [-2.2262,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 1.0 );\n ... }\n > y = new Array( 100 );\n ... for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 0.0, 2.0 );\n ... }\n > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n {\n rejected: false,\n pValue: ~0.35,\n statistic: ~-0.935\n ci: [ ~1.353, ~2.229 ],\n // ...\n }\n\n See Also\n --------\n ztest\n"} +{"abs":"\nabs( x[, options] )\n Computes the absolute value for each element in an ndarray.\n\n The function returns an ndarray having the same shape as the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array. Must have a numeric or \"generic\" data type.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Output array data type. Must be a real-valued or \"generic\" data type.\n\n options.order: string (optional)\n Output array order. Must be either row-major (C-style) or column-major\n (Fortran-style). By default, the order of the output array is the same\n as the input array.\n\n Returns\n -------\n y: ndarray\n Output array containing element-wise results.\n\n Examples\n --------\n > var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\n > var x = array( arr );\n > var y = abs( x )\n [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]\n\n\nabs.assign( x, y )\n Computes the absolute value for each element in an ndarray and assigns\n results to a provided output ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array. Must have a numeric or \"generic\" data type.\n\n y: ndarray\n Output array.\n\n Returns\n -------\n y: ndarray\n Output array.\n\n Examples\n --------\n > var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\n > var x = array( arr );\n > var sh = ndarrayShape( x );\n > var y = ndzeros( sh );\n > var out = abs.assign( x, y )\n [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]\n > var bool = ( out === y )\n true\n\n","abs.assign":"\nabs.assign( x, y )\n Computes the absolute value for each element in an ndarray and assigns\n results to a provided output ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array. Must have a numeric or \"generic\" data type.\n\n y: ndarray\n Output array.\n\n Returns\n -------\n y: ndarray\n Output array.\n\n Examples\n --------\n > var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\n > var x = array( arr );\n > var sh = ndarrayShape( x );\n > var y = ndzeros( sh );\n > var out = abs.assign( x, y )\n [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]\n > var bool = ( out === y )\n true","acartesianPower":"\nacartesianPower( x, n )\n Returns the Cartesian power.\n\n If provided an empty array, the function returns an empty array.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n n: integer\n Power.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = acartesianPower( x, 2 )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianProduct, acartesianSquare\n","acartesianProduct":"\nacartesianProduct( x1, x2 )\n Returns the Cartesian product.\n\n If provided one or more empty arrays, the function returns an empty array.\n\n Parameters\n ----------\n x1: ArrayLikeObject\n First input array.\n\n x2: ArrayLikeObject\n Second input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x1 = [ 1, 2 ];\n > var x2 = [ 3, 4 ];\n > var out = acartesianProduct( x1, x2 )\n [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n See Also\n --------\n acartesianPower, acartesianSquare\n","acartesianSquare":"\nacartesianSquare( x )\n Returns the Cartesian square.\n\n If provided an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var out = acartesianSquare( [ 1, 2 ] )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianPower, acartesianProduct\n","acronym":"\nacronym( str[, options] )\n Generates an acronym for a given string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n options: Object (optional)\n Options.\n\n options.stopwords: Array (optional)\n Array of custom stop words.\n\n Returns\n -------\n out: string\n Acronym for the given string.\n\n Examples\n --------\n > var out = acronym( 'the quick brown fox' )\n 'QBF'\n > out = acronym( 'Hard-boiled eggs' )\n 'HBE'\n","aempty":"\naempty( length[, dtype] )\n Creates an uninitialized array having a specified length.\n\n In browser environments, the function always returns zero-filled arrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled array.\n\n In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n is *not* initialized. Memory contents are unknown and may contain\n *sensitive* data.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aempty( 2 )\n \n > arr = aempty( 2, 'float32' )\n \n\n See Also\n --------\n aemptyLike, afull, aones, azeros, ndempty\n","aemptyLike":"\naemptyLike( x[, dtype] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n\n In browser environments, the function always returns zero-filled arrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled array.\n\n In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n is *not* initialized. Memory contents are unknown and may contain\n *sensitive* data.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var arr = aemptyLike( x )\n \n > arr = aemptyLike( x, 'float32' )\n \n\n See Also\n --------\n aempty, afullLike, aonesLike, azerosLike, ndemptyLike\n","AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_111\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_96\n","afull":"\nafull( length, value[, dtype] )\n Returns a filled array having a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n value: any\n Fill value.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = afull( 2, 1.0 )\n [ 1.0, 1.0 ]\n > arr = afull( 2, 1.0, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afullLike, aones, azeros\n","afullLike":"\nafullLike( x[, dtype] )\n Returns a filled array having the same length and data type as a provided\n input array.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = afullLike( x, 1.0 )\n [ 1.0, 1.0 ]\n > y = afullLike( x, 1.0, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afull, aonesLike, azerosLike\n","alias2pkg":"\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","alias2related":"\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( 'base.sin' )\n [...]\n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","alias2standalone":"\nalias2standalone( alias )\n Returns the standalone package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Standalone package name.\n\n Examples\n --------\n > var v = alias2standalone( 'base.sin' )\n '@stdlib/math-base-special-sin'\n\n See Also\n --------\n alias2pkg, alias2related, aliases, pkg2alias, pkg2standalone\n","aliases":"\naliases( [namespace] )\n Returns a list of standard library aliases.\n\n Parameters\n ----------\n namespace: string (optional)\n Namespace filter.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n > o = aliases( '@stdlib/math/base/special' )\n [...]\n\n See Also\n --------\n alias2pkg, alias2related, pkg2alias\n","allocUnsafe":"\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","amskfilter":"\namskfilter( x, mask )\n Returns a new array by applying a mask to a provided input array.\n\n If a mask array element is truthy, the corresponding element in `x` is\n included in the output array; otherwise, the corresponding element in `x` is\n \"masked\" and thus excluded from the output array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n mask: Array|TypedArray|Object\n Mask array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = amskfilter( x, [ 0, 1, 0, 1 ] )\n [ 2, 4 ]\n\n See Also\n --------\n amskreject\n","amskput":"\namskput( x, mask, values[, options] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n\n In broadcasting modes, the function supports broadcasting a values array\n containing a single element against the number of falsy values in the mask\n array.\n\n In repeat mode, the function supports recycling elements in a values array\n to satisfy the number of falsy values in the mask array.\n\n The function mutates the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n mask: ArrayLikeObject\n Mask array. If a mask array element is falsy, the corresponding element\n in `x` is *replaced*; otherwise, the corresponding element in `x` is\n \"masked\" and thus left unchanged.\n\n values: ArrayLikeObject\n Values to set.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n String specifying behavior when the number of values to set does not\n equal the number of falsy mask values. The function supports the\n following modes:\n\n - 'strict': specifies that the function must raise an exception when the\n number of values does not *exactly* equal the number of falsy mask\n values.\n - 'non_strict': specifies that the function must raise an exception when\n the function is provided insufficient values to satisfy the mask array.\n - 'strict_broadcast': specifies that the function must broadcast a\n single-element values array and otherwise raise an exception when the\n number of values does not **exactly** equal the number of falsy mask\n values.\n - 'broadcast': specifies that the function must broadcast a single-\n element values array and otherwise raise an exception when the function\n is provided insufficient values to satisfy the mask array.\n - 'repeat': specifies that the function must reuse provided values when\n replacing elements in `x` in order to satisfy the mask array.\n\n Default: 'repeat'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n aplace, aput, atake\n","amskreject":"\namskreject( x, mask )\n Returns a new array by applying a mask to a provided input array.\n\n If a mask array element is falsy, the corresponding element in `x` is\n included in the output array; otherwise, the corresponding element in `x` is\n \"masked\" and thus excluded from the output array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n mask: Array|TypedArray|Object\n Mask array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = amskreject( x, [ 0, 1, 0, 1 ] )\n [ 1, 3 ]\n\n See Also\n --------\n amskfilter\n","anans":"\nanans( length[, dtype] )\n Returns an array filled with NaNs and having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = anans( 2 )\n [ NaN, NaN ]\n > arr = anans( 2, 'float32' )\n [ NaN, NaN ]\n\n See Also\n --------\n afull, anansLike, aones, azeros\n","anansLike":"\nanansLike( x[, dtype] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = anansLike( x )\n [ NaN, NaN ]\n > y = anansLike( x, 'float32' )\n [ NaN, NaN ]\n\n See Also\n --------\n afullLike, anans, aonesLike, azerosLike\n","anova1":"\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatment: Object\n Treatment results.\n\n out.treatment.df: number\n Treatment degrees of freedom.\n\n out.treatment.ss: number\n Treatment sum of squares.\n\n out.treatment.ms: number\n Treatment mean sum of squares.\n\n out.error: Object\n Error results.\n\n out.error.df: number\n Error degrees of freedom.\n\n out.error.ss: number\n Error sum of squares.\n\n out.error.ms: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n","any":"\nany( collection )\n Tests whether at least one element in a collection is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an element is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 1 ];\n > var bool = any( arr )\n true\n\n See Also\n --------\n anyBy, every, forEach, none, some\n","anyBy":"\nanyBy( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4, -1 ];\n > var bool = anyBy( arr, negative )\n true\n\n See Also\n --------\n anyByAsync, anyByRight, everyBy, forEach, noneBy, someBy\n","anyByAsync":"\nanyByAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync\n","anyByAsync.factory":"\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync","anyByRight":"\nanyByRight( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, 2, 3, 4 ];\n > var bool = anyByRight( arr, negative )\n true\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByRight, forEachRight, noneByRight, someByRight\n","anyByRightAsync":"\nanyByRightAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync","anyInBy":"\nanyInBy( object, predicate[, thisArg ] )\n Tests whether at least one value in an object passes a test implemented by\n a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: the value of the current property being processed in the object\n - key: the key of the current property being processed in the object\n - object: the input object\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate. It must be non-null.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any value; otherwise, it returns `false`.\n\n Examples\n --------\n > function isNegative(value) { return value < 0 }\n > var obj = { a: 1, b: -2, c: 3, d: 4 }\n > var result = anyInBy(obj, isNegative)\n true\n\n See Also\n --------\n anyBy, anyOwnBy, everyInBy, someInBy","anyOwnBy":"\nanyOwnBy( object, predicate[, thisArg ] )\n Tests whether at least one own property of an object passes a\n test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return\n value.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for one own property; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var obj = { 'a': -1, 'b': 2, 'c': -3 };\n > var bool = anyOwnBy( obj, positive )\n true\n\n See Also\n --------\n anyBy, anyInBy, everyOwnBy, someOwnBy\n","aones":"\naones( length[, dtype] )\n Returns an array filled with ones and having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aones( 2 )\n [ 1.0, 1.0 ]\n > arr = aones( 2, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afull, anans, aonesLike, azeros\n","aonesLike":"\naonesLike( x[, dtype] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = aonesLike( x )\n [ 1.0, 1.0 ]\n > y = aonesLike( x, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afullLike, anansLike, aones, azerosLike\n","aoneTo":"\naoneTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aoneTo( 2 )\n [ 1.0, 2.0 ]\n > arr = aoneTo( 2, 'float32' )\n [ 1.0, 2.0 ]\n\n See Also\n --------\n afull, aones, aoneToLike, azeroTo\n","aoneToLike":"\naoneToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aoneToLike( [ 0, 0 ] )\n [ 1, 2 ]\n > arr = aoneToLike( [ 0, 0 ], 'float32' )\n [ 1.0, 2.0 ]\n\n See Also\n --------\n afullLike, aonesLike, aoneTo, azeroToLike\n","APERY":"\nAPERY\n Apéry's constant.\n\n Examples\n --------\n > APERY\n 1.2020569031595942\n\n","aplace":"\naplace( x, mask, values[, options] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n\n In broadcasting modes, the function supports broadcasting a values array\n containing a single element against the number of truthy values in the mask\n array.\n\n In repeat mode, the function supports recycling elements in a values array\n to satisfy the number of truthy values in the mask array.\n\n The function mutates the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n mask: ArrayLikeObject\n Mask array. If a mask array element is truthy, the corresponding element\n in `x` is *replaced*; otherwise, the corresponding element in `x` is\n \"masked\" and thus left unchanged.\n\n values: ArrayLikeObject\n Values to set.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n String specifying behavior when the number of values to set does not\n equal the number of truthy mask values. The function supports the\n following modes:\n\n - 'strict': specifies that the function must raise an exception when the\n number of values does not *exactly* equal the number of truthy mask\n values.\n - 'non_strict': specifies that the function must raise an exception when\n the function is provided insufficient values to satisfy the mask array.\n - 'strict_broadcast': specifies that the function must broadcast a\n single-element values array and otherwise raise an exception when the\n number of values does not **exactly** equal the number of truthy mask\n values.\n - 'broadcast': specifies that the function must broadcast a single-\n element values array and otherwise raise an exception when the function\n is provided insufficient values to satisfy the mask array.\n - 'repeat': specifies that the function must reuse provided values when\n replacing elements in `x` in order to satisfy the mask array.\n\n Default: 'repeat'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n amskput, aput, atake\n","append":"\nappend( collection1, collection2 )\n Adds the elements of one collection to the end of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = append( arr, [ 6.0, 7.0 ] )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = append( arr, [ 3.0, 4.0 ] )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = append( arr, [ 1.0, 2.0 ] )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n prepend, push\n","aput":"\naput( x, indices, values[, options] )\n Replaces specified elements of an array with provided values.\n\n The function supports broadcasting a `values` array containing a single\n element against an `indices` array containing one or more elements.\n\n The function mutates the input array.\n\n Because each index is only validated at the time of replacing a particular\n element, mutation may occur even when one or more indices are out-of-bounds,\n including when the index mode indicates to raise an exception.\n\n If `indices` is an empty array, the function returns the input array\n unchanged.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n indices: ArrayLikeObject\n List of element indices.\n\n values: ArrayLikeObject\n Values to set. When `indices` contains one or more elements, `values`\n must be broadcast compatible with `indices` (i.e., must have either one\n element or the same number of elements as `indices`).\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n Specifies how to handle an index outside the interval [0, max], where\n `max` is the maximum possible array index. If equal to 'throw', the\n function throws an error. If equal to 'normalize', the function throws\n an error if provided an out-of-bounds normalized index. If equal to\n 'wrap', the function wraps around an index using modulo arithmetic. If\n equal to 'clamp', the function sets an index to either 0 (minimum index)\n or the maximum index. Default: 'normalize'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = aput( x, [ 1, 3 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n amskput, aplace, atake\n","ARCH":"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n\n Current possible values:\n\n - arm\n - arm64\n - ia32\n - mips\n - mipsel\n - ppc\n - ppc64\n - s390\n - s390x\n - x32\n - x64\n\n Examples\n --------\n > ARCH\n \n\n See Also\n --------\n PLATFORM\n","argumentFunction":"\nargumentFunction( idx )\n Returns a function which always returns a specified argument.\n\n The input argument corresponds to the zero-based index of the argument to\n return.\n\n Parameters\n ----------\n idx: integer\n Argument index to return (zero-based).\n\n Returns\n -------\n out: Function\n Argument function.\n\n Examples\n --------\n > var argn = argumentFunction( 1 );\n > var v = argn( 3.14, -3.14, 0.0 )\n -3.14\n > v = argn( -1.0, -0.0, 1.0 )\n -0.0\n > v = argn( 'beep', 'boop', 'bop' )\n 'boop'\n > v = argn( 'beep' )\n undefined\n\n See Also\n --------\n constantFunction, identity\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n\n The first element is the absolute pathname of the executable that started\n the calling process.\n\n The second element is the path of the executed file.\n\n Any additional elements are additional command-line arguments.\n\n In browser environments, the array is empty.\n\n Examples\n --------\n > var execPath = ARGV[ 0 ]\n e.g., /usr/local/bin/node\n\n See Also\n --------\n ENV\n","array":"\narray( [buffer,] [options] )\n Returns a multidimensional array.\n\n Parameters\n ----------\n buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source.\n\n options: Object (optional)\n Options.\n\n options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source. If provided along with a `buffer` argument, the argument\n takes precedence.\n\n options.dtype: string|DataType (optional)\n Underlying storage data type. If not specified and a data source is\n provided, the data type is inferred from the provided data source. If an\n input data source is not of the same type, this option specifies the\n data type to which to cast the input data. For non-ndarray generic array\n data sources, the function casts generic array data elements to the\n default data type. In order to prevent this cast, the `dtype` option\n must be explicitly set to `'generic'`. Any time a cast is required, the\n `copy` option is set to `true`, as memory must be copied from the data\n source to an output data buffer. Default: 'float64'.\n\n options.order: string (optional)\n Specifies the memory layout of the data source as either row-major (C-\n style) or column-major (Fortran-style). The option may be one of the\n following values:\n\n - 'row-major': the order of the returned array is row-major.\n - 'column-major': the order of the returned array is column-major.\n - 'any': if a data source is column-major and not row-major, the order\n of the returned array is column-major; otherwise, the order of the\n returned array is row-major.\n - 'same': the order of the returned array matches the order of an input\n data source.\n\n Note that specifying an order which differs from the order of a\n provided data source does *not* entail a conversion from one memory\n layout to another. In short, this option is descriptive, not\n prescriptive. Default: 'row-major'.\n\n options.shape: Array (optional)\n Array shape (dimensions). If a shape is not specified, the function\n attempts to infer a shape based on a provided data source. For example,\n if provided a nested array, the function resolves nested array\n dimensions. If provided a multidimensional array data source, the\n function uses the array's associated shape. For most use cases, such\n inference suffices. For the remaining use cases, specifying a shape is\n necessary. For example, provide a shape to create a multidimensional\n array view over a linear data buffer, ignoring any existing shape meta\n data associated with a provided data source.\n\n options.flatten: boolean (optional)\n Boolean indicating whether to automatically flatten generic array data\n sources. If an array shape is not specified, the shape is inferred from\n the dimensions of nested arrays prior to flattening. If a use case\n requires partial flattening, partially flatten prior to invoking this\n function and set the option value to `false` to prevent further\n flattening during invocation. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to (shallow) copy source data to a new data\n buffer. The function does *not* perform a deep copy. To prevent\n undesired shared changes in state for generic arrays containing objects,\n perform a deep copy prior to invoking this function. Default: false.\n\n options.ndmin: integer (optional)\n Specifies the minimum number of dimensions. If an array shape has fewer\n dimensions than required by `ndmin`, the function prepends singleton\n dimensions to the array shape in order to satisfy the dimensions\n requirement. Default: 0.\n\n options.casting: string (optional)\n Specifies the casting rule used to determine acceptable casts. The\n option may be one of the following values:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'mostly-safe': allow \"safe casts\" and, for floating-point data types,\n downcasts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers\n and floats).\n\n Default: 'safe'.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. The\n option may be one of the following values:\n\n - 'throw': an ndarray instance throws an error when an index exceeds\n array dimensions.\n - 'normalize': an ndarray instance normalizes negative indices and\n throws an error when an index exceeds array dimensions.\n - 'wrap': an ndarray instance wraps around indices exceeding array\n dimensions using modulo arithmetic.\n - 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index.\n\n Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to\n\n - 'throw': an ndarray instance throws an error when a subscript exceeds\n array dimensions.\n - 'normalize': an ndarray instance normalizes negative subscripts and\n throws an error when a subscript exceeds array dimensions.\n - 'wrap': an ndarray instance wraps around subscripts exceeding array\n dimensions using modulo arithmetic.\n - 'clamp': an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index.\n\n If the number of modes is fewer than the number of dimensions, the\n function recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Multidimensional array.\n\n Examples\n --------\n // Create a 2x2 matrix:\n > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n ndarray\n","array2buffer":"\narray2buffer( arr )\n Allocates a buffer using an octet array.\n\n Parameters\n ----------\n arr: Array\n Array (or array-like object) of octets from which to copy.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n Buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","array2fancy":"\narray2fancy( x[, options] )\n Converts an array to an object supporting fancy indexing.\n\n An array supporting fancy indexing is an array which supports slicing via\n indexing expressions for both retrieval and assignment.\n\n A fancy array shares the *same* data as the provided input array. Hence, any\n mutations to the returned array will affect the underlying input array and\n vice versa.\n\n For operations returning a new array (e.g., when slicing or invoking an\n instance method), a fancy array returns a new fancy array having the same\n configuration as specified by provided options.\n\n A fancy array supports indexing using positive and negative integers (both\n numeric literals and strings), Slice instances, subsequence expressions,\n mask arrays, boolean arrays, and integer arrays.\n\n A fancy array supports all properties and methods of the input array, and,\n thus, a fancy array can be consumed by any API which supports array-like\n objects.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on array views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use (e.g., in the\n REPL) and scripting. For performance critical applications, prefer\n equivalent functional APIs supporting array-like objects.\n\n Fancy arrays support broadcasting in which assigned scalars and single-\n element arrays are repeated (without additional memory allocation) to match\n the length of a target array instance.\n\n Fancy array broadcasting follows the same rules as for ndarrays.\n\n Consequently, when assigning arrays to slices, the array on the right-hand-\n side must be broadcast-compatible with number of elements in the slice.\n\n Fancy arrays support (mostly) safe casts (i.e., any cast which can be\n performed without overflow or loss of precision, with the exception of\n floating-point arrays which are also allowed to downcast from higher\n precision to lower precision).\n\n When attempting to perform an unsafe cast, fancy arrays will raise an\n exception.\n\n When assigning a real-valued scalar to a complex number array (e.g.,\n Complex128Array or Complex64Array), a fancy array will cast the real-valued\n scalar to a complex number argument having an imaginary component equal to\n zero.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array supporting fancy indexing.\n\n Examples\n --------\n > var y = array2fancy( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]\n\n\narray2fancy.factory( [options] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an array to an object supporting fancy indexing.\n\n Examples\n --------\n > var f = array2fancy.factory();\n > var y = f( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]\n\n\narray2fancy.idx( x[, options] )\n Wraps a provided array as an array index object.\n\n For documentation and usage, see `ArrayIndex`.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n See Also\n --------\n aslice, FancyArray\n","array2fancy.factory":"\narray2fancy.factory( [options] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an array to an object supporting fancy indexing.\n\n Examples\n --------\n > var f = array2fancy.factory();\n > var y = f( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]","array2fancy.idx":"\narray2fancy.idx( x[, options] )\n Wraps a provided array as an array index object.\n\n For documentation and usage, see `ArrayIndex`.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n See Also\n --------\n aslice, FancyArray","array2iterator":"\narray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, circarray2iterator, array2iteratorRight, stridedarray2iterator\n","array2iteratorRight":"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator\n","ArrayBuffer":"\nArrayBuffer( size )\n Returns an array buffer having a specified number of bytes.\n\n Buffer contents are initialized to 0.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: ArrayBuffer\n An array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n\n\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1\n\n\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true\n\n\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","ArrayBuffer.length":"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1","ArrayBuffer.isView":"\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","arraybuffer2buffer":"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n Allocates a buffer from an ArrayBuffer.\n\n The behavior of this function varies across Node.js versions due to changes\n in the underlying Node.js APIs:\n\n - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n returns a view of an ArrayBuffer without copying the underlying memory.\n - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n Buffer which is not an ArrayBuffer view.\n - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n the underlying memory.\n\n Parameters\n ----------\n buf: ArrayBuffer\n Input array buffer.\n\n byteOffset: integer (optional)\n Index offset specifying the location of the first byte.\n\n length: integer (optional)\n Number of bytes to expose from the underlying ArrayBuffer.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var ab = new ArrayBuffer( 10 )\n \n > var buf = arraybuffer2buffer( ab )\n \n > var len = buf.length\n 10\n > buf = arraybuffer2buffer( ab, 2, 6 )\n \n > len = buf.length\n 6\n\n See Also\n --------\n Buffer, array2buffer, copyBuffer, string2buffer\n","arrayCtors":"\narrayCtors( dtype )\n Returns an array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = arrayCtors( 'float64' )\n \n > ctor = arrayCtors( 'float' )\n null\n\n See Also\n --------\n typedarrayCtors\n","arrayDataType":"\narrayDataType( array )\n Returns the data type of an array.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n array: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > var dt = arrayDataType( arr )\n 'float64'\n > dt = arrayDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataTypes\n","arrayDataTypes":"\narrayDataTypes( [kind] )\n Returns a list of array data types.\n\n When not provided a data type \"kind\", the function returns an array\n containing the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n The function supports the following data type \"kinds\":\n\n - floating_point: floating-point data types.\n - real_floating_point: real-valued floating-point data types.\n - complex_floating_point: complex-valued floating-point data types.\n - boolean: boolean data types.\n - integer: integer data types.\n - signed_integer: signed integer data types.\n - unsigned_integer: unsigned integer data types.\n - real: real-valued data types.\n - numeric: numeric data types.\n - typed: typed data types.\n - integer_index: integer index data types.\n - boolean_index: boolean index data types.\n - mask_index: mask index data types.\n - typed_index: typed index data types.\n - index: index data types.\n - all: all data types.\n\n Additionally, the function supports extending the \"kinds\" listed above by\n appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n Parameters\n ----------\n kind: string (optional)\n Data type kind.\n\n Returns\n -------\n out: Array\n List of array data types.\n\n Examples\n --------\n > var out = arrayDataTypes()\n [...]\n > out = arrayDataTypes( 'floating_point' )\n [...]\n > out = arrayDataTypes( 'floating_point_and_generic' )\n [...]\n\n See Also\n --------\n typedarrayDataTypes, ndarrayDataTypes\n","ArrayIndex":"\nArrayIndex( x[, options] )\n Wraps a provided array as an array index object.\n\n Array index instances have no explicit functionality; however, they are used\n by \"fancy\" arrays for element retrieval and assignment.\n\n By default, an instance is invalidated and removed from an internal cache\n immediately after a consumer resolves the underlying data associated with an\n instance using the `get` static method. Immediate invalidation and cache\n removal ensures that references to the underlying array are not the source\n of memory leaks.\n\n Because instances leverage an internal cache implementing the Singleton\n pattern, one must be sure to use the same constructor as consumers. If one\n uses a different constructor, the consumer will *not* be able to resolve the\n original wrapped array, as the consumer will attempt to resolve an instance\n in the wrong internal cache.\n\n Because non-persisted instances are freed after first use, in order to avoid\n holding onto memory and to allow garbage collection, one should avoid\n scenarios in which an instance is never used.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n\n\nArrayIndex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.free( idx.id )\n \n\n\nArrayIndex.get( id )\n Returns the array associated with the instance having a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing array data.\n\n out.data: Array|TypedArray|Object\n The underlying array associated with the provided identifier.\n\n out.type: string\n The type of array index.\n\n out.dtype: string\n The data type of the underlying array.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.get( idx.id )\n {...}\n\n\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array data.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.data\n [ 1, 2, 3, 4 ]\n\n\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.dtype\n 'generic'\n\n\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.id\n \n\n\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an array index is actively cached.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.isCached\n true\n\n\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n\n Returns\n -------\n out: string\n Array index type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.type\n \n\n\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toString()\n \n\n\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toJSON()\n { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n See Also\n --------\n array2fancy\n","ArrayIndex.free":"\nArrayIndex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.free( idx.id )\n ","ArrayIndex.get":"\nArrayIndex.get( id )\n Returns the array associated with the instance having a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing array data.\n\n out.data: Array|TypedArray|Object\n The underlying array associated with the provided identifier.\n\n out.type: string\n The type of array index.\n\n out.dtype: string\n The data type of the underlying array.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.get( idx.id )\n {...}","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array data.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.data\n [ 1, 2, 3, 4 ]","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.dtype\n 'generic'","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.id\n ","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an array index is actively cached.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.isCached\n true","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n\n Returns\n -------\n out: string\n Array index type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.type\n ","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toString()\n ","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toJSON()\n { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n See Also\n --------\n array2fancy","arrayMinDataType":"\narrayMinDataType( value )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n Array data type.\n\n Examples\n --------\n > var dt = arrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = arrayMinDataType( 3 )\n 'uint8'\n > dt = arrayMinDataType( -3 )\n 'int8'\n > dt = arrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n arrayDataTypes, arrayPromotionRules, arraySafeCasts\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type value.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be cast.\n\n Examples\n --------\n > var out = arrayMostlySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, arraySameKindCasts, ndarrayMostlySafeCasts\n","arrayNextDataType":"\narrayNextDataType( [dtype] )\n Returns the next larger array data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = arrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n arrayDataType, arrayDataTypes\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1, dtype2] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: any (optional)\n Array data type.\n\n dtype2: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = arrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n arrayDataTypes, arraySafeCasts, ndarrayPromotionRules\n","arraySafeCasts":"\narraySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = arraySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arrayMostlySafeCasts, arraySameKindCasts, ndarraySafeCasts\n","arraySameKindCasts":"\narraySameKindCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast or cast within\n the same \"kind\".\n\n Examples\n --------\n > var out = arraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, ndarraySameKindCasts\n","arrayShape":"\narrayShape( arr )\n Determines array dimensions.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Array shape.\n\n Examples\n --------\n > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ 2, 3 ]\n\n See Also\n --------\n ndarray\n","arrayStream":"\narrayStream( src[, options] )\n Creates a readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = arrayStream( [ 1, 2, 3 ] );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream\n","arrayStream.factory":"\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );","arrayStream.objectMode":"\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream","arrayview2iterator":"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, stridedarray2iterator, arrayview2iteratorRight\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, stridedarray2iterator, arrayview2iterator\n","aslice":"\naslice( x[, start[, end]] )\n Returns a shallow copy of a portion of an array.\n\n If provided an array-like object having a `slice` method, the function\n defers execution to that method and assumes that the method has the\n following signature:\n\n x.slice( start, end )\n\n If provided an array-like object without a `slice` method, the function\n copies input array elements to a new generic array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n start: integer (optional)\n Starting index (inclusive). Default: 0.\n\n end: integer (optional)\n Ending index (exclusive). Default: x.length.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = aslice( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1 )\n [ 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n [ 2, 3 ]\n\n See Also\n --------\n atake\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n\n See Also\n --------\n Symbol, IteratorSymbol\n","atake":"\natake( x, indices[, options] )\n Takes elements from an array.\n\n If `indices` is an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n indices: ArrayLikeObject\n List of element indices.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n Specifies how to handle an index outside the interval [0, max], where\n `max` is the maximum possible array index. If equal to 'throw', the\n function throws an error. If equal to 'normalize', the function throws\n an error if provided an out-of-bounds normalized index. If equal to\n 'wrap', the function wraps around an index using modulo arithmetic. If\n equal to 'clamp', the function sets an index to either 0 (minimum index)\n or the maximum index. Default: 'normalize'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = atake( x, [ 1, 3 ] )\n [ 2, 4 ]\n\n See Also\n --------\n aput, aslice\n","azeros":"\nazeros( length[, dtype] )\n Returns a zero-filled array having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeros( 2 )\n [ 0.0, 0.0 ]\n > arr = azeros( 2, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aempty, afull, anans, aones, azerosLike, ndzeros\n","azerosLike":"\nazerosLike( x[, dtype] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = azerosLike( x )\n [ 0.0, 0.0 ]\n > y = azerosLike( x, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aonesLike, azeros, ndzerosLike\n","azeroTo":"\nazeroTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroTo( 2 )\n [ 0.0, 1.0 ]\n > arr = azeroTo( 2, 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aempty, afull, aoneTo, azeroToLike, azeros\n","azeroToLike":"\nazeroToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroToLike( [ 0, 0 ] )\n [ 0, 1 ]\n > arr = azeroToLike( [ 0, 0 ], 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aoneToLike, aonesLike, azeroTo, azerosLike\n","bartlettTest":"\nbartlettTest( ...x[, options] )\n Computes Bartlett’s test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = bartlettTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = bartlettTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, leveneTest\n","base.abs":"\nbase.abs( x )\n Computes the absolute value of a double-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.abs( -1.0 )\n 1.0\n > y = base.abs( 2.0 )\n 2.0\n > y = base.abs( 0.0 )\n 0.0\n > y = base.abs( -0.0 )\n 0.0\n > y = base.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf, base.labs\n","base.abs2":"\nbase.abs2( x )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2( -1.0 )\n 1.0\n > y = base.abs2( 2.0 )\n 4.0\n > y = base.abs2( 0.0 )\n 0.0\n > y = base.abs2( -0.0 )\n 0.0\n > y = base.abs2( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f\n","base.abs2f":"\nbase.abs2f( x )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2f( -1.0 )\n 1.0\n > y = base.abs2f( 2.0 )\n 4.0\n > y = base.abs2f( 0.0 )\n 0.0\n > y = base.abs2f( -0.0 )\n 0.0\n > y = base.abs2f( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf\n","base.absdiff":"\nbase.absdiff( x, y )\n Computes the absolute difference.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Absolute difference.\n\n Examples\n --------\n > var d = base.absdiff( 2.0, 5.0 )\n 3.0\n > d = base.absdiff( -1.0, 3.14 )\n ~4.14\n > d = base.absdiff( 10.1, -2.05 )\n ~12.15\n > d = base.absdiff( -0.0, 0.0 )\n +0.0\n > d = base.absdiff( NaN, 5.0 )\n NaN\n > d = base.absdiff( PINF, NINF )\n Infinity\n > d = base.absdiff( PINF, PINF )\n NaN\n\n See Also\n --------\n base.reldiff, base.epsdiff\n","base.absf":"\nbase.absf( x )\n Computes the absolute value of a single-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.absf( -1.0 )\n 1.0\n > y = base.absf( 2.0 )\n 2.0\n > y = base.absf( 0.0 )\n 0.0\n > y = base.absf( -0.0 )\n 0.0\n > y = base.absf( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f, base.labs\n","base.acartesianPower":"\nbase.acartesianPower( x, n )\n Returns the Cartesian power.\n\n If provided an empty array, the function returns an empty array.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n n: integer\n Power.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = base.acartesianPower( x, 2 )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianPower, base.acartesianProduct, base.acartesianSquare\n","base.acartesianProduct":"\nbase.acartesianProduct( x1, x2 )\n Returns the Cartesian product.\n\n If provided one or more empty arrays, the function returns an empty array.\n\n Parameters\n ----------\n x1: ArrayLikeObject\n First input array.\n\n x2: ArrayLikeObject\n Second input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x1 = [ 1, 2 ];\n > var x2 = [ 3, 4 ];\n > var out = base.acartesianProduct( x1, x2 )\n [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n See Also\n --------\n acartesianProduct, base.acartesianPower, base.acartesianSquare\n","base.acartesianSquare":"\nbase.acartesianSquare( x )\n Returns the Cartesian square.\n\n If provided an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = base.acartesianSquare( x )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianSquare, base.acartesianPower, base.acartesianProduct\n","base.acos":"\nbase.acos( x )\n Compute the arccosine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acos( 1.0 )\n 0.0\n > y = base.acos( 0.707 )\n ~0.7855\n > y = base.acos( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asin, base.atan\n","base.acosd":"\nbase.acosd( x )\n Computes the arccosine (in degrees) of a double-precision floating-point \n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in degrees).\n\n Examples\n --------\n > var y = base.acosd( 0.0 )\n 90.0\n > y = base.acosd( PI/6.0 )\n ~58.43\n > y = base.acosd( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.acosdf, base.acosh, base.asind, base.atand\n","base.acosdf":"\nbase.acosdf( x )\n Computes the arccosine (in degrees) of a single-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in degrees).\n\n Examples\n --------\n > var y = base.acosdf( 0.0 )\n 90.0\n > y = base.acosdf( FLOAT32_PI / 6.0 )\n ~58.43\n > y = base.acosdf( NaN )\n NaN\n\n See Also\n --------\n base.acosd, base.acosf, base.asindf\n","base.acosf":"\nbase.acosf( x )\n Computes the arccosine of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acosf( 1.0 )\n 0.0\n > y = base.acosf( 0.707 )\n ~0.7855\n > y = base.acosf( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.acosh, base.asinf, base.atanf\n","base.acosh":"\nbase.acosh( x )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n\n If `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosine.\n\n Examples\n --------\n > var y = base.acosh( 1.0 )\n 0.0\n > y = base.acosh( 2.0 )\n ~1.317\n > y = base.acosh( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atanh\n","base.acot":"\nbase.acot( x )\n Computes the inverse cotangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse cotangent (in radians).\n\n Examples\n --------\n > var y = base.acot( 2.0 )\n ~0.4636\n > y = base.acot( 0.0 )\n ~1.5708\n > y = base.acot( 0.5 )\n ~1.1071\n > y = base.acot( 1.0 )\n ~0.7854\n > y = base.acot( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.atan, base.cot\n","base.acotd":"\nbase.acotd( x )\n Computes the arccotangent (in degrees) of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccotangent (in degrees).\n\n Examples\n --------\n > var y = base.acotd( 0.0 )\n 90.0\n > y = base.acotd( PI/6.0 )\n ~62.36\n > y = base.acotd( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acotdf, base.acoth, base.atand, base.cotd\n","base.acotdf":"\nbase.acotdf( x )\n Computes the arccotangent (in degrees) of a single-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccotangent (in degrees).\n\n Examples\n --------\n > var y = base.acotdf( 0.0 )\n 90.0\n > y = base.acotdf( FLOAT32_PI/6.0 )\n ~62.36\n > y = base.acotdf( NaN )\n NaN\n\n See Also\n --------\n base.acotd, base.acotf\n","base.acotf":"\nbase.acotf( x )\n Computes the inverse cotangent of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse cotangent (in radians).\n\n Examples\n --------\n > var y = base.acotf( 2.0 )\n ~0.4636\n > y = base.acotf( 0.0 )\n ~1.5708\n > y = base.acotf( 0.5 )\n ~1.1071\n > y = base.acotf( 1.0 )\n ~0.7854\n > y = base.acotf( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acoth, base.atanf\n","base.acoth":"\nbase.acoth( x )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n\n The domain of the inverse hyperbolic cotangent is the union of the intervals\n (-inf,-1] and [1,inf).\n\n If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse hyperbolic cotangent.\n\n Examples\n --------\n > var y = base.acoth( 2.0 )\n ~0.5493\n > y = base.acoth( 0.0 )\n NaN\n > y = base.acoth( 0.5 )\n NaN\n > y = base.acoth( 1.0 )\n Infinity\n > y = base.acoth( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.acot, base.asinh, base.atanh\n","base.acovercos":"\nbase.acovercos( x )\n Computes the inverse coversed cosine.\n\n The inverse coversed cosine is defined as `asin(x-1)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed cosine.\n\n Examples\n --------\n > var y = base.acovercos( 1.5 )\n ~0.5236\n > y = base.acovercos( -0.0 )\n ~-1.5708\n\n See Also\n --------\n base.acoversin, base.avercos, base.covercos, base.vercos\n","base.acoversin":"\nbase.acoversin( x )\n Computes the inverse coversed sine.\n\n The inverse coversed sine is defined as `asin(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed sine.\n\n Examples\n --------\n > var y = base.acoversin( 1.5 )\n ~-0.5236\n > y = base.acoversin( 0.0 )\n ~1.5708\n\n See Also\n --------\n base.acovercos, base.aversin, base.coversin, base.versin\n","base.acsc":"\nbase.acsc( x )\n Computes the arccosecant of a number.\n\n If `|x| < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in radians).\n\n Examples\n --------\n > var y = base.acsc( 1.0 )\n ~1.57\n > y = base.acsc( PI )\n ~0.32\n > y = base.acsc( -PI )\n ~-0.32\n > y = base.acsc( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acsch, base.asec, base.asin, base.csc\n","base.acscd":"\nbase.acscd( x )\n Computes the arccosecant of (in degrees) a double-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in degrees).\n\n Examples\n --------\n > var y = base.acscd( 0.0 )\n NaN\n > y = base.acscd( PI/6.0 )\n NaN\n > y = base.acscd( 1 )\n 90.0\n > y = base.acscd( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecd, base.asind, base.cscd\n","base.acscdf":"\nbase.acscdf( x )\n Computes the arccosecant (in degrees) of a single-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in degrees).\n\n Examples\n --------\n > var y = base.acscdf( 0.0 )\n NaN\n > y = base.acscdf( 3.1415927410125732 / 6.0 )\n NaN\n > y = base.acscdf( 1.0 )\n 90.0\n > y = base.acscdf( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecdf, base.asindf\n","base.acscf":"\nbase.acscf( x )\n Computes the arccosecant of a single-precision floating-point number.\n\n If `|x| < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in radians).\n\n Examples\n --------\n > var y = base.acscf( 1.0 )\n ~1.57\n > y = base.acscf( 3.141592653589793 )\n ~0.32\n > y = base.acscf( -3.141592653589793 )\n ~-0.32\n > y = base.acscf( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecf, base.asinf\n","base.acsch":"\nbase.acsch( x )\n Computes the hyperbolic arccosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosecant.\n\n Examples\n --------\n > var y = base.acsch( 0.0 )\n Infinity\n > y = base.acsch( -1.0 )\n ~-0.881\n > y = base.acsch( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.acsc, base.asech, base.asinh, base.csc, base.csch\n","base.add":"\nbase.add( x, y )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Sum.\n\n Examples\n --------\n > var v = base.add( -1.0, 5.0 )\n 4.0\n > v = base.add( 2.0, 5.0 )\n 7.0\n > v = base.add( 0.0, 5.0 )\n 5.0\n > v = base.add( -0.0, 0.0 )\n 0.0\n > v = base.add( NaN, NaN )\n NaN\n\n See Also\n --------\n base.div, base.mul, base.sub\n","base.add3":"\nbase.add3( x, y, z )\n Computes the sum of three double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add3( -1.0, 5.0, 2.0 )\n 6.0\n > v = base.add3( 2.0, 5.0, 2.0 )\n 9.0\n > v = base.add3( 0.0, 5.0, 2.0 )\n 7.0\n > v = base.add3( -0.0, 0.0, -0.0 )\n 0.0\n > v = base.add3( NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.add4":"\nbase.add4( x, y, z, w )\n Computes the sum of four double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n w: number\n Fourth input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\n 3.0\n > v = base.add4( 2.0, 5.0, 2.0, -3.0 )\n 6.0\n > v = base.add4( 0.0, 5.0, 2.0, -3.0 )\n 4.0\n > v = base.add4( -0.0, 0.0, -0.0, -0.0 )\n 0.0\n > v = base.add4( NaN, NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.add5":"\nbase.add5( x, y, z, w, u )\n Computes the sum of five double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n w: number\n Fourth input value.\n\n u: number\n Fifth input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\n 7.0\n > v = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\n 10.0\n > v = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\n 8.0\n > v = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\n 0.0\n > v = base.add5( NaN, NaN, NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.addf":"\nbase.addf( x, y )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Sum.\n\n Examples\n --------\n > var v = base.addf( -1.0, 5.0 )\n 4.0\n > v = base.addf( 2.0, 5.0 )\n 7.0\n > v = base.addf( 0.0, 5.0 )\n 5.0\n > v = base.addf( -0.0, 0.0 )\n 0.0\n > v = base.addf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.divf, base.mulf, base.subf\n","base.afilled":"\nbase.afilled( value, len )\n Returns a filled \"generic\" array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled( 0.0, 3 )\n [ 0.0, 0.0, 0.0 ]\n\n","base.afilled2d":"\nbase.afilled2d( value, shape )\n Returns a filled two-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled2d( 0.0, [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilled2dBy":"\nbase.afilled2dBy( shape, clbk[, thisArg] )\n Returns a filled two-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled2dBy( [ 1, 3 ], clbk )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.afilled2d\n","base.afilled3d":"\nbase.afilled3d( value, shape )\n Returns a filled three-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n","base.afilled3dBy":"\nbase.afilled3dBy( shape, clbk[, thisArg] )\n Returns a filled three-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n See Also\n --------\n base.afilled3d\n","base.afilled4d":"\nbase.afilled4d( value, shape )\n Returns a filled four-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n","base.afilled4dBy":"\nbase.afilled4dBy( shape, clbk[, thisArg] )\n Returns a filled four-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n See Also\n --------\n base.afilled4d\n","base.afilled5d":"\nbase.afilled5d( value, shape )\n Returns a filled five-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n","base.afilled5dBy":"\nbase.afilled5dBy( shape, clbk[, thisArg] )\n Returns a filled five-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n See Also\n --------\n base.afilled5d\n","base.afilledBy":"\nbase.afilledBy( len, clbk[, thisArg] )\n Returns a filled \"generic\" array according to a provided callback function.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilledBy( 3, clbk )\n [ 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n base.afilled\n","base.afillednd":"\nbase.afillednd( value, shape )\n Returns a filled n-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afillednd( 0.0, [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilledndBy":"\nbase.afilledndBy( shape, clbk[, thisArg] )\n Returns a filled n-dimensional nested array according to a callback\n function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilledndBy( [ 1, 3 ], clbk )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.afillednd\n","base.afilter":"\nbase.afilter( x, predicate[, thisArg] )\n Returns a shallow copy of an array containing only those elements which pass\n a test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the input array.\n\n If provided an array-like object having a `filter` method , the function\n defers execution to that method and assumes that the method has the\n following signature:\n\n x.filter( predicate, thisArg )\n\n If provided an array-like object without a `filter` method, the function\n performs a linear scan and always returns a generic array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > function f( v ) { return ( v > 0 ); };\n > var x = [ 1, -2, -3, 4 ];\n > var out = base.afilter( x, f )\n [ 1, 4 ]\n\n","base.afirst":"\nbase.afirst( arr )\n Returns the first element of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: any\n First element.\n\n Examples\n --------\n > var out = base.afirst( [ 1, 2, 3 ] )\n 1\n\n","base.aflatten":"\nbase.aflatten( x, shape, colexicographic )\n Flattens an n-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten( x, [ 2, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten( x, [ 2, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflattenBy\n","base.aflatten.assign":"\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflattenBy","base.aflatten2d":"\nbase.aflatten2d( x, shape, colexicographic )\n Flattens a two-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten2d( x, [ 2, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten2d( x, [ 2, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten2dBy\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten2dBy","base.aflatten2dBy":"\nbase.aflatten2dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten2d\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten2d","base.aflatten3d":"\nbase.aflatten3d( x, shape, colexicographic )\n Flattens a three-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = base.aflatten3d( x, [ 2, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten3d( x, [ 2, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten3dBy\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten3dBy","base.aflatten3dBy":"\nbase.aflatten3dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten3d\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten3d","base.aflatten4d":"\nbase.aflatten4d( x, shape, colexicographic )\n Flattens a four-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten4dBy\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten4dBy","base.aflatten4dBy":"\nbase.aflatten4dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten4d\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten4d","base.aflatten5d":"\nbase.aflatten5d( x, shape, colexicographic )\n Flattens a five-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten5dBy\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten5dBy","base.aflatten5dBy":"\nbase.aflatten5dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten5d\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten5d","base.aflattenBy":"\nbase.aflattenBy( x, shape, colex, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten","base.afliplr2d":"\nbase.afliplr2d( x )\n Reverses the order of elements along the last dimension of a two-dimensional\n nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ [ 2, 1 ], [ 4, 3 ] ]\n\n See Also\n --------\n base.afliplr3d, base.afliplr4d, base.afliplr5d\n","base.afliplr3d":"\nbase.afliplr3d( x )\n Reverses the order of elements along the last dimension of a three-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n [ [ [ 2, 1 ], [ 4, 3 ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr4d, base.afliplr5d\n","base.afliplr4d":"\nbase.afliplr4d( x )\n Reverses the order of elements along the last dimension of a four-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr3d, base.afliplr5d\n","base.afliplr5d":"\nbase.afliplr5d( x )\n Reverses the order of elements along the last dimension of a five-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n [ [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr3d, base.afliplr4d\n","base.aflipud2d":"\nbase.aflipud2d( x )\n Reverses the order of elements along the first dimension of a two-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ [ 3, 4 ], [ 1, 2 ] ]\n\n See Also\n --------\n base.aflipud3d, base.aflipud4d, base.aflipud5d\n","base.aflipud3d":"\nbase.aflipud3d( x )\n Reverses the order of elements along the second-to-last dimension of a\n three-dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n [ [ [ 3, 4 ], [ 1, 2 ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud4d, base.aflipud5d\n","base.aflipud4d":"\nbase.aflipud4d( x )\n Reverses the order of elements along the second-to-last dimension of a four-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud3d, base.aflipud5d\n","base.aflipud5d":"\nbase.aflipud5d( x )\n Reverses the order of elements along the second-to-last dimension of a five-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n [ [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud3d, base.aflipud4d\n","base.ahavercos":"\nbase.ahavercos( x )\n Computes the inverse half-value versed cosine.\n\n The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed cosine.\n\n Examples\n --------\n > var y = base.ahavercos( 0.5 )\n ~1.5708\n > y = base.ahavercos( 0.0 )\n ~3.1416\n\n See Also\n --------\n base.ahaversin, base.havercos, base.vercos\n","base.ahaversin":"\nbase.ahaversin( x )\n Computes the inverse half-value versed sine.\n\n The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed sine.\n\n Examples\n --------\n > var y = base.ahaversin( 0.5 )\n ~1.5708\n > y = base.ahaversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.ahavercos, base.haversin, base.versin\n","base.altcase":"\nbase.altcase( str )\n Converts a string to alternate case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Alternate-cased string.\n\n Examples\n --------\n > var out = base.altcase( 'Hello World!' )\n 'hElLo wOrLd!'\n > out = base.altcase( 'I am a tiny little teapot' )\n 'i aM A TiNy lItTlE TeApOt'\n\n See Also\n --------\n base.lowercase, base.uppercase","base.aones":"\nbase.aones( len )\n Returns a \"generic\" array filled with ones.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones( 3 )\n [ 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n base.azeros, base.aones2d, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones2d":"\nbase.aones2d( shape )\n Returns a two-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones2d( [ 1, 3 ] )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.azeros2d, base.aones, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones3d":"\nbase.aones3d( shape )\n Returns a three-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones3d( [ 1, 1, 3 ] )\n [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n See Also\n --------\n base.azeros3d, base.aones, base.aones2d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones4d":"\nbase.aones4d( shape )\n Returns a four-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones4d( [ 1, 1, 1, 3 ] )\n [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n See Also\n --------\n base.azeros4d, base.aones, base.aones2d, base.aones3d, base.aones5d, base.aonesnd\n","base.aones5d":"\nbase.aones5d( shape )\n Returns a five-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n See Also\n --------\n base.azeros5d, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aonesnd\n","base.aonesnd":"\nbase.aonesnd( shape )\n Returns an n-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aonesnd( [ 1, 3 ] )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.azerosnd, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aones5d\n","base.aoneTo":"\nbase.aoneTo( n )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n\n If `n` is a non-integer value greater than zero, the function returns an\n array having `ceil(n)` elements.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: number\n Number of elements.\n\n Returns\n -------\n out: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = base.aoneTo( 6 )\n [ 1, 2, 3, 4, 5, 6 ]\n\n\nbase.aoneTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.aoneTo.assign( out, -1, out.length-1 );\n > out\n [ 6, 5, 4, 3, 2, 1 ]\n\n See Also\n --------\n base.azeroTo, base.aones\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.aoneTo.assign( out, -1, out.length-1 );\n > out\n [ 6, 5, 4, 3, 2, 1 ]\n\n See Also\n --------\n base.azeroTo, base.aones","base.args2multislice":"\nbase.args2multislice( args )\n Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n\n Parameters\n ----------\n args: Array\n Constructor arguments.\n\n Returns\n -------\n s: MultiSlice\n MultiSlice instance.\n\n Examples\n --------\n > var args = [ null, null, null ];\n > var s = new base.args2multislice( args );\n > s.data\n [ null, null, null ]\n > args = [ 10, new Slice( 0, 10, 1 ), null ];\n > s = new base.args2multislice( args );\n > s.data\n [ 10, , null ]\n\n","base.asec":"\nbase.asec( x )\n Computes the inverse (arc) secant of a number.\n\n If `x > -1` and `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse (arc) secant.\n\n Examples\n --------\n > var y = base.asec( 1.0 )\n 0.0\n > y = base.asec( 2.0 )\n ~1.0472\n > y = base.asec( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acsc, base.asech, base.acos\n","base.asecd":"\nbase.asecd( x )\n Computes the arcsecant (in degrees) of a double-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsecant (in degrees).\n\n Examples\n --------\n > var y = base.asecd( 0.0 )\n NaN\n > y = base.asecd( 2 )\n ~60.0\n > y = base.asecd( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech, base.acosd, base.secd\n","base.asecdf":"\nbase.asecdf( x )\n Computes the arcsecant (in degrees) of a single-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsecant (in degrees).\n\n Examples\n --------\n > var y = base.asecdf( 2.0 )\n ~60.0\n > y = base.asecdf( 0.0 )\n NaN\n > y = base.asecdf( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech, base.acosdf\n","base.asecf":"\nbase.asecf( x )\n Computes the inverse (arc) secant of a single-precision\n floating-point number.\n\n If `x > -1` and `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse (arc) secant.\n\n Examples\n --------\n > var y = base.asecf( 1.0 )\n 0.0\n > y = base.asecf( 2.0 )\n ~1.0472\n > y = base.asecf( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech, base.acosf\n","base.asech":"\nbase.asech( x )\n Computes the hyperbolic arcsecant of a number.\n\n If `x < 0` or `x > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsecant.\n\n Examples\n --------\n > var y = base.asech( 1.0 )\n 0.0\n > y = base.asech( 0.5 )\n ~1.317\n > y = base.asech( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asec, base.asech, base.acoth\n","base.asin":"\nbase.asin( x )\n Computes the arcsine of a double-precision floating-point number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asin( 0.0 )\n 0.0\n > y = base.asin( -PI/6.0 )\n ~-0.551\n > y = base.asin( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atan\n","base.asind":"\nbase.asind( x )\n Computes the arcsine (in degrees) of a double-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in degrees).\n\n Examples\n --------\n > var y = base.asind( 0.0 )\n 0.0\n > y = base.asind( PI / 6.0 )\n ~31.57\n > y = base.asind( NaN )\n NaN\n\n See Also\n --------\n base.asin, base.asinh, base.atand\n","base.asindf":"\nbase.asindf( x )\n Computes the arcsine (in degrees) of a single-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in degrees).\n\n Examples\n --------\n > var y = base.asindf( 0.0 )\n 0.0\n > y = base.asindf( 3.1415927410125732 / 6.0 )\n ~31.57\n > y = base.asindf( NaN )\n NaN\n\n See Also\n --------\n base.asinf, base.asind\n","base.asinf":"\nbase.asinf( x )\n Computes the arcsine of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asinf( 0.0 )\n 0.0\n > y = base.asinf( -3.14/6.0 )\n ~-0.551\n > y = base.asinf( NaN )\n NaN\n\n See Also\n --------\n base.asin, base.asindf\n","base.asinh":"\nbase.asinh( x )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsine.\n\n Examples\n --------\n > var y = base.asinh( 0.0 )\n 0.0\n > y = base.asinh( 2.0 )\n ~1.444\n > y = base.asinh( -2.0 )\n ~-1.444\n > y = base.asinh( NaN )\n NaN\n > y = base.asinh( NINF )\n -Infinity\n > y = base.asinh( PINF )\n Infinity\n\n See Also\n --------\n base.acosh, base.asin, base.atanh\n","base.atan":"\nbase.atan( x )\n Computes the arctangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atan( 0.0 )\n ~0.0\n > y = base.atan( -PI/2.0 )\n ~-1.004\n > y = base.atan( PI/2.0 )\n ~1.004\n > y = base.atan( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asin, base.atanh\n","base.atan2":"\nbase.atan2( y, x )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n\n Parameters\n ----------\n y: number\n Coordinate along y-axis.\n\n x: number\n Coordinate along x-axis.\n\n Returns\n -------\n out: number\n Angle (in radians).\n\n Examples\n --------\n > var v = base.atan2( 2.0, 2.0 )\n ~0.785\n > v = base.atan2( 6.0, 2.0 )\n ~1.249\n > v = base.atan2( -1.0, -1.0 )\n ~-2.356\n > v = base.atan2( 3.0, 0.0 )\n ~1.571\n > v = base.atan2( -2.0, 0.0 )\n ~-1.571\n > v = base.atan2( 0.0, 0.0 )\n 0.0\n > v = base.atan2( 3.0, NaN )\n NaN\n > v = base.atan2( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.atan\n","base.atand":"\nbase.atand( x )\n Computes the arctangent (in degrees) of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in degrees).\n\n Examples\n --------\n > var y = base.atand( 0.0 )\n 0.0\n > y = base.atand( PI/6.0 )\n ~27.64\n > y = base.atand( NaN )\n NaN\n\n See Also\n --------\n base.atan, base.atanh, base.acosd\n","base.atanf":"\nbase.atanf( x )\n Computes the arctangent of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atanf( 0.0 )\n 0.0\n > y = base.atanf( -3.14/4.0 )\n ~-0.666\n > y = base.atanf( 3.14/4.0 )\n ~0.666\n > y = base.atanf( NaN )\n NaN\n\n See Also\n --------\n base.atan, base.atanh, base.acosf\n","base.atanh":"\nbase.atanh( x )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arctangent.\n\n Examples\n --------\n > var y = base.atanh( 0.0 )\n 0.0\n > y = base.atanh( 0.9 )\n ~1.472\n > y = base.atanh( 1.0 )\n Infinity\n > y = base.atanh( -1.0 )\n -Infinity\n > y = base.atanh( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asinh, base.atan\n","base.avercos":"\nbase.avercos( x )\n Computes the inverse versed cosine.\n\n The inverse versed cosine is defined as `acos(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed cosine.\n\n Examples\n --------\n > var y = base.avercos( -1.5 )\n ~2.0944\n > y = base.avercos( -0.0 )\n 0.0\n\n See Also\n --------\n base.aversin, base.versin\n","base.aversin":"\nbase.aversin( x )\n Computes the inverse versed sine.\n\n The inverse versed sine is defined as `acos(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed sine.\n\n Examples\n --------\n > var y = base.aversin( 1.5 )\n ~2.0944\n > y = base.aversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.avercos, base.vercos\n","base.azeros":"\nbase.azeros( len )\n Returns a zero-filled \"generic\" array.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros( 3 )\n [ 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.aones, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros2d":"\nbase.azeros2d( shape )\n Returns a zero-filled two-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros2d( [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n See Also\n --------\n base.azeros, base.aones2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros3d":"\nbase.azeros3d( shape )\n Returns a zero-filled three-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros3d( [ 1, 1, 3 ] )\n [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n See Also\n --------\n base.azeros, base.aones3d, base.azeros2d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros4d":"\nbase.azeros4d( shape )\n Returns a zero-filled four-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros4d( [ 1, 1, 1, 3 ] )\n [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n See Also\n --------\n base.azeros, base.aones4d, base.azeros2d, base.azeros3d, base.azeros5d, base.azerosnd\n","base.azeros5d":"\nbase.azeros5d( shape )\n Returns a zero-filled five-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros5d( [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n See Also\n --------\n base.azeros, base.aones5d, base.azeros2d, base.azeros3d, base.azeros4d, base.azerosnd\n","base.azerosnd":"\nbase.azerosnd( shape )\n Returns a zero-filled n-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azerosnd( [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n See Also\n --------\n base.azeros, base.aonesnd, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d\n","base.azeroTo":"\nbase.azeroTo( n )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n\n If `n` is a non-integer value greater than zero, the function returns an\n array having `ceil(n)` elements.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: number\n Number of elements.\n\n Returns\n -------\n out: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = base.azeroTo( 6 )\n [ 0, 1, 2, 3, 4, 5 ]\n\n\nbase.azeroTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.azeroTo.assign( out, -1, out.length-1 );\n > out\n [ 5, 4, 3, 2, 1, 0 ]\n\n See Also\n --------\n base.aoneTo\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.azeroTo.assign( out, -1, out.length-1 );\n > out\n [ 5, 4, 3, 2, 1, 0 ]\n\n See Also\n --------\n base.aoneTo","base.bernoulli":"\nbase.bernoulli( n )\n Computes the nth Bernoulli number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Bernoulli number.\n\n Examples\n --------\n > var y = base.bernoulli( 0 )\n 1.0\n > y = base.bernoulli( 1 )\n 0.5\n > y = base.bernoulli( 2 )\n ~0.167\n > y = base.bernoulli( 3 )\n 0.0\n > y = base.bernoulli( 4 )\n ~-0.033\n > y = base.bernoulli( 5 )\n 0.0\n > y = base.bernoulli( 20 )\n ~-529.124\n > y = base.bernoulli( 260 )\n -Infinity\n > y = base.bernoulli( 262 )\n Infinity\n > y = base.bernoulli( NaN )\n NaN\n\n","base.besselj0":"\nbase.besselj0( x )\n Computes the Bessel function of the first kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj0( 0.0 )\n 1.0\n > y = base.besselj0( 1.0 )\n ~0.765\n > y = base.besselj0( PINF )\n 0.0\n > y = base.besselj0( NINF )\n 0.0\n > y = base.besselj0( NaN )\n NaN\n\n See Also\n --------\n base.besselj1, base.bessely0, base.bessely1\n","base.besselj1":"\nbase.besselj1( x )\n Computes the Bessel function of the first kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj1( 0.0 )\n 0.0\n > y = base.besselj1( 1.0 )\n ~0.440\n > y = base.besselj1( PINF )\n 0.0\n > y = base.besselj1( NINF )\n 0.0\n > y = base.besselj1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.bessely0, base.bessely1\n","base.bessely0":"\nbase.bessely0( x )\n Computes the Bessel function of the second kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely0( 0.0 )\n -Infinity\n > y = base.bessely0( 1.0 )\n ~0.088\n > y = base.bessely0( -1.0 )\n NaN\n > y = base.bessely0( PINF )\n 0.0\n > y = base.bessely0( NINF )\n NaN\n > y = base.bessely0( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely1\n","base.bessely1":"\nbase.bessely1( x )\n Computes the Bessel function of the second kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely1( 0.0 )\n -Infinity\n > y = base.bessely1( 1.0 )\n ~-0.781\n > y = base.bessely1( -1.0 )\n NaN\n > y = base.bessely1( PINF )\n 0.0\n > y = base.bessely1( NINF )\n NaN\n > y = base.bessely1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely0\n","base.beta":"\nbase.beta( x, y )\n Evaluates the beta function.\n\n Parameters\n ----------\n x: number\n First function parameter (nonnegative).\n\n y: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Evaluated beta function.\n\n Examples\n --------\n > var v = base.beta( 0.0, 0.5 )\n Infinity\n > v = base.beta( 1.0, 1.0 )\n 1.0\n > v = base.beta( -1.0, 2.0 )\n NaN\n > v = base.beta( 5.0, 0.2 )\n ~3.382\n > v = base.beta( 4.0, 1.0 )\n 0.25\n > v = base.beta( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.betainc, base.betaincinv, base.betaln\n","base.betainc":"\nbase.betainc( x, a, b[, regularized[, upper]] )\n Computes the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betainc( 0.5, 2.0, 2.0 )\n 0.5\n > y = base.betainc( 0.5, 2.0, 2.0, false )\n ~0.083\n > y = base.betainc( 0.2, 1.0, 2.0 )\n 0.36\n > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n 0.64\n > y = base.betainc( NaN, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.8, NaN, 1.0 )\n NaN\n > y = base.betainc( 0.8, 1.0, NaN )\n NaN\n > y = base.betainc( 1.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betainc( 0.5, 2.0, -2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betaincinv, base.betaln\n","base.betaincinv":"\nbase.betaincinv( p, a, b[, upper] )\n Computes the inverse of the lower incomplete beta function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second and third arguments are `a` and `b`,\n respectively.\n\n By default, the function inverts the lower regularized incomplete beta\n function. To invert the upper function, set the `upper` argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n ~0.327\n > y = base.betaincinv( 0.4, 3.0, 3.0 )\n ~0.446\n > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n ~0.554\n > y = base.betaincinv( 0.4, 1.0, 6.0 )\n ~0.082\n > y = base.betaincinv( 0.8, 1.0, 6.0 )\n ~0.235\n > y = base.betaincinv( NaN, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, NaN, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, 1.0, NaN )\n NaN\n > y = base.betaincinv( 1.2, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 0.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, -2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, 0.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaln\n","base.betaln":"\nbase.betaln( a, b )\n Evaluates the natural logarithm of the beta function.\n\n Parameters\n ----------\n a: number\n First function parameter (nonnegative).\n\n b: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Natural logarithm of the beta function.\n\n Examples\n --------\n > var v = base.betaln( 0.0, 0.0 )\n Infinity\n > v = base.betaln( 1.0, 1.0 )\n 0.0\n > v = base.betaln( -1.0, 2.0 )\n NaN\n > v = base.betaln( 5.0, 0.2 )\n ~1.218\n > v = base.betaln( 4.0, 1.0 )\n ~-1.386\n > v = base.betaln( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaincinv\n","base.binet":"\nbase.binet( x )\n Evaluates Binet's formula extended to real numbers.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function result.\n\n Examples\n --------\n > var y = base.binet( 0.0 )\n 0.0\n > y = base.binet( 1.0 )\n 1.0\n > y = base.binet( 2.0 )\n 1.0\n > y = base.binet( 3.0 )\n 2.0\n > y = base.binet( 4.0 )\n 3.0\n > y = base.binet( 5.0 )\n ~5.0\n > y = base.binet( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negafibonacci\n","base.binomcoef":"\nbase.binomcoef( n, k )\n Computes the binomial coefficient of two integers.\n\n If `k < 0`, the function returns `0`.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = base.binomcoef( 8, 2 )\n 28\n > v = base.binomcoef( 0, 0 )\n 1\n > v = base.binomcoef( -4, 2 )\n 10\n > v = base.binomcoef( 5, 3 )\n 10\n > v = base.binomcoef( NaN, 3 )\n NaN\n > v = base.binomcoef( 5, NaN )\n NaN\n > v = base.binomcoef( NaN, NaN )\n NaN\n\n","base.binomcoefln":"\nbase.binomcoefln( n, k )\n Computes the natural logarithm of the binomial coefficient of two integers.\n\n If `k < 0`, the function returns negative infinity.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Natural logarithm of the binomial coefficient.\n\n Examples\n --------\n > var v = base.binomcoefln( 8, 2 )\n ~3.332\n > v = base.binomcoefln( 0, 0 )\n 0.0\n > v = base.binomcoefln( -4, 2 )\n ~2.303\n > v = base.binomcoefln( 88, 3 )\n ~11.606\n > v = base.binomcoefln( NaN, 3 )\n NaN\n > v = base.binomcoefln( 5, NaN )\n NaN\n > v = base.binomcoefln( NaN, NaN )\n NaN\n\n","base.boxcox":"\nbase.boxcox( x, lambda )\n Computes a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox( 1.0, 2.5 )\n 0.0\n > v = base.boxcox( 4.0, 2.5 )\n 12.4\n > v = base.boxcox( 10.0, 2.5 )\n ~126.0911\n > v = base.boxcox( 2.0, 0.0 )\n ~0.6931\n > v = base.boxcox( -1.0, 2.5 )\n NaN\n > v = base.boxcox( 0.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcoxinv, base.boxcox1p, base.boxcox1pinv","base.boxcox1p":"\nbase.boxcox1p( x, lambda )\n Computes a one-parameter Box-Cox transformation of 1+x.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1p( 1.0, 2.5 )\n ~1.8627\n > v = base.boxcox1p( 4.0, 2.5 )\n ~21.9607\n > v = base.boxcox1p( 10.0, 2.5 )\n ~160.1246\n > v = base.boxcox1p( 2.0, 0.0 )\n ~1.0986\n > v = base.boxcox1p( -1.0, 2.5 )\n -0.4\n > v = base.boxcox1p( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1p( -1.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcox, base.boxcox1pinv, base.boxcoxinv","base.boxcox1pinv":"\nbase.boxcox1pinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1pinv( 1.0, 2.5 )\n ~0.6505\n > v = base.boxcox1pinv( 4.0, 2.5 )\n ~1.6095\n > v = base.boxcox1pinv( 10.0, 2.5 )\n ~2.6812\n > v = base.boxcox1pinv( 2.0, 0.0 )\n ~6.3891\n > v = base.boxcox1pinv( -1.0, 2.5 )\n NaN\n > v = base.boxcox1pinv( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1pinv( 1.0, NaN )\n NaN\n > v = base.boxcox1pinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcoxinv","base.boxcoxinv":"\nbase.boxcoxinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcoxinv( 1.0, 2.5 )\n ~1.6505\n > v = base.boxcoxinv( 4.0, 2.5 )\n ~2.6095\n > v = base.boxcoxinv( 10.0, 2.5 )\n ~3.6812\n > v = base.boxcoxinv( 2.0, 0.0 )\n ~7.3891\n > v = base.boxcoxinv( -1.0, 2.5 )\n NaN\n > v = base.boxcoxinv( 0.0, -1.0 )\n 1.0\n > v = base.boxcoxinv( 1.0, NaN )\n NaN\n > v = base.boxcoxinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcox1pinv","base.cabs":"\nbase.cabs( z )\n Computes the absolute value of a double-precision complex floating-point\n number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n ~5.831\n\n See Also\n --------\n base.cabs2, base.abs\n","base.cabs2":"\nbase.cabs2( z )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n 34.0\n\n See Also\n --------\n base.cabs, base.abs2\n","base.cabs2f":"\nbase.cabs2f( z )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n 34.0\n\n See Also\n --------\n base.cabs2, base.cabsf, base.abs2f\n","base.cabsf":"\nbase.cabsf( z )\n Computes the absolute value of a single-precision complex floating-point\n number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n ~5.831\n\n See Also\n --------\n base.cabs, base.cabs2f, base.absf\n","base.cadd":"\nbase.cadd( z1, z2 )\n Adds two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var out = base.cadd( z, z )\n \n > var re = real( out )\n 10.0\n > var im = imag( out )\n 6.0\n\n\nbase.cadd.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Adds two double-precision complex floating-point numbers and assigns results\n to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cadd.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n\nbase.cadd.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Adds two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cadd.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.cdiv, base.cmul, base.csub\n","base.cadd.assign":"\nbase.cadd.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Adds two double-precision complex floating-point numbers and assigns results\n to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cadd.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ 3.0, 4.0 ]","base.cadd.strided":"\nbase.cadd.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Adds two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cadd.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.cdiv, base.cmul, base.csub","base.caddf":"\nbase.caddf( z1, z2 )\n Adds two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var out = base.caddf( z, z )\n \n > var re = realf( out )\n 10.0\n > var im = imagf( out )\n 6.0\n\n\nbase.caddf.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Adds two single-precision complex floating-point numbers and assigns results\n to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float32Array( 2 );\n > base.caddf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n\nbase.caddf.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Adds two single-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float32Array( [ 5.0, 3.0 ] );\n > var z2 = new Float32Array( [ -2.0, 1.0 ] );\n > var out = new Float32Array( 2 );\n > base.caddf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.cadd, base.cmulf, base.csubf\n","base.caddf.assign":"\nbase.caddf.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Adds two single-precision complex floating-point numbers and assigns results\n to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float32Array( 2 );\n > base.caddf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ 3.0, 4.0 ]","base.caddf.strided":"\nbase.caddf.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Adds two single-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float32Array( [ 5.0, 3.0 ] );\n > var z2 = new Float32Array( [ -2.0, 1.0 ] );\n > var out = new Float32Array( 2 );\n > base.caddf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.cadd, base.cmulf, base.csubf","base.camelcase":"\nbase.camelcase( str )\n Converts a string to camel case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Camel-cased string.\n\n Examples\n --------\n > var out = base.camelcase( 'Hello World!' )\n 'helloWorld'\n > out = base.camelcase( 'beep boop' )\n 'beepBoop'\n\n See Also\n --------\n base.constantcase, base.lowercase, base.snakecase, base.uppercase","base.capitalize":"\nbase.capitalize( str )\n Capitalizes the first character in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = base.capitalize( 'beep' )\n 'Beep'\n > out = base.capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n base.lowercase, base.uppercase\n","base.cbrt":"\nbase.cbrt( x )\n Computes the cube root of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrt( 64.0 )\n 4.0\n > y = base.cbrt( 27.0 )\n 3.0\n > y = base.cbrt( 0.0 )\n 0.0\n > y = base.cbrt( -0.0 )\n -0.0\n > y = base.cbrt( -9.0 )\n ~-2.08\n > y = base.cbrt( NaN )\n NaN\n\n See Also\n --------\n base.pow, base.sqrt\n","base.cbrtf":"\nbase.cbrtf( x )\n Computes the cube root of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrtf( 64.0 )\n 4.0\n > y = base.cbrtf( 27.0 )\n 3.0\n > y = base.cbrtf( 0.0 )\n 0.0\n > y = base.cbrtf( -0.0 )\n -0.0\n > y = base.cbrtf( -9.0 )\n ~-2.08\n > y = base.cbrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.sqrtf\n","base.cceil":"\nbase.cceil( z )\n Rounds each component of a double-precision complex floating-point number\n toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n [ -1.0, 3.0 ]\n\n See Also\n --------\n base.cceiln, base.cfloor, base.cround\n","base.cceilf":"\nbase.cceilf( z )\n Rounds each component of a single-precision complex floating-point number\n toward positive infinity.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n [ -1.0, 3.0 ]\n\n See Also\n --------\n base.cceil\n","base.cceiln":"\nbase.cceiln( z, n )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n [ 5.56, -3.33 ]\n\n See Also\n --------\n base.cceil, base.cfloorn, base.croundn\n","base.ccis":"\nbase.ccis( z )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.ccis( new Complex128( 0.0, 0.0 ) )\n [ 1.0, 0.0 ]\n > y = base.ccis( new Complex128( 1.0, 0.0 ) )\n [ ~0.540, ~0.841 ]\n\n","base.cdiv":"\nbase.cdiv( z1, z2 )\n Divides two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( -13.0, -1.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var y = base.cdiv( z1, z2 )\n \n > var re = real( y )\n 5.0\n > var im = imag( y )\n 3.0\n\n\nbase.cdiv.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Divides two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cdiv.assign( -13.0, -1.0, -2.0, 1.0, out, 1, 0 )\n [ 5.0, 3.0 ]\n\n\nbase.cdiv.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Divides two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ -13.0, -1.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cdiv.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n base.cadd, base.cmul, base.csub","base.cdiv.assign":"\nbase.cdiv.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Divides two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cdiv.assign( -13.0, -1.0, -2.0, 1.0, out, 1, 0 )\n [ 5.0, 3.0 ]","base.cdiv.strided":"\nbase.cdiv.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Divides two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ -13.0, -1.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cdiv.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n base.cadd, base.cmul, base.csub","base.ceil":"\nbase.ceil( x )\n Rounds a double-precision floating-point number toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil( 3.14 )\n 4.0\n > y = base.ceil( -4.2 )\n -4.0\n > y = base.ceil( -4.6 )\n -4.0\n > y = base.ceil( 9.5 )\n 10.0\n > y = base.ceil( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceiln, base.floor, base.round\n","base.ceil2":"\nbase.ceil2( x )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil2( 3.14 )\n 4.0\n > y = base.ceil2( -4.2 )\n -4.0\n > y = base.ceil2( -4.6 )\n -4.0\n > y = base.ceil2( 9.5 )\n 16.0\n > y = base.ceil2( 13.0 )\n 16.0\n > y = base.ceil2( -13.0 )\n -8.0\n > y = base.ceil2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil10, base.floor2, base.round2\n","base.ceil10":"\nbase.ceil10( x )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil10( 3.14 )\n 10.0\n > y = base.ceil10( -4.2 )\n -1.0\n > y = base.ceil10( -4.6 )\n -1.0\n > y = base.ceil10( 9.5 )\n 10.0\n > y = base.ceil10( 13.0 )\n 100.0\n > y = base.ceil10( -13.0 )\n -10.0\n > y = base.ceil10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil2, base.floor10, base.round10\n","base.ceilb":"\nbase.ceilb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.ceilb( 3.14159, -4, 10 )\n 3.1416\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.ceilb( 3.14159, 0, 2 )\n 4.0\n\n // Round to nearest multiple of two toward positive infinity:\n > y = base.ceilb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceil, base.ceiln, base.floorb, base.roundb\n","base.ceilf":"\nbase.ceilf( x )\n Rounds a single-precision floating-point number toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilf( 3.14 )\n 4.0\n > y = base.ceilf( -4.2 )\n -4.0\n > y = base.ceilf( -4.6 )\n -4.0\n > y = base.ceilf( 9.5 )\n 10.0\n > y = base.ceilf( -0.0 )\n -0.0\n\n See Also\n --------\n base.floorf\n","base.ceiln":"\nbase.ceiln( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.ceiln( 3.14159, -2 )\n 3.15\n\n // If `n = 0`, standard round toward positive infinity behavior:\n > y = base.ceiln( 3.14159, 0 )\n 4.0\n\n // Round to nearest thousand:\n > y = base.ceiln( 12368.0, 3 )\n 13000.0\n\n\n See Also\n --------\n base.ceil, base.ceilb, base.floorn, base.roundn\n","base.ceilsd":"\nbase.ceilsd( x, n, b )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilsd( 3.14159, 5, 10 )\n 3.1416\n > y = base.ceilsd( 3.14159, 1, 10 )\n 4.0\n > y = base.ceilsd( 12368.0, 2, 10 )\n 13000.0\n > y = base.ceilsd( 0.0313, 2, 2 )\n 0.046875\n\n See Also\n --------\n base.ceil, base.floorsd, base.roundsd, base.truncsd\n","base.cexp":"\nbase.cexp( z )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.cexp( new Complex128( 0.0, 0.0 ) )\n [ 1.0, 0.0 ]\n > y = base.cexp( new Complex128( 0.0, 1.0 ) )\n [ ~0.540, ~0.841 ]\n\n","base.cflipsign":"\nbase.cflipsign( z, y )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\n [ 4.2, -5.5 ]\n\n See Also\n --------\n base.cneg, base.csignum\n","base.cflipsignf":"\nbase.cflipsignf( z, y )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\n [ 4.0, -5.0 ]\n\n See Also\n --------\n base.cnegf, base.cflipsign\n","base.cfloor":"\nbase.cfloor( z )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n base.cceil, base.cfloorn, base.cround\n","base.cfloorn":"\nbase.cfloorn( z, n )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n z: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\n [ 5.55, -3.34 ]\n\n See Also\n --------\n base.cceiln, base.cfloor, base.croundn\n","base.cidentity":"\nbase.cidentity( z )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex128\n Input value.\n\n Returns\n -------\n v: Complex128\n Input value.\n\n Examples\n --------\n > var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\n \n > var re = real( v )\n -1.0\n > var img = imag( v )\n 2.0\n\n See Also\n --------\n base.cidentityf, base.identity\n","base.cidentityf":"\nbase.cidentityf( z )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex64\n Input value.\n\n Returns\n -------\n v: Complex64\n Input value.\n\n Examples\n --------\n > var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\n \n > var re = realf( v )\n -1.0\n > var img = imagf( v )\n 2.0\n\n See Also\n --------\n base.cidentity, base.identityf\n","base.cinv":"\nbase.cinv( z )\n Computes the inverse of a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n [ 0.1, -0.2 ]\n\n See Also\n --------\n base.cdiv, base.cinvf\n","base.cinvf":"\nbase.cinvf( z )\n Computes the inverse of a single-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cinvf( new Complex64( 2.0, 4.0 ) )\n [ ~0.1, ~-0.2 ]\n\n See Also\n --------\n base.cinv\n","base.clamp":"\nbase.clamp( v, min, max )\n Restricts a double-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clamp( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clamp( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clamp( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clamp( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clampf, base.wrap\n","base.clampf":"\nbase.clampf( v, min, max )\n Restricts a single-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clampf( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clampf( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clampf( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clampf( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.cmul":"\nbase.cmul( z1, z2 )\n Multiplies two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.cmul( z1, z2 )\n \n > var re = real( out )\n -13.0\n > var im = imag( out )\n -1.0\n\n\nbase.cmul.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n\nbase.cmul.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub\n","base.cmul.assign":"\nbase.cmul.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]","base.cmul.strided":"\nbase.cmul.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub","base.cmulf":"\nbase.cmulf( z1, z2 )\n Multiplies two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.cmulf( z1, z2 )\n \n > var re = realf( out )\n -13.0\n > var im = imagf( out )\n -1.0\n\n\nbase.cmulf.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two single-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float32Array( 2 );\n > base.cmulf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n\nbase.cmulf.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two single-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float32Array( [ 5.0, 3.0 ] );\n > var z2 = new Float32Array( [ -2.0, 1.0 ] );\n > var out = new Float32Array( 2 );\n > base.cmulf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.caddf, base.cmul, base.csubf\n","base.cmulf.assign":"\nbase.cmulf.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two single-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float32Array( 2 );\n > base.cmulf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]","base.cmulf.strided":"\nbase.cmulf.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two single-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float32Array( [ 5.0, 3.0 ] );\n > var z2 = new Float32Array( [ -2.0, 1.0 ] );\n > var out = new Float32Array( 2 );\n > base.cmulf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.caddf, base.cmul, base.csubf","base.cneg":"\nbase.cneg( z )\n Negates a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( -4.2, 5.5 )\n \n > var v = base.cneg( z )\n \n > var re = real( v )\n 4.2\n > var im = imag( v )\n -5.5\n\n See Also\n --------\n base.cabs\n","base.cnegf":"\nbase.cnegf( z )\n Negates a single-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( -4.0, 5.0 )\n \n > var v = base.cnegf( z )\n \n > var re = realf( v )\n 4.0\n > var im = imagf( v )\n -5.0\n\n See Also\n --------\n base.cneg, base.cabsf\n","base.codePointAt":"\nbase.codePointAt( str, idx, backward )\n Returns a Unicode code point from a string at a specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n idx: integer\n Position. If less than `0`, the string position is determined relative\n to the end of the input string.\n\n backward: boolean\n Backward iteration for low surrogates.\n\n Returns\n -------\n out: integer\n Unicode code point.\n\n Examples\n --------\n > var out = base.codePointAt( 'last man standing', 4, false )\n 32\n > out = base.codePointAt( 'presidential election', 8, true )\n 116\n > out = base.codePointAt( 'अनुच्छेद', 2, false )\n 2369\n > out = base.codePointAt( '🌷', 1, true )\n 127799\n","base.constantcase":"\nbase.constantcase( str )\n Converts a string to constant case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Constant-cased string.\n\n Examples\n --------\n > var out = base.constantcase( 'Hello World!' )\n 'HELLO_WORLD'\n > out = base.constantcase( 'I am a tiny little teapot' )\n 'I_AM_A_TINY_LITTLE_TEAPOT'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.continuedFraction":"\nbase.continuedFraction( generator[, options] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n\n `generator` can be either a function which returns an array with two\n elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n By default, the function computes\n\n a1\n ---------------\n b1 + a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n To evaluate\n\n b0 +\t a1\n ---------------\n b1 +\t a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n set the `keep` option to `true`.\n\n Parameters\n ----------\n generator: Function\n Function returning terms of continued fraction expansion.\n\n options: Object (optional)\n Options.\n\n options.maxIter: integer (optional)\n Maximum number of iterations. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n current term times the tolerance. Default: `2.22e-16`.\n\n options.keep: boolean (optional)\n Boolean indicating whether to keep the `b0` term in the continued\n fraction. Default: `false`.\n\n Returns\n -------\n out: number\n Value of continued fraction.\n\n Examples\n --------\n // Continued fraction for (e-1)^(-1):\n > function closure() {\n ... var i = 0;\n ... return function() {\n ... i += 1;\n ... return [ i, i ];\n ... };\n ... };\n > var gen = closure();\n > var out = base.continuedFraction( gen )\n ~0.582\n\n // Using an ES6 generator:\n > function* generator() {\n ... var i = 0;\n ... while ( true ) {\n ... i += 1;\n ... yield [ i, i ];\n ... }\n ... };\n > gen = generator();\n > out = base.continuedFraction( gen )\n ~0.582\n\n // Set options:\n > out = base.continuedFraction( generator(), { 'keep': true } )\n ~1.718\n > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n ~0.582\n > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n ~0.579\n\n","base.copysign":"\nbase.copysign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysign( -3.14, 10.0 )\n 3.14\n > z = base.copysign( 3.14, -1.0 )\n -3.14\n > z = base.copysign( 1.0, -0.0 )\n -1.0\n > z = base.copysign( -3.14, -0.0 )\n -3.14\n > z = base.copysign( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.flipsign\n","base.copysignf":"\nbase.copysignf( x, y )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Single-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysignf( -3.0, 10.0 )\n 3.0\n > z = base.copysignf( 3.0, -1.0 )\n -3.0\n > z = base.copysignf( 1.0, -0.0 )\n -1.0\n > z = base.copysignf( -3.0, -0.0 )\n -3.0\n > z = base.copysignf( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.copysign, base.flipsignf\n","base.cos":"\nbase.cos( x )\n Computes the cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cos( 0.0 )\n 1.0\n > y = base.cos( PI/4.0 )\n ~0.707\n > y = base.cos( -PI/6.0 )\n ~0.866\n > y = base.cos( NaN )\n NaN\n\n See Also\n --------\n base.cospi, base.cosm1, base.sin, base.tan\n","base.cosd":"\nbase.cosd( x )\n Computes the cosine of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cosd( 0.0 )\n 1.0\n > y = base.cosd( 90.0 )\n 0.0\n > y = base.cosd( 60.0 )\n ~0.5\n > y = base.cosd( NaN )\n NaN\n\n See Also\n --------\n base.tand\n","base.cosh":"\nbase.cosh( x )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic cosine.\n\n Examples\n --------\n > var y = base.cosh( 0.0 )\n 1.0\n > y = base.cosh( 2.0 )\n ~3.762\n > y = base.cosh( -2.0 )\n ~3.762\n > y = base.cosh( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinh, base.tanh\n","base.cosm1":"\nbase.cosm1( x )\n Computes the cosine of a number minus one.\n\n This function should be used instead of manually calculating `cos(x)-1` when\n `x` is near unity.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine minus one.\n\n Examples\n --------\n > var y = base.cosm1( 0.0 )\n 0.0\n > y = base.cosm1( PI/4.0 )\n ~-0.293\n > y = base.cosm1( -PI/6.0 )\n ~-0.134\n > y = base.cosm1( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cospi":"\nbase.cospi( x )\n Computes the value of `cos(πx)`.\n\n This function computes `cos(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.cospi( 0.0 )\n 1.0\n > y = base.cospi( 0.5 )\n 0.0\n > y = base.cospi( 0.1 )\n ~0.951\n > y = base.cospi( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cot":"\nbase.cot( x )\n Computes the cotangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cotangent.\n\n Examples\n --------\n > var y = base.cot( 0.0 )\n Infinity\n > y = base.cot( -PI/4.0 )\n ~-1.0\n > y = base.cot( PI/4.0 )\n ~1.0\n > y = base.cot( NaN )\n NaN\n\n See Also\n --------\n base.csc, base.tan\n","base.cotd":"\nbase.cotd( x )\n Computes the cotangent of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cotangent.\n\n Examples\n --------\n > var y = base.cotd( 0.0 )\n Infinity\n > y = base.cotd( 90.0 )\n 0.0\n > y = base.cotd( 60.0 )\n ~0.58\n > y = base.cotd( NaN )\n NaN\n\n See Also\n --------\n base.cscd, base.secd, base.tand\n","base.coth":"\nbase.coth( x )\n Computes the hyperbolic cotangent of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic cotangent.\n\n Examples\n --------\n > var y = base.coth( 0.0 )\n Infinity\n > y = base.coth( -0.0 )\n -Infinity\n > y = base.coth( 2.0 )\n ~1.0373\n > y = base.coth( -2.0 )\n ~-1.0373\n > y = base.coth( +Infinity )\n ~1\n > y = base.coth( -Infinity )\n ~-1\n > y = base.coth( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.cot, base.csch, base.tanh\n","base.covercos":"\nbase.covercos( x )\n Computes the coversed cosine.\n\n The coversed cosine is defined as `1 + sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed cosine.\n\n Examples\n --------\n > var y = base.covercos( 3.14 )\n ~1.0016\n > y = base.covercos( -4.2 )\n ~1.8716\n > y = base.covercos( -4.6 )\n ~1.9937\n > y = base.covercos( 9.5 )\n ~0.9248\n > y = base.covercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.coversin, base.vercos\n","base.coversin":"\nbase.coversin( x )\n Computes the coversed sine.\n\n The coversed sine is defined as `1 - sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed sine.\n\n Examples\n --------\n > var y = base.coversin( 3.14 )\n ~0.9984\n > y = base.coversin( -4.2 )\n ~0.1284\n > y = base.coversin( -4.6 )\n ~0.0063\n > y = base.coversin( 9.5 )\n ~1.0752\n > y = base.coversin( -0.0 )\n 1.0\n\n See Also\n --------\n base.covercos, base.versin\n","base.cphase":"\nbase.cphase( z )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n\n The argument of a complex number, also known as the phase, is the angle of\n the radius extending from the origin to the complex number plotted in the\n complex plane and the positive real axis.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n phi: number\n Argument.\n\n Examples\n --------\n > var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n ~0.5404\n\n See Also\n --------\n base.cabs\n","base.cpolar":"\nbase.cpolar( z )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Array\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n [ ~5.83, ~0.5404 ]\n\n\nbase.cpolar.assign( z, out, stride, offset )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n out: Array|TypedArray|Object\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase","base.cpolar.assign":"\nbase.cpolar.assign( z, out, stride, offset )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n out: Array|TypedArray|Object\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase","base.cround":"\nbase.cround( z )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Rounded complex number.\n\n Examples\n --------\n > var v = base.cround( new Complex128( 5.5, 3.3 ) )\n [ 6.0, 3.0 ]\n\n See Also\n --------\n base.cceil, base.cfloor, base.croundn\n","base.croundn":"\nbase.croundn( z, n )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\n [ 5.56, -3.34 ]\n\n See Also\n --------\n base.cceiln, base.cfloorn, base.cround\n","base.csc":"\nbase.csc( x )\n Computes the cosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosecant.\n\n Examples\n --------\n > var y = base.csc( 0.0 )\n Infinity\n > y = base.csc( PI/2.0 )\n ~1.0\n > y = base.csc( -PI/6.0 )\n ~-2.0\n > y = base.csc( NaN )\n NaN\n\n See Also\n --------\n base.cot, base.sin","base.cscd":"\nbase.cscd( x )\n Computes the cosecant of a degree.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cosecant.\n\n Examples\n --------\n > var y = base.cscd( 1.0 )\n ~57.30\n > y = base.cscd( PI )\n ~18.25\n > y = base.cscd( -PI )\n ~-18.25\n > y = base.cscd( NaN )\n NaN\n\n See Also\n --------\n base.cotd, base.secd\n","base.csch":"\nbase.csch( x )\n Computes the hyperbolic cosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic cosecant.\n\n Examples\n --------\n > var y = base.csch( +0.0 )\n +Infinity\n > var y = base.csch( -0.0 )\n -Infinity\n > var y = base.csch( +Infinity )\n +0.0\n > var y = base.csch( -Infinity )\n -0.0\n > y = base.csch( 2.0 )\n ~0.2757\n > y = base.csch( -2.0 )\n ~-0.2757\n > y = base.csch( NaN )\n NaN\n\n See Also\n --------\n base.acsch, base.csc, base.coth, base.sinh\n","base.csignum":"\nbase.csignum( z )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.csignum( new Complex128( -4.2, 5.5 ) )\n [ -0.6069136033622302, 0.79476781392673 ]\n\n See Also\n --------\n base.signum\n","base.csub":"\nbase.csub( z1, z2 )\n Subtracts two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.csub( z1, z2 )\n \n > var re = real( out )\n 7.0\n > var im = imag( out )\n 2.0\n\n See Also\n --------\n base.cadd, base.cdiv, base.cmul\n","base.csubf":"\nbase.csubf( z1, z2 )\n Subtracts two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.csubf( z1, z2 )\n \n > var re = realf( out )\n 7.0\n > var im = imagf( out )\n 2.0\n\n See Also\n --------\n base.caddf, base.cmulf, base.csub\n","base.deg2rad":"\nbase.deg2rad( x )\n Converts an angle from degrees to radians.\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2rad( 90.0 )\n ~1.571\n > r = base.deg2rad( -45.0 )\n ~-0.785\n > r = base.deg2rad( NaN )\n NaN\n\n See Also\n --------\n base.rad2deg\n","base.deg2radf":"\nbase.deg2radf( x )\n Converts an angle from degrees to radians (single-precision).\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2radf( 90.0 )\n ~1.571\n > r = base.deg2radf( -45.0 )\n ~-0.785\n > r = base.deg2radf( NaN )\n NaN\n\n See Also\n --------\n base.deg2rad, base.rad2degf\n","base.digamma":"\nbase.digamma( x )\n Evaluates the digamma function.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.digamma( -2.5 )\n ~1.103\n > y = base.digamma( 1.0 )\n ~-0.577\n > y = base.digamma( 10.0 )\n ~2.252\n > y = base.digamma( NaN )\n NaN\n > y = base.digamma( -1.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.trigamma\n","base.diracDelta":"\nbase.diracDelta( x )\n Evaluates the Dirac delta function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.diracDelta( 3.14 )\n 0.0\n > y = base.diracDelta( 0.0 )\n Infinity\n\n See Also\n --------\n base.kroneckerDelta\n","base.div":"\nbase.div( x, y )\n Divides two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value (dividend).\n\n y: number\n Second input value (divisor).\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.div( -1.0, 5.0 )\n -0.2\n > v = base.div( 2.0, 5.0 )\n 0.4\n > v = base.div( 0.0, 5.0 )\n 0.0\n > v = base.div( -0.0, 5.0 )\n -0.0\n > v = base.div( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.mul, base.sub\n","base.divf":"\nbase.divf( x, y )\n Divides two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value (dividend).\n\n y: number\n Second input value (divisor).\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.divf( -1.0, 5.0 )\n ~-0.2\n > v = base.divf( 2.0, 5.0 )\n ~0.4\n > v = base.divf( 0.0, 5.0 )\n 0.0\n > v = base.divf( -0.0, 5.0 )\n -0.0\n > v = base.divf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.div, base.mulf, base.subf\n","base.dotcase":"\nbase.dotcase( str )\n Converts a string to dot case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Dot-cased string.\n\n Examples\n --------\n > var out = base.dotcase( 'Hello World!' )\n 'hello.world'\n > out = base.dotcase( 'I am a tiny little teapot' )\n 'i.am.a.tiny.little.teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a, b] )\n Returns an arcsine distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be less than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n arcsine: Object\n Distribution instance.\n\n arcsine.a: number\n Minimum support. If set, the value must be less than `b`.\n\n arcsine.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n arcsine.entropy: number\n Read-only property which returns the differential entropy.\n\n arcsine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n arcsine.mean: number\n Read-only property which returns the expected value.\n\n arcsine.median: number\n Read-only property which returns the median.\n\n arcsine.mode: number\n Read-only property which returns the mode.\n\n arcsine.skewness: number\n Read-only property which returns the skewness.\n\n arcsine.stdev: number\n Read-only property which returns the standard deviation.\n\n arcsine.variance: number\n Read-only property which returns the variance.\n\n arcsine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n arcsine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n arcsine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n arcsine.pdf: Function\n Evaluates the probability density function (PDF).\n\n arcsine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n > arcsine.a\n 0.0\n > arcsine.b\n 1.0\n > arcsine.entropy\n ~-0.242\n > arcsine.kurtosis\n -1.5\n > arcsine.mean\n 0.5\n > arcsine.median\n 0.5\n > arcsine.mode\n 0.0\n > arcsine.skewness\n 0.0\n > arcsine.stdev\n ~0.354\n > arcsine.variance\n 0.125\n > arcsine.cdf( 0.8 )\n ~0.705\n > arcsine.logcdf( 0.8 )\n ~-0.35\n > arcsine.logpdf( 0.4 )\n ~-0.431\n > arcsine.pdf( 0.8 )\n ~0.796\n > arcsine.quantile( 0.8 )\n ~0.905\n\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n ~0.795\n > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n ~0.333\n > y = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705\n\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a, b )\n Returns the differential entropy of an arcsine distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n ~-0.242\n > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n ~1.838\n > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n ~1.55\n\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a, b )\n Returns the excess kurtosis of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n -1.5\n\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n ~-0.229\n > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n ~-1.1\n > y = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35\n\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n ~-1.838\n > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n ~-0.308\n > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity\n\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a, b )\n Returns the expected value of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a, b )\n Returns the median of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.arcsine.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a, b )\n Returns the mode of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.mode( 4.0, 12.0 )\n 4.0\n > v = base.dists.arcsine.mode( 2.0, 8.0 )\n 2.0\n\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x, a, b )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n ~0.159\n > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n ~0.735\n > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p, a, b )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n ~0.905\n > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n ~5.0\n\n > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618\n\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a, b )\n Returns the skewness of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a, b )\n Returns the standard deviation of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n ~0.354\n > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n ~2.121\n\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a, b )\n Returns the variance of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n ~0.125\n > v = base.dists.arcsine.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.variance( 2.0, 8.0 )\n ~4.5\n\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p] )\n Returns a Bernoulli distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n bernoulli: Object\n Distribution instance.\n\n bernoulli.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n bernoulli.entropy: number\n Read-only property which returns the differential entropy.\n\n bernoulli.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n bernoulli.mean: number\n Read-only property which returns the expected value.\n\n bernoulli.median: number\n Read-only property which returns the median.\n\n bernoulli.skewness: number\n Read-only property which returns the skewness.\n\n bernoulli.stdev: number\n Read-only property which returns the standard deviation.\n\n bernoulli.variance: number\n Read-only property which returns the variance.\n\n bernoulli.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n bernoulli.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n bernoulli.pmf: Function\n Evaluates the probability mass function (PMF).\n\n bernoulli.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n > bernoulli.p\n 0.6\n > bernoulli.entropy\n ~0.673\n > bernoulli.kurtosis\n ~-1.833\n > bernoulli.mean\n 0.6\n > bernoulli.median\n 1.0\n > bernoulli.skewness\n ~-0.408\n > bernoulli.stdev\n ~0.49\n > bernoulli.variance\n ~0.24\n > bernoulli.cdf( 0.5 )\n 0.4\n > bernoulli.mgf( 3.0 )\n ~12.451\n > bernoulli.pmf( 0.0 )\n 0.4\n > bernoulli.quantile( 0.7 )\n 1.0\n\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n 0.5\n > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n 0.9\n > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n 0.0\n > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n 1.0\n > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.bernoulli.cdf( 0.0, NaN )\n NaN\n // Invalid probability:\n > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5\n\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.bernoulli.entropy( 0.1 )\n ~0.325\n > v = base.dists.bernoulli.entropy( 0.5 )\n ~0.693\n\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.bernoulli.kurtosis( 0.1 )\n ~5.111\n > v = base.dists.bernoulli.kurtosis( 0.5 )\n -2.0\n\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mean( 0.1 )\n 0.1\n > v = base.dists.bernoulli.mean( 0.5 )\n 0.5\n\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p )\n Returns the median of a Bernoulli distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.bernoulli.median( 0.1 )\n 0\n > v = base.dists.bernoulli.median( 0.8 )\n 1\n\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n ~1.111\n > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n ~1.246\n > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855\n\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n\n For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n `0` for `p = 0.5`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mode( 0.1 )\n 0\n > v = base.dists.bernoulli.mode( 0.8 )\n 1\n\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x, p )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n 0.3\n > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n 0.3\n > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.bernoulli.pmf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5\n\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r, p )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n 1\n > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n 0\n > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n 0\n\n > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1\n\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.bernoulli.skewness( 0.1 )\n ~2.667\n > v = base.dists.bernoulli.skewness( 0.5 )\n 0.0\n\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.bernoulli.stdev( 0.1 )\n ~0.3\n > v = base.dists.bernoulli.stdev( 0.5 )\n 0.5\n\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.bernoulli.variance( 0.1 )\n ~0.09\n > v = base.dists.bernoulli.variance( 0.5 )\n 0.25\n\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α, β] )\n Returns a beta distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n beta: Object\n Distribution instance.\n\n beta.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n beta.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n beta.entropy: number\n Read-only property which returns the differential entropy.\n\n beta.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n beta.mean: number\n Read-only property which returns the expected value.\n\n beta.median: number\n Read-only property which returns the median.\n\n beta.mode: number\n Read-only property which returns the mode.\n\n beta.skewness: number\n Read-only property which returns the skewness.\n\n beta.stdev: number\n Read-only property which returns the standard deviation.\n\n beta.variance: number\n Read-only property which returns the variance.\n\n beta.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n beta.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n beta.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n beta.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n beta.pdf: Function\n Evaluates the probability density function (PDF).\n\n beta.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n > beta.alpha\n 1.0\n > beta.beta\n 1.0\n > beta.entropy\n 0.0\n > beta.kurtosis\n -1.2\n > beta.mean\n 0.5\n > beta.median\n 0.5\n > beta.mode\n NaN\n > beta.skewness\n 0.0\n > beta.stdev\n ~0.289\n > beta.variance\n ~0.0833\n > beta.cdf( 0.8 )\n 0.8\n > beta.logcdf( 0.8 )\n ~-0.223\n > beta.logpdf( 1.0 )\n 0.0\n > beta.mgf( 3.14 )\n ~7.0394\n > beta.pdf( 1.0 )\n 1.0\n > beta.quantile( 0.8 )\n 0.8\n\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n ~0.813\n > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n ~0.104\n > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n ~0.967\n > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369\n\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α, β )\n Returns the differential entropy of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.beta.entropy( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.entropy( 4.0, 12.0 )\n ~-0.869\n > v = base.dists.beta.entropy( 8.0, 2.0 )\n ~-0.795\n\n > v = base.dists.beta.entropy( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.entropy( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.entropy( 2.0, NaN )\n NaN\n > v = base.dists.beta.entropy( NaN, 2.0 )\n NaN\n\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α, β )\n Returns the excess kurtosis of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n -1.2\n > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n ~0.082\n > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n ~0.490\n\n > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.beta.kurtosis( NaN, 2.0 )\n NaN\n\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n ~-0.208\n > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n ~-2.263\n > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n ~-0.034\n > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997\n\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n ~0.223\n > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n ~-0.041\n > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n ~-0.556\n > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364\n\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364","base.dists.beta.mean":"\nbase.dists.beta.mean( α, β )\n Returns the expected value of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.beta.mean( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.mean( 4.0, 12.0 )\n 0.25\n > v = base.dists.beta.mean( 8.0, 2.0 )\n 0.8\n\n","base.dists.beta.median":"\nbase.dists.beta.median( α, β )\n Returns the median of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.beta.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.median( 4.0, 12.0 )\n ~0.239\n > v = base.dists.beta.median( 8.0, 2.0 )\n ~0.820\n\n > v = base.dists.beta.median( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.median( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.median( 2.0, NaN )\n NaN\n > v = base.dists.beta.median( NaN, 2.0 )\n NaN\n\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n ~1.297\n > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n ~1.186\n > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n ~5.575\n > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n ~0.676\n\n > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168\n\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168","base.dists.beta.mode":"\nbase.dists.beta.mode( α, β )\n Returns the mode of a beta distribution.\n\n If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.beta.mode( 4.0, 12.0 )\n ~0.214\n > v = base.dists.beta.mode( 8.0, 2.0 )\n ~0.875\n > v = base.dists.beta.mode( 1.0, 1.0 )\n NaN\n\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n 1.25\n > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n ~0.96\n > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n ~0.573\n > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695\n\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p, α, β )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n ~0.894\n > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n ~0.686\n > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433\n\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α, β )\n Returns the skewness of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.beta.skewness( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.skewness( 4.0, 12.0 )\n ~0.529\n > v = base.dists.beta.skewness( 8.0, 2.0 )\n ~-0.829\n\n > v = base.dists.beta.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.skewness( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.skewness( 2.0, NaN )\n NaN\n > v = base.dists.beta.skewness( NaN, 2.0 )\n NaN\n\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α, β )\n Returns the standard deviation of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.beta.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.beta.stdev( 4.0, 12.0 )\n ~0.105\n > v = base.dists.beta.stdev( 8.0, 2.0 )\n ~0.121\n\n > v = base.dists.beta.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.stdev( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.stdev( 2.0, NaN )\n NaN\n > v = base.dists.beta.stdev( NaN, 2.0 )\n NaN\n\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α, β )\n Returns the variance of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.beta.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.beta.variance( 4.0, 12.0 )\n ~0.011\n > v = base.dists.beta.variance( 8.0, 2.0 )\n ~0.015\n\n > v = base.dists.beta.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.variance( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.variance( 2.0, NaN )\n NaN\n > v = base.dists.beta.variance( NaN, 2.0 )\n NaN\n\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α, β] )\n Returns a beta prime distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n betaprime: Object\n Distribution instance.\n\n betaprime.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n betaprime.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n betaprime.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n betaprime.mean: number\n Read-only property which returns the expected value.\n\n betaprime.mode: number\n Read-only property which returns the mode.\n\n betaprime.skewness: number\n Read-only property which returns the skewness.\n\n betaprime.stdev: number\n Read-only property which returns the standard deviation.\n\n betaprime.variance: number\n Read-only property which returns the variance.\n\n betaprime.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n betaprime.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n betaprime.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n betaprime.pdf: Function\n Evaluates the probability density function (PDF).\n\n betaprime.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n > betaprime.alpha\n 6.0\n > betaprime.beta\n 5.0\n > betaprime.kurtosis\n 44.4\n > betaprime.mean\n 1.5\n > betaprime.mode\n ~0.833\n > betaprime.skewness\n ~3.578\n > betaprime.stdev\n ~1.118\n > betaprime.variance\n 1.25\n > betaprime.cdf( 0.8 )\n ~0.25\n > betaprime.logcdf( 0.8 )\n ~-1.387\n > betaprime.logpdf( 1.0 )\n ~-0.486\n > betaprime.pdf( 1.0 )\n ~0.615\n > betaprime.quantile( 0.8 )\n ~2.06\n\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n ~0.333\n > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n ~0.539\n > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n ~0.074\n > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n ~0.38\n > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319\n\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α, β )\n Returns the excess kurtosis of a beta prime distribution.\n\n If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n ~26.143\n > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n ~5.764\n > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n ~19.962\n\n > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n NaN\n\n > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n NaN\n\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n ~-1.099\n > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n ~-0.618\n > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n ~-2.603\n > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n ~-0.968\n > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143\n\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n ~-0.811\n > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n ~-0.13\n > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n ~-0.547\n > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n ~-0.43\n > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805\n\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α, β )\n Returns the expected value of a beta prime distribution.\n\n If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n 1.0\n > v = base.dists.betaprime.mean( 4.0, 12.0 )\n ~0.364\n > v = base.dists.betaprime.mean( 8.0, 2.0 )\n 8.0\n\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α, β )\n Returns the mode of a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n 0.0\n > v = base.dists.betaprime.mode( 4.0, 12.0 )\n ~0.231\n > v = base.dists.betaprime.mode( 8.0, 2.0 )\n ~2.333\n\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n ~0.444\n > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n ~0.878\n > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n ~0.579\n > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n ~0.65\n > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447\n\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p, α, β )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n ~8.472\n > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n ~2.187\n > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763\n\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α, β )\n Returns the skewness of a beta prime distribution.\n\n If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n ~6.261\n > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n ~1.724\n > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n ~5.729\n\n > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n NaN\n\n > v = base.dists.betaprime.skewness( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.skewness( NaN, 4.0 )\n NaN\n\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α, β )\n Returns the standard deviation of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n ~1.491\n > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n ~0.223\n > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n ~8.219\n\n > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.stdev( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.stdev( NaN, 3.0 )\n NaN\n\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α, β )\n Returns the variance of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n ~2.222\n > v = base.dists.betaprime.variance( 4.0, 12.0 )\n ~0.05\n > v = base.dists.betaprime.variance( 8.0, 2.5 )\n ~67.556\n\n > v = base.dists.betaprime.variance( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.variance( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.variance( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.variance( NaN, 3.0 )\n NaN\n\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n, p] )\n Returns a binomial distribution object.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials. Must be a positive integer. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n binomial: Object\n Distribution instance.\n\n binomial.n: number\n Number of trials. If set, the value must be a positive integer.\n\n binomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n binomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n binomial.mean: number\n Read-only property which returns the expected value.\n\n binomial.median: number\n Read-only property which returns the median.\n\n binomial.mode: number\n Read-only property which returns the mode.\n\n binomial.skewness: number\n Read-only property which returns the skewness.\n\n binomial.stdev: number\n Read-only property which returns the standard deviation.\n\n binomial.variance: number\n Read-only property which returns the variance.\n\n binomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n binomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n binomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n binomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n binomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n > binomial.n\n 8.0\n > binomial.p\n 0.5\n > binomial.kurtosis\n -0.25\n > binomial.mean\n 4.0\n > binomial.median\n 4.0\n > binomial.mode\n 4.0\n > binomial.skewness\n 0.0\n > binomial.stdev\n ~1.414\n > binomial.variance\n 2.0\n > binomial.cdf( 2.9 )\n ~0.145\n > binomial.logpmf( 3.0 )\n ~-1.52\n > binomial.mgf( 0.2 )\n ~2.316\n > binomial.pmf( 3.0 )\n ~0.219\n > binomial.quantile( 0.8 )\n 5.0\n\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x, n, p )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n ~0.411\n > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n 1.0\n > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n ~0.834\n > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011\n\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n, p )\n Returns the entropy of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.binomial.entropy( 100, 0.1 )\n ~2.511\n > v = base.dists.binomial.entropy( 20, 0.5 )\n ~2.223\n > v = base.dists.binomial.entropy( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.entropy( 20, 1.1 )\n NaN\n > v = base.dists.binomial.entropy( 20, NaN )\n NaN\n\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n, p )\n Returns the excess kurtosis of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n ~0.051\n > v = base.dists.binomial.kurtosis( 20, 0.5 )\n ~-0.1\n > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, 1.1 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, NaN )\n NaN\n\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x, n, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n ~-1.583\n > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n -Infinity\n > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n ~-1.606\n > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n ~-5.108\n > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402\n\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n, p )\n Returns the expected value of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.binomial.mean( 100, 0.1 )\n 10.0\n > v = base.dists.binomial.mean( 20, 0.5 )\n 10.0\n > v = base.dists.binomial.mean( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mean( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mean( 20, NaN )\n NaN\n\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n, p )\n Returns the median of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.binomial.median( 100, 0.1 )\n 10\n > v = base.dists.binomial.median( 20, 0.5 )\n 10\n > v = base.dists.binomial.median( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.median( 20, 1.1 )\n NaN\n > v = base.dists.binomial.median( 20, NaN )\n NaN\n\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t, n, p )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n ~11.471\n > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n ~4.798e+29\n > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n ~99.338\n > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n 1.0\n\n > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n NaN\n\n > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013\n\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n, p )\n Returns the mode of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.binomial.mode( 100, 0.1 )\n 10\n > v = base.dists.binomial.mode( 20, 0.5 )\n 10\n > v = base.dists.binomial.mode( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mode( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mode( 20, NaN )\n NaN\n\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x, n, p )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n ~0.205\n > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n 0.0\n > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n ~0.201\n > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246\n\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r, n, p )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n 3\n > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n 5\n > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n 4\n > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n 0\n > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n 10\n\n > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7\n\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n, p )\n Returns the skewness of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.binomial.skewness( 100, 0.1 )\n ~0.267\n > v = base.dists.binomial.skewness( 20, 0.5 )\n 0.0\n > v = base.dists.binomial.skewness( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.skewness( 20, 1.1 )\n NaN\n > v = base.dists.binomial.skewness( 20, NaN )\n NaN\n\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n, p )\n Returns the standard deviation of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.binomial.stdev( 100, 0.1 )\n 3.0\n > v = base.dists.binomial.stdev( 20, 0.5 )\n ~2.236\n > v = base.dists.binomial.stdev( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.stdev( 20, 1.1 )\n NaN\n > v = base.dists.binomial.stdev( 20, NaN )\n NaN\n\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n, p )\n Returns the variance of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.binomial.variance( 100, 0.1 )\n 9\n > v = base.dists.binomial.variance( 20, 0.5 )\n 5\n > v = base.dists.binomial.variance( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.variance( 20, 1.1 )\n NaN\n > v = base.dists.binomial.variance( 20, NaN )\n NaN\n\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n Returns a Cauchy distribution object.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter. Default: `0.0`.\n\n Ɣ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cauchy: Object\n Distribution instance.\n\n cauchy.x0: number\n Location parameter.\n\n cauchy.gamma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cauchy.entropy: number\n Read-only property which returns the differential entropy.\n\n cauchy.median: number\n Read-only property which returns the median.\n\n cauchy.mode: number\n Read-only property which returns the mode.\n\n cauchy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cauchy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cauchy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cauchy.pdf: Function\n Evaluates the probability density function (PDF).\n\n cauchy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n > cauchy.x0\n 0.0\n > cauchy.gamma\n 1.0\n > cauchy.entropy\n ~2.531\n > cauchy.median\n 0.0\n > cauchy.mode\n 0.0\n > cauchy.cdf( 0.8 )\n ~0.715\n > cauchy.logcdf( 1.0 )\n ~-0.288\n > cauchy.logpdf( 1.0 )\n ~-1.838\n > cauchy.pdf( 1.0 )\n ~0.159\n > cauchy.quantile( 0.8 )\n ~1.376\n\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n ~0.852\n > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n ~0.648\n > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n 0.25\n > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447\n\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0, Ɣ )\n Returns the differential entropy of a Cauchy distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n ~4.477\n > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n ~1.838\n > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n ~-0.16\n > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n ~-0.435\n > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n ~-1.386\n > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804\n\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n ~-1.838\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n ~-3.457\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n ~-2.349\n > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838\n\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0, Ɣ )\n Returns the median of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.cauchy.median( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.median( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.median( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0, Ɣ )\n Returns the mode of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.mode( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.mode( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n ~0.159\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n ~0.0315\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n ~0.095\n > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159\n\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n ~0.547\n > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n ~12.753\n > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n ~3.845\n\n > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chi.cdf( 2.0, 3.0 )\n ~0.739\n > y = base.dists.chi.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chi.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chi.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chi.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chi.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chi.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77\n\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k] )\n Returns a chi distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chi: Object\n Distribution instance.\n\n chi.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chi.entropy: number\n Read-only property which returns the differential entropy.\n\n chi.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chi.mean: number\n Read-only property which returns the expected value.\n\n chi.mode: number\n Read-only property which returns the mode.\n\n chi.skewness: number\n Read-only property which returns the skewness.\n\n chi.stdev: number\n Read-only property which returns the standard deviation.\n\n chi.variance: number\n Read-only property which returns the variance.\n\n chi.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chi.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n chi.pdf: Function\n Evaluates the probability density function (PDF).\n\n chi.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chi = base.dists.chi.Chi( 6.0 );\n > chi.k\n 6.0\n > chi.entropy\n ~1.04\n > chi.kurtosis\n ~0.025\n > chi.mean\n ~2.35\n > chi.mode\n ~2.236\n > chi.skewness\n ~0.318\n > chi.stdev\n ~0.691\n > chi.variance\n ~0.478\n > chi.cdf( 1.0 )\n ~0.014\n > chi.logpdf( 1.5 )\n ~-1.177\n > chi.pdf( 1.5 )\n ~0.308\n > chi.quantile( 0.5 )\n ~2.313\n\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k )\n Returns the differential entropy of a chi distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chi.entropy( 11.0 )\n ~1.056\n > v = base.dists.chi.entropy( 1.5 )\n ~0.878\n\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k )\n Returns the excess kurtosis of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chi.kurtosis( 9.0 )\n ~0.011\n > v = base.dists.chi.kurtosis( 1.5 )\n ~0.424\n\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n ~-4.35\n > y = base.dists.chi.logpdf( 0.7, 0.7 )\n ~-0.622\n > y = base.dists.chi.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086\n\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086","base.dists.chi.mean":"\nbase.dists.chi.mean( k )\n Returns the expected value of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chi.mean( 11.0 )\n ~3.242\n > v = base.dists.chi.mean( 4.5 )\n ~2.008\n\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k )\n Returns the mode of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chi.mode( 11.0 )\n ~3.162\n > v = base.dists.chi.mode( 1.5 )\n ~0.707\n\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chi.pdf( 0.3, 4.0 )\n ~0.013\n > y = base.dists.chi.pdf( 0.7, 0.7 )\n ~0.537\n > y = base.dists.chi.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337\n\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p, k )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chi.quantile( 0.8, 1.0 )\n ~1.282\n > y = base.dists.chi.quantile( 0.5, 4.0 )\n ~1.832\n > y = base.dists.chi.quantile( 0.8, 0.1 )\n ~0.116\n > y = base.dists.chi.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chi.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chi.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chi.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chi.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552\n\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k )\n Returns the skewness of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chi.skewness( 11.0 )\n ~0.225\n > v = base.dists.chi.skewness( 1.5 )\n ~0.763\n\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k )\n Returns the standard deviation of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chi.stdev( 11.0 )\n ~0.699\n > v = base.dists.chi.stdev( 1.5 )\n ~0.637\n\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k )\n Returns the variance of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chi.variance( 11.0 )\n ~0.488\n > v = base.dists.chi.variance( 1.5 )\n ~0.406\n\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n ~0.428\n > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chisquare.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727\n\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k] )\n Returns a chi-squared distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chisquare: Object\n Distribution instance.\n\n chisquare.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chisquare.entropy: number\n Read-only property which returns the differential entropy.\n\n chisquare.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chisquare.mean: number\n Read-only property which returns the expected value.\n\n chisquare.median: number\n Read-only property which returns the median.\n\n chisquare.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n chisquare.mode: number\n Read-only property which returns the mode.\n\n chisquare.skewness: number\n Read-only property which returns the skewness.\n\n chisquare.stdev: number\n Read-only property which returns the standard deviation.\n\n chisquare.variance: number\n Read-only property which returns the variance.\n\n chisquare.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chisquare.pdf: Function\n Evaluates the probability density function (PDF).\n\n chisquare.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n > chisquare.k\n 6.0\n > chisquare.entropy\n ~2.541\n > chisquare.kurtosis\n 2.0\n > chisquare.mean\n 6.0\n > chisquare.median\n ~5.348\n > chisquare.mode\n 4.0\n > chisquare.skewness\n ~1.155\n > chisquare.stdev\n ~3.464\n > chisquare.variance\n 12.0\n > chisquare.cdf( 3.0 )\n ~0.191\n > chisquare.mgf( 0.2 )\n ~4.63\n > chisquare.pdf( 1.5 )\n ~0.066\n > chisquare.quantile( 0.5 )\n ~5.348\n\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k )\n Returns the differential entropy of a chi-squared distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chisquare.entropy( 11.0 )\n ~2.901\n > v = base.dists.chisquare.entropy( 1.5 )\n ~1.375\n\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k )\n Returns the excess kurtosis of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chisquare.kurtosis( 9.0 )\n ~1.333\n > v = base.dists.chisquare.kurtosis( 1.5 )\n 8.0\n\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n ~-2.74\n > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n ~-1.295\n > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075\n\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k )\n Returns the expected value of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chisquare.mean( 11.0 )\n 11.0\n > v = base.dists.chisquare.mean( 4.5 )\n 4.5\n\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k )\n Returns the median of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var k = base.dists.chisquare.median( 9.0 )\n ~8.343\n > k = base.dists.chisquare.median( 2.0 )\n ~1.386\n\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t, k )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.chisquare.mgf( 0.4, 2 )\n ~5.0\n > y = base.dists.chisquare.mgf( -1.0, 5.0 )\n ~0.0642\n > y = base.dists.chisquare.mgf( 0.0, 10.0 )\n 1.0\n\n\nbase.dists.chisquare.mgf.factory( k )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n > var y = mymgf( 0.2 )\n ~1.291\n > y = mymgf( 0.4 )\n ~2.236\n\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n > var y = mymgf( 0.2 )\n ~1.291\n > y = mymgf( 0.4 )\n ~2.236","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k )\n Returns the mode of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chisquare.mode( 11.0 )\n 9.0\n > v = base.dists.chisquare.mode( 1.5 )\n 0.0\n\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n ~0.065\n > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n ~0.274\n > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126\n\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p, k )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n ~1.642\n > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n ~3.357\n > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n ~0.014\n > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408\n\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k )\n Returns the skewness of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chisquare.skewness( 11.0 )\n ~0.853\n > v = base.dists.chisquare.skewness( 1.5 )\n ~2.309\n\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k )\n Returns the standard deviation of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chisquare.stdev( 11.0 )\n ~4.69\n > v = base.dists.chisquare.stdev( 1.5 )\n ~1.732\n\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k )\n Returns the variance of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chisquare.variance( 11.0 )\n 22.0\n > v = base.dists.chisquare.variance( 1.5 )\n 3.0\n\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n ~0.971\n > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n ~0.196\n\n > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015\n\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ, s] )\n Returns a raised cosine distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cosine: Object\n Distribution instance.\n\n cosine.mu: number\n Location parameter.\n\n cosine.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cosine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n cosine.mean: number\n Read-only property which returns the expected value.\n\n cosine.median: number\n Read-only property which returns the median.\n\n cosine.mode: number\n Read-only property which returns the mode.\n\n cosine.skewness: number\n Read-only property which returns the skewness.\n\n cosine.stdev: number\n Read-only property which returns the standard deviation.\n\n cosine.variance: number\n Read-only property which returns the variance.\n\n cosine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cosine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cosine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cosine.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n cosine.pdf: Function\n Evaluates the probability density function (PDF).\n\n cosine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n > cosine.mu\n -2.0\n > cosine.s\n 3.0\n > cosine.kurtosis\n ~-0.594\n > cosine.mean\n -2.0\n > cosine.median\n -2.0\n > cosine.mode\n -2.0\n > cosine.skewness\n 0.0\n > cosine.stdev\n ~1.085\n > cosine.variance\n ~1.176\n > cosine.cdf( 0.5 )\n ~0.996\n > cosine.logcdf( 0.5 )\n ~-0.004\n > cosine.logpdf( -1.0 )\n ~-1.386\n > cosine.mgf( 0.2 )\n ~0.686\n > cosine.pdf( -2.0 )\n ~0.333\n > cosine.quantile( 0.9 )\n ~-0.553\n\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ, s )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x, μ, s )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n ~-0.029\n > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n ~-1.632\n\n > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2\n\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n ~-2.485\n > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n ~-3.307\n > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693\n\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ, s )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.cosine.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mean( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mean( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ, s )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.cosine.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.median( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.median( 0.0, NaN )\n NaN\n > y = base.dists.cosine.median( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n ~7.234\n > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n ~1.606e+47\n\n > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n NaN\n > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57\n\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ, s )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.cosine.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mode( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mode( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n ~0.083\n > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n ~0.048\n > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083\n\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p, μ, s )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n ~0.327\n > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n ~4.0\n\n > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586\n\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ, s )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.cosine.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.skewness( 0.0, NaN )\n NaN\n > y = base.dists.cosine.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ, s )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n ~0.362\n > y = base.dists.cosine.stdev( 4.0, 2.0 )\n ~0.723\n > y = base.dists.cosine.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.stdev( 0.0, NaN )\n NaN\n > y = base.dists.cosine.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ, s )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.cosine.variance( 0.0, 1.0 )\n ~0.131\n > y = base.dists.cosine.variance( 4.0, 2.0 )\n ~0.523\n > y = base.dists.cosine.variance( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.variance( 0.0, NaN )\n NaN\n > y = base.dists.cosine.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x, μ )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0\n\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ] )\n Returns a degenerate distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Constant value of distribution.\n\n Returns\n -------\n degenerate: Object\n Distribution instance.\n\n degenerate.mu: number\n Constant value of distribution.\n\n degenerate.entropy: number\n Read-only property which returns the differential entropy.\n\n degenerate.mean: number\n Read-only property which returns the expected value.\n\n degenerate.median: number\n Read-only property which returns the median.\n\n degenerate.stdev: number\n Read-only property which returns the standard deviation.\n\n degenerate.variance: number\n Read-only property which returns the variance.\n\n degenerate.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n degenerate.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n degenerate.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n degenerate.logpmf: Function\n Evaluates the natural logarithm of the probability mass function\n (PMF).\n\n degenerate.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n degenerate.pmf: Function\n Evaluates the probability mass function (PMF).\n\n degenerate.pdf: Function\n Evaluates the probability density function (PDF).\n\n degenerate.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n > degenerate.mu\n 2.0\n > degenerate.entropy\n 0.0\n > degenerate.mean\n 2.0\n > degenerate.mode\n 2.0\n > degenerate.median\n 2.0\n > degenerate.stdev\n 0.0\n > degenerate.variance\n 0.0\n > degenerate.cdf( 0.5 )\n 0.0\n > degenerate.logcdf( 2.5 )\n 0.0\n > degenerate.logpdf( 0.5 )\n -Infinity\n > degenerate.logpmf( 2.5 )\n -Infinity\n > degenerate.mgf( 0.2 )\n ~1.492\n > degenerate.pdf( 2.0 )\n +Infinity\n > degenerate.pmf( 2.0 )\n 1.0\n > degenerate.quantile( 0.7 )\n 2.0\n\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.degenerate.entropy( 20.0 )\n 0.0\n > v = base.dists.degenerate.entropy( -10.0 )\n 0.0\n\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x, μ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logcdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0\n\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x, μ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x, μ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0\n\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.degenerate.mean( 20.0 )\n 20.0\n > v = base.dists.degenerate.mean( -10.0 )\n -10.0\n\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ )\n Returns the median of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.degenerate.median( 20.0 )\n 20.0\n > v = base.dists.degenerate.median( -10.0 )\n -10.0\n\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x, μ )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n ~2.718\n > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n ~403.429\n > y = base.dists.degenerate.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.mgf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718\n\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ )\n Returns the mode of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.degenerate.mode( 20.0 )\n 20.0\n > v = base.dists.degenerate.mode( -10.0 )\n -10.0\n\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x, μ )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.pdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x, μ )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.pmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0\n\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p, μ )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n 2.0\n > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n 4.0\n > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.degenerate.stdev( 20.0 )\n 0.0\n > v = base.dists.degenerate.stdev( -10.0 )\n 0.0\n\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ )\n Returns the variance of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.degenerate.variance( 20.0 )\n 0.0\n > v = base.dists.degenerate.variance( -10.0 )\n 0.0\n\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n ~0.909\n > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n ~0.333\n > y = base.dists.discreteUniform.cdf( PINF, 2, 4 )\n 1.0\n > y = base.dists.discreteUniform.cdf( NINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818\n\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n Returns a discrete uniform distribution object.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n b: integer (optional)\n Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n Returns\n -------\n discreteUniform: Object\n Distribution instance.\n\n discreteUniform.a: integer\n Minimum support. If set, the value must be an integer smaller than or\n equal to `b`.\n\n discreteUniform.b: integer\n Maximum support. If set, the value must be an integer greater than or\n equal to `a`.\n\n discreteUniform.entropy: number\n Read-only property which returns the entropy.\n\n discreteUniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n discreteUniform.mean: number\n Read-only property which returns the expected value.\n\n discreteUniform.median: number\n Read-only property which returns the median.\n\n discreteUniform.skewness: number\n Read-only property which returns the skewness.\n\n discreteUniform.stdev: number\n Read-only property which returns the standard deviation.\n\n discreteUniform.variance: number\n Read-only property which returns the variance.\n\n discreteUniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n discreteUniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n discreteUniform.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n discreteUniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n discreteUniform.pmf: Function\n Evaluates the probability mass function (PMF).\n\n discreteUniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n > discreteUniform.a\n -2\n > discreteUniform.b\n 2\n > discreteUniform.entropy\n ~1.609\n > discreteUniform.kurtosis\n -1.3\n > discreteUniform.mean\n 0.0\n > discreteUniform.median\n 0.0\n > discreteUniform.skewness\n 0.0\n > discreteUniform.stdev\n ~1.414\n > discreteUniform.variance\n 2.0\n > discreteUniform.cdf( 0.8 )\n 0.6\n > discreteUniform.logcdf( 0.5 )\n ~-0.511\n > discreteUniform.logpmf( 1.0 )\n ~-1.609\n > discreteUniform.mgf( 0.8 )\n ~1.766\n > discreteUniform.pmf( 0.0 )\n 0.2\n > discreteUniform.quantile( 0.8 )\n 2.0\n\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a, b )\n Returns the entropy of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.entropy( 0, 1 )\n ~0.693\n > v = base.dists.discreteUniform.entropy( 4, 12 )\n ~2.197\n > v = base.dists.discreteUniform.entropy( 2, 8 )\n ~1.946\n\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a, b )\n Returns the excess kurtosis of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n -2.0\n > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n ~-1.23\n > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n ~-1.214\n\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n ~-0.095\n > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n ~-1.099\n > y = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201\n\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x, a, b )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n ~-1.609\n > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n ~-2.197\n > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity\n\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a, b )\n Returns the expected value of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.mean( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.mean( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.mean( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a, b )\n Returns the median of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.median( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.median( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.median( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n ~689.475\n > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n ~0.697\n > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n ~4.195\n > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n NaN\n > y = base.dists.discreteUniform.mgf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722\n\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x, a, b )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n ~0.2\n > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n 0.0\n > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n ~0.111\n > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0\n\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p, a, b )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n If provided `a > b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n 1\n > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n 5\n\n > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n NaN\n > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n NaN\n\n > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n NaN\n\n > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4\n\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a, b )\n Returns the skewness of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.skewness( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 4, 12 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 2, 8 )\n 0.0\n\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a, b )\n Returns the standard deviation of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.stdev( 0, 1 )\n ~0.5\n > v = base.dists.discreteUniform.stdev( 4, 12 )\n ~2.582\n > v = base.dists.discreteUniform.stdev( 2, 8 )\n 2.0\n\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a, b )\n Returns the variance of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.variance( 0, 1 )\n ~0.25\n > v = base.dists.discreteUniform.variance( 4, 12 )\n ~6.667\n > v = base.dists.discreteUniform.variance( 2, 8 )\n 4.0\n\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n ~0.865\n > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n ~0.323\n > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( PINF, 4, 2.0 )\n 1.0\n > y = base.dists.erlang.cdf( NINF, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264\n\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k, λ )\n Returns the differential entropy of an Erlang distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.erlang.entropy( 1, 1.0 )\n ~1.0\n > v = base.dists.erlang.entropy( 4, 12.0 )\n ~-0.462\n > v = base.dists.erlang.entropy( 8, 2.0 )\n ~1.723\n\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k, λ] )\n Returns an Erlang distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be a positive integer. Default: `1.0`.\n\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n erlang: Object\n Distribution instance.\n\n erlang.k: number\n Shape parameter. If set, the value must be a positive integer.\n\n erlang.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n erlang.entropy: number\n Read-only property which returns the differential entropy.\n\n erlang.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n erlang.mean: number\n Read-only property which returns the expected value.\n\n erlang.mode: number\n Read-only property which returns the mode.\n\n erlang.skewness: number\n Read-only property which returns the skewness.\n\n erlang.stdev: number\n Read-only property which returns the standard deviation.\n\n erlang.variance: number\n Read-only property which returns the variance.\n\n erlang.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n erlang.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n erlang.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n erlang.pdf: Function\n Evaluates the probability density function (PDF).\n\n erlang.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n > erlang.k\n 6\n > erlang.lambda\n 5.0\n > erlang.entropy\n ~0.647\n > erlang.kurtosis\n 1.0\n > erlang.mean\n 1.2\n > erlang.mode\n 1.0\n > erlang.skewness\n ~0.816\n > erlang.stdev\n ~0.49\n > erlang.variance\n 0.24\n > erlang.cdf( 3.0 )\n ~0.997\n > erlang.logpdf( 3.0 )\n ~-4.638\n > erlang.mgf( -0.5 )\n ~0.564\n > erlang.pdf( 3.0 )\n ~0.01\n > erlang.quantile( 0.8 )\n ~1.581\n\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k, λ )\n Returns the excess kurtosis of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n 6.0\n > v = base.dists.erlang.kurtosis( 4, 12.0 )\n 1.5\n > v = base.dists.erlang.kurtosis( 8, 2.0 )\n 0.75\n\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x, k, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n ~-0.1\n > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n ~-0.111\n > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382\n\n\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k, λ )\n Returns the expected value of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.erlang.mean( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.mean( 4, 12.0 )\n ~0.333\n > v = base.dists.erlang.mean( 8, 2.0 )\n 4.0\n\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t, k, λ )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n ~1.429\n > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n ~9.0\n > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n ~0.444\n\n > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25\n\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k, λ )\n Returns the mode of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.erlang.mode( 1, 1.0 )\n 0.0\n > v = base.dists.erlang.mode( 4, 12.0 )\n 0.25\n > v = base.dists.erlang.mode( 8, 2.0 )\n 3.5\n\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n ~0.905\n > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n ~0.895\n > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15\n\n\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p, k, λ )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive number for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n ~2.994\n > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n ~1.836\n\n > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n NaN\n\n > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n NaN\n\n // Non-integer shape parameter:\n > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n NaN\n // Non-positive shape parameter:\n > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452\n\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k, λ )\n Returns the skewness of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.erlang.skewness( 1, 1.0 )\n 2.0\n > v = base.dists.erlang.skewness( 4, 12.0 )\n 1.0\n > v = base.dists.erlang.skewness( 8, 2.0 )\n ~0.707\n\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k, λ )\n Returns the standard deviation of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.erlang.stdev( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.stdev( 4, 12.0 )\n ~0.167\n > v = base.dists.erlang.stdev( 8, 2.0 )\n ~1.414\n\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k, λ )\n Returns the variance of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.erlang.variance( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.variance( 4, 12.0 )\n ~0.028\n > v = base.dists.erlang.variance( 8, 2.0 )\n 2.0\n\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n ~0.181\n > y = base.dists.exponential.cdf( 1.0, 2.0 )\n ~0.865\n > y = base.dists.exponential.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.exponential.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.cdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.cdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777\n\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ )\n Returns the differential entropy of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.exponential.entropy( 11.0 )\n ~-1.398\n > v = base.dists.exponential.entropy( 4.5 )\n ~-0.504\n\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ] )\n Returns an exponential distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n exponential: Object\n Distribution instance.\n\n exponential.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n exponential.entropy: number\n Read-only property which returns the differential entropy.\n\n exponential.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n exponential.mean: number\n Read-only property which returns the expected value.\n\n exponential.median: number\n Read-only property which returns the median.\n\n exponential.mode: number\n Read-only property which returns the mode.\n\n exponential.skewness: number\n Read-only property which returns the skewness.\n\n exponential.stdev: number\n Read-only property which returns the standard deviation.\n\n exponential.variance: number\n Read-only property which returns the variance.\n\n exponential.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n exponential.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n exponential.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n exponential.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n exponential.pdf: Function\n Evaluates the probability density function (PDF).\n\n exponential.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var exponential = base.dists.exponential.Exponential( 6.0 );\n > exponential.lambda\n 6.0\n > exponential.entropy\n ~-0.792\n > exponential.kurtosis\n 6.0\n > exponential.mean\n ~0.167\n > exponential.median\n ~0.116\n > exponential.mode\n 0.0\n > exponential.skewness\n 2.0\n > exponential.stdev\n ~0.167\n > exponential.variance\n ~0.028\n > exponential.cdf( 1.0 )\n ~0.998\n > exponential.logcdf( 1.0 )\n ~-0.002\n > exponential.logpdf( 1.5 )\n ~-7.208\n > exponential.mgf( -0.5 )\n ~0.923\n > exponential.pdf( 1.5 )\n ~0.001\n > exponential.quantile( 0.5 )\n ~0.116\n\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ )\n Returns the excess kurtosis of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.exponential.kurtosis( 11.0 )\n 6.0\n > v = base.dists.exponential.kurtosis( 4.5 )\n 6.0\n\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x, λ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n ~-1.708\n > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n ~-0.145\n > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.exponential.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.logcdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252\n\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n ~0.186\n > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n ~-1.757\n > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.exponential.logpdf( 0, NaN )\n NaN\n > y = base.dists.exponential.logpdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193\n\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ )\n Returns the expected value of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.exponential.mean( 11.0 )\n ~0.091\n > v = base.dists.exponential.mean( 4.5 )\n ~0.222\n\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ )\n Returns the median of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.exponential.median( 11.0 )\n ~0.063\n > v = base.dists.exponential.median( 4.5 )\n ~0.154\n\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t, λ )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var v = base.dists.exponential.mgf( 2.0, 3.0 )\n 3.0\n > v = base.dists.exponential.mgf( 0.4, 1.2 )\n 1.5\n > v = base.dists.exponential.mgf( 0.8, 1.6 )\n 2.0\n > v = base.dists.exponential.mgf( 4.0, 3.0 )\n NaN\n > v = base.dists.exponential.mgf( NaN, 3.0 )\n NaN\n > v = base.dists.exponential.mgf( 2.0, NaN )\n NaN\n\n\nbase.dists.exponential.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n mg: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n > var y = myMGF( 3.0 )\n 4.0\n > y = myMGF( 0.5 )\n ~1.143\n\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n mg: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n > var y = myMGF( 3.0 )\n 4.0\n > y = myMGF( 0.5 )\n ~1.143","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ )\n Returns the mode of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.exponential.mode( 11.0 )\n 0.0\n > v = base.dists.exponential.mode( 4.5 )\n 0.0\n\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x, λ )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n ~1.205\n > y = base.dists.exponential.pdf( 2.0, 0.7 )\n ~0.173\n > y = base.dists.exponential.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.exponential.pdf( 0, NaN )\n NaN\n > y = base.dists.exponential.pdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.pdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112\n\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p, λ )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n ~1.609\n > y = base.dists.exponential.quantile( 0.5, 4.0 )\n ~0.173\n > y = base.dists.exponential.quantile( 0.5, 0.1 )\n ~6.931\n\n > y = base.dists.exponential.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.exponential.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.quantile( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ )\n Returns the skewness of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.exponential.skewness( 11.0 )\n 2.0\n > v = base.dists.exponential.skewness( 4.5 )\n 2.0\n\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ )\n Returns the standard deviation of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.exponential.stdev( 9.0 )\n ~0.11\n > v = base.dists.exponential.stdev( 1.0 )\n 1.0\n\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ )\n Returns the variance of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.exponential.variance( 9.0 )\n ~0.012\n > v = base.dists.exponential.variance( 1.0 )\n 1.0\n\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x, d1, d2 )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n ~0.608\n > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n ~0.737\n > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > var y = base.dists.f.cdf( PINF, 4.0, 2.0 )\n 1.0\n > var y = base.dists.f.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n NaN\n\n > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n NaN\n > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884\n\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884","base.dists.f.entropy":"\nbase.dists.f.entropy( d1, d2 )\n Returns the differential entropy of an F distribution (in nats).\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.f.entropy( 3.0, 7.0 )\n ~1.298\n > v = base.dists.f.entropy( 4.0, 12.0 )\n ~1.12\n > v = base.dists.f.entropy( 8.0, 2.0 )\n ~2.144\n\n","base.dists.f.F":"\nbase.dists.f.F( [d1, d2] )\n Returns an F distribution object.\n\n Parameters\n ----------\n d1: number (optional)\n Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n d2: number (optional)\n Denominator degrees of freedom. Must be greater than `0`.\n Default: `1.0`.\n\n Returns\n -------\n f: Object\n Distribution instance.\n\n f.d1: number\n Numerator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.d2: number\n Denominator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.entropy: number\n Read-only property which returns the differential entropy.\n\n f.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n f.mean: number\n Read-only property which returns the expected value.\n\n f.mode: number\n Read-only property which returns the mode.\n\n f.skewness: number\n Read-only property which returns the skewness.\n\n f.stdev: number\n Read-only property which returns the standard deviation.\n\n f.variance: number\n Read-only property which returns the variance.\n\n f.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n f.pdf: Function\n Evaluates the probability density function (PDF).\n\n f.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var f = base.dists.f.F( 6.0, 9.0 );\n > f.d1\n 6.0\n > f.d2\n 9.0\n > f.entropy\n ~1.134\n > f.kurtosis\n ~104.564\n > f.mean\n ~1.286\n > f.mode\n ~0.545\n > f.skewness\n ~4.535\n > f.stdev\n ~1.197\n > f.variance\n ~1.433\n > f.cdf( 3.0 )\n ~0.932\n > f.pdf( 2.5 )\n ~0.095\n > f.quantile( 0.8 )\n ~1.826\n\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1, d2 )\n Returns the excess kurtosis of an F distribution.\n\n If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n ~124.667\n > v = base.dists.f.kurtosis( 4.0, 12.0 )\n ~26.143\n > v = base.dists.f.kurtosis( 8.0, 9.0 )\n ~100.167\n\n","base.dists.f.mean":"\nbase.dists.f.mean( d1, d2 )\n Returns the expected value of an F distribution.\n\n If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.f.mean( 3.0, 5.0 )\n ~1.667\n > v = base.dists.f.mean( 4.0, 12.0 )\n ~1.2\n > v = base.dists.f.mean( 8.0, 4.0 )\n 2.0\n\n","base.dists.f.mode":"\nbase.dists.f.mode( d1, d2 )\n Returns the mode of an F distribution.\n\n If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.f.mode( 3.0, 5.0 )\n ~0.238\n > v = base.dists.f.mode( 4.0, 12.0 )\n ~0.429\n > v = base.dists.f.mode( 8.0, 4.0 )\n 0.5\n\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x, d1, d2 )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n ~0.057\n > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n ~0.915\n > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n NaN\n > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166\n\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166","base.dists.f.quantile":"\nbase.dists.f.quantile( p, d1, d2 )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n ~9.472\n > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n ~1.207\n\n > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382\n\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382","base.dists.f.skewness":"\nbase.dists.f.skewness( d1, d2 )\n Returns the skewness of an F distribution.\n\n If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.f.skewness( 3.0, 7.0 )\n 11.0\n > v = base.dists.f.skewness( 4.0, 12.0 )\n ~3.207\n > v = base.dists.f.skewness( 8.0, 7.0 )\n ~10.088\n\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1, d2 )\n Returns the standard deviation of an F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.f.stdev( 3.0, 5.0 )\n ~3.333\n > v = base.dists.f.stdev( 4.0, 12.0 )\n ~1.122\n > v = base.dists.f.stdev( 8.0, 5.0 )\n ~2.764\n\n","base.dists.f.variance":"\nbase.dists.f.variance( d1, d2 )\n Returns the variance of an F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.f.variance( 3.0, 5.0 )\n ~11.111\n > v = base.dists.f.variance( 4.0, 12.0 )\n ~1.26\n > v = base.dists.f.variance( 8.0, 5.0 )\n ~7.639\n\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x, α, s, m )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n ~0.914\n > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n ~0.105\n > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n ~0.018\n > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034\n\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α, s, m )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n ~2.154\n > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n ~1.028\n > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α, s, m] )\n Returns a Fréchet distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n m: number (optional)\n Location parameter. Default: `0.0`.\n\n Returns\n -------\n frechet: Object\n Distribution instance.\n\n frechet.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n frechet.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n frechet.m: number\n Location parameter.\n\n frechet.entropy: number\n Read-only property which returns the differential entropy.\n\n frechet.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n frechet.mean: number\n Read-only property which returns the expected value.\n\n frechet.median: number\n Read-only property which returns the median.\n\n frechet.mode: number\n Read-only property which returns the mode.\n\n frechet.skewness: number\n Read-only property which returns the skewness.\n\n frechet.stdev: number\n Read-only property which returns the standard deviation.\n\n frechet.variance: number\n Read-only property which returns the variance.\n\n frechet.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n frechet.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n frechet.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n frechet.pdf: Function\n Evaluates the probability density function (PDF).\n\n frechet.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n > frechet.alpha\n 1.0\n > frechet.s\n 1.0\n > frechet.m\n 0.0\n > frechet.entropy\n ~2.154\n > frechet.kurtosis\n Infinity\n > frechet.mean\n Infinity\n > frechet.median\n ~1.443\n > frechet.mode\n 0.5\n > frechet.skewness\n Infinity\n > frechet.stdev\n Infinity\n > frechet.variance\n Infinity\n > frechet.cdf( 0.8 )\n ~0.287\n > frechet.logcdf( 0.8 )\n -1.25\n > frechet.logpdf( 0.8 )\n ~-0.804\n > frechet.pdf( 0.8 )\n ~0.448\n > frechet.quantile( 0.8 )\n ~4.481\n\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α, s, m )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 4` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n ~45.092\n > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n ~45.092\n > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x, α, s, m )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n ~-0.09\n > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n ~-2.25\n > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n -4.0\n > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375\n\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x, α, s, m )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n ~-2.72\n > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n ~-1.901\n > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n ~-0.307\n > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11\n\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α, s, m )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 1` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n ~3.451\n > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α, s, m )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n ~3.192\n > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n ~-0.808\n > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n ~5.163\n > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α, s, m )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n ~2.891\n > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n ~-1.109\n > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n ~1.222\n > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x, α, s, m )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368\n\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p, α, s, m )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n ~4.963\n > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n ~5.56\n > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n ~6.491\n > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576\n\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α, s, m )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 3` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n ~5.605\n > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n ~5.605\n > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α, s, m )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n ~1.041\n > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n ~1.041\n > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α, s, m )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n ~1.083\n > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n ~1.083\n > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n ~0.323\n > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0` when `α = 0.0`:\n > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264\n\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α, β )\n Returns the differential entropy of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.entropy( 4.0, 12.0 )\n ~-0.462\n > v = base.dists.gamma.entropy( 8.0, 2.0 )\n ~1.723\n\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α, β] )\n Returns a gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gamma: Object\n Distribution instance.\n\n gamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n gamma.beta: number\n Rate parameter. If set, the value must be greater than `0`.\n\n gamma.entropy: number\n Read-only property which returns the differential entropy.\n\n gamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gamma.mean: number\n Read-only property which returns the expected value.\n\n gamma.mode: number\n Read-only property which returns the mode.\n\n gamma.skewness: number\n Read-only property which returns the skewness.\n\n gamma.stdev: number\n Read-only property which returns the standard deviation.\n\n gamma.variance: number\n Read-only property which returns the variance.\n\n gamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gamma.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gamma.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n gamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n > gamma.alpha\n 6.0\n > gamma.beta\n 5.0\n > gamma.entropy\n ~0.647\n > gamma.kurtosis\n 1.0\n > gamma.mean\n 1.2\n > gamma.mode\n 1.0\n > gamma.skewness\n ~0.816\n > gamma.stdev\n ~0.49\n > gamma.variance\n 0.24\n > gamma.cdf( 0.8 )\n ~0.215\n > gamma.logcdf( 0.8 )\n ~-1.538\n > gamma.logpdf( 1.0 )\n ~-0.131\n > gamma.mgf( -0.5 )\n ~0.564\n > gamma.pdf( 1.0 )\n ~0.877\n > gamma.quantile( 0.8 )\n ~1.581\n\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α, β )\n Returns the excess kurtosis of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n 1.5\n > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n 0.75\n\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x, α, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\n ~-0.047\n > y = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\n ~-2.352\n > y = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.logcdf.factory( α, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n > var y = mylogCDF( 2.0 )\n ~-0.006\n\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n > var y = mylogCDF( 2.0 )\n ~-0.006","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x, α, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.919\n > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646\n\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α, β )\n Returns the expected value of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.gamma.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.mean( 4.0, 12.0 )\n ~0.333\n > v = base.dists.gamma.mean( 8.0, 2.0 )\n 4.0\n\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n ~1.414\n > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n ~1.111\n > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n ~0.198\n\n > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375\n\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α, β )\n Returns the mode of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.gamma.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.gamma.mode( 4.0, 12.0 )\n 0.25\n > v = base.dists.gamma.mode( 8.0, 2.0 )\n 3.5\n\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n ~0.054\n > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026\n\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p, α, β )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n ~2.994\n > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n ~1.836\n\n > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688\n\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α, β )\n Returns the skewness of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.gamma.skewness( 4.0, 12.0 )\n 1.0\n > v = base.dists.gamma.skewness( 8.0, 2.0 )\n ~0.707\n\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α, β )\n Returns the standard deviation of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.stdev( 4.0, 12.0 )\n ~0.167\n > v = base.dists.gamma.stdev( 8.0, 2.0 )\n ~1.414\n\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α, β )\n Returns the variance of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.gamma.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.variance( 4.0, 12.0 )\n ~0.028\n > v = base.dists.gamma.variance( 8.0, 2.0 )\n 2.0\n\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n 0.875\n > y = base.dists.geometric.cdf( 2.0, 0.1 )\n ~0.271\n > y = base.dists.geometric.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.geometric.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.cdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75\n\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.geometric.entropy( 0.1 )\n ~3.251\n > v = base.dists.geometric.entropy( 0.5 )\n ~1.386\n\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p] )\n Returns a geometric distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n geometric: Object\n Distribution instance.\n\n geometric.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n geometric.entropy: number\n Read-only property which returns the differential entropy.\n\n geometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n geometric.mean: number\n Read-only property which returns the expected value.\n\n geometric.median: number\n Read-only property which returns the median.\n\n geometric.mode: number\n Read-only property which returns the mode.\n\n geometric.skewness: number\n Read-only property which returns the skewness.\n\n geometric.stdev: number\n Read-only property which returns the standard deviation.\n\n geometric.variance: number\n Read-only property which returns the variance.\n\n geometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n geometric.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n geometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n geometric.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n geometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n geometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var geometric = base.dists.geometric.Geometric( 0.6 );\n > geometric.p\n 0.6\n > geometric.entropy\n ~1.122\n > geometric.kurtosis\n ~6.9\n > geometric.mean\n ~0.667\n > geometric.median\n 0.0\n > geometric.mode\n 0.0\n > geometric.skewness\n ~2.214\n > geometric.stdev\n ~1.054\n > geometric.variance\n ~1.111\n > geometric.cdf( 3.0 )\n ~0.974\n > geometric.logcdf( 3.0 )\n ~-0.026\n > geometric.logpmf( 4.0 )\n ~-4.176\n > geometric.mgf( 0.5 )\n ~2.905\n > geometric.pmf( 2.0 )\n ~0.096\n > geometric.quantile( 0.7 )\n 1.0\n\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.geometric.kurtosis( 0.1 )\n ~6.011\n > v = base.dists.geometric.kurtosis( 0.5 )\n 6.5\n\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x, p )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n ~-0.134\n > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n ~-1.306\n > y = base.dists.geometric.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.geometric.logcdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.logcdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288\n\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x, p )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n ~-2.631\n > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n ~-2.765\n > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.geometric.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.logpmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386\n\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.geometric.mean( 0.1 )\n 9.0\n > v = base.dists.geometric.mean( 0.5 )\n 1.0\n\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p )\n Returns the median of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.geometric.median( 0.1 )\n 6\n > v = base.dists.geometric.median( 0.5 )\n 0\n\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `t >= -ln(1-p)`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n ~1.569\n > y = base.dists.geometric.mgf( 0.4, 0.5 )\n ~2.936\n // Case: t >= -ln(1-p)\n > y = base.dists.geometric.mgf( 0.8, 0.5 )\n NaN\n > y = base.dists.geometric.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783\n\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p )\n Returns the mode of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.geometric.mode( 0.1 )\n 0\n > v = base.dists.geometric.mode( 0.5 )\n 0\n\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x, p )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n ~0.072\n > y = base.dists.geometric.pmf( 2.0, 0.7 )\n ~0.063\n > y = base.dists.geometric.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.geometric.pmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.pmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25\n\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r, p )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n 3\n > y = base.dists.geometric.quantile( 0.5, 0.4 )\n 1\n > y = base.dists.geometric.quantile( 0.9, 0.1 )\n 21\n\n > y = base.dists.geometric.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.geometric.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.geometric.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.geometric.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.geometric.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity\n\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.geometric.skewness( 0.1 )\n ~2.003\n > v = base.dists.geometric.skewness( 0.5 )\n ~2.121\n\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.geometric.stdev( 0.1 )\n ~9.487\n > v = base.dists.geometric.stdev( 0.5 )\n ~1.414\n\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p )\n Returns the variance of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.geometric.variance( 0.1 )\n ~90.0\n > v = base.dists.geometric.variance( 0.5 )\n 2.0\n\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x, μ, β )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368\n\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ, β )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n ~1.577\n > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n ~2.27\n > y = base.dists.gumbel.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ, β] )\n Returns a Gumbel distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gumbel: Object\n Distribution instance.\n\n gumbel.mu: number\n Location parameter.\n\n gumbel.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n gumbel.entropy: number\n Read-only property which returns the differential entropy.\n\n gumbel.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gumbel.mean: number\n Read-only property which returns the expected value.\n\n gumbel.median: number\n Read-only property which returns the median.\n\n gumbel.mode: number\n Read-only property which returns the mode.\n\n gumbel.skewness: number\n Read-only property which returns the skewness.\n\n gumbel.stdev: number\n Read-only property which returns the standard deviation.\n\n gumbel.variance: number\n Read-only property which returns the variance.\n\n gumbel.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gumbel.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gumbel.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gumbel.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gumbel.pdf: Function\n Evaluates the probability density function (PDF).\n\n gumbel.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n > gumbel.mu\n -2.0\n > gumbel.beta\n 3.0\n > gumbel.entropy\n ~2.676\n > gumbel.kurtosis\n 2.4\n > gumbel.mean\n ~-0.268\n > gumbel.median\n ~-0.9\n > gumbel.mode\n -2.0\n > gumbel.skewness\n ~1.14\n > gumbel.stdev\n ~3.848\n > gumbel.variance\n ~14.804\n > gumbel.cdf( 0.8 )\n ~0.675\n > gumbel.logcdf( 0.8 )\n ~-0.393\n > gumbel.logpdf( 1.0 )\n ~-2.466\n > gumbel.mgf( 0.2 )\n ~1.487\n > gumbel.pdf( 1.0 )\n ~0.085\n > gumbel.quantile( 0.8 )\n ~2.5\n\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ, β )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x, μ, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n ~-0.036\n > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n ~-1.948\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n ~-1.0\n > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0\n\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x, μ, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n ~-1.693\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n ~-1\n > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n ~-2.411\n > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061\n\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ, β )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n ~0.577\n > y = base.dists.gumbel.mean( 4.0, 2.0 )\n ~5.154\n > y = base.dists.gumbel.mean( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mean( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ, β )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.gumbel.median( 0.0, 1.0 )\n ~0.367\n > y = base.dists.gumbel.median( 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.median( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.median( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.median( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t, μ, β )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n 6.0\n > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n ~1.298\n\n > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n NaN\n\n // Case: `t >= 1/beta`\n > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n NaN\n\n // Non-positive scale parameter:\n > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0\n\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ, β )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.gumbel.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.gumbel.mode( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mode( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x, μ, β )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n ~0.184\n > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n ~0.09\n > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127\n\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p, μ, β )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n ~1.5\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n ~5.466\n\n > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062\n\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ, β )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ, β )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n ~1.283\n > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n ~2.565\n > y = base.dists.gumbel.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ, β )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n ~1.645\n > y = base.dists.gumbel.variance( 4.0, 2.0 )\n ~6.58\n > y = base.dists.gumbel.variance( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.variance( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x, N, K, n )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceeds population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n 1.0\n > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n ~0.214\n\n > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031\n\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n Returns a hypergeometric distribution object.\n\n Parameters\n ----------\n N: integer (optional)\n Population size. Must be a nonnegative integer larger than or equal to\n `K` and `n`.\n\n K: integer (optional)\n Subpopulation size. Must be a nonnegative integer smaller than or equal\n to `N`.\n\n n: integer (optional)\n Number of draws. Must be a nonnegative integer smaller than or equal to\n `N`.\n\n Returns\n -------\n hypergeometric: Object\n Distribution instance.\n\n hypergeometric.N: number\n Population size. If set, the value must be a nonnegative integer larger\n than or equal to `K` and `n`.\n\n hypergeometric.K: number\n Subpopulation size. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.n: number\n Number of draws. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n hypergeometric.mean: number\n Read-only property which returns the expected value.\n\n hypergeometric.mode: number\n Read-only property which returns the mode.\n\n hypergeometric.skewness: number\n Read-only property which returns the skewness.\n\n hypergeometric.stdev: number\n Read-only property which returns the standard deviation.\n\n hypergeometric.variance: number\n Read-only property which returns the variance.\n\n hypergeometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n hypergeometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n hypergeometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n hypergeometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n > hypergeometric.N\n 100.0\n > hypergeometric.K\n 70.0\n > hypergeometric.n\n 20.0\n > hypergeometric.kurtosis\n ~-0.063\n > hypergeometric.mean\n 14.0\n > hypergeometric.mode\n 14.0\n > hypergeometric.skewness\n ~-0.133\n > hypergeometric.stdev\n ~1.842\n > hypergeometric.variance\n ~3.394\n > hypergeometric.cdf( 2.9 )\n ~0.0\n > hypergeometric.logpmf( 10 )\n ~-3.806\n > hypergeometric.pmf( 10 )\n ~0.022\n > hypergeometric.quantile( 0.8 )\n 16.0\n\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N, K, n )\n Returns the excess kurtosis of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceed population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n ~-0.326\n > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K`, or draws `n`\n which is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n ~-0.56\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n -Infinity\n\n > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524\n\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N, K, n )\n Returns the expected value of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n 2.75\n > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N, K, n )\n Returns the mode of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n 3\n > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n 1\n\n > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x, N, K, n )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n ~0.571\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n 0.0\n\n > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029\n\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p, N, K, n )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n 5\n > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n 15\n > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n 1\n > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n 0\n > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n 20\n\n > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4\n\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N, K, n )\n Returns the skewness of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n ~-0.258\n > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N, K, n )\n Returns the standard deviation of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n ~0.829\n > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N, K, n )\n Returns the variance of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n ~0.688\n > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n 0.25\n\n > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n NaN\n\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n ~0.607\n > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n ~0.986\n > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974\n\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α, β )\n Returns the differential entropy of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n ~2.154\n > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n ~1.996\n > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n ~-0.922\n\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α, β] )\n Returns an inverse gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n invgamma: Object\n Distribution instance.\n\n invgamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n invgamma.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n invgamma.entropy: number\n Read-only property which returns the differential entropy.\n\n invgamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n invgamma.mean: number\n Read-only property which returns the expected value.\n\n invgamma.mode: number\n Read-only property which returns the mode.\n\n invgamma.skewness: number\n Read-only property which returns the skewness.\n\n invgamma.stdev: number\n Read-only property which returns the standard deviation.\n\n invgamma.variance: number\n Read-only property which returns the variance.\n\n invgamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n invgamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n invgamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n invgamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n > invgamma.alpha\n 6.0\n > invgamma.beta\n 5.0\n > invgamma.entropy\n ~0.454\n > invgamma.kurtosis\n 19.0\n > invgamma.mean\n 1.0\n > invgamma.mode\n ~0.714\n > invgamma.skewness\n ~2.667\n > invgamma.stdev\n 0.5\n > invgamma.variance\n 0.25\n > invgamma.cdf( 0.8 )\n ~0.406\n > invgamma.pdf( 1.0 )\n ~0.877\n > invgamma.logpdf( 1.0 )\n ~-0.131\n > invgamma.quantile( 0.8 )\n ~1.281\n\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α, β )\n Returns the excess kurtosis of an inverse gamma distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n 12.0\n > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n 19.0\n > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n ~8.7\n\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.112\n > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n ~-1.781\n > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464\n\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α, β )\n Returns the expected value of an inverse gamma distribution.\n\n If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n 4.0\n > v = base.dists.invgamma.mean( 8.0, 2.0 )\n ~0.286\n\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α, β )\n Returns the mode of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n 0.5\n > v = base.dists.invgamma.mode( 4.0, 12.0 )\n 2.4\n > v = base.dists.invgamma.mode( 8.0, 2.0 )\n ~0.222\n\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n ~0.121\n > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n ~0.168\n > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231\n\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p, α, β )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n ~1.213\n > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n ~0.545\n > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n\n // Non-positive rate parameter:\n > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989\n\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α, β )\n Returns the skewness of an inverse gamma distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n ~5.657\n > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n ~1.96\n\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α, β )\n Returns the standard deviation of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n ~1.01\n > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n ~0.117\n\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α, β )\n Returns the variance of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n ~1.021\n > v = base.dists.invgamma.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.invgamma.variance( 8.0, 2.0 )\n ~0.014\n\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n ~0.5\n > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n ~0.684\n > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n ~0.078\n > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n ~0.878\n > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548\n\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n Returns a Kumaraswamy's double bounded distribution object.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n b: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n kumaraswamy: Object\n Distribution instance.\n\n kumaraswamy.a: number\n First shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.b: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n kumaraswamy.mean: number\n Read-only property which returns the expected value.\n\n kumaraswamy.mode: number\n Read-only property which returns the mode.\n\n kumaraswamy.skewness: number\n Read-only property which returns the skewness.\n\n kumaraswamy.stdev: number\n Read-only property which returns the standard deviation.\n\n kumaraswamy.variance: number\n Read-only property which returns the variance.\n\n kumaraswamy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n kumaraswamy.pdf: Function\n Evaluates the probability density function (PDF).\n\n kumaraswamy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n > kumaraswamy.a\n 6.0\n > kumaraswamy.b\n 5.0\n > kumaraswamy.kurtosis\n ~3.194\n > kumaraswamy.mean\n ~0.696\n > kumaraswamy.mode\n ~0.746\n > kumaraswamy.skewness\n ~-0.605\n > kumaraswamy.stdev\n ~0.126\n > kumaraswamy.variance\n ~0.016\n > kumaraswamy.cdf( 0.8 )\n ~0.781\n > kumaraswamy.pdf( 1.0 )\n ~0.0\n > kumaraswamy.quantile( 0.8 )\n ~0.807\n\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a, b )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n ~1.8\n > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n ~2.704\n > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n ~4.311\n\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n ~-0.38\n > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n ~-2.546\n > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n ~-0.13\n > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602\n\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n ~0.523\n > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n ~-0.264\n > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n ~0.522\n > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091\n\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a, b )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n ~0.512\n > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n ~0.481\n > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n ~0.846\n\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a, b )\n Returns the median of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n ~0.487\n > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n ~0.856\n\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a, b )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n ~0.543\n > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n ~0.503\n > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n ~0.875\n\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x, a, b )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n ~1.688\n > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n ~0.768\n > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n ~1.686\n > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913\n\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p, a, b )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n ~0.399\n > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n ~0.325\n > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n ~0.759\n\n > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09\n\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a, b )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n ~1.154e-15\n > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n ~-0.201\n > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n ~-0.94\n\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a, b )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n ~0.13\n > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n ~0.062\n\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a, b )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n ~0.017\n > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n ~0.004\n\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x, μ, b )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n ~0.932\n > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n ~0.094\n > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5\n\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ, b )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n ~1.693\n > y = base.dists.laplace.entropy( 4.0, 2.0 )\n ~2.386\n > y = base.dists.laplace.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.entropy( 0.0, NaN )\n NaN\n > y = base.dists.laplace.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ, b )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ, b] )\n Returns a Laplace distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n b: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n laplace: Object\n Distribution instance.\n\n laplace.mu: number\n Location parameter.\n\n laplace.b: number\n Scale parameter. If set, the value must be greater than `0`.\n\n laplace.entropy: number\n Read-only property which returns the differential entropy.\n\n laplace.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n laplace.mean: number\n Read-only property which returns the expected value.\n\n laplace.median: number\n Read-only property which returns the median.\n\n laplace.mode: number\n Read-only property which returns the mode.\n\n laplace.skewness: number\n Read-only property which returns the skewness.\n\n laplace.stdev: number\n Read-only property which returns the standard deviation.\n\n laplace.variance: number\n Read-only property which returns the variance.\n\n laplace.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n laplace.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n laplace.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n laplace.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n laplace.pdf: Function\n Evaluates the probability density function (PDF).\n\n laplace.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n > laplace.mu\n -2.0\n > laplace.b\n 3.0\n > laplace.entropy\n ~2.792\n > laplace.kurtosis\n 3.0\n > laplace.mean\n -2.0\n > laplace.median\n -2.0\n > laplace.mode\n -2.0\n > laplace.skewness\n 0.0\n > laplace.stdev\n ~4.243\n > laplace.variance\n 18.0\n > laplace.cdf( 0.8 )\n ~0.803\n > laplace.logcdf( 0.8 )\n ~-0.219\n > laplace.logpdf( 1.0 )\n ~-2.792\n > laplace.mgf( 0.2 )\n ~1.047\n > laplace.pdf( 2.0 )\n ~0.044\n > laplace.quantile( 0.9 )\n ~2.828\n\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x, μ, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n ~-0.07\n > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n ~-2.36\n > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693\n\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x, μ, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n ~-2.693\n > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n ~-2.792\n > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n ~-1.958\n > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386\n\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ, b )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.laplace.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mean( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mean( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ, b )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.laplace.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.median( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.median( 0.0, NaN )\n NaN\n > y = base.dists.laplace.median( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t, μ, b )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n ~1.333\n > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n ~0.019\n > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n NaN\n > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758\n\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ, b )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.laplace.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mode( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mode( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x, μ, b )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n ~0.068\n > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n ~0.061\n > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n ~0.141\n > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25\n\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p, μ, b )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n ~0.916\n > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n 4.0\n\n > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833\n\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ, b )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.laplace.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.skewness( 0.0, NaN )\n NaN\n > y = base.dists.laplace.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ, b )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n ~1.414\n > y = base.dists.laplace.stdev( 4.0, 2.0 )\n ~2.828\n > y = base.dists.laplace.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.stdev( 0.0, NaN )\n NaN\n > y = base.dists.laplace.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ, b )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.laplace.variance( 0.0, 1.0 )\n 2.0\n > y = base.dists.laplace.variance( 4.0, 2.0 )\n 8.0\n > y = base.dists.laplace.variance( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.variance( 0.0, NaN )\n NaN\n > y = base.dists.laplace.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x, μ, c )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n ~0.48\n > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n ~0.221\n > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n 0.0\n > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0\n\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ, c )\n Returns the differential entropy of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.levy.entropy( 0.0, 1.0 )\n ~3.324\n > y = base.dists.levy.entropy( 4.0, 2.0 )\n ~4.018\n > y = base.dists.levy.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.levy.entropy( 0.0, NaN )\n NaN\n > y = base.dists.levy.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ, c] )\n Returns a Lévy distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n c: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n levy: Object\n Distribution instance.\n\n levy.mu: number\n Location parameter.\n\n levy.c: number\n Scale parameter. If set, the value must be greater than `0`.\n\n levy.entropy: number\n Read-only property which returns the differential entropy.\n\n levy.mean: number\n Read-only property which returns the expected value.\n\n levy.median: number\n Read-only property which returns the median.\n\n levy.mode: number\n Read-only property which returns the mode.\n\n levy.stdev: number\n Read-only property which returns the standard deviation.\n\n levy.variance: number\n Read-only property which returns the variance.\n\n levy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n levy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n levy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n levy.pdf: Function\n Evaluates the probability density function (PDF).\n\n levy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n > levy.mu\n -2.0\n > levy.c\n 3.0\n > levy.entropy\n ~4.423\n > levy.mean\n Infinity\n > levy.median\n ~4.594\n > levy.mode\n -1.0\n > levy.stdev\n Infinity\n > levy.variance\n Infinity\n > levy.cdf( 0.8 )\n ~0.3\n > levy.logcdf( 0.8 )\n ~-1.2\n > levy.logpdf( 1.0 )\n ~-2.518\n > levy.pdf( 1.0 )\n ~0.081\n > levy.quantile( 0.8 )\n ~44.74\n\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x, μ, c )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n ~-0.735\n > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n ~-1.51\n > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n -Infinity\n > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity\n\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x, μ, c )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n ~-2.209\n > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572\n\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572","base.dists.levy.mean":"\nbase.dists.levy.mean( μ, c )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.levy.mean( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.mean( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.mean( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mean( 0.0, NaN )\n NaN\n > y = base.dists.levy.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.median":"\nbase.dists.levy.median( μ, c )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.levy.median( 0.0, 1.0 )\n ~2.198\n > y = base.dists.levy.median( 4.0, 3.0 )\n ~10.594\n > y = base.dists.levy.median( NaN, 1.0 )\n NaN\n > y = base.dists.levy.median( 0.0, NaN )\n NaN\n > y = base.dists.levy.median( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ, c )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.levy.mode( 0.0, 1.0 )\n ~0.333\n > y = base.dists.levy.mode( 4.0, 3.0 )\n 5.0\n > y = base.dists.levy.mode( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mode( 0.0, NaN )\n NaN\n > y = base.dists.levy.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x, μ, c )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n ~0.11\n > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208\n\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p, μ, c )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n ~15.58\n > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n ~8.396\n\n > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396\n\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ, c )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.levy.stdev( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.stdev( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.levy.stdev( 0.0, NaN )\n NaN\n > y = base.dists.levy.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ, c )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.levy.variance( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.variance( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.variance( NaN, 1.0 )\n NaN\n > y = base.dists.levy.variance( 0.0, NaN )\n NaN\n > y = base.dists.levy.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n ~0.881\n > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n ~0.159\n\n > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209\n\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ, s )\n Returns the differential entropy of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n 2.0\n > y = base.dists.logistic.entropy( 4.0, 2.0 )\n ~2.693\n > y = base.dists.logistic.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.entropy( 0.0, NaN )\n NaN\n > y = base.dists.logistic.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ, s )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n NaN\n\n\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x, μ, s )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n ~-0.127\n > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n ~-1.84\n > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567\n\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ, s] )\n Returns a logistic distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n logistic: Object\n Distribution instance.\n\n logistic.mu: number\n Location parameter.\n\n logistic.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n logistic.entropy: number\n Read-only property which returns the differential entropy.\n\n logistic.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n logistic.mean: number\n Read-only property which returns the expected value.\n\n logistic.median: number\n Read-only property which returns the median.\n\n logistic.mode: number\n Read-only property which returns the mode.\n\n logistic.skewness: number\n Read-only property which returns the skewness.\n\n logistic.stdev: number\n Read-only property which returns the standard deviation.\n\n logistic.variance: number\n Read-only property which returns the variance.\n\n logistic.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n logistic.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n logistic.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n logistic.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n logistic.pdf: Function\n Evaluates the probability density function (PDF).\n\n logistic.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n > logistic.mu\n -2.0\n > logistic.s\n 3.0\n > logistic.entropy\n ~3.1\n > logistic.kurtosis\n 1.2\n > logistic.mean\n -2.0\n > logistic.median\n -2.0\n > logistic.mode\n -2.0\n > logistic.skewness\n 0.0\n > logistic.stdev\n ~5.441\n > logistic.variance\n ~29.609\n > logistic.cdf( 0.8 )\n ~0.718\n > logistic.logcdf( 0.8 )\n ~-0.332\n > logistic.logpdf( 2.0 )\n ~-2.9\n > logistic.mgf( 0.2 )\n ~1.329\n > logistic.pdf( 2.0 )\n ~0.055\n > logistic.quantile( 0.9 )\n ~4.592\n\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n ~-2.254\n > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n ~-3.351\n > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079\n\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ, s )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.logistic.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mean( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mean( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ, s )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.logistic.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.median( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.median( 0.0, NaN )\n NaN\n > y = base.dists.logistic.median( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n ~9.15\n > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n ~1.971\n > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n ~1.921\n > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n Infinity\n > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity\n\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ, s )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.logistic.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mode( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mode( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n ~0.105\n > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n ~0.035\n > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125\n\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p, μ, s )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n ~1.386\n > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ, s )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.logistic.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.skewness( 0.0, NaN )\n NaN\n > y = base.dists.logistic.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ, s )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n ~1.814\n > y = base.dists.logistic.stdev( 4.0, 2.0 )\n ~3.628\n > y = base.dists.logistic.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.stdev( 0.0, NaN )\n NaN\n > y = base.dists.logistic.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ, s )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.logistic.variance( 0.0, 1.0 )\n ~3.29\n > y = base.dists.logistic.variance( 4.0, 2.0 )\n ~13.159\n > y = base.dists.logistic.variance( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.variance( 0.0, NaN )\n NaN\n > y = base.dists.logistic.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n ~0.756\n > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n ~0.003\n\n > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141\n\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ, σ )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n ~7.112\n > y = base.dists.lognormal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ, σ )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n ~110.936\n > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n ~9220556.977\n > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ, σ] )\n Returns a lognormal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n lognormal: Object\n Distribution instance.\n\n lognormal.mu: number\n Location parameter.\n\n lognormal.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n lognormal.entropy: number\n Read-only property which returns the differential entropy.\n\n lognormal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n lognormal.mean: number\n Read-only property which returns the expected value.\n\n lognormal.median: number\n Read-only property which returns the median.\n\n lognormal.mode: number\n Read-only property which returns the mode.\n\n lognormal.skewness: number\n Read-only property which returns the skewness.\n\n lognormal.stdev: number\n Read-only property which returns the standard deviation.\n\n lognormal.variance: number\n Read-only property which returns the variance.\n\n lognormal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n lognormal.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n lognormal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n lognormal.pdf: Function\n Evaluates the probability density function (PDF).\n\n lognormal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n > lognormal.mu\n -2.0\n > lognormal.sigma\n 3.0\n > lognormal.entropy\n ~0.518\n > lognormal.kurtosis\n 4312295840576300\n > lognormal.mean\n ~12.182\n > lognormal.median\n ~0.135\n > lognormal.mode\n ~0.0\n > lognormal.skewness\n ~729551.383\n > lognormal.stdev\n ~1096.565\n > lognormal.variance\n ~1202455.871\n > lognormal.cdf( 0.8 )\n ~0.723\n > lognormal.logcdf( 0.8 )\n ~-4.334\n > lognormal.logpdf( 2.0 )\n ~-3.114\n > lognormal.pdf( 2.0 )\n ~0.044\n > lognormal.quantile( 0.9 )\n ~6.326\n\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x, μ, σ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logcdf.\n\n Examples\n --------\n > var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\n ~-0.2799\n > y = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\n ~-1.442\n > y = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n -Infinity\n\n\nbase.dists.lognormal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-9.732\n\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-9.732","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n ~-1.852\n > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n ~-0.919\n > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n ~-5.419\n > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672\n\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ, σ )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n ~1.649\n > y = base.dists.lognormal.mean( 4.0, 2.0 )\n ~403.429\n > y = base.dists.lognormal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mean( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ, σ )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.lognormal.median( 0.0, 1.0 )\n 1.0\n > y = base.dists.lognormal.median( 5.0, 2.0 )\n ~148.413\n > y = base.dists.lognormal.median( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.median( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ, σ )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n ~0.368\n > y = base.dists.lognormal.mode( 5.0, 2.0 )\n ~2.718\n > y = base.dists.lognormal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mode( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n ~0.157\n > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n ~0.399\n > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n ~0.004\n > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025\n\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p, μ, σ )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n ~2.32\n > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n ~54.598\n > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901\n\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ, σ )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n ~6.185\n > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n ~414.359\n > y = base.dists.lognormal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ, σ )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n ~2.161\n > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n ~2953.533\n > y = base.dists.lognormal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ, σ )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n ~4.671\n > y = base.dists.lognormal.variance( 4.0, 2.0 )\n ~8723355.729\n > y = base.dists.lognormal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.variance( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x, r, p )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n ~0.617\n > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n ~0.622\n > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n ~0.034\n > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n ~0.859\n > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n ~0.131\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668\n\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r, p )\n Returns the excess kurtosis of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n ~0.061\n > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n ~0.325\n\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x, r, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n ~-1.853\n > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n ~-2.818\n > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n ~-4.115\n > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n ~-1.054\n > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n ~-3.292\n > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n ~-2.976\n\n > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795\n\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r, p )\n Returns the expected value of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n 400\n > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n 20\n\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x, r, p )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n ~267.839\n > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n ~9.347\n > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n ~42822.023\n\n > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83\n\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r, p )\n Returns the mode of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n 396\n > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n 19\n\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n Returns a negative binomial distribution object.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped. Must be a positive\n number. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n nbinomial: Object\n Distribution instance.\n\n nbinomial.r: number\n Number of trials. If set, the value must be a positive number.\n\n nbinomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n nbinomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n nbinomial.mean: number\n Read-only property which returns the expected value.\n\n nbinomial.mode: number\n Read-only property which returns the mode.\n\n nbinomial.skewness: number\n Read-only property which returns the skewness.\n\n nbinomial.stdev: number\n Read-only property which returns the standard deviation.\n\n nbinomial.variance: number\n Read-only property which returns the variance.\n\n nbinomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n nbinomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n nbinomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n nbinomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n nbinomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n > nbinomial.r\n 8.0\n > nbinomial.p\n 0.5\n > nbinomial.kurtosis\n 0.8125\n > nbinomial.mean\n 8.0\n > nbinomial.mode\n 7.0\n > nbinomial.skewness\n 0.75\n > nbinomial.stdev\n 4.0\n > nbinomial.variance\n 16.0\n > nbinomial.cdf( 2.9 )\n ~0.055\n > nbinomial.logpmf( 3.0 )\n ~-2.837\n > nbinomial.mgf( 0.2 )\n ~36.675\n > nbinomial.pmf( 3.0 )\n ~0.059\n > nbinomial.quantile( 0.8 )\n 11.0\n\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x, r, p )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n ~0.157\n > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n ~0.06\n > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n ~0.016\n > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n ~0.037\n > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n ~0.051\n\n > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061\n\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k, r, p )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n\n If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n k: number\n Input probability.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n 106\n > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n 8\n > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n 14\n > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n 0\n\n > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n 12\n > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n 10\n\n > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16\n\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r, p )\n Returns the skewness of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n ~0.201\n > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n ~0.474\n\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r, p )\n Returns the standard deviation of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n ~44.721\n > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n ~6.325\n\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r, p )\n Returns the variance of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n 2000.0\n > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n 40.0\n\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n ~0.977\n > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n 0.5\n > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n ~0.006\n > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5\n\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ, σ )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.normal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.normal.entropy( 4.0, 3.0 )\n ~2.518\n > y = base.dists.normal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.normal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.normal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ, σ )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x, μ, σ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logcdf.\n\n Examples\n --------\n > var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\n ~-0.023\n > y = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\n ~-5.082\n > y = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logcdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.normal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.693\n\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.693","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n ~-2.919\n > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n ~-4.737\n > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612\n\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612","base.dists.normal.mean":"\nbase.dists.normal.mean( μ, σ )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.normal.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mean( 0.0, NaN )\n NaN\n > y = base.dists.normal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.median":"\nbase.dists.normal.median( μ, σ )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.normal.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.median( NaN, 1.0 )\n NaN\n > y = base.dists.normal.median( 0.0, NaN )\n NaN\n > y = base.dists.normal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x, μ, σ )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n ~7.389\n > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n ~0.1353\n > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182\n\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182","base.dists.normal.mode":"\nbase.dists.normal.mode( μ, σ )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.normal.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mode( 0.0, NaN )\n NaN\n > y = base.dists.normal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ, σ] )\n Returns a normal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Mean parameter. Default: `0.0`.\n\n σ: number (optional)\n Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n normal: Object\n Distribution instance.\n\n normal.mu: number\n Mean parameter.\n\n normal.sigma: number\n Standard deviation. If set, the value must be greater than `0`.\n\n normal.entropy: number\n Read-only property which returns the differential entropy.\n\n normal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n normal.mean: number\n Read-only property which returns the expected value.\n\n normal.median: number\n Read-only property which returns the median.\n\n normal.mode: number\n Read-only property which returns the mode.\n\n normal.skewness: number\n Read-only property which returns the skewness.\n\n normal.stdev: number\n Read-only property which returns the standard deviation.\n\n normal.variance: number\n Read-only property which returns the variance.\n\n normal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n normal.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n normal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n normal.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n normal.pdf: Function\n Evaluates the probability density function (PDF).\n\n normal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n > normal.mu\n -2.0\n > normal.sigma\n 3.0\n > normal.entropy\n ~2.518\n > normal.kurtosis\n 0.0\n > normal.mean\n -2.0\n > normal.median\n -2.0\n > normal.mode\n -2.0\n > normal.skewness\n 0.0\n > normal.stdev\n 3.0\n > normal.variance\n 9.0\n > normal.cdf( 0.8 )\n ~0.825\n > normal.logcdf( 0.8 )\n ~-0.193\n > normal.logpdf( 2.0 )\n ~-2.9\n > normal.mgf( 0.2 )\n ~0.803\n > normal.pdf( 2.0 )\n ~0.055\n > normal.quantile( 0.9 )\n ~1.845\n\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n ~0.054\n > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n ~0.009\n > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199\n\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p, μ, σ )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n ~0.842\n > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n 8.0\n > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n 8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ, σ )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.normal.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.skewness( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.normal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.normal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ, σ )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.normal.stdev( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.stdev( 4.0, 3.0 )\n 3.0\n > y = base.dists.normal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.normal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.normal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ, σ )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.normal.variance( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.variance( 4.0, 3.0 )\n 9.0\n > y = base.dists.normal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.normal.variance( 0.0, NaN )\n NaN\n > y = base.dists.normal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n 0.5\n > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n ~0.36\n > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n 0.75\n > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893\n\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α, β )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n ~2.473\n > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n ~2.349\n > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n ~-0.261\n\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α, β )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n ~70.8\n > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n ~146.444\n > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n ~19.725\n\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n ~-1.022\n > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n ~-0.288\n > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114\n\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n ~-2.773\n > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n ~-3.689\n > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n ~-1.561\n > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n ~-5.238\n > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079\n\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α, β )\n Returns the expected value of a Pareto (Type I) distribution.\n\n If `0 < α <= 1`, the function returns `Infinity`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.mean( 4.0, 12.0 )\n 16.0\n > v = base.dists.pareto1.mean( 8.0, 2.0 )\n ~2.286\n\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α, β )\n Returns the median of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.pareto1.median( 0.8, 1.0 )\n ~2.378\n > v = base.dists.pareto1.median( 4.0, 12.0 )\n ~14.27\n > v = base.dists.pareto1.median( 8.0, 2.0 )\n ~2.181\n\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α, β )\n Returns the mode of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n 1.0\n > v = base.dists.pareto1.mode( 4.0, 12.0 )\n 12.0\n > v = base.dists.pareto1.mode( 8.0, 2.0 )\n 2.0\n\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α, β] )\n Returns a Pareto (Type I) distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n pareto1: Object\n Distribution instance.\n\n pareto1.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n pareto1.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n pareto1.entropy: number\n Read-only property which returns the differential entropy.\n\n pareto1.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n pareto1.mean: number\n Read-only property which returns the expected value.\n\n pareto1.median: number\n Read-only property which returns the median.\n\n pareto1.mode: number\n Read-only property which returns the mode.\n\n pareto1.skewness: number\n Read-only property which returns the skewness.\n\n pareto1.variance: number\n Read-only property which returns the variance.\n\n pareto1.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n pareto1.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF).\n\n pareto1.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (logPDF).\n\n pareto1.pdf: Function\n Evaluates the probability density function (PDF).\n\n pareto1.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n > pareto1.alpha\n 6.0\n > pareto1.beta\n 5.0\n > pareto1.entropy\n ~0.984\n > pareto1.kurtosis\n ~35.667\n > pareto1.mean\n 6.0\n > pareto1.median\n ~5.612\n > pareto1.mode\n 5.0\n > pareto1.skewness\n ~3.81\n > pareto1.variance\n 1.5\n > pareto1.cdf( 7.0 )\n ~0.867\n > pareto1.logcdf( 7.0 )\n ~-0.142\n > pareto1.logpdf( 5.0 )\n ~0.182\n > pareto1.pdf( 5.0 )\n 1.2\n > pareto1.quantile( 0.8 )\n ~6.538\n\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n ~0.063\n > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n 0.025\n > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n ~0.21\n > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n ~0.005\n > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125\n\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p, α, β )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n ~2.236\n > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n ~50.0\n > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n ~11.111\n\n > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952\n\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α, β )\n Returns the skewness of a Pareto (Type I) distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n ~11.784\n > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n ~7.071\n > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n ~3.118\n\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α, β )\n Returns the standard deviation of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.pareto1.stdev( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.stdev( 4.0, 12.0 )\n ~5.657\n > v = base.dists.pareto1.stdev( 8.0, 2.0 )\n ~0.33\n\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α, β )\n Returns the variance of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.variance( 4.0, 12.0 )\n 32.0\n > v = base.dists.pareto1.variance( 8.0, 2.0 )\n ~0.109\n\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n ~0.986\n > y = base.dists.poisson.cdf( 2.0, 10.0 )\n ~0.003\n > y = base.dists.poisson.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.poisson.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.poisson.cdf( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.poisson.cdf( 10.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932\n\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ )\n Returns the entropy of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.poisson.entropy( 11.0 )\n ~2.61\n > v = base.dists.poisson.entropy( 4.5 )\n ~2.149\n\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ )\n Returns the excess kurtosis of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.poisson.kurtosis( 11.0 )\n ~0.091\n > v = base.dists.poisson.kurtosis( 4.5 )\n ~0.222\n\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x, λ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n ~-1.784\n > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n ~-1.901\n > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.logpmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n 0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0\n\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ )\n Returns the expected value of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.poisson.mean( 11.0 )\n 11.0\n > v = base.dists.poisson.mean( 4.5 )\n 4.5\n\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ )\n Returns the median of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.poisson.median( 11.0 )\n 11\n > v = base.dists.poisson.median( 4.5 )\n 4\n\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x, λ )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.poisson.mgf( 1.0, 1.5 )\n ~13.163\n > y = base.dists.poisson.mgf( 0.5, 0.5 )\n ~1.383\n > y = base.dists.poisson.mgf( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.mgf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.mgf( -2.0, -1.0 )\n NaN\n\n\nbase.dists.poisson.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n > var y = myMGF( 0.1 )\n ~1.234\n\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n > var y = myMGF( 0.1 )\n ~1.234","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ )\n Returns the mode of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.poisson.mode( 11.0 )\n 11\n > v = base.dists.poisson.mode( 4.5 )\n 4\n\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x, λ )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n ~0.168\n > y = base.dists.poisson.pmf( 1.0, 3.0 )\n ~0.149\n > y = base.dists.poisson.pmf( -1.0, 2.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.pmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.pmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.pmf( 2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368\n\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ] )\n Returns a Poisson distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n poisson: Object\n Distribution instance.\n\n poisson.lambda: number\n Mean parameter. If set, the value must be greater than `0`.\n\n poisson.entropy: number\n Read-only property which returns the differential entropy.\n\n poisson.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n poisson.mean: number\n Read-only property which returns the expected value.\n\n poisson.median: number\n Read-only property which returns the median.\n\n poisson.mode: number\n Read-only property which returns the mode.\n\n poisson.skewness: number\n Read-only property which returns the skewness.\n\n poisson.stdev: number\n Read-only property which returns the standard deviation.\n\n poisson.variance: number\n Read-only property which returns the variance.\n\n poisson.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n poisson.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n poisson.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n poisson.pmf: Function\n Evaluates the probability mass function (PMF).\n\n poisson.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var poisson = base.dists.poisson.Poisson( 6.0 );\n > poisson.lambda\n 6.0\n > poisson.entropy\n ~2.3\n > poisson.kurtosis\n ~0.167\n > poisson.mean\n 6.0\n > poisson.median\n 6.0\n > poisson.mode\n 6.0\n > poisson.skewness\n ~0.408\n > poisson.stdev\n ~2.449\n > poisson.variance\n 6.0\n > poisson.cdf( 4.0 )\n ~0.285\n > poisson.logpmf( 2.0 )\n ~-3.11\n > poisson.mgf( 0.5 )\n ~49.025\n > poisson.pmf( 2.0 )\n ~0.045\n > poisson.quantile( 0.5 )\n 6.0\n\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p, λ )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n 2\n > y = base.dists.poisson.quantile( 0.9, 4.0 )\n 7\n > y = base.dists.poisson.quantile( 0.1, 200.0 )\n 182\n\n > y = base.dists.poisson.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.poisson.quantile( -0.2, 0.0 )\n NaN\n\n > y = base.dists.poisson.quantile( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.quantile( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.quantile( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.quantile( 0.1, 0.0 )\n 0.0\n > y = base.dists.poisson.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ )\n Returns the skewness of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.poisson.skewness( 11.0 )\n ~0.302\n > v = base.dists.poisson.skewness( 4.5 )\n ~0.471\n\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ )\n Returns the standard deviation of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.poisson.stdev( 11.0 )\n ~3.317\n > v = base.dists.poisson.stdev( 4.5 )\n ~2.121\n\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ )\n Returns the variance of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.poisson.variance( 11.0 )\n 11.0\n > v = base.dists.poisson.variance( 4.5 )\n 4.5\n\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x, sigma )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n ~0.199\n > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n ~0.118\n > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.cdf( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n 1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393\n\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ )\n Returns the differential entropy of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.rayleigh.entropy( 11.0 )\n ~3.34\n > v = base.dists.rayleigh.entropy( 4.5 )\n ~2.446\n\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ )\n Returns the excess kurtosis of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.rayleigh.kurtosis( 11.0 )\n ~0.245\n > v = base.dists.rayleigh.kurtosis( 4.5 )\n ~0.245\n\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x, sigma )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n ~-1.613\n > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n ~-2.141\n > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933\n\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x, sigma )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n ~-1.249\n > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n ~-1.986\n > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886\n\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ )\n Returns the expected value of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mean( 11.0 )\n ~13.786\n > v = base.dists.rayleigh.mean( 4.5 )\n ~5.64\n\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ )\n Returns the median of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.rayleigh.median( 11.0 )\n ~12.952\n > v = base.dists.rayleigh.median( 4.5 )\n ~5.298\n\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t, sigma )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n ~678.508\n > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n ~38.65\n > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n ~-0.947\n > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.mgf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888\n\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ )\n Returns the mode of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mode( 11.0 )\n 11.0\n > v = base.dists.rayleigh.mode( 4.5 )\n 4.5\n\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x, sigma )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n ~0.287\n > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n ~0.137\n > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n Infinity\n > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n 0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152\n\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p, sigma )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative probability for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n ~1.794\n > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n ~4.71\n\n > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n NaN\n\n > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ] )\n Returns a Rayleigh distribution object.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n rayleigh: Object\n Distribution instance.\n\n rayleigh.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n rayleigh.entropy: number\n Read-only property which returns the differential entropy.\n\n rayleigh.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n rayleigh.mean: number\n Read-only property which returns the expected value.\n\n rayleigh.median: number\n Read-only property which returns the median.\n\n rayleigh.mode: number\n Read-only property which returns the mode.\n\n rayleigh.skewness: number\n Read-only property which returns the skewness.\n\n rayleigh.stdev: number\n Read-only property which returns the standard deviation.\n\n rayleigh.variance: number\n Read-only property which returns the variance.\n\n rayleigh.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n rayleigh.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n rayleigh.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n rayleigh.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n rayleigh.pdf: Function\n Evaluates the probability density function (PDF).\n\n rayleigh.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n > rayleigh.sigma\n 6.0\n > rayleigh.entropy\n ~2.734\n > rayleigh.kurtosis\n ~0.245\n > rayleigh.mean\n ~7.52\n > rayleigh.median\n ~7.064\n > rayleigh.mode\n 6.0\n > rayleigh.skewness\n ~0.631\n > rayleigh.stdev\n ~3.931\n > rayleigh.variance\n ~15.451\n > rayleigh.cdf( 1.0 )\n ~0.014\n > rayleigh.logcdf( 1.0 )\n ~-4.284\n > rayleigh.logpdf( 1.5 )\n ~-3.209\n > rayleigh.mgf( -0.5 )\n ~-0.91\n > rayleigh.pdf( 1.5 )\n ~0.04\n > rayleigh.quantile( 0.5 )\n ~7.064\n\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ )\n Returns the skewness of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.rayleigh.skewness( 11.0 )\n ~0.631\n > v = base.dists.rayleigh.skewness( 4.5 )\n ~0.631\n\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ )\n Returns the standard deviation of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.rayleigh.stdev( 9.0 )\n ~5.896\n > v = base.dists.rayleigh.stdev( 4.5 )\n ~2.948\n\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ )\n Returns the variance of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.rayleigh.variance( 9.0 )\n ~34.765\n > v = base.dists.rayleigh.variance( 4.5 )\n ~8.691\n\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x, n )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `x`, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.signrank.cdf( 3, 7 )\n ~0.039\n > y = base.dists.signrank.cdf( 1.8, 3 )\n ~0.375\n > y = base.dists.signrank.cdf( -1.0, 40 )\n 0.0\n > y = base.dists.signrank.cdf( NaN, 10 )\n NaN\n > y = base.dists.signrank.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.cdf.factory( n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.signrank.cdf.factory( 8 );\n > var y = myCDF( 5.7 )\n ~0.055\n > y = myCDF( 2.2 )\n ~0.012\n\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.signrank.cdf.factory( 8 );\n > var y = myCDF( 5.7 )\n ~0.055\n > y = myCDF( 2.2 )\n ~0.012","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x, n )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `x`, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.signrank.pdf( 3, 7 )\n ~0.0156\n > y = base.dists.signrank.pdf( 1.8, 3 )\n 0.0\n > y = base.dists.signrank.pdf( -1.0, 40 )\n 0.0\n > y = base.dists.signrank.pdf( NaN, 10 )\n NaN\n > y = base.dists.signrank.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.pdf.factory( n )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.signrank.pdf.factory( 8 );\n > var y = myPDF( 6.0 )\n ~0.0156\n > y = myPDF( 2.0 )\n ~0.0039\n\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.signrank.pdf.factory( 8 );\n > var y = myPDF( 6.0 )\n ~0.0156\n > y = myPDF( 2.0 )\n ~0.0039","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p, n )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.signrank.quantile( 0.8, 5 )\n 11\n > y = base.dists.signrank.quantile( 0.5, 4 )\n 5\n\n > y = base.dists.signrank.quantile( 1.1, 5 )\n NaN\n > y = base.dists.signrank.quantile( -0.2, 5 )\n NaN\n\n > y = base.dists.signrank.quantile( NaN, 5 )\n NaN\n > y = base.dists.signrank.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.quantile.factory( n )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n > var y = myQuantile( 0.4 )\n 16\n > y = myQuantile( 1.0 )\n 36\n\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n > var y = myQuantile( 0.4 )\n 16\n > y = myQuantile( 1.0 )\n 36","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x, r, v[, nranges] )\n Evaluates the cumulative distribution function (CDF) of a studentized range\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\n ~0.0644\n\n > y = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n ~0.913\n\n\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n\n Parameters\n ----------\n r: number\n Number of samples.\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n > var y = mycdf( 3.0 )\n ~0.712\n > y = mycdf( 1.0 )\n ~0.216\n\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n\n Parameters\n ----------\n r: number\n Number of samples.\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n > var y = mycdf( 3.0 )\n ~0.712\n > y = mycdf( 1.0 )\n ~0.216","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p, r, v[, nranges] )\n Evaluates the quantile function for a studentized range distribution.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = quantile( 0.5, 3.0, 2.0 )\n ~0.0644\n\n > y = quantile( 0.9, 17.0, 2.0 )\n ~0.913\n\n > y = quantile( 0.5, 3.0, 2.0, 2 )\n ~0.01\n\n > y = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\n NaN\n\n > y = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\n NaN\n > y = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\n NaN\n\n > y = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n NaN\n\n\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n\n Parameters\n ----------\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = quantile.factory( 3.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~1.791\n\n > y = myQuantile( 0.8 )\n ~3.245\n\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n\n Parameters\n ----------\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = quantile.factory( 3.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~1.791\n\n > y = myQuantile( 0.8 )\n ~3.245","base.dists.t.cdf":"\nbase.dists.t.cdf( x, v )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.t.cdf( 2.0, 0.1 )\n ~0.611\n > y = base.dists.t.cdf( 1.0, 2.0 )\n ~0.789\n > y = base.dists.t.cdf( -1.0, 4.0 )\n ~0.187\n > y = base.dists.t.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.cdf( 0.0, NaN )\n NaN\n > y = base.dists.t.cdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699\n\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699","base.dists.t.entropy":"\nbase.dists.t.entropy( v )\n Returns the differential entropy of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.t.entropy( 11.0 )\n ~1.512\n > v = base.dists.t.entropy( 4.5 )\n ~1.652\n\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v )\n Returns the excess kurtosis of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 2`, the function returns `NaN`.\n\n If provided `2 < v <= 4`, the function returns positive infinity.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.t.kurtosis( 11.0 )\n ~0.857\n > v = base.dists.t.kurtosis( 4.5 )\n 12.0\n\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x, v )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.t.logcdf( 2.0, 0.1 )\n ~-0.493\n > y = base.dists.t.logcdf( 1.0, 2.0 )\n ~-0.237\n > y = base.dists.t.logcdf( -1.0, 4.0 )\n ~-1.677\n > y = base.dists.t.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.logcdf( 0.0, NaN )\n NaN\n > y = base.dists.t.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.logcdf.factory( v )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.203\n > y = mylogcdf( 1.0 )\n ~-0.358\n\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.203\n > y = mylogcdf( 1.0 )\n ~-0.358","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x, v )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Student's t distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.t.logpdf( 0.3, 4.0 )\n ~-1.036\n > y = base.dists.t.logpdf( 2.0, 0.7 )\n ~-2.841\n > y = base.dists.t.logpdf( -1.0, 0.5 )\n ~-2.134\n > y = base.dists.t.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.t.logpdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.logpdf.factory( v )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n > var y = mylogPDF( 1.0 )\n ~-1.576\n\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n > var y = mylogPDF( 1.0 )\n ~-1.576","base.dists.t.mean":"\nbase.dists.t.mean( v )\n Returns the expected value of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.t.mean( 11.0 )\n 0.0\n > v = base.dists.t.mean( 4.5 )\n 0.0\n\n","base.dists.t.median":"\nbase.dists.t.median( v )\n Returns the median of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.t.median( 11.0 )\n 0.0\n > v = base.dists.t.median( 4.5 )\n 0.0\n\n","base.dists.t.mode":"\nbase.dists.t.mode( v )\n Returns the mode of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.t.mode( 11.0 )\n 0.0\n > v = base.dists.t.mode( 4.5 )\n 0.0\n\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x, v )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.t.pdf( 0.3, 4.0 )\n ~0.355\n > y = base.dists.t.pdf( 2.0, 0.7 )\n ~0.058\n > y = base.dists.t.pdf( -1.0, 0.5 )\n ~0.118\n > y = base.dists.t.pdf( 0.0, NaN )\n NaN\n > y = base.dists.t.pdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.pdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207\n\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207","base.dists.t.quantile":"\nbase.dists.t.quantile( p, v )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.t.quantile( 0.8, 1.0 )\n ~1.376\n > y = base.dists.t.quantile( 0.1, 1.0 )\n ~-3.078\n > y = base.dists.t.quantile( 0.5, 0.1 )\n 0.0\n\n > y = base.dists.t.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.t.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.t.quantile( 0.0, NaN )\n NaN\n\n > y = base.dists.t.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533\n\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533","base.dists.t.skewness":"\nbase.dists.t.skewness( v )\n Returns the skewness of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 3`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.t.skewness( 11.0 )\n 0.0\n > v = base.dists.t.skewness( 4.5 )\n 0.0\n\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v )\n Returns the standard deviation of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.t.stdev( 9.0 )\n ~1.134\n > v = base.dists.t.stdev( 4.5 )\n ~1.342\n\n","base.dists.t.T":"\nbase.dists.t.T( [v] )\n Returns a Student's t distribution object.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n t: Object\n Distribution instance.\n\n t.v: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n t.entropy: number\n Read-only property which returns the differential entropy.\n\n t.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n t.mean: number\n Read-only property which returns the expected value.\n\n t.median: number\n Read-only property which returns the median.\n\n t.mode: number\n Read-only property which returns the mode.\n\n t.skewness: number\n Read-only property which returns the skewness.\n\n t.stdev: number\n Read-only property which returns the standard deviation.\n\n t.variance: number\n Read-only property which returns the variance.\n\n t.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n t.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n t.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n t.pdf: Function\n Evaluates the probability density function (PDF).\n\n t.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var t = base.dists.t.T( 6.0 );\n > t.v\n 6.0\n > t.entropy\n ~1.592\n > t.kurtosis\n 3.0\n > t.mean\n 0.0\n > t.median\n 0.0\n > t.mode\n 0.0\n > t.skewness\n 0.0\n > t.stdev\n ~1.225\n > t.variance\n 1.5\n > t.cdf( 1.0 )\n ~0.822\n > t.logcdf( 1.0 )\n ~-0.196\n > t.logpdf( 1.5 )\n ~-2.075\n > t.pdf( 1.5 )\n ~0.126\n > t.quantile( 0.8 )\n ~0.906\n\n","base.dists.t.variance":"\nbase.dists.t.variance( v )\n Returns the variance of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.t.variance( 9.0 )\n ~1.286\n > v = base.dists.t.variance( 4.5 )\n ~1.8\n\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x, a, b, c )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n 0.875\n > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n 0.75\n > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.278\n > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95\n\n\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a, b, c )\n Returns the differential entropy of a triangular distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n ~-0.193\n > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n ~1.886\n > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n ~1.599\n\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a, b, c )\n Returns the excess kurtosis of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n -0.6\n > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n -0.6\n > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n -0.6\n\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x, a, b, c )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.134\n > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n ~-0.288\n > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n ~-1.281\n > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051\n\n\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x, a, b, c )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.693\n > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n 0.0\n > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n ~-2.89\n > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity\n\n\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a, b, c )\n Returns the expected value of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n ~0.6\n > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n 7.0\n > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a, b, c )\n Returns the median of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n ~0.632\n > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n ~6.708\n > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t, a, b, c )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n ~1.021\n > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n ~1.111\n > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n ~24.334\n > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n ~1.381\n > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205\n\n\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a, b, c )\n Returns the mode of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n 0.8\n > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n 5.0\n > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x, a, b, c )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n 0.5\n > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n 1.0\n > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.056\n > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0\n\n\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p, a, b, c )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n ~0.553\n > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n ~-0.452\n > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n -14.0\n > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n ~11.056\n\n > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n NaN\n\n > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n NaN\n\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225\n\n\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a, b, c )\n Returns the skewness of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n ~-0.476\n > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n ~0.532\n > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n 0.0\n\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a, b, c )\n Returns the standard deviation of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n ~0.216\n > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n ~1.78\n > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n ~1.225\n\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a, b, c] )\n Returns a triangular distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n c: number (optional)\n Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n Returns\n -------\n triangular: Object\n Distribution instance.\n\n triangular.a: number\n Minimum support. If set, the value must be smaller or equal to `b` and\n `c`.\n\n triangular.b: number\n Maximum support. If set, the value must be greater than or equal to `a`\n and `c`.\n\n triangular.c: number\n Mode. If set, the value must be greater than or equal to `a` and smaller\n than or equal to `b`.\n\n triangular.entropy: number\n Read-only property which returns the differential entropy.\n\n triangular.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n triangular.mean: number\n Read-only property which returns the expected value.\n\n triangular.median: number\n Read-only property which returns the median.\n\n triangular.mode: number\n Read-only property which returns the mode.\n\n triangular.skewness: number\n Read-only property which returns the skewness.\n\n triangular.stdev: number\n Read-only property which returns the standard deviation.\n\n triangular.variance: number\n Read-only property which returns the variance.\n\n triangular.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n triangular.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n triangular.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n triangular.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n triangular.pdf: Function\n Evaluates the probability density function (PDF).\n\n triangular.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n > triangular.a\n 0.0\n > triangular.b\n 1.0\n > triangular.c\n 0.5\n > triangular.entropy\n ~-0.193\n > triangular.kurtosis\n -0.6\n > triangular.mean\n 0.5\n > triangular.median\n 0.5\n > triangular.mode\n 0.5\n > triangular.skewness\n 0.0\n > triangular.stdev\n ~0.204\n > triangular.variance\n ~0.042\n > triangular.cdf( 0.8 )\n 0.92\n > triangular.logcdf( 0.8 )\n ~-0.083\n > triangular.logpdf( 0.8 )\n ~-0.223\n > triangular.mgf( 0.8 )\n ~1.512\n > triangular.pdf( 0.8 )\n ~0.8\n > triangular.quantile( 0.8 )\n ~0.684\n\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a, b, c )\n Returns the variance of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n ~0.047\n > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n ~3.167\n > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n ~1.5\n\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n 0.9\n > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n 0.25\n > y = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8\n\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a, b )\n Returns the differential entropy of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.entropy( 4.0, 12.0 )\n ~2.079\n > v = base.dists.uniform.entropy( 2.0, 8.0 )\n ~1.792\n\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a, b )\n Returns the excess kurtosis of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n -1.2\n\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n ~-0.105\n > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n ~-1.386\n > y = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223\n\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n ~-1.386\n > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n -infinity\n > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n 0.0\n > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity\n\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a, b )\n Returns the expected value of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.uniform.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a, b )\n Returns the median of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.uniform.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n ~372.495\n > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n ~0.688\n > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n ~3.195\n > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n NaN\n > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321\n\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x, a, b )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n 0.25\n > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n 1.0\n > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p, a, b )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n 0.8\n > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n 5.0\n\n > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2\n\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a, b )\n Returns the skewness of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.uniform.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a, b )\n Returns the standard deviation of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n ~0.289\n > v = base.dists.uniform.stdev( 4.0, 12.0 )\n ~2.309\n > v = base.dists.uniform.stdev( 2.0, 8.0 )\n ~1.732\n\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a, b] )\n Returns a uniform distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n uniform: Object\n Distribution instance.\n\n uniform.a: number\n Minimum support. If set, the value must be smaller than `b`.\n\n uniform.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n uniform.entropy: number\n Read-only property which returns the differential entropy.\n\n uniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n uniform.mean: number\n Read-only property which returns the expected value.\n\n uniform.median: number\n Read-only property which returns the median.\n\n uniform.skewness: number\n Read-only property which returns the skewness.\n\n uniform.stdev: number\n Read-only property which returns the standard deviation.\n\n uniform.variance: number\n Read-only property which returns the variance.\n\n uniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n uniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n uniform.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n uniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n uniform.pdf: Function\n Evaluates the probability density function (PDF).\n\n uniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n > uniform.a\n 0.0\n > uniform.b\n 1.0\n > uniform.entropy\n 0.0\n > uniform.kurtosis\n -1.2\n > uniform.mean\n 0.5\n > uniform.median\n 0.5\n > uniform.skewness\n 0.0\n > uniform.stdev\n ~0.289\n > uniform.variance\n ~0.083\n > uniform.cdf( 0.8 )\n 0.8\n > uniform.logcdf( 0.5 )\n ~-0.693\n > uniform.logpdf( 1.0 )\n ~-0.0\n > uniform.mgf( 0.8 )\n ~1.532\n > uniform.pdf( 0.8 )\n 1.0\n > uniform.quantile( 0.8 )\n 0.8\n\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a, b )\n Returns the variance of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.uniform.variance( 0.0, 1.0 )\n ~0.083\n > v = base.dists.uniform.variance( 4.0, 12.0 )\n ~5.333\n > v = base.dists.uniform.variance( 2.0, 8.0 )\n 3.0\n\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763\n\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k, λ )\n Returns the differential entropy of a Weibull distribution (in nats).\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.entropy( 4.0, 12.0 )\n ~2.532\n > v = base.dists.weibull.entropy( 8.0, 2.0 )\n ~0.119\n\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k, λ )\n Returns the excess kurtosis of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n ~-0.252\n > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n ~0.328\n\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x, k, λ )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n ~-0.145\n > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27\n\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x, k, λ )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n ~-3.307\n > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863\n\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k, λ )\n Returns the expected value of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.weibull.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.mean( 4.0, 12.0 )\n ~10.877\n > v = base.dists.weibull.mean( 8.0, 2.0 )\n ~1.883\n\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k, λ )\n Returns the median of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.weibull.median( 1.0, 1.0 )\n ~0.693\n > v = base.dists.weibull.median( 4.0, 12.0 )\n ~10.949\n > v = base.dists.weibull.median( 8.0, 2.0 )\n ~1.91\n\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x, k, λ )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n ~2.0\n > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n ~0.019\n\n > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137\n\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k, λ )\n Returns the mode of a Weibull distribution.\n\n If `0 < k <= 1`, the function returns `0.0`.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.weibull.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.weibull.mode( 4.0, 12.0 )\n ~11.167\n > v = base.dists.weibull.mode( 8.0, 2.0 )\n ~1.967\n\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n ~0.037\n > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155\n\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p, k, λ )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n ~1.609\n > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n ~3.33\n\n > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147\n\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k, λ )\n Returns the skewness of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.weibull.skewness( 4.0, 12.0 )\n ~-0.087\n > v = base.dists.weibull.skewness( 8.0, 2.0 )\n ~-0.534\n\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k, λ )\n Returns the standard deviation of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.stdev( 4.0, 12.0 )\n ~3.051\n > v = base.dists.weibull.stdev( 8.0, 2.0 )\n ~0.279\n\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k, λ )\n Returns the variance of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.weibull.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.variance( 4.0, 12.0 )\n ~9.311\n > v = base.dists.weibull.variance( 8.0, 2.0 )\n ~0.078\n\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k, λ] )\n Returns a Weibull distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n λ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n weibull: Object\n Distribution instance.\n\n weibull.k: number\n Shape parameter. If set, the value must be greater than `0`.\n\n weibull.lambda: number\n Scale parameter. If set, the value must be greater than `0`.\n\n weibull.entropy: number\n Read-only property which returns the differential entropy.\n\n weibull.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n weibull.mean: number\n Read-only property which returns the expected value.\n\n weibull.median: number\n Read-only property which returns the median.\n\n weibull.mode: number\n Read-only property which returns the mode.\n\n weibull.skewness: number\n Read-only property which returns the skewness.\n\n weibull.stdev: number\n Read-only property which returns the standard deviation.\n\n weibull.variance: number\n Read-only property which returns the variance.\n\n weibull.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n weibull.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n weibull.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n weibull.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n weibull.pdf: Function\n Evaluates the probability density function (PDF).\n\n weibull.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n > weibull.k\n 6.0\n > weibull.lambda\n 5.0\n > weibull.entropy\n ~1.299\n > weibull.kurtosis\n ~0.035\n > weibull.mean\n ~4.639\n > weibull.median\n ~4.704\n > weibull.mode\n ~4.85\n > weibull.skewness\n ~-0.373\n > weibull.stdev\n ~0.899\n > weibull.variance\n ~0.808\n > weibull.cdf( 3.0 )\n ~0.046\n > weibull.logcdf( 3.0 )\n ~-3.088\n > weibull.logpdf( 1.0 )\n ~-7.865\n > weibull.mgf( -0.5 )\n ~0.075\n > weibull.pdf( 3.0 )\n ~0.089\n > weibull.quantile( 0.8 )\n ~5.413\n\n","base.ellipe":"\nbase.ellipe( m )\n Computes the complete elliptic integral of the second kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipe( 0.5 )\n ~1.351\n > y = base.ellipe( -1.0 )\n ~1.910\n > y = base.ellipe( 2.0 )\n NaN\n > y = base.ellipe( PINF )\n NaN\n > y = base.ellipe( NINF )\n NaN\n > y = base.ellipe( NaN )\n NaN\n\n See Also\n --------\n base.ellipj, base.ellipk\n","base.ellipj":"\nbase.ellipj( u, m )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: Array\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var v = base.ellipj( 0.3, 0.5 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > v = base.ellipj( 0.0, 0.0 )\n [ ~0.0, ~1.0, ~1.0, ~0.0 ]\n > v = base.ellipj( Infinity, 1.0 )\n [ ~1.0, ~0.0, ~0.0, ~1.571 ]\n > v = base.ellipj( 0.0, -2.0)\n [ ~0.0, ~1.0, ~1.0, NaN ]\n > v = base.ellipj( NaN, NaN )\n [ NaN, NaN, NaN, NaN ]\n\n\nbase.ellipj.assign( u, m, out, stride, offset )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var out = new Float64Array( 4 );\n > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > var bool = ( v === out )\n true\n\n\nbase.ellipj.sn( u, m )\n Computes the Jacobi elliptic function sn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function sn.\n\n Examples\n --------\n > var v = base.ellipj.sn( 0.3, 0.5 )\n ~0.293\n\n\nbase.ellipj.cn( u, m )\n Computes the Jacobi elliptic functions cn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function cn.\n\n Examples\n --------\n > var v = base.ellipj.cn( 0.3, 0.5 )\n ~0.956\n\n\nbase.ellipj.dn( u, m )\n Computes the Jacobi elliptic function dn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function dn.\n\n Examples\n --------\n > var v = base.ellipj.dn( 0.3, 0.5 )\n ~0.978\n\n\nbase.ellipj.am( u, m )\n Computes the Jacobi amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function am.\n\n Examples\n --------\n > var v = base.ellipj.am( 0.3, 0.5 )\n ~0.298\n\n See Also\n --------\n base.ellipe, base.ellipk","base.ellipj.assign":"\nbase.ellipj.assign( u, m, out, stride, offset )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var out = new Float64Array( 4 );\n > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > var bool = ( v === out )\n true","base.ellipj.sn":"\nbase.ellipj.sn( u, m )\n Computes the Jacobi elliptic function sn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function sn.\n\n Examples\n --------\n > var v = base.ellipj.sn( 0.3, 0.5 )\n ~0.293","base.ellipj.cn":"\nbase.ellipj.cn( u, m )\n Computes the Jacobi elliptic functions cn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function cn.\n\n Examples\n --------\n > var v = base.ellipj.cn( 0.3, 0.5 )\n ~0.956","base.ellipj.dn":"\nbase.ellipj.dn( u, m )\n Computes the Jacobi elliptic function dn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function dn.\n\n Examples\n --------\n > var v = base.ellipj.dn( 0.3, 0.5 )\n ~0.978","base.ellipj.am":"\nbase.ellipj.am( u, m )\n Computes the Jacobi amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function am.\n\n Examples\n --------\n > var v = base.ellipj.am( 0.3, 0.5 )\n ~0.298\n\n See Also\n --------\n base.ellipe, base.ellipk","base.ellipk":"\nbase.ellipk( m )\n Computes the complete elliptic integral of the first kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipk( 0.5 )\n ~1.854\n > y = base.ellipk( -1.0 )\n ~1.311\n > y = base.ellipk( 2.0 )\n NaN\n > y = base.ellipk( PINF )\n NaN\n > y = base.ellipk( NINF )\n NaN\n > y = base.ellipk( NaN )\n NaN\n\n See Also\n --------\n base.ellipe, base.ellipj\n","base.endsWith":"\nbase.endsWith( str, search, len )\n Tests if a string ends with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, and is thus\n equivalent to `str.length + len`. Default: str.length.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string ends with the characters of another\n string.\n\n Examples\n --------\n > var bool = base.endsWith( 'beep', 'ep', 4 )\n true\n > bool = base.endsWith( 'Beep', 'op', 4 )\n false\n > bool = base.endsWith( 'Beep', 'ee', 3 )\n true\n > bool = base.endsWith( 'Beep', 'ee', -1 )\n true\n > bool = base.endsWith( 'beep', '', 4 )\n true\n\n See Also\n --------\n base.startsWith\n","base.epsdiff":"\nbase.epsdiff( x, y[, scale] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If computing the relative difference in units of epsilon will result in\n overflow, the function returns the maximum double-precision floating-point\n number.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference in units of double-precision floating-point epsilon.\n\n Examples\n --------\n > var d = base.epsdiff( 12.15, 12.149999999999999 )\n ~0.658\n > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n ~64761.512\n\n // Custom scale function:\n > function scale( x, y ) { return ( x > y ) ? y : x; };\n > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n ~44\n\n See Also\n --------\n base.absdiff, base.reldiff\n","base.erf":"\nbase.erf( x )\n Evaluates the error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erf( 2.0 )\n ~0.9953\n > y = base.erf( -1.0 )\n ~-0.8427\n > y = base.erf( -0.0 )\n -0.0\n > y = base.erf( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfinv, base.erfcinv\n","base.erfc":"\nbase.erfc( x )\n Evaluates the complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfc( 2.0 )\n ~0.0047\n > y = base.erfc( -1.0 )\n ~1.8427\n > y = base.erfc( 0.0 )\n 1.0\n > y = base.erfc( PINF )\n 0.0\n > y = base.erfc( NINF )\n 2.0\n > y = base.erfc( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfinv, base.erfcinv, base.erfcx\n","base.erfcinv":"\nbase.erfcinv( x )\n Evaluates the inverse complementary error function.\n\n The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcinv( 0.5 )\n ~0.4769\n > y = base.erfcinv( 0.8 )\n ~0.1791\n > y = base.erfcinv( 0.0 )\n Infinity\n > y = base.erfcinv( 2.0 )\n -Infinity\n > y = base.erfcinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfinv, base.erfcx\n","base.erfcx":"\nbase.erfcx( x )\n Evaluates the scaled complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcx( 1.0 )\n ~0.4276\n > y = base.erfcx( -1.0 )\n ~5.01\n > y = base.erfcx( 0.0 )\n 1.0\n > y = base.erfcx( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfcinv, base.erf, base.erfinv","base.erfinv":"\nbase.erfinv( x )\n Evaluates the inverse error function.\n\n If `|x| > 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfinv( 0.5 )\n ~0.4769\n > y = base.erfinv( 0.8 )\n ~0.9062\n > y = base.erfinv( 0.0 )\n 0.0\n > y = base.erfinv( -0.0 )\n -0.0\n > y = base.erfinv( -1.0 )\n -Infinity\n > y = base.erfinv( 1.0 )\n Infinity\n > y = base.erfinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfcinv\n","base.eta":"\nbase.eta( s )\n Evaluates the Dirichlet eta function for a double-precision\n floating-point number `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.eta( 0.0 )\n 0.5\n > y = base.eta( -1.0 )\n 0.25\n > y = base.eta( 1.0 )\n ~0.6931\n > y = base.eta( 3.14 )\n ~0.9096\n > y = base.eta( NaN )\n NaN\n\n","base.evalpoly":"\nbase.evalpoly( c, x )\n Evaluates a polynomial using double-precision floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n out: number\n Evaluated polynomial.\n\n Examples\n --------\n > var arr = [ 3.0, 2.0, 1.0 ];\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = base.evalpoly( arr, 10.0 )\n 123.0\n\n\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = f( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = f( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = f( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = f( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational","base.evalrational":"\nbase.evalrational( P, Q, x )\n Evaluates a rational function using double-precision floating-point\n arithmetic.\n\n A rational function `f(x)` is defined as\n\n P(x)\n f(x) = ----\n Q(x)\n\n where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n For polynomials of different degree, the coefficient array for the lower\n degree polynomial should be padded with zeros.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the rational function.\n\n Returns\n -------\n out: number\n Evaluated rational function.\n\n Examples\n --------\n // 2x^3 + 4x^2 - 5x^1 - 6x^0\n > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n // 0.5x^1 + 3x^0\n > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n // Evaluate the rational function:\n > var v = base.evalrational( P, Q, 6.0 )\n 90.0\n\n\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var f = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = f( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = f( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly\n","base.evalrational.factory":"\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var f = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = f( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = f( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly","base.exp":"\nbase.exp( x )\n Evaluates the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp( 4.0 )\n ~54.5982\n > y = base.exp( -9.0 )\n ~1.234e-4\n > y = base.exp( 0.0 )\n 1.0\n > y = base.exp( NaN )\n NaN\n\n See Also\n --------\n base.exp10, base.exp2, base.expm1, base.ln\n","base.exp2":"\nbase.exp2( x )\n Evaluates the base 2 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp2( 3.0 )\n 8.0\n > y = base.exp2( -9.0 )\n ~0.002\n > y = base.exp2( 0.0 )\n 1.0\n > y = base.exp2( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp10, base.log2\n","base.exp10":"\nbase.exp10( x )\n Evaluates the base 10 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp10( 3.0 )\n 1000\n > y = base.exp10( -9.0 )\n 1.0e-9\n > y = base.exp10( 0.0 )\n 1.0\n > y = base.exp10( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp2, base.log10\n","base.expit":"\nbase.expit( x )\n Evaluates the standard logistic function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expit( 0.0 )\n 0.5\n > y = base.expit( 1.0 )\n ~0.731\n > y = base.expit( -1.0 )\n ~0.269\n > y = base.expit( Infinity )\n 1.0\n > y = base.expit( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.logit","base.expm1":"\nbase.expm1( x )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1( 0.2 )\n ~0.221\n > y = base.expm1( -9.0 )\n ~-1.0\n > y = base.expm1( 0.0 )\n 0.0\n > y = base.expm1( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.expm1rel\n","base.expm1rel":"\nbase.expm1rel( x )\n Relative error exponential.\n\n When `x` is near zero,\n\n e^x - 1\n\n can suffer catastrophic cancellation (i.e., significant loss of precision).\n This function avoids the loss of precision when `x` is near zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1rel( 0.0 )\n 1.0\n > y = base.expm1rel( 1.0 )\n ~1.718\n > y = base.expm1rel( -1.0 )\n ~0.632\n > y = base.expm1rel( NaN )\n NaN\n\t\n See Also\n --------\n base.exp, base.expm1\n","base.exponent":"\nbase.exponent( x )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponent( 3.14e-307 )\n -1019\n > exponent = base.exponent( -3.14 )\n 1\n > exponent = base.exponent( 0.0 )\n -1023\n > exponent = base.exponent( NaN )\n 1024\n\n See Also\n --------\n base.exponentf\n","base.exponentf":"\nbase.exponentf( x )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\n 114\n > exponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\n -112\n > exponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\n 1\n > exponent = base.exponentf( 0.0 )\n -127\n > exponent = base.exponentf( NaN )\n 128\n\n See Also\n --------\n base.exponent\n","base.factorial":"\nbase.factorial( x )\n Evaluates the factorial of `x`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Factorial.\n\n Examples\n --------\n > var y = base.factorial( 3.0 )\n 6.0\n > y = base.factorial( -1.5 )\n ~-3.545\n > y = base.factorial( -0.5 )\n ~1.772\n > y = base.factorial( 0.5 )\n ~0.886\n > y = base.factorial( -10.0 )\n NaN\n > y = base.factorial( 171.0 )\n Infinity\n > y = base.factorial( NaN )\n NaN\n\n See Also\n --------\n base.factorialln\n","base.factorial2":"\nbase.factorial2( n )\n Evaluates the double factorial of `n`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: number\n Input value.\n\n Returns\n -------\n y: number\n Double factorial.\n\n Examples\n --------\n > var y = base.factorial2( 3 )\n 3\n > y = base.factorial2( 5 )\n 15\n > y = base.factorial2( 6 )\n 48\n > y = base.factorial2( 301 )\n Infinity\n > y = base.factorial2( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.factorialln":"\nbase.factorialln( x )\n Evaluates the natural logarithm of the factorial of `x`.\n\n For input values other than negative integers, the function returns\n\n ln( x! ) = ln( Γ(x+1) )\n\n where `Γ` is the Gamma function. For negative integers, the function returns\n `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the factorial of `x`.\n\n Examples\n --------\n > var y = base.factorialln( 3.0 )\n ~1.792\n > y = base.factorialln( 2.4 )\n ~1.092\n > y = base.factorialln( -1.0 )\n NaN\n > y = base.factorialln( -1.5 )\n ~1.266\n > y = base.factorialln( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.fallingFactorial":"\nbase.fallingFactorial( x, n )\n Computes the falling factorial of `x` and `n`.\n\n If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.fallingFactorial( 0.9, 5 )\n ~0.644\n > v = base.fallingFactorial( -9.0, 3 )\n -990.0\n > v = base.fallingFactorial( 0.0, 2 )\n 0.0\n > v = base.fallingFactorial( 3.0, -2 )\n NaN\n\n See Also\n --------\n base.risingFactorial\n","base.fibonacci":"\nbase.fibonacci( n )\n Computes the nth Fibonacci number.\n\n Fibonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2}\n\n with seed values F_0 = 0 and F_1 = 1.\n\n If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Fibonacci number.\n\n Examples\n --------\n > var y = base.fibonacci( 0 )\n 0\n > y = base.fibonacci( 1 )\n 1\n > y = base.fibonacci( 2 )\n 1\n > y = base.fibonacci( 3 )\n 2\n > y = base.fibonacci( 4 )\n 3\n > y = base.fibonacci( 79 )\n NaN\n > y = base.fibonacci( NaN )\n NaN\n\n See Also\n --------\n base.binet, base.fibonacciIndex, base.lucas, base.negafibonacci\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F )\n Computes the Fibonacci number index.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n F: integer\n Fibonacci number.\n\n Returns\n -------\n n: number\n Fibonacci number index.\n\n Examples\n --------\n > var n = base.fibonacciIndex( 2 )\n 3\n > n = base.fibonacciIndex( 3 )\n 4\n > n = base.fibonacciIndex( 5 )\n 5\n > n = base.fibonacciIndex( NaN )\n NaN\n > n = base.fibonacciIndex( 1 )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.fibpoly":"\nbase.fibpoly( n, x )\n Evaluates a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Fibonacci polynomial.\n\n Returns\n -------\n out: number\n Evaluated Fibonacci polynomial.\n\n Examples\n --------\n // 2^4 + 3*2^2 + 1\n > var v = base.fibpoly( 5, 2.0 )\n 29.0\n\n\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly","base.firstCodePoint":"\nbase.firstCodePoint( str, n )\n Returns the first `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstCodePoint( 'beep', 1 )\n 'b'\n > out = base.firstCodePoint( 'Boop', 1 )\n 'B'\n > out = base.firstCodePoint( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodeUnit, base.firstGraphemeCluster, base.lastCodePoint, base.removeFirstCodePoint, firstChar\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str, n )\n Returns the first `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstCodeUnit( 'beep', 1 )\n 'b'\n > out = base.firstCodeUnit( 'Boop', 1 )\n 'B'\n > out = base.firstCodeUnit( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodePoint, base.firstGraphemeCluster, base.last, base.removeFirst, firstChar\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str, n )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstGraphemeCluster( 'beep', 1 )\n 'b'\n > out = base.firstGraphemeCluster( 'Boop', 1 )\n 'B'\n > out = base.firstGraphemeCluster( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodeUnit, base.firstCodePoint, base.lastGraphemeCluster, base.removeFirstGraphemeCluster, firstChar\n","base.flipsign":"\nbase.flipsign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n or `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`; otherwise, behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsign( -3.0, 10.0 )\n -3.0\n > z = base.flipsign( -3.0, -1.0 )\n 3.0\n > z = base.flipsign( 1.0, -0.0 )\n -1.0\n > z = base.flipsign( -3.0, -0.0 )\n 3.0\n > z = base.flipsign( -0.0, 1.0 )\n -0.0\n > z = base.flipsign( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysign\n","base.flipsignf":"\nbase.flipsignf( x, y )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `255`, a significand greater than `0`, and a sign bit equal to either `1` or\n `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`; otherwise, behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Single-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsignf( -3.0, 10.0 )\n -3.0\n > z = base.flipsignf( -3.0, -1.0 )\n 3.0\n > z = base.flipsignf( 1.0, -0.0 )\n -1.0\n > z = base.flipsignf( -3.0, -0.0 )\n 3.0\n > z = base.flipsignf( -0.0, 1.0 )\n -0.0\n > z = base.flipsignf( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysignf, base.flipsign\n","base.float32ToInt32":"\nbase.float32ToInt32( x )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\n 0\n > y = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\n -3\n > y = base.float32ToInt32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToInt32( FLOAT32_PINF )\n 0\n > y = base.float32ToInt32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToUint32","base.float32ToUint32":"\nbase.float32ToUint32( x )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\n 0\n > y = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\n 4294967293\n > y = base.float32ToUint32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToUint32( FLOAT32_PINF )\n 0\n > y = base.float32ToUint32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToInt32","base.float64ToFloat32":"\nbase.float64ToFloat32( x )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: float\n Nearest single-precision floating-point number.\n\n Examples\n --------\n > var y = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n","base.float64ToInt32":"\nbase.float64ToInt32( x )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToInt32( 4294967295.0 )\n -1\n > y = base.float64ToInt32( 3.14 )\n 3\n > y = base.float64ToInt32( -3.14 )\n -3\n > y = base.float64ToInt32( NaN )\n 0\n > y = base.float64ToInt32( PINF )\n 0\n > y = base.float64ToInt32( NINF )\n 0\n\n See Also\n --------\n base.float64ToUint32","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n Returns\n -------\n out: Uint8Array\n Byte array.\n\n Examples\n --------\n > var y = base.float64ToInt64Bytes( 4294967297.0 )\n \n\n\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Uint8Array( 16 );\n > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n \n\n See Also\n --------\n base.float64ToInt32","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Uint8Array( 16 );\n > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n \n\n See Also\n --------\n base.float64ToInt32","base.float64ToUint32":"\nbase.float64ToUint32( x )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToUint32( 4294967297.0 )\n 1\n > y = base.float64ToUint32( 3.14 )\n 3\n > y = base.float64ToUint32( -3.14 )\n 4294967293\n > y = base.float64ToUint32( NaN )\n 0\n > y = base.float64ToUint32( PINF )\n 0\n > y = base.float64ToUint32( NINF )\n 0\n\n See Also\n --------\n base.float64ToInt32","base.floor":"\nbase.floor( x )\n Rounds a double-precision floating-point number toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor( 3.14 )\n 3.0\n > y = base.floor( -4.2 )\n -5.0\n > y = base.floor( -4.6 )\n -5.0\n > y = base.floor( 9.5 )\n 9.0\n > y = base.floor( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.round\n","base.floor2":"\nbase.floor2( x )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor2( 3.14 )\n 2.0\n > y = base.floor2( -4.2 )\n -8.0\n > y = base.floor2( -4.6 )\n -8.0\n > y = base.floor2( 9.5 )\n 8.0\n > y = base.floor2( 13.0 )\n 8.0\n > y = base.floor2( -13.0 )\n -16.0\n > y = base.floor2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor, base.floor10, base.round2\n","base.floor10":"\nbase.floor10( x )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor10( 3.14 )\n 1.0\n > y = base.floor10( -4.2 )\n -10.0\n > y = base.floor10( -4.6 )\n -10.0\n > y = base.floor10( 9.5 )\n 1.0\n > y = base.floor10( 13.0 )\n 10.0\n > y = base.floor10( -13.0 )\n -100.0\n > y = base.floor10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor, base.floor2, base.round10\n","base.floorb":"\nbase.floorb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.floorb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward negative infinity:\n > y = base.floorb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floor, base.floorn, base.roundb\n","base.floorf":"\nbase.floorf( x )\n Rounds a single-precision floating-point number toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorf( 3.14 )\n 3.0\n > y = base.floorf( -4.2 )\n -5.0\n > y = base.floorf( -4.6 )\n -5.0\n > y = base.floorf( 9.5 )\n 9.0\n > y = base.floorf( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceilf, base.floor\n","base.floorn":"\nbase.floorn( x, n )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round toward negative infinity behavior:\n > y = base.floorn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.floorn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floor, base.floorb, base.roundn\n","base.floorsd":"\nbase.floorsd( x, n, b )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorsd( 3.14159, 5, 10 )\n 3.1415\n > y = base.floorsd( 3.14159, 1, 10 )\n 3.0\n > y = base.floorsd( 12368.0, 2, 10 )\n 12000.0\n > y = base.floorsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floor, base.roundsd, base.truncsd\n","base.forEachChar":"\nbase.forEachChar( str, clbk[, thisArg] )\n Invokes a function for each UTF-16 code unit in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each UTF-16 code unit in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachChar( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachCodePoint, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str, clbk[, thisArg] )\n Invokes a function for each Unicode code point in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: code point.\n - index: starting code point index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each Unicode code point in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachCodePoint( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str, clbk[, thisArg] )\n Invokes a function for each Unicode code point in a string, iterating from\n right to left.\n\n When invoked, the provided function is provided three arguments:\n\n - value: code point.\n - index: starting code point index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each Unicode code point in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachCodePointRight( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachCodePoint, base.forEachRight\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str, clbk[, thisArg] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: grapheme cluster.\n - index: starting grapheme cluster index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each grapheme cluster in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachGraphemeCluster( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachCodePoint, forEachChar\n","base.forEachRight":"\nbase.forEachRight( str, clbk[, thisArg] )\n Invokes a function for each UTF-16 code unit in a string, iterating from\n right to left.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n Function to invoke for each UTF-16 code unit in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachRight( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachCodePointRight\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens, ...args )\n Generate string from a token array by interpolating values.\n\n Parameters\n ----------\n tokens: Array\n Array of string parts and format identifier objects.\n\n args: ...any\n Variable values.\n\n Returns\n -------\n out: string\n Formatted string.\n\n Examples\n --------\n > var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\n 'beep boop'\n > out = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\n 'baz 1.00'\n > out = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n ' 12'\n\n See Also\n --------\n base.formatTokenize\n","base.formatTokenize":"\nbase.formatTokenize( str )\n Tokenize a string into an array of string parts and format identifier\n objects.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: Array\n Array of string parts and format identifier objects.\n\n Examples\n --------\n > var out = base.formatTokenize( 'Hello %s!' )\n [ 'Hello ', {...}, '!' ]\n > out = base.formatTokenize( '%s %s %d' )\n [ {...}, ' ', {...}, ' ', {...}, ' ' ]\n > out = base.formatTokenize( 'Pi: %.2f' )\n [ 'Pi: ', {...} ]\n\n See Also\n --------\n base.formatInterpolate\n","base.fresnel":"\nbase.fresnel( x )\n Computes the Fresnel integrals S(x) and C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: Array\n S(x) and C(x).\n\n Examples\n --------\n > var y = base.fresnel( 0.0 )\n [ ~0.0, ~0.0 ]\n > y = base.fresnel( 1.0 )\n [ ~0.438, ~0.780 ]\n > y = base.fresnel( PINF )\n [ ~0.5, ~0.5 ]\n > y = base.fresnel( NINF )\n [ ~-0.5, ~-0.5 ]\n > y = base.fresnel( NaN )\n [ NaN, NaN ]\n\n\nbase.fresnel.assign( x, out, stride, offset )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n S(x) and C(x).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels","base.fresnel.assign":"\nbase.fresnel.assign( x, out, stride, offset )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n S(x) and C(x).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels","base.fresnelc":"\nbase.fresnelc( x )\n Computes the Fresnel integral C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n C(x).\n\n Examples\n --------\n > var y = base.fresnelc( 0.0 )\n ~0.0\n > y = base.fresnelc( 1.0 )\n ~0.780\n > y = base.fresnelc( PINF )\n ~0.5\n > y = base.fresnelc( NINF )\n ~-0.5\n > y = base.fresnelc( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnels\n","base.fresnels":"\nbase.fresnels( x )\n Computes the Fresnel integral S(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n S(x).\n\n Examples\n --------\n > var y = base.fresnels( 0.0 )\n ~0.0\n > y = base.fresnels( 1.0 )\n ~0.438\n > y = base.fresnels( PINF )\n ~0.5\n > y = base.fresnels( NINF )\n ~-0.5\n > y = base.fresnels( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnelc\n","base.frexp":"\nbase.frexp( x )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = base.frexp( 4.0 )\n [ 0.5, 3 ]\n > out = base.frexp( 0.0 )\n [ 0.0, 0 ]\n > out = base.frexp( -0.0 )\n [ -0.0, 0 ]\n > out = base.frexp( NaN )\n [ NaN, 0 ]\n > out = base.frexp( PINF )\n [ Infinity, 0 ]\n > out = base.frexp( NINF )\n [ -Infinity, 0 ]\n\n\nbase.frexp.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.frexp.assign( 4.0, out, 1, 0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp\n","base.frexp.assign":"\nbase.frexp.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.frexp.assign( 4.0, out, 1, 0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp","base.fromBinaryString":"\nbase.fromBinaryString( bstr )\n Creates a double-precision floating-point number from a literal bit\n representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var bstr;\n > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n > var val = base.fromBinaryString( bstr )\n 4.0\n > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n > val = base.fromBinaryString( bstr )\n 3.141592653589793\n > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n > val = base.fromBinaryString( bstr )\n -1.0e308\n\n // The function handles subnormals:\n > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n > val = base.fromBinaryString( bstr )\n -3.14e-320\n > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n > val = base.fromBinaryString( bstr )\n 5.0e-324\n\n // The function handles special values:\n > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n 0.0\n > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -0.0\n > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n NaN\n > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n Infinity\n > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -Infinity\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var bstr = '01000000100000000000000000000000';\n > var val = base.fromBinaryStringf( bstr )\n 4.0\n > bstr = '01000000010010010000111111011011';\n > val = base.fromBinaryStringf( bstr )\n ~3.14\n > bstr = '11111111011011000011101000110011';\n > val = base.fromBinaryStringf( bstr )\n ~-3.14e+38\n\n // The function handles subnormals:\n > bstr = '10000000000000000000000000010110';\n > val = base.fromBinaryStringf( bstr )\n ~-3.08e-44\n > bstr = '00000000000000000000000000000001';\n > val = base.fromBinaryStringf( bstr )\n ~1.40e-45\n\n // The function handles special values:\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n 0.0\n > bstr = '10000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -0.0\n > bstr = '01111111110000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n NaN\n > bstr = '01111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n Infinity\n > bstr = '11111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -Infinity\n\n See Also\n --------\n base.toBinaryStringf, base.fromBinaryString\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr )\n Creates an unsigned 8-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 8-bit integer.\n\n Examples\n --------\n > var bstr = '01010101';\n > var val = base.fromBinaryStringUint8( bstr )\n 85\n > bstr = '00000000';\n > val = base.fromBinaryStringUint8( bstr )\n 0\n > bstr = '00000010';\n > val = base.fromBinaryStringUint8( bstr )\n 2\n > bstr = '11111111';\n > val = base.fromBinaryStringUint8( bstr )\n 255\n\n See Also\n --------\n base.fromBinaryStringUint16, base.fromBinaryStringUint32, base.toBinaryStringUint8\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr )\n Creates an unsigned 16-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 16-bit integer.\n\n Examples\n --------\n > var bstr = '0101010101010101';\n > var val = base.fromBinaryStringUint16( bstr )\n 21845\n > bstr = '0000000000000000';\n > val = base.fromBinaryStringUint16( bstr )\n 0\n > bstr = '0000000000000010';\n > val = base.fromBinaryStringUint16( bstr )\n 2\n > bstr = '1111111111111111';\n > val = base.fromBinaryStringUint16( bstr )\n 65535\n\n See Also\n --------\n base.toBinaryStringUint16, base.fromBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr )\n Creates an unsigned 32-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var bstr = '01010101010101010101010101010101';\n > var val = base.fromBinaryStringUint32( bstr )\n 1431655765\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringUint32( bstr )\n 0\n > bstr = '00000000000000000000000000000010';\n > val = base.fromBinaryStringUint32( bstr )\n 2\n > bstr = '11111111111111111111111111111111';\n > val = base.fromBinaryStringUint32( bstr )\n 4294967295\n\n See Also\n --------\n base.fromBinaryStringUint16, base.toBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes, stride, offset )\n Converts a signed 64-bit integer byte array to a double-precision floating-\n point number.\n\n The function assumes host byte order (endianness).\n\n Parameters\n ----------\n bytes: Array|TypedArray|Object\n Byte array.\n\n stride: integer\n Index stride.\n\n offset: integer\n Index offset.\n\n Returns\n -------\n out: number\n Number.\n\n Examples\n --------\n > var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\n > var y = base.fromInt64Bytes( bytes, 1, 0 )\n -1.0\n\n See Also\n --------\n base.float64ToInt64Bytes","base.fromWordf":"\nbase.fromWordf( word )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n\n Parameters\n ----------\n word: integer\n Unsigned integer.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var word = 1068180177; // => 0 01111111 01010110010001011010001\n > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n 1.3370000123977661\n\n See Also\n --------\n base.fromWords\n","base.fromWords":"\nbase.fromWords( high, low )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n Parameters\n ----------\n high: integer\n Higher order word (unsigned 32-bit integer).\n\n low: integer\n Lower order word (unsigned 32-bit integer).\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var v = base.fromWords( 1774486211, 2479577218 )\n 3.14e201\n > v = base.fromWords( 3221823995, 1413754136 )\n -3.141592653589793\n > v = base.fromWords( 0, 0 )\n 0.0\n > v = base.fromWords( 2147483648, 0 )\n -0.0\n > v = base.fromWords( 2146959360, 0 )\n NaN\n > v = base.fromWords( 2146435072, 0 )\n Infinity\n > v = base.fromWords( 4293918720, 0 )\n -Infinity\n\n See Also\n --------\n base.fromWordf\n","base.gamma":"\nbase.gamma( x )\n Evaluates the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma( 4.0 )\n 6.0\n > y = base.gamma( -1.5 )\n ~2.363\n > y = base.gamma( -0.5 )\n ~-3.545\n > y = base.gamma( 0.5 )\n ~1.772\n > y = base.gamma( 0.0 )\n Infinity\n > y = base.gamma( -0.0 )\n -Infinity\n > y = base.gamma( NaN )\n NaN\n\n See Also\n --------\n base.gamma1pm1, base.gammainc, base.gammaincinv, base.gammaln\n","base.gamma1pm1":"\nbase.gamma1pm1( x )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma1pm1( 0.2 )\n ~-0.082\n > y = base.gamma1pm1( -6.7 )\n ~-0.991\n > y = base.gamma1pm1( 0.0 )\n 0.0\n > y = base.gamma1pm1( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv, base.gammaln\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z, delta )\n Computes the ratio of two gamma functions.\n\n The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n Parameters\n ----------\n z: number\n First gamma parameter.\n\n delta: number\n Difference.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n ~0.042\n > y = base.gammaDeltaRatio( 4.0, 0.5 )\n ~0.516\n > y = base.gammaDeltaRatio( 100.0, 0.0 )\n 1.0\n > y = base.gammaDeltaRatio( NaN, 3.0 )\n NaN\n > y = base.gammaDeltaRatio( 5.0, NaN )\n NaN\n > y = base.gammaDeltaRatio( NaN, NaN )\n NaN\n\n See Also\n --------\n base.gamma\n","base.gammainc":"\nbase.gammainc( x, s[, regularized[, upper]] )\n Computes the regularized incomplete gamma function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete gamma functions, respectively.\n\n If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n s: number\n Second function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete gamma function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete gamma function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammainc( 6.0, 2.0 )\n ~0.9826\n > y = base.gammainc( 1.0, 2.0, true, true )\n ~0.7358\n > y = base.gammainc( 7.0, 5.0 )\n ~0.8270\n > y = base.gammainc( 7.0, 5.0, false )\n ~19.8482\n > y = base.gammainc( NaN, 2.0 )\n NaN\n > y = base.gammainc( 6.0, NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammaincinv, base.gammaln\n","base.gammaincinv":"\nbase.gammaincinv( p, a[, upper] )\n Computes the inverse of the lower incomplete gamma function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second argument is the scale factor `a`.\n\n By default, the function inverts the lower regularized incomplete gamma\n function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Scale parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaincinv( 0.5, 2.0 )\n ~1.678\n > y = base.gammaincinv( 0.1, 10.0 )\n ~6.221\n > y = base.gammaincinv( 0.75, 3.0 )\n ~3.92\n > y = base.gammaincinv( 0.75, 3.0, true )\n ~1.727\n > y = base.gammaincinv( 0.75, NaN )\n NaN\n > y = base.gammaincinv( NaN, 3.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammainc, base.gammaln\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x )\n Calculates the Lanczos sum for the approximation of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSum( 4.0 )\n ~950.366\n > y = base.gammaLanczosSum( -1.5 )\n ~1373366.245\n > y = base.gammaLanczosSum( -0.5 )\n ~-699841.735\n > y = base.gammaLanczosSum( 0.5 )\n ~96074.186\n > y = base.gammaLanczosSum( 0.0 )\n Infinity\n > y = base.gammaLanczosSum( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSumExpGScaled\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Scaled Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n ~0.018\n > y = base.gammaLanczosSumExpGScaled( -1.5 )\n ~25.337\n > y = base.gammaLanczosSumExpGScaled( -0.5 )\n ~-12.911\n > y = base.gammaLanczosSumExpGScaled( 0.5 )\n ~1.772\n > y = base.gammaLanczosSumExpGScaled( 0.0 )\n Infinity\n > y = base.gammaLanczosSumExpGScaled( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSum\n","base.gammaln":"\nbase.gammaln( x )\n Evaluates the natural logarithm of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the gamma function.\n\n Examples\n --------\n > var y = base.gammaln( 1.0 )\n 0.0\n > y = base.gammaln( 2.0 )\n 0.0\n > y = base.gammaln( 4.0 )\n ~1.792\n > y = base.gammaln( -0.5 )\n ~1.266\n > y = base.gammaln( 0.5 )\n ~0.572\n > y = base.gammaln( 0.0 )\n Infinity\n > y = base.gammaln( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv\n","base.gammasgn":"\nbase.gammasgn( x )\n Computes the sign of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Sign of the gamma function.\n\n Examples\n --------\n > var y = base.gammasgn( 1.0 )\n 1.0\n > y = base.gammasgn( -2.5 )\n -1.0\n > y = base.gammasgn( 0.0 )\n 0.0\n > y = base.gammasgn( NaN )\n NaN\n\n See Also\n --------\n base.gamma","base.gcd":"\nbase.gcd( a, b )\n Computes the greatest common divisor (gcd).\n\n If both `a` and `b` are `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First number.\n\n b: integer\n Second number.\n\n Returns\n -------\n out: integer\n Greatest common divisor.\n\n Examples\n --------\n > var v = base.gcd( 48, 18 )\n 6\n\n See Also\n --------\n base.lcm\n","base.getHighWord":"\nbase.getHighWord( x )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Higher order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getHighWord( 3.14e201 )\n 1774486211\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.getLowWord":"\nbase.getLowWord( x )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Lower order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getLowWord( 3.14e201 )\n 2479577218\n\n See Also\n --------\n base.getHighWord, base.setHighWord\n","base.hacovercos":"\nbase.hacovercos( x )\n Computes the half-value coversed cosine.\n\n The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed cosine.\n\n Examples\n --------\n > var y = base.hacovercos( 3.14 )\n ~0.5008\n > y = base.hacovercos( -4.2 )\n ~0.9358\n > y = base.hacovercos( -4.6 )\n ~0.9968\n > y = base.hacovercos( 9.5 )\n ~0.4624\n > y = base.hacovercos( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacoversin, base.havercos\n","base.hacoversin":"\nbase.hacoversin( x )\n Computes the half-value coversed sine.\n\n The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed sine.\n\n Examples\n --------\n > var y = base.hacoversin( 3.14 )\n ~0.4992\n > y = base.hacoversin( -4.2 )\n ~0.0642\n > y = base.hacoversin( -4.6 )\n ~0.0032\n > y = base.hacoversin( 9.5 )\n ~0.538\n > y = base.hacoversin( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacovercos, base.haversin\n","base.havercos":"\nbase.havercos( x )\n Computes the half-value versed cosine.\n\n The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed cosine.\n\n Examples\n --------\n > var y = base.havercos( 3.14 )\n ~0.0\n > y = base.havercos( -4.2 )\n ~0.2549\n > y = base.havercos( -4.6 )\n ~0.4439\n > y = base.havercos( 9.5 )\n ~0.0014\n > y = base.havercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.haversin, base.vercos\n","base.haversin":"\nbase.haversin( x )\n Computes the half-value versed sine.\n\n The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed sine.\n\n Examples\n --------\n > var y = base.haversin( 3.14 )\n ~1.0\n > y = base.haversin( -4.2 )\n ~0.7451\n > y = base.haversin( -4.6 )\n ~0.5561\n > y = base.haversin( 9.5 )\n ~0.9986\n > y = base.haversin( -0.0 )\n 0.0\n\n See Also\n --------\n base.havercos, base.versin\n","base.headercase":"\nbase.headercase( str )\n Converts a string to HTTP header case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n HTTP header-cased string.\n\n Examples\n --------\n > var out = base.headercase( 'Hello World!' )\n 'Hello-World'\n > out = base.headercase( 'beep boop' )\n 'Beep-Boop'\n\n See Also\n --------\n base.camelcase, base.pascalcase, base.uppercase","base.heaviside":"\nbase.heaviside( x[, continuity] )\n Evaluates the Heaviside function.\n\n The `continuity` parameter may be one of the following:\n\n - 'half-maximum': if `x == 0`, the function returns `0.5`.\n - 'left-continuous': if `x == 0`, the function returns `0`.\n - 'right-continuous': if `x == 0`, the function returns `1`.\n\n By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n discontinuous).\n\n Parameters\n ----------\n x: number\n Input value.\n\n continuity: string (optional)\n Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n returns `NaN`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.heaviside( 3.14 )\n 1.0\n > y = base.heaviside( -3.14 )\n 0.0\n > y = base.heaviside( 0.0 )\n NaN\n > y = base.heaviside( 0.0, 'half-maximum' )\n 0.5\n > y = base.heaviside( 0.0, 'left-continuous' )\n 0.0\n > y = base.heaviside( 0.0, 'right-continuous' )\n 1.0\n\n See Also\n --------\n base.ramp\n","base.hermitepoly":"\nbase.hermitepoly( n, x )\n Evaluates a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.hermitepoly( 1, 0.5 )\n 1.0\n > y = base.hermitepoly( -1, 0.5 )\n NaN\n > y = base.hermitepoly( 0, 0.5 )\n 1.0\n > y = base.hermitepoly( 2, 0.5 )\n -1.0\n\n\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly","base.hypot":"\nbase.hypot( x, y )\n Computes the hypotenuse avoiding overflow and underflow.\n\n If either argument is `NaN` and the other argument is not `+-Infinity`,\n the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypot( -5.0, 12.0 )\n 13.0\n > h = base.hypot( NaN, 12.0 )\n NaN\n > h = base.hypot( -0.0, -0.0 )\n 0.0\n\n","base.hypotf":"\nbase.hypotf( x, y )\n Computes the hypotenuse avoiding overflow and underflow (single-precision).\n\n If either argument is `NaN` and the other argument is not `+-Infinity`,\n the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypotf( -5.0, 12.0 )\n 13.0\n > h = base.hypotf( NaN, 12.0 )\n NaN\n > h = base.hypotf( -0.0, -0.0 )\n 0.0\n\n See Also\n --------\n base.hypot\n","base.identity":"\nbase.identity( x )\n Evaluates the identity function for a double-precision floating-point number\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Input value.\n\n Examples\n --------\n > var y = base.identity( -1.0 )\n -1.0\n > y = base.identity( 2.0 )\n 2.0\n > y = base.identity( 0.0 )\n 0.0\n > y = base.identity( -0.0 )\n -0.0\n > y = base.identity( NaN )\n NaN\n\n See Also\n --------\n base.identityf\n","base.identityf":"\nbase.identityf( x )\n Evaluates the identity function for a single-precision floating-point number\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Input value.\n\n Examples\n --------\n > var y = base.identityf( -1.0 )\n -1.0\n > y = base.identityf( 2.0 )\n 2.0\n > y = base.identityf( 0.0 )\n 0.0\n > y = base.identityf( -0.0 )\n -0.0\n > y = base.identityf( NaN )\n NaN\n\n See Also\n --------\n base.identity\n","base.imul":"\nbase.imul( a, b )\n Performs C-like multiplication of two signed 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.imul( -10|0, 4|0 )\n -40\n\n See Also\n --------\n base.imuldw\n","base.imuldw":"\nbase.imuldw( a, b )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: Array\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.imuldw( 1, 10 )\n [ 0, 10 ]\n\n\nbase.imuldw.assign( a, b, out, stride, offset )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imul","base.imuldw.assign":"\nbase.imuldw.assign( a, b, out, stride, offset )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imul","base.int2slice":"\nbase.int2slice( value, max, strict )\n Converts an integer to a Slice object.\n\n In strict mode, the function returns an error object if an input value\n exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n Parameters\n ----------\n value: integer\n Input value.\n\n max: integer\n Index upper bound (exclusive).\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance (or an error object).\n\n Examples\n --------\n > var s = base.int2slice( -1, 5, false );\n > s.start\n 4\n > s.stop\n 5\n > s.step\n 1\n\n See Also\n --------\n base.seq2slice, base.str2slice\n","base.int32ToUint32":"\nbase.int32ToUint32( x )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\n 4294967264\n > y = base.int32ToUint32( base.float64ToInt32( 3 ) )\n 3\n\n See Also\n --------\n base.uint32ToInt32\n","base.inv":"\nbase.inv( x )\n Computes the multiplicative inverse of a double-precision floating-point\n number `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.inv( -1.0 )\n -1.0\n > y = base.inv( 2.0 )\n 0.5\n > y = base.inv( 0.0 )\n Infinity\n > y = base.inv( -0.0 )\n -Infinity\n > y = base.inv( NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.invcase":"\nbase.invcase( str )\n Converts a string to inverse case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Inverse-cased string.\n\n Examples\n --------\n > var out = base.invcase( 'Hello World!' )\n 'hELLO wORLD!'\n > out = base.invcase( 'I am A tiny LITTLE teapot' )\n 'i AM a TINY little TEAPOT'\n\n See Also\n --------\n base.lowercase, base.uppercase","base.invf":"\nbase.invf( x )\n Computes the multiplicative inverse of a single-precision floating-point\n number `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.invf( -1.0 )\n -1.0\n > y = base.invf( 2.0 )\n 0.5\n > y = base.invf( 0.0 )\n Infinity\n > y = base.invf( -0.0 )\n -Infinity\n > y = base.invf( NaN )\n NaN\n\n See Also\n --------\n base.inv\n","base.isComposite":"\nbase.isComposite( x )\n Tests if a number is composite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a composite number.\n\n Examples\n --------\n > var bool = base.isComposite( 10.0 )\n true\n > bool = base.isComposite( 11.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isPrime\n","base.isCoprime":"\nbase.isCoprime( a, b )\n Tests if two numbers are coprime.\n\n Parameters\n ----------\n a: number\n First value.\n\n b: number\n Second value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the values are coprime.\n\n Examples\n --------\n > var bool = base.isCoprime( 14.0, 15.0 )\n true\n > bool = base.isCoprime( 14.0, 21.0 )\n false\n\n See Also\n --------\n base.isComposite, base.isPrime, base.gcd\n","base.isEven":"\nbase.isEven( x )\n Tests if a finite numeric value is an even number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEven( 5.0 )\n false\n > bool = base.isEven( -2.0 )\n true\n > bool = base.isEven( 0.0 )\n true\n > bool = base.isEven( NaN )\n false\n\n See Also\n --------\n base.isOdd\n","base.isEvenInt32":"\nbase.isEvenInt32( x )\n Tests if a 32-bit integer is even.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEvenInt32( 5 )\n false\n > bool = base.isEvenInt32( -2 )\n true\n > bool = base.isEvenInt32( 0 )\n true\n\n See Also\n --------\n base.isEven, base.isOddInt32\n","base.isFinite":"\nbase.isFinite( x )\n Tests if a double-precision floating-point numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinite( 5.0 )\n true\n > bool = base.isFinite( -2.0e64 )\n true\n > bool = base.isFinite( PINF )\n false\n > bool = base.isFinite( NINF )\n false\n\n See Also\n --------\n base.isInfinite\n","base.isFinitef":"\nbase.isFinitef( x )\n Tests if a single-precision floating-point numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinitef( 5.0 )\n true\n > bool = base.isFinitef( -1.0e38 )\n true\n > bool = base.isFinitef( FLOAT32_PINF )\n false\n > bool = base.isFinitef( FLOAT32_NINF )\n false\n\n See Also\n --------\n base.isInfinitef\n","base.isInfinite":"\nbase.isInfinite( x )\n Tests if a double-precision floating-point numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinite( PINF )\n true\n > bool = base.isInfinite( NINF )\n true\n > bool = base.isInfinite( 5.0 )\n false\n > bool = base.isInfinite( NaN )\n false\n\n See Also\n --------\n base.isFinite\n","base.isInfinitef":"\nbase.isInfinitef( x )\n Tests if a single-precision floating-point numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinitef( FLOAT32_PINF )\n true\n > bool = base.isInfinitef( FLOAT32_NINF )\n true\n > bool = base.isInfinitef( 5.0 )\n false\n > bool = base.isInfinitef( NaN )\n false\n\n See Also\n --------\n base.isFinitef\n","base.isInteger":"\nbase.isInteger( x )\n Tests if a finite double-precision floating-point number is an integer.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an integer.\n\n Examples\n --------\n > var bool = base.isInteger( 1.0 )\n true\n > bool = base.isInteger( 3.14 )\n false\n\n","base.isnan":"\nbase.isnan( x )\n Tests if a double-precision floating-point numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnan( NaN )\n true\n > bool = base.isnan( 7.0 )\n false\n\n See Also\n --------\n base.isnanf\n","base.isnanf":"\nbase.isnanf( x )\n Tests if a single-precision floating-point numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnanf( NaN )\n true\n > bool = base.isnanf( 7.0 )\n false\n\n See Also\n --------\n base.isnan\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x )\n Tests if a double-precision floating-point numeric value is a negative\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether the value is a negative finite number.\n\n Examples\n --------\n > var bool = base.isNegativeFinite( -3.14 )\n true\n > bool = base.isNegativeFinite( -Infinity )\n false\n > bool = base.isNegativeFinite( 2.0 )\n false\n > bool = base.isNegativeFinite( NaN )\n false\n > bool = base.isNegativeFinite( -0.0 )\n false\n\n See Also\n --------\n base.isPositiveFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a negative integer.\n\n Examples\n --------\n > var bool = base.isNegativeInteger( -1.0 )\n true\n > bool = base.isNegativeInteger( 0.0 )\n false\n > bool = base.isNegativeInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNonNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNegativeZero":"\nbase.isNegativeZero( x )\n Tests if a double-precision floating-point numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZero( -0.0 )\n true\n > bool = base.isNegativeZero( 0.0 )\n false\n\n See Also\n --------\n base.isPositiveZero\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x )\n Tests if a single-precision floating-point numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZerof( -0.0 )\n true\n > bool = base.isNegativeZerof( 0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero, base.isPositiveZerof\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x )\n Tests if a double-precision floating-point numeric value is a nonnegative\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative finite number.\n\n Examples\n --------\n > var out = base.isNonNegativeFinite( 5.0 )\n true\n > out = base.isNonNegativeFinite( 3.14 )\n true\n > out = base.isNonNegativeFinite( 0.0 )\n true\n > out = base.isNonNegativeFinite( Infinity )\n false\n > out = base.isNonNegativeFinite( -3.14 )\n false\n > out = base.isNonNegativeFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isPositiveFinite, base.isNonPositiveFinite\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative integer.\n\n Examples\n --------\n > var bool = base.isNonNegativeInteger( 1.0 )\n true\n > bool = base.isNonNegativeInteger( 0.0 )\n true\n > bool = base.isNonNegativeInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x )\n Tests if a double-precision floating-point numeric value is a nonpositive\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether the value is a nonpositive finite number.\n\n Examples\n --------\n > var bool = base.isNonPositiveFinite( -3.14 )\n true\n > var bool = base.isNonPositiveFinite( 0.0 )\n true\n > var bool = base.isNonPositiveFinite( -Infinity )\n false\n > var bool = base.isNonPositiveFinite( 3.14 )\n false\n > var bool = base.isNonPositiveFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isPositiveFinite, base.isNonNegativeFinite\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonpositive integer.\n\n Examples\n --------\n > var bool = base.isNonPositiveInteger( -1.0 )\n true\n > bool = base.isNonPositiveInteger( 0.0 )\n true\n > bool = base.isNonPositiveInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isPositiveInteger\n","base.isOdd":"\nbase.isOdd( x )\n Tests if a finite numeric value is an odd number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOdd( 5.0 )\n true\n > bool = base.isOdd( -2.0 )\n false\n > bool = base.isOdd( 0.0 )\n false\n > bool = base.isOdd( NaN )\n false\n\n See Also\n --------\n base.isEven\n","base.isOddInt32":"\nbase.isOddInt32( x )\n Tests if a 32-bit integer is odd.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOddInt32( 5 )\n true\n > bool = base.isOddInt32( -2 )\n false\n > bool = base.isOddInt32( 0 )\n false\n\n See Also\n --------\n base.isEvenInt32, base.isOdd\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x )\n Tests if a double-precision floating-point numeric value is a positive\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive finite number.\n\n Examples\n --------\n > var bool = base.isPositiveFinite( 5.0 )\n true\n > bool = base.isPositiveFinite( 3.14 )\n true\n > bool = base.isPositiveFinite( 0.0 )\n false\n > bool = base.isPositiveFinite( Infinity )\n false\n > bool = base.isPositiveFinite( -3.14 )\n false\n > bool = base.isPositiveFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive integer.\n\n Examples\n --------\n > var bool = base.isPositiveInteger( 1.0 )\n true\n > bool = base.isPositiveInteger( 0.0 )\n false\n > bool = base.isPositiveInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isNonPositiveInteger\n","base.isPositiveZero":"\nbase.isPositiveZero( x )\n Tests if a double-precision floating-point numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZero( 0.0 )\n true\n > bool = base.isPositiveZero( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x )\n Tests if a single-precision floating-point numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZerof( 0.0 )\n true\n > bool = base.isPositiveZerof( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZerof, base.isPositiveZero\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x )\n Tests whether an unsigned integer is a power of 2.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a power of 2.\n\n Examples\n --------\n > var bool = base.isPow2Uint32( 2 )\n true\n > bool = base.isPow2Uint32( 5 )\n false\n\n","base.isPrime":"\nbase.isPrime( x )\n Tests if a number is prime.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a prime number.\n\n Examples\n --------\n > var bool = base.isPrime( 11.0 )\n true\n > bool = base.isPrime( 3.14 )\n false\n\n See Also\n --------\n base.isComposite, base.isInteger\n","base.isProbability":"\nbase.isProbability( x )\n Tests if a double-precision floating-point number value is a probability.\n\n A probability is defined as a number on the closed interval [0,1].\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a probability.\n\n Examples\n --------\n > var bool = base.isProbability( 0.5 )\n true\n > bool = base.isProbability( 3.14 )\n false\n > bool = base.isProbability( NaN )\n false\n\n","base.isSafeInteger":"\nbase.isSafeInteger( x )\n Tests if a finite double-precision floating-point number is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a safe integer.\n\n Examples\n --------\n > var bool = base.isSafeInteger( 1.0 )\n true\n > bool = base.isSafeInteger( 2.0e200 )\n false\n > bool = base.isSafeInteger( 3.14 )\n false\n\n","base.kebabcase":"\nbase.kebabcase( str )\n Converts a string to kebab case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Kebab-cased string.\n\n Examples\n --------\n > var out = base.kebabcase( 'Hello World!' )\n 'hello-world'\n > out = base.kebabcase( 'I am a tiny little teapot' )\n 'i-am-a-tiny-little-teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.pascalcase, base.snakecase, base.uppercase","base.kernelBetainc":"\nbase.kernelBetainc( x, a, b, regularized, upper )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n [ ~1.277, ~0.926 ]\n > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n [ 0.36, 1.6 ]\n\n\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a, b, p, q )\n Computes the inverse of the lower incomplete beta function.\n\n Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n Parameters\n ----------\n a: number\n First function parameter (a positive number).\n\n b: number\n Second function parameter (a positive number).\n\n p: number\n Probability.\n\n q: number\n Probability equal to `1-p`.\n\n Returns\n -------\n out: Array\n Two-element array holding function value `y` and `1-y`.\n\n Examples\n --------\n > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n [ ~0.327, ~0.673 ]\n > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n [ ~0.446, ~0.554 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n [ ~0.082, ~0.918 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n [ ~0.235, ~0.765 ]\n\n See Also\n --------\n base.betaincinv\n","base.kernelCos":"\nbase.kernelCos( x, y )\n Computes the cosine of a double-precision floating-point number on the\n interval [-π/4, π/4].\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Cosine.\n\n Examples\n --------\n > var out = base.kernelCos( 0.0, 0.0 )\n ~1.0\n > out = base.kernelCos( PI/6.0, 0.0 )\n ~0.866\n > out = base.kernelCos( 0.785, -1.144e-17 )\n ~0.707\n > out = base.kernelCos( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.kernelSin, base.kernelTan\n","base.kernelLog1p":"\nbase.kernelLog1p( f )\n Evaluates a correction term for double-precision base-2 and base-10\n logarithms when `1+f` is in `[√2/2, √2]`.\n\n This function provides a common means for computing logarithms in base e.\n Argument reduction and adding the final term of the polynomial must be done\n by the caller for increased accuracy when different bases are used.\n\n Parameters\n ----------\n f: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var y = base.kernelLog1p( 1.0 )\n ~0.1931\n > y = base.kernelLog1p( 1.4142135623730951 )\n ~0.4672\n > y = base.kernelLog1p( NaN )\n NaN\n\n See Also\n --------\n base.log1p\n","base.kernelSin":"\nbase.kernelSin( x, y )\n Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Sine.\n\n Examples\n --------\n > var y = base.kernelSin( 0.0, 0.0 )\n ~0.0\n > y = base.kernelSin( PI/6.0, 0.0 )\n ~0.5\n > y = base.kernelSin( 0.619, 9.279e-18 )\n ~0.58\n\n > y = base.kernelSin( NaN, 0.0 )\n NaN\n > y = base.kernelSin( 2.0, NaN )\n NaN\n > y = base.kernelSin( NaN, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelTan, base.sin\n","base.kernelTan":"\nbase.kernelTan( x, y, k )\n Computes the tangent of a double-precision floating-point number on the\n interval [-π/4, π/4].\n\n For increased accuracy, the number for which the tangent should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n k: integer\n If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n returns the negative inverse `-1/tan(x+y)`.\n\n Returns\n -------\n out: number\n Tangent.\n\n Examples\n --------\n > var out = base.kernelTan( PI/4.0, 0.0, 1 )\n ~1.0\n > out = base.kernelTan( PI/4.0, 0.0, -1 )\n ~-1.0\n > out = base.kernelTan( PI/6.0, 0.0, 1 )\n ~0.577\n > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n ~0.783\n\n > out = base.kernelTan( NaN, 0.0, 1 )\n NaN\n > out = base.kernelTan( 3.0, NaN, 1 )\n NaN\n > out = base.kernelTan( 3.0, 0.0, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelSin, base.tan\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i, j )\n Evaluates the Kronecker delta.\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDelta( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDelta( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.diracDelta\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i, j )\n Evaluates the Kronecker delta (single-precision).\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDeltaf( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDeltaf( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.kroneckerDelta\n","base.labs":"\nbase.labs( x )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Absolute value.\n\n Examples\n --------\n > var v = base.labs( -1|0 )\n 1\n > v = base.labs( 2|0 )\n 2\n > v = base.labs( 0|0 )\n 0\n\n See Also\n --------\n base.abs\n","base.last":"\nbase.last( str, n )\n Returns the last `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.last( 'hello', 1 )\n 'o'\n > out = base.last( 'JavaScript', 6 )\n 'Script'\n > out = base.last( 'foo bar', 10 )\n 'foo bar'\n\n See Also\n --------\n base.firstCodeUnit, base.lastCodePoint, base.lastGraphemeCluster\n","base.lastCodePoint":"\nbase.lastCodePoint( str, n )\n Returns the last `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.lastCodePoint( 'hello world', 1 )\n 'd'\n > out = base.lastCodePoint( 'JavaScript', 6 )\n 'Script'\n > out = base.lastCodePoint( 'अनुच्छेद', 1 )\n 'द'\n\n See Also\n --------\n base.firstCodePoint, base.lastGraphemeCluster, base.last\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str, n )\n Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.lastGraphemeCluster( 'beep', 1 )\n 'p'\n > out = base.lastGraphemeCluster( 'Boop', 2 )\n 'op'\n > out = base.lastGraphemeCluster( 'JavaScript', 6 )\n 'Script'\n\n See Also\n --------\n base.firstGraphemeCluster, base.lastCodePoint, base.last\n","base.lcm":"\nbase.lcm( a, b )\n Computes the least common multiple (lcm).\n\n If either `a` or `b` is `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Least common multiple.\n\n Examples\n --------\n > var v = base.lcm( 21, 6 )\n 42\n\n See Also\n --------\n base.gcd\n","base.ldexp":"\nbase.ldexp( frac, exp )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n\n If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n infinity, the function returns a value equal to `frac`.\n\n Parameters\n ----------\n frac: number\n Fraction.\n\n exp: number\n Exponent.\n\n Returns\n -------\n out: number\n Double-precision floating-point number equal to `frac * 2^exp`.\n\n Examples\n --------\n > var x = base.ldexp( 0.5, 3 )\n 4.0\n > x = base.ldexp( 4.0, -2 )\n 1.0\n > x = base.ldexp( 0.0, 20 )\n 0.0\n > x = base.ldexp( -0.0, 39 )\n -0.0\n > x = base.ldexp( NaN, -101 )\n NaN\n > x = base.ldexp( PINF, 11 )\n Infinity\n > x = base.ldexp( NINF, -118 )\n -Infinity\n\n See Also\n --------\n base.frexp\n","base.leftPad":"\nbase.leftPad( str, len, pad )\n Left pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string\n String used to pad.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = base.leftPad( 'a', 5, ' ' )\n ' a'\n > out = base.leftPad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = base.leftPad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n base.rightPad\n","base.leftTrim":"\nbase.leftTrim( str )\n Trims whitespace from the beginning of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.leftTrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n See Also\n --------\n base.rightTrim, base.trim\n","base.ln":"\nbase.ln( x )\n Evaluates the natural logarithm of a double-precision floating-point number.\n\n For negative numbers, the natural logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ln( 4.0 )\n ~1.386\n > y = base.ln( 0.0 )\n -Infinity\n > y = base.ln( PINF )\n Infinity\n > y = base.ln( NaN )\n NaN\n > y = base.ln( -4.0 )\n NaN\n\n See Also\n --------\n base.exp, base.log10, base.log1p, base.log2\n","base.log":"\nbase.log( x, b )\n Computes the base `b` logarithm of a double-precision floating-point number.\n\n For negative `b` or `x`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n b: number\n Base.\n\n Returns\n -------\n y: number\n Logarithm (base `b`).\n\n Examples\n --------\n > var y = base.log( 100.0, 10.0 )\n 2.0\n > y = base.log( 16.0, 2.0 )\n 4.0\n > y = base.log( 5.0, 1.0 )\n Infinity\n > y = base.log( NaN, 2.0 )\n NaN\n > y = base.log( 1.0, NaN )\n NaN\n > y = base.log( -4.0, 2.0 )\n NaN\n > y = base.log( 4.0, -2.0 )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log10, base.log1p, base.log2\n","base.log1mexp":"\nbase.log1mexp( x )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1mexp( -10.0 )\n ~-0.00005\n > y = base.log1mexp( 0.0 )\n -Infinity\n > y = base.log1mexp( 5.0 )\n ~-0.00676\n > y = base.log1mexp( 10.0 )\n ~-0.00005\n > y = base.log1mexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1p, base.log1pexp","base.log1p":"\nbase.log1p( x )\n Evaluates the natural logarithm of `1+x`.\n\n For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n defined for negative numbers.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1p( 4.0 )\n ~1.609\n > y = base.log1p( -1.0 )\n -Infinity\n > y = base.log1p( 0.0 )\n 0.0\n > y = base.log1p( -0.0 )\n -0.0\n > y = base.log1p( -2.0 )\n NaN\n > y = base.log1p( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log\n","base.log1pexp":"\nbase.log1pexp( x )\n Evaluates the natural logarithm of `1+exp(x)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1pexp( -10.0 )\n ~0.000045\n > y = base.log1pexp( 0.0 )\n ~0.693147\n > y = base.log1pexp( 5.0 )\n ~5.006715\n > y = base.log1pexp( 34.0 )\n 34.0\n > y = base.log1pexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1mexp, base.log1p","base.log1pmx":"\nbase.log1pmx( x )\n Evaluates `ln(1+x) - x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > base.log1pmx( 1.1 )\n ~-0.358\n > base.log1pmx( 0.99 )\n ~-0.302\n > base.log1pmx( -0.99 )\n ~-3.615\n > base.log1pmx( -1.1 )\n NaN\n > base.log1pmx( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log1p","base.log2":"\nbase.log2( x )\n Evaluates the binary logarithm (base two).\n\n For negative numbers, the binary logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log2( 4.0 )\n 2.0\n > y = base.log2( 8.0 )\n 3.0\n > y = base.log2( 0.0 )\n -Infinity\n > y = base.log2( PINF )\n Infinity\n > y = base.log2( NaN )\n NaN\n > y = base.log2( -4.0 )\n NaN\n\n See Also\n --------\n base.exp2, base.ln, base.log\n","base.log10":"\nbase.log10( x )\n Evaluates the common logarithm (base 10).\n\n For negative numbers, the common logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log10( 100.0 )\n 2.0\n > y = base.log10( 8.0 )\n ~0.903\n > y = base.log10( 0.0 )\n -Infinity\n > y = base.log10( PINF )\n Infinity\n > y = base.log10( NaN )\n NaN\n > y = base.log10( -4.0 )\n NaN\n\n See Also\n --------\n base.exp10, base.ln, base.log\n","base.logaddexp":"\nbase.logaddexp( x, y )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.logaddexp( 90.0, 90.0 )\n ~90.6931\n > v = base.logaddexp( -20.0, 90.0 )\n 90.0\n > v = base.logaddexp( 0.0, -100.0 )\n ~3.7201e-44\n > v = base.logaddexp( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln\n","base.logit":"\nbase.logit( p )\n Evaluates the logit function.\n\n Let `p` be the probability of some event. The logit function is defined as\n the logarithm of the odds `p / (1-p)`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.logit( 0.2 )\n ~-1.386\n > y = base.logit( 0.9 )\n ~2.197\n > y = base.logit( -4.0 )\n NaN\n > y = base.logit( 1.5 )\n NaN\n > y = base.logit( NaN )\n NaN\n\n","base.lowercase":"\nbase.lowercase( str )\n Converts a string to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = base.lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n base.snakecase, base.uppercase\n","base.lucas":"\nbase.lucas( n )\n Computes the nth Lucas number.\n\n Lucas numbers follow the recurrence relation\n\n L_n = L_{n-1} + L_{n-2}\n\n with seed values L_0 = 2 and L_1 = 1.\n\n If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Lucas number.\n\n Examples\n --------\n > var y = base.lucas( 0 )\n 2\n > y = base.lucas( 1 )\n 1\n > y = base.lucas( 2 )\n 3\n > y = base.lucas( 3 )\n 4\n > y = base.lucas( 4 )\n 7\n > y = base.lucas( 77 )\n NaN\n > y = base.lucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.lucaspoly":"\nbase.lucaspoly( n, x )\n Evaluates a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Lucas polynomial.\n\n Returns\n -------\n out: number\n Evaluated Lucas polynomial.\n\n Examples\n --------\n // 2^5 + 5*2^3 + 5*2\n > var v = base.lucaspoly( 5, 2.0 )\n 82.0\n\n\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly","base.max":"\nbase.max( x, y )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.max( 3.14, 4.2 )\n 4.2\n > v = base.max( 3.14, NaN )\n NaN\n > v = base.max( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.maxn, base.min\n","base.maxabs":"\nbase.maxabs( x, y )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabs( 3.14, -4.2 )\n 4.2\n > v = base.maxabs( 3.14, NaN )\n NaN\n > v = base.maxabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.minabs\n","base.maxabsn":"\nbase.maxabsn( [x[, y[, ...args]]] )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n the absolute value of `-infinity`).\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabsn( 3.14, -4.2 )\n 4.2\n > v = base.maxabsn( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxabsn( 3.14, NaN )\n NaN\n > v = base.maxabsn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxn, base.maxabs, base.minabsn\n","base.maxn":"\nbase.maxn( [x[, y[, ...args]]] )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns negative infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.maxn( 3.14, 4.2 )\n 4.2\n > v = base.maxn( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxn( 3.14, NaN )\n NaN\n > v = base.maxn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.maxabsn, base.minn\n","base.min":"\nbase.min( x, y )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.min( 3.14, 4.2 )\n 3.14\n > v = base.min( 3.14, NaN )\n NaN\n > v = base.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max, base.minabs, base.minn\n","base.minabs":"\nbase.minabs( x, y )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabs( 3.14, -4.2 )\n 3.14\n > v = base.minabs( 3.14, NaN )\n NaN\n > v = base.minabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.min\n","base.minabsn":"\nbase.minabsn( [x[, y[, ...args]]] )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabsn( 3.14, -4.2 )\n 3.14\n > v = base.minabsn( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minabsn( 3.14, NaN )\n NaN\n > v = base.minabsn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabsn, base.minn, base.minabs\n","base.minmax":"\nbase.minmax( x, y )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: Array\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmax( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmax( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmax( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n\n\nbase.minmax.assign( x, y, out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs","base.minmax.assign":"\nbase.minmax.assign( x, y, out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs","base.minmaxabs":"\nbase.minmaxabs( x, y )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: Array\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabs( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabs( -5.9, 3.14)\n [ 3.14, 5.9 ]\n > v = base.minmaxabs( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabs( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n\n\nbase.minmaxabs.assign( x, y, out, stride, offset )\n Returns the minimum and maximum absolute values and assigns results to a\n provided output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x, y, out, stride, offset )\n Returns the minimum and maximum absolute values and assigns results to a\n provided output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax","base.minmaxabsn":"\nbase.minmaxabsn( [x[, y[, ...args]]] )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound and negative infinity is the least upper bound. Similar\n to zero being the identity element for the sum of an empty set and to one\n being the identity element for the product of an empty set, positive\n infinity is the identity element for the minimum and negative infinity is\n the identity element for the maximum, and thus, if not provided any\n arguments, the function returns positive infinity for both the minimum and\n maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabsn( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabsn( -5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxabsn( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabsn( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n > v = base.minmaxabsn( 3.14 )\n [ 3.14, 3.14 ]\n\n\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabsn, base.minabsn, base.minmaxn\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabsn, base.minabsn, base.minmaxn","base.minmaxn":"\nbase.minmaxn( [x[, y[, ...args]]] )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound and negative infinity is the least upper bound. Similar\n to zero being the identity element for the sum of an empty set and to one\n being the identity element for the product of an empty set, positive\n infinity is the identity element for the minimum and negative infinity is\n the identity element for the maximum, and thus, if not provided any\n arguments, the function returns positive infinity for the minimum value and\n negative infinity for the maximum value.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmaxn( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxn( 5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxn( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxn( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n > v = base.minmaxn( 3.14 )\n [ 3.14, 3.14 ]\n\n\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxn, base.minn, base.minmaxabsn","base.minmaxn.assign":"\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxn, base.minn, base.minmaxabsn","base.minn":"\nbase.minn( [x[, y[, ...args]]] )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.minn( 3.14, 4.2 )\n 3.14\n > v = base.minn( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minn( 3.14, NaN )\n NaN\n > v = base.minn( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.maxn, base.min, base.minabsn\n","base.modf":"\nbase.modf( x )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n Integral and fractional parts.\n\n Examples\n --------\n > var parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( +0.0 )\n [ +0.0, +0.0 ]\n > parts = base.modf( -0.0 )\n [ -0.0, -0.0 ]\n > parts = base.modf( PINF )\n [ Infinity, +0.0 ]\n > parts = base.modf( NINF )\n [ -Infinity, -0.0 ]\n > parts = base.modf( NaN )\n [ NaN, NaN ]\n\n\nbase.modf.assign( x, out, stride, offset )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var parts = base.modf.assign( 3.14, out, 1, 0 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true\n","base.modf.assign":"\nbase.modf.assign( x, out, stride, offset )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var parts = base.modf.assign( 3.14, out, 1, 0 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true","base.mul":"\nbase.mul( x, y )\n Multiplies two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.mul( -1.0, 5.0 )\n -5.0\n > v = base.mul( 2.0, 5.0 )\n 10.0\n > v = base.mul( 0.0, 5.0 )\n 0.0\n > v = base.mul( -0.0, 0.0 )\n -0.0\n > v = base.mul( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.div, base.sub\n","base.mulf":"\nbase.mulf( x, y )\n Multiplies two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.mulf( -1.0, 5.0 )\n -5.0\n > v = base.mulf( 2.0, 5.0 )\n 10.0\n > v = base.mulf( 0.0, 5.0 )\n 0.0\n > v = base.mulf( -0.0, 0.0 )\n -0.0\n > v = base.mulf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.divf, base.mul, base.subf\n","base.ndarray":"\nbase.ndarray( dtype, buffer, shape, strides, offset, order )\n Returns an ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n Returns\n -------\n ndarray: ndarray\n ndarray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.ndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nbase.ndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nbase.ndarray.prototype.order: string\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nbase.ndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nbase.ndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nbase.ndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nbase.ndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nbase.ndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nbase.ndarray.prototype.toLocaleString( [locales[, options]] )\n Serializes an ndarray as a locale-aware string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n Configuration options.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toLocaleString()\n '...'\n\n\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","base.ndarray.prototype.toLocaleString":"\nbase.ndarray.prototype.toLocaleString( [locales[, options]] )\n Serializes an ndarray as a locale-aware string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n Configuration options.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toLocaleString()\n '...'","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays, fcn )\n Applies a unary callback to elements in an input ndarray and assigns results\n to elements in an output ndarray.\n\n Each provided \"ndarray\" should be an object with the following properties:\n\n - dtype: data type.\n - data: data buffer.\n - shape: dimensions.\n - strides: stride lengths.\n - offset: index offset.\n - order: specifies whether an ndarray is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one input ndarray and one output ndarray.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n // Define ndarray data and meta data...\n > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dtype = 'float64';\n > var shape = [ 2, 2 ];\n > var sx = [ 2, 1 ];\n > var sy = [ 2, 1 ];\n > var ox = 0;\n > var oy = 0;\n > var order = 'row-major';\n\n // Using ndarrays...\n > var x = ndarray( dtype, xbuf, shape, sx, ox, order );\n > var y = ndarray( dtype, ybuf, shape, sy, oy, order );\n > base.ndarrayUnary( [ x, y ], base.abs );\n > y.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using minimal ndarray-like objects...\n > x = {\n ... 'dtype': dtype,\n ... 'data': xbuf,\n ... 'shape': shape,\n ... 'strides': sx,\n ... 'offset': ox,\n ... 'order': order\n ... };\n > y = {\n ... 'dtype': dtype,\n ... 'data': ybuf,\n ... 'shape': shape,\n ... 'strides': sy,\n ... 'offset': oy,\n ... 'order': order\n ... };\n > base.ndarrayUnary( [ x, y ], base.abs );\n > y.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n ndarrayDispatch\n","base.ndzeros":"\nbase.ndzeros( dtype, shape, order )\n Returns a zero-filled ndarray having a specified shape and data type.\n\n Parameters\n ----------\n dtype: string|DataType\n Underlying data type. Must be a numeric or \"generic\" data type.\n\n shape: ArrayLikeObject\n Array shape.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n base.ndarray, base.ndzerosLike\n","base.ndzerosLike":"\nbase.ndzerosLike( x )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n\n Along with data type, shape, and order, the function infers the \"class\" of\n the returned ndarray from the provided ndarray. For example, if provided a\n \"base\" ndarray, the function returns a base ndarray. If provided a non-base\n ndarray, the function returns a non-base ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n > var y = base.ndzerosLike( x )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n base.ndarray, base.ndzeros\n","base.negafibonacci":"\nbase.negafibonacci( n )\n Computes the nth negaFibonacci number.\n\n The negaFibonacci numbers follow the recurrence relation\n\n F_{n-2} = F_{n} - F_{n-1}\n\n with seed values F_0 = 0 and F_{-1} = 1.\n\n If `|n|` is greater than `78`, the function returns `NaN` as larger\n negaFibonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaFibonacci number.\n\n Examples\n --------\n > var y = base.negafibonacci( 0 )\n 0\n > y = base.negafibonacci( -1 )\n 1\n > y = base.negafibonacci( -2 )\n -1\n > y = base.negafibonacci( -3 )\n 2\n > y = base.negafibonacci( -4 )\n -3\n > y = base.negafibonacci( -79 )\n NaN\n > y = base.negafibonacci( -80 )\n NaN\n > y = base.negafibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.negalucas":"\nbase.negalucas( n )\n Computes the nth negaLucas number.\n\n The negaLucas numbers follow the recurrence relation\n\n L_{n-2} = L_{n} - L_{n-1}\n\n with seed values L_0 = 2 and L_{-1} = -1.\n\n If `|n|` is greater than `76`, the function returns `NaN` as larger\n negaLucas numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaLucas number.\n\n Examples\n --------\n > var y = base.negalucas( 0 )\n 2\n > y = base.negalucas( -1 )\n -1\n > y = base.negalucas( -2 )\n 3\n > y = base.negalucas( -3 )\n -4\n > y = base.negalucas( -4 )\n 7\n > y = base.negalucas( -77 )\n NaN\n > y = base.negalucas( -78 )\n NaN\n > y = base.negalucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.lucas, base.negafibonacci\n","base.nonfibonacci":"\nbase.nonfibonacci( n )\n Computes the nth non-Fibonacci number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Non-Fibonacci number.\n\n Examples\n --------\n > var v = base.nonfibonacci( 1 )\n 4\n > v = base.nonfibonacci( 2 )\n 6\n > v = base.nonfibonacci( 3 )\n 7\n > v = base.nonfibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.normalize":"\nbase.normalize( x )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalize( 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > var y = out[ 0 ];\n > var exponent = out[ 1 ];\n > var bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n true\n\n // Special cases:\n > out = base.normalize( 0.0 )\n [ 0.0, 0 ];\n > out = base.normalize( PINF )\n [ Infinity, 0 ]\n > out = base.normalize( NINF )\n [ -Infinity, 0 ]\n > out = base.normalize( NaN )\n [ NaN, 0 ]\n\n\nbase.normalize.assign( x, out, stride, offset )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 )\n > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n [ 1.4141234400356668e-303, -52 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef\n","base.normalize.assign":"\nbase.normalize.assign( x, out, stride, offset )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 )\n > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n [ 1.4141234400356668e-303, -52 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef","base.normalizef":"\nbase.normalizef( x )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: Array\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23 ]\n > var y = out[ 0 ];\n > var exp = out[ 1 ];\n > var bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n true\n\n // Special cases:\n > out = base.normalizef( FLOAT32_PINF )\n [ Infinity, 0 ]\n > out = base.normalizef( FLOAT32_NINF )\n [ -Infinity, 0 ]\n > out = base.normalizef( NaN )\n [ NaN, 0 ]\n\n\nbase.normalizef.assign( x, out, stride, offset )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > out = new Float32Array( 2 );\n > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize","base.normalizef.assign":"\nbase.normalizef.assign( x, out, stride, offset )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > out = new Float32Array( 2 );\n > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize","base.normalizeMultiSlice":"\nbase.normalizeMultiSlice( slice, shape, strict )\n Returns a normalized MultiSlice object.\n\n In strict mode, the function returns an error object if an input slice\n exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n Parameters\n ----------\n slice: MultiSlice\n Input slice object.\n\n shape: Array\n Maximum slice shape.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: MultiSlice|Object\n MultiSlice instance (or an error object).\n\n Examples\n --------\n > var s1 = new MultiSlice( 1, 3, null );\n > var s2 = base.normalizeMultiSlice( s1, [ 5, 5, 5 ], false );\n > var v = s2.data[ 0 ];\n > v.start\n 1\n > v.stop\n 2\n > v.step\n 1\n > v = s2.data[ 1 ];\n > v.start\n 3\n > v.stop\n 4\n > v.step\n 1\n > v = s2.data[ 2 ];\n > v.start\n 0\n > v.stop\n 5\n > v.step\n 1\n\n See Also\n --------\n base.normalizeSlice\n","base.normalizeSlice":"\nbase.normalizeSlice( slice, len, strict )\n Returns a normalized Slice object.\n\n In strict mode, the function returns an error object if an input slice\n exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n Parameters\n ----------\n slice: Slice\n Input slice object.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance (or an error object).\n\n Examples\n --------\n > var s1 = new Slice( 1, 10, 1 );\n > var s2 = base.normalizeSlice( s1, 5, false );\n > s2.start\n 1\n > s2.stop\n 5\n > s2.step\n 1\n > s1 = new Slice( -2, null, -1 );\n > s2 = base.normalizeSlice( s1, 10, false );\n > s2.start\n 8\n > s2.stop\n null\n > s2.step\n -1\n\n See Also\n --------\n base.normalizeMultiSlice\n","base.normhermitepoly":"\nbase.normhermitepoly( n, x )\n Evaluates a normalized Hermite polynomial using double-precision floating-\n point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.normhermitepoly( 1, 0.5 )\n 0.5\n > y = base.normhermitepoly( -1, 0.5 )\n NaN\n > y = base.normhermitepoly( 0, 0.5 )\n 1.0\n > y = base.normhermitepoly( 2, 0.5 )\n -0.75\n\n\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var f = base.normhermitepoly.factory( 2 );\n > var v = f( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var f = base.normhermitepoly.factory( 2 );\n > var v = f( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly","base.pascalcase":"\nbase.pascalcase( str )\n Converts a string to Pascal case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Pascal-cased string.\n\n Examples\n --------\n > var out = base.pascalcase( 'Hello World!' )\n 'HelloWorld'\n > out = base.pascalcase( 'beep boop' )\n 'BeepBoop'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.uppercase","base.pdiff":"\nbase.pdiff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdiff( 5.9, 3.14 )\n 2.76\n > v = base.pdiff( 3.14, 4.2 )\n 0.0\n > v = base.pdiff( 3.14, NaN )\n NaN\n > v = base.pdiff( -0.0, +0.0 )\n +0.0\n\n","base.pdifff":"\nbase.pdifff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdifff( 5.9, 3.15 )\n 2.75\n > v = base.pdifff( 3.14, 4.2 )\n 0.0\n > v = base.pdifff( 3.14, NaN )\n NaN\n > v = base.pdifff( -0.0, +0.0 )\n +0.0\n\n See Also\n --------\n base.pdiff\n","base.percentEncode":"\nbase.percentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = base.percentEncode( '☃' )\n '%E2%98%83'\n\n","base.polygamma":"\nbase.polygamma( n, x )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n\n If `n` is not a nonnegative integer, the function returns `NaN`.\n\n If `x` is zero or a negative odd integer, the function returns `+Infinity`.\n If `x` is a negative even integer, the function returns `NaN`.\n\n If provided `NaN` as either parameter, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Derivative order.\n\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.polygamma( 3, 1.2 )\n ~3.245\n > v = base.polygamma( 5, 1.2 )\n ~41.39\n > v = base.polygamma( 3, -4.9 )\n ~60014.239\n > v = base.polygamma( -1, 5.3 )\n NaN\n > v = base.polygamma( 2, -1.0 )\n Infinity\n\n See Also\n --------\n base.trigamma, base.digamma, base.gamma\n","base.pow":"\nbase.pow( b, x )\n Evaluates the exponential function `bˣ`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.pow( 2.0, 3.0 )\n 8.0\n > y = base.pow( 4.0, 0.5 )\n 2.0\n > y = base.pow( 100.0, 0.0 )\n 1.0\n > y = base.pow( PI, 5.0 )\n ~306.0197\n > y = base.pow( PI, -0.2 )\n ~0.7954\n > y = base.pow( NaN, 3.0 )\n NaN\n > y = base.pow( 5.0, NaN )\n NaN\n > y = base.pow( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.powm1\n","base.powm1":"\nbase.powm1( b, x )\n Evaluates `bˣ - 1`.\n\n When `b` is close to `1` and/or `x` is small, this function is more accurate\n than naively computing `bˣ` and subtracting `1`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.powm1( 2.0, 3.0 )\n 7.0\n > y = base.powm1( 4.0, 0.5 )\n 1.0\n > y = base.powm1( 0.0, 100.0 )\n -1.0\n > y = base.powm1( 100.0, 0.0 )\n 0.0\n > y = base.powm1( 0.0, 0.0 )\n 0.0\n > y = base.powm1( PI, 5.0 )\n ~305.0197\n > y = base.powm1( NaN, 3.0 )\n NaN\n > y = base.powm1( 5.0, NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.rad2deg":"\nbase.rad2deg( x )\n Converts an angle from radians to degrees.\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2deg( PI/2.0 )\n 90.0\n > d = base.rad2deg( -PI/4.0 )\n -45.0\n > d = base.rad2deg( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2deg( PI/6.0 )\n 29.999999999999996\n\n See Also\n --------\n base.deg2rad\n","base.rad2degf":"\nbase.rad2degf( x )\n Converts an angle from radians to degrees (single-precision).\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2degf( 3.141592653589793 / 2.0 )\n 90.0\n > d = base.rad2degf( -3.141592653589793 / 4.0 )\n -45.0\n > d = base.rad2degf( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2degf( 3.141592653589793 / 6.0 )\n 30.000001907348633\n\n See Also\n --------\n base.rad2deg\n","base.ramp":"\nbase.ramp( x )\n Evaluates the ramp function.\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ramp( 3.14 )\n 3.14\n > y = base.ramp( -3.14 )\n 0.0\n\n See Also\n --------\n base.heaviside\n","base.rampf":"\nbase.rampf( x )\n Evaluates the ramp function (single-precision).\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.rampf( 3.14 )\n 3.14\n > y = base.rampf( -3.14 )\n 0.0\n\n See Also\n --------\n base.ramp\n","base.random.arcsine":"\nbase.random.arcsine( a, b )\n Returns a pseudorandom number drawn from an arcsine distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 5.0 )\n \n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n \n\n\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'\n\n\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n ","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;","base.random.arcsine.state":"\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n ","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta","base.random.bernoulli":"\nbase.random.bernoulli( p )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n ","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial","base.random.beta":"\nbase.random.beta( α, β )\n Returns a pseudorandom number drawn from a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'\n\n\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.beta, random.iterators.beta, random.streams.beta\n","base.random.beta.factory":"\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.beta.NAME":"\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;","base.random.beta.seed":"\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;","base.random.beta.state":"\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n ","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.beta, random.iterators.beta, random.streams.beta","base.random.betaprime":"\nbase.random.betaprime( α, β )\n Returns a pseudorandom number drawn from a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'\n\n\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.betaprime, random.iterators.betaprime, random.streams.betaprime\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;","base.random.betaprime.state":"\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n ","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.betaprime, random.iterators.betaprime, random.streams.betaprime","base.random.binomial":"\nbase.random.binomial( n, p )\n Returns a pseudorandom number drawn from a binomial distribution.\n\n If `n` is not a positive integer or `p` is not a probability, the function\n returns `NaN`.\n\n If `n` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'\n\n\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.binomial, random.iterators.binomial, random.streams.binomial\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;","base.random.binomial.seed":"\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;","base.random.binomial.state":"\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n ","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.binomial, random.iterators.binomial, random.streams.binomial","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'\n\n\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.boxMuller, random.streams.boxMuller\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n ","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.boxMuller, random.streams.boxMuller","base.random.cauchy":"\nbase.random.cauchy( x0, Ɣ )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n\n If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'\n\n\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cauchy, random.iterators.cauchy, random.streams.cauchy\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;","base.random.cauchy.state":"\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n ","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cauchy, random.iterators.cauchy, random.streams.cauchy","base.random.chi":"\nbase.random.chi( k )\n Returns a pseudorandom number drawn from a chi distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'\n\n\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chi, random.iterators.chi, random.streams.chi\n","base.random.chi.factory":"\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();","base.random.chi.NAME":"\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;","base.random.chi.seed":"\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;","base.random.chi.state":"\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n ","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chi, random.iterators.chi, random.streams.chi","base.random.chisquare":"\nbase.random.chisquare( k )\n Returns a pseudorandom number drawn from a chi-square distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'\n\n\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chisquare, random.iterators.chisquare, random.streams.chisquare\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;","base.random.chisquare.state":"\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n ","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chisquare, random.iterators.chisquare, random.streams.chisquare","base.random.cosine":"\nbase.random.cosine( μ, s )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'\n\n\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cosine, random.iterators.cosine, random.streams.cosine\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;","base.random.cosine.seed":"\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;","base.random.cosine.state":"\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n ","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cosine, random.iterators.cosine, random.streams.cosine","base.random.discreteUniform":"\nbase.random.discreteUniform( a, b )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();\n\n\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n ","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform","base.random.erlang":"\nbase.random.erlang( k, λ )\n Returns a pseudorandom number drawn from an Erlang distribution.\n\n If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'\n\n\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.erlang, random.iterators.erlang, random.streams.erlang\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;","base.random.erlang.seed":"\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;","base.random.erlang.state":"\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n ","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.erlang, random.iterators.erlang, random.streams.erlang","base.random.exponential":"\nbase.random.exponential( λ )\n Returns a pseudorandom number drawn from an exponential distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'\n\n\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.exponential, random.iterators.exponential, random.streams.exponential\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;","base.random.exponential.seed":"\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;","base.random.exponential.state":"\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n ","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.exponential, random.iterators.exponential, random.streams.exponential","base.random.f":"\nbase.random.f( d1, d2 )\n Returns a pseudorandom number drawn from an F distribution.\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'\n\n\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.f, random.iterators.f, random.streams.f\n","base.random.f.factory":"\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.f.NAME":"\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'","base.random.f.PRNG":"\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;","base.random.f.seed":"\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;","base.random.f.seedLength":"\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;","base.random.f.state":"\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n ","base.random.f.stateLength":"\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;","base.random.f.byteLength":"\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;","base.random.f.toJSON":"\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.f, random.iterators.f, random.streams.f","base.random.frechet":"\nbase.random.frechet( α, s, m )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'\n\n\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.frechet, random.iterators.frechet, random.streams.frechet\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;","base.random.frechet.seed":"\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;","base.random.frechet.state":"\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n ","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.frechet, random.iterators.frechet, random.streams.frechet","base.random.gamma":"\nbase.random.gamma( α, β )\n Returns a pseudorandom number drawn from a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'\n\n\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gamma, random.iterators.gamma, random.streams.gamma\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;","base.random.gamma.seed":"\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;","base.random.gamma.state":"\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n ","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gamma, random.iterators.gamma, random.streams.gamma","base.random.geometric":"\nbase.random.geometric( p )\n Returns a pseudorandom number drawn from a geometric distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'\n\n\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.geometric, random.iterators.geometric, random.streams.geometric\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;","base.random.geometric.seed":"\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;","base.random.geometric.state":"\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n ","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.geometric, random.iterators.geometric, random.streams.geometric","base.random.gumbel":"\nbase.random.gumbel( μ, β )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n\n If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'\n\n\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gumbel, random.iterators.gumbel, random.streams.gumbel\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;","base.random.gumbel.state":"\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n ","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gumbel, random.iterators.gumbel, random.streams.gumbel","base.random.hypergeometric":"\nbase.random.hypergeometric( N, K, n )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n returns `NaN`.\n\n If `n > N` or `K > N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();\n\n\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n ","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.improvedZiggurat, random.streams.improvedZiggurat\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n ","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.improvedZiggurat, random.streams.improvedZiggurat","base.random.invgamma":"\nbase.random.invgamma( α, β )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'\n\n\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.invgamma, random.iterators.invgamma, random.streams.invgamma\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;","base.random.invgamma.state":"\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n ","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.invgamma, random.iterators.invgamma, random.streams.invgamma","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a, b )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n ","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy","base.random.laplace":"\nbase.random.laplace( μ, b )\n Returns a pseudorandom number drawn from a Laplace distribution.\n\n If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'\n\n\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.laplace, random.iterators.laplace, random.streams.laplace\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;","base.random.laplace.seed":"\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;","base.random.laplace.state":"\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n ","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.laplace, random.iterators.laplace, random.streams.laplace","base.random.levy":"\nbase.random.levy( μ, c )\n Returns a pseudorandom number drawn from a Lévy distribution.\n\n If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'\n\n\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.levy, random.iterators.levy, random.streams.levy\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.levy.NAME":"\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;","base.random.levy.seed":"\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;","base.random.levy.state":"\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n ","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.levy, random.iterators.levy, random.streams.levy","base.random.logistic":"\nbase.random.logistic( μ, s )\n Returns a pseudorandom number drawn from a logistic distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'\n\n\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.logistic, random.iterators.logistic, random.streams.logistic\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;","base.random.logistic.seed":"\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;","base.random.logistic.state":"\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n ","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.logistic, random.iterators.logistic, random.streams.logistic","base.random.lognormal":"\nbase.random.lognormal( μ, σ )\n Returns a pseudorandom number drawn from a lognormal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'\n\n\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.lognormal, random.iterators.lognormal, random.streams.lognormal\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;","base.random.lognormal.state":"\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n ","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.lognormal, random.iterators.lognormal, random.streams.lognormal","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838\n\n\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'\n\n\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1\n\n\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646\n\n\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();","base.random.minstd.factory":"\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646","base.random.minstd.seed":"\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;","base.random.minstd.state":"\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n ","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654\n\n\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1\n\n\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646\n\n\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n ","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775\n\n\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'\n\n\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 0\n\n\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295\n\n\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 0","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;","base.random.mt19937.state":"\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n ","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r, p )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n\n If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n If `r` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n ","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial","base.random.normal":"\nbase.random.normal( μ, σ )\n Returns a pseudorandom number drawn from a normal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'\n\n\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.normal, random.iterators.normal, random.streams.normal\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.normal.NAME":"\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;","base.random.normal.seed":"\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;","base.random.normal.state":"\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n ","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.normal, random.iterators.normal, random.streams.normal","base.random.pareto1":"\nbase.random.pareto1( α, β )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.pareto1, random.iterators.pareto1, random.streams.pareto1\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;","base.random.pareto1.state":"\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n ","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.pareto1, random.iterators.pareto1, random.streams.pareto1","base.random.poisson":"\nbase.random.poisson( λ )\n Returns a pseudorandom number drawn from a Poisson distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'\n\n\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.poisson, random.iterators.poisson, random.streams.poisson\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;","base.random.poisson.seed":"\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;","base.random.poisson.state":"\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n ","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.poisson, random.iterators.poisson, random.streams.poisson","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();\n\n\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'\n\n\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937\n","base.random.randi.factory":"\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();","base.random.randi.NAME":"\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;","base.random.randi.MIN":"\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;","base.random.randi.MAX":"\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;","base.random.randi.seed":"\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;","base.random.randi.state":"\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n ","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'\n\n\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu\n","base.random.randn.factory":"\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();","base.random.randn.NAME":"\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;","base.random.randn.seed":"\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;","base.random.randn.state":"\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n ","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number on the interval `[0,1)`.\n\n Examples\n --------\n > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'\n\n\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn\n","base.random.randu.factory":"\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();","base.random.randu.NAME":"\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;","base.random.randu.MIN":"\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;","base.random.randu.MAX":"\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;","base.random.randu.seed":"\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;","base.random.randu.state":"\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n ","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn","base.random.rayleigh":"\nbase.random.rayleigh( σ )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n ","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh","base.random.t":"\nbase.random.t( v )\n Returns a pseudorandom number drawn from a Student's t distribution.\n\n If `v <= 0` or `v` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'\n\n\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.t, random.iterators.t, random.streams.t\n","base.random.t.factory":"\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();","base.random.t.NAME":"\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'","base.random.t.PRNG":"\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;","base.random.t.seed":"\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;","base.random.t.seedLength":"\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;","base.random.t.state":"\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n ","base.random.t.stateLength":"\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;","base.random.t.byteLength":"\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;","base.random.t.toJSON":"\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.t, random.iterators.t, random.streams.t","base.random.triangular":"\nbase.random.triangular( a, b, c )\n Returns a pseudorandom number drawn from a triangular distribution.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'\n\n\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.triangular, random.iterators.triangular, random.streams.triangular\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;","base.random.triangular.seed":"\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;","base.random.triangular.state":"\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n ","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.triangular, random.iterators.triangular, random.streams.triangular","base.random.uniform":"\nbase.random.uniform( a, b )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support (inclusive).\n\n b: number\n Maximum support (exclusive).\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'\n\n\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;","base.random.uniform.seed":"\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;","base.random.uniform.state":"\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n ","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu","base.random.weibull":"\nbase.random.weibull( k, λ )\n Returns a pseudorandom number drawn from a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'\n\n\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.weibull, random.iterators.weibull, random.streams.weibull\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;","base.random.weibull.seed":"\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;","base.random.weibull.state":"\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n ","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.weibull, random.iterators.weibull, random.streams.weibull","base.rcbrt":"\nbase.rcbrt( x )\n Computes the reciprocal cube root of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal cube root.\n\n Examples\n --------\n > var y = base.rcbrt( 8.0 )\n 0.5\n > y = base.rcbrt( 1000.0 )\n 0.1\n > y = base.rcbrt( 0.0 )\n Infinity\n > y = base.rcbrt( PINF )\n 0.0\n > y = base.rcbrt( -8.0 )\n -0.5\n > y = base.rcbrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt\n","base.rcbrtf":"\nbase.rcbrtf( x )\n Computes the reciprocal cube root of a single-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal cube root.\n\n Examples\n --------\n > var y = base.rcbrtf( 8.0 )\n 0.5\n > y = base.rcbrtf( 1000.0 )\n ~0.1\n > y = base.rcbrtf( 0.0 )\n Infinity\n > y = base.rcbrtf( PINF )\n 0.0\n > y = base.rcbrtf( -8.0 )\n -0.5\n > y = base.rcbrtf( NaN )\n NaN\n\n See Also\n --------\n base.rcbrt, base.cbrtf\n","base.reldiff":"\nbase.reldiff( x, y[, scale] )\n Computes the relative difference of two real numbers.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference.\n\n Examples\n --------\n > var d = base.reldiff( 2.0, 5.0 )\n 0.6\n > d = base.reldiff( -1.0, 3.14 )\n ~1.318\n > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'max' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'min' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n 2.0\n > d = base.reldiff( -2.0, 5.0, 'mean' )\n ~4.667\n > d = base.reldiff( -2.0, 5.0, 'x' )\n 3.5\n > d = base.reldiff( 5.0, -2.0, 'x' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'y' )\n 1.4\n > d = base.reldiff( 5.0, -2.0, 'y' )\n 3.5\n\n // Custom scale function:\n > function scale( x, y ) {\n ... var s;\n ...\n ... x = base.abs( x );\n ... y = base.abs( y );\n ...\n ... // Maximum absolute value:\n ... s = (x < y ) ? y : x;\n ...\n ... // Scale in units of epsilon:\n ... return s * EPS;\n ... };\n > d = base.reldiff( 12.15, 12.149999999999999, scale )\n ~0.658\n\n See Also\n --------\n base.absdiff, base.epsdiff\n","base.removeFirst":"\nbase.removeFirst( str, n )\n Removes the first `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirst( 'beep', 1 )\n 'eep'\n > out = base.removeFirst( 'Boop', 1 )\n 'oop'\n > out = base.removeFirst( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeFirstGraphemeCluster, base.removeLast\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str, n )\n Removes the first `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirstCodePoint( 'beep', 1 )\n 'eep'\n > out = base.removeFirstCodePoint( 'Boop', 1 )\n 'oop'\n > out = base.removeFirstCodePoint( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeLastCodePoint, base.removeFirstGraphemeCluster, base.removeFirst\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str, n )\n Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirstGraphemeCluster( 'beep', 1 )\n 'eep'\n > out = base.removeFirstGraphemeCluster( 'Boop', 1 )\n 'oop'\n > out = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLast":"\nbase.removeLast( str, n )\n Removes the last `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLast( 'beep', 1 )\n 'bee'\n > out = base.removeLast( 'Boop', 1 )\n 'Boo'\n > out = base.removeLast( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeLastCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str, n )\n Removes the last `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLastCodePoint( 'beep', 1 )\n 'bee'\n > out = base.removeLastCodePoint( 'Boop', 1 )\n 'Boo'\n > out = base.removeLastCodePoint( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeLast\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str, n )\n Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLastGraphemeCluster( 'beep', 1 )\n 'bee'\n > out = base.removeLastGraphemeCluster( 'Boop', 1 )\n 'Boo'\n > out = base.removeLastGraphemeCluster( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastCodePoint, base.removeLast\n","base.rempio2":"\nbase.rempio2( x, y )\n Computes `x - nπ/2 = r`.\n\n The function returns `n` and stores the remainder `r` as the two numbers\n `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n For input values larger than `2^20 * π/2` in magnitude, the function only\n returns the last three binary digits of `n` and not the full result.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: Array|TypedArray|Object\n Remainder elements.\n\n Returns\n -------\n n: integer\n Factor of `π/2`.\n\n Examples\n --------\n > var y = [ 0.0, 0.0 ];\n > var n = base.rempio2( 128.0, y )\n 81\n > var y1 = y[ 0 ]\n ~0.765\n > var y2 = y[ 1 ]\n ~3.618e-17\n\n\n","base.repeat":"\nbase.repeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = base.repeat( 'a', 5 )\n 'aaaaa'\n > out = base.repeat( '', 100 )\n ''\n > out = base.repeat( 'beep', 0 )\n ''\n\n","base.replace":"\nbase.replace( str, search, newval )\n Replaces search occurrences with a replacement string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > var out = base.replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = base.replace( 'beep', /e/, 'o' )\n 'boep'\n\n See Also\n --------\n base.replaceAfter, base.replaceBefore, base.replaceAfterLast, base.replaceBeforeLast\n","base.replaceAfter":"\nbase.replaceAfter( str, search, replacement, fromIndex )\n Replaces the substring after the first occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\n 'beep foo'\n > out = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\n 'beep bofoo'\n > out = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\n 'Hello Wofoo'\n > out = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n 'beep boop beepfoo'\n\n See Also\n --------\n base.replaceAfterLast, base.replaceBefore, base.replaceBeforeLast\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str, search, replacement, fromIndex )\n Replaces the substring after the last occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n The function scans an input string from the starting index to the beginning\n of the string (i.e., backward).\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.replaceAfterLast( str, ' ', 'foo', str.length )\n 'beep foo'\n > out = base.replaceAfterLast( str, 'o', 'foo', str.length )\n 'beep boofoo'\n > out = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n 'Hellofoo'\n\n See Also\n --------\n base.replaceAfter, base.replaceBeforeLast, base.replaceBefore\n","base.replaceBefore":"\nbase.replaceBefore( str, search, replacement, fromIndex )\n Replaces the substring before the first occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\n 'foo boop'\n > out = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n 'foooop'\n\n See Also\n --------\n base.replaceAfter, base.replaceBeforeLast, base.replaceAfterLast\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str, search, replacement, fromIndex )\n Replaces the substring before the last occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n The function scans an input string from the starting index to the beginning\n of the string (i.e., backward).\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\n 'foo boop'\n > out = base.replaceBeforeLast( str, 'o', 'foo', str.length )\n 'fooop'\n > out = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n 'fooo World!'\n\n See Also\n --------\n base.replaceAfterLast, base.replaceAfter, base.replaceBefore\n","base.reverse":"\nbase.reverse( str )\n Reverses the UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverse( 'beep' )\n 'peeb'\n > out = base.reverse( 'Boop' )\n 'pooB'\n > out = base.reverse( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseCodePoints, base.reverseGraphemeClusters\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str )\n Reverses the Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverseCodePoints( 'beep' )\n 'peeb'\n > out = base.reverseCodePoints( 'Boop' )\n 'pooB'\n > out = base.reverseCodePoints( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseGraphemeClusters, base.reverse\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str )\n Reverses the grapheme clusters (i.e., user-perceived characters) of a\n string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverseGraphemeClusters( 'beep' )\n 'peeb'\n > out = base.reverseGraphemeClusters( 'Boop' )\n 'pooB'\n > out = base.reverseGraphemeClusters( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseCodePoints, base.reverse\n","base.rightPad":"\nbase.rightPad( str, len, pad )\n Right pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string\n String used to pad.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = base.rightPad( 'a', 5, ' ' )\n 'a '\n > out = base.rightPad( 'beep', 10, 'b' )\n 'beepbbbbbb'\n > out = base.rightPad( 'boop', 12, 'beep' )\n 'boopbeepbeep'\n\n See Also\n --------\n base.leftPad\n","base.rightTrim":"\nbase.rightTrim( str )\n Trims whitespace from the end of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.rightTrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n See Also\n --------\n base.leftTrim\n","base.risingFactorial":"\nbase.risingFactorial( x, n )\n Computes the rising factorial of `x` and `n`.\n\n If provided a non-integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.risingFactorial( 0.9, 5 )\n ~94.766\n > v = base.risingFactorial( -9.0, 3 )\n -504.0\n > v = base.risingFactorial( 0.0, 2 )\n 0.0\n > v = base.risingFactorial( 3.0, -2 )\n 0.5\n\n See Also\n --------\n base.fallingFactorial\n","base.rotl32":"\nbase.rotl32( x, shift )\n Performs a bitwise rotation to the left.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 2147483649;\n > var bStr = base.toBinaryStringUint32( x )\n '10000000000000000000000000000001'\n > var y = base.rotl32( x, 10 )\n 1536\n > bstr = base.toBinaryStringUint32( y )\n '00000000000000000000011000000000'\n\n See Also\n --------\n base.rotr32\n","base.rotr32":"\nbase.rotr32( x, shift )\n Performs a bitwise rotation to the right.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 1;\n > var bStr = base.toBinaryStringUint32( x )\n '00000000000000000000000000000001'\n > var y = base.rotr32( x, 10 )\n 4194304\n > bstr = base.toBinaryStringUint32( y )\n '00000000010000000000000000000000'\n\n See Also\n --------\n base.rotl32\n","base.round":"\nbase.round( x )\n Rounds a numeric value to the nearest integer.\n\n Ties are rounded toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round( 3.14 )\n 3.0\n > y = base.round( -4.2 )\n -4.0\n > y = base.round( -4.6 )\n -5.0\n > y = base.round( 9.5 )\n 10.0\n > y = base.round( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.roundn, base.trunc\n","base.round2":"\nbase.round2( x )\n Rounds a numeric value to the nearest power of two on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round2( 3.14 )\n 4.0\n > y = base.round2( -4.2 )\n -4.0\n > y = base.round2( -4.6 )\n -4.0\n > y = base.round2( 9.5 )\n 8.0\n > y = base.round2( 13.0 )\n 16.0\n > y = base.round2( -13.0 )\n -16.0\n > y = base.round2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round, base.round10\n","base.round10":"\nbase.round10( x )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round10( 3.14 )\n 1.0\n > y = base.round10( -4.2 )\n -1.0\n > y = base.round10( -4.6 )\n -1.0\n > y = base.round10( 9.5 )\n 10.0\n > y = base.round10( 13.0 )\n 10.0\n > y = base.round10( -13.0 )\n -10.0\n > y = base.round10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round, base.round2\n","base.roundb":"\nbase.roundb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundb( 3.14159, -2, 10 )\n 3.14\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.roundb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two:\n > y = base.roundb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.round, base.roundn\n","base.roundn":"\nbase.roundn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundn( 3.14159, -2 )\n 3.14\n\n // If `n = 0`, standard round behavior:\n > y = base.roundn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.roundn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.round, base.roundb\n","base.roundsd":"\nbase.roundsd( x, n[, b] )\n Rounds a double-precision floating-point number to the nearest value with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.roundsd( 3.14159, 3 )\n 3.14\n > y = base.roundsd( 3.14159, 1 )\n 3.0\n > y = base.roundsd( 12368.0, 2 )\n 12000.0\n > y = base.roundsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.round, base.truncsd\n","base.rsqrt":"\nbase.rsqrt( x )\n Computes the reciprocal square root of a double-precision floating-point\n number.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrt( 4.0 )\n 0.5\n > y = base.rsqrt( 100.0 )\n 0.1\n > y = base.rsqrt( 0.0 )\n Infinity\n > y = base.rsqrt( Infinity )\n 0.0\n > y = base.rsqrt( -4.0 )\n NaN\n > y = base.rsqrt( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.rsqrtf":"\nbase.rsqrtf( x )\n Computes the reciprocal square root of a single-precision floating-point\n number.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrtf( 4.0 )\n 0.5\n > y = base.rsqrtf( 0.0 )\n Infinity\n > y = base.rsqrtf( Infinity )\n 0.0\n > y = base.rsqrtf( -4.0 )\n NaN\n > y = base.rsqrtf( NaN )\n NaN\n\n See Also\n --------\n base.rsqrt, base.sqrtf\n","base.sargs2multislice":"\nbase.sargs2multislice( str )\n Creates a MultiSlice object from a comma-separated list of string-serialized\n MultiSlice constructor arguments.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string containing constructor arguments.\n\n Returns\n -------\n s: MultiSlice|null\n MultiSlice instance (or null).\n\n Examples\n --------\n > var s = new base.sargs2multislice( 'null,null,null' );\n > s.data\n [ null, null, null ]\n > s = new base.sargs2multislice( '10,Slice(0,10,1),null' );\n > s.data\n [ 10, , null ]\n\n See Also\n --------\n base.args2multislice, base.seq2multislice\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value, dtype, order )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n\n If `value` is a number and `dtype` is a complex number data type, the\n function returns a zero-dimensional ndarray containing a complex number\n whose real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n dtype: string|DataType\n Data type.\n\n order: string\n Memory layout (either 'row-major' or 'column-major').\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\n \n > var sh = ndarrayShape( x )\n []\n > var v = x.get()\n 1.0\n\n See Also\n --------\n array, base.ndarray, ndarray\n","base.secd":"\nbase.secd( x )\n Computes the secant of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Secant.\n\n Examples\n --------\n > var y = base.secd( 1.0 )\n ~1.0\n > y = base.secd( PI )\n ~1.0\n > y = base.secd( -PI )\n ~1.0\n > y = base.secd( NaN )\n NaN\n\n See Also\n --------\n base.cosd, base.cos\n","base.seq2multislice":"\nbase.seq2multislice( str, shape, strict )\n Converts a multidimensional subsequence string to a MultiSlice object.\n\n A multidimensional subsequence string is a comma-separated list of single-\n dimension indexing expressions (i.e., integers and/or subsequence strings).\n\n For example, the following\n\n 2\n :\n 2:\n :10\n 2:10\n ::-1\n 10:2:-1\n :2:\n 2:10:\n 2::2\n :10:2\n :, :, :\n 1, 2, 3\n 0:10, 1:20:2, ::-1\n ...\n :, ..., 2\n\n are all valid multidimensional subsequence strings.\n\n Providing a single nonnegative integer `i` as a single-dimension index\n indexes the same elements as the subsequence `i:i+1`.\n\n Providing a single negative integer `i` as a single-dimension index indexes\n the same elements as the subsequence `n+i:n+i+i`, where `n` is the dimension\n size.\n\n While integers index the same elements as equivalent subsequences, providing\n an integer as a single-dimension index indicates to reduce the number of\n dimensions by one (e.g., if the provided shape corresponds to an array\n having rank 2, then rank(A)-1 == rank(A['0,:'])).\n\n In contrast, providing a subsequence indicates to retain a respective\n dimension (e.g., if the provided shape corresponds to an array having rank\n 2, then rank(A) == rank(A[':,:'])).\n\n A multidimensional subsequence string can only contain **one** ellipsis\n ('...') operator. An ellipsis indicates to apply ':' to each dimension\n necessary to index all dimensions (e.g., if A has rank 4, A['1:,...,2:5']\n equals A['1:,:,:,2:5']).\n\n Except in the case of providing a single ellipsis, the number of single-\n dimension indexing expressions must equal the number of dimensions in the\n input shape.\n\n The function returns an error object if provided an invalid subsequence\n string.\n\n In strict mode, the function returns an error object if a single-dimension\n index expression which exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n increment.\n - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n exceeding index bounds.\n - ERR_SLICE_TOO_MANY_DIMENSIONS: a subsequence string has more dimensions\n than the provided shape.\n - ERR_SLICE_INSUFFICIENT_DIMENSIONS: a subsequence string has too few\n dimensions.\n - ERR_SLICE_INVALID_ELLIPSIS: a subsequence string must only contain at most\n one ellipsis.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n shape: Array\n Maximum allowed slice shape.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: MultiSlice|Object\n MultiSlice instance or an error object.\n\n Examples\n --------\n > var s = new base.seq2multislice( '1:10', [ 10 ], false );\n > s.data\n [ ]\n > s = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\n > s.data\n [ 4, , ]\n\n See Also\n --------\n base.seq2slice, base.sargs2multislice\n","base.seq2slice":"\nbase.seq2slice( str, len, strict )\n Converts a subsequence string to a Slice object.\n\n A subsequence string has the following format:\n\n ::\n\n If an increment is not specified, the default increment is one. An increment\n of zero is not allowed.\n\n The start index is inclusive.\n\n The stop index is exclusive.\n\n Both start and stop indices are optional. If not provided, the start and\n stop indices default to index extremes. Which extremes correspond to which\n index depends on whether the increment is positive or negative.\n\n Both start and stop indices can be negative; in which case, the\n corresponding index is resolved by subtracting the respective value from the\n provided length.\n\n Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n 'end-3:', etc), which supports basic subtraction and division.\n\n The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n exception is when performing a division operation when the increment is less\n than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n user expectations when 'end/d' equals a whole number and slicing from right-\n to-left. The result from a division operation is rounded down to the nearest\n integer value.\n\n In non-strict mode, the resolved slice start is clamped to the slice index\n bounds [0, len).\n\n In non-strict mode, Tte resolved slice end is upper bound clamped to the\n provided length (i.e., one greater than the last possible index).\n\n When the increment is negative, the resolved slice end value may be `null`,\n thus indicating that a non-empty slice should include the first index.\n\n The function ensures that results satisfy the convention that ':n' combined\n with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n When the provided length is zero, the function always returns a slice object\n equivalent to '0:0:'.\n\n The function returns an error object if provided an invalid subsequence\n string.\n\n In strict mode, the function returns an error object if provided a\n subsequence string which exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n increment.\n - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n exceeding index bounds.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance or an error object.\n\n Examples\n --------\n > var s = new base.seq2slice( '1:10', 10, false );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new base.seq2slice( '2:5:2', 10, false );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n base.seq2multislice, base.slice2seq\n","base.setHighWord":"\nbase.setHighWord( x, high )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n high: integer\n Unsigned 32-bit integer to replace the higher order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same lower order word as `x`.\n\n Examples\n --------\n // Set the higher order bits of `+infinity` to return `1`:\n > var high = 1072693248 >>> 0;\n > var y = base.setHighWord( PINF, high )\n 1.0\n\n See Also\n --------\n base.getHighWord, base.setLowWord\n","base.setLowWord":"\nbase.setLowWord( x, low )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n\n Setting the lower order bits of `NaN` or positive or negative infinity will\n return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n all ones and whose fraction can be any bit sequence except all zeros.\n Positive and negative infinity are defined as doubles with an exponent bit\n sequence equal to all ones and a fraction equal to all zeros. Hence,\n changing the less significant bits of positive and negative infinity\n converts each value to `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n low: integer\n Unsigned 32-bit integer to replace the lower order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same higher order word as `x`.\n\n Examples\n --------\n > var low = 5 >>> 0;\n > var x = 3.14e201;\n > var y = base.setLowWord( x, low )\n 3.139998651394392e+201\n\n // Special cases:\n > var low = 12345678;\n > var y = base.setLowWord( PINF, low )\n NaN\n > y = base.setLowWord( NINF, low )\n NaN\n > y = base.setLowWord( NaN, low )\n NaN\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.sici":"\nbase.sici( x )\n Computes the sine and cosine integrals.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n Sine and cosine integrals.\n\n Examples\n --------\n > var y = base.sici( 3.0 )\n [ ~1.849, ~0.12 ]\n > y = base.sici( 0.0 )\n [ 0.0, -Infinity ]\n > y = base.sici( -9.0 )\n [ ~-1.665, ~0.055 ]\n > y = base.sici( NaN )\n [ NaN, NaN ]\n\n\nbase.sici.assign( x, out, stride, offset )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.sici.assign( 3.0, out, 1, 0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true\n","base.sici.assign":"\nbase.sici.assign( x, out, stride, offset )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.sici.assign( 3.0, out, 1, 0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true","base.signbit":"\nbase.signbit( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbit( 4.0 )\n false\n > bool = base.signbit( -9.14e-34 )\n true\n > bool = base.signbit( 0.0 )\n false\n > bool = base.signbit( -0.0 )\n true\n\n See Also\n --------\n base.signbitf\n","base.signbitf":"\nbase.signbitf( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\n false\n > bool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\n true\n > bool = base.signbitf( 0.0 )\n false\n > bool = base.signbitf( -0.0 )\n true\n\n See Also\n --------\n base.signbit\n","base.significandf":"\nbase.significandf( x )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Significand.\n\n Examples\n --------\n > var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\n 4293751\n > s = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\n 5288021\n > s = base.significandf( base.float64ToFloat32( -3.14 ) )\n 4781507\n > s = base.significandf( 0.0 )\n 0\n > s = base.significandf( NaN )\n 4194304\n\n","base.signum":"\nbase.signum( x )\n Evaluates the signum function for a double-precision floating-point number.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signum( -5.0 )\n -1.0\n > sign = base.signum( 5.0 )\n 1.0\n > sign = base.signum( -0.0 )\n -0.0\n > sign = base.signum( 0.0 )\n 0.0\n > sign = base.signum( NaN )\n NaN\n\n","base.signumf":"\nbase.signumf( x )\n Evaluates the signum function for a single-precision floating-point number.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signumf( -5.0 )\n -1.0\n > sign = base.signumf( 5.0 )\n 1.0\n > sign = base.signumf( -0.0 )\n -0.0\n > sign = base.signumf( 0.0 )\n 0.0\n > sign = base.signumf( NaN )\n NaN\n\n See Also\n --------\n base.signum\n","base.sin":"\nbase.sin( x )\n Computes the sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Sine.\n\n Examples\n --------\n > var y = base.sin( 0.0 )\n ~0.0\n > y = base.sin( PI/2.0 )\n ~1.0\n > y = base.sin( -PI/6.0 )\n ~-0.5\n > y = base.sin( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinpi, base.tan\n","base.sinc":"\nbase.sinc( x )\n Computes the normalized cardinal sine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cardinal sine.\n\n Examples\n --------\n > var y = base.sinc( 0.5 )\n ~0.637\n > y = base.sinc( -1.2 )\n ~-0.156\n > y = base.sinc( 0.0 )\n 1.0\n > y = base.sinc( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.sincos":"\nbase.sincos( x )\n Simultaneously computes the sine and cosine of an angle measured in radians.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: Array\n Sine and cosine.\n\n Examples\n --------\n > var y = base.sincos( 0.0 )\n [ ~0.0, ~1.0 ]\n > y = base.sincos( PI/2.0 )\n [ ~1.0, ~0.0 ]\n > y = base.sincos( -PI/6.0 )\n [ ~-0.5, ~0.866 ]\n > y = base.sincos( NaN )\n [ NaN, NaN ]\n\n\nbase.sincos.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of an angle measured in radians\n and assigns the results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincos.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cos, base.sin, base.sincospi","base.sincos.assign":"\nbase.sincos.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of an angle measured in radians\n and assigns the results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincos.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cos, base.sin, base.sincospi","base.sincospi":"\nbase.sincospi( x )\n Simultaneously computes the sine and cosine of a number times π.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: Array\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var y = base.sincospi( 0.0 )\n [ 0.0, 1.0 ]\n > y = base.sincospi( 0.5 )\n [ 1.0, 0.0 ]\n > y = base.sincospi( 0.1 )\n [ ~0.309, ~0.951 ]\n > y = base.sincospi( NaN )\n [ NaN, NaN ]\n\n\nbase.sincospi.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi","base.sincospi.assign":"\nbase.sincospi.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi","base.sinh":"\nbase.sinh( x )\n Computes the hyperbolic sine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic sine.\n\n Examples\n --------\n > var y = base.sinh( 0.0 )\n 0.0\n > y = base.sinh( 2.0 )\n ~3.627\n > y = base.sinh( -2.0 )\n ~-3.627\n > y = base.sinh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sin, base.tanh\n","base.sinpi":"\nbase.sinpi( x )\n Computes the value of `sin(πx)`.\n\n The function computes `sin(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.sinpi( 0.0 )\n 0.0\n > y = base.sinpi( 0.5 )\n 1.0\n > y = base.sinpi( 0.9 )\n ~0.309\n > y = base.sinpi( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.slice2seq":"\nbase.slice2seq( slice )\n Converts a Slice object to a subsequence string.\n\n Parameters\n ----------\n slice: Slice\n Input slice.\n\n Returns\n -------\n out: string\n Subsequence string.\n\n Examples\n --------\n > var out = base.slice2seq( new Slice( 1, 10, 1 ) )\n '1:10:1'\n > out = base.slice2seq( new Slice( null, 10 ) )\n ':10'\n\n See Also\n --------\n base.seq2slice\n","base.sliceLength":"\nbase.sliceLength( slice )\n Returns the number of elements in a normalized slice.\n\n Parameters\n ----------\n slice: Slice\n Input normalized slice object.\n\n Returns\n -------\n len: integer\n Number of elements.\n\n Examples\n --------\n > var s = new Slice( 1, 10, 1 );\n > base.sliceLength( s )\n 9\n\n See Also\n --------\n base.sliceNonReducedDimensions, base.sliceReducedDimensions, base.sliceShape\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice )\n Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input slice object.\n\n Returns\n -------\n out: Array\n Dimension indices.\n\n Examples\n --------\n > var s = new MultiSlice( 1, 3, null );\n > var out = base.sliceNonReducedDimensions( s )\n [ 2 ]\n\n See Also\n --------\n base.sliceLength, base.sliceReducedDimensions, base.sliceShape\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice )\n Returns a list of reduced dimensions in an un-normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input slice object.\n\n Returns\n -------\n out: Array\n Dimension indices.\n\n Examples\n --------\n > var s = new MultiSlice( 1, 3, null );\n > var out = base.sliceReducedDimensions( s )\n [ 0, 1 ]\n\n See Also\n --------\n base.sliceLength, base.sliceNonReducedDimensions, base.sliceShape\n","base.sliceShape":"\nbase.sliceShape( slice )\n Returns the shape of a normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input normalized multi-slice object.\n\n Returns\n -------\n sh: Array\n Slice shape.\n\n Examples\n --------\n > var s = new Slice( 1, 10, 1 );\n > var ms = new MultiSlice( s, s );\n > base.sliceShape( ms )\n [ 9, 9 ]\n\n See Also\n --------\n base.sliceLength, base.sliceNonReducedDimensions, base.sliceReducedDimensions\n","base.snakecase":"\nbase.snakecase( str )\n Converts a string to snake case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Snake-cased string.\n\n Examples\n --------\n > var out = base.snakecase( 'Hello World!' )\n 'hello_world'\n > out = base.snakecase( 'I am a tiny little teapot' )\n 'i_am_a_tiny_little_teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.stickycase, base.uppercase","base.spence":"\nbase.spence( x )\n Evaluates Spence's function, which is also known as the dilogarithm.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.spence( 3.0 )\n ~-1.437\n > y = base.spence( 0.0 )\n ~1.645\n > y = base.spence( -9.0 )\n NaN\n > y = base.spence( NaN )\n NaN\n\n","base.sqrt":"\nbase.sqrt( x )\n Computes the principal square root of a double-precision floating-point\n number.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrt( 4.0 )\n 2.0\n > y = base.sqrt( 9.0 )\n 3.0\n > y = base.sqrt( 0.0 )\n 0.0\n > y = base.sqrt( -4.0 )\n NaN\n > y = base.sqrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.rsqrt\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x )\n Computes the principal square root of `1+x` minus one.\n\n This function is more accurate than the obvious approach for small `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Square root of `1+x` minus one.\n\n Examples\n --------\n > var y = base.sqrt1pm1( 3.0 )\n 1.0\n > y = base.sqrt1pm1( 0.5 )\n ~0.225\n > y = base.sqrt1pm1( 0.02 )\n ~0.01\n > y = base.sqrt1pm1( -0.5 )\n ~-0.293\n > y = base.sqrt1pm1( -1.1 )\n NaN\n > y = base.sqrt1pm1( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.sqrtf":"\nbase.sqrtf( x )\n Computes the principal square root of a single-precision floating-point\n number.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrtf( 4.0 )\n 2.0\n > y = base.sqrtf( 9.0 )\n 3.0\n > y = base.sqrtf( 0.0 )\n 0.0\n > y = base.sqrtf( -4.0 )\n NaN\n > y = base.sqrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrtf, base.rsqrtf, base.sqrt\n","base.sqrtpi":"\nbase.sqrtpi( x )\n Computes the principal square root of the product of π and a positive\n double-precision floating-point number.\n\n For `x < 0`, the square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root of the product of π and the input value.\n\n Examples\n --------\n > var y = base.sqrtpi( 4.0 )\n ~3.5449\n > y = base.sqrtpi( 10.0 )\n ~5.60499\n > y = base.sqrtpi( 0.0 )\n 0.0\n > y = base.sqrtpi( -4.0 )\n NaN\n > y = base.sqrtpi( NaN )\n NaN\n\n See Also\n --------\n base.sqrt","base.startcase":"\nbase.startcase( str )\n Capitalizes the first letter of each word in an input string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = base.startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n base.capitalize, base.lowercase, base.uppercase\n","base.startsWith":"\nbase.startsWith( str, search, position )\n Tests if a string starts with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string starts with the characters of\n another string.\n\n Examples\n --------\n > var bool = base.startsWith( 'Beep', 'Be', 0 )\n true\n > bool = base.startsWith( 'Beep', 'ep', 0 )\n false\n > bool = base.startsWith( 'Beep', 'ee', 1 )\n true\n > bool = base.startsWith( 'Beep', 'ee', -3 )\n true\n > bool = base.startsWith( 'Beep', '', 0 )\n true\n\n See Also\n --------\n base.endsWith\n","base.stickycase":"\nbase.stickycase( str[, p] )\n Converts a string to sticky case.\n\n Parameters\n ----------\n str: string\n Input string.\n \n p: number\n Probability of capitalization.\n\n Returns\n -------\n out: string\n Sticky-cased string.\n\n Examples\n --------\n > var out = base.stickycase( 'Hello World!' )\n \n\n > out = base.stickycase( 'I am a tiny little teapot' )\n \n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase\n","base.strided.binary":"\nbase.strided.binary( arrays, shape, strides, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary( [ x, y, z ], shape, strides, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1, dtypes2, dtypes3[, options] )\n Generates a list of binary interface signatures from strided array data\n types.\n\n The function returns a strided array having a stride length of `3` (i.e.,\n every `3` elements define a binary interface signature).\n\n For each signature (i.e., set of three consecutive non-overlapping strided\n array elements), the first two elements are the input data types and the\n third element is the return data type.\n\n All signatures follow type promotion rules.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the first input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the second input argument.\n\n dtypes3: ArrayLike\n List of supported data types for the output value.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing binary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n [...]\n\n See Also\n --------\n base.strided.binarySignatureCallbacks\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table, signatures )\n Assigns callbacks to binary interfaces according to type promotion rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing binary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\n > var t = {\n ... 'default': base.add,\n ... 'complex64': base.caddf,\n ... 'complex128': base.cadd\n ... };\n > var out = base.strided.binarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.binaryDtypeSignatures\n","base.strided.ccopy":"\nbase.strided.ccopy( N, x, strideX, y, strideY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy( 2, x, -2, y, 1 )\n [ 5.0, 6.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0 ]\n\n // Using typed array views:\n > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.ccopy( 2, x1, -2, y1, 1 )\n [ 7.0, 8.0, 3.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.cswap\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.cswap","base.strided.cmap":"\nbase.strided.cmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\n > var v = y.get( 0 )\n [ 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > y = new Complex64Array( x.length );\n > base.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\n > v = y.get( 0 )\n [ 5.0, 6.0 ]\n\n // Using view offsets:\n > var x0 = new Complex64Array( xbuf );\n > var y0 = new Complex64Array( x0.length );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\n > v = y1.get( 0 )\n [ 7.0, 8.0 ]\n\n\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n > var v = y.get( 0 )\n [ 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( xbuf );\n > y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n > v = y.get( y.length-1 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.zmap, base.strided.unary\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n > var v = y.get( 0 )\n [ 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( xbuf );\n > y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n > v = y.get( y.length-1 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.zmap, base.strided.unary","base.strided.cswap":"\nbase.strided.cswap( N, x, strideX, y, strideY )\n Interchanges two complex single-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap( x.length, x, 1, y, 1 );\n > x\n [ 6.0, 7.0, 8.0, 9.0 ]\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap( 2, x, -2, y, 1 );\n > x\n [ 0.0, 0.0, 3.0, 4.0, 0.0, 0.0, 7.0, 8.0 ]\n > y\n [ 5.0, 6.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0 ]\n\n // Using typed array views:\n > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.cswap( 2, x1, -2, y1, 1 );\n > x0\n [ 1.0, 2.0, 0.0, 0.0, 5.0, 6.0, 0.0, 0.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > x\n [ 6.0, 7.0, 8.0, 9.0 ]\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > x\n [ 1.0, 2.0, 0.0, 0.0, 5.0, 6.0, 0.0, 0.0 ]\n > y\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.ccopy\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > x\n [ 6.0, 7.0, 8.0, 9.0 ]\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > x\n [ 1.0, 2.0, 0.0, 0.0, 5.0, 6.0, 0.0, 0.0 ]\n > y\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.ccopy","base.strided.cumax":"\nbase.strided.cumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of a strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.cumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumax\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumax","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.cumaxabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs","base.strided.cumin":"\nbase.strided.cumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of a strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumin( 3, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.cumin( 3, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumin\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumin","base.strided.cuminabs":"\nbase.strided.cuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.cuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs","base.strided.dabs":"\nbase.strided.dabs( N, x, strideX, y, strideY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs( N, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs","base.strided.dabs2":"\nbase.strided.dabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2","base.strided.dapx":"\nbase.strided.dapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx","base.strided.dapxsum":"\nbase.strided.dapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumkbn( 3, 5.0, x1, 2)\n 14.0\n\n\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation.\n\n The `N` and stride parameters determine which elements in\n the strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw","base.strided.dasum":"\nbase.strided.dasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.dasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.dasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum","base.strided.dasumpw":"\nbase.strided.dasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var stride = 2;\n > base.strided.dasumpw( 3, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.dasumpw( 3, x1, stride )\n 5.0\n\n\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw","base.strided.daxpy":"\nbase.strided.daxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.daxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.dasum, base.strided.gaxpy, base.strided.saxpy\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.dasum, base.strided.gaxpy, base.strided.saxpy","base.strided.dcbrt":"\nbase.strided.dcbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, base.strided.scbrt\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, base.strided.scbrt","base.strided.dceil":"\nbase.strided.dceil( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil( x.length, x, 1, y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil( N, x, 2, y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dceil( N, x1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil","base.strided.dcopy":"\nbase.strided.dcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy","base.strided.dcumax":"\nbase.strided.dcumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumaxabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs","base.strided.dcumin":"\nbase.strided.dcumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin( 3, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumin( 3, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs","base.strided.dcusum":"\nbase.strided.dcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2","base.strided.dcusumors":"\nbase.strided.dcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N, x, strideX, y, strideY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ddeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n strided.deg2rad, base.strided.sdeg2rad\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n strided.deg2rad, base.strided.sdeg2rad","base.strided.ddot":"\nbase.strided.ddot( N, x, strideX, y, strideY )\n Computes the dot product of two double-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.ddot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot","base.strided.dfill":"\nbase.strided.dfill( N, alpha, x, strideX )\n Fills a double-precision floating-point strided array with a specified\n scalar constant.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a double-precision floating-point strided array with a specified\n scalar constant using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill, base.strided.sfill\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a double-precision floating-point strided array with a specified\n scalar constant using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill, base.strided.sfill","base.strided.dfloor":"\nbase.strided.dfloor( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor( x.length, x, 1, y, 1 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor( N, x, 2, y, -1 )\n [ 3.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dfloor( N, x1, -2, y1, 1 )\n [ 4.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor","base.strided.dinv":"\nbase.strided.dinv( N, x, strideX, y, strideY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv( x.length, x, 1, y, 1 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv( N, x, 2, y, -1 )\n [ 0.5, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dinv( N, x1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n strided.inv, base.strided.sinv\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n strided.inv, base.strided.sinv","base.strided.dmap":"\nbase.strided.dmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap( x.length, x, 1, y, 1, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap( 2, x, 2, y, -1, base.identity )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmap( 2, x1, -2, y1, 1, base.identity )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.smap, base.strided.unary\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.smap, base.strided.unary","base.strided.dmap2":"\nbase.strided.dmap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays and assigns results to a double-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary","base.strided.dmax":"\nbase.strided.dmax( N, x, strideX )\n Computes the maximum value of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N, x, strideX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N, x, strideX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxabssorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxabssorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N, x, strideX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxsorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxsorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted","base.strided.dmean":"\nbase.strided.dmean( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeankbn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeankbn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeankbn2( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeankbn2( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2","base.strided.dmeanli":"\nbase.strided.dmeanli( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanli( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanli( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanlipw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanlipw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanlipw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanlipw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanlipw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw","base.strided.dmeanors":"\nbase.strided.dmeanors( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev( 3, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev( 3, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( 3, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( 3, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar( 3, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar( 3, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( 3, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( 3, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N, x, strideX )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted","base.strided.dmidrange":"\nbase.strided.dmidrange( N, x, strideX )\n Computes the mid-range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange","base.strided.dmin":"\nbase.strided.dmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmin( N, x1, stride )\n -2.0\n\n\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin","base.strided.dminabs":"\nbase.strided.dminabs( N, x, strideX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs","base.strided.dminsorted":"\nbase.strided.dminsorted( N, x, strideX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dminsorted( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dminsorted( 3, x1, 2 )\n -2.0\n\n\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted","base.strided.dmskabs":"\nbase.strided.dmskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N, x, sx, m, sm, y, sy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt","base.strided.dmskceil":"\nbase.strided.dmskceil( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N, x, sx, m, sm, y, sy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor","base.strided.dmskinv":"\nbase.strided.dmskinv( N, x, sx, m, sm, y, sy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\n [ 0.0, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.smskinv\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.smskinv","base.strided.dmskmap":"\nbase.strided.dmskmap( N, x, sx, m, sm, y, sy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n [ 0.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2","base.strided.dmskmax":"\nbase.strided.dmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax","base.strided.dmskmin":"\nbase.strided.dmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin","base.strided.dmskramp":"\nbase.strided.dmskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp","base.strided.dmskrange":"\nbase.strided.dmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc","base.strided.dnanasum":"\nbase.strided.dnanasum( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum( 4, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanasum( 4, x1, 2 )\n 5.0\n\n\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasumors( 4, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanasumors( 4, x1, 2 )\n 5.0\n\n\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasumors.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasumors.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum","base.strided.dnanmax":"\nbase.strided.dnanmax( N, x, strideX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs","base.strided.dnanmean":"\nbase.strided.dnanmean( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmean( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmean( 4, x1,2 )\n ~-0.3333\n\n\nbase.strided.dnanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanors( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpn( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanpn( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmeanpw( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanpw( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanwd( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanwd( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd","base.strided.dnanmin":"\nbase.strided.dnanmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N, x, strideX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange","base.strided.dnannsum":"\nbase.strided.dnannsum( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnansum, base.strided.dsum","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnansum, base.strided.dsum","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw","base.strided.dnanrange":"\nbase.strided.dnanrange( N, x, strideX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanrange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanrange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dnanstdev( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdev( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnanstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnanstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevch( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevch( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevch.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevch.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevpn( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevpn( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevpn.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevpn.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevtk( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevtk( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevtk.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevtk.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevwd( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevwd( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevwd.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevwd.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevyc( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevyc( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevyc.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevyc.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc","base.strided.dnansum":"\nbase.strided.dnansum( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumkbn( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumkbn2( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2","base.strided.dnansumors":"\nbase.strided.dnansumors( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariance( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariance( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariance.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariance.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, NaN, -2.0, 2.0 ] );\n > base.strided.dnanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancech( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariancech( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancech.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancech.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancepn( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariancepn( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancepn.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancepn.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancetk( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariancetk( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancetk.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancetk.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancewd( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariancewd( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancewd.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancewd.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvarianceyc( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvarianceyc( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvarianceyc.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvarianceyc.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc","base.strided.dnrm2":"\nbase.strided.dnrm2( N, x, stride )\n Computes the L2-norm of a double-precision floating-point vector.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2","base.strided.dramp":"\nbase.strided.dramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( x.length, x, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( N, x, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp","base.strided.drange":"\nbase.strided.drange( N, x, strideX )\n Computes the range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.drange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.drange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.drange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.drange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange","base.strided.drev":"\nbase.strided.drev( N, x, strideX )\n Reverses a double-precision floating-point strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.drev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev","base.strided.drsqrt":"\nbase.strided.drsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( x.length, x, 1, y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( N, x, 2, y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.drsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using extended accumulation and returning\n an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N, alpha, x, strideX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw","base.strided.dscal":"\nbase.strided.dscal( N, alpha, x, stride )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy","base.strided.dsdot":"\nbase.strided.dsdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation and result.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > dot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot","base.strided.dsem":"\nbase.strided.dsem( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsem( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsem( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsem.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsem.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsem.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev","base.strided.dsemch":"\nbase.strided.dsemch( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemch( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemch( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch","base.strided.dsempn":"\nbase.strided.dsempn( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsempn( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsempn( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsempn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsempn.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsempn.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn","base.strided.dsemtk":"\nbase.strided.dsemtk( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemtk( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemtk( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk","base.strided.dsemwd":"\nbase.strided.dsemwd( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemwd( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemwd( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd","base.strided.dsemyc":"\nbase.strided.dsemyc( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemyc( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemyc( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc","base.strided.dsmean":"\nbase.strided.dsmean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed.\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmean( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnanmean( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsnanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnanmeanors( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using a two-pass error correction algorithm\n with extended accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanpn( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnanmeanpn( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsnanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using Welford's algorithm with extended\n accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanwd( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnanmeanwd( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N, x, strideX, out, strideOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors","base.strided.dsnansum":"\nbase.strided.dsnansum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation,\n and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh","base.strided.dsorthp":"\nbase.strided.dsorthp( N, order, x, strideX )\n Sorts a double-precision floating-point strided array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsorthp( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.dsorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp","base.strided.dsortins":"\nbase.strided.dsortins( N, order, x, strideX )\n Sorts a double-precision floating-point strided array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsortins( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.dsortins.ndarray( N, order, x, strideX, offsetX )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N, order, x, strideX, offsetX )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins","base.strided.dsortsh":"\nbase.strided.dsortsh( N, order, x, stride )\n Sorts a double-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsortsh( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh","base.strided.dsqrt":"\nbase.strided.dsqrt( N, x, strideX, y, strideY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt( x.length, x, 1, y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt( N, x, 2, y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsqrt( N, x1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt","base.strided.dssum":"\nbase.strided.dssum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssum.ndarray(3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssum.ndarray(3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean","base.strided.dssumors":"\nbase.strided.dssumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and returning\n an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors","base.strided.dssumpw":"\nbase.strided.dssumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw","base.strided.dstdev":"\nbase.strided.dstdev( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdev( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdev( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev","base.strided.dstdevch":"\nbase.strided.dstdevch( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevch( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevch( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevpn( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevpn( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevtk( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevtk( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevwd( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevwd( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc( x.length, 1.0, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevyc( 3, 1.0, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevyc( 3, 1.0, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc","base.strided.dsum":"\nbase.strided.dsum( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2","base.strided.dsumors":"\nbase.strided.dsumors( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors","base.strided.dsumpw":"\nbase.strided.dsumpw( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw","base.strided.dsvariance":"\nbase.strided.dsvariance( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsvariance( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsvariance( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dsvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsvariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsvariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsvariancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsvariancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dsvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn","base.strided.dswap":"\nbase.strided.dswap( N, x, strideX, y, strideY )\n Interchanges two double-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped\n with values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap","base.strided.dtrunc":"\nbase.strided.dtrunc( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc( N, x, 2, y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dtrunc( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype )\n Returns the data type string associated with a strided array data type\n enumeration constant.\n\n Parameters\n ----------\n dtype: integer\n Data type enumeration constant.\n\n Returns\n -------\n out: string|null\n Data type string.\n\n Examples\n --------\n > var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n 'float64'\n\n See Also\n --------\n base.strided.dtypeStr2Enum\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype )\n Returns the enumeration constant associated with a supported strided array\n data type value.\n\n Downstream consumers of this function should *not* rely on specific integer\n values (e.g., `INT8 == 0`). Instead, the function should be used in an\n opaque manner.\n\n Parameters\n ----------\n dtype: any\n Data type value.\n\n Returns\n -------\n out: integer|null\n Enumeration constant.\n\n Examples\n --------\n > var out = base.strided.dtypeResolveEnum( 'float64' )\n \n > out = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n \n\n See Also\n --------\n base.strided.dtypeResolveStr\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype )\n Returns the data type string associated with a supported data type value.\n\n Parameters\n ----------\n dtype: any\n Data type value.\n\n Returns\n -------\n out: string|null\n Data type string.\n\n Examples\n --------\n > var out = base.strided.dtypeResolveStr( 'float64' )\n 'float64'\n > out = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n 'float64'\n\n See Also\n --------\n base.strided.dtypeResolveEnum\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype )\n Returns the enumeration constant associated with a strided array data type\n string.\n\n Downstream consumers of this function should *not* rely on specific integer\n values (e.g., `INT8 == 0`). Instead, the function should be used in an\n opaque manner.\n\n Parameters\n ----------\n dtype: string\n Data type string.\n\n Returns\n -------\n out: integer|null\n Enumeration constant.\n\n Examples\n --------\n > var out = base.strided.dtypeStr2Enum( 'float64' )\n \n\n See Also\n --------\n base.strided.dtypeEnum2Str\n","base.strided.dvariance":"\nbase.strided.dvariance( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariance( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariance( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance","base.strided.dvariancech":"\nbase.strided.dvariancech( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancech( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancech( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancetk( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancetk( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancewd( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancewd( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarianceyc( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarianceyc( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc","base.strided.dvarm":"\nbase.strided.dvarm( N, correction, mean, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm( x.length, 1, 1.0/3.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarm( 3, 1, 1.0/3.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarm( 3, 1, 1.0/3.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarm.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarm.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarm.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N, correction, mean, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn( x.length, 1, 1.0/3.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarmpn( 3, 1, 1.0/3.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarmpn( 3, 1, 1.0/3.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarmpn.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmpn.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmpn.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N, correction, mean, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk( x.length, 1, 1.0/3.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarmtk( 3, 1, 1.0/3.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarmtk( 3, 1, 1.0/3.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarmtk.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmtk.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmtk.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm","base.strided.gapx":"\nbase.strided.gapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 5.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gapx( 4, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, 0.0, 4.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.gapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx","base.strided.gapxsum":"\nbase.strided.gapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw","base.strided.gasum":"\nbase.strided.gasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > s = base.strided.gasum( 3, x, 2 )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.gasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum","base.strided.gasumpw":"\nbase.strided.gasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.gasumpw( 3, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gasumpw( 3, x1, 2 )\n 5.0\n\n\nbase.strided.gasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.gasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.gasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw","base.strided.gaxpy":"\nbase.strided.gaxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy","base.strided.gcopy":"\nbase.strided.gcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy","base.strided.gcusum":"\nbase.strided.gcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2","base.strided.gcusumors":"\nbase.strided.gcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw","base.strided.gdot":"\nbase.strided.gdot( N, x, strideX, y, strideY )\n Computes the dot product of two vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.gdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot","base.strided.gfill":"\nbase.strided.gfill( N, alpha, x, strideX )\n Fills a strided array with a specified scalar constant.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill","base.strided.gfillBy":"\nbase.strided.gfillBy( N, x, strideX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: current array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback return value is used as the fill value for the current array\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy( x.length, x, 1, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy( 3, x, 2, fill )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gfillBy( 3, x1, 2, fill )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfillBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn","base.strided.gnansum":"\nbase.strided.gnansum( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumkbn( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumkbn2( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2","base.strided.gnansumors":"\nbase.strided.gnansumors( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw","base.strided.gnrm2":"\nbase.strided.gnrm2( N, x, stride )\n Computes the L2-norm of a vector.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Stride length.\n\n Returns\n -------\n out: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2","base.strided.grev":"\nbase.strided.grev( N, x, strideX )\n Reverses a strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.grev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.grev.ndarray( N, x, strideX, offsetX )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.grev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N, x, strideX, offsetX )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.grev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev","base.strided.gscal":"\nbase.strided.gscal( N, alpha, x, strideX )\n Multiplies a vector by a scalar constant.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.gscal.ndarray( N, alpha, x, strideX, offsetX )\n Multiplies a vector by a scalar constant using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N, alpha, x, strideX, offsetX )\n Multiplies a vector by a scalar constant using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsort2hp( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsort2ins( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsort2sh( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.gsorthp":"\nbase.strided.gsorthp( N, order, x, strideX )\n Sorts a strided array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsorthp( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.gsorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.gsortins":"\nbase.strided.gsortins( N, order, x, strideX )\n Sorts a strided array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsortins( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.gsortins.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins","base.strided.gsortsh":"\nbase.strided.gsortsh( N, order, x, strideX )\n Sorts a strided array using Shellsort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsortsh( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.gsortsh.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.gsum":"\nbase.strided.gsum( N, x, strideX )\n Computes the sum of strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N, x, strideX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N, x, strideX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2","base.strided.gsumors":"\nbase.strided.gsumors( N, x, strideX )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors","base.strided.gsumpw":"\nbase.strided.gsumpw( N, x, strideX )\n Computes the sum of strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw","base.strided.gswap":"\nbase.strided.gswap( N, x, strideX, y, strideY )\n Interchanges vectors `x` and `y`.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap","base.strided.mapBy":"\nbase.strided.mapBy( N, x, sx, y, sy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary","base.strided.mapBy2":"\nbase.strided.mapBy2( N, x, sx, y, sy, z, sz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\n [ 8.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\n [ -4.0, 0.0 ]\n > z0\n [ 0.0, 0.0, -4.0, 0.0 ]\n\n\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 1.0, 1.0, 2.0, 2.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n [ 0.0, -4.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.binary\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 1.0, 1.0, 2.0, 2.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n [ 0.0, -4.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.binary","base.strided.max":"\nbase.strided.max( N, x, strideX )\n Computes the maximum value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.max( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.max( 3, x1, 2 )\n 2.0\n\n\nbase.strided.max.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.max.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.max.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax","base.strided.maxabs":"\nbase.strided.maxabs( N, x, strideX )\n Computes the maximum absolute value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.maxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.maxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.maxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.maxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.maxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs","base.strided.maxBy":"\nbase.strided.maxBy( N, x, strideX, clbk[, thisArg] )\n Computes the maximum value of a strided array via a callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `NaN`.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy( x.length, x, 1, accessor )\n 8.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy( 3, x, 2, accessor )\n 8.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.maxBy( 3, x1, 2, accessor )\n -4.0\n\n\nbase.strided.maxBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.maxBy.ndarray( 3, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.maxBy.ndarray( 3, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax","base.strided.maxsorted":"\nbase.strided.maxsorted( N, x, strideX )\n Computes the maximum value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.maxsorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.maxsorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.maxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.maxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.maxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N, stride, offset )\n Returns the maximum accessible index based on a set of provided strided\n array parameters.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n idx: integer\n Minimum accessible index.\n\n Examples\n --------\n > var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n 14\n\n","base.strided.mean":"\nbase.strided.mean( N, x, strideX )\n Computes the arithmetic mean of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.mean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.mean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.mean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.mean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.mean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.mean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.smean\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.mean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.mean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.smean","base.strided.meankbn":"\nbase.strided.meankbn( N, x, strideX )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meankbn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meankbn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn","base.strided.meankbn2":"\nbase.strided.meankbn2( N, x, strideX )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meankbn2( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meankbn2( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2","base.strided.meanors":"\nbase.strided.meanors( N, x, strideX )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors","base.strided.meanpn":"\nbase.strided.meanpn( N, x, strideX )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn","base.strided.meanpw":"\nbase.strided.meanpw( N, x, strideX )\n Computes the arithmetic mean of a strided array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw","base.strided.meanwd":"\nbase.strided.meanwd( N, x, strideX )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd","base.strided.mediansorted":"\nbase.strided.mediansorted( N, x, strideX )\n Computes the median value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.mediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.mediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.mediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.mediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.mediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta, dtypes, obj, bool )\n Defines non-enumerable read-only properties which expose strided array\n function meta data.\n\n Parameters\n ----------\n meta: Object\n Function meta data.\n\n meta.nargs: integer\n Total number of arguments (excluding offsets).\n\n meta.nin: integer\n Total number of input arrays.\n\n meta.nout: integer\n Total number of output arrays.\n\n dtypes: ArrayLikeObject\n List of strided array data types.\n\n obj: Object|Function\n Object on which to define properties.\n\n bool: boolean\n Boolean indicating whether the provided object should describe an\n \"ndarray\" function interface.\n\n Returns\n -------\n out: Object|Function\n Object on which properties were defined.\n\n Examples\n --------\n > var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\n > var dt = [ 'float64', 'float64' ];\n > var obj = {};\n > base.strided.metaDataProps( meta, dt, obj, false );\n > obj.nargs\n 7\n > obj.nin\n 1\n > obj.nout\n 1\n > obj.types\n [...]\n\n","base.strided.min":"\nbase.strided.min( N, x, strideX )\n Computes the minimum value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.min( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.min( 3, x1, 2 )\n -2.0\n\n\nbase.strided.min.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.min.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.min.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin","base.strided.minabs":"\nbase.strided.minabs( N, x, strideX )\n Computes the minimum absolute value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.minabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.minabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.minabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.minabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.minabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs","base.strided.minBy":"\nbase.strided.minBy( N, x, strideX, clbk[, thisArg] )\n Computes the minimum value of a strided array via a callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `NaN`.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy( x.length, x, 1, accessor )\n -10.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\n > base.strided.minBy( 3, x, 2, accessor )\n -4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.minBy( 3, x1, 2, accessor )\n -12.0\n\n\nbase.strided.minBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.minBy.ndarray( 3, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.minBy.ndarray( 3, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin","base.strided.minsorted":"\nbase.strided.minsorted( N, x, strideX )\n Computes the minimum value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.minsorted( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.minsorted( 3, x1, 2 )\n -2.0\n\n\nbase.strided.minsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.minsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.minsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N, stride, offset )\n Returns the minimum accessible index based on a set of provided strided\n array parameters.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n idx: integer\n Minimum accessible index.\n\n Examples\n --------\n > var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n 6\n\n See Also\n --------\n base.strided.offsetView\n","base.strided.mskmax":"\nbase.strided.mskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a strided array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.mskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax","base.strided.mskmin":"\nbase.strided.mskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a strided array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, -4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.mskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin","base.strided.mskrange":"\nbase.strided.mskrange( N, x, strideX, mask, strideMask )\n Computes the range of a strided array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.mskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange","base.strided.mskunary":"\nbase.strided.mskunary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array and assigns results to elements in a\n strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > base.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.smskmap, base.strided.unary\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.smskmap, base.strided.unary","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1, dtypes2[, options] )\n Generates a list of masked unary interface signatures from strided array\n data types.\n\n The function returns a strided array having a stride length of three (i.e.,\n every three elements define a masked unary interface signature).\n\n For each signature (i.e., set of three consecutive non-overlapping strided\n array elements), the first element is the input data type, the second\n element is the mask data type, and the last element is the return data type.\n\n All signatures follow type promotion rules.\n\n The mask array data type is always `uint8`.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the output argument.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing masked unary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.mskunaryDtypeSignatures( dt, dt )\n [...]\n\n See Also\n --------\n base.strided.mskunarySignatureCallbacks\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table, signatures )\n Assigns callbacks to masked unary interfaces according to type promotion\n rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing masked unary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\n > var t = {\n ... 'default': base.identity,\n ... 'complex64': base.cidentityf,\n ... 'complex128': base.cidentity\n ... };\n > var out = base.strided.mskunarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.mskunaryDtypeSignatures\n","base.strided.nanmax":"\nbase.strided.nanmax( N, x, strideX )\n Computes the maximum value of a strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanmax( 4, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmax( 4, x1, 2 )\n 2.0\n\n\nbase.strided.nanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmax.ndarray( 4, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmax.ndarray( 4, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanmaxabs( 4, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmaxabs( 4, x1, 2 )\n 2.0\n\n\nbase.strided.nanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmaxabs.ndarray( 4, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmaxabs.ndarray( 4, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N, x, strideX, clbk[, thisArg] )\n Computes the maximum value of strided array via a callback function,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `NaN`.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy( x.length, x, 1, accessor )\n 8.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.nanmaxBy( 3, x, 2, accessor )\n 8.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmaxBy( 3, x1, 2, accessor )\n -4.0\n\n\nbase.strided.nanmaxBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Computes the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanmaxBy.ndarray( 3, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Computes the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanmaxBy.ndarray( 3, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax","base.strided.nanmean":"\nbase.strided.nanmean( N, x, strideX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanmean( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmean( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.nanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.snanmean\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.snanmean","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N, x, strideX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmeanors( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.nanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N, x, strideX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanmeanpn( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmeanpn( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.nanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanmeanwd( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmeanwd( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.nanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd","base.strided.nanmin":"\nbase.strided.nanmin( N, x, strideX )\n Computes the minimum value of a strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanmin( 4, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmin( 4, x1, 2 )\n -2.0\n\n\nbase.strided.nanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmin.ndarray( 4, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmin.ndarray( 4, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin","base.strided.nanminabs":"\nbase.strided.nanminabs( N, x, strideX )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanminabs( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanminabs( 4, x1, 2 )\n 1.0\n\n\nbase.strided.nanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanminabs.ndarray( 4, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanminabs.ndarray( 4, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs","base.strided.nanminBy":"\nbase.strided.nanminBy( N, x, strideX, clbk[, thisArg] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `NaN`.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy( x.length, x, 1, accessor )\n -10.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\n > base.strided.nanminBy( 4, x, 2, accessor )\n -4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanminBy( 3, x1, 2, accessor )\n -12.0\n\n\nbase.strided.nanminBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanminBy.ndarray( 3, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanminBy.ndarray( 3, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a strided array according to a mask and\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskmax( 4, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmskmax( 4, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0, NaN, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmax.ndarray( 4, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0, NaN, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmax.ndarray( 4, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a strided array according to a mask and\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskmin( 4, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmskmin( 4, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0, NaN, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmin.ndarray( 4, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0, NaN, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmin.ndarray( 4, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a strided array according to a mask and ignoring `NaN`\n values.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskrange( 5, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskrange.ndarray( 5, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskrange.ndarray( 5, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange","base.strided.nanrange":"\nbase.strided.nanrange( N, x, strideX )\n Computes the range of a strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanrange( 4, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanrange( 4, x1, 2 )\n 4.0\n\n\nbase.strided.nanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanrange.ndarray( 4, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanrange.ndarray( 4, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N, x, strideX, clbk[, thisArg] )\n Computes the range of a strided array via a callback function, ignoring\n `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy( x.length, x, 1, accessor )\n 18.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\n > base.strided.nanrangeBy( 4, x, 2, accessor )\n 14.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanrangeBy( 3, x1, 2, accessor )\n 8.0\n\n\nbase.strided.nanrangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanrangeBy.ndarray( 3, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanrangeBy.ndarray( 3, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange","base.strided.nanstdev":"\nbase.strided.nanstdev( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdev( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0,NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdev( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdev.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdev.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevch( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevch( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevch.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevch.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevpn( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevpn( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevpn.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevpn.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevtk( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevtk( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevtk.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevtk.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevwd( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevwd( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevwd.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevwd.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevyc( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevyc( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevyc.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevyc.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc","base.strided.nanvariance":"\nbase.strided.nanvariance( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanvariance( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariance( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariance.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariance.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancech( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariancech( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancech.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancech.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.nanvariancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.nanvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.nanvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanvariancetk( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariancetk( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancetk.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancetk.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanvariancewd( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariancewd( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancewd.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancewd.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc( 4, 1.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.nanvarianceyc( 3, 1.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvarianceyc( 3, 1.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc.ndarray( 4, 1.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.nanvarianceyc.ndarray( 3, 1.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc.ndarray( 4, 1.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.nanvarianceyc.ndarray( 3, 1.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc","base.strided.nullary":"\nbase.strided.nullary( arrays, shape, strides, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n output array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary( [ x ], shape, strides, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting index (i.e., index offset) for\n the strided output array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1 ];\n > var offsets = [ 0 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting index (i.e., index offset) for\n the strided output array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1 ];\n > var offsets = [ 0 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.offsetView":"\nbase.strided.offsetView( x, offset )\n Returns a typed array view having the same data type as a provided input\n typed array and starting at a specified index offset.\n\n Parameters\n ----------\n x: TypedArray\n Input array.\n\n offset: integer\n Starting index of the view relative to the input array.\n\n Returns\n -------\n out: TypedArray\n Typed array view having the same data type as the input array.\n\n Examples\n --------\n > var x = new Float64Array( 10 );\n > var out = base.strided.offsetView( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.minViewBufferIndex\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays, shape, strides, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.quinary":"\nbase.strided.quinary( arrays, shape, strides, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary","base.strided.range":"\nbase.strided.range( N, x, strideX )\n Computes the range of a strided array.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a\n typed array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.range( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.range( 3, x1, 2 )\n 4.0\n\n\nbase.strided.range.ndarray( N, x, strideX, offsetX )\n Computes the range of a strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.range.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N, x, strideX, offsetX )\n Computes the range of a strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.range.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange","base.strided.rangeBy":"\nbase.strided.rangeBy( N, x, strideX, clbk[, thisArg] )\n Computes the range of a strided array via a callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy( x.length, x, 1, accessor )\n 18.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy( 3, x, 2, accessor )\n 12.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.rangeBy( 3, x1, 2, accessor )\n 8.0\n\n\nbase.strided.rangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.rangeBy.ndarray( 3, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.rangeBy.ndarray( 3, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x, offset )\n Returns a real-valued floating-point array view of a complex-valued\n floating-point array having the same precision.\n\n Parameters\n ----------\n x: Complex128Array|Complex64Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the input array.\n\n Returns\n -------\n out: Float64Array|Float32Array\n Real-valued floating-point array view.\n\n Examples\n --------\n > var x = new Complex128Array( 10 );\n > var out = base.strided.reinterpretComplex( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n > x = new Complex64Array( 10 );\n > out = base.strided.reinterpretComplex( x, 0 )\n \n > bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex128, base.strided.reinterpretComplex64\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x, offset )\n Returns a Float32Array view of a Complex64Array.\n\n Parameters\n ----------\n x: Complex64Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the Complex64Array.\n\n Returns\n -------\n out: Float32Array\n Float32Array view.\n\n Examples\n --------\n > var x = new Complex64Array( 10 );\n > var out = base.strided.reinterpretComplex64( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex, base.strided.reinterpretComplex128\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x, offset )\n Returns a Float64Array view of a Complex128Array.\n\n Parameters\n ----------\n x: Complex128Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the Complex128Array.\n\n Returns\n -------\n out: Float64Array\n Float64Array view.\n\n Examples\n --------\n > var x = new Complex128Array( 10 );\n > var out = base.strided.reinterpretComplex128( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex, base.strided.reinterpretComplex64\n","base.strided.sabs":"\nbase.strided.sabs( N, x, strideX, y, strideY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs( N, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2","base.strided.sabs2":"\nbase.strided.sabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs","base.strided.sapx":"\nbase.strided.sapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.sapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx","base.strided.sapxsum":"\nbase.strided.sapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw","base.strided.sasum":"\nbase.strided.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and stride parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.sasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.sasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum","base.strided.sasumpw":"\nbase.strided.sasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sasumpw( 3, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sasumpw( 3, x1, 2 )\n 5.0\n\n\nbase.strided.sasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw","base.strided.saxpy":"\nbase.strided.saxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.saxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy","base.strided.scbrt":"\nbase.strided.scbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt","base.strided.sceil":"\nbase.strided.sceil( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil( x.length, x, 1, y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil( N, x, 2, y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sceil( N, x1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc","base.strided.scopy":"\nbase.strided.scopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap","base.strided.scumax":"\nbase.strided.scumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumaxabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs","base.strided.scumin":"\nbase.strided.scumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin( 3, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumin( 3, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax","base.strided.scuminabs":"\nbase.strided.scuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin","base.strided.scusum":"\nbase.strided.scusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn","base.strided.scusumors":"\nbase.strided.scusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum","base.strided.scusumpw":"\nbase.strided.scusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N, x, strideX, y, strideY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sdeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad","base.strided.sdot":"\nbase.strided.sdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sdsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsdot":"\nbase.strided.sdsdot( N, scalar, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns the provided scalar constant.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot","base.strided.sdsmean":"\nbase.strided.sdsmean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsmean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsmean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.sdsmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.sdsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.sdsnanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsnanmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.sdsnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.sdsnanmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.sdsnanmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignore `NaN` values and using extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.sdsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.sdsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw","base.strided.sdssum":"\nbase.strided.sdssum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.sdssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.sdssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw","base.strided.sfill":"\nbase.strided.sfill( N, alpha, x, strideX )\n Fills a single-precision floating-point strided array with a specified\n scalar value.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.gfill\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.gfill","base.strided.sfloor":"\nbase.strided.sfloor( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor( x.length, x, 1, y, 1 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor( N, x, 2, y, -1 )\n [ 3.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sfloor( N, x1, -2, y1, 1 )\n [ 4.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc","base.strided.sinv":"\nbase.strided.sinv( N, x, strideX, y, strideY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv( x.length, x, 1, y, 1 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv( N, x, 2, y, -1 )\n [ 0.5, ~-0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sinv( N, x1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, strided.inv\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, strided.inv","base.strided.smap":"\nbase.strided.smap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap( x.length, x, 1, y, 1, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap( 2, x, 2, y, -1, base.identityf )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap( 2, x1, -2, y1, 1, base.identityf )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary","base.strided.smap2":"\nbase.strided.smap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary","base.strided.smax":"\nbase.strided.smax( N, x, strideX )\n Computes the maximum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax","base.strided.smaxabs":"\nbase.strided.smaxabs( N, x, strideX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N, x, strideX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxabssorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxabssorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N, x, strideX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxsorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxsorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted","base.strided.smean":"\nbase.strided.smean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean","base.strided.smeankbn":"\nbase.strided.smeankbn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeankbn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeankbn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeankbn2( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeankbn2( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean","base.strided.smeanli":"\nbase.strided.smeanli( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanli( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanli( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanlipw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanlipw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanlipw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanlipw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanlipw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli","base.strided.smeanors":"\nbase.strided.smeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors","base.strided.smeanpn":"\nbase.strided.smeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn","base.strided.smeanpw":"\nbase.strided.smeanpw( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean","base.strided.smeanwd":"\nbase.strided.smeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd","base.strided.smediansorted":"\nbase.strided.smediansorted( N, x, strideX )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean","base.strided.smidrange":"\nbase.strided.smidrange( N, x, strideX )\n Computes the mid-range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange","base.strided.smin":"\nbase.strided.smin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin","base.strided.sminabs":"\nbase.strided.sminabs( N, x, strideX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs","base.strided.sminsorted":"\nbase.strided.sminsorted( N, x, strideX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sminsorted( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sminsorted( 3, x1, 2 )\n -2.0\n\n\nbase.strided.sminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin","base.strided.smskabs":"\nbase.strided.smskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2","base.strided.smskabs2":"\nbase.strided.smskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N, x, sx, m, sm, y, sy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt","base.strided.smskceil":"\nbase.strided.smskceil( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N, x, sx, m, sm, y, sy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.dmskdeg2rad, base.strided.sdeg2rad\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.dmskdeg2rad, base.strided.sdeg2rad","base.strided.smskfloor":"\nbase.strided.smskfloor( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc","base.strided.smskinv":"\nbase.strided.smskinv( N, x, sx, m, sm, y, sy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv( 2, x, 2, m, 2, y, -1 )\n [ 0.0, ~-0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.dmskinv\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.dmskinv","base.strided.smskmap":"\nbase.strided.smskmap( N, x, sx, m, sm, y, sy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n [ 0.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2","base.strided.smskmap2":"\nbase.strided.smskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap","base.strided.smskmax":"\nbase.strided.smskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax","base.strided.smskmin":"\nbase.strided.smskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin","base.strided.smskramp":"\nbase.strided.smskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp","base.strided.smskrange":"\nbase.strided.smskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc","base.strided.snanmax":"\nbase.strided.snanmax( N, x, strideX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs","base.strided.snanmean":"\nbase.strided.snanmean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmean( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmean( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.snanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmeanors( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.snanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanpn( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmeanpn( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.snanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanwd( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmeanwd( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.snanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean","base.strided.snanmin":"\nbase.strided.snanmin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax","base.strided.snanminabs":"\nbase.strided.snanminabs( N, x, strideX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride lengt for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride lengt for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride lengt for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride lengt for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin","base.strided.snanrange":"\nbase.strided.snanrange( N, x, strideX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanrange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanrange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange","base.strided.snanstdev":"\nbase.strided.snanstdev( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc","base.strided.snansum":"\nbase.strided.snansum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansumkbn( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn2( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansumkbn2( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2","base.strided.snansumors":"\nbase.strided.snansumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var stride = 2;\n > base.strided.snansumors( 4, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.snansumors( 4, x1, stride )\n -1.0\n\n\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors","base.strided.snansumpw":"\nbase.strided.snansumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw","base.strided.snanvariance":"\nbase.strided.snanvariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariance( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancech( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancepn( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancetk( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancewd( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvarianceyc( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc","base.strided.snrm2":"\nbase.strided.snrm2( N, x, stride )\n Computes the L2-norm of a single-precision floating-point vector.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.snrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2","base.strided.sramp":"\nbase.strided.sramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( N, x, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp","base.strided.srange":"\nbase.strided.srange( N, x, strideX )\n Computes the range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.srange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.srange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.srange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range","base.strided.srev":"\nbase.strided.srev( N, x, strideX )\n Reverses a single-precision floating-point strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.srev.ndarray( N, x, strideX, offsetX )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N, x, strideX, offsetX )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev","base.strided.srsqrt":"\nbase.strided.srsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( x.length, x, 1, y, 1 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( N, x, 2, y, -1 )\n [ ~0.333, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.srsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt","base.strided.sscal":"\nbase.strided.sscal( N, alpha, x, stride )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves the strided arrays\n are unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.ssorthp":"\nbase.strided.ssorthp( N, order, x, strideX )\n Sorts a single-precision floating-point strided array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns the strided array\n unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssorthp( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.ssortins":"\nbase.strided.ssortins( N, order, x, stride )\n Sorts a single-precision floating-point strided array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssortins( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins","base.strided.ssortsh":"\nbase.strided.ssortsh( N, order, x, stride )\n Sorts a single-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssortsh( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.ssqrt":"\nbase.strided.ssqrt( N, x, strideX, y, strideY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt( x.length, x, 1, y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt( N, x, 2, y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssqrt( N, x1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt","base.strided.sstdev":"\nbase.strided.sstdev( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdev( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdev( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance","base.strided.sstdevch":"\nbase.strided.sstdevch( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevch( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevch( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevpn( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevpn( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevtk( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevtk( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevwd( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevwd( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevyc( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevyc( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevyc.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevyc.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc","base.strided.ssum":"\nbase.strided.ssum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumors":"\nbase.strided.ssumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw","base.strided.ssumpw":"\nbase.strided.ssumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors","base.strided.sswap":"\nbase.strided.sswap( N, x, strideX, y, strideY )\n Interchanges two single-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped\n with values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.sswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap","base.strided.stdev":"\nbase.strided.stdev( N, correction, x, strideX )\n Computes the standard deviation of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdev( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdev( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance","base.strided.stdevch":"\nbase.strided.stdevch( N, correction, x, strideX )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevch( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevch( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech","base.strided.stdevpn":"\nbase.strided.stdevpn( N, correction, x, strideX )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevpn( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevpn( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn","base.strided.stdevtk":"\nbase.strided.stdevtk( N, correction, x, strideX )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevtk( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevtk( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk","base.strided.stdevwd":"\nbase.strided.stdevwd( N, correction, x, strideX )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevwd( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevwd( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd","base.strided.stdevyc":"\nbase.strided.stdevyc( N, correction, x, strideX )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevyc( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevyc( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevyc.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevyc.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc","base.strided.strunc":"\nbase.strided.strunc( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc( N, x, 2, y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.strunc( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc","base.strided.svariance":"\nbase.strided.svariance( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariance( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariance( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance","base.strided.svariancech":"\nbase.strided.svariancech( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancech( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancech( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech","base.strided.svariancepn":"\nbase.strided.svariancepn( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn","base.strided.svariancetk":"\nbase.strided.svariancetk( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancetk( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancetk( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk","base.strided.svariancewd":"\nbase.strided.svariancewd( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancewd( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancewd( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svarianceyc( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svarianceyc( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.ternary":"\nbase.strided.ternary( arrays, shape, strides, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary( [ x, y, z, w ], shape, strides, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary","base.strided.unary":"\nbase.strided.unary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > base.strided.unary( [ x, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays, shape, strides, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The shape and stride parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using shape and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n > y\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > sh = [ 2 ];\n > st = [ -2, 1 ];\n > base.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\n > y1\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > var o = [ 0, 0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > o = [ 1, y.length-1 ];\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.unary\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > var o = [ 0, 0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > o = [ 1, y.length-1 ];\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.unary","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1, dtypes2[, options] )\n Generates a list of unary interface signatures from strided array data\n types.\n\n The function returns a strided array having a stride length of two (i.e.,\n every two elements define a unary interface signature).\n\n For each signature (i.e., set of two consecutive non-overlapping strided\n array elements), the first element is the input data type and the second\n element is the return data type.\n\n All signatures follow type promotion rules.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the output argument.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing unary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.unaryDtypeSignatures( dt, dt )\n [...]\n\n See Also\n --------\n base.strided.unarySignatureCallbacks\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table, signatures )\n Assigns callbacks to unary interfaces according to type promotion rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing unary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.unaryDtypeSignatures( dt, dt );\n > var t = {\n ... 'default': base.identity,\n ... 'complex64': base.cidentityf,\n ... 'complex128': base.cidentity\n ... };\n > var out = base.strided.unarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.unaryDtypeSignatures\n","base.strided.variance":"\nbase.strided.variance( N, correction, x, strideX )\n Computes the variance of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variance( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variance( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance","base.strided.variancech":"\nbase.strided.variancech( N, correction, x, strideX )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variancech( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variancech( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance","base.strided.variancepn":"\nbase.strided.variancepn( N, correction, x, strideX )\n Computes the variance of a strided array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance","base.strided.variancetk":"\nbase.strided.variancetk( N, correction, x, strideX )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variancetk( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variancetk( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance","base.strided.variancewd":"\nbase.strided.variancewd( N, correction, x, strideX )\n Computes the variance of a strided array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variancewd( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variancewd( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance","base.strided.varianceyc":"\nbase.strided.varianceyc( N, correction, x, strideX )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc( x.length, 1.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.varianceyc( 3, 1.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.varianceyc( 3, 1.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.varianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.varianceyc.ndarray( 3, 1.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.varianceyc.ndarray( 3, 1.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance","base.strided.zmap":"\nbase.strided.zmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\n > var v = y.get( 0 )\n [ 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > y = new Complex128Array( x.length );\n > base.strided.zmap( 2, x, 2, y, -1, base.cidentity );\n > v = y.get( 0 )\n [ 5.0, 6.0 ]\n\n // Using view offsets:\n > var x0 = new Complex128Array( xbuf );\n > var y0 = new Complex128Array( x0.length );\n > var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\n > v = y1.get( 0 )\n [ 7.0, 8.0 ]\n\n\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n > var v = y.get( 0 )\n [ 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Complex128Array( xbuf );\n > y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n > v = y.get( y.length-1 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.cmap, base.strided.unary\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n > var v = y.get( 0 )\n [ 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Complex128Array( xbuf );\n > y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n > v = y.get( y.length-1 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.cmap, base.strided.unary","base.str2multislice":"\nbase.str2multislice( str )\n Parses a string-serialized MultiSlice object.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n s: MultiSlice|null\n MultiSlice instance (or null).\n\n Examples\n --------\n > var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\n > s.data\n [ null, null, null ]\n > s = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\n > s.data\n [ 10, , null ]\n\n See Also\n --------\n base.str2slice\n","base.str2slice":"\nbase.str2slice( str )\n Parses a string-serialized Slice object.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n s: Slice|null\n Slice instance (or null).\n\n Examples\n --------\n > var s = new base.str2slice( 'Slice(1,10,1)' );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new base.str2slice( 'Slice(2,5,2)' );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n base.str2multislice\n","base.sub":"\nbase.sub( x, y )\n Subtracts two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.sub( -1.0, 5.0 )\n -6.0\n > v = base.sub( 2.0, 5.0 )\n -3.0\n > v = base.sub( 0.0, 5.0 )\n -5.0\n > v = base.sub( -0.0, 0.0 )\n -0.0\n > v = base.sub( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.div, base.mul\n","base.subf":"\nbase.subf( x, y )\n Subtracts two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.subf( -1.0, 5.0 )\n -6.0\n > v = base.subf( 2.0, 5.0 )\n -3.0\n > v = base.subf( 0.0, 5.0 )\n -5.0\n > v = base.subf( -0.0, 0.0 )\n -0.0\n > v = base.subf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.divf, base.mulf, base.sub\n","base.sumSeries":"\nbase.sumSeries( generator[, options] )\n Sum the elements of the series given by the supplied function.\n\n Parameters\n ----------\n generator: Function\n Series function.\n\n options: Object (optional)\n Options.\n\n options.maxTerms: integer (optional)\n Maximum number of terms to be added. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n the current term times the tolerance. Default: `2.22e-16`.\n\n options.initialValue: number (optional)\n Initial value of the resulting sum. Default: `0`.\n\n Returns\n -------\n out: number\n Sum of series terms.\n\n Examples\n --------\n // Using an ES6 generator function:\n > function* geometricSeriesGenerator( x ) {\n ... var exponent = 0;\n ... while ( true ) {\n ... yield Math.pow( x, exponent );\n ... exponent += 1;\n ... }\n ... };\n > var gen = geometricSeriesGenerator( 0.9 );\n > var out = base.sumSeries( gen )\n 10\n\n // Using a closure:\n > function geometricSeriesClosure( x ) {\n ... var exponent = -1;\n ... return function() {\n ... exponent += 1;\n ... return Math.pow( x, exponent );\n ... };\n ... };\n > gen = geometricSeriesClosure( 0.9 );\n > out = base.sumSeries( gen )\n 10\n\n // Setting an initial value for the sum:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n 3\n // Changing the maximum number of terms to be summed:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n ~1.998 // Infinite sum is 2\n\n // Adjusting the used tolerance:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n ~1.998\n\n","base.tan":"\nbase.tan( x )\n Computes the tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tan( 0.0 )\n ~0.0\n > y = base.tan( -PI/4.0 )\n ~-1.0\n > y = base.tan( PI/4.0 )\n ~1.0\n > y = base.tan( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sin\n","base.tand":"\nbase.tand( x )\n Computes the tangent of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tand( 0.0 )\n 0.0\n > y = base.tand( 90.0 )\n Infinity\n > y = base.tand( 60.0 )\n ~1.73\n > y = base.tand( NaN )\n NaN\n\n See Also\n --------\n base.tan, base.cosd\n","base.tanh":"\nbase.tanh( x )\n Computes the hyperbolic tangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic tangent.\n\n Examples\n --------\n > var y = base.tanh( 0.0 )\n 0.0\n > var y = base.tanh( -0.0 )\n -0.0\n > y = base.tanh( 2.0 )\n ~0.964\n > y = base.tanh( -2.0 )\n ~-0.964\n > y = base.tanh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sinh, base.tan\n","base.toBinaryString":"\nbase.toBinaryString( x )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bstr: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryString( 4.0 )\n '0100000000010000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PI )\n '0100000000001001001000011111101101010100010001000010110100011000'\n > str = base.toBinaryString( -1.0e308 )\n '1111111111100001110011001111001110000101111010111100100010100000'\n > str = base.toBinaryString( -3.14e-320 )\n '1000000000000000000000000000000000000000000000000001100011010011'\n > str = base.toBinaryString( 5.0e-324 )\n '0000000000000000000000000000000000000000000000000000000000000001'\n > str = base.toBinaryString( 0.0 )\n '0000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( -0.0 )\n '1000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NaN )\n '0111111111111000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PINF )\n '0111111111110000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NINF )\n '1111111111110000000000000000000000000000000000000000000000000000'\n\n See Also\n --------\n base.fromBinaryString, base.toBinaryStringf\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\n '01000000100000000000000000000000'\n > str = base.toBinaryStringf( base.float64ToFloat32( PI ) )\n '01000000010010010000111111011011'\n > str = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\n '11111110100101100111011010011001'\n > str = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\n '10000000001000100011000100001011'\n > str = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringf( 0.0 )\n '00000000000000000000000000000000'\n > str = base.toBinaryStringf( -0.0 )\n '10000000000000000000000000000000'\n > str = base.toBinaryStringf( NaN )\n '01111111110000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_PINF )\n '01111111100000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_NINF )\n '11111111100000000000000000000000'\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 8-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 8-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned 8-bit\n integers. Accordingly, care should be taken to ensure that only nonnegative\n integer values less than `256` (`2^8`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint8Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint8( a[ 0 ] )\n '00000001'\n > str = base.toBinaryStringUint8( a[ 1 ] )\n '00000100'\n > str = base.toBinaryStringUint8( a[ 2 ] )\n '00001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 16-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 16-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 16-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `65536` (`2^16`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint16Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint16( a[ 0 ] )\n '0000000000000001'\n > str = base.toBinaryStringUint16( a[ 1 ] )\n '0000000000000100'\n > str = base.toBinaryStringUint16( a[ 2 ] )\n '0000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 32-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 32-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 32-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint32Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint32( a[ 0 ] )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringUint32( a[ 1 ] )\n '00000000000000000000000000000100'\n > str = base.toBinaryStringUint32( a[ 2 ] )\n '00000000000000000000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toWordf":"\nbase.toWordf( x )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var f32 = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n > var w = base.toWordf( f32 )\n 1068180177\n\n See Also\n --------\n base.fromWordf, base.toWords\n","base.toWords":"\nbase.toWords( x )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array\n Higher and lower order words.\n\n Examples\n --------\n > var w = base.toWords( 3.14e201 )\n [ 1774486211, 2479577218 ]\n\n\nbase.toWords.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var out = new Uint32Array( 2 );\n > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.toWords.assign":"\nbase.toWords.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var out = new Uint32Array( 2 );\n > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.transpose":"\nbase.transpose( x, writable )\n Transposes a matrix (or a stack of matrices).\n\n The returned ndarray is a *view* of the input ndarray. Accordingly, writing\n to the original ndarray will mutate the returned ndarray and vice versa.\n\n The `writable` parameter only applies to ndarray constructors supporting\n read-only instances.\n\n If provided an ndarray with fewer than two dimensions, the function raises\n an exception.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n writable: boolean\n Boolean indicating whether the returned ndarray should be writable.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ [ 1, 2, 3 ], [ 4, 5, 6 ] ]\n > var y = base.transpose( x, false )\n [ [ 1, 4 ], [ 2, 5 ], [ 3, 6 ] ]\n\n See Also\n --------\n ndarray\n","base.tribonacci":"\nbase.tribonacci( n )\n Computes the nth Tribonacci number.\n\n Tribonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2} + F_{n-3}\n\n with seed values F_0 = 0, F_1 = 0, and F_2 = 1.\n\n If `n` is greater than `63`, the function returns `NaN`, as larger\n Tribonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Tribonacci number.\n\n Examples\n --------\n > var y = base.tribonacci( 0 )\n 0\n > y = base.tribonacci( 1 )\n 0\n > y = base.tribonacci( 2 )\n 1\n > y = base.tribonacci( 3 )\n 1\n > y = base.tribonacci( 4 )\n 2\n > y = base.tribonacci( 64 )\n NaN\n > y = base.tribonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.trigamma":"\nbase.trigamma( x )\n Evaluates the trigamma function.\n\n If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n If provided `NaN`, the `function` returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.trigamma( -2.5 )\n ~9.539\n > y = base.trigamma( 1.0 )\n ~1.645\n > y = base.trigamma( 10.0 )\n ~0.105\n > y = base.trigamma( NaN )\n NaN\n > y = base.trigamma( -1.0 )\n NaN\n\n See Also\n --------\n base.digamma, base.gamma\n","base.trim":"\nbase.trim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n See Also\n --------\n base.leftTrim, base.rightTrim\n","base.trunc":"\nbase.trunc( x )\n Rounds a double-precision floating-point number toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc( 3.14 )\n 3.0\n > y = base.trunc( -4.2 )\n -4.0\n > y = base.trunc( -4.6 )\n -4.0\n > y = base.trunc( 9.5 )\n 9.0\n > y = base.trunc( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.round\n","base.trunc2":"\nbase.trunc2( x )\n Rounds a numeric value to the nearest power of two toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc2( 3.14 )\n 2.0\n > y = base.trunc2( -4.2 )\n -4.0\n > y = base.trunc2( -4.6 )\n -4.0\n > y = base.trunc2( 9.5 )\n 8.0\n > y = base.trunc2( 13.0 )\n 8.0\n > y = base.trunc2( -13.0 )\n -8.0\n > y = base.trunc2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round2, base.trunc, base.trunc10\n","base.trunc10":"\nbase.trunc10( x )\n Rounds a numeric value to the nearest power of ten toward zero.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc10( 3.14 )\n 1.0\n > y = base.trunc10( -4.2 )\n -1.0\n > y = base.trunc10( -4.6 )\n -1.0\n > y = base.trunc10( 9.5 )\n 1.0\n > y = base.trunc10( 13.0 )\n 10.0\n > y = base.trunc10( -13.0 )\n -10.0\n > y = base.trunc10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round10, base.trunc, base.trunc2\n","base.truncateMiddle":"\nbase.truncateMiddle( str, len, seq )\n Truncates the middle UTF-16 code units of a string to return a string\n having a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n seq: string\n Custom replacement sequence.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.truncateMiddle( str, 5, '...' )\n 'b...p'\n > out = base.truncateMiddle( str, 5, '|' )\n 'be|op'\n","base.truncb":"\nbase.truncb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.truncb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward zero:\n > y = base.truncb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.roundb, base.trunc, base.truncn\n","base.truncf":"\nbase.truncf( x )\n Rounds a single-precision floating-point number toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncf( 3.14 )\n 3.0\n > y = base.truncf( -4.2 )\n -4.0\n > y = base.truncf( -4.6 )\n -4.0\n > y = base.truncf( 9.5 )\n 9.0\n > y = base.truncf( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceilf, base.floorf, base.trunc\n","base.truncn":"\nbase.truncn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round behavior:\n > y = base.truncn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.truncn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.roundn, base.trunc, base.truncb\n","base.truncsd":"\nbase.truncsd( x, n, b )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncsd( 3.14159, 5, 10 )\n 3.1415\n > y = base.truncsd( 3.14159, 1, 10 )\n 3.0\n > y = base.truncsd( 12368.0, 2, 10 )\n 12000.0\n > y = base.truncsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.roundsd, base.trunc\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\n -1\n > y = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n 3\n\n","base.umul":"\nbase.umul( x, y )\n Multiples two unsigned 32-bit integers.\n\n The function performs C-like multiplication of two unsigned 32-bit integers,\n including wraparound semantics.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n y: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.umul( 10>>>0, 4>>>0 )\n 40\n\n See Also\n --------\n base.imul\n","base.umuldw":"\nbase.umuldw( a, b )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: Array\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.umuldw( 1, 10 )\n [ 0, 10 ]\n\n\nbase.umuldw.assign( a, b, out, stride, offset )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imuldw, base.umul\n","base.umuldw.assign":"\nbase.umuldw.assign( a, b, out, stride, offset )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imuldw, base.umul","base.uncapitalize":"\nbase.uncapitalize( str )\n Lowercases the first character of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = base.uncapitalize( 'Beep' )\n 'beep'\n > out = base.uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n base.capitalize\n","base.uppercase":"\nbase.uppercase( str )\n Converts a string to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = base.uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n base.lowercase\n","base.vercos":"\nbase.vercos( x )\n Computes the versed cosine.\n\n The versed cosine is defined as `1 + cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed cosine.\n\n Examples\n --------\n > var y = base.vercos( 3.14 )\n ~0.0\n > y = base.vercos( -4.2 )\n ~0.5097\n > y = base.vercos( -4.6 )\n ~0.8878\n > y = base.vercos( 9.5 )\n ~0.0028\n > y = base.vercos( -0.0 )\n 2.0\n\n See Also\n --------\n base.cos, base.versin\n","base.versin":"\nbase.versin( x )\n Computes the versed sine.\n\n The versed sine is defined as `1 - cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed sine.\n\n Examples\n --------\n > var y = base.versin( 3.14 )\n ~2.0\n > y = base.versin( -4.2 )\n ~1.490\n > y = base.versin( -4.6 )\n ~1.112\n > y = base.versin( 9.5 )\n ~1.997\n > y = base.versin( -0.0 )\n 0.0\n\n See Also\n --------\n base.cos, base.sin, base.vercos\n","base.wrap":"\nbase.wrap( v, min, max )\n Wraps a value to the half-open interval `[min,max)`.\n\n The function does not distinguish between positive and negative zero. Where\n appropriate, the function returns positive zero.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to wrap.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Wrapped value.\n\n Examples\n --------\n > var y = base.wrap( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.wrap( -3.14, 0.0, 5.0 )\n ~1.86\n > y = base.wrap( 3.14, 0.0, 3.0 )\n ~0.14\n > y = base.wrap( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.wrap( 0.0, -3.14, -0.0 )\n -3.14\n > y = base.wrap( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.xlog1py":"\nbase.xlog1py( x, y )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlog1py( 3.0, 2.0 )\n ~3.296\n > out = base.xlog1py( 1.5, 5.9 )\n ~2.897\n > out = base.xlog1py( 0.9, 1.0 )\n ~0.624\n > out = base.xlog1py( 1.0, 0.0 )\n 0.0\n > out = base.xlog1py( 0.0, -2.0 )\n 0.0\n > out = base.xlog1py( 1.5, NaN )\n NaN\n > out = base.xlog1py( 0.0, NaN )\n NaN\n > out = base.xlog1py( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.log1p, base.xlogy\n","base.xlogy":"\nbase.xlogy( x, y )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlogy( 3.0, 2.0 )\n ~2.079\n > out = base.xlogy( 1.5, 5.9 )\n ~2.662\n > out = base.xlogy( 0.9, 1.0 )\n 0.0\n > out = base.xlogy( 0.0, -2.0 )\n 0.0\n > out = base.xlogy( 1.5, NaN )\n NaN\n > out = base.xlogy( 0.0, NaN )\n NaN\n > out = base.xlogy( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.ln, base.xlog1py\n","base.zeta":"\nbase.zeta( s )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.zeta( 1.1 )\n ~10.584\n > y = base.zeta( -4.0 )\n 0.0\n > y = base.zeta( 70.0 )\n 1.0\n > y = base.zeta( 0.5 )\n ~-1.46\n > y = base.zeta( NaN )\n NaN\n\n // Evaluate at a pole:\n > y = base.zeta( 1.0 )\n NaN\n\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and other characteristics.\n\n Each array element has the following eleven fields:\n\n - education: number of years of education.\n - south: indicator variable for southern region (1 if a person lives in the\n South; 0 if a person does not live in the South).\n - gender: gender of the person.\n - experience: number of years of work experience.\n - union: indicator variable for union membership (1 if union member; 0 if\n not a union member).\n - wage: log-transformed wage (in dollars per hour).\n - age: age (in years).\n - race: ethnicity/race (white, hispanic, and other).\n - occupation: occupational category (management, sales, clerical, service,\n professional, and other).\n - sector: sector (other, manufacturing, or construction).\n - married: marital status (0 if unmarried; 1 if married).\n\n Based on residual plots, wages were log-transformed to stabilize the\n variance.\n\n Returns\n -------\n out: Array\n CPS data.\n\n Examples\n --------\n > var data = BERNDT_CPS_WAGES_1985()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n Longman Publishing Co.\n\n","bifurcate":"\nbifurcate( collection, [options,] filter )\n Splits values into two groups.\n\n If an element in `filter` is truthy, then the corresponding element in the\n input collection belongs to the first group; otherwise, the collection\n element belongs to the second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n filter: Array|TypedArray|Object\n A collection indicating which group an element in the input collection\n belongs to. If an element in `filter` is truthy, the corresponding\n element in `collection` belongs to the first group; otherwise, the\n collection element belongs to the second group. If provided an object,\n the object must be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var f = [ true, true, false, true ];\n > var out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n > f = [ 1, 1, 0, 1 ];\n > out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > f = [ true, true, false, true ];\n > var opts = { 'returns': 'indices' };\n > out = bifurcate( collection, opts, f )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = bifurcate( collection, opts, f )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n See Also\n --------\n bifurcateBy, bifurcateOwn, group\n","bifurcateBy":"\nbifurcateBy( collection, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If a predicate function returns a truthy value, a collection value is\n placed in the first group; otherwise, a collection value is placed in the\n second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = bifurcateBy( collection, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, groupBy\n","bifurcateByAsync":"\nbifurcateByAsync( collection, [options,] predicate, done )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an predicate function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If a predicate function calls the `next` callback with a truthy group value,\n a collection value is placed in the first group; otherwise, a collection\n value is placed in the second group.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n [ [ 1000, 3000 ], [ 2500 ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ 2, 0 ], [ 1 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n // Limit number of concurrent invocations:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n // Process sequentially:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync","bifurcateIn":"\nbifurcateIn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object with no prototype, the function returns an empty\n array.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var out = bifurcateIn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateOwn, groupIn\n","bifurcateOwn":"\nbifurcateOwn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object, the function returns an empty array.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = bifurcateOwn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateIn, groupOwn\n","BigInt":"\nBigInt( value )\n Returns a BigInt.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support BigInts.\n\n Parameters\n ----------\n value: integer|string\n Value of the BigInt.\n\n Returns\n -------\n out: BigInt\n BigInt.\n\n Examples\n --------\n > var v = ( BigInt ) ? BigInt( '1' ) : null\n\n\nTODO: document properties/methods\n\n","binomialTest":"\nbinomialTest( x[, n][, options] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: (number|Array)\n Number of successes or two-element array with successes and failures.\n\n n: Array (optional)\n Total number of observations.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.p: number (optional)\n Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Sample proportion.\n\n out.ci: Array\n 1-alpha confidence interval for the success probability.\n\n out.nullValue: number\n Assumed success probability under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var out = binomialTest( 682, 925 )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( [ 682, 925 - 682 ] )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( 21, 40, {\n ... 'p': 0.4,\n ... 'alternative': 'greater'\n ... })\n {\n 'pValue': ~0.074,\n 'statistic': 0.525\n // ...\n }\n\n","Boolean":"\nBoolean( value )\n Returns a boolean.\n\n When invoked without `new`,\n\n - if provided `false`, `null`, `undefined`, `-0`, `0`, `NaN`, or an empty\n string, the function returns `false`.\n - if provided any other value, including an empty object, an empty array,\n the string `'false'`, or a `Boolean` object (including a `Boolean` object\n whose value is `false`), the function returns `true`.\n\n When invoked with `new`, the constructor returns a `Boolean` object, which\n is an object wrapper for a primitive boolean value. The value of the\n returned `Boolean` object follows the same conversion semantics as when the\n constructor is invoked without `new`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: boolean|Boolean\n Boolean primitive or object.\n\n Examples\n --------\n > var b = new Boolean( null )\n \n > b = Boolean( null )\n false\n > b = Boolean( [] )\n true\n\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n\n Returns\n -------\n out: string\n String representation.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.toString()\n 'true'\n\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n\n Returns\n -------\n out: boolean\n Boolean primitive.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.valueOf()\n true\n\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n\n Returns\n -------\n out: string\n String representation.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.toString()\n 'true'","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n\n Returns\n -------\n out: boolean\n Boolean primitive.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.valueOf()\n true","BooleanArray":"\nBooleanArray()\n A Boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = new BooleanArray()\n \n\n\nBooleanArray( length )\n Creates a boolean array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10\n\n\nBooleanArray( booleanarray )\n Creates a boolean array from another boolean array.\n\n Parameters\n ----------\n booleanarray: BooleanArray\n Boolean array from which to generate another boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new BooleanArray( [ true, false, false, true ] )\n \n > var arr2 = new BooleanArray( arr1 )\n \n > var len = arr2.length\n 4\n\n\nBooleanArray( typedarray )\n Creates a boolean array from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var buf = new Uint8Array( [ 1, 0, 0, 1 ] )\n \n > var arr = new BooleanArray( buf )\n \n > var len = arr.length\n 4\n\n\nBooleanArray( obj )\n Creates a boolean array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new BooleanArray( [ true, false, false, true ] )\n \n > var len = arr1.length\n 4\n > var arr2 = new BooleanArray( [ {}, null, '', 4 ] );\n > len = arr2.length\n 4\n\n\nBooleanArray( buffer[, byteOffset[, length]] )\n Returns a boolean array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 240 );\n > var arr1 = new BooleanArray( buf )\n \n > var len = arr1.length\n 240\n > var arr2 = new BooleanArray( buf, 8 )\n \n > len = arr2.length\n 232\n > var arr3 = new BooleanArray( buf, 8, 20 )\n \n > len = arr3.length\n 20\n\n\nBooleanArray.from( src[, clbk[, thisArg]] )\n Creates a new boolean array from an array-like object or an iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > function map( v ) { return !v };\n > var src = [ true, false ];\n > var arr = BooleanArray.from( src, map )\n \n > var len = arr.length\n 2\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.of( element0[, element1[, ...elementN]] )\n Creates a new boolean array from a variable number of arguments.\n\n Parameters\n ----------\n element0: bool\n Array element.\n\n element1: bool (optional)\n Array element.\n\n elementN: ...bool (optional)\n Array elements.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = BooleanArray.of( true, false, false, true )\n \n > var len = arr.length\n 4\n\n\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n 1\n\n\nBooleanArray.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = BooleanArray.name\n 'BooleanArray'\n\n\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > var buf = arr.buffer\n \n\n\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var nbytes = arr.byteLength\n 10\n\n\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new BooleanArray( buf, 64 )\n \n > offset = arr.byteOffset\n 64\n\n\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 1\n\n\nBooleanArray.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10\n\n\nBooleanArray.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n An array element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > var v = arr.at( 1 )\n false\n > v = arr.at( -1 )\n true\n\n\nBooleanArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, true ]\n > v = it.next().value\n [ 1, false ]\n > v = it.next().value\n [ 2, true ]\n > var bool = it.next().done\n true\n\n\nBooleanArray.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, true, true ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nBooleanArray.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: boolean\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( 3 )\n \n > arr.fill( true );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n true\n\n\nBooleanArray.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( v === true ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.find( predicate )\n true\n\n\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.findLast( predicate )\n true\n\n\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findLastIndex( predicate )\n 2\n\n\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.forEach( clbk );\n > str\n '%true%false%false%true%'\n\n\nBooleanArray.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.set( true, 0 );\n > var v = arr.get( 0 )\n true\n\n\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var bool = arr.includes( true )\n true\n > bool = arr.includes( false, 3 )\n false\n\n\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var idx = arr.indexOf( true )\n 0\n > idx = arr.indexOf( false, 3 )\n -1\n\n\nBooleanArray.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.join()\n 'true,false,true'\n > str = arr.join( '|' )\n 'true|false|true'\n\n\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, true, true, false, true ] )\n \n > var idx = arr.lastIndexOf( false )\n 3\n > idx = arr.lastIndexOf( false, 2 )\n -1\n\n\nBooleanArray.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function invert( v ) { return !v; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.map( invert )\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false\n\n\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduce( reducer )\n false\n\n\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduceRight( reducer )\n false\n\n\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > arr.reverse();\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n false\n > v = arr.get( 2 )\n true\n\n\nBooleanArray.prototype.set( v[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n truthy and falsy values.\n\n Parameters\n ----------\n v: bool|BooleanArray|ArrayLikeObject\n Boolean value or Boolean value array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > arr.set( false );\n > var v = arr.get( 0 )\n false\n > arr.set( true, 1 );\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 4\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ false, true, false ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nBooleanArray.prototype.sort( [compareFunction] )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > arr.sort( compare );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n false\n\n\nBooleanArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array view.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toLocaleString()\n 'true,false,true'\n\n\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > var out = arr.toReversed()\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n false\n > v = out.get( 2 )\n true\n\n\nBooleanArray.prototype.toSorted( [compareFunction] )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.toSorted( compare );\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false\n\n\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n out: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toString()\n 'true,false,true'\n\n\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.values();\n > var v = it.next().value\n true\n > v = it.next().value\n false\n > var bool = it.next().done\n true\n\n\nBooleanArray.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: boolean\n Element value.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.with( 0, false )\n \n > var v = out.get( 0 )\n false\n\n\n See Also\n --------\n ArrayBuffer","BooleanArray.from":"\nBooleanArray.from( src[, clbk[, thisArg]] )\n Creates a new boolean array from an array-like object or an iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > function map( v ) { return !v };\n > var src = [ true, false ];\n > var arr = BooleanArray.from( src, map )\n \n > var len = arr.length\n 2\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true","BooleanArray.of":"\nBooleanArray.of( element0[, element1[, ...elementN]] )\n Creates a new boolean array from a variable number of arguments.\n\n Parameters\n ----------\n element0: bool\n Array element.\n\n element1: bool (optional)\n Array element.\n\n elementN: ...bool (optional)\n Array elements.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = BooleanArray.of( true, false, false, true )\n \n > var len = arr.length\n 4","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n 1","BooleanArray.name":"\nBooleanArray.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = BooleanArray.name\n 'BooleanArray'","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > var buf = arr.buffer\n ","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var nbytes = arr.byteLength\n 10","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new BooleanArray( buf, 64 )\n \n > offset = arr.byteOffset\n 64","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 1","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n An array element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > var v = arr.at( 1 )\n false\n > v = arr.at( -1 )\n true","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, true ]\n > v = it.next().value\n [ 1, false ]\n > v = it.next().value\n [ 2, true ]\n > var bool = it.next().done\n true","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, true, true ] )\n \n > var bool = arr.every( predicate )\n true","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: boolean\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( 3 )\n \n > arr.fill( true );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n true","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( v === true ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.find( predicate )\n true","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findIndex( predicate )\n 0","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.findLast( predicate )\n true","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findLastIndex( predicate )\n 2","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.forEach( clbk );\n > str\n '%true%false%false%true%'","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.set( true, 0 );\n > var v = arr.get( 0 )\n true","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var bool = arr.includes( true )\n true\n > bool = arr.includes( false, 3 )\n false","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var idx = arr.indexOf( true )\n 0\n > idx = arr.indexOf( false, 3 )\n -1","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.join()\n 'true,false,true'\n > str = arr.join( '|' )\n 'true|false|true'","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, true, true, false, true ] )\n \n > var idx = arr.lastIndexOf( false )\n 3\n > idx = arr.lastIndexOf( false, 2 )\n -1","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function invert( v ) { return !v; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.map( invert )\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduce( reducer )\n false","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduceRight( reducer )\n false","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > arr.reverse();\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n false\n > v = arr.get( 2 )\n true","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n truthy and falsy values.\n\n Parameters\n ----------\n v: bool|BooleanArray|ArrayLikeObject\n Boolean value or Boolean value array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > arr.set( false );\n > var v = arr.get( 0 )\n false\n > arr.set( true, 1 );\n > v = arr.get( 1 )\n true","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 4\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ false, true, false ] )\n \n > var bool = arr.some( predicate )\n true","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction] )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > arr.sort( compare );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n false","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array view.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toLocaleString()\n 'true,false,true'","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > var out = arr.toReversed()\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n false\n > v = out.get( 2 )\n true","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction] )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.toSorted( compare );\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n out: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toString()\n 'true,false,true'","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.values();\n > var v = it.next().value\n true\n > v = it.next().value\n false\n > var bool = it.next().done\n true","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: boolean\n Element value.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.with( 0, false )\n \n > var v = out.get( 0 )\n false\n\n\n See Also\n --------\n ArrayBuffer","broadcastArray":"\nbroadcastArray( x, shape )\n Broadcasts an ndarray to a specified shape.\n\n The returned array is a read-only view on the input array data buffer. The\n view is typically *not* contiguous. As more than one element of a returned\n view may refer to the same memory location, writing to the input array may\n affect multiple elements. If you need to write to the input array, copy the\n input array before broadcasting.\n\n The function throws an error if a provided ndarray is incompatible with a\n provided shape.\n\n The function always returns a new ndarray instance even if the input ndarray\n shape and the desired shape are the same.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n shape: ArrayLikeObject\n Desired shape.\n\n Returns\n -------\n out: ndarray\n Broadcasted array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = broadcastArray( x, [ 3, 2, 2 ] )\n \n > sh = y.shape\n [ 3, 2, 2 ]\n > var v = y.get( 0, 0, 0 )\n 1\n > v = y.get( 0, 0, 1 )\n 2\n > v = y.get( 0, 1, 0 )\n 3\n > v = y.get( 0, 1, 1 )\n 4\n > v = y.get( 1, 0, 0 )\n 1\n > v = y.get( 1, 1, 0 )\n 3\n > v = y.get( 2, 0, 0 )\n 1\n > v = y.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, broadcastArrays, ndarray, maybeBroadcastArray\n","broadcastArrays":"\nbroadcastArrays( ...arrays )\n Broadcasts ndarrays to a common shape.\n\n The function supports two (mutually exclusive) means of providing ndarray\n arguments:\n\n 1. Providing a single array containing ndarray arguments.\n 2. Providing ndarray arguments as separate arguments.\n\n The returned arrays are read-only views on their respective underlying\n array data buffers. The views are typically **not** contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to a view may affect multiple elements. If you need to write to an\n input array, copy the array before broadcasting.\n\n The function throws an error if provided broadcast-incompatible ndarrays.\n\n The function always returns new ndarray instances even if an input ndarray\n and the broadcasted shape are the same.\n\n Parameters\n ----------\n arrays: ...ndarray|ArrayLikeObject\n Array arguments.\n\n Returns\n -------\n out: Array\n Broadcasted arrays.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = ndzeros( [ 3, 2, 2 ] )\n \n > var out = broadcastArrays( [ x, y ] )\n [ , ]\n\n // Retrieve the broadcasted \"x\" array:\n > var bx = out[ 0 ]\n \n > sh = bx.shape\n [ 3, 2, 2 ]\n\n // Retrieve broadcasted elements...\n > var v = bx.get( 0, 0, 0 )\n 1\n > v = bx.get( 0, 0, 1 )\n 2\n > v = bx.get( 0, 1, 0 )\n 3\n > v = bx.get( 0, 1, 1 )\n 4\n > v = bx.get( 1, 0, 0 )\n 1\n > v = bx.get( 1, 1, 0 )\n 3\n > v = bx.get( 2, 0, 0 )\n 1\n > v = bx.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, broadcastArray, ndarray, maybeBroadcastArrays\n","Buffer":"\nBuffer\n Buffer constructor.\n\n\nBuffer( size )\n Allocates a buffer having a specified number of bytes.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 4 )\n \n\n\nBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n > var b2 = new Buffer( b1 )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n Allocates a buffer using an array of octets.\n\n Parameters\n ----------\n array: Array\n Array of octets.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 'beep boop' )\n \n\n\nTODO: add methods and properties\n\n\n See Also\n --------\n ArrayBuffer\n","buffer2json":"\nbuffer2json( buffer )\n Returns a JSON representation of a buffer.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n out.type: string\n Value type. The assigned value is always \"Buffer\".\n\n out.data: Array\n Buffer data.\n\n Examples\n --------\n > var buf = new allocUnsafe( 2 );\n > buf[ 0 ] = 1;\n > buf[ 1 ] = 2;\n > var json = buffer2json( buf )\n { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n See Also\n --------\n typedarray2json, reviveBuffer\n","BYTE_ORDER":"\nBYTE_ORDER\n Platform byte order.\n\n Possible values:\n\n - 'little-endian'\n - 'big-endian'\n - 'mixed-endian'\n - 'unknown'\n\n Examples\n --------\n > BYTE_ORDER\n \n\n See Also\n --------\n IS_BIG_ENDIAN, IS_LITTLE_ENDIAN\n","camelcase":"\ncamelcase( str )\n Converts a string to camel case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Camel-cased string.\n\n Examples\n --------\n > var out = camelcase( 'Hello World!' )\n 'helloWorld'\n > out = camelcase( 'beep boop' )\n 'beepBoop'\n\n See Also\n --------\n constantcase, kebabcase, pascalcase, snakecase","capitalize":"\ncapitalize( str )\n Capitalizes the first character in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = capitalize( 'beep' )\n 'Beep'\n > out = capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n uncapitalize, uppercase\n","capitalizeKeys":"\ncapitalizeKeys( obj )\n Converts the first letter of each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'aa': 1, 'bb': 2 };\n > var out = capitalizeKeys( obj )\n { 'Aa': 1, 'Bb': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","CATALAN":"\nCATALAN\n Catalan's constant.\n\n Examples\n --------\n > CATALAN\n 0.915965594177219\n\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n\n Examples\n --------\n > CBRT_EPS\n 0.0000060554544523933395\n\n See Also\n --------\n EPS, SQRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n Returns US birth data from 1969 to 1988, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_BIRTHS_1969_1988()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1994_2003, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n Returns US birth data from 1994 to 2003, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_BIRTHS_1994_2003()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1969_1988, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n the Center for Disease Control and Prevention's National Center for Health\n Statistics.\n\n All birth data by race before 1980 are based on race of the child. Starting\n in 1980, birth data by race are based on race of the mother. Birth data are\n used to calculate infant mortality rate.\n\n Returns\n -------\n out: Object\n Infant mortality data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n { 'black': [...], 'white': [...] }\n\n","chdir":"\nchdir( path )\n Changes the current working directory.\n\n If unable to set the current working directory (e.g., due to a non-existent\n path), the function returns an error; otherwise, the function returns\n `null`.\n\n Parameters\n ----------\n path: string\n Desired working directory.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = chdir( '/path/to/current/working/directory' )\n\n See Also\n --------\n cwd\n","chi2gof":"\nchi2gof( x, y[, ...args][, options] )\n Performs a chi-square goodness-of-fit test.\n\n A chi-square goodness-of-fit test is computed for the null hypothesis that\n the values of `x` come from the discrete probability distribution specified\n by `y`.\n\n The second argument can either be expected frequencies, population\n probabilities summing to one, or a discrete probability distribution name to\n test against.\n\n When providing a discrete probability distribution name, distribution\n parameters *must* be supplied as additional arguments.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n By default, the p-value is computed using a chi-square distribution with\n `k-1` degrees of freedom, where `k` is the length of `x`.\n\n If provided distribution arguments are estimated (e.g., via maximum\n likelihood estimation), the degrees of freedom should be corrected. Set the\n `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n freedom adjustment.\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five.\n\n Instead of relying on chi-square approximation to calculate the p-value, one\n can use Monte Carlo simulation. When the `simulate` option is `true`, the\n simulation is performed by re-sampling from the discrete probability\n distribution specified by `y`.\n\n Parameters\n ----------\n x: ndarray|Array|TypedArray\n Observation frequencies.\n\n y: ndarray|Array|TypedArray|string\n Expected frequencies, population probabilities, or a discrete\n probability distribution name.\n\n args: ...number (optional)\n Distribution parameters. Distribution parameters will be passed to a\n probability mass function (PMF) as arguments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.ddof: number (optional)\n Delta degrees of freedom adjustment. Default: 0.\n\n options.simulate: boolean (optional)\n Boolean indicating whether to calculate p-values by Monte Carlo\n simulation. The simulation is performed by re-sampling from the discrete\n distribution specified by `y`. Default: false.\n\n options.iterations: number (optional)\n Number of Monte Carlo iterations. Default: 500.\n\n Returns\n -------\n out: Object\n Test results object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number|null\n Degrees of freedom.\n\n out.method: string\n Test name.\n\n out.toString: Function\n Serializes results as formatted output.\n\n out.toJSON: Function\n Serializes results as JSON.\n\n Examples\n --------\n // Provide expected probabilities...\n > var x = [ 89, 37, 30, 28, 2 ];\n > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > var out = chi2gof( x, p );\n > var o = out.toJSON()\n { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n > out.toString()\n\n // Set significance level...\n > var opts = { 'alpha': 0.01 };\n > out = chi2gof( x, p, opts );\n > out.toString()\n\n // Calculate the test p-value via Monte Carlo simulation...\n > x = [ 89, 37, 30, 28, 2 ];\n > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > opts = { 'simulate': true, 'iterations': 1000 };\n > out = chi2gof( x, p, opts );\n > out.toString()\n\n // Verify that data comes from Poisson distribution...\n > var lambda = 3.0;\n > var rpois = base.random.poisson.factory( lambda );\n > var len = 400;\n > x = [];\n > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n // Generate a frequency table...\n > var freqs = new Int32Array( len );\n > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n > out = chi2gof( freqs, 'poisson', lambda );\n > out.toString()\n\n","chi2test":"\nchi2test( x[, options] )\n Performs a chi-square independence test.\n\n For a two-way contingency table, the function computes a chi-square\n independence test for the null hypothesis that the joint distribution of the\n cell counts is the product of the row and column marginals (i.e. that the\n row and column variables are independent).\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five. The Yates' continuity correction is enabled\n by default for 2x2 tables to account for this, although it tends to\n over-correct.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n Parameters\n ----------\n x: ndarray|Array>\n Two-way table of observed frequencies.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.correct: boolean (optional)\n Boolean indicating whether to use Yates' continuity correction when\n provided a 2x2 contingency table. Default: true.\n\n Returns\n -------\n out: Object\n Test results object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number\n Degrees of freedom.\n\n out.expected: ndarray\n Expected frequencies.\n\n out.method: string\n Test name.\n\n out.toString: Function\n Serializes results as formatted output.\n\n out.toJSON: Function\n Serializes results as JSON.\n\n Examples\n --------\n > var x = [ [ 20, 30 ], [ 30, 20 ] ];\n > var out = chi2test( x );\n > var o = out.toJSON()\n { 'rejected': false, 'pValue': ~0.072, 'statistic': 3.24, ... }\n > out.toString()\n\n // Set significance level...\n > var opts = { 'alpha': 0.1 };\n > out = chi2test( x, opts );\n > o = out.toJSON()\n { 'rejected': true, 'pValue': ~0.072, 'statistic': 3.24, ... }\n > out.toString()\n\n // Disable Yates' continuity correction (primarily used with small counts):\n > opts = { 'correct': false };\n > out = chi2test( x, opts );\n > out.toString()\n\n","circarray2iterator":"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, an iterator iterates over elements\n from right-to-left. Default: 1.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n array2iterator, stridedarray2iterator\n","circularArrayStream":"\ncircularArrayStream( src[, options] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream","CircularBuffer":"\nCircularBuffer( buffer )\n Circular buffer constructor.\n\n Parameters\n ----------\n buffer: integer|ArrayLike\n Buffer size or an array-like object to use as the underlying buffer.\n\n Returns\n -------\n buf: Object\n Circular buffer data structure.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.length\n 3\n > b.count\n 3\n > b.push( 'boop' )\n 'foo'\n\n\nCircularBuffer.prototype.clear()\n Clears a buffer.\n\n Returns\n -------\n out: Object\n Circular buffer instance.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.count\n 3\n > b.clear();\n > b.count\n 0\n\n\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n\n Returns\n -------\n out: integer\n Number of elements currently in the buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.count\n 0\n > b.push( 'foo' );\n > b.count\n 1\n > b.push( 'bar' );\n > b.count\n 2\n\n\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a circular buffer is full.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.full\n false\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.full\n true\n\n\nCircularBuffer.prototype.iterator( [niters] )\n Returns an iterator for iterating over a circular buffer.\n\n A returned iterator does not iterate over partially full buffers.\n\n Parameters\n ----------\n niters: integer (optional)\n Number of iterations. Default: infinity.\n\n Returns\n -------\n out: Iterator\n Iterator.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var it = b.iterator( b.length );\n > var v = it.next().value\n 'bar'\n > v = it.next().value\n 'beep'\n > v = it.next().value\n 'boop'\n > var bool = it.next().done\n true\n\n\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n\n Returns\n -------\n out: integer\n Buffer length.\n\n Examples\n --------\n > var b = CircularBuffer( [ 0, 0, 0 ] );\n > var len = b.length\n 3\n\n\nCircularBuffer.prototype.push( value )\n Adds a value to a circular buffer.\n\n Parameters\n ----------\n value: any\n Value to add.\n\n Returns\n -------\n out: any\n Removed element (or undefined).\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' )\n undefined\n > b.push( 'bar' )\n undefined\n > b.push( 'beep' )\n undefined\n > b.push( 'boop' )\n 'foo'\n\n\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n\n Returns\n -------\n out: Array\n Circular buffer values.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var vals = b.toArray()\n [ 'bar', 'beep', 'boop' ]\n\n\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n\n Returns\n -------\n out: Object\n Serialized circular buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var o = b.toJSON()\n {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n See Also\n --------\n FIFO, Stack\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n Clears a buffer.\n\n Returns\n -------\n out: Object\n Circular buffer instance.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.count\n 3\n > b.clear();\n > b.count\n 0","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n\n Returns\n -------\n out: integer\n Number of elements currently in the buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.count\n 0\n > b.push( 'foo' );\n > b.count\n 1\n > b.push( 'bar' );\n > b.count\n 2","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a circular buffer is full.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.full\n false\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.full\n true","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters] )\n Returns an iterator for iterating over a circular buffer.\n\n A returned iterator does not iterate over partially full buffers.\n\n Parameters\n ----------\n niters: integer (optional)\n Number of iterations. Default: infinity.\n\n Returns\n -------\n out: Iterator\n Iterator.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var it = b.iterator( b.length );\n > var v = it.next().value\n 'bar'\n > v = it.next().value\n 'beep'\n > v = it.next().value\n 'boop'\n > var bool = it.next().done\n true","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n\n Returns\n -------\n out: integer\n Buffer length.\n\n Examples\n --------\n > var b = CircularBuffer( [ 0, 0, 0 ] );\n > var len = b.length\n 3","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value )\n Adds a value to a circular buffer.\n\n Parameters\n ----------\n value: any\n Value to add.\n\n Returns\n -------\n out: any\n Removed element (or undefined).\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' )\n undefined\n > b.push( 'bar' )\n undefined\n > b.push( 'beep' )\n undefined\n > b.push( 'boop' )\n 'foo'","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n\n Returns\n -------\n out: Array\n Circular buffer values.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var vals = b.toArray()\n [ 'bar', 'beep', 'boop' ]","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n\n Returns\n -------\n out: Object\n Serialized circular buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var o = b.toJSON()\n {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n See Also\n --------\n FIFO, Stack","close":"\nclose( fd, clbk )\n Asynchronously closes a file descriptor, so that the file descriptor no\n longer refers to any file and may be reused.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n clbk: Function\n Callback to invoke upon closing a file descriptor.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close( fd, done ); };\n\n\nclose.sync( fd )\n Synchronously closes a file descriptor.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n Returns\n -------\n out: Error|void\n If an error occurs, an error object; otherwise, undefined.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n exists, open, readFile\n","close.sync":"\nclose.sync( fd )\n Synchronously closes a file descriptor.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n Returns\n -------\n out: Error|void\n If an error occurs, an error object; otherwise, undefined.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n exists, open, readFile","CMUDICT":"\nCMUDICT( [options] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n Data includes the following:\n\n - dict: the main pronouncing dictionary.\n - phones: manners of articulation for each sound.\n - symbols: complete list of ARPABET symbols used by the dictionary.\n - vp: verbal pronunciations of punctuation marks.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n CMUdict dataset.\n\n Examples\n --------\n > var data = CMUDICT();\n > var dict = data.dict\n {...}\n > var phones = data.phones\n {...}\n > var symbols = data.symbols\n [...]\n > var vp = data.vp\n {...}\n\n","codePointAt":"\ncodePointAt( str, idx[, backward] )\n Returns a Unicode code point from a string at a specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n idx: integer\n Position. If less than `0`, the string position is determined relative\n to the end of the input string.\n\n backward: boolean (optional)\n Backward iteration for low surrogates. Default: false.\n\n Returns\n -------\n out: integer\n Unicode code point.\n\n Examples\n --------\n > var out = codePointAt( 'last man standing', 4 )\n 32\n > out = codePointAt( 'presidential election', 8, true )\n 116\n > out = codePointAt( 'अनुच्छेद', 2 )\n 2369\n > out = codePointAt( '🌷', 1, true )\n 127799\n\n See Also\n --------\n fromCodePoint","commonKeys":"\ncommonKeys( obj1, obj2[, ...obj] )\n Returns the common own property names of two or more objects.\n\n Parameters\n ----------\n obj1: any\n First object.\n\n obj2: any\n Second object.\n\n obj: ...any (optional)\n Additional objects.\n\n Returns\n -------\n out: Array\n Common keys of objects.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > var keys = commonKeys( obj1, obj2 )\n [ 'a', 'b' ]\n\n See Also\n --------\n commonKeysIn, objectKeys","commonKeysIn":"\ncommonKeysIn( obj1, obj2[, ...obj] )\n Returns the common own and inherited property names of two or more objects.\n\n Parameters\n ----------\n obj1: any\n First object.\n\n obj2: any\n Second object.\n\n obj: ...any (optional)\n Additional objects.\n\n Returns\n -------\n out: Array\n Common keys.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > var keys = commonKeysIn( obj1, obj2 )\n [ 'a', 'b' ]\n\n See Also\n --------\n commonKeys, keysIn","complex":"\ncomplex( real, imag[, dtype] )\n Creates a complex number.\n\n The function supports the following data types:\n\n - float64\n - float32\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n z: Complex\n Complex number.\n\n Examples\n --------\n > var z = complex( 5.0, 3.0, 'float64' )\n \n > z = complex( 5.0, 3.0, 'float32' )\n \n\n See Also\n --------\n Complex128, Complex64\n","Complex64":"\nComplex64( real, imag )\n 64-bit complex number constructor.\n\n Both the real and imaginary components are stored as single-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex64\n 64-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n\nComplex64.name\n Constructor name.\n\n Examples\n --------\n > var str = Complex64.name\n 'Complex64'\n\n\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex64.BYTES_PER_ELEMENT\n 4\n\n\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 4\n\n\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.byteLength\n 8\n\n See Also\n --------\n complex, Complex128\n","Complex64.name":"\nComplex64.name\n Constructor name.\n\n Examples\n --------\n > var str = Complex64.name\n 'Complex64'","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex64.BYTES_PER_ELEMENT\n 4","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 4","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.byteLength\n 8\n\n See Also\n --------\n complex, Complex128","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n Canonical single-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX64_NAN\n \n\n See Also\n --------\n COMPLEX128_NAN\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n\n Examples\n --------\n > COMPLEX64_NUM_BYTES\n 8\n\n See Also\n --------\n COMPLEX128_NUM_BYTES, FLOAT32_NUM_BYTES\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n Single-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX64_ZERO\n \n\n See Also\n --------\n COMPLEX128_ZERO\n","Complex64Array":"\nComplex64Array()\n A 64-bit complex number array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex64Array()\n \n\n\nComplex64Array( length )\n Creates a 64-bit complex number array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex64Array( complexarray )\n Creates a 64-bit complex number array from another complex number array.\n\n Parameters\n ----------\n complexarray: Complex64Array\n Complex array from which to generate another complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr2 = new Complex64Array( arr1 )\n \n > var len = arr2.length\n 2\n\n\nComplex64Array( typedarray )\n Creates a 64-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr = new Complex64Array( buf )\n \n > var len = arr.length\n 2\n\n\nComplex64Array( obj )\n Creates a 64-bit complex number array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var len = arr1.length\n 2\n > var buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\n > var arr2 = new Complex64Array( buf )\n \n > len = arr2.length\n 2\n\n\nComplex64Array( buffer[, byteOffset[, length]] )\n Returns a 64-bit complex number array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 240 );\n > var arr1 = new Complex64Array( buf )\n \n > var len = arr1.length\n 30\n > var arr2 = new Complex64Array( buf, 8 )\n \n > len = arr2.length\n 29\n > var arr3 = new Complex64Array( buf, 8, 20 )\n \n > len = arr3.length\n 20\n\n\nComplex64Array.from( src[, clbk[, thisArg]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n \n Returns\n -------\n out: Complex64Array\n A typed array.\n \n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n\n\nComplex64Array.of( element0[, element1[, ...elementN]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex64( 1.0, -1.0 );\n > var z2 = new Complex64( 2.0, -2.0 );\n > arr = Complex64Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n\n\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n 8\n\n\nComplex64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex64Array.name\n 'Complex64Array'\n\n\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > var buf = arr.buffer\n \n\n\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var nbytes = arr.byteLength\n 80\n\n\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 5 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new Complex64Array( buf, 64 )\n \n > offset = arr.byteOffset\n 64\n\n\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 8\n\n\nComplex64Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex64Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex64|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n\n\nComplex64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, ]\n > var re = realf( v[ 1 ] )\n 1.0\n > var im = imagf( v[ 1 ] )\n -1.0\n > v = it.next().value\n [ 1, ]\n > re = realf( v[ 1 ] )\n 2.0\n > im = imagf( v[ 1 ] )\n -2.0\n > v = it.next().value\n [ 2, ]\n > re = realf( v[ 1 ] )\n 3.0\n > im = imagf( v[ 1 ] )\n -3.0\n > var bool = it.next().done\n true\n\n\nComplex64Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nComplex64Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex64\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex64Array( 3 )\n \n > arr.fill( new Complex64( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 1.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0\n\n\nComplex64Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n 2.0\n\n\nComplex64Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 1.0\n\n\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context. \n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n 2.0\n\n\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1\n\n\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'\n\n\nComplex64Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n\n\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n false\n\n\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n -1\n\n\nComplex64Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n \n Returns\n -------\n out: string\n Array serialized as a string.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'\n\n\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n 0\n\n\nComplex64Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n \n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n\n\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element. \n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.caddf )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.caddf )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n -1.0\n\n\nComplex64Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex64|Complex64Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > arr.set( new Complex64( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n\n\nComplex64Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n \n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n \n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nComplex64Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n \n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'\n\n\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n 3.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n 2.0\n > z = out.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0\n\n\nComplex64Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n \n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = out.get( 2 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = realf( v )\n 1.0\n > var im = imagf( v )\n -1.0\n > v = it.next().value\n \n > re = realf( v )\n 2.0\n > im = imagf( v )\n -2.0\n > var bool = it.next().done\n true\n\n\nComplex64Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: Complex64\n Element value. \n\n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\n See Also\n --------\n Complex128Array, complex, Complex64","Complex64Array.from":"\nComplex64Array.from( src[, clbk[, thisArg]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n \n Returns\n -------\n out: Complex64Array\n A typed array.\n \n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0","Complex64Array.of":"\nComplex64Array.of( element0[, element1[, ...elementN]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex64( 1.0, -1.0 );\n > var z2 = new Complex64( 2.0, -2.0 );\n > arr = Complex64Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n 8","Complex64Array.name":"\nComplex64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex64Array.name\n 'Complex64Array'","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > var buf = arr.buffer\n ","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var nbytes = arr.byteLength\n 80","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 5 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new Complex64Array( buf, 64 )\n \n > offset = arr.byteOffset\n 64","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 8","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex64|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, ]\n > var re = realf( v[ 1 ] )\n 1.0\n > var im = imagf( v[ 1 ] )\n -1.0\n > v = it.next().value\n [ 1, ]\n > re = realf( v[ 1 ] )\n 2.0\n > im = imagf( v[ 1 ] )\n -2.0\n > v = it.next().value\n [ 2, ]\n > re = realf( v[ 1 ] )\n 3.0\n > im = imagf( v[ 1 ] )\n -3.0\n > var bool = it.next().done\n true","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex64\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex64Array( 3 )\n \n > arr.fill( new Complex64( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 1.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n 2.0","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 1.0","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context. \n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n 2.0","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n false","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n -1","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n \n Returns\n -------\n out: string\n Array serialized as a string.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n 0","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n \n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element. \n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.caddf )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.caddf )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n -1.0","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex64|Complex64Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > arr.set( new Complex64( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n \n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n \n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n \n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n 3.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n 2.0\n > z = out.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n \n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = out.get( 2 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = realf( v )\n 1.0\n > var im = imagf( v )\n -1.0\n > v = it.next().value\n \n > re = realf( v )\n 2.0\n > im = imagf( v )\n -2.0\n > var bool = it.next().done\n true","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: Complex64\n Element value. \n\n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\n See Also\n --------\n Complex128Array, complex, Complex64","Complex128":"\nComplex128( real, imag )\n 128-bit complex number constructor.\n\n Both the real and imaginary components are stored as double-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex128\n 128-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n\nComplex128.name\n Constructor name.\n\n Examples\n --------\n > var str = Complex128.name\n 'Complex128'\n\n\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex128.BYTES_PER_ELEMENT\n 8\n\n\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 8\n\n\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.byteLength\n 16\n\n See Also\n --------\n complex, Complex64\n","Complex128.name":"\nComplex128.name\n Constructor name.\n\n Examples\n --------\n > var str = Complex128.name\n 'Complex128'","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex128.BYTES_PER_ELEMENT\n 8","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 8","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.byteLength\n 16\n\n See Also\n --------\n complex, Complex64","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX128_NAN\n \n\n See Also\n --------\n COMPLEX64_NAN\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n\n Examples\n --------\n > COMPLEX128_NUM_BYTES\n 16\n\n See Also\n --------\n COMPLEX64_NUM_BYTES, FLOAT64_NUM_BYTES\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX128_ZERO\n \n\n See Also\n --------\n COMPLEX64_ZERO\n","Complex128Array":"\nComplex128Array()\n A 128-bit complex number array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex128Array()\n \n\n\nComplex128Array( length )\n Creates a 128-bit complex number array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex128Array( complexarray )\n Creates a 64-bit complex number array from another complex number array.\n\n Parameters\n ----------\n complexarray: Complex128Array\n Complex array from which to generate another complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr2 = new Complex128Array( arr1 )\n \n > var len = arr2.length\n 2\n\n\nComplex128Array( typedarray )\n Creates a 128-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr = new Complex128Array( buf )\n \n > var len = arr.length\n 2\n\n\nComplex128Array( obj )\n Creates a 128-bit complex number array from an array-like object or\n iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var len = arr1.length\n 2\n > var buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\n > var arr2 = new Complex128Array( buf )\n \n > len = arr2.length\n 2\n\n\nComplex128Array( buffer[, byteOffset[, length]] )\n Returns a 128-bit complex number array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 480 );\n > var arr1 = new Complex128Array( buf )\n \n > var len = arr1.length\n 30\n > var arr2 = new Complex128Array( buf, 16 )\n \n > len = arr2.length\n 29\n > var arr3 = new Complex128Array( buf, 16, 20 )\n \n > len = arr3.length\n 20\n\n\nComplex128Array.from( src[, clbk[, thisArg]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.of( element0[, element1[, ...elementN]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number|ComplexLike\n Array element.\n\n element1: number |ComplexLike(optional)\n Array element.\n\n elementN: ...number|ComplexLike (optional)\n Array elements.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex128( 1.0, -1.0 );\n > var z2 = new Complex128( 2.0, -2.0 );\n > arr = Complex128Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n\n\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n 16\n\n\nComplex128Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex128Array.name\n 'Complex128Array'\n\n\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > var buf = arr.buffer\n \n\n\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var nbytes = arr.byteLength\n 160\n\n\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 480 );\n > arr = new Complex128Array( buf, 128 )\n \n > offset = arr.byteOffset\n 128\n\n\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 16\n\n\nComplex128Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex128Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, [ 1.0, -1.0 ] ]\n > v = it.next().value\n [ 1, [ 2.0, -2.0 ] ]\n > v = it.next().value\n [ 2, [ 3.0, -3.0 ] ]\n > var bool = it.next().done\n true\n\n\nComplex128Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) > 0.0 ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nComplex128Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex128\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( 3 )\n \n > arr.fill( new Complex128( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, 1.0 ]\n > z = arr.get( 1 )\n [ 1.0, 1.0 ]\n > z = arr.get( 2 )\n [ 1.0, 1.0 ]\n\n\nComplex128Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n [ 2.0, 2.0 ]\n\n\nComplex128Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n [ 1.0, 1.0 ]\n\n\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n [ 2.0, 2.0 ]\n\n\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1\n\n\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'\n\n\nComplex128Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n false\n\n\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n -1\n\n\nComplex128Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'\n\n\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n 0\n\n\nComplex128Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n\n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n [ 1.0, -1.0 ]\n > z = out.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.cadd )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.cadd )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 1.0, -1.0 ]\n\n\nComplex128Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex128|Complex128Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > arr.set( new Complex128( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n [ 2.0, -2.0 ]\n > z = out.get( 1 )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nComplex128Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'\n\n\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n 3.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n 2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n\n\nComplex128Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n -1.0\n > v = it.next().value\n \n > re = real( v )\n 2.0\n > im = imag( v )\n -2.0\n > var bool = it.next().done\n true\n\n\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: Complex128\n Element value.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\n See Also\n --------\n Complex64Array, complex, Complex128","Complex128Array.from":"\nComplex128Array.from( src[, clbk[, thisArg]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 2.0, -2.0 ]","Complex128Array.of":"\nComplex128Array.of( element0[, element1[, ...elementN]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number|ComplexLike\n Array element.\n\n element1: number |ComplexLike(optional)\n Array element.\n\n elementN: ...number|ComplexLike (optional)\n Array elements.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex128( 1.0, -1.0 );\n > var z2 = new Complex128( 2.0, -2.0 );\n > arr = Complex128Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n 16","Complex128Array.name":"\nComplex128Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex128Array.name\n 'Complex128Array'","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > var buf = arr.buffer\n ","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var nbytes = arr.byteLength\n 160","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 480 );\n > arr = new Complex128Array( buf, 128 )\n \n > offset = arr.byteOffset\n 128","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 16","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n [ 2.0, -2.0 ]","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, [ 1.0, -1.0 ] ]\n > v = it.next().value\n [ 1, [ 2.0, -2.0 ] ]\n > v = it.next().value\n [ 2, [ 3.0, -3.0 ] ]\n > var bool = it.next().done\n true","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) > 0.0 ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex128\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( 3 )\n \n > arr.fill( new Complex128( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, 1.0 ]\n > z = arr.get( 1 )\n [ 1.0, 1.0 ]\n > z = arr.get( 2 )\n [ 1.0, 1.0 ]","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n [ 2.0, 2.0 ]","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n [ 1.0, 1.0 ]","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n [ 2.0, 2.0 ]","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n [ 2.0, -2.0 ]","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n false","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n -1","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n 0","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n\n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n [ 1.0, -1.0 ]\n > z = out.get( 1 )\n [ 2.0, -2.0 ]","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.cadd )\n [ 3.0, -3.0 ]","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.cadd )\n [ 3.0, -3.0 ]","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 1.0, -1.0 ]","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex128|Complex128Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > arr.set( new Complex128( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n [ 2.0, -2.0 ]\n > z = out.get( 1 )\n [ 3.0, -3.0 ]","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 3.0, -3.0 ]","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n 3.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n 2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n -1.0\n > v = it.next().value\n \n > re = real( v )\n 2.0\n > im = imag( v )\n -2.0\n > var bool = it.next().done\n true","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: Complex128\n Element value.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\n See Also\n --------\n Complex64Array, complex, Complex128","complexarray":"\ncomplexarray( [dtype] )\n Creates a complex typed array.\n\n The function supports the following data types:\n\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n\n The default typed array data type is `complex128`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray()\n \n > arr = complexarray( 'complex64' )\n \n\n\ncomplexarray( length[, dtype] )\n Returns a complex number typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray( 5 )\n \n > arr = complexarray( 5, 'complex64' )\n \n\n\ncomplexarray( complexarray[, dtype] )\n Creates a complex number typed array from another complex number typed\n array.\n\n Parameters\n ----------\n complexarray: ComplexArray\n Complex number typed array from which to generate another complex number\n typed array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( obj[, dtype] )\n Creates a complex number typed array from an array-like object or iterable.\n\n If an array-like object contains interleaved real and imaginary components,\n the array-like object must have a length which is a multiple of two.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a complex number typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first array element.\n Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = complexarray( buf, 0, 8, 'complex64' )\n \n\n See Also\n --------\n typedarray, realarray\n","complexarrayCtors":"\ncomplexarrayCtors( dtype )\n Returns a complex typed array constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Complex typed array constructor.\n\n Examples\n --------\n > var ctor = complexarrayCtors( 'complex64' )\n \n > ctor = complexarrayCtors( 'float32' )\n null\n\n See Also\n --------\n arrayCtors, typedarrayCtors, realarrayCtors\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n\n Returns\n -------\n out: Array\n List of complex typed array data types.\n\n Examples\n --------\n > var out = complexarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, typedarrayDataTypes, realarrayDataTypes, ndarrayDataTypes\n","complexCtors":"\ncomplexCtors( dtype )\n Returns a complex number constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = complexCtors( 'complex128' )\n \n > ctor = complexCtors( 'complex' )\n null\n\n See Also\n --------\n complexarrayCtors\n","complexDataType":"\ncomplexDataType( value )\n Returns the data type of a complex number object.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var v = new Complex128( 1.0, 2.0 );\n > var dt = complexDataType( v )\n 'complex128'\n > dt = complexDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataType\n","complexDataTypes":"\ncomplexDataTypes()\n Returns a list of complex number data types.\n\n The output array contains the following data types:\n\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n\n Returns\n -------\n out: Array\n List of complex number data types.\n\n Examples\n --------\n > var out = complexDataTypes()\n \n\n See Also\n --------\n complexarrayDataTypes\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1, dtype2] )\n Returns the complex number data type with the smallest size and closest\n \"kind\" to which data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n Data type.\n\n dtype2: string (optional)\n Data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = complexPromotionRules( 'complex128', 'complex64' )\n 'complex128'\n\n See Also\n --------\n arrayPromotionRules, ndarrayPromotionRules\n","compose":"\ncompose( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as an argument\n to the next function. The result of the leftmost function is the result\n of the whole.\n\n Notes:\n\n - Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n - The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x ) {\n ... return 2 * x;\n ... }\n > function b( x ) {\n ... return x + 3;\n ... }\n > function c( x ) {\n ... return x / 5;\n ... }\n > var f = compose( c, b, a );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n composeAsync\n","composeAsync":"\ncomposeAsync( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as the first argument\n of the next function. The result of the leftmost function is the result\n of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - error: error argument.\n - result: function result.\n\n If a composed function calls the `next` callback with a truthy `error`\n argument, the composite function suspends execution and immediately calls\n the `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = composeAsync( c, b, a );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n compose\n","configdir":"\nconfigdir( [p] )\n Returns a directory for user-specific configuration files.\n\n On Windows platforms, the function first checks for a `LOCALAPPDATA`\n environment variable before checking for an `APPDATA` environment variable.\n This means that machine specific user configuration files have precedence\n over roaming user configuration files.\n\n On non-Windows platforms, if the function is unable to locate the current\n user's `home` directory, the function returns `null`. Similarly, on Windows\n platforms, if the function is unable to locate an application data\n directory, the function also returns `null`.\n\n Parameters\n ----------\n p: string (optional)\n Path to append to a base directory.\n\n Returns\n -------\n out: string|null\n Directory.\n\n Examples\n --------\n > var dir = configdir()\n e.g., '/Users//Library/Preferences'\n > dir = configdir( 'appname/config' )\n e.g., '/Users//Library/Preferences/appname/config'\n\n See Also\n --------\n homedir, tmpdir\n","conj":"\nconj( z )\n Returns the complex conjugate of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conj( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n imag, real, reim\n","conjf":"\nconjf( z )\n Returns the complex conjugate of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conjf( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n conj, imagf, realf, reimf\n","constantcase":"\nconstantcase( str )\n Converts a string to constant case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Constant-cased string.\n\n Examples\n --------\n > var out = constantcase( 'Hello World!' )\n 'HELLO_WORLD'\n > out = constantcase( 'I am a tiny little teapot' )\n 'I_AM_A_TINY_LITTLE_TEAPOT'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","constantFunction":"\nconstantFunction( val )\n Creates a function which always returns the same value.\n\n Notes:\n\n - When provided an object reference, the returned `function` always returns\n the same reference.\n\n Parameters\n ----------\n val: any\n Value to always return.\n\n Returns\n -------\n out: Function\n Constant function.\n\n Examples\n --------\n > var fcn = constantFunction( 3.14 );\n > var v = fcn()\n 3.14\n > v = fcn()\n 3.14\n > v = fcn()\n 3.14\n\n See Also\n --------\n argumentFunction, identity\n","constantStream":"\nconstantStream( value[, options] )\n Returns a readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream( 'beep', opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream\n","constantStream.factory":"\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );","constantStream.objectMode":"\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream","constructorName":"\nconstructorName( val )\n Determines the name of a value's constructor.\n\n Parameters\n ----------\n val: any\n Input value.\n\n Returns\n -------\n out: string\n Name of a value's constructor.\n\n Examples\n --------\n > var v = constructorName( 'a' )\n 'String'\n > v = constructorName( {} )\n 'Object'\n > v = constructorName( true )\n 'Boolean'\n\n See Also\n --------\n functionName\n","contains":"\ncontains( value, searchValue[, position] )\n Tests if an array-like value contains a search value.\n\n When `value` is a string, the function checks whether the characters of the\n search string are found in the input string. The search is case-sensitive.\n\n When `value` is an array-like object, the function checks whether the input\n array contains an element strictly equal to the specified search value.\n\n For strings, this function is modeled after `String.prototype.includes`,\n part of the ECMAScript 6 specification. This function is different from a\n call to `String.prototype.includes.call` insofar as type-checking is\n performed for all arguments.\n\n The function does distinguish between positive and negative zero.\n\n If `position < 0`, the search is performed for the entire input array or\n string.\n\n\n Parameters\n ----------\n value: ArrayLike\n Input value.\n\n searchValue: any\n Value to search for.\n\n position: integer (optional)\n Position at which to start searching for `searchValue`. Default: `0`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input value contains another value.\n\n Examples\n --------\n > var bool = contains( 'Hello World', 'World' )\n true\n > bool = contains( 'Hello World', 'world' )\n false\n > bool = contains( [ 1, 2, 3, 4 ], 2 )\n true\n > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n true\n\n // Supply a position:\n > bool = contains( 'Hello World', 'Hello', 6 )\n false\n > bool = contains( [ true, NaN, false ], true, 1 )\n false\n\n","convertArray":"\nconvertArray( arr, dtype )\n Converts an input array to an array of a different data type.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Array to convert.\n\n dtype: string\n Output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n > var out = convertArray( arr, 'float32' )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArraySame\n","convertArraySame":"\nconvertArraySame( x, y )\n Converts an input array to the same data type as a second input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Array to convert.\n\n y: Array|TypedArray\n Array having desired output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = new Float32Array( 0 );\n > var out = convertArraySame( x, y )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArray\n","convertPath":"\nconvertPath( from, to )\n Converts between POSIX and Windows paths.\n\n Parameters\n ----------\n from: string\n Input path.\n\n to: string\n Output path convention: 'win32', 'mixed', or 'posix'.\n\n Returns\n -------\n out: string\n Converted path.\n\n Examples\n --------\n > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n 'c:\\foo\\bar\\beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n 'c:/foo/bar/beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\n 'C:\\\\foo\\bar\\beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\n 'C:/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n\n","copy":"\ncopy( value[, level] )\n Copy or deep clone a value to an arbitrary depth.\n\n The implementation can handle circular references.\n\n If a `Number`, `String`, or `Boolean` object is encountered, the value is\n cloned as a primitive. This behavior is intentional.\n\n For objects, the implementation only copies enumerable keys and their\n associated property descriptors.\n\n The implementation only checks whether basic `Objects`, `Arrays`, and class\n instances are extensible, sealed, and/or frozen.\n\n Functions are not cloned; their reference is copied.\n\n The implementation supports custom error types which are `Error` instances\n (e.g., ES2015 subclasses).\n\n Support for copying class instances is inherently fragile. Any instances\n with privileged access to variables (e.g., within closures) cannot be\n cloned. This stated, basic copying of class instances is supported. Provided\n an environment which supports ES5, the implementation is greedy and performs\n a deep clone of any arbitrary class instance and its properties. The\n implementation assumes that the concept of `level` applies only to the class\n instance reference, but not to its internal state.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n level: integer (optional)\n Copy depth. Default: Infinity.\n\n Returns\n -------\n out: any\n Value copy.\n\n Examples\n --------\n > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > var out = copy( value )\n [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n > var bool = ( value[ 0 ].c === out[ 0 ].c )\n false\n\n // Set the `level` option to limit the copy depth:\n > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > out = copy( value, 1 );\n > bool = ( value[ 0 ] === out[ 0 ] )\n true\n > bool = ( value[ 0 ].c === out[ 0 ].c )\n true\n\n\n See Also\n --------\n merge\n","copyBuffer":"\ncopyBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = array2buffer( [ 1, 2, 3, 4 ] );\n > var b2 = copyBuffer( b1 )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n allocUnsafe, Buffer\n","countBy":"\ncountBy( collection, [options,] indicator )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = countBy( collection, indicator )\n { 'b': 3, 'other': 1 }\n\n See Also\n --------\n group, groupBy\n","countByAsync":"\ncountByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"even\": 2, \"odd\": 1 }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync\n","countByAsync.factory":"\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync","currentYear":"\ncurrentYear()\n Returns the current year.\n\n Returns\n -------\n out: integer\n Current year.\n\n Examples\n --------\n > var y = currentYear()\n \n\n See Also\n --------\n isCurrentYear\n","curry":"\ncurry( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curry( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curry( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curry( obj.greet, obj );\n > var str = f( 'Hello' )( 'there' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curryRight, uncurry, uncurryRight\n","curryRight":"\ncurryRight( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n This function applies arguments starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curryRight( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curryRight( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curryRight( obj.greet, obj );\n > var str = f( 'there' )( 'Hello' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curry, uncurry, uncurryRight\n","cwd":"\ncwd()\n Returns the current working directory.\n\n Returns\n -------\n path: string\n Current working directory of the process.\n\n Examples\n --------\n > var dir = cwd()\n '/path/to/current/working/directory'\n\n See Also\n --------\n chdir\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar American-English words.\n\n Returns\n -------\n out: Array\n List of familiar American-English words.\n\n Examples\n --------\n > var list = DALE_CHALL_NEW()\n [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n References\n ----------\n - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n the new Dale-Chall readability formula*. Brookline Books.\n .\n\n","datasets":"\ndatasets( name[, options] )\n Returns a dataset.\n\n The function forwards provided options to the dataset interface specified\n by `name`.\n\n Parameters\n ----------\n name: string\n Dataset name.\n\n options: Object (optional)\n Function options.\n\n Returns\n -------\n out: any\n Dataset.\n\n Examples\n --------\n > var out = datasets( 'MONTH_NAMES_EN' )\n [ 'January', 'February', ... ]\n > var opts = { 'data': 'cities' };\n > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n [ {...}, {...}, ... ]\n\n","DataType":"\nDataType( value[, options] )\n Data type constructor.\n\n Parameters\n ----------\n value: any\n Data type value.\n\n options: Object (optional)\n Constructor options.\n\n options.description: string (optional)\n Data type description.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteLength\n 8\n\n\nDataType.name\n Constructor name.\n\n Returns\n -------\n out: string\n Constructor name.\n\n Examples\n --------\n > DataType.name\n 'DataType'\n\n\nDataType.prototype.alignment\n Alignment (in bytes) for the data type.\n\n If a data type does not have a known alignment, the returned value is -1.\n\n Returns\n -------\n out: integer\n Alignment (in bytes).\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.alignment\n 8\n\n\nDataType.prototype.byteLength\n Size (in bytes) of the data type.\n\n If a data type does not have a known size, the returned value is -1.\n\n Returns\n -------\n out: integer\n Byte length (in bytes).\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteLength\n 8\n\n\nDataType.prototype.byteOrder\n Data type byte order.\n\n May be one of the following values:\n\n - host: host platform byte order.\n - little-endian: little-endian byte order.\n - big-endian: big-endian byte order.\n\n Returns\n -------\n out: string\n Byte order.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteOrder\n 'host'\n\n\nDataType.prototype.char\n Single letter character abbreviation for the data type.\n\n If a data type does not have a corresponding single letter character\n abbreviation, the returned value is an empty string.\n\n Returns\n -------\n out: string\n Single letter character abbreviation.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.char\n 'd'\n\n\nDataType.prototype.description\n Data type description.\n\n If a data type does not have an associated description, the returned value\n is an empty string.\n\n Returns\n -------\n out: string\n Description.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.description\n '...'\n\n\nDataType.prototype.enum\n Enumeration constant for the data type.\n\n If a data type does not have a corresponding known enumeration constant, the\n returned value is -1.\n\n Returns\n -------\n out: integer\n Enumeration constant.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.enum\n \n\n\nDataType.prototype.value\n Raw (original) data type value.\n\n Returns\n -------\n out: any\n Data type value.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.value\n 'float64'\n\n\nDataType.prototype.toJSON()\n Serializes a data type instance as a JSON object.\n\n Returns\n -------\n out: Object\n JSON object.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.toJSON()\n {...}\n\n\nDataType.prototype.toString()\n Serializes a data type instance to a string.\n\n Returns\n -------\n out: string\n Serialized string.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.toString()\n 'float64'\n\n\nDataType.prototype.valueOf()\n Converts a data type instance to a primitive.\n\n This method returns the same value as `#.toString()`.\n\n Returns\n -------\n out: string\n Primitive value.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.valueOf()\n 'float64'\n\n See Also\n --------\n ndarray, ndarrayDataType\n\n","DataType.name":"\nDataType.name\n Constructor name.\n\n Returns\n -------\n out: string\n Constructor name.\n\n Examples\n --------\n > DataType.name\n 'DataType'","DataType.prototype.alignment":"\nDataType.prototype.alignment\n Alignment (in bytes) for the data type.\n\n If a data type does not have a known alignment, the returned value is -1.\n\n Returns\n -------\n out: integer\n Alignment (in bytes).\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.alignment\n 8","DataType.prototype.byteLength":"\nDataType.prototype.byteLength\n Size (in bytes) of the data type.\n\n If a data type does not have a known size, the returned value is -1.\n\n Returns\n -------\n out: integer\n Byte length (in bytes).\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteLength\n 8","DataType.prototype.byteOrder":"\nDataType.prototype.byteOrder\n Data type byte order.\n\n May be one of the following values:\n\n - host: host platform byte order.\n - little-endian: little-endian byte order.\n - big-endian: big-endian byte order.\n\n Returns\n -------\n out: string\n Byte order.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteOrder\n 'host'","DataType.prototype.char":"\nDataType.prototype.char\n Single letter character abbreviation for the data type.\n\n If a data type does not have a corresponding single letter character\n abbreviation, the returned value is an empty string.\n\n Returns\n -------\n out: string\n Single letter character abbreviation.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.char\n 'd'","DataType.prototype.description":"\nDataType.prototype.description\n Data type description.\n\n If a data type does not have an associated description, the returned value\n is an empty string.\n\n Returns\n -------\n out: string\n Description.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.description\n '...'","DataType.prototype.enum":"\nDataType.prototype.enum\n Enumeration constant for the data type.\n\n If a data type does not have a corresponding known enumeration constant, the\n returned value is -1.\n\n Returns\n -------\n out: integer\n Enumeration constant.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.enum\n ","DataType.prototype.value":"\nDataType.prototype.value\n Raw (original) data type value.\n\n Returns\n -------\n out: any\n Data type value.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.value\n 'float64'","DataType.prototype.toJSON":"\nDataType.prototype.toJSON()\n Serializes a data type instance as a JSON object.\n\n Returns\n -------\n out: Object\n JSON object.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.toJSON()\n {...}","DataType.prototype.toString":"\nDataType.prototype.toString()\n Serializes a data type instance to a string.\n\n Returns\n -------\n out: string\n Serialized string.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.toString()\n 'float64'","DataType.prototype.valueOf":"\nDataType.prototype.valueOf()\n Converts a data type instance to a primitive.\n\n This method returns the same value as `#.toString()`.\n\n Returns\n -------\n out: string\n Primitive value.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.valueOf()\n 'float64'\n\n See Also\n --------\n ndarray, ndarrayDataType","DataView":"\nDataView( buffer[, byteOffset[, byteLength]] )\n Returns a data view representing a provided array buffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer|SharedArrayBuffer\n Array buffer.\n\n byteOffset: integer (optional)\n Offset (in bytes) to the first byte in the array buffer for the new view\n to reference. Default: 0.\n\n byteLength: integer (optional)\n Number of elements in the byte array. If not provided, the view's length\n will equal the buffer's length.\n\n Returns\n -------\n out: DataView\n A data view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n > var dv = new DataView( buf )\n \n\n\nDataView.prototype.buffer\n Read-only property which returns the underlying array buffer.\n\n Examples\n --------\n > var buf1 = new ArrayBuffer( 5 );\n > var dv = new DataView( buf1 );\n > var buf2 = dv.buffer\n \n > var b = ( buf1 === buf2 )\n true\n\n\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf );\n > dv.byteLength\n 5\n\n\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf, 2 );\n > dv.byteLength\n 3\n > dv.byteOffset\n 2\n\n\nTODO: document properties/methods\n\n\n See Also\n --------\n ArrayBuffer, typedarray\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n Read-only property which returns the underlying array buffer.\n\n Examples\n --------\n > var buf1 = new ArrayBuffer( 5 );\n > var dv = new DataView( buf1 );\n > var buf2 = dv.buffer\n \n > var b = ( buf1 === buf2 )\n true","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf );\n > dv.byteLength\n 5","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf, 2 );\n > dv.byteLength\n 3\n > dv.byteOffset\n 2","datespace":"\ndatespace( start, stop[, length][ , options] )\n Generates an array of linearly spaced dates.\n\n Parameters\n ----------\n start: number\n Start time as either a `Date` object, Unix timestamp, JavaScript\n timestamp, or date string.\n\n stop: number\n Stop time as either a `Date` object, Unix timestamp, JavaScript\n timestamp, or date string.\n\n length: integer (optional)\n Length of output array. Default: `100`.\n\n options: Object (optional)\n Options.\n\n options.round: string (optional)\n Specifies how sub-millisecond times should be rounded:\n [ 'floor', 'ceil', 'round' ]. Default: 'floor'.\n\n Returns\n -------\n arr: Array\n Array of dates.\n\n Examples\n --------\n > var stop = '2014-12-02T07:00:54.973Z';\n > var start = new Date( stop ) - 60000;\n > var arr = datespace( start, stop, 6 )\n [...]\n\n // Equivalent of Math.ceil():\n > var opts = { 'round': 'ceil' };\n > arr = datespace( 1417503655000, 1417503655001, 3, opts )\n [...]\n\n See Also\n --------\n linspace, logspace\n","dayOfQuarter":"\ndayOfQuarter( [month[, day, year]] )\n Returns the day of the quarter.\n\n By default, the function returns the day of the quarter for the current date\n (according to local time). To determine the day of the quarter for a\n particular day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the quarter.\n\n Examples\n --------\n > var day = dayOfQuarter()\n \n > day = dayOfQuarter( new Date() )\n \n > day = dayOfQuarter( 12, 31, 2017 )\n 92\n\n // Other ways to supply month:\n > day = dayOfQuarter( 'dec', 31, 2017 )\n 92\n > day = dayOfQuarter( 'december', 31, 2017 )\n 92\n\n See Also\n --------\n dayOfYear\n","dayOfYear":"\ndayOfYear( [month[, day, year]] )\n Returns the day of the year.\n\n By default, the function returns the day of the year for the current date\n (according to local time). To determine the day of the year for a particular\n day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the year.\n\n Examples\n --------\n > var day = dayOfYear()\n \n > day = dayOfYear( new Date() )\n \n > day = dayOfYear( 12, 31, 2016 )\n 366\n\n // Other ways to supply month:\n > day = dayOfYear( 'dec', 31, 2016 )\n 366\n > day = dayOfYear( 'december', 31, 2016 )\n 366\n\n See Also\n --------\n dayOfQuarter\n","daysInMonth":"\ndaysInMonth( [month[, year]] )\n Returns the number of days in a month.\n\n By default, the function returns the number of days in the current month\n of the current year (according to local time). To determine the number of\n days for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Days in a month.\n\n Examples\n --------\n > var num = daysInMonth()\n \n > num = daysInMonth( 2 )\n \n > num = daysInMonth( 2, 2016 )\n 29\n > num = daysInMonth( 2, 2017 )\n 28\n\n // Other ways to supply month:\n > num = daysInMonth( 'feb', 2016 )\n 29\n > num = daysInMonth( 'february', 2016 )\n 29\n\n See Also\n --------\n daysInYear\n","daysInYear":"\ndaysInYear( [value] )\n Returns the number of days in a year according to the Gregorian calendar.\n\n By default, the function returns the number of days in the current year\n (according to local time). To determine the number of days for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of days in a year.\n\n Examples\n --------\n > var num = daysInYear()\n \n > num = daysInYear( 2016 )\n 366\n > num = daysInYear( 2017 )\n 365\n\n See Also\n --------\n daysInMonth\n","ddot":"\nddot( x, y[, dim] )\n Computes the dot product of two double-precision floating-point vectors.\n\n If provided at least one input array having more than one dimension, the\n input arrays are broadcasted to a common shape.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function computes the dot product for each pair\n of vectors in `x` and `y` according to the specified dimension index.\n\n The size of the contracted dimension must be the same for both input arrays.\n\n The function resolves the dimension index for which to compute the dot\n product *before* broadcasting.\n\n If provided empty vectors, the dot product is `0`.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float64' data type. Must have at least\n one dimension and be broadcast-compatible with the second input array.\n\n y: ndarray\n Second input array. Must have a 'float64' data type. Must have at least\n one dimension and be broadcast-compatible with the first input array.\n\n dim: integer (optional)\n Dimension index for which to compute the dot product. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n out: ndarray\n The dot product. The output array has the same data type as the input\n arrays and has a shape which is determined by broadcasting and excludes\n the contracted dimension.\n\n Examples\n --------\n > var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var x = array( xbuf );\n > var ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var y = array( ybuf );\n > var z = ddot( x, y )\n [ -5.0 ]\n\n See Also\n --------\n base.strided.ddot, gdot, sdot\n","debugSinkStream":"\ndebugSinkStream( [options,] [clbk] )\n Returns a writable stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > var s = debugSinkStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream","debugStream":"\ndebugStream( [options,] [clbk] )\n Returns a transform stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = debugStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","debugStream.factory":"\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );","debugStream.objectMode":"\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream","decorateAfter":"\ndecorateAfter( fcn, arity, after[, thisArg] )\n Decorates a provided function such that the function's return value is\n provided as an argument to another function.\n\n Decorators are intended to be transparent, meaning that, when interfacing\n with an API, the decorated API should have the same signature (i.e., number\n of parameters) as the decorated function.\n\n Thus, a typical value for `arity` is `fcn.length`. This function does not\n require equality, however, and the `arity` argument is allowed to diverge\n from that of the decorated function. Specifying a differing `arity` does\n *not* affect function evaluation behavior, as the returned function passes\n all provided arguments to the decorated function.\n\n If the `after` function returns `undefined`, the returned decorator returns\n the return value of the decorated function `fcn`; otherwise, the returned\n decorator returns the return value of `after`.\n\n The returned decorator supports an `arity` less than or equal to `10` (i.e.,\n the maximum arity of the returned function is `10`). For an arity greater\n than `10`, the returned function has an arity equal to `0`. While this\n violates strict notions of a decorator, for all practical purposes, this is\n unlikely to be an issue, as the vast majority of functions have fewer than\n `10` parameters and the need for explicitly checking function length is\n relatively uncommon.\n\n Common use cases for decorating a function with additional actions *after*\n invocation include logging, capturing invocation statistics, and validating\n return values.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5\n\n\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n\n Code generation may be problematic in browser contexts enforcing a strict\n content security policy] (CSP). If running in or targeting an environment\n with a CSP, avoid using code generation.\n\n For non-native functions, the function supports returning a decorator whose\n API exactly matches the API of the decorated function, including function\n length and parameter names.\n\n For native functions, due to how native functions serialize to strings, the\n function generates placeholder parameter names, which are unlikely to match\n the canonical parameter names. Using placeholder parameter names ensures\n that the length of the decorator (i.e., number of parameters) matches the\n decorated function and, except in scenarios involving function source code\n inspection, will not affect runtime behavior.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter.factory( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5\n\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n\n Code generation may be problematic in browser contexts enforcing a strict\n content security policy] (CSP). If running in or targeting an environment\n with a CSP, avoid using code generation.\n\n For non-native functions, the function supports returning a decorator whose\n API exactly matches the API of the decorated function, including function\n length and parameter names.\n\n For native functions, due to how native functions serialize to strings, the\n function generates placeholder parameter names, which are unlikely to match\n the canonical parameter names. Using placeholder parameter names ensures\n that the length of the decorator (i.e., number of parameters) matches the\n decorated function and, except in scenarios involving function source code\n inspection, will not affect runtime behavior.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter.factory( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5","deepEqual":"\ndeepEqual( a, b )\n Tests for deep equality between two values.\n\n Parameters\n ----------\n a: any\n First comparison value.\n\n b: any\n Second comparison value.\n\n Returns\n -------\n out: boolean\n Boolean indicating if `a` is deep equal to `b`.\n\n Examples\n --------\n > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n true\n\n > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n false\n\n > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n false\n\n See Also\n --------\n isStrictEqual, isSameValue\n","deepGet":"\ndeepGet( obj, path[, options] )\n Returns a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: any\n Nested property value.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a.b.c' )\n 'd'\n\n // Specify a custom separator via the `sep` option:\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n 'd'\n\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet\n","deepGet.factory":"\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet","deepHasOwnProp":"\ndeepHasOwnProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path.\n\n The function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepHasOwnProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet","deepHasProp":"\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasProp.factory":"\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet","deepPluck":"\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n See Also\n --------\n deepGet, deepSet\n","deepSet":"\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj1 = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj1, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > var obj2 = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj2, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj2\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > var obj3 = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj3, 'a.e.c', 'boop', { 'create': true } );\n > obj3\n { 'a': { 'b': { 'c': 'd' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep set function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck\n","deepSet.factory":"\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep set function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck","defineMemoizedProperty":"\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n See Also\n --------\n setMemoizedReadOnly, defineProperty\n","defineProperties":"\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default: undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n See Also\n --------\n defineProperty, setReadOnly\n","defineProperty":"\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n defineProperties, setReadOnly\n","dirname":"\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n See Also\n --------\n extname\n","dotcase":"\ndotcase( str )\n Converts a string to dot case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Dot-cased string.\n\n Examples\n --------\n > var out = dotcase( 'Hello World!' )\n 'hello.world'\n > out = dotcase( 'beep boop' )\n 'beep.boop'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n\n Returns\n -------\n list: Object\n Doubly linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the first list node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node. For its third argument, the\n method accepts a location: 'before' or 'after'. Default: 'after'.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation. For its sole argument, the method accepts a\n direction: 'forward' or 'reverse'. Default: 'forward'.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = DoublyLinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n LinkedList, Stack\n","doUntil":"\ndoUntil( fcn, predicate[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doUntil( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntilAsync, doUntilEach, doWhile, until, whilst\n","doUntilAsync":"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from one).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is falsy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doUntilAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, untilAsync, whileAsync\n","doUntilEach":"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doUntilEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, untilEach\n","doUntilEachRight":"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doUntilEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, untilEachRight\n","doWhile":"\ndoWhile( fcn, predicate[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doWhile( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, doWhileEach, until, whilst\n","doWhileAsync":"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from one).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is truthy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doWhileAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhile, untilAsync, whileAsync\n","doWhileEach":"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doWhileEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, whileEach\n","doWhileEachRight":"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doWhileEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, whileEachRight\n","dswap":"\ndswap( x, y[, dim] )\n Interchanges two double-precision floating-point vectors.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function interchanges each pair of vectors in `x`\n and `y` according to the specified dimension index.\n\n Both input arrays must have the same shape.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float64' data type. Must have at least\n one dimension and must have the same shape as the second input array.\n\n y: ndarray\n Second input array. Must have a 'float64' data type. Must have at least\n one dimension and must have the same shape as the first input array.\n\n dim: integer (optional)\n Dimension index along which to interchange vectors. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > dswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dswap, gswap, sswap\n","E":"\nE\n Euler's number.\n\n Examples\n --------\n > E\n 2.718281828459045\n\n","EMOJI":"\nEMOJI()\n Returns an emoji database.\n\n Returns\n -------\n out: Array\n Emoji database.\n\n Examples\n --------\n > var data = EMOJI()\n [ {...}, ... ]\n\n See Also\n --------\n EMOJI_CODE_PICTO, EMOJI_PICTO_CODE\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n Returns an object mapping emoji codes to pictographs.\n\n Returns\n -------\n out: Object\n An object mapping emoji codes to pictographs.\n\n Examples\n --------\n > var out = EMOJI_CODE_PICTO()\n\n See Also\n --------\n EMOJI, EMOJI_PICTO_CODE\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n Returns an object mapping emoji pictographs to codes.\n\n Returns\n -------\n out: Object\n An object mapping emoji pictographs to codes.\n\n Examples\n --------\n > var out = EMOJI_PICTO_CODE()\n\n See Also\n --------\n EMOJI, EMOJI_CODE_PICTO\n","emptyStream":"\nemptyStream( [options] )\n Returns an \"empty\" readable stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = emptyStream();\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream\n","emptyStream.factory":"\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );","emptyStream.objectMode":"\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream","endsWith":"\nendsWith( str, search[, len] )\n Tests if a string ends with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer (optional)\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, returning\n the same output as `str.length + len`. Default: `str.length`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string ends with the characters of another\n string.\n\n Examples\n --------\n > var bool = endsWith( 'beep', 'ep' )\n true\n > bool = endsWith( 'Beep', 'op' )\n false\n > bool = endsWith( 'Beep', 'ee', 3 )\n true\n > bool = endsWith( 'Beep', 'ee', -1 )\n true\n > bool = endsWith( 'beep', '' )\n true\n\n See Also\n --------\n startsWith\n","enumerableProperties":"\nenumerableProperties( value )\n Returns an array of an object's own enumerable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = enumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerablePropertiesIn, enumerablePropertySymbols, inheritedEnumerableProperties, objectKeys, nonEnumerableProperties, properties\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = enumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbolsIn, inheritedEnumerableProperties, keysIn, nonEnumerablePropertiesIn, propertiesIn\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value )\n Returns an array of an object's own enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedEnumerablePropertySymbols, objectKeys, nonEnumerablePropertySymbols, propertySymbols\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedEnumerablePropertySymbols, keysIn, nonEnumerablePropertySymbolsIn, propertySymbolsIn\n","ENV":"\nENV\n An object containing the user environment.\n\n Examples\n --------\n > var user = ENV.USER\n \n\n See Also\n --------\n ARGV\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n\n Examples\n --------\n > EPS\n 2.220446049250313e-16\n\n See Also\n --------\n FLOAT32_EPS\n","error2json":"\nerror2json( error )\n Returns a JSON representation of an error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n The JSON object is guaranteed to have the following properties:\n\n - type: error type.\n - message: error message.\n\n The only standardized cross-platform property is `message`. Depending on the\n platform, the following properties *may* be present:\n\n - name: error name.\n - stack: stack trace.\n - code: error code (Node.js system errors).\n - errno: error code string (Node.js system errors).\n - syscall: string representing the failed system call (Node.js system\n errors).\n\n The function also serializes all enumerable properties.\n\n The implementation supports custom error types and sets the `type` field to\n the closest built-in error type.\n\n Parameters\n ----------\n error: Error\n Error to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var err = new Error( 'beep' );\n > var json = error2json( err )\n \n\n See Also\n --------\n reviveError\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n\n Examples\n --------\n > EULERGAMMA\n 0.5772156649015329\n\n","every":"\nevery( collection )\n Tests whether all elements in a collection are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 1, 1, 1, 1, 1 ];\n > var bool = every( arr )\n true\n\n See Also\n --------\n any, everyBy, forEach, none, some\n","everyBy":"\neveryBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyBy( arr, positive )\n true\n\n See Also\n --------\n anyBy, everyByRight, forEach, noneBy, someBy\n","everyByAsync":"\neveryByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync\n","everyByAsync.factory":"\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync","everyByRight":"\neveryByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyByRight( arr, positive )\n true\n\n See Also\n --------\n anyBy, every, everyBy, forEachRight, noneByRight, someByRight\n","everyByRightAsync":"\neveryByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync","everyInBy":"\neveryInBy( object, predicate[, thisArg ] )\n Test whether all properties (own and inherited) of an object pass a\n test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - object: the input object.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var o = {a: 1, b: 2, c: 3};\n > var bool = everyInBy( o, positive )\n true\n\n See Also\n --------\n anyInBy, noneInBy, someInBy, everyOwnBy\n","everyOwnBy":"\neveryOwnBy( object, predicate[, thisArg ] )\n Tests whether every own property of an object pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > var bool = everyOwnBy( obj, positive )\n true\n\n See Also\n --------\n anyOwnBy, everyInBy, noneOwnBy, someOwnBy, everyBy\n","evil":"\nevil( str )\n Alias for `eval` global.\n\n A reference to `eval` is treated differently by the compiler. For example,\n when evaluating code containing block-scoped declarations (e.g., `let`,\n `const`, `function`, `class`), the compiler may throw an `error` complaining\n that block-scoped declarations are not yet supported outside of\n `strict mode`. One possible workaround is to include `\"use strict\";` in the\n evaluated code.\n\n Parameters\n ----------\n str: string\n Code to evaluate.\n\n Returns\n -------\n out: any\n Returned value if applicable.\n\n Examples\n --------\n > var v = evil( '5*4*3*2*1' )\n 120\n\n","EXEC_PATH":"\nEXEC_PATH\n Absolute pathname of the executable which started the current Node.js\n process.\n\n Examples\n --------\n > EXEC_PATH\n \n\n","exists":"\nexists( path, clbk )\n Asynchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n clbk: Function\n Callback to invoke after testing for path existence. A callback may\n accept a single argument, a boolean indicating whether a path exists, or\n two arguments, an error argument and a boolean, matching the error-first\n callback convention used in most asynchronous Node.js APIs.\n\n Examples\n --------\n > function done( error, bool ) { console.log( bool ); };\n > exists( './beep/boop', done );\n\n\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir\n","exists.sync":"\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir","expandAcronyms":"\nexpandAcronyms( str )\n Expands acronyms in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded acronyms.\n\n Examples\n --------\n > var str = 'LOL, this is fun. I am ROFL.';\n > var out = expandAcronyms( str )\n 'laughing out loud, this is fun. I am rolling on the floor laughing.'\n\n > str = 'brb, I need to check my mail. thx!';\n > out = expandAcronyms( str )\n 'be right back, I need to check my mail. thanks!'\n\n See Also\n --------\n expandContractions\n","expandContractions":"\nexpandContractions( str )\n Expands all contractions to their formal equivalents.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded contractions.\n\n Examples\n --------\n > var str = 'I won\\'t be able to get y\\'all out of this one.';\n > var out = expandContractions( str )\n 'I will not be able to get you all out of this one.'\n\n > str = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\n > out = expandContractions( str )\n 'It ought not to be my fault, because, you know, I did not know'\n\n","extname":"\nextname( filename )\n Returns a filename extension.\n\n Parameters\n ----------\n filename: string\n Filename.\n\n Returns\n -------\n ext: string\n Filename extension.\n\n Examples\n --------\n > var ext = extname( 'index.js' )\n '.js'\n\n See Also\n --------\n dirname\n","FancyArray":"\nFancyArray( dtype, buffer, shape, strides, offset, order[, options] )\n Returns a FancyArray instance.\n\n A FancyArray is an ndarray which supports slicing via indexing expressions.\n\n A FancyArray is an ndarray instance and supports all ndarray options,\n attributes, and methods. A FancyArray can be consumed by any API which\n supports ndarray instances.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on ndarray views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use and\n scripting. For performance critical applications, prefer equivalent\n functional APIs supporting ndarray instances.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n ndarray: FancyArray\n FancyArray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nFancyArray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nFancyArray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nFancyArray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nFancyArray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nFancyArray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nFancyArray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nFancyArray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nFancyArray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","FancyArray.prototype.data":"\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","FancyArray.prototype.length":"\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","FancyArray.prototype.order":"\nFancyArray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray","fastmath.abs":"\nfastmath.abs( x )\n Computes an absolute value.\n\n This implementation is not IEEE 754 compliant. If provided `-0`, the\n function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Absolute value.\n\n Examples\n --------\n > var v = fastmath.abs( -1.0 )\n 1.0\n > v = fastmath.abs( 2.0 )\n 2.0\n > v = fastmath.abs( 0.0 )\n 0.0\n > v = fastmath.abs( -0.0 )\n -0.0\n > v = fastmath.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs\n","fastmath.acosh":"\nfastmath.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n will return `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var v = fastmath.acosh( 1.0 )\n 0.0\n > v = fastmath.acosh( 2.0 )\n ~1.317\n > v = fastmath.acosh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.acosh( 1.0e308 )\n Infinity\n\n See Also\n --------\n base.acosh\n","fastmath.ampbm":"\nfastmath.ampbm( x, y )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n The algorithm computes only an approximation.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.ampbm( 5.0, 12.0 )\n ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot","fastmath.asinh":"\nfastmath.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var v = fastmath.asinh( 0.0 )\n 0.0\n > v = fastmath.asinh( 2.0 )\n ~1.444\n > v = fastmath.asinh( -2.0 )\n ~-1.444\n > v = fastmath.asinh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.asinh( 1.0e200 )\n Infinity\n\n // The function underflows for small `x`:\n > v = fastmath.asinh( 1.0e-50 )\n 0.0\n\n See Also\n --------\n base.asinh\n","fastmath.atanh":"\nfastmath.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var v = fastmath.atanh( 0.0 )\n 0.0\n > v = fastmath.atanh( 0.9 )\n ~1.472\n > v = fastmath.atanh( 1.0 )\n Infinity\n > v = fastmath.atanh( -1.0 )\n -Infinity\n > v = fastmath.atanh( NaN )\n NaN\n\n // The function underflows for small `x`:\n > v = fastmath.atanh( 1.0e-17 )\n 0.0\n\n See Also\n --------\n base.atanh\n","fastmath.hypot":"\nfastmath.hypot( x, y )\n Computes the hypotenuse.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.hypot( -5.0, 12.0 )\n 13.0\n\n // For a sufficiently large `x` and/or `y`, the function overflows:\n > h = fastmath.hypot( 1.0e154, 1.0e154 )\n Infinity\n\n // For sufficiently small `x` and/or `y`, the function underflows:\n > h = fastmath.hypot( 1e-200, 1.0e-200 )\n 0.0\n\n See Also\n --------\n base.hypot\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n\n This function provides a performance boost when requiring only approximate\n computations for integer arguments.\n\n For high-precision applications, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer binary logarithm (base two).\n\n Examples\n --------\n > var v = fastmath.log2Uint32( 4 >>> 0 )\n 2\n > v = fastmath.log2Uint32( 8 >>> 0 )\n 3\n > v = fastmath.log2Uint32( 9 >>> 0 )\n 3\n\n See Also\n --------\n base.log2\n","fastmath.max":"\nfastmath.max( x, y )\n Returns the maximum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = fastmath.max( 3.14, 4.2 )\n 4.2\n > v = fastmath.max( 3.14, NaN )\n NaN\n > v = fastmath.max( NaN, 3.14 )\n 3.14\n > v = fastmath.max( -0.0, +0.0 )\n +0.0\n > v = fastmath.max( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max\n","fastmath.min":"\nfastmath.min( x, y )\n Returns the minimum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = fastmath.min( 3.14, 4.2 )\n 3.14\n > v = fastmath.min( 3.14, NaN )\n NaN\n > v = fastmath.min( NaN, 3.14 )\n 3.14\n > v = fastmath.min( -0.0, +0.0 )\n +0.0\n > v = fastmath.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.min\n","fastmath.powint":"\nfastmath.powint( x, y )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n\n This function is not recommended for high-precision applications due to\n error accumulation.\n\n If provided a negative exponent, the function first computes the reciprocal\n of the base and then evaluates the exponential function. This can introduce\n significant error.\n\n Parameters\n ----------\n x: number\n Base.\n\n y: integer\n Signed 32-bit integer exponent.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = fastmath.powint( 2.0, 3 )\n 8.0\n > v = fastmath.powint( 3.14, 0 )\n 1.0\n > v = fastmath.powint( 2.0, -2 )\n 0.25\n > v = fastmath.powint( 0.0, 0 )\n 1.0\n > v = fastmath.powint( -3.14, 1 )\n -3.14\n > v = fastmath.powint( NaN, 0 )\n NaN\n\n See Also\n --------\n base.pow\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n Prefer hardware `sqrt` over a software implementation.\n\n When using a software `sqrt`, this function provides a performance boost\n when an application requires only approximate computations for integer\n arguments.\n\n For applications requiring high-precision, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer square root.\n\n Examples\n --------\n > var v = fastmath.sqrtUint32( 9 >>> 0 )\n 3\n > v = fastmath.sqrtUint32( 2 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 3 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 0 >>> 0 )\n 0\n\n See Also\n --------\n base.sqrt\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common female first names.\n\n Examples\n --------\n > var list = FEMALE_FIRST_NAMES_EN()\n [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. \"Moby Word II.\" .\n\n See Also\n --------\n MALE_FIRST_NAMES_EN\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n\n Returns\n -------\n queue: Object\n First-in-first-out queue.\n\n queue.clear: Function\n Clears the queue.\n\n queue.first: Function\n Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.iterator: Function\n Returns an iterator for iterating over a queue. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from queue mutation during\n iteration, a returned iterator **always** iterates over a queue\n \"snapshot\", which is defined as the list of queue elements at the time\n of the method's invocation.\n\n queue.last: Function\n Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.length: integer\n Queue length.\n\n queue.pop: Function\n Removes and returns the current \"first-out\" value from the queue. If the\n queue is empty, the returned value is `undefined`.\n\n queue.push: Function\n Adds a value to the queue.\n\n queue.toArray: Function\n Returns an array of queue values.\n\n queue.toJSON: Function\n Serializes a queue as JSON.\n\n Examples\n --------\n > var q = FIFO();\n > q.push( 'foo' ).push( 'bar' );\n > q.length\n 2\n > q.pop()\n 'foo'\n > q.length\n 1\n > q.pop()\n 'bar'\n > q.length\n 0\n\n See Also\n --------\n Stack\n","filledarray":"\nfilledarray( [dtype] )\n Creates a filled array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarray()\n \n > arr = filledarray( 'float32' )\n \n\n\nfilledarray( value, length[, dtype] )\n Returns a filled array having a specified length.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarray( 1.0, 5 )\n [ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n > arr = filledarray( 1, 5, 'int32' )\n [ 1, 1, 1, 1, 1 ]\n\n\nfilledarray( value, array[, dtype] )\n Creates a filled array from another array (or array-like object).\n\n Parameters\n ----------\n value: any\n Fill value.\n\n array: ArrayLikeObject\n Array from which to generate another array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\n [ 2.0, 2.0, 2.0 ]\n > var arr2 = filledarray( 1.0, arr1, 'float32' )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, iterable[, dtype] )\n Creates a filled array from an iterable.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n iterable: Iterable\n Iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = iterConstant( 3.0, {'iter': 3} );\n > var arr2 = filledarray( 1.0, arr1, 'float32' )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, buffer[, byteOffset[, length]][, dtype] )\n Returns a filled typed array view of an ArrayBuffer.\n\n The 'generic' array data type is *not* supported.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n [ 1.0, 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n filledarrayBy, typedarray\n","filledarrayBy":"\nfilledarrayBy( [dtype] )\n Creates a filled array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarrayBy()\n \n > arr = filledarrayBy( 'float32' )\n \n\n\nfilledarrayBy( length[, dtype], clbk[, thisArg] )\n Returns a filled array according to a provided callback function and having\n a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var arr = filledarrayBy( 5, clbk )\n [ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n > arr = filledarrayBy( 5, 'int32', clbk )\n [ 1, 1, 1, 1, 1 ]\n\n\nfilledarrayBy( array[, dtype], clbk[, thisArg] )\n Creates a filled array from another array (or array-like object) according\n to a provided callback function.\n\n Parameters\n ----------\n array: ArrayLikeObject\n Array from which to generate another array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\n [ 2.0, 2.0, 2.0 ]\n > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( iterable[, dtype], clbk[, thisArg] )\n Creates a filled array from an iterable according to a provided callback\n function.\n\n Parameters\n ----------\n iterable: Iterable\n Iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = iterConstant( 3.0, {'iter': 3} );\n > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( buffer[, byteOffset[, length]][, dtype], clbk[, thisArg] )\n Returns a filled typed array view of an ArrayBuffer according to a provided\n callback function.\n\n The 'generic' array data type is *not* supported.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n filledarray, typedarray\n","filterArguments":"\nfilterArguments( fcn, predicate[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n\n Only those arguments in which the predicate function returns a truthy value\n are applied to a provided function.\n\n The predicate function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > function predicate( v ) { return ( v !== 2 ); };\n > var bar = filterArguments( foo, predicate );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n maskArguments, rejectArguments, reorderArguments, reverseArguments\n","find":"\nfind( arr, [options,] clbk )\n Finds elements in an array-like object that satisfy a test condition.\n\n Parameters\n ----------\n arr: Array|TypedArray|string\n Object from which elements will be tested.\n\n options: Object (optional)\n Options.\n\n options.k: integer (optional)\n Limits the number of returned elements. The sign determines the\n direction in which to search. If set to a negative integer, the function\n searches from last element to first element. Default: arr.length.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'indices'.\n\n clbk: Function\n Function invoked for each array element. If the return value is truthy,\n the value is considered to have satisfied the test condition.\n\n Returns\n -------\n out: Array\n Array of indices, element values, or arrays of index-value pairs.\n\n Examples\n --------\n > var data = [ 30, 20, 50, 60, 10 ];\n > function condition( val ) { return val > 20; };\n > var vals = find( data, condition )\n [ 0, 2, 3 ]\n\n // Limit number of results:\n > data = [ 30, 20, 50, 60, 10 ];\n > var opts = { 'k': 2, 'returns': 'values' };\n > vals = find( data, opts, condition )\n [ 30, 50 ]\n\n // Return both indices and values as index-value pairs:\n > data = [ 30, 20, 50, 60, 10 ];\n > opts = { 'k': -2, 'returns': '*' };\n > vals = find( data, opts, condition )\n [ [ 3, 60 ], [ 2, 50 ] ]\n\n","firstChar":"\nfirstChar( str[, n][, options] )\n Returns the first character(s) of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to return. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = firstChar( 'beep' )\n 'b'\n > out = firstChar( 'Boop', 1 )\n 'B'\n > out = firstChar( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n removeFirst, last\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n Returns FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n\n Returns\n -------\n out: Array\n FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n\n Examples\n --------\n > var data = FIVETHIRTYEIGHT_FFQ()\n [ {...}, ... ]\n\n References\n ----------\n - Aschwanden, Christie. 2016. \"You Can't Trust What You Read About\n Nutrition.\" .\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n","flattenArray":"\nflattenArray( arr[, options] )\n Flattens an array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > var out = flattenArray( arr )\n [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Set the maximum depth:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2 } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n true\n\n // Deep copy:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n false\n\n\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: ArrayLike\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject\n","flattenArray.factory":"\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: ArrayLike\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject","flattenObject":"\nflattenObject( obj[, options] )\n Flattens an object.\n\n Parameters\n ----------\n obj: ObjectLike\n Object to flatten.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n out: ObjectLike\n Flattened object.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flattenObject( obj )\n { 'a.b.c': 'd' }\n\n // Set the `depth` option to flatten to a specified depth:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'depth': 1 } )\n { 'a.b': { 'c': 'd' } }\n > var bool = ( obj.a.b === out[ 'a.b' ] )\n true\n\n // Set the `delimiter` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'delimiter': '-|-' } )\n { 'a-|-b-|-c': 'd' }\n\n // Flatten arrays:\n > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n > out = flattenObject( obj, { 'flattenArrays': true } )\n { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray\n","flattenObject.factory":"\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray","flignerTest":"\nflignerTest( ...x[, options] )\n Computes the Fligner-Killeen test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = flignerTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = flignerTest( arr, { 'groups': groups } )\n\n See Also\n --------\n bartlettTest\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n Platform float word order.\n\n Possible values:\n\n - 'little-endian'\n - 'big-endian'\n - 'unknown'\n\n Examples\n --------\n > FLOAT_WORD_ORDER\n \n\n See Also\n --------\n BYTE_ORDER\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_CBRT_EPS\n 0.09921256574801247\n\n See Also\n --------\n FLOAT16_EPS, FLOAT16_SQRT_EPS, FLOAT32_CBRT_EPS, CBRT_EPS\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_EPS\n 0.0009765625\n\n See Also\n --------\n FLOAT32_EPS, EPS\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT16_EXPONENT_BIAS\n 15\n\n See Also\n --------\n FLOAT32_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_MAX\n 65504.0\n\n See Also\n --------\n FLOAT32_MAX, FLOAT64_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n\n The maximum safe half-precision floating-point integer is given by\n `2^11 - 1`.\n\n Examples\n --------\n > FLOAT16_MAX_SAFE_INTEGER\n 2047\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n\n The minimum safe half-precision floating-point integer is given by\n `-(2^11 - 1)`.\n\n Examples\n --------\n > FLOAT16_MIN_SAFE_INTEGER\n -2047\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT16_NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_PINF, FLOAT32_NINF, NINF\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_NUM_BYTES\n 2\n\n See Also\n --------\n FLOAT32_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT16_PINF\n Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_PINF, PINF\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n\n The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT16_PRECISION\n 11\n\n See Also\n --------\n FLOAT32_PRECISION, FLOAT64_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_NORMAL\n 6.103515625e-5\n\n See Also\n --------\n FLOAT16_SMALLEST_SUBNORMAL, FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_SUBNORMAL\n 5.960464477539063e-8\n\n See Also\n --------\n FLOAT16_SMALLEST_NORMAL, FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_SQRT_EPS\n 0.03125\n\n See Also\n --------\n FLOAT16_EPS, FLOAT32_SQRT_EPS, SQRT_EPS\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n Mask for excluding the sign bit of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_ABS_MASK\n 2147483647\n > base.toBinaryStringUint32( FLOAT32_ABS_MASK )\n '01111111111111111111111111111111'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_CBRT_EPS\n 0.004921566694974899\n\n See Also\n --------\n FLOAT32_EPS, FLOAT32_SQRT_EPS, CBRT_EPS\n","FLOAT32_E":"\nFLOAT32_E\n Euler's number.\n\n Examples\n --------\n > FLOAT32_E\n 2.7182817459106445\n\n See Also\n --------\n E\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EPS\n 1.1920928955078125e-7\n\n See Also\n --------\n EPS\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT32_EXPONENT_BIAS\n 127\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n Mask for the exponent of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EXPONENT_MASK\n 2139095040\n > base.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n '01111111100000000000000000000000'\n\n See Also\n --------\n FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_FOURTH_PI\n 7.853981852531433e-1\n\n See Also\n --------\n FLOAT32_HALF_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n One half times the natural logarithm of 2 as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_HALF_LN_TWO\n 0.3465735912322998\n\n See Also\n --------\n HALF_LN2\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_HALF_PI\n 1.5707963705062866\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n Natural logarithm of `1/2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_HALF\n -0.6931471824645996\n\n See Also\n --------\n LN_HALF\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n Natural logarithm of the mathematical constant `π` as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_PI\n 1.1447298526763916\n\n See Also\n --------\n FLOAT32_PI, LN_PI\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n Natural logarithm of `10` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_TEN\n 2.3025851249694824\n\n See Also\n --------\n FLOAT32_LN_TWO, LN10\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n Natural logarithm of `2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_TWO\n 0.6931471824645996\n\n See Also\n --------\n FLOAT32_LN_TEN, LN2\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX\n 3.4028234663852886e+38\n\n See Also\n --------\n FLOAT16_MAX, FLOAT64_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a single-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE2_EXPONENT\n 127\n\n See Also\n --------\n FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n -127\n\n See Also\n --------\n FLOAT32_MAX_BASE2_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE10_EXPONENT\n 38\n\n See Also\n --------\n FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal single-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n -38\n\n See Also\n --------\n FLOAT32_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in single-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_FIBONACCI\n 14930352\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n\n The maximum safe single-precision floating-point integer is given by\n `2^24 - 1`.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_INTEGER\n 16777215\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n Maximum safe nth factorial when stored in single-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_FACTORIAL\n 10\n\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in single-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_FIBONACCI\n 36\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in single-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_LUCAS\n 34\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE2_EXPONENT\n -126\n\n See Also\n --------\n FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n -149\n\n See Also\n --------\n FLOAT32_MIN_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normal single-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE10_EXPONENT\n -37\n\n See Also\n --------\n FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal single-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n -45\n\n See Also\n --------\n FLOAT32_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n\n The minimum safe single-precision floating-point integer is given by\n `-(2^24 - 1)`.\n\n Examples\n --------\n > FLOAT32_MIN_SAFE_INTEGER\n -16777215\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"\nFLOAT32_NAN\n Single-precision floating-point NaN.\n\n Examples\n --------\n > FLOAT32_NAN\n NaN\n\n See Also\n --------\n NAN\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT32_NINF\n -Infinity\n\n See Also\n --------\n FLOAT32_PINF, NINF\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_NUM_BYTES\n 4\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT32_PHI":"\nFLOAT32_PHI\n Golden ratio.\n\n Examples\n --------\n > FLOAT32_PHI\n 1.6180340051651\n\n See Also\n --------\n PHI\n","FLOAT32_PI":"\nFLOAT32_PI\n The mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_PI\n 3.1415927410125732\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_TWO_PI\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT32_PINF\n Infinity\n\n See Also\n --------\n FLOAT32_NINF, PINF\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n\n The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT32_PRECISION\n 24\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT64_PRECISION\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n Mask for the sign bit of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SIGN_MASK\n 2147483648\n > base.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n '10000000000000000000000000000000'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n Mask for the significand of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SIGNIFICAND_MASK\n 8388607\n > base.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n '00000000011111111111111111111111'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_NORMAL\n 1.1754943508222875e-38\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_SUBNORMAL\n 1.401298464324817e-45\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_SQRT_EPS\n 0.0003452669770922512\n\n See Also\n --------\n FLOAT32_EPS, SQRT_EPS\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n Square root of `1/2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_HALF\n 0.7071067690849304\n\n See Also\n --------\n SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n Square root of `π` divided by `2` as a single-precision \n floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_HALF_PI\n 1.2533141374588013\n\n See Also\n --------\n SQRT_HALF_PI","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n Square root of the golden ratio as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_PHI\n 1.272019624710083\n\n See Also\n --------\n SQRT_PHI\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n Square root of the mathematical constant `π` as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_PI\n 1.7724539041519165\n\n See Also\n --------\n FLOAT32_PI, SQRT_PI\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n Square root of `3` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_THREE\n 1.7320507764816284\n\n See Also\n --------\n FLOAT32_SQRT_TWO, SQRT_THREE\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n Square root of `2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_TWO\n 1.4142135381698608\n\n See Also\n --------\n FLOAT32_SQRT_THREE, SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n Square root of the mathematical constant `π` times `2` as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_TWO_PI\n 2.5066282749176025\n\n See Also\n --------\n FLOAT32_PI, FLOAT32_TWO_PI, SQRT_TWO_PI\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > FLOAT32_TWO_PI\n 6.2831854820251465\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_PI\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array()\n \n\n\nFloat32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Float32Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'\n\n\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n \n\n\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20\n\n\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float32Array.from":"\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]","Float32Array.of":"\nFloat32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4","Float32Array.name":"\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n ","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT64_EXPONENT_BIAS\n 1023\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT32_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n High word mask for excluding the sign bit of a double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_ABS_MASK\n 2147483647\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n '01111111111111111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_EXPONENT_MASK\n 2146435072\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n '01111111111100000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n High word mask for the sign bit of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGN_MASK\n 2147483648\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n '10000000000000000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n 1048575\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n '00000000000011111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX\n 1.7976931348623157e+308\n\n See Also\n --------\n FLOAT16_MAX, FLOAT32_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT\n 1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n -1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT\n 308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_LN\n 709.782712893384\n\n See Also\n --------\n FLOAT64_MIN_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_FIBONACCI\n 8944394323791464\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n\n The maximum safe double-precision floating-point integer is given by\n `2^53 - 1`.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_INTEGER\n 9007199254740991\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_LUCAS\n 7639424778862807\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI, FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n 78\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_LUCAS\n 76\n\n See Also\n --------\n FLOAT64_MAX_SAFE_LUCAS, FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT\n -1022\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n -1074\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n -324\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MIN_LN\n -708.3964185322641\n\n See Also\n --------\n FLOAT64_MAX_LN\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n\n The minimum safe double-precision floating-point integer is given by\n `-(2^53 - 1)`.\n\n Examples\n --------\n > FLOAT64_MIN_SAFE_INTEGER\n -9007199254740991\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_NUM_BYTES\n 8\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT32_NUM_BYTES\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n\n The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT64_PRECISION\n 53\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT32_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_NORMAL\n 2.2250738585072014e-308\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_SUBNORMAL\n 4.940656458412465e-324\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array()\n \n\n\nFloat64Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = new Float64Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'\n\n\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n \n\n\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40\n\n\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float64Array.from":"\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]","Float64Array.of":"\nFloat64Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8","Float64Array.name":"\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n ","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","forEach":"\nforEach( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEach( arr, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachAsync":"\nforEachAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachAsync.factory":"\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync","forEachChar":"\nforEachChar( str, [options,] clbk[, thisArg] )\n Invokes a function for each character in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: starting character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters over which to iterate. The following modes are\n supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n clbk: Function\n The function to invoke for each character in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > forEachChar( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n forEach\n","forEachRight":"\nforEachRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEachRight( arr, logger )\n 3: 4\n 2: 3\n 1: 2\n 0: 1\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachRightAsync":"\nforEachRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight","forIn":"\nforIn( obj, fcn[, thisArg] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n\n When invoked, the function is provided three arguments:\n\n - value: object property value.\n - key: object property.\n - obj: the input object.\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > function Foo() { return this; };\n > Foo.prototype.beep = 'boop';\n > var obj = new Foo();\n > forIn( obj, logger )\n beep: boop\n\n See Also\n --------\n forEach, forOwn\n","format":"\nformat( str, ...args )\n Insert supplied variable values into a format string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n args: ...any\n Variable values.\n\n Returns\n -------\n out: string\n Formatted string.\n\n Examples\n --------\n > var out = format( 'Hello, %s!', 'World' )\n 'Hello, World!'\n\n > out = format( '%s %s', 'Hello', 'World' )\n 'Hello World'\n\n > out = format( 'Pi: %.2f', PI )\n 'Pi: 3.14'\n\n","forOwn":"\nforOwn( obj, fcn[, thisArg] )\n Invokes a function for each own enumerable property of an object.\n\n When invoked, the function is provided three arguments:\n\n - value: object property value.\n - key: object property.\n - obj: the input object.\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n The function determines the list of own enumerable properties *before*\n invoking the provided function. Hence, any modifications made to the input\n object *after* calling this function (such as adding and removing\n properties) will *not* affect the list of visited properties.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > forOwn( obj, logger )\n a: 1\n b: 2\n c: 3\n d: 4\n\n See Also\n --------\n forEach, forIn\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FOURTH_PI\n 7.85398163397448309616e-1\n\n See Also\n --------\n PI\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n\n Examples\n --------\n > FOURTH_ROOT_EPS\n 0.0001220703125\n\n See Also\n --------\n EPS\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n\n Each array element has the following fields:\n\n - date: collection date (month/day/year; e.g., 01/01/1980).\n - all_workers: wage rates for hourly and non-hourly workers.\n - hourly_workers: wage rates for hourly workers.\n - non_hourly_workers: wage rates for non-hourly workers.\n - less_than_high_school: wage rates for workers with less than a high school\n education.\n - high_school: wage rates for workers with a high school education.\n - some_college: wage rates for workers with some college education.\n - college: wage rates for workers with a college education.\n - construction: wage rates for workers in the construction industry.\n - finance: wage rates for workers in the finance industry.\n - manufacturing: wage rates for workers in the manufacturing industry.\n\n Returns\n -------\n out: Array\n Wage rates.\n\n Examples\n --------\n > var data = FRB_SF_WAGE_RIGIDITY()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" .\n\n","fromCodePoint":"\nfromCodePoint( ...pt )\n Creates a string from a sequence of Unicode code points.\n\n In addition to multiple arguments, the function also supports providing an\n array-like object as a single argument containing a sequence of Unicode code\n points.\n\n Parameters\n ----------\n pt: ...integer\n Sequence of Unicode code points.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = fromCodePoint( 9731 )\n '☃'\n > out = fromCodePoint( [ 9731 ] )\n '☃'\n > out = fromCodePoint( 97, 98, 99 )\n 'abc'\n > out = fromCodePoint( [ 97, 98, 99 ] )\n 'abc'\n\n See Also\n --------\n codePointAt\n","Function":"\nFunction( [...argNames,] body )\n Returns a Function object.\n\n Argument names must be strings corresponding to valid JavaScript parameters\n (i.e., a plain identifier, or, in environments supporting such parameters, a\n rest parameter or destructured parameter, optionally with a default).\n\n Parameters\n ----------\n argNames: ...any (optional)\n Parameter names.\n\n body: string\n Function body.\n\n Returns\n -------\n fcn: Function\n Function object.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f( 1, 2 )\n 3\n\n\nFunction.prototype.apply( thisArg, args )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: Array\n Array of arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.apply( null, [ 1, 2 ] )\n 3\n\nFunction.prototype.call( thisArg, ...args )\n Calls a function with a given `this` value and arguments provided\n individually.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.call( null, 1, 2 )\n 3\n\nFunction.prototype.bind( thisArg, ...args )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n fcn: Function\n Bound function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > var g = f.bind( null, 1 );\n > g( 2 )\n 3\n\nFunction.prototype.toString()\n Returns a string representation of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.toString()\n 'function anonymous( x, y ) { return x + y; }'\n\nFunction.prototype.length\n The number of arguments expected by the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.length\n 2\n\nFunction.prototype.name\n The name of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name\n 'anonymous'\n\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name = 'add';\n > f.name\n 'add'\n\nFunction.prototype.prototype\n The prototype of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.prototype\n {}\n\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg, args )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: Array\n Array of arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.apply( null, [ 1, 2 ] )\n 3","Function.prototype.call":"\nFunction.prototype.call( thisArg, ...args )\n Calls a function with a given `this` value and arguments provided\n individually.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.call( null, 1, 2 )\n 3","Function.prototype.bind":"\nFunction.prototype.bind( thisArg, ...args )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n fcn: Function\n Bound function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > var g = f.bind( null, 1 );\n > g( 2 )\n 3","Function.prototype.toString":"\nFunction.prototype.toString()\n Returns a string representation of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.toString()\n 'function anonymous( x, y ) { return x + y; }'","Function.prototype.length":"\nFunction.prototype.length\n The number of arguments expected by the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.length\n 2","Function.prototype.name":"\nFunction.prototype.name\n The name of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name\n 'anonymous'\n\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name = 'add';\n > f.name\n 'add'","Function.prototype.prototype":"\nFunction.prototype.prototype\n The prototype of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.prototype\n {}","function2string":"\nfunction2string( fcn )\n Returns a string representing the source code of a provided function.\n\n If called on built-in functions, functions created by `Function#bind()`, or\n other non-JavaScript functions, the function returns a \"native\" function\n string similar to the following:\n\n \"function foo() { [native code] }\"\n\n For intrinsic object methods and functions, `foo` is the initial name of the\n function.\n\n If called on a function created by the `Function` constructor, the function\n returns the source code of a synthesized function declaration having the\n name \"anonymous\" and using the provided parameters and function body.\n\n Starting in ES2018, the ECMAScript specification requires that the returned\n string contain the exact same source code as it was declared, including any\n whitespace and/or comments. If the host is unable to access the source code,\n the specification requires that the returned string be the native function\n string.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n String representing the function's source code.\n\n Examples\n --------\n > function2string( base.erf )\n \n\n See Also\n --------\n Function\n","functionName":"\nfunctionName( fcn )\n Returns the name of a function.\n\n If provided an anonymous function, the function returns an empty `string` or\n the string `\"anonymous\"`.\n\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n Function name.\n\n Examples\n --------\n > var v = functionName( String )\n 'String'\n > v = functionName( function foo(){} )\n 'foo'\n > v = functionName( function(){} )\n '' || 'anonymous'\n\n See Also\n --------\n constructorName\n","functionSequence":"\nfunctionSequence( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as an argument to the next function. The result of the\n rightmost function is the result of the whole.\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x ) { return 2 * x; };\n > function b( x ) { return x + 3; };\n > function c( x ) { return x / 5; };\n > var f = functionSequence( a, b, c );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n compose, functionSequenceAsync\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as the first argument of the next function. The result of\n the rightmost function is the result of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - error: error argument.\n - result: function result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the pipeline function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = functionSequenceAsync( a, b, c );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n composeAsync, functionSequence\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n Examples\n --------\n > GAMMA_LANCZOS_G\n 10.900511\n\n","gdot":"\ngdot( x, y )\n Computes the dot product of two vectors.\n\n In general, for best performance, especially for large vectors, provide\n 1-dimensional ndarrays whose underlying data type is either 'float64' or\n 'float32'.\n\n If provided empty vectors, the function returns `0.0`.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n First input array.\n\n y: ndarray|ArrayLikeObject\n Second input array.\n\n Returns\n -------\n dot: number\n The dot product.\n\n Examples\n --------\n // Using ndarrays...\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > gdot( x, y )\n -5.0\n\n // Using array-like objects...\n > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > gdot( x, y )\n -5.0\n\n See Also\n --------\n base.strided.gdot, ddot, sdot\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n\n The function only returns an effective group identity on POSIX platforms.\n For all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric group identity.\n\n Examples\n --------\n > var gid = getegid()\n\n See Also\n --------\n geteuid, getgid, getuid\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n\n The function only returns an effective user identity on POSIX platforms. For\n all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric user identity.\n\n Examples\n --------\n > var uid = geteuid()\n\n See Also\n --------\n getegid, getgid, getuid\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n\n The function only returns a group identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric group identity.\n\n Examples\n --------\n > var gid = getgid()\n\n See Also\n --------\n getegid, geteuid, getuid\n","getGlobal":"\ngetGlobal( [codegen] )\n Returns the global object.\n\n Parameters\n ----------\n codegen: boolean (optional)\n Boolean indicating whether to use code generation to resolve the global\n object. Code generation is the *most* reliable means for resolving the\n global object; however, using code generation may violate content\n security policies (CSPs). Default: false.\n\n Returns\n -------\n global: Object\n Global object.\n\n Examples\n --------\n > var g = getGlobal()\n {...}\n\n","getPrototypeOf":"\ngetPrototypeOf( value )\n Returns the prototype of a provided object.\n\n In contrast to the native `Object.getPrototypeOf`, this function does not\n throw when provided `null` or `undefined`. Instead, similar to when provided\n any value with *no* inherited properties, the function returns `null`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object|null\n Prototype.\n\n Examples\n --------\n > var proto = getPrototypeOf( {} )\n {}\n\n See Also\n --------\n isPrototypeOf\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n\n The function only returns a user identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric user identity.\n\n Examples\n --------\n > var uid = getuid()\n\n See Also\n --------\n getegid, geteuid, getgid\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n\n Examples\n --------\n > GLAISHER\n 1.2824271291006226\n\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over each grapheme cluster in a string.\n\n When invoked, an input function is provided three arguments:\n\n - value: grapheme cluster.\n - index: iterated value index.\n - src: source string.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke a string's `@@iterator` method, regardless of whether this method is\n defined. To convert a string to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: string\n String from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = graphemeClusters2iterator( '🌷🍕' );\n > var v = it.next().value\n '🌷'\n > v = it.next().value\n '🍕'\n > var bool = it.next().done\n true\n\n See Also\n --------\n array2iterator, graphemeClusters2iteratorRight\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over each grapheme\n cluster in a string.\n\n When invoked, an input function is provided three arguments:\n\n - value: grapheme cluster.\n - index: iterated value index.\n - src: source string.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke a string's `@@iterator` method, regardless of whether this method is\n defined. To convert a string to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: string\n String from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = graphemeClusters2iteratorRight( '🌷🍕' );\n > var v = it.next().value\n '🍕'\n > v = it.next().value\n '🌷'\n > var bool = it.next().done\n true\n\n See Also\n --------\n array2iteratorRight, graphemeClusters2iterator\n","group":"\ngroup( collection, [options,] groups )\n Groups values as arrays associated with distinct keys.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n groups: Array|TypedArray|Object\n A collection defining which group an element in the input collection\n belongs to. Each value in `groups` should resolve to a value which can\n be serialized as an object key. If provided an object, the object must\n be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var groups = [ 'b', 'b', 'f', 'b' ];\n > var out = group( collection, groups )\n { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n > groups = [ 1, 1, 2, 1 ];\n > out = group( collection, groups )\n { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n // Output group results as indices:\n > groups = [ 'b', 'b', 'f', 'b' ];\n > var opts = { 'returns': 'indices' };\n > out = group( collection, opts, groups )\n { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = group( collection, opts, groups )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n See Also\n --------\n bifurcate, countBy, groupBy\n","groupBy":"\ngroupBy( collection, [options,] indicator )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = groupBy( collection, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n See Also\n --------\n bifurcateBy, countBy, group\n","groupByAsync":"\ngroupByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy\n","groupByAsync.factory":"\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy","groupIn":"\ngroupIn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object with no prototype, the function returns an empty\n object.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > var out = groupIn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateIn, groupBy, groupOwn\n","groupOwn":"\ngroupOwn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object, the function returns an empty object.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = groupOwn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateOwn, group, groupBy\n","gswap":"\ngswap( x, y )\n Interchanges two vectors.\n\n In general, for best performance, especially for large vectors, provide\n 1-dimensional ndarrays whose underlying data type is either 'float64' or\n 'float32'.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n First input array.\n\n y: ndarray|ArrayLikeObject\n Second input array.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n // Using ndarrays...\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > gswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n // Using array-like objects...\n > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > gswap( x, y );\n > x\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gswap, dswap, sswap\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n\n Examples\n --------\n > HALF_LN2\n 3.46573590279972654709e-01\n\n See Also\n --------\n LN2\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > HALF_PI\n 1.5707963267948966\n\n See Also\n --------\n PI\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 14 attributes:\n\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n - lstat: percent lower status of the population.\n - medv: median value of owner-occupied homes in $1000's.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n Additionally, as documented by Gilley and Pace (1996), the dataset contains\n eight miscoded median values.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES_CORRECTED, PACE_BOSTON_HOUSE_PRICES\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 15 attributes:\n\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population.\n - medv: median value of owner-occupied homes in $1000's.\n - cmedv: corrected median value of owner-occupied homes in $1000's.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, PACE_BOSTON_HOUSE_PRICES\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `ArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasArrayBufferSupport()\n \n\n See Also\n --------\n hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasSharedArrayBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n Tests whether an environment supports native arrow functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support arrow functions.\n\n Examples\n --------\n > var bool = hasArrowFunctionSupport()\n \n\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `async`/`await` support.\n\n Examples\n --------\n > var bool = hasAsyncAwaitSupport()\n \n\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.asyncIterator`\n support.\n\n Examples\n --------\n > var bool = hasAsyncIteratorSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport, hasSymbolSupport\n","hasAtobSupport":"\nhasAtobSupport()\n Tests for native `atob` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `atob` support.\n\n Examples\n --------\n > var bool = hasAtobSupport()\n \n\n See Also\n --------\n hasBtoaSupport\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n Tests for native `BigInt64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `BigInt64Array` support.\n\n Examples\n --------\n > var bool = hasBigInt64ArraySupport()\n \n\n See Also\n --------\n hasBigIntSupport, hasBigUint64ArraySupport\n","hasBigIntSupport":"\nhasBigIntSupport()\n Tests for native `BigInt` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `BigInt` support.\n\n Examples\n --------\n > var bool = hasBigIntSupport()\n \n\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n Tests for native `BigUint64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `BigUint64Array` support.\n\n Examples\n --------\n > var bool = hasBigUint64ArraySupport()\n \n\n See Also\n --------\n hasBigIntSupport, hasBigInt64ArraySupport\n","hasBtoaSupport":"\nhasBtoaSupport()\n Tests for native `btoa` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `btoa` support.\n\n Examples\n --------\n > var bool = hasBtoaSupport()\n \n\n See Also\n --------\n hasAtobSupport\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `class` support.\n\n Examples\n --------\n > var bool = hasClassSupport()\n \n\n","hasDataViewSupport":"\nhasDataViewSupport()\n Tests for native `DataView` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `DataView` support.\n\n Examples\n --------\n > var bool = hasDataViewSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperties`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertiesSupport()\n \n\n See Also\n --------\n hasDefinePropertySupport\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperty`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertySupport()\n \n\n See Also\n --------\n hasDefinePropertiesSupport\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float32Array` support.\n\n Examples\n --------\n > var bool = hasFloat32ArraySupport()\n \n\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float64Array` support.\n\n Examples\n --------\n > var bool = hasFloat64ArraySupport()\n \n\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has function `name` support.\n\n Examples\n --------\n > var bool = hasFunctionNameSupport()\n \n\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support generator functions.\n\n Examples\n --------\n > var bool = hasGeneratorSupport()\n \n\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n Tests for `globalThis` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `globalThis` support.\n\n Examples\n --------\n > var bool = hasGlobalThisSupport()\n \n\n See Also\n --------\n getGlobal\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int8Array` support.\n\n Examples\n --------\n > var bool = hasInt8ArraySupport()\n \n\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int16Array` support.\n\n Examples\n --------\n > var bool = hasInt16ArraySupport()\n \n\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int32Array` support.\n\n Examples\n --------\n > var bool = hasInt32ArraySupport()\n \n\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.iterator`\n support.\n\n Examples\n --------\n > var bool = hasIteratorSymbolSupport()\n \n\n See Also\n --------\n hasAsyncIteratorSymbolSupport, hasSymbolSupport\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Map` support.\n\n Examples\n --------\n > var bool = hasMapSupport()\n \n\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Buffer` support.\n\n Examples\n --------\n > var bool = hasNodeBufferSupport()\n \n\n","hasOwnProp":"\nhasOwnProp( value, property )\n Tests if an object has a specified property.\n\n In contrast to the native `Object.prototype.hasOwnProperty`, this function\n does not throw when provided `null` or `undefined`. Instead, the function\n returns `false`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasOwnProp( beep, 'boop' )\n true\n > bool = hasOwnProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp\n","hasProp":"\nhasProp( value, property )\n Tests if an object has a specified property, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasProp( beep, 'boop' )\n true\n > bool = hasProp( beep, 'toString' )\n true\n > bool = hasProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Proxy` support.\n\n Examples\n --------\n > var bool = hasProxySupport()\n \n\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Set` support.\n\n Examples\n --------\n > var bool = hasSetSupport()\n \n\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasSharedArrayBufferSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport, hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol` support.\n\n Examples\n --------\n > var bool = hasSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `Symbol.toStringTag` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Symbol.toStringTag` support.\n\n Examples\n --------\n > var bool = hasToStringTagSupport()\n \n\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8Array` support.\n\n Examples\n --------\n > var bool = hasUint8ArraySupport()\n \n\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n Examples\n --------\n > var bool = hasUint8ClampedArraySupport()\n \n\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint16Array` support.\n\n Examples\n --------\n > var bool = hasUint16ArraySupport()\n \n\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint32Array` support.\n\n Examples\n --------\n > var bool = hasUint32ArraySupport()\n \n\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str, pos )\n Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n\n Parameters\n ----------\n str: string\n Input string.\n\n pos: integer\n Position.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether surrogate pair exists at specified position.\n\n Examples\n --------\n > var out = hasUTF16SurrogatePairAt( '🌷', 0 )\n true\n > out = hasUTF16SurrogatePairAt( '🌷', 1 )\n false\n\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakMap` support.\n\n Examples\n --------\n > var bool = hasWeakMapSupport()\n \n\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakSet` support.\n\n Examples\n --------\n > var bool = hasWeakSetSupport()\n \n\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native WebAssembly support.\n\n Examples\n --------\n > var bool = hasWebAssemblySupport()\n \n\n","headercase":"\nheadercase( str )\n Converts a string to HTTP header case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n HTTP header-cased string.\n\n Examples\n --------\n > var out = headercase( 'Hello World!' )\n 'Hello-World'\n > out = headercase( 'beep boop' )\n 'Beep-Boop'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n\n This dataset is a classic dataset commonly used in examples demonstrating\n outlier detection.\n\n Returns\n -------\n out: Array\n Observations.\n\n Examples\n --------\n > var d = HERNDON_VENUS_SEMIDIAMETERS()\n [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n References\n ----------\n - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n 5th ed. Vol. 5. London, England: Trübner & Co.\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n\n If unable to locate a home directory, the function returns `null`.\n\n Returns\n -------\n out: string|null\n Home directory.\n\n Examples\n --------\n > var home = homedir()\n e.g., '/Users/'\n\n See Also\n --------\n configdir, tmpdir\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var hrs = days * HOURS_IN_DAY\n 75.36\n\n See Also\n --------\n HOURS_IN_WEEK\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var hrs = wks * HOURS_IN_WEEK\n 527.52\n\n See Also\n --------\n HOURS_IN_DAY\n","hoursInMonth":"\nhoursInMonth( [month[, year]] )\n Returns the number of hours in a month.\n\n By default, the function returns the number of hours in the current month of\n the current year (according to local time). To determine the number of hours\n for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Hours in a month.\n\n Examples\n --------\n > var num = hoursInMonth()\n \n > num = hoursInMonth( 2 )\n \n > num = hoursInMonth( 2, 2016 )\n 696\n > num = hoursInMonth( 2, 2017 )\n 672\n\n // Other ways to supply month:\n > num = hoursInMonth( 'feb', 2016 )\n 696\n > num = hoursInMonth( 'february', 2016 )\n 696\n\n See Also\n --------\n hoursInYear\n","hoursInYear":"\nhoursInYear( [value] )\n Returns the number of hours in a year according to the Gregorian calendar.\n\n By default, the function returns the number of hours in the current year\n (according to local time). To determine the number of hours for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of hours in a year.\n\n Examples\n --------\n > var num = hoursInYear()\n \n > num = hoursInYear( 2016 )\n 8784\n > num = hoursInYear( 2017 )\n 8760\n\n See Also\n --------\n hoursInMonth\n","httpServerFactory":"\nhttpServerFactory( [options,] [requestListener] )\n Returns a function to create an HTTP server.\n\n In addition to options documented below, the function supports any options\n supported by `http.createServer`. Which server options are supported depends\n on the Node.js version. Older Node.js versions (e.g., <= v8.12.0) do not\n support an options object when calling `http.createServer`, and, for those\n versions, any options supported by `http.createServer` in later Node.js\n versions are ignored.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.port: integer (optional)\n Server port. Default: `0` (i.e., randomly assigned).\n\n options.maxport: integer (optional)\n Max server port when port hunting. Default: `maxport = port`.\n\n options.hostname: string (optional)\n Server hostname.\n\n options.address: string (optional)\n Server address. Default: `'127.0.0.1'`.\n\n requestListener: Function (optional)\n Request callback.\n\n Returns\n -------\n httpServer: Function\n Function to create an HTTP server.\n\n Examples\n --------\n // Basic usage:\n > var boot = httpServerFactory()\n \n\n // Provide a request callback:\n > function onRequest( request, response ) {\n ... console.log( request.url );\n ... response.end( 'OK' );\n ... };\n > boot = httpServerFactory( onRequest )\n \n\n // Specify a specific port:\n > var opts = { 'port': 7331 };\n > boot = httpServerFactory( opts )\n \n\n\nboot( done )\n Creates an HTTP server.\n\n Parameters\n ----------\n done: Function\n Callback to invoke after creating a server.\n\n Examples\n --------\n > function done( error, server ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Success!' );\n ... server.close();\n ... };\n > var boot = httpServerFactory();\n > boot( done );\n\n","identity":"\nidentity( x )\n Identity function.\n\n Parameters\n ----------\n x: any\n Input value.\n\n Returns\n -------\n out: any\n Input value.\n\n Examples\n --------\n > var v = identity( 3.14 )\n 3.14\n\n See Also\n --------\n constantFunction\n","ifelse":"\nifelse( bool, x, y )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n Returns\n -------\n z: any\n Either `x` or `y`.\n\n Examples\n --------\n > var z = ifelse( true, 1.0, -1.0 )\n 1.0\n > z = ifelse( false, 1.0, -1.0 )\n -1.0\n\n See Also\n --------\n ifelseAsync, ifthen\n","ifelseAsync":"\nifelseAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n\n A predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate completion.\n\n The callback function accepts two arguments:\n\n - error: error object.\n - bool: condition used to determine whether to invoke `x` or `y`.\n\n The `done` callback is invoked upon function completion and is provided at\n most two arguments:\n\n - error: error object.\n - result: either `x` or `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, true );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifelseAsync( predicate, 'beep', 'boop', done )\n 'beep'\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthen":"\nifthen( bool, x, y )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n Returns\n -------\n z: any\n Return value of either `x` or `y`.\n\n Examples\n --------\n > function x() { return 1.0; };\n > function y() { return -1.0; };\n > var z = ifthen( true, x, y )\n 1.0\n > z = ifthen( false, x, y )\n -1.0\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthenAsync":"\nifthenAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n\n The predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate function completion.\n\n The predicate function callback accepts two arguments:\n\n - error: error object.\n - bool: condition used to determine whether to invoke `x` or `y`.\n\n Both `x` and `y` are provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the `done` callback is invoked with only an\n error argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, false );\n ... }\n ... };\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'beep' );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifthenAsync( predicate, x, y, done )\n 'boop'\n\n See Also\n --------\n ifelseAsync, ifthen\n","imag":"\nimag( z )\n Returns the imaginary component of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var im = imag( z )\n 3.0\n\n See Also\n --------\n real, reim\n","imagf":"\nimagf( z )\n Returns the imaginary component of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var im = imagf( z )\n 3.0\n\n See Also\n --------\n imag, realf, reimf\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ACANTHUS_MOLLIS()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Acanthus mollis*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ALLIUM_OREOPHILUM\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_AIRPLANE_FROM_ABOVE()\n \n\n References\n ----------\n - Azari, Fédèle. 1929. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium oreophilum*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ALLIUM_OREOPHILUM()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Allium oreophilum*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ACANTHUS_MOLLIS\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_BLACK_CANYON()\n \n\n References\n ----------\n - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n Looking Above*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_DUST_BOWL_HOME()\n \n\n References\n ----------\n - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n \n\n References\n ----------\n - Braun, Adolphe. 1870. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_HOUSE_CAT()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_NUDE_MALE\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_NUDE_MALE()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_HOUSE_CAT\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_MARCH_PASTORAL()\n \n\n References\n ----------\n - Emerson, Peter Henry. 1888. *A March Pastoral*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_NAGASAKI_BOATS()\n \n\n References\n ----------\n - Beato, Felice. 1865. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","incrapcorr":"\nincrapcorr( [mx, my] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrapcorr();\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator()\n ~1.0\n\n See Also\n --------\n incrmapcorr, incrpcorr, incrpcorr2\n","incrBinaryClassification":"\nincrBinaryClassification( N[, options] )\n Returns an accumulator function which incrementally performs binary\n classification using stochastic gradient descent (SGD).\n\n If provided a feature vector and response value, the accumulator function\n updates a binary classification model and returns updated model\n coefficients.\n\n If not provided a feature vector and response value, the accumulator\n function returns the current model coefficients.\n\n Stochastic gradient descent is sensitive to the scaling of the features. One\n is advised to either scale each feature to `[0,1]` or `[-1,1]` or to\n transform the features into z-scores with zero mean and unit variance. One\n should keep in mind that the same scaling has to be applied to training data\n in order to obtain accurate predictions.\n\n In general, the more data provided to an accumulator, the more reliable the\n model predictions.\n\n Parameters\n ----------\n N: integer\n Number of features.\n\n options: Object (optional)\n Function options.\n\n options.intercept: boolean (optional)\n Boolean indicating whether to include an intercept. Default: true.\n\n options.lambda: number (optional)\n Regularization parameter. Default: 1.0e-4.\n\n options.learningRate: ArrayLike (optional)\n Learning rate function and associated (optional) parameters. The first\n array element specifies the learning rate function and must be one of\n the following:\n\n - ['constant', ...]: constant learning rate function. To set the\n learning rate, provide a second array element. By default, when the\n learn rate function is 'constant', the learning rate is set to 0.02.\n\n - ['basic']: basic learning rate function according to the formula\n `10/(10+t)` where `t` is the current iteration.\n\n - ['invscaling', ...]: inverse scaling learning rate function according\n to the formula `eta0/pow(t, power_t)` where `eta0` is the initial\n learning rate and `power_t` is the exponent controlling how quickly the\n learning rate decreases. To set the initial learning rate, provide a\n second array element. By default, the initial learning rate is 0.02. To\n set the exponent, provide a third array element. By default, the\n exponent is 0.5.\n\n - ['pegasos']: Pegasos learning rate function according to the formula\n `1/(lambda*t)` where `t` is the current iteration and `lambda` is the\n regularization parameter.\n\n Default: ['basic'].\n\n options.loss: string (optional)\n Loss function. Must be one of the following:\n\n - hinge: hinge loss function. Corresponds to a soft-margin linear\n Support Vector Machine (SVM), which can handle non-linearly separable\n data.\n\n - log: logistic loss function. Corresponds to Logistic Regression.\n\n - modifiedHuber: Huber loss function variant for classification.\n\n - perceptron: hinge loss function without a margin. Corresponds to the\n original Perceptron by Rosenblatt.\n\n - squaredHinge: squared hinge loss function SVM (L2-SVM).\n\n Default: 'log'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts response values for one ore more observation vectors. Provide a\n second argument to specify the prediction type. Must be one of the\n following: 'label', 'probability', or 'linear'. Default: 'label'.\n\n Note that the probability prediction type is only compatible with 'log'\n and 'modifiedHuber' loss functions.\n\n Examples\n --------\n // Create an accumulator:\n > var opts = {};\n > opts.intercept = true;\n > opts.lambda = 1.0e-5;\n > var acc = incrBinaryClassification( 3, opts );\n\n // Update the model:\n > var buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\n > var x = array( buf );\n > var coefs = acc( x, 1 )\n \n\n // Create a new observation vector:\n > buf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\n > x = array( buf );\n\n // Predict the response value:\n > var yhat = acc.predict( x )\n \n\n See Also\n --------\n incrSGDRegression\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrmean, incrsum, incrsummary\n","incrcovariance":"\nincrcovariance( [mx, my] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n\n If provided values, the accumulator function returns an updated unbiased\n sample covariance. If not provided values, the accumulator function returns\n the current unbiased sample covariance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovariance();\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator()\n ~-7.49\n\n See Also\n --------\n incrmcovariance, incrpcorr, incrvariance\n","incrcovmat":"\nincrcovmat( out[, means] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n unbiased sample covariance matrix. If not provided a data vector, the\n accumulator function returns the current unbiased sample covariance matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the covariance matrix or a square 2-dimensional ndarray for\n storing the covariance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovariance, incrpcorrmat\n","incrcv":"\nincrcv( [mean] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcv();\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator()\n ~0.47\n\n See Also\n --------\n incrmean, incrmcv, incrstdev, incrvmr\n","increwmean":"\nincrewmean( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwmean( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -1.5\n > v = accumulator()\n -1.5\n\n See Also\n --------\n increwvariance, incrmean, incrmmean, incrwmean\n","increwstdev":"\nincrewstdev( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n\n If provided a value, the accumulator function returns an updated standard\n deviation. If not provided a value, the accumulator function returns the\n current standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwstdev( 0.5 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n 3.5\n > s = accumulator()\n 3.5\n\n See Also\n --------\n increwvariance, incrmstdev, incrstdev\n","increwvariance":"\nincrewvariance( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n\n If provided a value, the accumulator function returns an updated variance.\n If not provided a value, the accumulator function returns the current\n variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwvariance( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 0.0\n > v = accumulator( -5.0 )\n 12.25\n > v = accumulator()\n 12.25\n\n See Also\n --------\n increwmean, increwstdev, incrvariance, incrmvariance\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n\n If provided a value, the accumulator function returns an updated geometric\n mean. If not provided a value, the accumulator function returns the current\n geometric mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n If provided a negative value, the accumulated value is `NaN` for all future\n invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrgmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator()\n ~3.16\n\n See Also\n --------\n incrhmean, incrmean, incrmgmean, incrsummary\n","incrgrubbs":"\nincrgrubbs( [options] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the test statistic is `NaN` for all future invocations.\n\n The accumulator must be provided *at least* three data points before\n performing Grubbs' test. Until at least three data points are provided, the\n accumulator returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n options.init: integer (optional)\n Number of data points the accumulator should use to compute initial\n statistics *before* testing for an outlier. Until the accumulator is\n provided the number of data points specified by this option, the\n accumulator returns `null`. Default: 100.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrgrubbs();\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrmgrubbs\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n\n If provided a value, the accumulator function returns an updated harmonic\n mean. If not provided a value, the accumulator function returns the current\n harmonic mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrhmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator()\n ~2.86\n\n See Also\n --------\n incrgmean, incrmean, incrmhmean, incrsummary\n","incrkmeans":"\nincrkmeans( k[, ndims][, options] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n\n If not provided initial centroids, the accumulator caches data vectors for\n subsequent centroid initialization. Until an accumulator computes initial\n centroids, an accumulator returns `null`.\n\n Once an accumulator has initial centroids (either provided or computed), if\n provided a data vector, the accumulator function returns updated cluster\n results. If not provided a data vector, the accumulator function returns the\n current cluster results.\n\n Cluster results are comprised of the following:\n\n - centroids: a `k x ndims` matrix containing centroid locations. Each\n centroid is the component-wise mean of the data points assigned to a\n centroid's corresponding cluster.\n - stats: a `k x 4` matrix containing cluster statistics.\n\n Cluster statistics consists of the following columns:\n\n - 0: number of data points assigned to a cluster.\n - 1: total within-cluster sum of squared distances.\n - 2: arithmetic mean of squared distances.\n - 3: corrected sample standard deviation of squared distances.\n\n Because an accumulator incrementally partitions data, one should *not*\n expect cluster statistics to match similar statistics had provided data been\n analyzed via a batch algorithm. In an incremental context, data points which\n would not be considered part of a particular cluster when analyzed via a\n batch algorithm may contribute to that cluster's statistics when analyzed\n incrementally.\n\n In general, the more data provided to an accumulator, the more reliable the\n cluster statistics.\n\n Parameters\n ----------\n k: integer|ndarray\n Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n ndims: integer (optional)\n Number of dimensions. This argument must accompany an integer-valued\n first argument.\n\n options: Object (optional)\n Function options.\n\n options.metric: string (optional)\n Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n 'correlation'. Default: 'euclidean'.\n\n options.init: ArrayLike (optional)\n Centroid initialization method and associated (optional) parameters. The\n first array element specifies the initialization method and must be one\n of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n element specifies the number of data points to use when calculating\n initial centroids. When performing kmeans++ initialization, the third\n array element specifies the number of trials to perform when randomly\n selecting candidate centroids. Typically, more trials is correlated with\n initial centroids which lead to better clustering; however, a greater\n number of trials increases computational overhead. Default: ['kmeans++',\n k, 2+⌊ln(k)⌋ ].\n\n options.normalize: boolean (optional)\n Boolean indicating whether to normalize incoming data. This option is\n only relevant for non-Euclidean distance metrics. If set to `true`, an\n accumulator partitioning data based on cosine distance normalizes\n provided data to unit Euclidean length. If set to `true`, an accumulator\n partitioning data based on correlation distance first centers provided\n data and then normalizes data dimensions to have zero mean and unit\n variance. If this option is set to `false` and the metric is either\n cosine or correlation distance, then incoming data *must* already be\n normalized. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy incoming data to prevent mutation\n during normalization. Default: true.\n\n options.seed: any (optional)\n PRNG seed. Setting this option is useful when wanting reproducible\n initial centroids.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts centroid assignment for each data point in a provided matrix.\n To specify an output vector, provide a 1-dimensional ndarray as the\n first argument. Each element in the returned vector corresponds to a\n predicted cluster index for a respective data point.\n\n Examples\n --------\n > var accumulator = incrkmeans( 5, 2 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v );\n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v );\n\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n\n If provided a value, the accumulator function returns an updated corrected\n sample excess kurtosis. If not provided a value, the accumulator function\n returns the current corrected sample excess kurtosis.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrkurtosis();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( 2.0 )\n null\n > v = accumulator( -4.0 )\n null\n > v = accumulator( -4.0 )\n -6.0\n\n See Also\n --------\n incrmean, incrskewness, incrstdev, incrsummary, incrvariance\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n\n If provided input values, the accumulator function returns an updated mean\n arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current mean arctangent absolute percentage\n error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.3218\n > m = accumulator( 5.0, 2.0 )\n ~0.6523\n > m = accumulator()\n ~0.6523\n\n See Also\n --------\n incrmae, incrmape, incrmean, incrmmaape\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute error. If not provided input values, the accumulator function\n returns the current mean absolute error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmae();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmape, incrme, incrmean, incrmmae\n","incrmapcorr":"\nincrmapcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample absolute correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample absolute correlation coefficient. If not provided values, the\n accumulator function returns the current moving sample absolute correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmapcorr( 3 );\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator( 3.0, -1.0 )\n ~0.925\n > ar = accumulator( 5.0, -9.5 )\n ~0.863\n > ar = accumulator()\n ~0.863\n\n See Also\n --------\n incrapcorr, incrmpcorr, incrmpcorr2\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute percentage error. If not provided input values, the accumulator\n function returns the current mean absolute percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator()\n ~91.67\n\n See Also\n --------\n incrmaape, incrmae, incrmean, incrmmape\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n\n If provided a value, the accumulator function returns an updated maximum\n value. If not provided a value, the accumulator function returns the current\n maximum value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmax();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmidrange, incrmin, incrmmax, incrrange, incrsummary\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n\n If provided a value, the accumulator function returns an updated maximum\n absolute value. If not provided a value, the accumulator function returns\n the current maximum absolute value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaxabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmax, incrminabs, incrmmaxabs\n","incrmcovariance":"\nincrmcovariance( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample covariance.\n\n If provided values, the accumulator function returns an updated moving\n unbiased sample covariance. If not provided values, the accumulator function\n returns the current moving unbiased sample covariance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcovariance( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator( 3.0, -1.0 )\n -8.35\n > v = accumulator( 5.0, -9.5 )\n -29.42\n > v = accumulator()\n -29.42\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrmvariance\n","incrmcv":"\nincrmcv( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n\n The `W` parameter defines the number of values over which to compute the\n moving coefficient of variation.\n\n If provided a value, the accumulator function returns an updated moving\n coefficient of variation. If not provided a value, the accumulator function\n returns the current moving coefficient of variation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcv( 3 );\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator( 3.0 )\n 0.5\n > cv = accumulator( 7.0 )\n ~0.83\n > cv = accumulator()\n ~0.83\n\n See Also\n --------\n incrcv, incrmmean, incrmstdev, incrmvmr\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n\n If provided input values, the accumulator function returns an updated mean\n directional accuracy. If not provided input values, the accumulator function\n returns the current mean directional accuracy.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmda();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 4.0 )\n 0.5\n > m = accumulator()\n 0.5\n\n See Also\n --------\n incrmape, incrmmda\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n\n If provided input values, the accumulator function returns an updated mean\n error. If not provided input values, the accumulator function returns the\n current mean error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrme();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmae, incrmean, incrmme\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator()\n -1.5\n\n See Also\n --------\n incrmidrange, incrmmean, incrstdev, incrsum, incrsummary, incrvariance\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator()\n 3.5\n\n See Also\n --------\n incrmean, incrmmeanabs, incrsumabs\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs2();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 4.0\n > mu = accumulator( -5.0 )\n 14.5\n > mu = accumulator()\n 14.5\n\n See Also\n --------\n incrmean, incrmeanabs, incrmmeanabs2, incrsumabs2\n","incrmeanstdev":"\nincrmeanstdev( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanstdev();\n > var ms = accumulator()\n null\n > ms = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > ms = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > ms = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > ms = accumulator( 5.0 )\n [ 1.25, ~4.35 ]\n > ms = accumulator()\n [ 1.25, ~4.35 ]\n\n See Also\n --------\n incrmean, incrmeanvar, incrmmeanstdev, incrstdev\n","incrmeanvar":"\nincrmeanvar( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanvar();\n > var mv = accumulator()\n null\n > mv = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > mv = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > mv = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > mv = accumulator( 5.0 )\n [ 1.25, ~18.92 ]\n > mv = accumulator()\n [ 1.25, ~18.92 ]\n\n See Also\n --------\n incrmean, incrmeanstdev, incrmmeanvar, incrvariance\n","incrmgmean":"\nincrmgmean( W )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving geometric mean.\n\n If provided a value, the accumulator function returns an updated moving\n geometric mean. If not provided a value, the accumulator function returns\n the current moving geometric mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmgmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator( 3.0 )\n ~3.11\n > v = accumulator( 5.0 )\n ~4.22\n > v = accumulator()\n ~4.22\n\n See Also\n --------\n incrgmean, incrmhmean, incrmmean\n","incrmgrubbs":"\nincrmgrubbs( W[, options] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n The `W` parameter defines the number of values over which to perform Grubbs'\n test. The minimum window size is 3.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n Until provided `W` values, the accumulator function returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrmgrubbs( 20 );\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrgrubbs\n","incrmhmean":"\nincrmhmean( W )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving harmonic mean.\n\n If provided a value, the accumulator function returns an updated moving\n harmonic mean. If not provided a value, the accumulator function returns the\n current moving harmonic mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmhmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator( 3.0 )\n ~2.90\n > v = accumulator( 5.0 )\n ~4.09\n > v = accumulator()\n ~4.09\n\n See Also\n --------\n incrhmean, incrmgmean, incrmmean\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If provided a value, the accumulator function returns an updated mid-range.\n If not provided a value, the accumulator function returns the current mid-\n range.\n\n If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmidrange();\n > var v = accumulator()\n null\n > v = accumulator( 3.14 )\n 3.14\n > v = accumulator( -5.0 )\n ~-0.93\n > v = accumulator( 10.1 )\n 2.55\n > v = accumulator()\n 2.55\n\n See Also\n --------\n incrmean, incrmax, incrmin, incrrange, incrsummary\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n\n If provided a value, the accumulator function returns an updated minimum\n value. If not provided a value, the accumulator function returns the current\n minimum value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmin();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 10.1 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmax, incrmidrange, incrmmin, incrrange, incrsummary\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n\n If provided a value, the accumulator function returns an updated minimum\n absolute value. If not provided a value, the accumulator function returns\n the current minimum absolute value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 3.14\n > m = accumulator()\n 3.14\n\n See Also\n --------\n incrmaxabs, incrmin, incrmminabs\n","incrminmax":"\nincrminmax( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmax();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmminmax, incrrange\n","incrminmaxabs":"\nincrminmaxabs( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmaxabs();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator()\n [ 2.0, 5.0 ]\n\n See Also\n --------\n incrmaxabs, incrminabs, incrminmax, incrmminmaxabs\n","incrmmaape":"\nincrmmaape( W )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean arctangent absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean arctangent absolute\n percentage error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.32\n > m = accumulator( 5.0, 2.0 )\n ~0.65\n > m = accumulator( 3.0, 2.0 )\n ~0.59\n > m = accumulator( 2.0, 5.0 )\n ~0.66\n > m = accumulator()\n ~0.66\n\n See Also\n --------\n incrmaape, incrmmape, incrmmpe, incrmmean\n","incrmmae":"\nincrmmae( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute error.\n\n If provided a value, the accumulator function returns an updated moving\n mean absolute error. If not provided a value, the accumulator function\n returns the current moving mean absolute error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmae( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n 3.0\n > m = accumulator( 5.0, -2.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmae, incrmme, incrmmean\n","incrmmape":"\nincrmmape( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean absolute percentage\n error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator( 3.0, 2.0 )\n ~77.78\n > m = accumulator( 2.0, 5.0 )\n ~86.67\n > m = accumulator()\n ~86.67\n\n See Also\n --------\n incrmape, incrmmaape, incrmmpe, incrmmean\n","incrmmax":"\nincrmmax( W )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum.\n\n If provided a value, the accumulator function returns an updated moving\n maximum. If not provided a value, the accumulator function returns the\n current moving maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmax( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 3.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmmidrange, incrmmin, incrmrange, incrmsummary\n","incrmmaxabs":"\nincrmmaxabs( W )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n maximum absolute value. If not provided a value, the accumulator function\n returns the current moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaxabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 3.0 )\n 5.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmaxabs, incrmmax, incrmminabs\n","incrmmda":"\nincrmmda( W )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean directional accuracy.\n\n If provided input values, the accumulator function returns an updated moving\n mean directional accuracy. If not provided input values, the accumulator\n function returns the current moving mean directional accuracy.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmda( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( 5.0, 2.0 )\n 0.5\n > m = accumulator( 3.0, 2.0 )\n ~0.33\n > m = accumulator( 4.0, 5.0 )\n ~0.33\n > m = accumulator()\n ~0.33\n\n See Also\n --------\n incrmda, incrmmape\n","incrmme":"\nincrmme( W )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean error.\n\n If provided a value, the accumulator function returns an updated moving\n mean error. If not provided a value, the accumulator function returns the\n current moving mean error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmme( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n ~2.33\n > m = accumulator( 5.0, -2.0 )\n ~-0.33\n > m = accumulator()\n ~-0.33\n\n See Also\n --------\n incrme, incrmmae, incrmmean\n","incrmmean":"\nincrmmean( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmean( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator( 3.0 )\n 0.0\n > mu = accumulator( 5.0 )\n 1.0\n > mu = accumulator()\n 1.0\n\n See Also\n --------\n incrmean, incrmsum, incrmstdev, incrmsummary, incrmvariance\n","incrmmeanabs":"\nincrmmeanabs( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator( 3.0 )\n ~3.33\n > mu = accumulator( 5.0 )\n ~4.33\n > mu = accumulator()\n ~4.33\n\n See Also\n --------\n incrmeanabs, incrmmean, incrmsumabs\n","incrmmeanabs2":"\nincrmmeanabs2( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs2( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 4.0\n > m = accumulator( -5.0 )\n 14.5\n > m = accumulator( 3.0 )\n ~12.67\n > m = accumulator( 5.0 )\n ~19.67\n > m = accumulator()\n ~19.67\n\n See Also\n --------\n incrmeanabs2, incrmmeanabs, incrmsumabs2\n","incrmmeanstdev":"\nincrmmeanstdev( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanstdev( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > v = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > v = accumulator( 5.0 )\n [ 1.0, ~5.29 ]\n > v = accumulator()\n [ 1.0, ~5.29 ]\n\n See Also\n --------\n incrmeanstdev, incrmmean, incrmmeanvar, incrmstdev\n","incrmmeanvar":"\nincrmmeanvar( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanvar( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > v = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > v = accumulator( 5.0 )\n [ 1.0, 28.0 ]\n > v = accumulator()\n [ 1.0, 28.0 ]\n\n See Also\n --------\n incrmeanvar, incrmmean, incrmmeanstdev, incrmvariance\n","incrmmidrange":"\nincrmmidrange( W )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of values over which to compute\n the moving mid-range.\n\n If provided a value, the accumulator function returns an updated moving mid-\n range. If not provided a value, the accumulator function returns the current\n moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmidrange( 3 );\n > var mr = accumulator()\n null\n > mr = accumulator( 2.0 )\n 2.0\n > mr = accumulator( -5.0 )\n -1.5\n > mr = accumulator( 3.0 )\n -1.0\n > mr = accumulator( 5.0 )\n 0.0\n > mr = accumulator()\n 0.0\n\n See Also\n --------\n incrmmean, incrmmax, incrmmin, incrmrange\n","incrmmin":"\nincrmmin( W )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum. If not provided a value, the accumulator function returns the\n current moving minimum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmin( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 3.0 )\n -5.0\n > m = accumulator( 5.0 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmin, incrmmax, incrmmidrange, incrmrange, incrmsummary\n","incrmminabs":"\nincrmminabs( W )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n minimum absolute value. If not provided a value, the accumulator function\n returns the current moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 2.0\n > m = accumulator( 5.0 )\n 3.0\n > m = accumulator()\n 3.0\n\n See Also\n --------\n incrminabs, incrmmaxabs, incrmmin\n","incrmminmax":"\nincrmminmax( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum and maximum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmax( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmmax, incrminmax, incrmmin, incrmrange\n","incrmminmaxabs":"\nincrmminmaxabs( [out,] W )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n\n The `W` parameter defines the number of values over which to compute moving\n minimum and maximum absolute values.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmaxabs( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 3.0, 5.0 ]\n > mm = accumulator()\n [ 3.0, 5.0 ]\n\n See Also\n --------\n incrminmaxabs, incrmmax, incrmmaxabs, incrmmin, incrmminabs, incrmminmax\n","incrmmpe":"\nincrmmpe( W )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean percentage error. If not provided input values, the accumulator\n function returns the current moving mean percentage error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmpe( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator( 3.0, 2.0 )\n ~-55.56\n > m = accumulator( 2.0, 5.0 )\n ~-46.67\n > m = accumulator()\n ~-46.67\n\n See Also\n --------\n incrmmape, incrmme, incrmpe\n","incrmmse":"\nincrmmse( W )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean squared error.\n\n If provided a value, the accumulator function returns an updated moving mean\n squared error. If not provided a value, the accumulator function returns the\n current moving mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmse( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator( 3.0, 2.0 )\n 17.0\n > m = accumulator( 5.0, -2.0 )\n 33.0\n > m = accumulator()\n 33.0\n\n See Also\n --------\n incrmrmse, incrmrss, incrmse\n","incrmpcorr":"\nincrmpcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation coefficient. If not provided values, the accumulator\n function returns the current moving sample correlation coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator( 3.0, -1.0 )\n ~-0.925\n > r = accumulator( 5.0, -9.5 )\n ~-0.863\n > r = accumulator()\n ~-0.863\n\n See Also\n --------\n incrmcovariance, incrmpcorrdist, incrpcorr\n","incrmpcorr2":"\nincrmpcorr2( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving squared sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n squared sample correlation coefficient. If not provided values, the\n accumulator function returns the current moving squared sample correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr2( 3 );\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator( 3.0, -1.0 )\n ~0.86\n > r2 = accumulator( 5.0, -9.5 )\n ~0.74\n > r2 = accumulator()\n ~0.74\n\n See Also\n --------\n incrmapcorr, incrmpcorr, incrpcorr2\n","incrmpcorrdist":"\nincrmpcorrdist( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n However, due to limitations inherent in representing numeric values using\n floating-point format (i.e., the inability to represent numeric values with\n infinite precision), the correlation distance between perfectly correlated\n random variables may *not* be `0` or `2`. In fact, the correlation distance\n is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n distance should, however, be within floating-point roundoff error.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation distance.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation distance. If not provided values, the accumulator\n function returns the current moving sample correlation distance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorrdist( 3 );\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator( 3.0, -1.0 )\n ~1.925\n > d = accumulator( 5.0, -9.5 )\n ~1.863\n > d = accumulator()\n ~1.863\n\n See Also\n --------\n incrmpcorr, incrpcorrdist\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n\n If provided input values, the accumulator function returns an updated mean\n percentage error. If not provided input values, the accumulator function\n returns the current mean percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpe();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator()\n ~-58.33\n\n See Also\n --------\n incrmape, incrme, incrmmpe\n","incrmprod":"\nincrmprod( W )\n Returns an accumulator function which incrementally computes a moving\n product.\n\n The `W` parameter defines the number of values over which to compute the\n moving product.\n\n If provided a value, the accumulator function returns an updated moving\n product. If not provided a value, the accumulator function returns the\n current moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n For accumulations over large windows or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmprod( 3 );\n > var p = accumulator()\n null\n > p = accumulator( 2.0 )\n 2.0\n > p = accumulator( -5.0 )\n -10.0\n > p = accumulator( 3.0 )\n -30.0\n > p = accumulator( 5.0 )\n -75.0\n > p = accumulator()\n -75.0\n\n See Also\n --------\n incrmsum, incrprod\n","incrmrange":"\nincrmrange( W )\n Returns an accumulator function which incrementally computes a moving range.\n\n The `W` parameter defines the number of values over which to compute the\n moving range.\n\n If provided a value, the accumulator function returns an updated moving\n range. If not provided a value, the accumulator function returns the current\n moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrange( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0 )\n 0.0\n > r = accumulator( -5.0 )\n 7.0\n > r = accumulator( 3.0 )\n 8.0\n > r = accumulator( 5.0 )\n 10.0\n > r = accumulator()\n 10.0\n\n See Also\n --------\n incrmmax, incrmmean, incrmmin, incrmsummary, incrrange\n","incrmrmse":"\nincrmrmse( W )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving root mean squared error.\n\n If provided a value, the accumulator function returns an updated moving root\n mean squared error. If not provided a value, the accumulator function\n returns the current moving root mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrmse( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator( 3.0, 2.0 )\n ~4.12\n > r = accumulator( 5.0, -2.0 )\n ~5.74\n > r = accumulator()\n ~5.74\n\n See Also\n --------\n incrmmse, incrmrss, incrrmse\n","incrmrss":"\nincrmrss( W )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n\n The `W` parameter defines the number of values over which to compute the\n moving residual sum of squares.\n\n If provided a value, the accumulator function returns an updated moving\n residual sum of squares. If not provided a value, the accumulator function\n returns the current moving residual sum of squares.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrss( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator( 3.0, 2.0 )\n 51.0\n > r = accumulator( 5.0, -2.0 )\n 99.0\n > r = accumulator()\n 99.0\n\n See Also\n --------\n incrrss, incrmmse, incrmrmse\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n\n If provided input values, the accumulator function returns an updated mean\n squared error. If not provided input values, the accumulator function\n returns the current mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmse();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator()\n 25.0\n\n See Also\n --------\n incrmmse, incrrmse, incrrss\n","incrmstdev":"\nincrmstdev( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving corrected sample standard deviation.\n\n If provided a value, the accumulator function returns an updated moving\n corrected sample standard deviation. If not provided a value, the\n accumulator function returns the current moving corrected sample standard\n deviation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmstdev( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator( 3.0 )\n ~4.36\n > s = accumulator( 5.0 )\n ~5.29\n > s = accumulator()\n ~5.29\n\n See Also\n --------\n incrmmean, incrmsummary, incrmvariance, incrstdev\n","incrmsum":"\nincrmsum( W )\n Returns an accumulator function which incrementally computes a moving sum.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsum( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator( 3.0 )\n 0.0\n > s = accumulator( 5.0 )\n 3.0\n > s = accumulator()\n 3.0\n\n See Also\n --------\n incrmmean, incrmsummary, incrsum\n","incrmsumabs":"\nincrmsumabs( W )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator( 3.0 )\n 10.0\n > s = accumulator( -5.0 )\n 13.0\n > s = accumulator()\n 13.0\n\n See Also\n --------\n incrmmeanabs, incrmsum, incrsum, incrsumabs\n","incrmsumabs2":"\nincrmsumabs2( W )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs2( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator( 3.0 )\n 38.0\n > s = accumulator( -5.0 )\n 59.0\n > s = accumulator()\n 59.0\n\n See Also\n --------\n incrmmeanabs2, incrmsumabs, incrsumabs, incrsumabs2\n","incrmsummary":"\nincrmsummary( W )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n\n The `W` parameter defines the number of values over which to compute the\n moving statistical summary.\n\n If provided a value, the accumulator function returns an updated moving\n statistical summary. If not provided a value, the accumulator function\n returns the current moving statistical summary.\n\n The returned summary is an object containing the following fields:\n\n - window: window size.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - range: range.\n - midrange: arithmetic mean of the minimum and maximum values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n summaries are calculated from smaller sample sizes. Until the window is\n full, each returned summary is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsummary( 3 );\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsum, incrmvariance, incrsummary\n","incrmsumprod":"\nincrmsumprod( W )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n\n The `W` parameter defines the number of (x,y) pairs over which to compute\n the moving sum of products.\n\n If provided input values, the accumulator function returns an updated moving\n sum. If not provided input values, the accumulator function returns the\n current moving sum.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumprod( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator( 3.0, -2.0 )\n -10.0\n > s = accumulator( 5.0, 3.0 )\n -1.0\n > s = accumulator()\n -1.0\n\n See Also\n --------\n incrmprod, incrmsum, incrsumprod\n","incrmvariance":"\nincrmvariance( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample variance.\n\n If provided a value, the accumulator function returns an updated moving\n unbiased sample variance. If not provided a value, the accumulator function\n returns the current moving unbiased sample variance.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvariance( 3 );\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator( 3.0 )\n 19.0\n > s2 = accumulator( 5.0 )\n 28.0\n > s2 = accumulator()\n 28.0\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsummary, incrvariance\n","incrmvmr":"\nincrmvmr( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n\n The `W` parameter defines the number of values over which to compute the\n moving variance-to-mean ratio.\n\n If provided a value, the accumulator function returns an updated moving\n variance-to-mean ratio. If not provided a value, the accumulator function\n returns the current moving variance-to-mean ratio.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvmr( 3 );\n > var F = accumulator()\n null\n > F = accumulator( 2.0 )\n 0.0\n > F = accumulator( 1.0 )\n ~0.33\n > F = accumulator( 3.0 )\n 0.5\n > F = accumulator( 7.0 )\n ~2.55\n > F = accumulator()\n ~2.55\n\n See Also\n --------\n incrmmean, incrmvariance, incrvmr\n","incrnancount":"\nincrnancount()\n Returns an accumulator function which incrementally updates a count,\n ignoring `NaN` values.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnancount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrnansum\n","incrnansum":"\nincrnansum()\n Returns an accumulator function which incrementally computes a sum, ignoring\n `NaN` values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( NaN )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrnansumabs, incrsum\n","incrnansumabs":"\nincrnansumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values, ignoring NaN values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( NaN )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrnansum, incrnansumabs2, incrsumabs\n","incrnansumabs2":"\nincrnansumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values, ignoring NaN values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( NaN )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrnansum, incrnansumabs, incrsumabs2\n","incrpcorr":"\nincrpcorr( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated sample\n correlation coefficient. If not provided values, the accumulator function\n returns the current sample correlation coefficient.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator()\n ~-1.0\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrsummary\n","incrpcorr2":"\nincrpcorr2( [mx, my] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr2();\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator()\n ~1.0\n\n See Also\n --------\n incrapcorr, incrmpcorr2, incrpcorr\n","incrpcorrdist":"\nincrpcorrdist( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n If provided values, the accumulator function returns an updated sample\n correlation distance. If not provided values, the accumulator function\n returns the current sample correlation distance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdist();\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator()\n ~2.0\n\n See Also\n --------\n incrcovariance, incrpcorr, incrsummary\n","incrpcorrdistmat":"\nincrpcorrdistmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation distance matrix. If not provided a data vector, the\n accumulator function returns the current sample correlation distance matrix.\n\n Due to limitations inherent in representing numeric values using floating-\n point format (i.e., the inability to represent numeric values with infinite\n precision), the correlation distance between perfectly correlated random\n variables may *not* be `0` or `2`. In fact, the correlation distance is\n *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n should, however, be within floating-point roundoff error.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation distance matrix or a square 2-dimensional\n ndarray for storing the correlation distance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdistmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrpcorrdist, incrpcorrmat\n","incrpcorrmat":"\nincrpcorrmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation matrix. If not provided a data vector, the accumulator\n function returns the current sample correlation matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation matrix or a square 2-dimensional ndarray for\n storing the correlation matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovmat, incrpcorr, incrpcorrdistmat\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n\n If provided a value, the accumulator function returns an updated product. If\n not provided a value, the accumulator function returns the current product.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrprod();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -10.0\n > v = accumulator()\n -10.0\n\n See Also\n --------\n incrmprod, incrsum, incrsummary\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n\n If provided a value, the accumulator function returns an updated range. If\n not provided a value, the accumulator function returns the current range.\n\n If provided `NaN`, the range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrange();\n > var v = accumulator()\n null\n > v = accumulator( -2.0 )\n 0.0\n > v = accumulator( 1.0 )\n 3.0\n > v = accumulator( 3.0 )\n 5.0\n > v = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmean, incrmin, incrmrange, incrsummary\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n\n If provided input values, the accumulator function returns an updated root\n mean squared error. If not provided input values, the accumulator function\n returns the current root mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrmse();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator()\n 5.0\n\n See Also\n --------\n incrmrmse, incrmse, incrrss\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n\n If provided input values, the accumulator function returns an updated\n residual sum of squares. If not provided input values, the accumulator\n function returns the current residual sum of squares.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrss();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator()\n 50.0\n\n See Also\n --------\n incrmrss, incrmse, incrrmse\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n\n If provided a value, the accumulator function returns an updated corrected\n sample skewness. If not provided a value, the accumulator function returns\n the current corrected sample skewness.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrskewness();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( -5.0 )\n null\n > v = accumulator( -10.0 )\n ~0.492\n > v = accumulator()\n ~0.492\n\n See Also\n --------\n incrkurtosis, incrmean, incrstdev, incrsummary, incrvariance\n","incrspace":"\nincrspace( start, stop[, increment] )\n Generates a linearly spaced numeric array using a provided increment.\n\n If an `increment` is not provided, the default `increment` is `1`.\n\n The output array is guaranteed to include the `start` value but does not\n include the `stop` value.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Array element bound.\n\n increment: number (optional)\n Increment. Default: `1`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = incrspace( 0, 11, 2 )\n [ 0, 2, 4, 6, 8, 10 ]\n\n See Also\n --------\n linspace, logspace\n","incrstdev":"\nincrstdev( [mean] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n\n If provided a value, the accumulator function returns an updated corrected\n sample standard deviation. If not provided a value, the accumulator function\n returns the current corrected sample standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrstdev();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator()\n ~4.95\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrsummary, incrvariance\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrcount, incrmean, incrmsum, incrprod, incrsummary\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrmeanabs, incrmsumabs, incrsum\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrmeanabs2, incrmsumabs2, incrsumabs\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n\n If provided a value, the accumulator function returns an updated summary. If\n not provided a value, the accumulator function returns the current summary.\n\n The returned summary is an object containing the following fields:\n\n - count: count.\n - max: maximum value.\n - min: minimum value.\n - range: range.\n - midrange: mid-range.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - skewness: corrected sample skewness.\n - kurtosis: corrected sample excess kurtosis.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsummary();\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrcount, incrkurtosis, incrmax, incrmean, incrmidrange, incrmin, incrmsummary, incrrange, incrskewness, incrstdev, incrsum, incrvariance\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n\n If provided input values, the accumulator function returns an updated sum.\n If not provided input values, the accumulator function returns the current\n sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumprod();\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator()\n -4.0\n\n See Also\n --------\n incrmsumprod, incrprod, incrsum\n","incrvariance":"\nincrvariance( [mean] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n\n If provided a value, the accumulator function returns an updated unbiased\n sample variance. If not provided a value, the accumulator function returns\n the current unbiased sample variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvariance();\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator()\n 24.5\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrstdev, incrsummary\n","incrvmr":"\nincrvmr( [mean] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvmr();\n > var D = accumulator()\n null\n > D = accumulator( 2.0 )\n 0.0\n > D = accumulator( 1.0 )\n ~0.33\n > D = accumulator()\n ~0.33\n\n See Also\n --------\n incrmean, incrmvmr, incrvariance\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n\n If provided arguments, the accumulator function returns an updated weighted\n mean. If not provided arguments, the accumulator function returns the\n current weighted mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n The accumulator function accepts two arguments:\n\n - x: value.\n - w: weight.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrwmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0, 1.0 )\n 2.0\n > mu = accumulator( 2.0, 0.5 )\n 2.0\n > mu = accumulator( 3.0, 1.5 )\n 2.5\n > mu = accumulator()\n 2.5\n\n See Also\n --------\n increwmean, incrmean, incrmmean\n","ind2sub":"\nind2sub( shape, idx[, options] )\n Converts a linear index to an array of subscripts.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n Returns\n -------\n out: Array\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var s = ind2sub( d, 17 )\n [ 1, 2, 2 ]\n\n\nind2sub.assign( shape, idx[, options], out )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n out: Array|TypedArray|Object\n Output array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var out = [ 0, 0, 0 ];\n > var s = ind2sub.assign( d, 17, out )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind\n","ind2sub.assign":"\nind2sub.assign( shape, idx[, options], out )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n out: Array|TypedArray|Object\n Output array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var out = [ 0, 0, 0 ];\n > var s = ind2sub.assign( d, 17, out )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind","indexOf":"\nindexOf( arr, searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n Search is performed using *strict equality* comparison.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object.\n\n searchElement: any\n Element to find.\n\n fromIndex: integer (optional)\n Starting index (if negative, the start index is determined relative to\n last element).\n\n Returns\n -------\n out: integer\n Index or -1.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ 4, 3, 2, 1 ];\n > var idx = indexOf( arr, 3 )\n 1\n > arr = [ 4, 3, 2, 1 ];\n > idx = indexOf( arr, 5 )\n -1\n\n // Using a `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, 3 )\n 5\n\n // `fromIndex` which exceeds `array` length:\n > arr = [ 1, 2, 3, 4, 2, 5 ];\n > idx = indexOf( arr, 2, 10 )\n -1\n\n // Negative `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n > idx = indexOf( arr, 2, -4 )\n 5\n > idx = indexOf( arr, 2, -1 )\n 7\n\n // Negative `fromIndex` exceeding input `array` length:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, -10 )\n 1\n\n // Array-like objects:\n > var str = 'bebop';\n > idx = indexOf( str, 'o' )\n 3\n\n","inherit":"\ninherit( ctor, superCtor )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n\n This function is not designed to work with ES2015/ES6 classes. For\n ES2015/ES6 classes, use `class` with `extends`.\n\n Parameters\n ----------\n ctor: Object|Function\n Constructor which will inherit.\n\n superCtor: Object|Function\n Super (parent) constructor.\n\n Returns\n -------\n out: Object|Function\n Child constructor.\n\n Examples\n --------\n // Create a parent constructor:\n > function Foo() { return this; };\n > Foo.prototype.beep = function beep() { return 'boop'; };\n\n // Create a child constructor:\n > function Bar() { Foo.call( this ); return this; };\n\n // Setup inheritance:\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var v = bar.beep()\n 'boop'\n\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value[, level] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited enumerable properties.\n\n Examples\n --------\n > var props = inheritedEnumerableProperties( {} )\n\n See Also\n --------\n enumerableProperties, enumerablePropertiesIn, inheritedEnumerablePropertySymbols, inheritedKeys, inheritedNonEnumerableProperties, inheritedProperties\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbols, inheritedKeys, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedKeys":"\ninheritedKeys( value[, level] )\n Returns an array of an object's inherited enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable property names.\n\n Examples\n --------\n > var keys = inheritedKeys( {} )\n\n See Also\n --------\n objectKeys, keysIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value[, level] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited non-enumerable properties.\n\n Examples\n --------\n > var props = inheritedNonEnumerableProperties( {} )\n\n See Also\n --------\n inheritedEnumerableProperties, inheritedNonEnumerablePropertyNames, inheritedNonEnumerablePropertySymbols, inheritedKeys, nonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value[, level] )\n Returns an array of an object's inherited non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited non-enumerable property names.\n\n Examples\n --------\n > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertySymbols, objectKeys, nonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertyNames, nonEnumerableProperties, nonEnumerablePropertyNames, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedProperties":"\ninheritedProperties( value[, level] )\n Returns an array of an object's inherited property names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited property names and symbols.\n\n Examples\n --------\n > var symbols = inheritedProperties( [] )\n\n See Also\n --------\n properties, propertiesIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value, property[, level] )\n Returns a property descriptor for an object's inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n {...}\n\n See Also\n --------\n propertyDescriptor, propertyDescriptorIn, inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value[, level] )\n Returns an object's inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object\n An object's inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = inheritedPropertyDescriptors( obj )\n { 'foo': {...}, ... }\n\n See Also\n --------\n propertyDescriptors, propertyDescriptorsIn, inheritedKeys, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyNames":"\ninheritedPropertyNames( value[, level] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable and non-enumerable property\n names.\n\n Examples\n --------\n > var keys = inheritedPropertyNames( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertySymbols, propertyNames, propertyNamesIn\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value[, level] )\n Returns an array of an object's inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited symbol properties.\n\n Examples\n --------\n > var symbols = inheritedPropertySymbols( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, propertySymbols, propertySymbolsIn\n","inheritedWritableProperties":"\ninheritedWritableProperties( value[, level] )\n Returns an array of an object's inherited writable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited writable properties.\n\n Examples\n --------\n > var props = inheritedWritableProperties( {} )\n\n See Also\n --------\n inheritedWritablePropertyNames, inheritedWritablePropertySymbols, writableProperties, writablePropertiesIn, properties\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value[, level] )\n Returns an array of an object's inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited writable property names.\n\n Examples\n --------\n > var keys = inheritedWritablePropertyNames( {} )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertyNames, writablePropertyNamesIn, properties\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value[, level] )\n Returns an array of an object's inherited writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited writable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedWritablePropertySymbols( [] )\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertySymbols, writablePropertySymbolsIn, properties\n","inmap":"\ninmap( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmap( arr, foo )\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEach, inmapRight, map\n","inmapAsync":"\ninmapAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: value used to update the collection.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 2000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 2000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap\n","inmapAsync.factory":"\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap","inmapRight":"\ninmapRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmapRight( arr, foo )\n 2: 3.0\n 1: 2.0\n 0: 1.0\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEachRight, inmap, mapRight\n","inmapRightAsync":"\ninmapRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: value used to update the collection.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 6000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 6000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight","inspectSinkStream":"\ninspectSinkStream( [options,] clbk )\n Returns a writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream","inspectStream":"\ninspectStream( [options,] clbk )\n Returns a transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream\n","inspectStream.factory":"\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","inspectStream.objectMode":"\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream","instanceOf":"\ninstanceOf( value, constructor )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n\n While the prototype of an `object` created using object literal notion is\n `undefined`, the function returns `true` when provided an `object` literal\n and the `Object` constructor. This maintains consistent behavior with the\n `instanceof` operator.\n\n Parameters\n ----------\n value: any\n Input value.\n\n constructor: Function\n Constructor.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an instance of a provided constructor.\n\n Examples\n --------\n > var bool = instanceOf( [], Array )\n true\n > bool = instanceOf( {}, Object )\n true\n > bool = instanceOf( null, Object )\n false\n\n See Also\n --------\n isPrototypeOf, constructorName, inherit, typeOf\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n\n The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n Examples\n --------\n > INT8_MAX\n 127\n\n See Also\n --------\n INT8_MIN\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n\n The minimum signed 8-bit integer is given by `-(2^7)`.\n\n Examples\n --------\n > INT8_MIN\n -128\n\n See Also\n --------\n INT8_MAX\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n\n Examples\n --------\n > INT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT16_NUM_BYTES, INT32_NUM_BYTES, UINT8_NUM_BYTES\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array()\n \n\n\nInt8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Int8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'\n\n\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n \n\n\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5\n\n\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int8Array.from":"\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int8Array.of":"\nInt8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1","Int8Array.name":"\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n ","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Int8Array.prototype.length":"\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n\n The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n Examples\n --------\n > INT16_MAX\n 32767\n\n See Also\n --------\n INT16_MIN\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n\n The minimum signed 16-bit integer is given by `-(2^15)`.\n\n Examples\n --------\n > INT16_MIN\n -32768\n\n See Also\n --------\n INT16_MAX\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n\n Examples\n --------\n > INT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT32_NUM_BYTES, INT8_NUM_BYTES, UINT16_NUM_BYTES\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array()\n \n\n\nInt16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Int16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'\n\n\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n \n\n\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10\n\n\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int16Array.from":"\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int16Array.of":"\nInt16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2","Int16Array.name":"\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n ","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2","Int16Array.prototype.length":"\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n\n The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n Examples\n --------\n > INT32_MAX\n 2147483647\n\n See Also\n --------\n INT32_MIN\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n\n The minimum signed 32-bit integer is given by `-(2^31)`.\n\n Examples\n --------\n > INT32_MIN\n -2147483648\n\n See Also\n --------\n INT32_MAX\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n\n Examples\n --------\n > INT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT16_NUM_BYTES, INT8_NUM_BYTES, UINT32_NUM_BYTES\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array()\n \n\n\nInt32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 5, 5, 5 ] );\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Int32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'\n\n\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n \n\n\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20\n\n\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int32Array.from":"\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int32Array.of":"\nInt32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4","Int32Array.name":"\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n ","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Int32Array.prototype.length":"\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n\n Examples\n --------\n > IS_BIG_ENDIAN\n \n\n See Also\n --------\n IS_LITTLE_ENDIAN\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n\n Examples\n --------\n > IS_BROWSER\n \n\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n\n Examples\n --------\n > IS_DARWIN\n \n\n","IS_DOCKER":"\nIS_DOCKER\n Boolean indicating if the process is running in a Docker container.\n\n Examples\n --------\n > IS_DOCKER\n \n\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n\n Examples\n --------\n > IS_ELECTRON\n \n\n See Also\n --------\n IS_ELECTRON_MAIN, IS_ELECTRON_RENDERER\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n\n Examples\n --------\n > IS_ELECTRON_MAIN\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_RENDERER\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n\n Examples\n --------\n > IS_ELECTRON_RENDERER\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_MAIN\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n\n Examples\n --------\n > IS_LITTLE_ENDIAN\n \n\n See Also\n --------\n IS_BIG_ENDIAN\n","IS_MOBILE":"\nIS_MOBILE\n Boolean indicating if the current environment is a mobile device.\n\n Examples\n --------\n > IS_MOBILE\n \n\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n\n Examples\n --------\n > IS_NODE\n \n\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n Boolean indicating if the current environment is a touch device.\n\n Examples\n --------\n > IS_TOUCH_DEVICE\n \n\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n\n Examples\n --------\n > IS_WEB_WORKER\n \n\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n\n Examples\n --------\n > IS_WINDOWS\n \n\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value )\n Tests whether a value is an absolute HTTP(S) URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is an absolute HTTP(S) URI.\n\n Examples\n --------\n > var bool = isAbsoluteHttpURI( 'http://example.com/' )\n true\n > bool = isAbsoluteHttpURI( 'example.com' )\n false\n > bool = isAbsoluteHttpURI( 'foo@bar.com' )\n false\n\n See Also\n --------\n isAbsoluteURI","isAbsolutePath":"\nisAbsolutePath( value )\n Tests if a value is an absolute path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an absolute path.\n\n Examples\n --------\n // Windows environment:\n > var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n\n // POSIX environment:\n > bool = isAbsolutePath( '/foo/bar/baz' )\n true\n\n\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false\n\n\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false","isAbsolutePath.win32":"\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath","isAbsoluteURI":"\nisAbsoluteURI( value )\n Tests whether a value is an absolute URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is an absolute URI.\n\n Examples\n --------\n > var bool = isAbsoluteURI( 'http://example.com/' )\n true\n > bool = isAbsoluteURI( 'example.com' )\n false\n > bool = isAbsoluteURI( 'foo@bar.com' )\n false\n\n See Also\n --------\n isRelativeURI","isAccessorArray":"\nisAccessorArray( value )\n Tests if a value is an array-like object supporting the accessor (get/set)\n protocol.\n\n An accessor array is defined as an array, typed array, or an array-like\n object (excluding strings and functions) having `get` and `set` methods for\n accessing array elements.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an accessor array.\n\n Examples\n --------\n > var bool = isAccessorArray( new Complex64Array( 10 ) )\n true\n > bool = isAccessorArray( [] )\n false\n > bool = isAccessorArray( { 'length': 0 } )\n false\n > bool = isAccessorArray( {} )\n false\n\n See Also\n --------\n isArrayLike, isArrayLikeObject, isCollection\n","isAccessorProperty":"\nisAccessorProperty( value, property )\n Tests if an object's own property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has an accessor\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorProperty( obj, 'boop' )\n false\n > bool = isAccessorProperty( obj, 'beep' )\n true\n\n See Also\n --------\n hasOwnProp, isAccessorPropertyIn, isDataProperty\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value, property )\n Tests if an object's own or inherited property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has an\n accessor descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorPropertyIn( obj, 'boop' )\n false\n > bool = isAccessorPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n hasProp, isAccessorProperty, isDataPropertyIn\n","isAlphagram":"\nisAlphagram( value )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n\n The function first checks that an input value is a string before validating\n that the value is an alphagram. For non-string values, the function returns\n `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an alphagram.\n\n Examples\n --------\n > var out = isAlphagram( 'beep' )\n true\n > out = isAlphagram( 'zba' )\n false\n > out = isAlphagram( '' )\n false\n\n See Also\n --------\n isAnagram\n","isAlphaNumeric":"\nisAlphaNumeric( str )\n Tests whether a string contains only alphanumeric characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only alphanumeric\n characters.\n\n Examples\n --------\n > var bool = isAlphaNumeric( 'abc0123456789' )\n true\n > bool = isAlphaNumeric( 'abcdef' )\n true\n > bool = isAlphaNumeric( '0xff' )\n true\n > bool = isAlphaNumeric( '' )\n false\n\n See Also\n --------\n isDigitString\n","isAnagram":"\nisAnagram( str, value )\n Tests if a value is an anagram.\n\n Parameters\n ----------\n str: string\n Comparison string.\n\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an anagram.\n\n Examples\n --------\n > var str1 = 'I am a weakish speller';\n > var str2 = 'William Shakespeare';\n > var bool = isAnagram( str1, str2 )\n true\n > bool = isAnagram( 'bat', 'tabba' )\n false\n\n See Also\n --------\n isAlphagram\n","isArguments":"\nisArguments( value )\n Tests if a value is an arguments object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arguments object.\n\n Examples\n --------\n > function foo() { return arguments; };\n > var bool = isArguments( foo() )\n true\n > bool = isArguments( [] )\n false\n\n","isArray":"\nisArray( value )\n Tests if a value is an array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array.\n\n Examples\n --------\n > var bool = isArray( [] )\n true\n > bool = isArray( {} )\n false\n\n See Also\n --------\n isArrayLike\n","isArrayArray":"\nisArrayArray( value )\n Tests if a value is an array of arrays.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of arrays.\n\n Examples\n --------\n > var bool = isArrayArray( [ [], [] ] )\n true\n > bool = isArrayArray( [ {}, {} ] )\n false\n > bool = isArrayArray( [] )\n false\n\n","isArrayBuffer":"\nisArrayBuffer( value )\n Tests if a value is an ArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an ArrayBuffer.\n\n Examples\n --------\n > var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\n true\n > bool = isArrayBuffer( [] )\n false\n\n See Also\n --------\n isSharedArrayBuffer, isTypedArray\n","isArrayBufferView":"\nisArrayBufferView( value )\n Tests if a value is a `ArrayBuffer` view.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `ArrayBuffer` view.\n\n Examples\n --------\n > var bool = isArrayBufferView( new Int8Array() )\n true\n > bool = isArrayBufferView( [] )\n false\n\n See Also\n --------\n isDataView, isTypedArray\n","isArrayLength":"\nisArrayLength( value )\n Tests if a value is a valid array length.\n\n A valid length property for an Array instance is any integer value on the\n interval [0, 2^32-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a valid array length.\n\n Examples\n --------\n > var bool = isArrayLength( 5 )\n true\n > bool = isArrayLength( 2.0e200 )\n false\n > bool = isArrayLength( -3.14 )\n false\n > bool = isArrayLength( null )\n false\n\n See Also\n --------\n isArray\n","isArrayLike":"\nisArrayLike( value )\n Tests if a value is array-like.\n\n If provided a string, the function returns `true`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is array-like.\n\n Examples\n --------\n > var bool = isArrayLike( [] )\n true\n > bool = isArrayLike( { 'length': 10 } )\n true\n > bool = isArrayLike( 'beep' )\n true\n > bool = isArrayLike( null )\n false\n\n See Also\n --------\n isArray, isArrayLikeObject, isCollection\n","isArrayLikeObject":"\nisArrayLikeObject( value )\n Tests if a value is an array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object.\n\n Examples\n --------\n > var bool = isArrayLikeObject( [] )\n true\n > bool = isArrayLikeObject( { 'length': 10 } )\n true\n > bool = isArrayLikeObject( 'beep' )\n false\n\n See Also\n --------\n isArray, isArrayLike, isCollection\n","isArrowFunction":"\nisArrowFunction( value )\n Tests if a value is an arrow function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arrow function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isArrowFunction( beep )\n false\n > bool = isArrowFunction( {} )\n false\n\n","isASCII":"\nisASCII( str )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string has all ASCII characters.\n\n Examples\n --------\n > var str = 'beep boop';\n > var bool = isASCII( str )\n true\n > bool = isASCII( fromCodePoint( 130 ) )\n false\n\n See Also\n --------\n isString\n","isBetween":"\nisBetween( value, a, b[, left, right] )\n Tests if a value is between two values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is between two values.\n\n Examples\n --------\n > var bool = isBetween( 3.14, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.0, 4.0 )\n true\n > bool = isBetween( 4.0, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.14, 4.0 )\n false\n > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n false\n > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetweenArray\n","isBetweenArray":"\nisBetweenArray( value, a, b[, left, right] )\n Tests if a value is an array-like object where every element is between two\n values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object where every\n element is between two values.\n\n Examples\n --------\n > var arr = [ 3.0, 3.14, 4.0 ];\n > var bool = isBetweenArray( arr, 3.0, 4.0 )\n true\n > bool = isBetweenArray( arr, 3.14, 4.0 )\n false\n > bool = isBetweenArray( arr, 3.0, 3.14 )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetween\n","isBigInt":"\nisBigInt( value )\n Tests if a value is a BigInt.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a BigInt.\n\n Examples\n --------\n > var bool = isBigInt( BigInt( '1' ) )\n true\n > bool = isBigInt( Object( BigInt( '1' ) ) )\n true\n > bool = isBigInt( {} )\n false\n > bool = isBigInt( null )\n false\n > bool = isBigInt( true )\n false\n\n","isBigInt64Array":"\nisBigInt64Array( value )\n Tests if a value is a BigInt64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a BigInt64Array.\n\n Examples\n --------\n > var bool = isBigInt64Array( new BigInt64Array( 10 ) )\n true\n > bool = isBigInt64Array( [] )\n false\n\n See Also\n --------\n isBigUint64Array\n","isBigUint64Array":"\nisBigUint64Array( value )\n Tests if a value is a BigUint64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a BigUint64Array.\n\n Examples\n --------\n > var bool = isBigUint64Array( new BigUint64Array( 10 ) )\n true\n > bool = isBigUint64Array( [] )\n false\n\n See Also\n --------\n isBigInt64Array\n","isBinaryString":"\nisBinaryString( value )\n Tests if a value is a binary string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a binary string.\n\n Examples\n --------\n > var bool = isBinaryString( '1000101' )\n true\n > bool = isBinaryString( 'beep' )\n false\n > bool = isBinaryString( '' )\n false\n\n See Also\n --------\n isString\n","isBlankString":"\nisBlankString( value )\n Tests if a value is a blank string (i.e., an empty string or a string\n consisting only of whitespace characters).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a blank string.\n\n Examples\n --------\n > var bool = isBlankString( ' ' )\n true\n > bool = isBlankString( 'beep' )\n false\n > bool = isBlankString( null )\n false\n\n See Also\n --------\n isString, isEmptyString\n","isBoolean":"\nisBoolean( value )\n Tests if a value is a boolean.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean.\n\n Examples\n --------\n > var bool = isBoolean( false )\n true\n > bool = isBoolean( new Boolean( false ) )\n true\n\n\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false\n\n\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true\n\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false","isBoolean.isObject":"\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true","isBooleanArray":"\nisBooleanArray( value )\n Tests if a value is an array-like object of booleans.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object of booleans.\n\n Examples\n --------\n > var bool = isBooleanArray( [ true, false, true ] )\n true\n > bool = isBooleanArray( [ true, 'abc', false ] )\n false\n\n\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false\n\n\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true\n\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false","isBooleanArray.objects":"\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true","isBoxedPrimitive":"\nisBoxedPrimitive( value )\n Tests if a value is a JavaScript boxed primitive.\n\n Boxed primitive objects can be created with one of the following:\n\n - new Boolean()\n - new Number()\n - new String()\n - Object( Symbol() ) (ES6/ES2015)\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a JavaScript boxed primitive.\n\n Examples\n --------\n > var bool = isBoxedPrimitive( new Boolean( false ) )\n true\n > bool = isBoxedPrimitive( true )\n false\n\n See Also\n --------\n isPrimitive\n","isBuffer":"\nisBuffer( value )\n Tests if a value is a Buffer instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Buffer instance.\n\n Examples\n --------\n > var bool = isBuffer( new Buffer( 'beep' ) )\n true\n > bool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\n true\n > bool = isBuffer( {} )\n false\n > bool = isBuffer( [] )\n false\n\n","isCamelcase":"\nisCamelcase( value )\n Tests if a value is a camelcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a camelcase string.\n\n Examples\n --------\n > var bool = isCamelcase( 'helloWorld' )\n true\n > bool = isCamelcase( 'hello world' )\n false\n\n See Also\n --------\n isString, isConstantcase","isCapitalized":"\nisCapitalized( value )\n Tests if a value is a string having an uppercase first character.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string with an uppercase first\n character.\n\n Examples\n --------\n > var bool = isCapitalized( 'Hello' )\n true\n > bool = isCapitalized( 'world' )\n false\n\n See Also\n --------\n isString\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value )\n Tests if a value is a matrix which is symmetric about its center.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a centrosymmetric matrix.\n\n Examples\n --------\n > var buf = [ 2, 1, 1, 2 ];\n > var M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isCentrosymmetricMatrix( M )\n true\n > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isCentrosymmetricMatrix( 3.14 )\n false\n > bool = isCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isCircular":"\nisCircular( value )\n Tests if an object-like value contains a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an object-like value contains a circular\n reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircular( obj )\n true\n > bool = isCircular( {} )\n false\n > bool = isCircular( null )\n false\n\n See Also\n --------\n isCircularArray, isCircularPlainObject\n","isCircularArray":"\nisCircularArray( value )\n Tests if a value is an array containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing a\n circular reference.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > arr.push( arr );\n > var bool = isCircularArray( arr )\n true\n > bool = isCircularArray( [] )\n false\n > bool = isCircularArray( null )\n false\n\n See Also\n --------\n isCircular, isCircularPlainObject\n","isCircularPlainObject":"\nisCircularPlainObject( value )\n Tests if a value is a plain object containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object containing a\n circular reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircularPlainObject( obj )\n true\n > bool = isCircularPlainObject( {} )\n false\n > bool = isCircularPlainObject( null )\n false\n\n See Also\n --------\n isCircular, isCircularArray\n","isClass":"\nisClass( value )\n Tests if a value is a class.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a class.\n\n Examples\n --------\n > var bool = isClass( class Person {} )\n true\n > bool = isClass( function Person() {} )\n false\n > bool = isClass( {} )\n false\n > bool = isClass( null )\n false\n > bool = isClass( true )\n false\n","isCollection":"\nisCollection( value )\n Tests if a value is a collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a collection.\n\n Examples\n --------\n > var bool = isCollection( [] )\n true\n > bool = isCollection( { 'length': 0 } )\n true\n > bool = isCollection( {} )\n false\n\n See Also\n --------\n isArrayLike, isArrayLikeObject\n","isComplex":"\nisComplex( value )\n Tests if a value is a 64-bit or 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit or 128-bit complex\n number.\n\n Examples\n --------\n > var bool = isComplex( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex( 3.14 )\n false\n > bool = isComplex( {} )\n false\n\n See Also\n --------\n isComplex64, isComplex128\n","isComplex64":"\nisComplex64( value )\n Tests if a value is a 64-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit complex number.\n\n Examples\n --------\n > var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex64( new Complex128( 3.0, 1.0 ) )\n false\n > bool = isComplex64( 3.14 )\n false\n > bool = isComplex64( {} )\n false\n\n See Also\n --------\n isComplex, isComplex128\n","isComplex64Array":"\nisComplex64Array( value )\n Tests if a value is a Complex64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex64Array.\n\n Examples\n --------\n > var bool = isComplex64Array( new Complex64Array( 10 ) )\n true\n > bool = isComplex64Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128Array, isComplexTypedArray\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64MatrixLike( M )\n true\n > bool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64MatrixLike( 3.14 )\n false\n > bool = isComplex64MatrixLike( {} )\n false\n\n See Also\n --------\n isComplex128MatrixLike, isndarrayLike, isMatrixLike\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value )\n Tests if a value is an ndarray-like object containing single-precision\n complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64ndarrayLike( M )\n true\n > bool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64ndarrayLike( 3.14 )\n false\n > bool = isComplex64ndarrayLike( {} )\n false\n\n See Also\n --------\n isComplex128ndarrayLike, isndarrayLike\n","isComplex64VectorLike":"\nisComplex64VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64VectorLike( M )\n true\n > bool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64VectorLike( 3.14 )\n false\n > bool = isComplex64VectorLike( {} )\n false\n\n See Also\n --------\n isComplex128VectorLike, isndarrayLike, isVectorLike\n","isComplex128":"\nisComplex128( value )\n Tests if a value is a 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 128-bit complex number.\n\n Examples\n --------\n > var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex128( new Complex64( 2.0, 2.0 ) )\n false\n > bool = isComplex128( 3.14 )\n false\n > bool = isComplex128( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64\n","isComplex128Array":"\nisComplex128Array( value )\n Tests if a value is a Complex128Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex128Array.\n\n Examples\n --------\n > var bool = isComplex128Array( new Complex128Array( 10 ) )\n true\n > bool = isComplex128Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex128, isComplex64Array, isComplexTypedArray\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128MatrixLike( M )\n true\n > bool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128MatrixLike( 3.14 )\n false\n > bool = isComplex128MatrixLike( {} )\n false\n\n See Also\n --------\n isComplex64MatrixLike, isndarrayLike, isMatrixLike\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value )\n Tests if a value is an ndarray-like object containing double-precision\n complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128ndarrayLike( M )\n true\n > bool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128ndarrayLike( 3.14 )\n false\n > bool = isComplex128ndarrayLike( {} )\n false\n\n See Also\n --------\n isComplex64ndarrayLike, isndarrayLike\n","isComplex128VectorLike":"\nisComplex128VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128VectorLike( M )\n true\n > bool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128VectorLike( 3.14 )\n false\n > bool = isComplex128VectorLike( {} )\n false\n\n See Also\n --------\n isComplex64VectorLike, isndarrayLike, isVectorLike\n","isComplexLike":"\nisComplexLike( value )\n Tests if a value is a complex number-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a complex number-like object.\n\n Examples\n --------\n > var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplexLike( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplexLike( 3.14 )\n false\n > bool = isComplexLike( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128\n","isComplexTypedArray":"\nisComplexTypedArray( value )\n Tests if a value is a complex typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a complex typed array.\n\n Examples\n --------\n > var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n true\n\n See Also\n --------\n isComplex, isComplex64Array, isComplex128Array\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value )\n Tests if a value is complex-typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is complex-typed-array-like.\n\n Examples\n --------\n > var bool = isComplexTypedArrayLike( new Complex128Array() )\n true\n > bool = isComplexTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4,\n ... 'get': function get() {},\n ... 'set': function set() {}\n ... })\n true\n\n See Also\n --------\n isComplexLike, isComplexTypedArray, isComplex64Array, isComplex128Array\n","isComposite":"\nisComposite( value )\n Tests if a value is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a composite number.\n\n Examples\n --------\n > var bool = isComposite( 4.0 )\n true\n > bool = isComposite( new Number( 4.0 ) )\n true\n > bool = isComposite( 3.14 )\n false\n > bool = isComposite( -4.0 )\n false\n > bool = isComposite( null )\n false\n\n\nisComposite.isPrimitive( value )\n Tests if a value is a number primitive which is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n composite number.\n\n Examples\n --------\n > var bool = isComposite.isPrimitive( 4.0 )\n true\n > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n false\n\n\nisComposite.isObject( value )\n Tests if a value is a number object having a value which is a composite\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a composite number.\n\n Examples\n --------\n > var bool = isComposite.isObject( 4.0 )\n false\n > bool = isComposite.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isPrime\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value )\n Tests if a value is a number primitive which is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n composite number.\n\n Examples\n --------\n > var bool = isComposite.isPrimitive( 4.0 )\n true\n > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n false","isComposite.isObject":"\nisComposite.isObject( value )\n Tests if a value is a number object having a value which is a composite\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a composite number.\n\n Examples\n --------\n > var bool = isComposite.isObject( 4.0 )\n false\n > bool = isComposite.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isPrime","isConfigurableProperty":"\nisConfigurableProperty( value, property )\n Tests if an object's own property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurableProperty( obj, 'boop' )\n true\n > bool = isConfigurableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isReadableProperty, isWritableProperty\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurablePropertyIn( obj, 'boop' )\n true\n > bool = isConfigurablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isConstantcase":"\nisConstantcase( value )\n Tests if a value is a constantcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a constantcase string.\n\n Examples\n --------\n > var bool = isConstantcase( 'BEEP_BOOP' )\n true\n > bool = isConstantcase( 'BEEP and BOOP' )\n false\n\n See Also\n --------\n isString, isCamelcase","isCubeNumber":"\nisCubeNumber( value )\n Tests if a value is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber( 8.0 )\n true\n > bool = isCubeNumber( new Number( 8.0 ) )\n true\n > bool = isCubeNumber( 3.14 )\n false\n > bool = isCubeNumber( -5.0 )\n false\n > bool = isCubeNumber( null )\n false\n\n\nisCubeNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a cube\n number.\n\n Examples\n --------\n > var bool = isCubeNumber.isPrimitive( 8.0 )\n true\n > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n false\n\n\nisCubeNumber.isObject( value )\n Tests if a value is a number object having a value which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber.isObject( 8.0 )\n false\n > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a cube\n number.\n\n Examples\n --------\n > var bool = isCubeNumber.isPrimitive( 8.0 )\n true\n > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n false","isCubeNumber.isObject":"\nisCubeNumber.isObject( value )\n Tests if a value is a number object having a value which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber.isObject( 8.0 )\n false\n > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber","isCurrentYear":"\nisCurrentYear( value )\n Tests if a value is the current year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is the current year.\n\n Examples\n --------\n > var bool = isCurrentYear( new Date() )\n true\n > bool = isCurrentYear( currentYear() )\n true\n > bool = isCurrentYear( 2021 )\n false\n > bool = isCurrentYear( null )\n false\n\n","isDataProperty":"\nisDataProperty( value, property )\n Tests if an object's own property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has a data descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataProperty( obj, 'boop' )\n true\n > bool = isDataProperty( obj, 'beep' )\n false\n\n See Also\n --------\n hasOwnProp, isAccessorProperty, isDataPropertyIn\n","isDataPropertyIn":"\nisDataPropertyIn( value, property )\n Tests if an object's own or inherited property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has a data\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataPropertyIn( obj, 'boop' )\n true\n > bool = isDataPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n hasProp, isAccessorPropertyIn, isDataProperty\n","isDataView":"\nisDataView( value )\n Tests if a value is a DataView.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a DataView.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 10 );\n > var bool = isDataView( new DataView( buf ) )\n true\n > bool = isDataView( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isDateObject":"\nisDateObject( value )\n Tests if a value is a Date object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Date object.\n\n Examples\n --------\n > var bool = isDateObject( new Date() )\n true\n > bool = isDateObject( '2017-01-01' )\n false\n\n","isDateObjectArray":"\nisDateObjectArray( value )\n Tests if a value is an array-like object containing only Date objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if value is an array-like object containing only Date\n objects.\n\n Examples\n --------\n > var bool = isDateObjectArray( [ new Date(), new Date() ] )\n true\n > bool = isDateObjectArray( [ {}, {} ] )\n false\n > bool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\n false\n > bool = isDateObjectArray( [] )\n false\n\n See Also\n --------\n isDateObject\n","isDigitString":"\nisDigitString( str )\n Tests whether a string contains only numeric digits.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only numeric digits.\n\n Examples\n --------\n > var bool = isDigitString( '0123456789' )\n true\n > bool = isDigitString( 'abcdef' )\n false\n > bool = isDigitString( '0xff' )\n false\n > bool = isDigitString( '' )\n false\n\n See Also\n --------\n isHexString, isString\n","isDomainName":"\nisDomainName( value )\n Tests if a value is a domain name.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a domain name.\n\n Examples\n --------\n > var bool = isDomainName( 'example.com' )\n true\n > bool = isDomainName( 'foo@bar.com' )\n false\n","isDurationString":"\nisDurationString( value )\n Tests if a value is a duration string.\n\n The function validates that a value is a string. For all other types, the\n function returns `false`.\n\n A duration string is a string containing a sequence of time units. A time\n unit is a nonnegative integer followed by a unit identifier. The following\n unit identifiers are supported:\n\n - d: days.\n - h: hours.\n - m: minutes.\n - s: seconds.\n - ms: milliseconds.\n\n For example, the string `1m3s10ms` is a duration string containing three\n time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n The string `60m` is a duration string containing a single time unit: `60m`\n (60 minutes). Time units must be supplied in descending order of magnitude\n (i.e., days, hours, minutes, seconds, milliseconds).\n\n Duration strings are case insensitive. For example, the string `1M3S10MS` is\n equivalent to `1m3s10ms`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a duration string.\n\n Examples\n --------\n > var bool = isDurationString( '1d' )\n true\n > bool = isDurationString( '1h' )\n true\n > bool = isDurationString( 'beep' )\n false\n","isEmailAddress":"\nisEmailAddress( value )\n Tests if a value is an email address.\n\n Validation is not rigorous. *9* RFCs relate to email addresses, and\n accounting for all of them is a fool's errand. The function performs the\n simplest validation; i.e., requiring at least one `@` symbol.\n\n For rigorous validation, send a confirmation email. If the email bounces,\n consider the email invalid.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an email address.\n\n Examples\n --------\n > var bool = isEmailAddress( 'beep@boop.com' )\n true\n > bool = isEmailAddress( 'beep' )\n false\n > bool = isEmailAddress( null )\n false\n\n","isEmptyArray":"\nisEmptyArray( value )\n Tests if a value is an empty array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty array.\n\n Examples\n --------\n > var bool = isEmptyArray( [] )\n true\n > bool = isEmptyArray( [ 1, 2, 3 ] )\n false\n > bool = isEmptyArray( {} )\n false\n\n See Also\n --------\n isArray, isEmptyArrayLikeObject, isEmptyCollection\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value )\n Tests if a value is an empty array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an empty array-like object.\n\n Examples\n --------\n > var bool = isEmptyArrayLikeObject( [] )\n true\n > bool = isEmptyArrayLikeObject( { 'length': 0 } )\n true\n > bool = isEmptyArrayLikeObject( '' )\n false\n\n See Also\n --------\n isArrayLikeObject, isEmptyArray, isEmptyCollection\n","isEmptyCollection":"\nisEmptyCollection( value )\n Tests if a value is an empty collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty collection.\n\n Examples\n --------\n > var bool = isEmptyCollection( [] )\n true\n > bool = isEmptyCollection( { 'length': 0 } )\n true\n > bool = isEmptyCollection( [ 1, 2, 3 ] )\n false\n > bool = isEmptyCollection( {} )\n false\n\n See Also\n --------\n isCollection, isEmptyArray, isEmptyArrayLikeObject\n","isEmptyObject":"\nisEmptyObject( value )\n Tests if a value is an empty object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty object.\n\n Examples\n --------\n > var bool = isEmptyObject( {} )\n true\n > bool = isEmptyObject( { 'beep': 'boop' } )\n false\n > bool = isEmptyObject( [] )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isEmptyString":"\nisEmptyString( value )\n Tests if a value is an empty string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty string.\n\n Examples\n --------\n > var bool = isEmptyString( '' )\n true\n > bool = isEmptyString( new String( '' ) )\n true\n > bool = isEmptyString( 'beep' )\n false\n > bool = isEmptyString( [] )\n false\n\n\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false\n\n\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false","isEmptyString.isObject":"\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString","isEnumerableProperty":"\nisEnumerableProperty( value, property )\n Tests if an object's own property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is enumerable.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isEnumerableProperty( beep, 'boop' )\n true\n > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isEnumerablePropertyIn( obj, 'boop' )\n true\n > bool = isEnumerablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isEqualArray":"\nisEqualArray( v1, v2 )\n Tests if two arguments are both generic arrays and have equal values.\n\n The function performs strict equality comparison; thus, the function treats\n `-0` and `+0` as equal and `NaNs` as distinct.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are equal.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isEqualArray( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isEqualArray( x, y )\n false\n\n See Also\n --------\n isArray, isSameArray\n","isEqualDateObject":"\nisEqualDateObject( d1, d2 )\n Tests if two values are both Date objects corresponding to the same date\n and time.\n\n Parameters\n ----------\n d1: any\n First input value.\n d2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether both values are Date objects corresponding to\n the same date and time.\n\n Examples\n --------\n > var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > var d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > var bool = isEqualDateObject( d1, d2 )\n true\n > d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > d2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\n > bool = isEqualDateObject( d1, d2 )\n false\n\n See Also\n --------\n isDateObject, isSameValue\n","isError":"\nisError( value )\n Tests if a value is an Error object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Error object.\n\n Examples\n --------\n > var bool = isError( new Error( 'beep' ) )\n true\n > bool = isError( {} )\n false\n\n","isEvalError":"\nisEvalError( value )\n Tests if a value is an EvalError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided an EvalError (or a descendant) object,\n false positives may occur due to the fact that the EvalError constructor\n inherits from Error and has no internal class of its own. Hence, EvalError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an EvalError object.\n\n Examples\n --------\n > var bool = isEvalError( new EvalError( 'beep' ) )\n true\n > bool = isEvalError( {} )\n false\n\n See Also\n --------\n isError\n","isEven":"\nisEven( value )\n Tests if a value is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an even number.\n\n Examples\n --------\n > var bool = isEven( 4.0 )\n true\n > bool = isEven( new Number( 4.0 ) )\n true\n > bool = isEven( 3.0 )\n false\n > bool = isEven( -3.14 )\n false\n > bool = isEven( null )\n false\n\n\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false\n\n\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd\n","isEven.isPrimitive":"\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false","isEven.isObject":"\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd","isFalsy":"\nisFalsy( value )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is falsy.\n\n Examples\n --------\n > var bool = isFalsy( false )\n true\n > bool = isFalsy( '' )\n true\n > bool = isFalsy( 0 )\n true\n > bool = isFalsy( null )\n true\n > bool = isFalsy( void 0 )\n true\n > bool = isFalsy( NaN )\n true\n > bool = isFalsy( {} )\n false\n > bool = isFalsy( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isFalsyArray":"\nisFalsyArray( value )\n Tests if a value is an array-like object containing only falsy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only falsy values.\n\n Examples\n --------\n > var bool = isFalsyArray( [ null, '' ] )\n true\n > bool = isFalsyArray( [ {}, [] ] )\n false\n > bool = isFalsyArray( [] )\n false\n\n See Also\n --------\n isFalsy, isTruthyArray\n","isFinite":"\nisFinite( value )\n Tests if a value is a finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite number.\n\n Examples\n --------\n > var bool = isFinite( 5.0 )\n true\n > bool = isFinite( new Number( 5.0 ) )\n true\n > bool = isFinite( 1.0/0.0 )\n false\n > bool = isFinite( null )\n false\n\n\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false","isFinite.isObject":"\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite","isFiniteArray":"\nisFiniteArray( value )\n Tests if a value is an array-like object of finite numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of finite\n numbers.\n\n Examples\n --------\n > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n false\n\n\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isFiniteArray.objects":"\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite","isFloat32Array":"\nisFloat32Array( value )\n Tests if a value is a Float32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float32Array.\n\n Examples\n --------\n > var bool = isFloat32Array( new Float32Array( 10 ) )\n true\n > bool = isFloat32Array( [] )\n false\n\n See Also\n --------\n isFloat64Array\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32MatrixLike( M )\n true\n > bool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32MatrixLike( 3.14 )\n false\n > bool = isFloat32MatrixLike( {} )\n false\n\n See Also\n --------\n isFloat64MatrixLike, isndarrayLike, isMatrixLike\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value )\n Tests if a value is an ndarray-like object containing single-precision\n floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32ndarrayLike( M )\n true\n > bool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32ndarrayLike( 3.14 )\n false\n > bool = isFloat32ndarrayLike( {} )\n false\n\n See Also\n --------\n isFloat64ndarrayLike, isndarrayLike\n","isFloat32VectorLike":"\nisFloat32VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32VectorLike( M )\n true\n > bool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32VectorLike( 3.14 )\n false\n > bool = isFloat32VectorLike( {} )\n false\n\n See Also\n --------\n isFloat64VectorLike, isndarrayLike, isVectorLike\n","isFloat64Array":"\nisFloat64Array( value )\n Tests if a value is a Float64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float64Array.\n\n Examples\n --------\n > var bool = isFloat64Array( new Float64Array( 10 ) )\n true\n > bool = isFloat64Array( [] )\n false\n\n See Also\n --------\n isFloat32Array\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64MatrixLike( M )\n true\n > bool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64MatrixLike( 3.14 )\n false\n > bool = isFloat64MatrixLike( {} )\n false\n\n See Also\n --------\n isFloat32MatrixLike, isndarrayLike, isMatrixLike\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value )\n Tests if a value is an ndarray-like object containing double-precision\n floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64ndarrayLike( M )\n true\n > bool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64ndarrayLike( 3.14 )\n false\n > bool = isFloat64ndarrayLike( {} )\n false\n\n See Also\n --------\n isFloat32ndarrayLike, isndarrayLike\n","isFloat64VectorLike":"\nisFloat64VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64VectorLike( M )\n true\n > bool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64VectorLike( 3.14 )\n false\n > bool = isFloat64VectorLike( {} )\n false\n\n See Also\n --------\n isFloat32VectorLike, isndarrayLike, isVectorLike\n","isFunction":"\nisFunction( value )\n Tests if a value is a function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isFunction( beep )\n true\n > bool = isFunction( {} )\n false\n\n","isFunctionArray":"\nisFunctionArray( value )\n Tests if a value is an array-like object containing only functions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n functions.\n\n Examples\n --------\n > function beep() {};\n > function boop() {};\n > var bool = isFunctionArray( [ beep, boop ] )\n true\n > bool = isFunctionArray( [ {}, beep ] )\n false\n > bool = isFunctionArray( [] )\n false\n\n See Also\n --------\n isArray\n","isGeneratorObject":"\nisGeneratorObject( value )\n Tests if a value is a generator object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a generator object.\n\n Examples\n --------\n > function* generateID() {\n ... var idx = 0;\n ... while ( idx < idx+1 ) {\n ... yield idx;\n ... idx += 1;\n ... }\n ... };\n > var bool = isGeneratorObject( generateID() )\n true\n > bool = isGeneratorObject( generateID )\n false\n > bool = isGeneratorObject( {} )\n false\n > bool = isGeneratorObject( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObjectLike\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value )\n Tests if a value is generator object-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is generator object-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {},\n ... 'return': function noop() {},\n ... 'throw': function noop() {}\n ... };\n > var bool = isGeneratorObjectLike( obj )\n true\n > bool = isGeneratorObjectLike( {} )\n false\n > bool = isGeneratorObjectLike( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObject\n","isgzipBuffer":"\nisgzipBuffer( value )\n Tests if a value is a gzip buffer.\n\n A gzip buffer is defined as either a Node.js Buffer or Uint8Array which\n contains a 10-byte header, a body containing the compressed payload, and an\n 8-byte footer containing a CRC-32 checksum and the length of the original\n uncompressed data, modulo 2^32.\n\n This function only examines the 10-byte header to ensure the header includes\n the expected magic number and compression method. The function does not\n perform an integrity check.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a gzip buffer.\n\n Examples\n --------\n > var buf = new Uint8Array( 20 );\n > buf[ 0 ] = 31; // 0x1f => magic number\n > buf[ 1 ] = 139; // 0x8b\n > buf[ 2 ] = 8; // 0x08 => compression method\n > var bool = isgzipBuffer( buf )\n true\n > bool = isgzipBuffer( [] )\n false\n\n See Also\n --------\n isBuffer, isUint8Array\n","isHexString":"\nisHexString( str )\n Tests whether a string contains only hexadecimal digits.\n\n The function does not recognize `x` (as in the standard `0x` prefix).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only hexadecimal digits.\n\n Examples\n --------\n > var bool = isHexString( '0123456789abcdefABCDEF' )\n true\n > bool = isHexString( '0xffffff' )\n false\n > bool = isHexString( 'x' )\n false\n > bool = isHexString( '' )\n false\n\n See Also\n --------\n isString\n","isInfinite":"\nisInfinite( value )\n Tests if a value is an infinite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an infinite number.\n\n Examples\n --------\n > var bool = isInfinite( 1.0/0.0 )\n true\n > bool = isInfinite( new Number( -1.0/0.0 ) )\n true\n > bool = isInfinite( 5.0 )\n false\n > bool = isInfinite( '1.0/0.0' )\n false\n\n\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false","isInfinite.isObject":"\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite","isInheritedProperty":"\nisInheritedProperty( value, property )\n Tests if an object has an inherited property.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has an inherited property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isInheritedProperty( beep, 'boop' )\n false\n > bool = isInheritedProperty( beep, 'toString' )\n true\n > bool = isInheritedProperty( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp, hasProp\n","isInt8Array":"\nisInt8Array( value )\n Tests if a value is an Int8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int8Array.\n\n Examples\n --------\n > var bool = isInt8Array( new Int8Array( 10 ) )\n true\n > bool = isInt8Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt32Array\n","isInt16Array":"\nisInt16Array( value )\n Tests if a value is an Int16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int16Array.\n\n Examples\n --------\n > var bool = isInt16Array( new Int16Array( 10 ) )\n true\n > bool = isInt16Array( [] )\n false\n\n See Also\n --------\n isInt32Array, isInt8Array\n","isInt32Array":"\nisInt32Array( value )\n Tests if a value is an Int32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int32Array.\n\n Examples\n --------\n > var bool = isInt32Array( new Int32Array( 10 ) )\n true\n > bool = isInt32Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt8Array\n","isInteger":"\nisInteger( value )\n Tests if a value is an integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an integer.\n\n Examples\n --------\n > var bool = isInteger( 5.0 )\n true\n > bool = isInteger( new Number( 5.0 ) )\n true\n > bool = isInteger( -3.14 )\n false\n > bool = isInteger( null )\n false\n\n\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false","isInteger.isObject":"\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber","isIntegerArray":"\nisIntegerArray( value )\n Tests if a value is an array-like object of integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of integer\n values.\n\n Examples\n --------\n > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isIntegerArray( [ -3.0, '3.0' ] )\n false\n\n\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isIntegerArray.objects":"\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isIterableLike":"\nisIterableLike( value )\n Tests if a value is iterable-like.\n\n In order to be iterable, an object must implement the @@iterator method,\n which, when called, returns an iterator protocol-compliant object.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n In environments lacking Symbol.iterator support, this function always\n returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterable-like.\n\n Examples\n --------\n > var bool = isIterableLike( [ 1, 2, 3 ] )\n \n > bool = isIterableLike( {} )\n false\n > bool = isIterableLike( null )\n false\n\n See Also\n --------\n isIteratorLike\n","isIteratorLike":"\nisIteratorLike( value )\n Tests if a value is iterator-like.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterator-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {}\n ... };\n > var bool = isIteratorLike( obj )\n true\n > bool = isIteratorLike( {} )\n false\n > bool = isIteratorLike( null )\n false\n\n See Also\n --------\n isIterableLike\n","isJSON":"\nisJSON( value )\n Tests if a value is a parseable JSON string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a parseable JSON string.\n\n Examples\n --------\n > var bool = isJSON( '{\"a\":5}' )\n true\n > bool = isJSON( '{a\":5}' )\n false\n\n","isKebabcase":"\nisKebabcase( value )\n Tests if a value is a string in kebab case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in kebab case.\n\n Examples\n --------\n > var bool = isKebabcase( 'beep-boop' )\n true\n > bool = isKebabcase( 'BEEP_BOOP' )\n false\n\n See Also\n --------\n isString","isLeapYear":"\nisLeapYear( value )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n A leap year is defined as any year which is exactly divisible by 4, except\n for years which are exactly divisible by 100 and not by 400. In this\n definition, 100 corresponds to years marking a new century, and 400\n corresponds to the length of the *leap cycle*.\n\n If not provided any arguments, the function returns a boolean indicating\n if the current year (according to local time) is a leap year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value corresponds to a leap year.\n\n Examples\n --------\n > var bool = isLeapYear( new Date() )\n \n > bool = isLeapYear( 1996 )\n true\n > bool = isLeapYear( 2001 )\n false\n\n","isLocalhost":"\nisLocalhost( value )\n Tests whether a value is a localhost hostname.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a localhost hostname.\n\n Examples\n --------\n > var bool = isLocalhost( 'localhost' )\n true\n > bool = isLocalhost( '127.0.0.1' )\n true\n > bool = isLocalhost( 'stdlib.io' )\n false\n","isLowercase":"\nisLowercase( value )\n Tests if a value is a lowercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a lowercase string.\n\n Examples\n --------\n > var bool = isLowercase( 'hello' )\n true\n > bool = isLowercase( 'World' )\n false\n\n See Also\n --------\n isString, isUppercase\n","isMatrixLike":"\nisMatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isMatrixLike( M )\n true\n > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isMatrixLike( 3.14 )\n false\n > bool = isMatrixLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isndarrayLike, isTypedArrayLike, isVectorLike\n","isMethod":"\nisMethod( value, property )\n Tests if an object has a specified method name.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n The function only searches own properties.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': function beep() { return 'beep'; } };\n > var bool = isMethod( beep, 'boop' )\n true\n > bool = isMethod( beep, 'toString' )\n false\n\n See Also\n --------\n hasOwnProp, isFunction, isMethodIn\n","isMethodIn":"\nisMethodIn( value, property )\n Tests if an object has a specified method name, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isMethodIn( beep, 'toString' )\n true\n > bool = isMethodIn( beep, 'boop' )\n false\n > bool = isMethodIn( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp, isFunction, isMethod\n","isMultiSlice":"\nisMultiSlice( value )\n Tests if a value is a MultiSlice object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a MultiSlice object.\n\n Examples\n --------\n > var bool = isMultiSlice( new MultiSlice() )\n true\n > bool = isMultiSlice( 3.14 )\n false\n > bool = isMultiSlice( {} )\n false\n\n See Also\n --------\n isSlice, MultiSlice\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value )\n Tests if a value is named typed tuple-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is named typed tuple-like.\n\n Examples\n --------\n > var Point = namedtypedtuple( [ 'x', 'y' ] );\n > var p = new Point();\n > var bool = isNamedTypedTupleLike( p )\n true\n > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isNamedTypedTupleLike( 3.14 )\n false\n > bool = isNamedTypedTupleLike( {} )\n false\n\n See Also\n --------\n namedtypedtuple\n","isnan":"\nisnan( value )\n Tests if a value is NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is NaN.\n\n Examples\n --------\n > var bool = isnan( NaN )\n true\n > bool = isnan( new Number( NaN ) )\n true\n > bool = isnan( 3.14 )\n false\n > bool = isnan( null )\n false\n\n\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false\n\n\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber\n","isnan.isPrimitive":"\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false","isnan.isObject":"\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber","isNaNArray":"\nisNaNArray( value )\n Tests if a value is an array-like object containing only NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n NaN values.\n\n Examples\n --------\n > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n true\n > bool = isNaNArray( [ NaN, 2 ] )\n false\n\n\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true\n\n\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan\n","isNaNArray.primitives":"\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true","isNaNArray.objects":"\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan","isNativeFunction":"\nisNativeFunction( value )\n Tests if a value is a native function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a native function.\n\n Examples\n --------\n > var bool = isNativeFunction( Date )\n true\n > function beep() {};\n > bool = isNativeFunction( beep )\n false\n > bool = isNativeFunction( {} )\n false\n\n See Also\n --------\n isFunction\n","isndarrayLike":"\nisndarrayLike( value )\n Tests if a value is ndarray-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is ndarray-like.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLike( M )\n true\n > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isndarrayLike( 3.14 )\n false\n > bool = isndarrayLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isTypedArrayLike, isVectorLike\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value, dtype )\n Tests if a value is an ndarray-like object having a specified data type.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n dtype: any\n Data type value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object having a\n specified data type.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLikeWithDataType( M, 'generic' )\n true\n > bool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\n false\n > bool = isndarrayLikeWithDataType( 3.14, 'generic' )\n false\n > bool = isndarrayLikeWithDataType( {}, 'generic' )\n false\n\n See Also\n --------\n isndarrayLike\n","isNegativeFinite":"\nisNegativeFinite( value )\n Tests if a value is a finite negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite negative number.\n\n Examples\n --------\n > var bool = isNegativeFinite( -5.0 )\n true\n > bool = isNegativeFinite( new Number( -5.0 ) )\n true\n > bool = isNegativeFinite( -3.14 )\n true\n > bool = isNegativeFinite( 5.0 )\n false\n > bool = isNegativeFinite( null )\n false\n > bool = isNegativeFinite( -1.0/0.0 )\n false\n > bool = isNegativeFinite( new Number( -1.0/0.0 ) )\n false\n\n\nisNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isPrimitive( -3.0 )\n true\n > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n false\n > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisNegativeFinite.isObject( value )\n Tests if a value is a number object having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isObject( -3.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n true\n > bool = isNegativeFinite.isObject( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n false\n\n See Also\n --------\n isFinite, isNegativeNumber, isPositiveFinite\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isPrimitive( -3.0 )\n true\n > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n false\n > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n false","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value )\n Tests if a value is a number object having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isObject( -3.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n true\n > bool = isNegativeFinite.isObject( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n false\n\n See Also\n --------\n isFinite, isNegativeNumber, isPositiveFinite","isNegativeInteger":"\nisNegativeInteger( value )\n Tests if a value is a negative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative integer.\n\n Examples\n --------\n > var bool = isNegativeInteger( -5.0 )\n true\n > bool = isNegativeInteger( new Number( -5.0 ) )\n true\n > bool = isNegativeInteger( 5.0 )\n false\n > bool = isNegativeInteger( -3.14 )\n false\n > bool = isNegativeInteger( null )\n false\n\n\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isNegativeIntegerArray":"\nisNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only negative integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative integers.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNegativeNumber":"\nisNegativeNumber( value )\n Tests if a value is a negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative number.\n\n Examples\n --------\n > var bool = isNegativeNumber( -5.0 )\n true\n > bool = isNegativeNumber( new Number( -5.0 ) )\n true\n > bool = isNegativeNumber( -3.14 )\n true\n > bool = isNegativeNumber( 5.0 )\n false\n > bool = isNegativeNumber( null )\n false\n\n\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber","isNegativeNumberArray":"\nisNegativeNumberArray( value )\n Tests if a value is an array-like object containing only negative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNegativeZero":"\nisNegativeZero( value )\n Tests if a value is negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero( -0.0 )\n true\n > bool = isNegativeZero( new Number( -0.0 ) )\n true\n > bool = isNegativeZero( -3.14 )\n false\n > bool = isNegativeZero( 0.0 )\n false\n > bool = isNegativeZero( null )\n false\n\n\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false\n\n\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false","isNegativeZero.isObject":"\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero","isNodeBuiltin":"\nisNodeBuiltin( str )\n Tests whether a string matches a Node.js built-in module name.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string matches a Node.js built-in module\n name.\n\n Examples\n --------\n > var bool = isNodeBuiltin( 'cluster' )\n true\n > bool = isNodeBuiltin( 'crypto' )\n true\n > bool = isNodeBuiltin( 'fs-extra' )\n false\n > bool = isNodeBuiltin( '' )\n false\n\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value )\n Tests if a value is Node duplex stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node duplex stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Duplex;\n > s = new Stream();\n > var bool = isNodeDuplexStreamLike( s )\n true\n > bool = isNodeDuplexStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value )\n Tests if a value is Node readable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node readable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Readable;\n > s = new Stream();\n > var bool = isNodeReadableStreamLike( s )\n true\n > bool = isNodeReadableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if running in a Node.js REPL environment.\n\n Examples\n --------\n > var bool = isNodeREPL()\n \n\n","isNodeStreamLike":"\nisNodeStreamLike( value )\n Tests if a value is Node stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Stream;\n > s = new Stream();\n > var bool = isNodeStreamLike( s )\n true\n > bool = isNodeStreamLike( {} )\n false\n\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value )\n Tests if a value is Node transform stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node transform stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Transform;\n > s = new Stream();\n > var bool = isNodeTransformStreamLike( s )\n true\n > bool = isNodeTransformStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value )\n Tests if a value is Node writable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node writable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Writable;\n > s = new Stream();\n > var bool = isNodeWritableStreamLike( s )\n true\n > bool = isNodeWritableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value, property )\n Tests if an object's own property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurableProperty( obj, 'boop' )\n false\n > bool = isNonConfigurableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n false\n > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value, property )\n Tests if an object's own property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerableProperty( obj, 'boop' )\n false\n > bool = isNonEnumerableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadableProperty, isWritableProperty\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n false\n > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadablePropertyIn, isWritablePropertyIn\n","isNonNegativeFinite":"\nisNonNegativeFinite( value )\n Tests if a value is a nonnegative finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative finite number.\n\n Examples\n --------\n > var bool = isNonNegativeFinite( 5.0 )\n true\n > bool = isNonNegativeFinite( new Number( 5.0 ) )\n true\n > bool = isNonNegativeFinite( 3.14 )\n true\n > bool = isNonNegativeFinite( -5.0 )\n false\n > bool = isNonNegativeFinite( null )\n false\n > bool = isNonNegativeFinite( PINF )\n false\n\n\nisNonNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeFinite.isObject( value )\n Tests if a value is a number object having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a \n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isObject( 3.0 )\n false\n > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonNegativeNumber, isNumber\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value )\n Tests if a value is a number object having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a \n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isObject( 3.0 )\n false\n > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonNegativeNumber, isNumber","isNonNegativeInteger":"\nisNonNegativeInteger( value )\n Tests if a value is a nonnegative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative integer.\n\n Examples\n --------\n > var bool = isNonNegativeInteger( 5.0 )\n true\n > bool = isNonNegativeInteger( new Number( 5.0 ) )\n true\n > bool = isNonNegativeInteger( 3.14 )\n false\n > bool = isNonNegativeInteger( -5.0 )\n false\n > bool = isNonNegativeInteger( null )\n false\n\n\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNonNegativeNumber, isNumber\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNonNegativeNumber, isNumber","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative integers.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonNegativeNumber":"\nisNonNegativeNumber( value )\n Tests if a value is a nonnegative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative number.\n\n Examples\n --------\n > var bool = isNonNegativeNumber( 5.0 )\n true\n > bool = isNonNegativeNumber( new Number( 5.0 ) )\n true\n > bool = isNonNegativeNumber( 3.14 )\n true\n > bool = isNonNegativeNumber( -5.0 )\n false\n > bool = isNonNegativeNumber( null )\n false\n\n\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNonNegativeFinite, isNonNegativeInteger, isNumber\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNonNegativeFinite, isNonNegativeInteger, isNumber","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonPositiveFinite":"\nisNonPositiveFinite( value )\n Tests if a value is a nonpositive finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive finite number.\n\n Examples\n --------\n > var bool = isNonPositiveFinite( -5.0 )\n true\n > bool = isNonPositiveFinite( new Number( -5.0 ) )\n true\n > bool = isNonPositiveFinite( -3.14 )\n true\n > bool = isNonPositiveFinite( 5.0 )\n false\n > bool = isNonPositiveFinite( null )\n false\n\n\nisNonPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveFinite.isObject( value )\n Tests if a value is a number object having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isObject( -3.0 )\n false\n > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonPositiveNumber\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value )\n Tests if a value is a number object having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isObject( -3.0 )\n false\n > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonPositiveNumber","isNonPositiveInteger":"\nisNonPositiveInteger( value )\n Tests if a value is a nonpositive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive integer.\n\n Examples\n --------\n > var bool = isNonPositiveInteger( -5.0 )\n true\n > bool = isNonPositiveInteger( new Number( -5.0 ) )\n true\n > bool = isNonPositiveInteger( 5.0 )\n false\n > bool = isNonPositiveInteger( -3.14 )\n false\n > bool = isNonPositiveInteger( null )\n false\n\n\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive integers.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonPositiveNumber":"\nisNonPositiveNumber( value )\n Tests if a value is a nonpositive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive number.\n\n Examples\n --------\n > var bool = isNonPositiveNumber( -5.0 )\n true\n > bool = isNonPositiveNumber( new Number( -5.0 ) )\n true\n > bool = isNonPositiveNumber( -3.14 )\n true\n > bool = isNonPositiveNumber( 5.0 )\n false\n > bool = isNonPositiveNumber( null )\n false\n\n\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value )\n Tests if a value is a non-symmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a non-symmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 2, 3, 4 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isNonSymmetricMatrix( M )\n true\n > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isNonSymmetricMatrix( 3.14 )\n false\n > bool = isNonSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isNull":"\nisNull( value )\n Tests if a value is null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is null.\n\n Examples\n --------\n > var bool = isNull( null )\n true\n > bool = isNull( true )\n false\n\n See Also\n --------\n isUndefined, isUndefinedOrNull\n","isNullArray":"\nisNullArray( value )\n Tests if a value is an array-like object containing only null values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n null values.\n\n Examples\n --------\n > var bool = isNullArray( [ null, null, null ] )\n true\n > bool = isNullArray( [ NaN, 2, null ] )\n false\n\n See Also\n --------\n isArray, isNull\n","isNumber":"\nisNumber( value )\n Tests if a value is a number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number.\n\n Examples\n --------\n > var bool = isNumber( 3.14 )\n true\n > bool = isNumber( new Number( 3.14 ) )\n true\n > bool = isNumber( NaN )\n true\n > bool = isNumber( null )\n false\n\n\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false\n\n\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true\n\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false","isNumber.isObject":"\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true","isNumberArray":"\nisNumberArray( value )\n Tests if a value is an array-like object containing only numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n numbers.\n\n Examples\n --------\n > var bool = isNumberArray( [ 1, 2, 3 ] )\n true\n > bool = isNumberArray( [ '1', 2, 3 ] )\n false\n\n\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false\n\n\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray\n","isNumberArray.primitives":"\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false","isNumberArray.objects":"\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray","isNumericArray":"\nisNumericArray( value )\n Tests if a value is a numeric array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a numeric array.\n\n Examples\n --------\n > var bool = isNumericArray( new Int8Array( 10 ) )\n true\n > bool = isNumericArray( [ 1, 2, 3 ] )\n true\n > bool = isNumericArray( [ '1', '2', '3' ] )\n false\n\n See Also\n --------\n isArray, isNumberArray, isTypedArray\n\n","isObject":"\nisObject( value )\n Tests if a value is an object; e.g., `{}`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an object.\n\n Examples\n --------\n > var bool = isObject( {} )\n true\n > bool = isObject( true )\n false\n\n See Also\n --------\n isObjectLike, isPlainObject\n","isObjectArray":"\nisObjectArray( value )\n Tests if a value is an array-like object containing only objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n objects.\n\n Examples\n --------\n > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n true\n > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isObject\n","isObjectLike":"\nisObjectLike( value )\n Tests if a value is object-like.\n\n Return values are the same as would be obtained using the built-in `typeof`\n operator except that `null` is not considered an object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is object-like.\n\n Examples\n --------\n > var bool = isObjectLike( {} )\n true\n > bool = isObjectLike( [] )\n true\n > bool = isObjectLike( null )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isOdd":"\nisOdd( value )\n Tests if a value is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an odd number.\n\n Examples\n --------\n > var bool = isOdd( 5.0 )\n true\n > bool = isOdd( new Number( 5.0 ) )\n true\n > bool = isOdd( 4.0 )\n false\n > bool = isOdd( new Number( 4.0 ) )\n false\n > bool = isOdd( -3.14 )\n false\n > bool = isOdd( null )\n false\n\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false\n\n\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false","isOdd.isObject":"\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven","isoWeeksInYear":"\nisoWeeksInYear( [year] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n\n By default, the function returns the number of ISO weeks in the current year\n (according to local time). To determine the number of ISO weeks for a\n particular year, provide either a year or a `Date` object.\n\n Parameters\n ----------\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Number of ISO weeks in a year.\n\n Examples\n --------\n > var num = isoWeeksInYear()\n \n > num = isoWeeksInYear( 2015 )\n 53\n > num = isoWeeksInYear( 2017 )\n 52\n\n","isPascalcase":"\nisPascalcase( value )\n Tests if a value is a string in Pascal case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in Pascal case.\n\n Examples\n --------\n > var bool = isPascalcase( 'HelloWorld' )\n true\n > bool = isPascalcase( 'hello-world' )\n false\n\n See Also\n --------\n isString","isPersymmetricMatrix":"\nisPersymmetricMatrix( value )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a persymmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 2, 3, 1 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isPersymmetricMatrix( M )\n true\n > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isPersymmetricMatrix( 3.14 )\n false\n > bool = isPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isPlainObject":"\nisPlainObject( value )\n Tests if a value is a plain object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object.\n\n Examples\n --------\n > var bool = isPlainObject( {} )\n true\n > bool = isPlainObject( null )\n false\n\n See Also\n --------\n isObject\n","isPlainObjectArray":"\nisPlainObjectArray( value )\n Tests if a value is an array-like object containing only plain objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n plain objects.\n\n Examples\n --------\n > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n false\n > bool = isPlainObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPlainObject\n","isPositiveFinite":"\nisPositiveFinite( value )\n Tests if a value is a positive finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a positive finite number.\n\n Examples\n --------\n > var bool = isPositiveFinite( 5.0 )\n true\n > bool = isPositiveFinite( new Number( 5.0 ) )\n true\n > bool = isPositiveFinite( 3.14 )\n true\n > bool = isPositiveFinite( -5.0 )\n false\n > var bool = isPositiveFinite( 1.0/0.0 )\n false\n > bool = isPositiveFinite( new Number( 1.0/0.0 ) )\n false\n > bool = isPositiveFinite( null )\n false\n\n\nisPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a number primitive having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isPrimitive( 3.0 )\n true\n > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n false\n > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveFinite.isObject( value )\n Tests if a value is a number object having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isObject( 3.0 )\n false\n > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n true\n > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n false\n\n\n See Also\n --------\n isFinite, isPositiveNumber\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a number primitive having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isPrimitive( 3.0 )\n true\n > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n false\n > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n false","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value )\n Tests if a value is a number object having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isObject( 3.0 )\n false\n > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n true\n > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n false\n\n\n See Also\n --------\n isFinite, isPositiveNumber","isPositiveInteger":"\nisPositiveInteger( value )\n Tests if a value is a positive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive integer.\n\n Examples\n --------\n > var bool = isPositiveInteger( 5.0 )\n true\n > bool = isPositiveInteger( new Number( 5.0 ) )\n true\n > bool = isPositiveInteger( 3.14 )\n false\n > bool = isPositiveInteger( -5.0 )\n false\n > bool = isPositiveInteger( null )\n false\n\n\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isPositiveIntegerArray":"\nisPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only positive integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive integers.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger","isPositiveNumber":"\nisPositiveNumber( value )\n Tests if a value is a positive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive number.\n\n Examples\n --------\n > var bool = isPositiveNumber( 5.0 )\n true\n > bool = isPositiveNumber( new Number( 5.0 ) )\n true\n > bool = isPositiveNumber( 3.14 )\n true\n > bool = isPositiveNumber( -5.0 )\n false\n > bool = isPositiveNumber( null )\n false\n\n\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber","isPositiveNumberArray":"\nisPositiveNumberArray( value )\n Tests if a value is an array-like object containing only positive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive numbers.\n\n Examples\n --------\n > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber","isPositiveZero":"\nisPositiveZero( value )\n Tests if a value is positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero( 0.0 )\n true\n > bool = isPositiveZero( new Number( 0.0 ) )\n true\n > bool = isPositiveZero( -3.14 )\n false\n > bool = isPositiveZero( -0.0 )\n false\n > bool = isPositiveZero( null )\n false\n\n\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false\n\n\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false","isPositiveZero.isObject":"\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero","isPrime":"\nisPrime( value )\n Tests if a value is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a prime number.\n\n Examples\n --------\n > var bool = isPrime( 5.0 )\n true\n > bool = isPrime( new Number( 5.0 ) )\n true\n > bool = isPrime( 3.14 )\n false\n > bool = isPrime( -5.0 )\n false\n > bool = isPrime( null )\n false\n\n\nisPrime.isPrimitive( value )\n Tests if a value is a number primitive which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a prime\n number.\n\n Examples\n --------\n > var bool = isPrime.isPrimitive( 5.0 )\n true\n > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n false\n\n\nisPrime.isObject( value )\n Tests if a value is a number object having a value which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a prime number.\n\n Examples\n --------\n > var bool = isPrime.isObject( 5.0 )\n false\n > bool = isPrime.isObject( new Number( 5.0 ) )\n true\n\n\n See Also\n --------\n isComposite, isInteger, isNumber\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value )\n Tests if a value is a number primitive which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a prime\n number.\n\n Examples\n --------\n > var bool = isPrime.isPrimitive( 5.0 )\n true\n > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n false","isPrime.isObject":"\nisPrime.isObject( value )\n Tests if a value is a number object having a value which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a prime number.\n\n Examples\n --------\n > var bool = isPrime.isObject( 5.0 )\n false\n > bool = isPrime.isObject( new Number( 5.0 ) )\n true\n\n\n See Also\n --------\n isComposite, isInteger, isNumber","isPrimitive":"\nisPrimitive( value )\n Tests if a value is a JavaScript primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a JavaScript primitive.\n\n Examples\n --------\n > var bool = isPrimitive( true )\n true\n > bool = isPrimitive( {} )\n false\n\n See Also\n --------\n isBoxedPrimitive\n","isPrimitiveArray":"\nisPrimitiveArray( value )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n JavaScript primitives.\n\n Examples\n --------\n > var bool = isPrimitiveArray( [ '3', 2, null ] )\n true\n > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n false\n > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPrimitive\n","isPRNGLike":"\nisPRNGLike( value )\n Tests if a value is PRNG-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is PRNG-like.\n\n Examples\n --------\n > var bool = isPRNGLike( base.random.randu )\n true\n > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isPRNGLike( 3.14 )\n false\n > bool = isPRNGLike( {} )\n false\n\n","isProbability":"\nisProbability( value )\n Tests if a value is a probability.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a probability.\n\n Examples\n --------\n > var bool = isProbability( 0.5 )\n true\n > bool = isProbability( new Number( 0.5 ) )\n true\n > bool = isProbability( 3.14 )\n false\n > bool = isProbability( -5.0 )\n false\n > bool = isProbability( null )\n false\n\n\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false\n\n\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false","isProbability.isObject":"\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber","isProbabilityArray":"\nisProbabilityArray( value )\n Tests if a value is an array-like object containing only probabilities.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n true\n > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n false\n > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n false\n\n\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false\n\n\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false","isProbabilityArray.objects":"\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability","isPropertyKey":"\nisPropertyKey( value )\n Tests whether a value is a property key.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether value is a property key.\n\n Examples\n --------\n > var out = isPropertyKey( 'foo' )\n true\n > out = isPropertyKey( 1 )\n true\n > out = isPropertyKey( true )\n false\n\n See Also\n --------\n isString, isSymbol, isNonNegativeInteger, hasOwnProp, hasProp","isPrototypeOf":"\nisPrototypeOf( value, proto )\n Tests if an object's prototype chain contains a provided prototype.\n\n The function returns `false` if provided a primitive value.\n\n This function is generally more robust than the `instanceof` operator (e.g.,\n where inheritance is performed without using constructors).\n\n Parameters\n ----------\n value: any\n Input value.\n\n proto: Object|Function\n Prototype.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a provided prototype exists in a prototype chain.\n\n Examples\n --------\n > function Foo() { return this; };\n > function Bar() { return this; };\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var bool = isPrototypeOf( bar, Foo.prototype )\n true\n\n See Also\n --------\n getPrototypeOf\n","isRaggedNestedArray":"\nisRaggedNestedArray( value )\n Tests if a value is a ragged nested array. \n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a ragged nested array.\n\n Examples\n --------\n > var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\n true\n > bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n false\n > bool = isRaggedNestedArray( 'beep' )\n false\n\n","isRangeError":"\nisRangeError( value )\n Tests if a value is a RangeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a RangeError (or a descendant) object,\n false positives may occur due to the fact that the RangeError constructor\n inherits from Error and has no internal class of its own. Hence, RangeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a RangeError object.\n\n Examples\n --------\n > var bool = isRangeError( new RangeError( 'beep' ) )\n true\n > bool = isRangeError( {} )\n false\n\n See Also\n --------\n isError\n","isReadableProperty":"\nisReadableProperty( value, property )\n Tests if an object's own property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadableProperty( obj, 'boop' )\n true\n > bool = isReadableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isReadablePropertyIn, isWritableProperty\n","isReadablePropertyIn":"\nisReadablePropertyIn( value, property )\n Tests if an object's own or inherited property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadablePropertyIn( obj, 'boop' )\n true\n > bool = isReadablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isReadableProperty, isWritablePropertyIn\n","isReadOnlyProperty":"\nisReadOnlyProperty( value, property )\n Tests if an object's own property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is read-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyProperty( obj, 'boop' )\n true\n > bool = isReadOnlyProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadableProperty, isWritableProperty\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is read-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n true\n > bool = isReadOnlyPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isReadWriteProperty":"\nisReadWriteProperty( value, property )\n Tests if an object's own property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWriteProperty( obj, 'boop' )\n true\n > bool = isReadWriteProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadableProperty, isWritableProperty\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value, property )\n Tests if an object's own or inherited property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable\n and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWritePropertyIn( obj, 'boop' )\n true\n > bool = isReadWritePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadablePropertyIn, isWritablePropertyIn\n","isReferenceError":"\nisReferenceError( value )\n Tests if a value is a ReferenceError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a ReferenceError (or a descendant)\n object, false positives may occur due to the fact that the ReferenceError\n constructor inherits from Error and has no internal class of its own.\n Hence, ReferenceError impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a ReferenceError object.\n\n Examples\n --------\n > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n true\n > bool = isReferenceError( {} )\n false\n\n See Also\n --------\n isError\n","isRegExp":"\nisRegExp( value )\n Tests if a value is a regular expression.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression.\n\n Examples\n --------\n > var bool = isRegExp( /\\.+/ )\n true\n > bool = isRegExp( {} )\n false\n\n","isRegExpString":"\nisRegExpString( value )\n Tests if a value is a regular expression string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression string.\n\n Examples\n --------\n > var bool = isRegExpString( '/beep/' )\n true\n > bool = isRegExpString( 'beep' )\n false\n > bool = isRegExpString( '' )\n false\n > bool = isRegExpString( null )\n false\n\n See Also\n --------\n isRegExp\n","isRelativePath":"\nisRelativePath( value )\n Tests if a value is a relative path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a relative path.\n\n Examples\n --------\n // Windows environments:\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n\n // POSIX environments:\n > bool = isRelativePath( './foo/bar/baz' )\n true\n\n\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false\n\n\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath\n","isRelativePath.posix":"\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false","isRelativePath.win32":"\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath","isRelativeURI":"\nisRelativeURI( value )\n Tests whether a value is a relative URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is a relative URI.\n\n Examples\n --------\n > var bool = isRelativeURI( '/images/example.png' )\n true\n > bool = isRelativeURI( 'http://www.example.com' )\n false\n > bool = isRelativeURI( null )\n false\n\n See Also\n --------\n isURI","isSafeInteger":"\nisSafeInteger( value )\n Tests if a value is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a safe integer.\n\n Examples\n --------\n > var bool = isSafeInteger( 5.0 )\n true\n > bool = isSafeInteger( new Number( 5.0 ) )\n true\n > bool = isSafeInteger( 2.0e200 )\n false\n > bool = isSafeInteger( -3.14 )\n false\n > bool = isSafeInteger( null )\n false\n\n\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false","isSafeInteger.isObject":"\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber","isSafeIntegerArray":"\nisSafeIntegerArray( value )\n Tests if a value is an array-like object containing only safe integers.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing\n only safe integers.\n\n Examples\n --------\n > var arr = [ -3.0, new Number(0.0), 2.0 ];\n > var bool = isSafeIntegerArray( arr )\n true\n > arr = [ -3.0, '3.0' ];\n > bool = isSafeIntegerArray( arr )\n false\n\n\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false\n\n\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger","isSameArray":"\nisSameArray( v1, v2 )\n Tests if two arguments are both generic arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isSameArray( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isSameArray( x, y )\n true\n\n See Also\n --------\n isArray, isEqualArray, isSameArrayLike, isSameValue\n","isSameArrayLike":"\nisSameArrayLike( v1, v2 )\n Tests if two arguments are both array-like and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isSameArrayLike( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isSameArrayLike( x, y )\n true\n\n See Also\n --------\n isArrayLike, isSameArray, isSameValue\n","isSameComplex64":"\nisSameComplex64( v1, v2 )\n Tests if two arguments are both single-precision complex floating-point\n numbers and have the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex64( 1.0, 2.0 );\n > var y = new Complex64( 1.0, 2.0 );\n > var bool = isSameComplex64( x, y )\n true\n\n > x = new Complex64( NaN, NaN );\n > y = new Complex64( NaN, NaN );\n > bool = isSameComplex64( x, y )\n true\n\n See Also\n --------\n isComplex64, isSameComplex128, isSameValue\n","isSameComplex64Array":"\nisSameComplex64Array( v1, v2 )\n Tests if two arguments are both Complex64Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var bool = isSameComplex64Array( x, y )\n true\n\n > x = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n > y = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n > bool = isSameComplex64Array( x, y )\n true\n\n See Also\n --------\n isComplex64Array, isSameComplex128Array, isSameFloat32Array, isSameValue\n","isSameComplex128":"\nisSameComplex128( v1, v2 )\n Tests if two arguments are both double-precision complex floating-point\n numbers and have the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex128( 1.0, 2.0 );\n > var y = new Complex128( 1.0, 2.0 );\n > var bool = isSameComplex128( x, y )\n true\n\n > x = new Complex128( NaN, NaN );\n > y = new Complex128( NaN, NaN );\n > bool = isSameComplex128( x, y )\n true\n\n See Also\n --------\n isComplex128, isSameComplex64, isSameValue\n","isSameComplex128Array":"\nisSameComplex128Array( v1, v2 )\n Tests if two arguments are both Complex128Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var bool = isSameComplex128Array( x, y )\n true\n\n > x = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n > y = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n > bool = isSameComplex128Array( x, y )\n true\n\n See Also\n --------\n isComplex128Array, isSameComplex64Array, isSameFloat64Array, isSameValue\n","isSameFloat32Array":"\nisSameFloat32Array( v1, v2 )\n Tests if two arguments are both Float32Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > var bool = isSameFloat32Array( x, y )\n true\n\n > x = new Float32Array( [ NaN, NaN, NaN ] );\n > y = new Float32Array( [ NaN, NaN, NaN ] );\n > bool = isSameFloat32Array( x, y )\n true\n\n See Also\n --------\n isSameFloat64Array, isSameValue\n","isSameFloat64Array":"\nisSameFloat64Array( v1, v2 )\n Tests if two arguments are both Float64Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > var bool = isSameFloat64Array( x, y )\n true\n\n > x = new Float64Array( [ NaN, NaN, NaN ] );\n > y = new Float64Array( [ NaN, NaN, NaN ] );\n > bool = isSameFloat64Array( x, y )\n true\n\n See Also\n --------\n isSameFloat32Array, isSameValue\n","isSameNativeClass":"\nisSameNativeClass( a, b )\n Tests if two arguments have the same native class.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments have the same native class.\n\n Examples\n --------\n > var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\n true\n > bool = isSameNativeClass( 'beep', 'boop' )\n true\n > bool = isSameNativeClass( {}, [] )\n false\n\n See Also\n --------\n isSameType, isSameValue, isStrictEqual\n","isSameType":"\nisSameType( a, b )\n Tests if two arguments have the same type.\n\n The function uses the `typeof` operator to test for the same type.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments have the same type.\n\n Examples\n --------\n > var bool = isSameType( true, true )\n true\n > bool = isSameType( {}, [] )\n true\n > bool = isSameType( 3.12, -3.12 )\n true\n > bool = isSameType( 0.0, '0.0' )\n false\n\n See Also\n --------\n isSameNativeClass, isSameValue, isStrictEqual\n","isSameValue":"\nisSameValue( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValue( true, true )\n true\n > bool = isSameValue( {}, {} )\n false\n > bool = isSameValue( -0.0, -0.0 )\n true\n > bool = isSameValue( -0.0, 0.0 )\n false\n > bool = isSameValue( NaN, NaN )\n true\n\n See Also\n --------\n isSameValueZero, isStrictEqual\n","isSameValueZero":"\nisSameValueZero( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValueZero( true, true )\n true\n > bool = isSameValueZero( {}, {} )\n false\n > bool = isSameValueZero( -0.0, -0.0 )\n true\n > bool = isSameValueZero( -0.0, 0.0 )\n true\n > bool = isSameValueZero( NaN, NaN )\n true\n\n See Also\n --------\n isSameValue, isStrictEqual\n","isSemVer":"\nisSemVer( value )\n Tests if a value is a semantic version string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a provided value is a semantic version\n string.\n\n Examples\n --------\n > var bool = isSemVer( '1.0.0' )\n true\n > bool = isSemVer( '1.0.0-alpha.1' )\n true\n > bool = isSemVer( '0.1' )\n false\n > bool = isSemVer( null )\n false\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value )\n Tests if a value is a SharedArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SharedArrayBuffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffer...\n > var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\n true\n > bool = isSharedArrayBuffer( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value )\n Tests if a value is a skew-centrosymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n Examples\n --------\n > var buf = [ 2, 1, -1, -2 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewCentrosymmetricMatrix( M )\n true\n > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewCentrosymmetricMatrix( 3.14 )\n false\n > bool = isSkewCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isCentrosymmetricMatrix, isMatrixLike, isSkewSymmetricMatrix\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value )\n Tests if a value is a skew-persymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-persymmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 0, 0, -1 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewPersymmetricMatrix( M )\n true\n > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewPersymmetricMatrix( 3.14 )\n false\n > bool = isSkewPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isPersymmetricMatrix, isSkewSymmetricMatrix\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-symmetric matrix.\n\n Examples\n --------\n > var buf = [ 0, -1, 1, 0 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewSymmetricMatrix( M )\n true\n > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewSymmetricMatrix( 3.14 )\n false\n > bool = isSkewSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix\n","isSlice":"\nisSlice( value )\n Tests if a value is a Slice object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a Slice object.\n\n Examples\n --------\n > var bool = isSlice( new Slice( 10 ) )\n true\n > bool = isSlice( 3.14 )\n false\n > bool = isSlice( {} )\n false\n\n See Also\n --------\n isMultiSlice, Slice\n","isSnakecase":"\nisSnakecase( value )\n Tests if a value is a string in snake case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in snake case.\n\n Examples\n --------\n > var bool = isSnakecase( 'hello_world' )\n true\n > bool = isSnakecase( 'Hello World' )\n false\n\n See Also\n --------\n isString","isSquareMatrix":"\nisSquareMatrix( value )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object having equal dimensions.\n\n Examples\n --------\n > var buf = [ 0, 0, 0, 0 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSquareMatrix( M )\n true\n > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSquareMatrix( 3.14 )\n false\n > bool = isSquareMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSymmetricMatrix\n","isSquareNumber":"\nisSquareNumber( value )\n Tests if a value is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber( 4.0 )\n true\n > bool = isSquareNumber( new Number( 4.0 ) )\n true\n > bool = isSquareNumber( 3.14 )\n false\n > bool = isSquareNumber( -5.0 )\n false\n > bool = isSquareNumber( null )\n false\n\n\nisSquareNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isPrimitive( 4.0 )\n true\n > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n false\n\n\nisSquareNumber.isObject( value )\n Tests if a value is a number object having a value which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isObject( 4.0 )\n false\n > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isCubeNumber, isInteger, isNumber, isTriangularNumber\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isPrimitive( 4.0 )\n true\n > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n false","isSquareNumber.isObject":"\nisSquareNumber.isObject( value )\n Tests if a value is a number object having a value which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isObject( 4.0 )\n false\n > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isCubeNumber, isInteger, isNumber, isTriangularNumber","isSquareTriangularNumber":"\nisSquareTriangularNumber( value )\n Tests if a value is a square triangular number.\n\n Return values are not reliable for numbers greater than 1125899906842624.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber( 36.0 )\n true\n > bool = isSquareTriangularNumber( new Number( 36.0 ) )\n true\n > bool = isSquareTriangularNumber( 3.14 )\n false\n > bool = isSquareTriangularNumber( -5.0 )\n false\n > bool = isSquareTriangularNumber( null )\n false\n\n\nisSquareTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false\n\n\nisSquareTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a square\n triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isObject( 36.0 )\n false\n > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isTriangularNumber\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a square\n triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isObject( 36.0 )\n false\n > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isTriangularNumber","isStartcase":"\nisStartcase( value )\n Tests if a value is a startcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if value is a startcase string.\n\n Examples\n --------\n > var bool = isStartcase( 'Beep Boop' )\n true\n > bool = isStartcase( 'Beep and Boop' )\n false\n\n See Also\n --------\n isString","isStrictEqual":"\nisStrictEqual( a, b )\n Tests if two arguments are strictly equal.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are strictly equal.\n\n Examples\n --------\n > var bool = isStrictEqual( true, true )\n true\n > bool = isStrictEqual( {}, {} )\n false\n > bool = isStrictEqual( -0.0, -0.0 )\n true\n > bool = isStrictEqual( -0.0, 0.0 )\n false\n > bool = isStrictEqual( NaN, NaN )\n false\n\n See Also\n --------\n isSameValue\n","isString":"\nisString( value )\n Tests if a value is a string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string.\n\n Examples\n --------\n > var bool = isString( 'beep' )\n true\n > bool = isString( new String( 'beep' ) )\n true\n > bool = isString( 5 )\n false\n\n\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false\n\n\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false\n\n","isString.isPrimitive":"\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false","isString.isObject":"\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false","isStringArray":"\nisStringArray( value )\n Tests if a value is an array of strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of strings.\n\n Examples\n --------\n > var bool = isStringArray( [ 'abc', 'def' ] )\n true\n > bool = isStringArray( [ 'abc', 123 ] )\n false\n\n\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false\n\n\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString\n","isStringArray.primitives":"\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false","isStringArray.objects":"\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString","isStruct":"\nisStruct( value )\n Tests if a value is a `struct` instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a `struct` instance.\n\n Examples\n --------\n > var schema = [ { 'name': 'foo', 'type': 'float64' } ];\n > var S = structFactory( schema );\n > var bool = isStruct( new S() )\n true\n > bool = isStruct( [ 1, 2, 3, 4 ] )\n false\n > bool = isStruct( 3.14 )\n false\n > bool = isStruct( {} )\n false\n\n See Also\n --------\n isStructConstructorLike, structFactory\n","isStructConstructorLike":"\nisStructConstructorLike( value )\n Tests if a value is struct constructor-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is struct constructor-like.\n\n Examples\n --------\n > var schema = [ { 'name': 'foo', 'type': 'float64' } ];\n > var S = structFactory( schema );\n > var bool = isStructConstructorLike( S )\n true\n > bool = isStructConstructorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isStructConstructorLike( 3.14 )\n false\n > bool = isStructConstructorLike( {} )\n false\n\n See Also\n --------\n isStruct, structFactory\n","isSymbol":"\nisSymbol( value )\n Tests if a value is a symbol.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symbol.\n\n Examples\n --------\n > var bool = isSymbol( Symbol( 'beep' ) )\n true\n > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n true\n > bool = isSymbol( {} )\n false\n > bool = isSymbol( null )\n false\n > bool = isSymbol( true )\n false\n\n","isSymbolArray":"\nisSymbolArray( value )\n Tests if a value is an array-like object containing only symbols.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only symbols.\n\n Examples\n --------\n > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n true\n > bool = isSymbolArray( Symbol( 'beep' ) )\n false\n > bool = isSymbolArray( [] )\n false\n > bool = isSymbolArray( {} )\n false\n > bool = isSymbolArray( null )\n false\n > bool = isSymbolArray( true )\n false\n\n\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false\n\n\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false","isSymbolArray.objects":"\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol","isSymmetricMatrix":"\nisSymmetricMatrix( value )\n Tests if a value is a square matrix which equals its transpose.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symmetric matrix.\n\n Examples\n --------\n > var buf = [ 0, 1, 1, 2 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSymmetricMatrix( M )\n true\n > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSymmetricMatrix( 3.14 )\n false\n > bool = isSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isNonSymmetricMatrix, isSquareMatrix\n","isSyntaxError":"\nisSyntaxError( value )\n Tests if a value is a SyntaxError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a SyntaxError (or a descendant) object,\n false positives may occur due to the fact that the SyntaxError constructor\n inherits from Error and has no internal class of its own. Hence, SyntaxError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SyntaxError object.\n\n Examples\n --------\n > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n true\n > bool = isSyntaxError( {} )\n false\n\n See Also\n --------\n isError\n","isTriangularNumber":"\nisTriangularNumber( value )\n Tests if a value is a triangular number.\n\n Return values are not reliable for numbers greater than 1125899906842624.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber( 36.0 )\n true\n > bool = isTriangularNumber( new Number( 36.0 ) )\n true\n > bool = isTriangularNumber( 3.14 )\n false\n > bool = isTriangularNumber( -5.0 )\n false\n > bool = isTriangularNumber( null )\n false\n\n\nisTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false\n\n\nisTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a triangular\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isObject( 36.0 )\n false\n > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isSquareTriangularNumber\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a triangular\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isObject( 36.0 )\n false\n > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isSquareTriangularNumber","isTruthy":"\nisTruthy( value )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is truthy.\n\n Examples\n --------\n > var bool = isTruthy( true )\n true\n > bool = isTruthy( {} )\n true\n > bool = isTruthy( [] )\n true\n > bool = isTruthy( false )\n false\n > bool = isTruthy( '' )\n false\n > bool = isTruthy( 0 )\n false\n > bool = isTruthy( null )\n false\n > bool = isTruthy( void 0 )\n false\n > bool = isTruthy( NaN )\n false\n\n See Also\n --------\n isFalsy\n","isTruthyArray":"\nisTruthyArray( value )\n Tests if a value is an array-like object containing only truthy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only truthy values.\n\n Examples\n --------\n > var bool = isTruthyArray( [ {}, [] ] )\n true\n > bool = isTruthyArray( [ null, '' ] )\n false\n > bool = isTruthyArray( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isTypedArray":"\nisTypedArray( value )\n Tests if a value is a typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a typed array.\n\n Examples\n --------\n > var bool = isTypedArray( new Int8Array( 10 ) )\n true\n\n See Also\n --------\n isArray, isTypedArrayLike\n","isTypedArrayLength":"\nisTypedArrayLength( value )\n Tests if a value is a valid typed array length.\n\n A valid length property for a typed array instance is any integer value on\n the interval [0, 2^53-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a valid typed array length.\n\n Examples\n --------\n > var bool = isTypedArrayLength( 5 )\n true\n > bool = isTypedArrayLength( 2.0e200 )\n false\n > bool = isTypedArrayLength( -3.14 )\n false\n > bool = isTypedArrayLength( null )\n false\n\n See Also\n --------\n isArrayLength, isTypedArray\n","isTypedArrayLike":"\nisTypedArrayLike( value )\n Tests if a value is typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is typed-array-like.\n\n Examples\n --------\n > var bool = isTypedArrayLike( new Int16Array() )\n true\n > bool = isTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4\n ... })\n true\n\n See Also\n --------\n isTypedArray\n","isTypeError":"\nisTypeError( value )\n Tests if a value is a TypeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a TypeError (or a descendant) object,\n false positives may occur due to the fact that the TypeError constructor\n inherits from Error and has no internal class of its own. Hence, TypeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a TypeError object.\n\n Examples\n --------\n > var bool = isTypeError( new TypeError( 'beep' ) )\n true\n > bool = isTypeError( {} )\n false\n\n See Also\n --------\n isError\n","isUint8Array":"\nisUint8Array( value )\n Tests if a value is a Uint8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8Array.\n\n Examples\n --------\n > var bool = isUint8Array( new Uint8Array( 10 ) )\n true\n > bool = isUint8Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint32Array\n","isUint8ClampedArray":"\nisUint8ClampedArray( value )\n Tests if a value is a Uint8ClampedArray.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8ClampedArray.\n\n Examples\n --------\n > var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\n true\n > bool = isUint8ClampedArray( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint8Array\n","isUint16Array":"\nisUint16Array( value )\n Tests if a value is a Uint16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint16Array.\n\n Examples\n --------\n > var bool = isUint16Array( new Uint16Array( 10 ) )\n true\n > bool = isUint16Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint32Array, isUint8Array\n","isUint32Array":"\nisUint32Array( value )\n Tests if a value is a Uint32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint32Array.\n\n Examples\n --------\n > var bool = isUint32Array( new Uint32Array( 10 ) )\n true\n > bool = isUint32Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint8Array\n","isUNCPath":"\nisUNCPath( value )\n Tests if a value is a UNC path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a UNC path.\n\n Examples\n --------\n > var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isUNCPath( '/foo/bar/baz' )\n false\n\n","isUndefined":"\nisUndefined( value )\n Tests if a value is undefined.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined.\n\n Examples\n --------\n > var bool = isUndefined( void 0 )\n true\n > bool = isUndefined( null )\n false\n\n See Also\n --------\n isNull, isUndefinedOrNull\n","isUndefinedOrNull":"\nisUndefinedOrNull( value )\n Tests if a value is undefined or null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined or null.\n\n Examples\n --------\n > var bool = isUndefinedOrNull( void 0 )\n true\n > bool = isUndefinedOrNull( null )\n true\n > bool = isUndefinedOrNull( false )\n false\n\n See Also\n --------\n isNull, isUndefined\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value )\n Tests if a value is an array of probabilities that sum to one.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of probabilities that sum\n to one.\n\n Examples\n --------\n > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n true\n > bool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\n true\n > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n false\n > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n false\n\n See Also\n --------\n isProbability, isProbabilityArray\n","isUppercase":"\nisUppercase( value )\n Tests if a value is an uppercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an uppercase string.\n\n Examples\n --------\n > var bool = isUppercase( 'HELLO' )\n true\n > bool = isUppercase( 'World' )\n false\n\n See Also\n --------\n isLowercase, isString\n","isURI":"\nisURI( value )\n Tests if a value is a URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URI.\n\n Examples\n --------\n > var bool = isURI( 'http://google.com' )\n true\n > bool = isURI( 'http://localhost/' )\n true\n > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n true\n > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n true\n\n // No scheme:\n > bool = isURI( '' )\n false\n > bool = isURI( 'foo@bar' )\n false\n > bool = isURI( '://foo/' )\n false\n\n // Illegal characters:\n > bool = isURI( 'http://' )\n false\n\n // Invalid path:\n > bool = isURI( 'http:////foo.html' )\n false\n\n // Incomplete hex escapes:\n > bool = isURI( 'http://example.w3.org/%a' )\n false\n\n","isURIError":"\nisURIError( value )\n Tests if a value is a URIError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a URIError (or a descendant) object,\n false positives may occur due to the fact that the URIError constructor\n inherits from Error and has no internal class of its own. Hence, URIError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URIError object.\n\n Examples\n --------\n > var bool = isURIError( new URIError( 'beep' ) )\n true\n > bool = isURIError( {} )\n false\n\n See Also\n --------\n isError\n","isVectorLike":"\nisVectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isVectorLike( M )\n true\n > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isVectorLike( 3.14 )\n false\n > bool = isVectorLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isndarrayLike, isTypedArrayLike\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value )\n Tests if a value is a WebAssembly memory instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a WebAssembly memory instance.\n\n Examples\n --------\n > var bool = isWebAssemblyMemory( {} )\n false\n\n See Also\n --------\n hasWebAssemblySupport\n","isWellFormedString":"\nisWellFormedString( str )\n Tests if a string is well-formed.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is well-formed.\n\n Examples\n --------\n > var bool = isWellFormedString( '' )\n true\n\n > bool = isWellFormedString( new String( '' ) )\n true\n\n > bool = isWellFormedString( '\\uDBFF' )\n false\n\n > bool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\n false\n\n > bool = isWellFormedString( [] )\n false\n\n > bool = isWellFormedString( '-5' )\n true\n\n > bool = isWellFormedString( null )\n false\n\n\nisWellFormedString.isPrimitive( str )\n Tests if a string is a well-formed string primitive.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string primitive.\n\n Examples\n --------\n > var bool = isWellFormedString.isPrimitive( '' )\n true\n > bool = isWellFormedString.isPrimitive( new String( '' ) )\n false\n\n\nisWellFormedString.isObject( str )\n Tests if a string is a well-formed string object.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string object.\n\n Examples\n --------\n > var bool = isWellFormedString.isObject( '' )\n false\n > bool = isWellFormedString.isObject( new String( '' ) )\n true\n\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str )\n Tests if a string is a well-formed string primitive.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string primitive.\n\n Examples\n --------\n > var bool = isWellFormedString.isPrimitive( '' )\n true\n > bool = isWellFormedString.isPrimitive( new String( '' ) )\n false","isWellFormedString.isObject":"\nisWellFormedString.isObject( str )\n Tests if a string is a well-formed string object.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string object.\n\n Examples\n --------\n > var bool = isWellFormedString.isObject( '' )\n false\n > bool = isWellFormedString.isObject( new String( '' ) )\n true","isWhitespace":"\nisWhitespace( str )\n Tests whether a string contains only white space characters.\n\n A white space character is defined as one of the 25 characters defined as a\n white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n database, as well as one related white space character without the Unicode\n character property \"WSpace=Y\" (zero width non-breaking space which was\n deprecated as of Unicode 3.2).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only white space\n characters.\n\n Examples\n --------\n > var bool = isWhitespace( ' ' )\n true\n > bool = isWhitespace( 'abcdef' )\n false\n > bool = isWhitespace( '' )\n false\n\n See Also\n --------\n reWhitespace\n","isWritableProperty":"\nisWritableProperty( value, property )\n Tests if an object's own property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritableProperty( obj, 'boop' )\n true\n > bool = isWritableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadableProperty, isReadWriteProperty, isWritablePropertyIn, isWriteOnlyProperty\n","isWritablePropertyIn":"\nisWritablePropertyIn( value, property )\n Tests if an object's own or inherited property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritablePropertyIn( obj, 'boop' )\n true\n > bool = isWritablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadablePropertyIn, isReadWritePropertyIn, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value, property )\n Tests if an object's own property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is write-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyProperty( obj, 'boop' )\n false\n > bool = isWriteOnlyProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is write-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n false\n > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isWritablePropertyIn, isWriteOnlyProperty\n","iterAbs":"\niterAbs( iterator )\n Returns an iterator which iteratively computes the absolute value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAbs( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.abs, iterAbs2\n","iterAbs2":"\niterAbs2( iterator )\n Returns an iterator which iteratively computes the squared absolute value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAbs2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.abs2, iterAbs\n","iterAcos":"\niterAcos( iterator )\n Returns an iterator which iteratively computes the arccosine.\n\n The domain of arccosine is restricted to [-1,1]. If an iterated value is\n outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acos, iterAcosh, iterAsin, iterAtan\n","iterAcosh":"\niterAcosh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arccosine.\n\n The domain of the hyperbolic arccosine is restricted to [1,+infinity). If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acosh, iterAcos, iterAsinh, iterAtanh\n","iterAcot":"\niterAcot( iterator )\n Returns an iterator which iteratively computes the inverse cotangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acot, iterAcos, iterAcoth, iterAsin, iterAtan\n","iterAcoth":"\niterAcoth( iterator )\n Returns an iterator which iteratively computes the inverse hyperbolic\n cotangent.\n\n The domain of the inverse hyperbolic cotangent is restricted to (-inf,-1]\n and [1,inf). If an iterated value is outside of the domain, the returned\n iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acoth, iterAcosh, iterAcot, iterAsinh, iterAtanh\n","iterAcovercos":"\niterAcovercos( iterator )\n Returns an iterator which iteratively computes the inverse coversed cosine.\n\n The domain of inverse coversed cosine is restricted to [0,2]. If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcovercos( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acovercos, iterAcoversin, iterAvercos, iterCovercos, iterVercos\n","iterAcoversin":"\niterAcoversin( iterator )\n Returns an iterator which iteratively computes the inverse coversed sine.\n\n The domain of inverse coversed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acoversin, iterAcovercos, iterAversin, iterCoversin, iterVersin\n","iterAdd":"\niterAdd( iter0, ...iterator )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to add.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterAdd( it1, it2 );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide, iterMultiply, iterSubtract\n","iterAdvance":"\niterAdvance( iterator[, n] )\n Advances an entire iterator.\n\n The function *eagerly* advances an input iterator `n` iterations or until\n the input iterator finishes, whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Input iterator to advance.\n\n n: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Input iterator.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var it = iterAdvance( arr, 4 );\n > var v = it.next().value\n 1\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterHead, iterSlice\n","iterAhavercos":"\niterAhavercos( iterator )\n Returns an iterator which iteratively computes the inverse half-value versed\n cosine.\n\n The domain of inverse half-value versed cosine is restricted to [0,1]. If\n an iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ahavercos, iterAhaversin, iterHavercos, iterVercos\n","iterAhaversin":"\niterAhaversin( iterator )\n Returns an iterator which iteratively computes the inverse half-value versed\n sine.\n\n The domain of inverse half-value versed sine is restricted to [-2,0]. If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ahaversin, iterAhavercos, iterHaversin, iterVersin\n","iterAny":"\niterAny( iterator )\n Tests whether at least one iterated value is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a value is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterAny( arr )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNone, iterSome\n","iterAnyBy":"\niterAnyBy( iterator, predicate[, thisArg ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for any iterated value. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > function fcn( v ) { return ( v === 1 ); };\n > var bool = iterAnyBy( arr, fcn )\n true\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNoneBy, iterSomeBy\n","iterAsin":"\niterAsin( iterator )\n Returns an iterator which iteratively computes the arcsine.\n\n The domain of arcsine is restricted to [-1,1]. If an iterated value is\n outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.asin, iterAcos, iterAsinh, iterAtan\n","iterAsinh":"\niterAsinh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arcsine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.asinh, iterAcosh, iterAsin, iterAtanh\n","iterAtan":"\niterAtan( iterator )\n Returns an iterator which iteratively computes the arctangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atan, iterAcos, iterAsin, iterAtanh\n","iterAtan2":"\niterAtan2( y, x )\n Returns an iterator which iteratively computes the angle in the plane (in\n radians) between the positive x-axis and the ray from (0,0) to the point\n (x,y).\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n y: Object|number\n Input iterator.\n\n x: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( -2.0, 2.0 );\n > var y = random.iterators.uniform( -2.0, 2.0 );\n > var it = iterAtan2( y, x );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atan2, iterAtan\n","iterAtanh":"\niterAtanh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arctangent.\n\n The domain of hyperbolic arctangent is restricted to [-1,1]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atanh, iterAcosh, iterAsinh, iterAtan\n","iterator2array":"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n Creates (or fills) an array from an iterator.\n\n When invoked, an input function is provided two arguments:\n\n - value: iterated value.\n - index: iterated value index (zero-based).\n\n If provided an output array, the function fills the output array with\n iterated values.\n\n Iteration stops when an output array is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n out: ArrayLikeObject (optional)\n Output array-like object.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var opts = { 'iter': 10 };\n > var arr = iterator2array( random.iterators.randu( opts ) )\n\n See Also\n --------\n array2iterator, iterator2arrayview\n","iterator2arrayview":"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view with values returned from an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: destination index (zero-based).\n - n: iteration index (zero-based).\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayview( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iterator, iterator2arrayviewRight\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: destination index (zero-based).\n - n: iteration index (zero-based).\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iteratorRight, iterator2arrayview\n","iteratorStream":"\niteratorStream( iterator[, options] )\n Creates a readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n In binary mode, if an iterator generates `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n explicitly map `undefined` values to a different value by wrapping the\n provided iterator with another iterator.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream( it );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","iteratorStream.factory":"\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n\n See Also\n --------\n Symbol\n","iterAvercos":"\niterAvercos( iterator )\n Returns an iterator which iteratively computes the inverse versed cosine.\n\n The domain of inverse versed cosine is restricted to [-2,0]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.avercos, iterAversin, iterVersin\n","iterAversin":"\niterAversin( iterator )\n Returns an iterator which iteratively computes the inverse versed sine.\n\n The domain of inverse versed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.aversin, iterAvercos, iterVercos\n","iterawgn":"\niterawgn( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n drawn from a standard normal distribution. If provided, the `state` and\n `seed` options are ignored. In order to seed the returned iterator, one\n must seed the provided `prng` (assuming the provided `prng` is\n seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function|null\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawgn( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawln, iterawun\n","iterawln":"\niterawln( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawln( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawun\n","iterawun":"\niterawun( iterator, sigma[, options] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawun( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawln\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettPulse, iterHannPulse, iterPulse, iterTriangleWave\n","iterBartlettPulse":"\niterBartlettPulse( [options] )\n Returns an iterator which generates a Bartlett pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterTriangleWave\n","iterBesselj0":"\niterBesselj0( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBesselj0( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.besselj0, iterBesselj1, iterBessely0, iterBessely1\n","iterBesselj1":"\niterBesselj1( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order one.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBesselj1( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.besselj1, iterBesselj0, iterBessely0, iterBessely1\n","iterBessely0":"\niterBessely0( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBessely0( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.bessely0, iterBesselj0, iterBesselj1, iterBessely1\n","iterBessely1":"\niterBessely1( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order one.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBessely1( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.bessely1, iterBesselj0, iterBesselj1, iterBessely0\n","iterBeta":"\niterBeta( x, y )\n Returns an iterator which iteratively evaluates the beta function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n y: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( 0.0, 2.0 );\n > var it = iterBeta( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.beta, iterBetaln\n","iterBetaln":"\niterBetaln( x, y )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n beta function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n y: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( 0.0, 2.0 );\n > var it = iterBetaln( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.betaln, iterBeta\n","iterBinet":"\niterBinet( iterator )\n Returns an iterator which iteratively evaluates Binet's formula extended to\n real numbers.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBinet( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.binet\n","iterCbrt":"\niterCbrt( iterator )\n Returns an iterator which iteratively computes the cube root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCbrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cbrt, iterPow, iterSqrt\n","iterCeil":"\niterCeil( iterator )\n Returns an iterator which rounds each iterated value toward positive\n infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil, iterFloor, iterRound\n","iterCeil2":"\niterCeil2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward positive infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil2, iterCeil, iterCeil10, iterFloor2, iterRound2\n","iterCeil10":"\niterCeil10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward positive infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil10, iterCeil, iterCeil2, iterFloor10, iterRound10\n","iterCompositesSeq":"\niterCompositesSeq( [options] )\n Returns an iterator which generates a sequence of composite numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCompositesSeq();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n > v = it.next().value\n 8\n\n See Also\n --------\n iterIntegersSeq, iterPositiveIntegersSeq, iterPrimesSeq\n","iterConcat":"\niterConcat( iter0, ...iterator )\n Returns an iterator which iterates over the values of two or more iterators.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to concatenate.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = array2iterator( [ 3, 4 ] );\n > var it = iterConcat( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n","iterConstant":"\niterConstant( value[, options] )\n Returns an iterator which always returns the same value.\n\n When provided an object reference, the returned iterator always returns the\n same reference.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n value: any\n Value to return.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterConstant( 3.14 );\n > var v = it.next().value\n 3.14\n > v = it.next().value\n 3.14\n\n See Also\n --------\n constantFunction\n","iterContinuedFraction":"\niterContinuedFraction( iterator[, options] )\n Evaluates the terms of a continued fraction.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Maximum number of iterations. Default: 1e308.\n\n options.tol: number (optional)\n Tolerance at which to terminate further evaluation of the continued\n fraction. Default: floating-point epsilon.\n\n Returns\n -------\n out: number|null\n Result.\n\n Examples\n --------\n > var terms = array2iterator( [ 3, 4, 12, 4 ] );\n > var v = iterContinuedFraction( terms )\n ~3.245\n\n See Also\n --------\n iterContinuedFractionSeq\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x[, options] )\n Returns an iterator which generates a list of all continued fraction terms\n which can be obtained given the precision of `x`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x: number\n Input value.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Maximum number of iterations. Default: 1e308.\n\n options.tol: number (optional)\n Tolerance at which to terminate further evaluation of the continued\n fraction. Default: floating-point epsilon.\n\n options.returns: string (optional)\n Specifies the type of result to return. Must be one of\n\n - terms: return continued fraction terms\n - convergents: return continued fraction convergents\n - *: return both continued fraction terms and their associated\n convergents as a two-element array.\n\n Default: 'terms'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n // Return continued fraction terms...\n > var it = iterContinuedFractionSeq( 3.245 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 4\n > v = it.next().value\n 12\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n // Return continued fraction convergents...\n > it = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\n > v = it.next().value\n 3.0\n > v = it.next().value\n 3.25\n > v = it.next().value\n ~3.2449\n > v = it.next().value\n 3.245\n > bool = it.next().done\n true\n\n See Also\n --------\n iterContinuedFraction\n","iterCos":"\niterCos( iterator )\n Returns an iterator which iteratively computes the cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCos( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cos, iterCospi, iterSin, iterTan\n","iterCosh":"\niterCosh( iterator )\n Returns an iterator which iteratively computes the hyperbolic cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterCosh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.cosh, iterCos, iterSinh, iterTanh\n","iterCosineWave":"\niterCosineWave( [options] )\n Returns an iterator which generates a cosine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a cosine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCosineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterCosm1":"\niterCosm1( iterator )\n Returns an iterator which iteratively computes `cos(x) - 1`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCosm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.cosm1, iterCos\n","iterCospi":"\niterCospi( iterator )\n Returns an iterator which computes the cosine of each iterated value times\n π.\n\n Computes cos(πx) more accurately than cos(pi*x), especially for large x.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCospi( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cospi, iterCos\n","iterCounter":"\niterCounter( iterator )\n Returns an iterator which iteratively computes the number of iterated\n values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCounter( random.iterators.randu() );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterLength\n","iterCovercos":"\niterCovercos( iterator )\n Returns an iterator which iteratively computes the coversed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCovercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.covercos, iterCoversin, iterVercos\n","iterCoversin":"\niterCoversin( iterator )\n Returns an iterator which iteratively computes the coversed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCoversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.coversin, iterCovercos, iterVersin\n","iterCubesSeq":"\niterCubesSeq( [options] )\n Returns an iterator which generates a sequence of cubes.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 208063.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCubesSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 8\n\n See Also\n --------\n iterFourthPowersSeq, iterSquaresSeq\n","itercugmean":"\nitercugmean( iterator )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n\n If provided a negative value, the iterated value is `NaN` for all future\n invocations.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercugmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~3.16\n > v = it.next().value\n ~3.11\n > v = it.next().value\n ~3.50\n\n See Also\n --------\n itercuhmean, itercumean\n","itercuhmean":"\nitercuhmean( iterator )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercuhmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~2.86\n > v = it.next().value\n ~2.90\n > v = it.next().value\n ~3.24\n\n See Also\n --------\n itercugmean, itercumean\n","itercumax":"\nitercumax( iterator )\n Returns an iterator which iteratively computes a cumulative maximum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumax( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumidrange, itercumin, itercurange, itermax\n","itercumaxabs":"\nitercumaxabs( iterator )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumaxabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumax, itercuminabs, itermaxabs\n","itercumean":"\nitercumean( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumean( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.25\n\n See Also\n --------\n itercumidrange, itercusum, itermean\n","itercumeanabs":"\nitercumeanabs( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n 3.75\n\n See Also\n --------\n itercumean, itercumeanabs2, itercusumabs, itermeanabs\n","itercumeanabs2":"\nitercumeanabs2( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs2( arr );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n 15.75\n\n See Also\n --------\n itercumean, itercumeanabs, itercusumabs2, itermeanabs2\n","itercumidrange":"\nitercumidrange( iterator )\n Returns an iterator which iteratively computes a cumulative mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumidrange( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itercumean, itercumax, itercumin, itercurange, itermidrange\n","itercumin":"\nitercumin( iterator )\n Returns an iterator which iteratively computes a cumulative minimum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumin( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itercumax, itercumidrange, itercurange, itermin\n","itercuminabs":"\nitercuminabs( iterator )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuminabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n\n See Also\n --------\n itercumaxabs, itercumin, iterminabs\n","itercuprod":"\nitercuprod( iterator )\n Returns an iterator which iteratively computes a cumulative product.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuprod( arr );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -150.0\n\n See Also\n --------\n itercusum, iterprod\n","itercurange":"\nitercurange( iterator )\n Returns an iterator which iteratively computes a cumulative range.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercurange( arr );\n > var r = it.next().value\n 0.0\n > r = it.next().value\n 7.0\n > r = it.next().value\n 8.0\n > r = it.next().value\n 10.0\n\n See Also\n --------\n itercumax, itercumean, itercumin, iterrange\n","itercusum":"\nitercusum( iterator )\n Returns an iterator which iteratively computes a cumulative sum.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusum( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 5.0\n\n See Also\n --------\n itercumean, itersum, itercuprod\n","itercusumabs":"\nitercusumabs( iterator )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 15.0\n\n See Also\n --------\n itercumeanabs, itercusum, itersumabs\n","itercusumabs2":"\nitercusumabs2( iterator )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs2( arr );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 63.0\n\n See Also\n --------\n itercumeanabs2, itercusumabs, itersumabs2\n","iterDatespace":"\niterDatespace( start, stop[, N][, options] )\n Returns an iterator which returns evenly spaced dates over a specified\n interval.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: integer|string|Date\n Starting date either as a `Date` object, JavaScript timestamp, or a date\n string (inclusive).\n\n stop: integer|string|Date\n Stopping value either as a `Date` object, JavaScript timestamp, or a\n date string (inclusive).\n\n N: integer (optional)\n Number of values. Default: 100.\n\n options: Object (optional)\n Function options.\n\n options.round: string (optional)\n Specifies how sub-millisecond times should be rounded. Must be one of\n the following: 'floor', 'ceil', or 'round'. Default: 'floor'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var t1 = new Date();\n > var it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterator2array, iterIncrspace, iterLinspace, iterLogspace, iterStep\n","iterDedupe":"\niterDedupe( iterator[, limit] )\n Returns an iterator which removes consecutive duplicated values.\n\n `NaN` values are considered distinct.\n\n Uniqueness is determined according to strict equality. Accordingly, objects\n are *not* checked for deep equality.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > var it = iterDedupe( arr );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupeBy, iterUnique\n","iterDedupeBy":"\niterDedupeBy( iterator, [limit,] fcn )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n\n The provided function is provided five arguments:\n\n - curr: current source iterated value.\n - sprev: previous source iterated value.\n - dprev: previous downstream iterated value.\n - index: source iteration index (zero-based).\n - acc: previous resolved value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n fcn: Function\n Function indicating whether an iterated value is a \"duplicate\".\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > function fcn( v ) { return v; };\n > var it = iterDedupeBy( arr, fcn );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupe, iterUnique\n","iterDeg2rad":"\niterDeg2rad( iterator )\n Returns an iterator which iteratively converts an angle from degrees to\n radians.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -360.0, 360.0 );\n > var it = iterDeg2rad( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.deg2rad, iterRad2deg\n","iterDigamma":"\niterDigamma( iterator )\n Returns an iterator which iteratively evaluates the digamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.01, 5.0 );\n > var it = iterDigamma( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.digamma, iterGamma, iterTrigamma\n","iterDiracComb":"\niterDiracComb( [options] )\n Returns an iterator which generates a Dirac comb.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracComb();\n > var v = it.next().value\n Infinity\n > v = it.next().value\n 0.0\n\n See Also\n --------\n iterPulse\n","iterDiracDelta":"\niterDiracDelta( iterator )\n Returns an iterator which iteratively evaluates the Dirac delta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracDelta( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.diracDelta\n","iterDivide":"\niterDivide( iter0, ...iterator )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterDivide( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 0.5\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n","iterDoUntilEach":"\niterDoUntilEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v !== v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterDoUntilEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterDoWhileEach, iterUntilEach, iterWhileEach\n","iterDoWhileEach":"\niterDoWhileEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v === v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterDoWhileEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterDoUntilEach, iterUntilEach, iterWhileEach\n","iterEllipe":"\niterEllipe( iterator )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the second kind.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.0, 1.0 );\n > var it = iterEllipe( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.ellipe, iterEllipk\n","iterEllipk":"\niterEllipk( iterator )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the first kind.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.0, 1.0 );\n > var it = iterEllipk( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.ellipk, iterEllipe\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEmpty();\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterConstant\n","iterErf":"\niterErf( iterator )\n Returns an iterator which iteratively evaluates the error function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErf( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erf, iterErfc, iterErfinv, iterErfcinv\n","iterErfc":"\niterErfc( iterator )\n Returns an iterator which iteratively evaluates the complementary error\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfc( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfc, iterErf, iterErfinv, iterErfcinv\n","iterErfcinv":"\niterErfcinv( iterator )\n Returns an iterator which iteratively evaluates the inverse complementary\n error function.\n\n The domain of inverse complementary error function is restricted to [0,2].\n If an iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfcinv, iterErf, iterErfc, iterErfinv\n","iterErfinv":"\niterErfinv( iterator )\n Returns an iterator which iteratively evaluates the inverse error function.\n\n The domain of inverse error function is restricted to [-1,1]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfinv, iterErf, iterErfc, iterErfcinv\n","iterEta":"\niterEta( iterator )\n Returns an iterator which iteratively evaluates the Dirichlet eta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEta( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.eta\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options] )\n Returns an iterator which generates an interleaved sequence of even\n integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n > v = it.next().value\n -2\n\n See Also\n --------\n iterIntegersSeq, iterOddIntegersSeq\n","iterEvery":"\niterEvery( iterator )\n Tests whether all iterated values are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is falsy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\n > var bool = iterEvery( arr )\n false\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNone, iterSome\n","iterEveryBy":"\niterEveryBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a falsy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterEveryBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNoneBy, iterSomeBy\n","iterExp":"\niterExp( iterator )\n Returns an iterator which iteratively evaluates the natural exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterExp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.exp, iterExp10, iterExp2, iterExpm1, iterLn\n","iterExp2":"\niterExp2( iterator )\n Returns an iterator which iteratively evaluates the base `2` exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExp2( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.exp2, iterExp, iterExp10, iterLog2\n","iterExp10":"\niterExp10( iterator )\n Returns an iterator which iteratively evaluates the base `10` exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExp10( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.exp10, iterExp, iterExp2, iterLog10\n","iterExpit":"\niterExpit( iterator )\n Returns an iterator which iteratively evaluates the standard logistic\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 1.0 );\n > var it = iterExpit( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expit, iterExp, iterLogit\n","iterExpm1":"\niterExpm1( iterator )\n Returns an iterator which iteratively computes `exp(x) - 1`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterExpm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expm1, iterExp, iterExpm1rel\n","iterExpm1rel":"\niterExpm1rel( iterator )\n Returns an iterator which iteratively evaluates the relative error\n exponential.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExpm1rel( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expm1rel, iterExp, iterExpm1\n","iterFactorial":"\niterFactorial( iterator )\n Returns an iterator which iteratively evaluates the factorial function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorial( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.factorial, iterFactorialln\n","iterFactorialln":"\niterFactorialln( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n factorial function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorialln( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.factorialln, iterFactorial\n","iterFactorialsSeq":"\niterFactorialsSeq( [options] )\n Returns an iterator which generates a sequence of factorials.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorialsSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterFactorial\n","iterFibonacciSeq":"\niterFibonacciSeq( [options] )\n Returns an iterator which generates a Fibonacci sequence.\n\n The returned iterator can only generate the first 79 Fibonacci numbers, as\n larger Fibonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFibonacciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.fibonacci, iterLucasSeq, iterNegaFibonacciSeq, iterNonFibonacciSeq\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options] )\n Returns an iterator which generates a sequence of fifth powers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1552.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFifthPowersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 32\n\n See Also\n --------\n iterCubesSeq, iterFourthPowersSeq, iterSquaresSeq\n","iterFill":"\niterFill( iterator, value[, begin[, end]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n replaces the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n value: any\n Static value.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\n > var r = it.next().value\n 3.14\n > r = it.next().value\n 3.14\n > r = it.next().value\n \n\n","iterFilter":"\niterFilter( iterator, predicate[, thisArg] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilter( it1, f );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterFilterMap, iterMap, iterReject\n","iterFilterMap":"\niterFilterMap( iterator, fcn[, thisArg] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n\n When invoked, the callback function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If the callback returns `undefined`, the iterator invokes the function for\n the next value of the provided iterator; otherwise, the iterator returns\n the callback's return value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Callback function which both filters and maps.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilterMap( it1, f );\n > var v = it2.next().value\n 30\n > v = it2.next().value\n 40\n\n See Also\n --------\n iterFilter, iterMap\n","iterFirst":"\niterFirst( iterator )\n Returns the first iterated value.\n\n The function does *not* consume an entire iterator before returning.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The first iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\n > var v = iterFirst( arr )\n 1\n\n See Also\n --------\n iterHead, iterLast, iterNth\n","iterFlatTopPulse":"\niterFlatTopPulse( [options] )\n Returns an iterator which generates a flat top pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFlatTopPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse\n","iterFloor":"\niterFloor( iterator )\n Returns an iterator which rounds each iterated value toward negative\n infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor, iterCeil, iterRound\n","iterFloor2":"\niterFloor2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward negative infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor2, iterCeil2, iterFloor, iterFloor10, iterRound2\n","iterFloor10":"\niterFloor10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward negative infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor10, iterCeil10, iterFloor, iterFloor2, iterRound10\n","iterFlow":"\niterFlow( methods )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n\n The methods argument should be an object which maps constructor method names\n to iterator functions.\n\n Each iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n When a fluent interface iterator method is invoked, the method invokes the\n corresponding iterator function with an iterator and provided method\n arguments.\n\n If an iterator function returns an iterator, the corresponding fluent\n interface method returns a new fluent interface instance; otherwise, the\n corresponding fluent interface method returns the iterator function result.\n\n The iterator function evaluation context is always `null`.\n\n Iterator functions which return iterators are expected to return iterator\n protocol-compliant objects (i.e., an object having a `next` method which\n returns the next iterated value (if one exists) assigned to a `value`\n property and a `done` property having a boolean value indicating whether the\n iterator is finished).\n\n If an environment supports `Symbol.iterator`, the returned constructor\n returns iterators which are iterable.\n\n Parameters\n ----------\n methods: Object\n An object mapping method names to iterator functions.\n\n Returns\n -------\n FluentIterator: Function\n Fluent interface iterator constructor.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n Returns a new fluent interface iterator from a source iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n Returns\n -------\n iterator: Object\n Fluent interface iterator.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var bool = it.head( 3 ).some( 2 )\n false\n\n\nFluentIterator.prototype.next()\n Returns the next iterated value.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > v = it2.next().value\n 0\n > v = it2.next().value\n 1\n\n\nFluentIterator.prototype.return( [value] )\n Finishes an iterator and returns a provided value.\n\n Parameters\n ----------\n value: any (optional)\n Value to return.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > var bool = it2.return().done\n true\n > v = it2.next().value\n undefined\n\n See Also\n --------\n iterPipeline\n","iterForEach":"\niterForEach( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterForEach( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterMap\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options] )\n Returns an iterator which generates a sequence of fourth powers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9741.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFourthPowersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 16\n\n See Also\n --------\n iterCubesSeq, iterFifthPowersSeq, iterSquaresSeq\n","iterFresnelc":"\niterFresnelc( iterator )\n Returns an iterator which iteratively computes the Fresnel integral C(x).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterFresnelc( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.fresnelc, iterFresnels\n","iterFresnels":"\niterFresnels( iterator )\n Returns an iterator which iteratively computes the Fresnel integral S(x).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterFresnels( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.fresnels, iterFresnelc\n","iterGamma":"\niterGamma( iterator )\n Returns an iterator which iteratively evaluates the gamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterGamma( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.gamma, iterGamma1pm1, iterGammaln\n","iterGamma1pm1":"\niterGamma1pm1( iterator )\n Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n cancellation errors for small `x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterGamma1pm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.gamma1pm1, iterGamma\n","iterGammaln":"\niterGammaln( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n gamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterGammaln( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.gammaln, iterGamma\n","iterHacovercos":"\niterHacovercos( iterator )\n Returns an iterator which iteratively computes the half-value coversed\n cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHacovercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.hacovercos, iterCovercos, iterHacoversin\n","iterHacoversin":"\niterHacoversin( iterator )\n Returns an iterator which iteratively computes the half-value coversed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHacoversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.hacoversin, iterCoversin, iterHacovercos\n","iterHannPulse":"\niterHannPulse( [options] )\n Returns an iterator which generates a Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterSineWave\n","iterHavercos":"\niterHavercos( iterator )\n Returns an iterator which iteratively computes the half-value versed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHavercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.havercos, iterHaversin, iterVercos\n","iterHaversin":"\niterHaversin( iterator )\n Returns an iterator which iteratively computes the half-value versed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHaversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.haversin, iterHavercos, iterVersin\n","iterHead":"\niterHead( iterator, n )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n\n If a provided iterator only generates `m` values and `m` is less than `n`,\n the returned iterator only returns `m` values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of values.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHead( random.iterators.randu(), 5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterSlice\n","iterIncrspace":"\niterIncrspace( start, stop[, increment] )\n Returns an iterator which returns evenly spaced numbers according to a\n specified increment.\n\n Beware that values which follow the starting value are subject to floating-\n point rounding errors.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number\n Stopping value (exclusive).\n\n increment: number (optional)\n Increment. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterIncrspace( 0, 101, 2 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, iterDatespace, iterLinspace, iterLogspace, iterStep, iterUnitspace\n","iterIntegersSeq":"\niterIntegersSeq( [options] )\n Returns an iterator which generates an interleaved integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 18014398509481984.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n -1\n\n See Also\n --------\n iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterIntersection":"\niterIntersection( iter0, ...iterator )\n Returns an iterator which returns the intersection of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterIntersection( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersectionByHash, iterUnion, iterUnique\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n A returned iterator internally buffers unique hashes, along with the *first*\n iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > function f( v ) { return v.toString(); };\n > var it = iterIntersectionByHash( it1, it2, f );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUniqueByHash\n","iterInv":"\niterInv( iterator )\n Returns an iterator which iteratively computes the multiplicative inverse.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterInv( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.inv, iterPow\n","iterLanczosPulse":"\niterLanczosPulse( [options] )\n Returns an iterator which generates a Lanczos pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLanczosPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterPeriodicSinc\n","iterLast":"\niterLast( iterator )\n Consumes an entire iterator and returns the last iterated value.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The last iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var v = iterLast( arr )\n 1\n\n See Also\n --------\n iterFirst, iterNth\n","iterLength":"\niterLength( iterator )\n Consumes an entire iterator and returns the number of iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n len: integer\n Iterator length.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var len = iterLength( arr )\n 5\n\n See Also\n --------\n iterCounter\n","iterLinspace":"\niterLinspace( start, stop[, N] )\n Returns an iterator which returns evenly spaced numbers over a specified\n interval.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number\n Stopping value (inclusive).\n\n N: integer (optional)\n Number of values. Default: 100.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLinspace( 0, 99, 100 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLogspace, iterStep, iterUnitspace\n","iterLn":"\niterLn( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLn( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ln, iterExp, iterLog10, iterLog1p, iterLog2\n","iterLog":"\niterLog( x, b )\n Returns an iterator which iteratively computes the base `b` logarithm.\n\n For negative `b` or `x` iterated values, the returned iterator returns\n `NaN`.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n b: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 100.0 );\n > var y = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterLog( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log, iterLog10, iterLog1p, iterLog2, iterPow\n","iterLog1mexp":"\niterLog1mexp( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1-exp(-|x|)`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1mexp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1mexp, iterLog, iterLog1p, iterLog1pexp, iterPow\n","iterLog1p":"\niterLog1p( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1p( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1p, iterLog, iterLog10, iterLog2, iterPow\n","iterLog1pexp":"\niterLog1pexp( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+exp(x)`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1pexp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1pexp, iterLog, iterLog1p, iterLog1mexp, iterPow\n","iterLog2":"\niterLog2( iterator )\n Returns an iterator which iteratively evaluates the binary logarithm.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log2, iterLog, iterLog10, iterLog1p, iterPow\n","iterLog10":"\niterLog10( iterator )\n Returns an iterator which iteratively evaluates the common logarithm\n (logarithm with base 10).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog10( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log10, iterLog, iterLog1p, iterLog2, iterPow\n","iterLogit":"\niterLogit( iterator )\n Returns an iterator which iteratively evaluates the logit function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 1.0 );\n > var it = iterLogit( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.logit\n","iterLogspace":"\niterLogspace( start, stop[, N][, options] )\n Returns an iterator which returns evenly spaced numbers on a log scale.\n\n In linear space, the sequence starts at `base` raised to the power of\n `start` and ends with `base` raised to the power of `stop`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Exponent of starting value.\n\n stop: number\n Exponent of stopping value.\n\n N: integer (optional)\n Number of values. Default: 100.\n\n options: Object (optional)\n Function options.\n\n options.base: number (optional)\n Base of log space. Default: 10.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLogspace( 0, 3, 4 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 10\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterStep\n","iterLucasSeq":"\niterLucasSeq( [options] )\n Returns an iterator which generates a Lucas sequence.\n\n The returned iterator can only generate the first 77 Lucas numbers, as\n larger Lucas numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 77.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLucasSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 1\n\n See Also\n --------\n base.lucas, iterFibonacciSeq, iterNegaLucasSeq\n","iterMap":"\niterMap( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return v * 10.0; };\n > var it = iterMap( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFilter, iterFilterMap, iterForEach, iterReject\n","iterMapN":"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n\n When invoked, the callback function is provided `N+1` arguments, where `N`\n is the number of provided iterators and the last argument is the iteration\n index:\n\n - ...value: iterated values.\n - index: iteration index (zero-based).\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators.\n\n fcn: Function\n Function to invoke with iterated values.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > function fcn( x, y ) { return x + y; };\n > var it = iterMapN( it1, it2, fcn );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterMap\n","itermax":"\nitermax( iterator )\n Computes the maximum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermax( arr )\n 3.0\n\n See Also\n --------\n itermidrange, itermin, itermmax, iterrange\n","itermaxabs":"\nitermaxabs( iterator )\n Computes the maximum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermaxabs( arr )\n 4.0\n\n See Also\n --------\n itermax, iterminabs, itermmaxabs\n","itermean":"\nitermean( iterator )\n Computes an arithmetic mean over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = itermean( arr )\n 2.5\n\n See Also\n --------\n itermidrange, itermmean, iterstdev, itersum, itervariance\n","itermeanabs":"\nitermeanabs( iterator )\n Computes an arithmetic mean of absolute values for all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs( arr )\n 2.5\n\n See Also\n --------\n itermean, itermmeanabs, itersumabs\n","itermeanabs2":"\nitermeanabs2( iterator )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs2( arr )\n 7.5\n\n See Also\n --------\n itermean, itermeanabs, itermmeanabs2, itersumabs2\n","itermidrange":"\nitermidrange( iterator )\n Computes the mid-range of all iterated values.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Mid-range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = itermidrange( arr )\n -0.5\n\n See Also\n --------\n itermean, itermax, itermin, iterrange\n","itermin":"\nitermin( iterator )\n Computes the minimum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermin( arr )\n -3.0\n\n See Also\n --------\n itermax, itermidrange, itermmin, iterrange\n","iterminabs":"\niterminabs( iterator )\n Computes the minimum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = iterminabs( arr )\n 1.0\n\n See Also\n --------\n itermaxabs, itermin, itermminabs\n","itermmax":"\nitermmax( iterator, W )\n Returns an iterator which iteratively computes a moving maximum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmax( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermax, itermmidrange, itermmin, itermrange\n","itermmaxabs":"\nitermmaxabs( iterator, W )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmaxabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermaxabs, itermmax, itermminabs\n","itermmean":"\nitermmean( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmean( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.0\n\n See Also\n --------\n itermean, itermsum\n","itermmeanabs":"\nitermmeanabs( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n ~4.33\n\n See Also\n --------\n itermeanabs, itermmean, itermsumabs\n","itermmeanabs2":"\nitermmeanabs2( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of squared absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs2( arr, 3 );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n ~19.67\n\n See Also\n --------\n itermeanabs2, itermmeanabs, itermsumabs2\n","itermmidrange":"\nitermmidrange( iterator, W )\n Returns an iterator which iteratively computes a moving mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmidrange( arr, 3 );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itermidrange, itermmean, itermmax, itermmin, itermrange\n","itermmin":"\nitermmin( iterator, W )\n Returns an iterator which iteratively computes a moving minimum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmin( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itermin, itermmax, itermmidrange, itermrange\n","itermminabs":"\nitermminabs( iterator, W )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermminabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n\n See Also\n --------\n iterminabs, itermmaxabs, itermmin\n","iterMod":"\niterMod( iter0, ...iterator )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterMod( it1, it2 );\n > var v = it.next().value\n 0.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide\n","itermprod":"\nitermprod( iterator, W )\n Returns an iterator which iteratively computes a moving product.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermprod( arr, 3 );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -75.0\n\n See Also\n --------\n itermsum, iterprod\n","itermrange":"\nitermrange( iterator, W )\n Returns an iterator which iteratively computes a moving range.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermrange( arr, 3 );\n > var m = it.next().value\n 0.0\n > m = it.next().value\n 7.0\n > m = it.next().value\n 8.0\n > m = it.next().value\n 10.0\n\n See Also\n --------\n itermmax, itermmean, itermmin, iterrange\n","itermsum":"\nitermsum( iterator, W )\n Returns an iterator which iteratively computes a moving sum.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsum( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 3.0\n\n See Also\n --------\n itermmean, itersum\n","itermsumabs":"\nitermsumabs( iterator, W )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 13.0\n\n See Also\n --------\n itermmeanabs, itermsum, itersum, itersumabs\n","itermsumabs2":"\nitermsumabs2( iterator, W )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs2( arr, 3 );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 59.0\n\n See Also\n --------\n itermmeanabs2, itermsumabs, itersumabs, itersumabs2\n","iterMultiply":"\niterMultiply( iter0, ...iterator )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to multiply.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterMultiply( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 8.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterSubtract\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options] )\n Returns an iterator which generates a negaFibonacci sequence.\n\n The returned iterator can only generate the first 79 negaFibonacci numbers,\n as larger negaFibonacci numbers cannot be safely represented in double-\n precision floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegaFibonacciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.negafibonacci, iterFibonacciSeq, iterNonFibonacciSeq\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options] )\n Returns an iterator which generates a negaLucas sequence.\n\n The returned iterator can only generate the first 77 negaLucas numbers, as\n larger negaLucas numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 77.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegaLucasSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n -1\n\n See Also\n --------\n base.negalucas, iterLucasSeq, iterNegaFibonacciSeq\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of negative even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeEvenIntegersSeq();\n > var v = it.next().value\n -2\n > v = it.next().value\n -4\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterNonPositiveEvenIntegersSeq\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options] )\n Returns an iterator which generates a negative integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740991.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeIntegersSeq();\n > var v = it.next().value\n -1\n > v = it.next().value\n -2\n\n See Also\n --------\n iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options] )\n Returns an iterator which generates a sequence of negative odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeOddIntegersSeq();\n > var v = it.next().value\n -1\n > v = it.next().value\n -3\n\n See Also\n --------\n iterOddIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeEvenIntegersSeq, iterPositiveOddIntegersSeq\n","iterNone":"\niterNone( iterator )\n Tests whether all iterated values are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is truthy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterNone( arr )\n false\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNoneBy, iterSome\n","iterNoneBy":"\niterNoneBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a falsy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v <= 0 ); };\n > var bool = iterNoneBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNone, iterSomeBy\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonFibonacciSeq();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n\n See Also\n --------\n base.nonfibonacci, iterFibonacciSeq\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of nonnegative even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370497.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonNegativeEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveEvenIntegersSeq, iterPositiveEvenIntegersSeq\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options] )\n Returns an iterator which generates a nonnegative integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonNegativeIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterIntegersSeq, iterNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of nonpositive even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370497.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonPositiveEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n -2\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeEvenIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeEvenIntegersSeq\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options] )\n Returns an iterator which generates a nonpositive integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonPositiveIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n -1\n\n See Also\n --------\n iterIntegersSeq, iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterPositiveIntegersSeq\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options] )\n Returns an iterator which generates a sequence of nonsquares.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199349647256.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonSquaresSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 5\n\n See Also\n --------\n iterCubesSeq, iterSquaresSeq\n","iterNth":"\niterNth( iterator, n )\n Returns the nth iterated value.\n\n If `n` exceeds the total number of iterations, the function returns\n `undefined`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Iteration number.\n\n Returns\n -------\n v: any\n The nth iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\n > var v = iterNth( arr, 3 )\n 1\n\n See Also\n --------\n iterFirst, iterLast\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options] )\n Returns an iterator which generates an interleaved sequence of odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterOddIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n -1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq\n","iterPeriodicSinc":"\niterPeriodicSinc( n[, options] )\n Returns an iterator which generates a periodic sinc waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Order.\n\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 100.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPeriodicSinc( 7 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterSineWave\n","iterPipeline":"\niterPipeline( iterFcn[, ...iterFcn] )\n Returns an iterator pipeline.\n\n Parameters\n ----------\n iterFcn: Function|Array\n Iterator function or an array of iterator functions.\n\n iterFcn: ...Function (optional)\n Iterator functions.\n\n Returns\n -------\n fcn( src ): Function\n Iterator pipeline which accepts a single argument, a source iterator.\n\n Examples\n --------\n > var it1 = iterThunk( iterHead, 100 );\n > function f( r ) { return ( r > 0.95 ); };\n > var it2 = iterThunk( iterSomeBy, 5, f );\n > var p = iterPipeline( it1, it2 );\n > var bool = p( random.iterators.randu() )\n \n\n See Also\n --------\n iterFlow, iterThunk\n","iterPop":"\niterPop( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the last value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPop( it1 );\n > var v = it2.next().value\n 1\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPush, iterShift, iterSlice\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of positive even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveEvenIntegersSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 4\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNegativeEvenIntegersSeq, iterNonNegativeEvenIntegersSeq, iterPositiveIntegersSeq, iterPositiveOddIntegersSeq\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options] )\n Returns an iterator which generates a positive integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740991.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeIntegersSeq\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options] )\n Returns an iterator which generates a sequence of positive odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveOddIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterOddIntegersSeq, iterIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterPositiveIntegersSeq\n","iterPow":"\niterPow( base, exponent )\n Returns an iterator which iteratively evaluates the exponential function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n base: Object|number\n Input iterator.\n\n exponent: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( -2.0, 2.0 );\n > var it = iterPow( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.pow, iterExp, iterLog\n","iterPrimesSeq":"\niterPrimesSeq( [options] )\n Returns an iterator which generates a sequence of prime numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 245181918813464.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPrimesSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 5\n\n See Also\n --------\n iterCompositesSeq, iterIntegersSeq, iterPositiveIntegersSeq\n","iterprod":"\niterprod( iterator )\n Computes the product of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Product.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = iterprod( arr )\n 24.0\n\n See Also\n --------\n itermprod, itersum\n","iterPulse":"\niterPulse( [options] )\n Returns an iterator which generates a pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 10.\n\n options.duration: integer (optional)\n Pulse duration (i.e., the number of consecutive iterations of maximum\n amplitude during one period). Default: floor(options.period/2).\n\n options.min: number (optional)\n Minimum amplitude. Default: 0.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPulse();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterPush":"\niterPush( iterator, ...items )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to append.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPush( it1, 3, 4 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterUnshift\n","iterRad2deg":"\niterRad2deg( iterator )\n Returns an iterator which iteratively converts an angle from radians to\n degrees.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterRad2deg( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.rad2deg, iterDeg2rad\n","iterRamp":"\niterRamp( iterator )\n Returns an iterator which iteratively evaluates the ramp function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRamp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ramp\n","iterrange":"\niterrange( iterator )\n Computes the range of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = iterrange( arr )\n 7.0\n\n See Also\n --------\n itermax, itermean, itermin, itermrange\n","iterReject":"\niterReject( iterator, predicate[, thisArg] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterReject( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterFilter, iterMap\n","iterReplicate":"\niterReplicate( iterator, n )\n Returns an iterator which replicates each iterated value `n` times.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of times each iterated value is replicated.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > var it2 = iterReplicate( it1, 2 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterReplicateBy\n","iterReplicateBy":"\niterReplicateBy( iterator, fcn[, thisArg] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n\n The callback function is provided three arguments:\n\n - value: iterated value.\n - index: source iteration index (zero-based).\n - n: iteration index (zero-based).\n\n The callback function is invoked *once* per iterated value of the provided\n iterator.\n\n The callback function *must* return an integer value. If the return value is\n less than or equal to zero, the returned iterator skips an iterated value\n and invokes the callback for the next iterated value of the provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function which returns the number of times an iterated value should be\n replicated.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > function f( v, i ) { return i + 1; };\n > var it2 = iterReplicateBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterReplicate\n","iterRound":"\niterRound( iterator )\n Returns an iterator which rounds each iterated value to the nearest integer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round, iterCeil, iterFloor, iterTrunc\n","iterRound2":"\niterRound2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two on a linear scale.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round2, iterCeil2, iterFloor2, iterRound, iterRound10, iterTrunc2\n","iterRound10":"\niterRound10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 on a linear scale.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round10, iterCeil10, iterFloor10, iterRound, iterRound2, iterTrunc10\n","iterRsqrt":"\niterRsqrt( iterator )\n Returns an iterator which iteratively computes the reciprocal (inverse)\n square root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRsqrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.rsqrt, iterSqrt\n","iterSawtoothWave":"\niterSawtoothWave( [options] )\n Returns an iterator which generates a sawtooth wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSawtoothWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSineWave, iterSquareWave, iterTriangleWave\n","iterShift":"\niterShift( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the first value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterShift( it1 );\n > var v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPop, iterSlice, iterUnshift\n","iterSignum":"\niterSignum( iterator )\n Returns an iterator which iteratively evaluates the signum function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSignum( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.signum\n","iterSin":"\niterSin( iterator )\n Returns an iterator which iteratively computes the sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSin( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sin, iterCos, iterSinpi, iterTan\n","iterSinc":"\niterSinc( iterator )\n Returns an iterator which iteratively computes the normalized cardinal sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterSinc( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sinc, iterSin\n","iterSineWave":"\niterSineWave( [options] )\n Returns an iterator which generates a sine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a sine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterCosineWave, iterPulse, iterSawtoothWave, iterSquareWave, iterTriangleWave\n","iterSinh":"\niterSinh( iterator )\n Returns an iterator which iteratively evaluates the hyperbolic sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterSinh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sinh, iterCosh, iterTanh\n","iterSinpi":"\niterSinpi( iterator )\n Returns an iterator which computes the sine of each iterated value times π.\n\n Computes sin(πx) more accurately than sin(pi*x), especially for large x.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSinpi( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sinpi, iterSin\n","iterSlice":"\niterSlice( iterator[, begin[, end]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n returns the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSlice( random.iterators.randu(), 5, 10 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterHead\n","iterSome":"\niterSome( iterator, n )\n Tests whether at least `n` iterated values are truthy.\n\n The function immediately returns upon finding `n` truthy values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an iterator returns at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = iterSome( arr, 3 )\n true\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNone, iterSomeBy\n","iterSomeBy":"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering `n` truthy return values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Minimum number of successful values.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for at least `n` iterated values. Otherwise, the function returns\n `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterSomeBy( arr, 3, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNoneBy, iterSome\n","iterSpence":"\niterSpence( iterator )\n Returns an iterator which iteratively evaluates Spence's function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 100.0 );\n > var it = iterSpence( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.spence\n","iterSqrt":"\niterSqrt( iterator )\n Returns an iterator which iteratively computes the principal square root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSqrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sqrt, iterCbrt, iterRsqrt\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator )\n Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n accurately for small `x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 100.0 );\n > var it = iterSqrt1pm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sqrt1pm1, iterSqrt\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options] )\n Returns an iterator which generates a sequence of squared triangular\n numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 11585.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquaredTriangularSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 9\n\n See Also\n --------\n iterTriangularSeq\n","iterSquaresSeq":"\niterSquaresSeq( [options] )\n Returns an iterator which generates a sequence of squares.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 94906265.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquaresSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 4\n\n See Also\n --------\n iterCubesSeq, iterNonSquaresSeq\n","iterSquareWave":"\niterSquareWave( [options] )\n Returns an iterator which generates a square wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a square wave repeats).\n This must be an even integer in order to ensure a 50% duty cycle.\n Default: 10.\n\n options.min: number (optional)\n Minimum amplitude. Default: -1.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquareWave();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterTriangleWave\n","iterstdev":"\niterstdev( iterator[, mean] )\n Computes a correct sample standard deviation over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Corrected sample standard deviation.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var m = iterstdev( arr )\n ~4.95\n\n See Also\n --------\n itermean, itervariance\n","iterStep":"\niterStep( start, increment[, N] )\n Returns an iterator which returns a sequence of numbers according to a\n specified increment.\n\n Beware that values which follow the starting value are subject to floating-\n point rounding errors.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n increment: number\n Increment.\n\n N: number (optional)\n Number of values. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterStep( 0, 2, 10 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterLogspace, iterUnitspace\n","iterStrided":"\niterStrided( iterator, stride[, offset[, eager]] )\n Returns an iterator which steps by a specified amount.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n stride: integer\n Stride (i.e., step amount).\n\n offset: integer (optional)\n Index of the first iterated value. Default: 0.\n\n eager: boolean (optional)\n Boolean indicating whether to eagerly advance the input iterator when\n provided a non-zero offset. Default: false.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n > var it = iterStrided( arr, 2, 1 );\n > var r = it.next().value\n 1\n > r = it.next().value\n 3\n\n See Also\n --------\n iterAdvance, iterNth, iterStridedBy\n","iterStridedBy":"\niterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )\n Returns an iterator which steps according to a provided callback function.\n\n When invoked, the input function is provided four arguments:\n\n - value: iterated value.\n - i: input iteration index (zero-based).\n - n: output (strided) iteration index (zero-based).\n - curr: current stride.\n\n The return value of the input function specifies the next stride.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Stride function (i.e., a function which returns the step amount).\n\n offset: integer (optional)\n Index of the first iterated value. Default: 0.\n\n eager: boolean (optional)\n Boolean indicating whether to eagerly advance the input iterator when\n provided a non-zero offset. Default: false.\n\n thisArg: any (optional)\n Stride function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n > function stride( v, i ) { return (i % 10)+1; };\n > var it = iterStridedBy( arr, stride );\n > var r = it.next().value\n 0\n > r = it.next().value\n 1\n > r = it.next().value\n 3\n\n See Also\n --------\n iterAdvance, iterNth, iterStrided\n","iterSubtract":"\niterSubtract( iter0, ...iterator )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to subtract.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 5.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterSubtract( it1, it2 );\n > var v = it.next().value\n -2.0\n > v = it.next().value\n 1.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n","itersum":"\nitersum( iterator )\n Computes the sum of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = itersum( arr )\n 10.0\n\n See Also\n --------\n itermean, itermsum, iterprod\n","itersumabs":"\nitersumabs( iterator )\n Computes the sum of absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs( arr )\n 10.0\n\n See Also\n --------\n itermeanabs, itermsumabs, itersum\n","itersumabs2":"\nitersumabs2( iterator )\n Computes the sum of squared absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs2( arr )\n 30.0\n\n See Also\n --------\n itermeanabs2, itermsumabs2, itersumabs\n","iterTan":"\niterTan( iterator )\n Returns an iterator which iteratively evaluates the tangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.57, 1.57 );\n > var it = iterTan( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.tan, iterCos, iterSin\n","iterTanh":"\niterTanh( iterator )\n Returns an iterator which iteratively evaluates the hyperbolic tangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -4.0, 4.0 );\n > var it = iterTanh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.tanh, iterCosh, iterSinh, iterTan\n","iterThunk":"\niterThunk( iterFcn[, ...args] )\n Returns an iterator \"thunk\".\n\n A provided iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n The returned function expects a single argument, an iterator.\n\n This function is useful within the context of iterator pipelines as a means\n to defer execution until a pipeline is ready for data flow.\n\n Parameters\n ----------\n iterFcn: Function\n Iterator function.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n fcn( iter ): Function\n Function which accepts a single argument, an iterator, and invokes a\n previously provided iterator function with the provided iterator and any\n previously provided arguments.\n\n Examples\n --------\n > var fcn = iterThunk( iterSome, 3 );\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = fcn( arr )\n true\n\n See Also\n --------\n iterPipeline\n","iterTriangleWave":"\niterTriangleWave( [options] )\n Returns an iterator which generates a triangle wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangleWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave\n","iterTriangularSeq":"\niterTriangularSeq( [options] )\n Returns an iterator which generates a sequence of triangular numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 134217727.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangularSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterSquaredTriangularSeq\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options] )\n Returns an iterator which generates a Tribonacci sequence.\n \n The returned iterator can only generate the first 64 Tribonacci numbers, as\n larger Tribonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 64.\n\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant\n object has the next\n iterated value (if one exists) and a\n boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n\n Examples\n --------\n > var it = iterTribonnaciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 0\n\n See Also\n --------\n base.tribonacci, base.fibonacci, iterLucasSeq\n","iterTrigamma":"\niterTrigamma( iterator )\n Returns an iterator which iteratively evaluates the trigamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.01, 50.0 );\n > var it = iterTrigamma( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.trigamma, iterDigamma, iterGamma\n","iterTrunc":"\niterTrunc( iterator )\n Returns an iterator which rounds each iterated value toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc, iterCeil, iterFloor, iterRound\n","iterTrunc2":"\niterTrunc2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc2, iterCeil2, iterFloor2, iterRound2, iterTrunc\n","iterTrunc10":"\niterTrunc10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc10, iterCeil10, iterFloor10, iterRound10, iterTrunc\n","iterUnion":"\niterUnion( iter0, ...iterator )\n Returns an iterator which returns the union of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the total number of source iterator\n values.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterUnion( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 4\n > v = it.next().value\n 5\n > v = it.next().value\n 3\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUnique\n","iterUnique":"\niterUnique( iterator )\n Returns an iterator which returns unique values.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = iterUnique( it1 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUniqueBy, iterUniqueByHash\n","iterUniqueBy":"\niterUniqueBy( iterator, predicate[, thisArg] )\n Returns an iterator which returns unique values according to a predicate\n function.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n A predicate function is invoked for each iterated value against each value\n in an internal buffer consisting of previously identified unique values.\n Thus, as the number of unique values grows, so, too, does the number of\n predicate function invocations per iterated value.\n\n An iterated value is considered \"unique\" if the predicate function returns\n truthy values for all comparisons of the iterated value with each value in\n the internal buffer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n A binary function with parameters `a` and `b` corresponding to iterated\n values. If the values are the same, the function should return `false`\n (i.e., non-unique); otherwise, if the values are distinct, the function\n should return `true` (i.e., unique).\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( a, b ) { return ( a !== b ); };\n > var it2 = iterUniqueBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueByHash\n","iterUniqueByHash":"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n Returns an iterator which returns unique values according to a hash\n function.\n\n A returned iterator internally buffers unique hashes and, thus, has O(N)\n memory requirements.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( v ) { return v.toString(); };\n > var it2 = iterUniqueByHash( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueBy\n","iterUnitspace":"\niterUnitspace( start[, stop] )\n Returns an iterator which returns numbers incremented by one.\n\n The iterator stops once the `stop` value is exceeded.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number (optional)\n Stopping value. Default: +infinity.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterUnitspace( 0, 99 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterator2array, iterIncrspace, iterLinspace, iterStep\n","iterUnshift":"\niterUnshift( iterator, ...items )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to prepend.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterUnshift( it1, 3, 4 );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterPush, iterShift\n","iterUntilEach":"\niterUntilEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v !== v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterUntilEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterWhileEach\n","itervariance":"\nitervariance( iterator[, mean] )\n Computes an unbiased sample variance over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Unbiased sample variance.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var s2 = itervariance( arr )\n 24.5\n\n See Also\n --------\n itermean, iterstdev\n","iterVercos":"\niterVercos( iterator )\n Returns an iterator which iteratively computes the versed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterVercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.vercos, iterCos, iterSin, iterVersin\n","iterVersin":"\niterVersin( iterator )\n Returns an iterator which iteratively computes the versed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterVersin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.versin, iterCos, iterSin, iterVercos\n","iterWhileEach":"\niterWhileEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v === v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterWhileEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterUntilEach\n","iterZeta":"\niterZeta( iterator )\n Returns an iterator which iteratively evaluates the Riemann zeta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 1.1, 50.0 );\n > var it = iterZeta( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.zeta\n","joinStream":"\njoinStream( [options] )\n Returns a transform stream which joins streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = joinStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream\n","joinStream.factory":"\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","joinStream.objectMode":"\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream","kde2d":"\nkde2d( x, y[, options] )\n Two-dimensional kernel density estimation.\n\n Parameters\n ----------\n x: Array\n Array of x values.\n\n y: Array\n Array of y values.\n\n options: Object (optional)\n Function options.\n\n options.h: number (optional)\n Array of length two containing the bandwidth values for x and y.\n\n options.n: number (optional)\n Number of partitions on the x- and y-axes. Default: `25`.\n\n options.xMin: number (optional)\n Lower limit of x.\n\n options.xMax: number (optional)\n Upper limit of x.\n\n options.yMin: number (optional)\n Lower limit of y.\n\n options.yMax: number (optional)\n Upper limit of y.\n\n options.kernel: string|Function\n A string or function to specifying the used kernel function. Default:\n `'gaussian'`.\n\n Returns\n -------\n out: Object\n Object containing the density estimates (`z`) along grid points (`x` and\n `y` values).\n\n Examples\n --------\n > var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\n > var y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\n > var out = kde2d( x, y )\n { 'x': [1, ... ], 'y': [0.05, ...], 'z': ndarray{Float64Array[0.031, ...] }\n\n","kebabcase":"\nkebabcase( str )\n Converts a string to kebab case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Kebab-cased string.\n\n Examples\n --------\n > var out = kebabcase( 'Hello World!' )\n 'hello-world'\n > out = kebabcase( 'I am a tiny little teapot' )\n 'i-am-a-tiny-little-teapot'\n\n See Also\n --------\n camelcase, constantcase, pascalcase, snakecase","keyBy":"\nkeyBy( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n\n When invoked, the input function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyBy( arr, toKey )\n { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n See Also\n --------\n forEach\n","keyByRight":"\nkeyByRight( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n\n When invoked, the input function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyByRight( arr, toKey )\n { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n See Also\n --------\n forEachRight, keyBy\n","keysIn":"\nkeysIn( obj )\n Returns an array of an object's own and inherited enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = keysIn( obj )\n e.g., [ 'beep', 'foo' ]\n\n See Also\n --------\n objectEntriesIn, objectKeys, objectValuesIn\n","kruskalTest":"\nkruskalTest( ...x[, options] )\n Computes the Kruskal-Wallis test for equal medians.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = kruskalTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = kruskalTest( arr, { 'groups': groups } )\n\n","kstest":"\nkstest( x, y[, ...params][, options] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n is computed for the null hypothesis that the values of `x` come from the\n distribution specified by `y`. `y` can be either a string with the name of\n the distribution to test against, or a function.\n\n In the latter case, `y` is expected to be the cumulative distribution\n function (CDF) of the distribution to test against, with its first parameter\n being the value at which to evaluate the CDF and the remaining parameters\n constituting the parameters of the distribution. The parameters of the\n distribution are passed as additional arguments after `y` from `kstest` to\n the chosen CDF. The function returns an object holding the calculated test\n statistic `statistic` and the `pValue` of the test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the hypothesis test results.\n\n Parameters\n ----------\n x: Array\n Input array holding numeric values.\n\n y: Function|string\n Either a CDF function or a string denoting the name of a distribution.\n\n params: ...number (optional)\n Distribution parameters passed to reference CDF.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array is already in sorted order.\n Default: `false`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that the true distribution of `x` is not equal\n to the reference distribution specified by `y` (`two-sided`), whether it\n is `less` than the reference distribution or `greater` than the\n reference distribution. Default: `'two-sided'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.alternative: string\n Used test alternative. Either `two-sided`, `less` or `greater`.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Verify that data is drawn from a normal distribution:\n > var rnorm = base.random.normal.factory({ 'seed': 4839 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n // Test against N(0,1)\n > var out = kstest( x, 'normal', 0.0, 1.0 )\n { pValue: 0.0, statistic: 0.847, ... }\n\n // Test against N(3,1)\n > out = kstest( x, 'normal', 3.0, 1.0 )\n { pValue: 0.6282, statistic: 0.0733, ... }\n\n // Verify that data is drawn from a uniform distribution:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0 )\n { pValue: ~0.703, statistic: ~0.069, ... }\n\n // Print output:\n > out.print()\n Kolmogorov-Smirnov goodness-of-fit test.\n\n Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n pValue: 0.7039\n statistic: 0.0689\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Set custom significance level:\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\n { pValue: ~0.7039, statistic: ~0.069, ... }\n\n // Carry out one-sided hypothesis tests:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\n { pValue: ~0.358, statistic: ~0.07, ... }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\n { pValue: ~0.907, statistic: ~0.02, ... }\n\n // Set `sorted` option to true when data is in increasing order:\n > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n { pValue: ~1, statistic: 0.1, ... }\n\n","last":"\nlast( str[, n][, options] )\n Returns the last character(s) of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to return. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = last( 'beep' )\n 'p'\n > out = last( 'Boop', 2 )\n 'op'\n > out = last( 'foo bar', 3 )\n 'bar'\n\n See Also\n --------\n firstChar\n","leveneTest":"\nleveneTest( x[, ...y[, options]] )\n Computes Levene's test for equal variances.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n y: ...Array (optional)\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Array\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = leveneTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = leveneTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, bartlettTest\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n\n Returns\n -------\n list: Object\n Linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the last node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = LinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n DoublyLinkedList, Stack\n","linspace":"\nlinspace( start, stop, length[, options] )\n Generates a linearly spaced array over a specified interval.\n\n If the specified length is zero, the function returns an empty array.\n\n If the specified length is one, the function returns an array containing\n `stop`, but not `start`, when `endpoint` is true; otherwise, the function\n returns an array containing `start`, but not `stop`.\n\n For real-valued `start` and `stop`, if `start` is less than `stop`, the\n output array will contain ascending values, and, if `start` is greater than\n `stop`, the output array will contain descending values.\n\n When the output array length is greater than one and `endpoint` is true, the\n output array is guaranteed to include the `start` and `stop` values. Beware,\n however, that values between `start` and `stop` are subject to floating-\n point rounding errors.\n\n If both `start` and `stop` are real-valued, the output array data type may\n be any floating-point data type or 'generic'. However, if either `start` or\n `stop` are complex numbers, the output array type must be a complex\n floating-point data type or 'generic'.\n\n When writing to a complex floating-point output array, real-valued `start`\n and `stop` values are treated as complex numbers having a real component\n equaling the provided value and having an imaginary component equaling zero.\n\n When generating linearly spaced complex floating-point numbers, the real and\n imaginary components are generated separately.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n length: integer\n Length of output array.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Must be a floating-point data type or 'generic'.\n If both `start` and `stop` are the same type (either 'float64',\n 'complex64', or 'complex128'), the default output array data type is\n the same type as the input values (either 'float64', 'complex64', or\n 'complex128', respectively). Otherwise, the default output array data\n type is 'complex128'.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `length + 1` linearly spaced\n values over the interval `[start, stop]` and only writes `length` values\n to the output array, thus excluding `stop` from the output array.\n Accordingly, for a fixed `length`, the spacing between adjacent values\n in the output array changes depending on the value of `endpoint`.\n Default: true.\n\n Returns\n -------\n arr: Array\n Linearly spaced array.\n\n Examples\n --------\n > var arr = linspace( 0.0, 100.0, 6 )\n [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n > arr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\n [ 0.0, 20.0, 40.0, 60.0, 80.0 ]\n > arr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n\n\nlinspace.assign( start, stop, out[, options] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n\n If the provided output array is empty, the function returns the provided\n output array unchanged.\n\n If the provided output array contains a single element, the function writes\n the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n function writes the `start` value, but not `stop`.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n out: ArrayLikeObject\n Output array.\n\n options: Object (optional)\n Options.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `N+1` linearly spaced values\n (where `N` is the length of the provided output array) over the interval\n `[start, stop]` and only writes `N` values to the output array, thus\n excluding `stop` from the output array. Accordingly, for a fixed `N`,\n the spacing between adjacent values in the output array changes\n depending on the value of `endpoint`. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0, 0 ];\n > var out = linspace.assign( 0, 100, arr )\n [ 0, 20, 40, 60, 80, 100 ]\n > var bool = ( arr === out )\n true\n > arr = [ 0, 0, 0, 0, 0 ];\n > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n [ 0, 20, 40, 60, 80 ]\n\n See Also\n --------\n incrspace, logspace\n","linspace.assign":"\nlinspace.assign( start, stop, out[, options] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n\n If the provided output array is empty, the function returns the provided\n output array unchanged.\n\n If the provided output array contains a single element, the function writes\n the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n function writes the `start` value, but not `stop`.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n out: ArrayLikeObject\n Output array.\n\n options: Object (optional)\n Options.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `N+1` linearly spaced values\n (where `N` is the length of the provided output array) over the interval\n `[start, stop]` and only writes `N` values to the output array, thus\n excluding `stop` from the output array. Accordingly, for a fixed `N`,\n the spacing between adjacent values in the output array changes\n depending on the value of `endpoint`. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0, 0 ];\n > var out = linspace.assign( 0, 100, arr )\n [ 0, 20, 40, 60, 80, 100 ]\n > var bool = ( arr === out )\n true\n > arr = [ 0, 0, 0, 0, 0 ];\n > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n [ 0, 20, 40, 60, 80 ]\n\n See Also\n --------\n incrspace, logspace","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of negative opinion words.\n\n Examples\n --------\n > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_POSITIVE_OPINION_WORDS_EN\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of positive opinion words.\n\n Examples\n --------\n > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_NEGATIVE_OPINION_WORDS_EN\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n\n Examples\n --------\n > LN_HALF\n -0.6931471805599453\n\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n\n Examples\n --------\n > LN_PI\n 1.1447298858494002\n\n See Also\n --------\n PI\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n\n Examples\n --------\n > LN_SQRT_TWO_PI\n 0.9189385332046728\n\n See Also\n --------\n PI\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n\n Examples\n --------\n > LN_TWO_PI\n 1.8378770664093456\n\n See Also\n --------\n TWO_PI\n","LN2":"\nLN2\n Natural logarithm of `2`.\n\n Examples\n --------\n > LN2\n 0.6931471805599453\n\n See Also\n --------\n LN10\n","LN10":"\nLN10\n Natural logarithm of `10`.\n\n Examples\n --------\n > LN10\n 2.302585092994046\n\n See Also\n --------\n LN2\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n\n Examples\n --------\n > LOG2E\n 1.4426950408889634\n\n See Also\n --------\n E, LOG10E\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n\n Examples\n --------\n > LOG10E\n 0.4342944819032518\n\n See Also\n --------\n E, LOG2E\n","logspace":"\nlogspace( a, b[, length] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n If a `length` is not provided, the default output array length is `10`.\n\n The output array includes the values `10^a` and `10^b`.\n\n Parameters\n ----------\n a: number\n Exponent of start value.\n\n b: number\n Exponent of end value.\n\n length: integer (optional)\n Length of output array. Default: `10`.\n\n Returns\n -------\n arr: Array\n Logarithmically spaced numeric array.\n\n Examples\n --------\n > var arr = logspace( 0, 2, 6 )\n [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n See Also\n --------\n incrspace, linspace\n","lowercase":"\nlowercase( str )\n Converts a string to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n uncapitalize, uppercase\n","lowercaseKeys":"\nlowercaseKeys( obj )\n Converts each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'A': 1, 'B': 2 };\n > var out = lowercaseKeys( obj )\n { 'a': 1, 'b': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","lowess":"\nlowess( x, y[, options] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n\n Parameters\n ----------\n x: Array\n x-axis values (abscissa values).\n\n y: Array\n Corresponding y-axis values (ordinate values).\n\n options: Object (optional)\n Function options.\n\n options.f: number (optional)\n Positive number specifying the smoothing span, i.e., the proportion of\n points which influence smoothing at each value. Larger values\n correspond to more smoothing. Default: `2/3`.\n\n options.nsteps: number (optional)\n Number of iterations in the robust fit (fewer iterations translates to\n faster function execution). If set to zero, the nonrobust fit is\n returned. Default: `3`.\n\n options.delta: number (optional)\n Nonnegative number which may be used to reduce the number of\n computations. Default: 1/100th of the range of `x`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n Returns\n -------\n out: Object\n Object with ordered x-values and fitted values.\n\n Examples\n --------\n > var x = new Float64Array( 100 );\n > var y = new Float64Array( x.length );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = i;\n ... y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n ... }\n > var out = lowess( x, y );\n > var yhat = out.y;\n\n > var h = Plot( [ x, x ], [ y, yhat ] );\n > h.lineStyle = [ 'none', '-' ];\n > h.symbols = [ 'closed-circle', 'none' ];\n\n > h.view( 'window' );\n\n","lpad":"\nlpad( str, len[, pad] )\n Left pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = lpad( 'a', 5 )\n ' a'\n > out = lpad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = lpad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n pad, rpad\n","ltrim":"\nltrim( str )\n Trims whitespace from the beginning of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n See Also\n --------\n trim, rtrim\n","ltrimN":"\nltrimN( str, n[, chars] )\n Trims `n` characters from the beginning of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of characters to trim.\n\n chars: Array|string (optional)\n Characters to trim. Default: whitespace characters.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrimN( ' abc ', 2 )\n 'abc '\n > var out = ltrimN( '!!!abc!!!', 2, '!' )\n '!abc!!!'\n\n See Also\n --------\n rtrimN, trim","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common male first names.\n\n Examples\n --------\n > var list = MALE_FIRST_NAMES_EN()\n [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. 'Moby Word II.' .\n\n See Also\n --------\n FEMALE_FIRST_NAMES_EN\n","map":"\nmap( arr, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = map( arr, f )\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = map( arr, f );\n > var v = out.get( 1, 1 )\n 5\n\n\nmap.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n mapRight, reduce\n","map.assign":"\nmap.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n mapRight, reduce","map2":"\nmap2( x, y, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to a new array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Input arrays must be either both array-like objects or both ndarray-like\n objects.\n\n If input arrays are array-like objects, the arrays must have the same number\n of elements.\n\n If input arrays are ndarray-like objects, the arrays must be broadcast\n compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = map2( x, y, f )\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > x = array( x, { 'shape': [ 2, 3 ] } );\n > y = array( y, { 'shape': [ 2, 3 ] } );\n > out = map2( x, y, f );\n > var v = out.get( 1, 1 )\n 6\n\n\nmap2.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n map\n","map2.assign":"\nmap2.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n map","map2d":"\nmap2d( arr, fcn[, thisArg] )\n Applies a function to each nested element in an array of arrays and assigns\n the result to a nested element in a new array of arrays.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array of arrays.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\n > var out = map2d( arr, f );\n > out[ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map3d, map4d, map5d, reduce2d\n","map2Right":"\nmap2Right( x, y, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to a new array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Input arrays must be either both array-like objects or both ndarray-like\n objects.\n\n If input arrays are array-like objects, the arrays must have the same number\n of elements.\n\n If input arrays are ndarray-like objects, the arrays must be broadcast\n compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = map2Right( x, y, f )\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > x = array( x, { 'shape': [ 2, 3 ] } );\n > y = array( y, { 'shape': [ 2, 3 ] } );\n > out = map2Right( x, y, f );\n > var v = out.get( 1, 1 )\n 6\n\n\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2Right.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2Right.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n mapRight, map2\n","map2Right.assign":"\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2Right.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2Right.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n mapRight, map2","map3d":"\nmap3d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a three-dimensional nested\n array and assigns the result to a nested element in a new three-dimensional\n nested array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject>\n Input three-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>\n Three-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\n > var out = map3d( arr, f );\n > out[ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map4d, map5d\n","map4d":"\nmap4d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a four-dimensional nested array\n and assigns the result to a nested element in a new four-dimensional nested\n array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input four-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>>\n Four-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\n > var out = map4d( arr, f );\n > out[ 0 ][ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map3d, map5d\n","map5d":"\nmap5d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a five-dimensional nested array\n and assigns the result to a nested element in a new five-dimensional nested\n array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input five-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>>>\n Five-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\n > var out = map5d( arr, f );\n > out[ 0 ][ 0 ][ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ][ 0 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map3d, map4d\n","mapArguments":"\nmapArguments( fcn, clbk[, thisArg] )\n Returns a function that applies arguments to a provided function after\n transforming arguments according to a callback function.\n\n The callback function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > function clbk( v ) { return v * 2; };\n > var bar = mapArguments( foo, clbk );\n > var out = bar( 1, 2, 3 )\n [ 2, 4, 6 ]\n\n See Also\n --------\n filterArguments\n","mapFun":"\nmapFun( fcn, n[, thisArg] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n The invoked function is provided a single argument: the invocation index\n (zero-based).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n thisArg: any (optional)\n Function execution context.\n\n Returns\n -------\n out: Array\n Array of accumulated function return values.\n\n Examples\n --------\n > function fcn( i ) { return i; };\n > var arr = mapFun( fcn, 5 )\n [ 0, 1, 2, 3, 4 ]\n\n See Also\n --------\n mapFunAsync\n","mapFunAsync":"\nmapFunAsync( fcn, n, [options,] done )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n For each iteration, the provided function is invoked with two arguments:\n\n - index: invocation index (starting from zero).\n - next: callback to be invoked upon function completion.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: function result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n done: Function\n A callback invoked upon executing a provided function `n` times or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > mapFunAsync( fcn, 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Limit number of concurrent invocations:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'limit': 2 };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Sequential invocation:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'series': true };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun","mapKeys":"\nmapKeys( obj, transform )\n Maps keys from one object to a new object having the same values.\n\n The transform function is provided three arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n\n The value returned by a transform function should be a value which can be\n serialized as an object key.\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values specify the keys of the output object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapKeys( obj, transform )\n { 'a1': 1, 'b2': 2 }\n\n See Also\n --------\n mapValues\n","mapKeysAsync":"\nmapKeysAsync( obj, [options,] transform, done )\n Maps keys from one object to a new object having the same values.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n - next: a callback to be invoked after processing an object `key`.\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - key\n - next\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - key\n - value\n - next\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - key: transformed key.\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The key returned by a transform function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapKeysAsync( obj, transform, done )\n { 'a:1': 1, 'b:2': 2 }\n\n // Limit number of concurrent invocations:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n // Process sequentially:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync","mapReduce":"\nmapReduce( arr, initial, mapper, reducer[, thisArg] )\n Performs a map-reduce operation for each element in an array and returns the\n accumulated result.\n\n When invoked, the mapping function is provided three arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n When invoked, the reducing function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: result after applying the mapping function to the current array\n element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a single-pass map-reduce\n operation over the entire input ndarray (i.e., higher-order ndarray\n dimensions are flattened to a single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n mapper: Function\n Mapping function.\n\n reducer: Function\n Reducing function.\n\n thisArg: any (optional)\n Execution context for the reducing function.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f1 = naryFunction( base.abs, 1 );\n > var f2 = naryFunction( base.add, 2 );\n > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n > var out = mapReduce( arr, 0.0, f1, f2 )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapReduce( arr, 0.0, f1, f2 )\n 21.0\n\n See Also\n --------\n map, mapReduceRight, reduce\n","mapReduceRight":"\nmapReduceRight( arr, initial, mapper, reducer[, thisArg] )\n Performs a map-reduce operation for each element in an array while iterating\n from right to left and returns the accumulated result.\n\n When invoked, the mapping function is provided three arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n When invoked, the reducing function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: result after applying the mapping function to the current array\n element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a single-pass map-reduce\n operation over the entire input ndarray (i.e., higher-order ndarray\n dimensions are flattened to a single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n mapper: Function\n Mapping function.\n\n reducer: Function\n Reducing function.\n\n thisArg: any (optional)\n Execution context for the reducing function.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f1 = naryFunction( base.abs, 1 );\n > var f2 = naryFunction( base.add, 2 );\n > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n > var out = mapReduceRight( arr, 0.0, f1, f2 )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapReduceRight( arr, 0.0, f1, f2 )\n 21.0\n\n See Also\n --------\n mapRight, mapReduce, reduceRight\n","mapRight":"\nmapRight( arr, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = mapRight( arr, f )\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapRight( arr, f );\n > var v = out.get( 1, 1 )\n 5\n\n\nmapRight.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > mapRight.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > mapRight.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n map, reduce\n","mapRight.assign":"\nmapRight.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > mapRight.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > mapRight.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n map, reduce","mapValues":"\nmapValues( obj, transform )\n Maps values from one object to a new object having the same keys.\n\n The transform function is provided three arguments:\n\n - value: object value corresponding to `key`.\n - key: object key.\n - obj: the input object.\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( value, key ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapValues( obj, transform )\n { 'a': 'a1', 'b': 'b2' }\n\n See Also\n --------\n mapKeys, omitBy, pickBy\n","mapValuesAsync":"\nmapValuesAsync( obj, [options,] transform, done )\n Maps values from one object to a new object having the same keys.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - value: object value corresponding to `key`.\n - key: object key.\n - obj: the input object.\n - next: a callback to be invoked after processing an object `value`.\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - value\n - next\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - value\n - key\n - next\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - value: transformed value.\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapValuesAsync( obj, transform, done )\n { 'a': 'a:1', 'b': 'b:2' }\n\n // Limit number of concurrent invocations:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n // Process sequentially:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues","maskArguments":"\nmaskArguments( fcn, mask[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a specified mask.\n\n Only those arguments having a truthy mask value are applied to a provided\n function.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n mask: ArrayLikeObject\n Mask array.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > var bar = maskArguments( foo, [ 1, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n filterArguments, rejectArguments, reorderArguments, reverseArguments\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n\n Examples\n --------\n > MAX_ARRAY_LENGTH\n 4294967295\n\n See Also\n --------\n MAX_TYPED_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n\n Examples\n --------\n > MAX_TYPED_ARRAY_LENGTH\n 9007199254740991\n\n See Also\n --------\n MAX_ARRAY_LENGTH\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x, shape )\n Broadcasts an ndarray to a specified shape if and only if the specified\n shape differs from the provided ndarray's shape.\n\n If a provided ndarray has the same shape as the specified shape, the\n function returns the provided ndarray.\n\n If a provided ndarray has a different (broadcast compatible) shape than the\n specified shape, the function returns a new *read-only* ndarray view of the\n provided ndarray's data. The view is typically *not* contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to the input ndarray may affect multiple elements. If you need to\n write to the input ndarray, copy the input ndarray before broadcasting.\n\n The function throws an error if a provided ndarray is incompatible with a\n provided shape.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n shape: ArrayLikeObject\n Desired shape.\n\n Returns\n -------\n out: ndarray\n Broadcasted array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\n \n > sh = y.shape\n [ 3, 2, 2 ]\n > var v = y.get( 0, 0, 0 )\n 1\n > v = y.get( 0, 0, 1 )\n 2\n > v = y.get( 0, 1, 0 )\n 3\n > v = y.get( 0, 1, 1 )\n 4\n > v = y.get( 1, 0, 0 )\n 1\n > v = y.get( 1, 1, 0 )\n 3\n > v = y.get( 2, 0, 0 )\n 1\n > v = y.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, ndarray, broadcastArray, maybeBroadcastArrays\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays )\n Broadcasts ndarrays to a common shape.\n\n The function supports two (mutually exclusive) means of providing ndarray\n arguments:\n\n 1. Providing a single array containing ndarray arguments.\n 2. Providing ndarray arguments as separate arguments.\n\n If a provided ndarray has a shape matching the common shape, the function\n returns the provided ndarray.\n\n If a provided ndarray has a different (broadcast compatible) shape than the\n common shape, the function returns a new *read-only* ndarray view of the\n provided ndarray's data. The view is typically *not* contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to a view may affect multiple elements. If you need to write to an\n input ndarray, copy the input ndarray before broadcasting.\n\n The function throws an error if a provided broadcast-incompatible ndarrays.\n\n Parameters\n ----------\n arrays: ...ndarray|ArrayLikeObject\n Array arguments.\n\n Returns\n -------\n out: Array\n Broadcasted arrays.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = ndzeros( [ 3, 2, 2 ] )\n \n > var out = maybeBroadcastArrays( [ x, y ] )\n [ , ]\n\n // Retrieve the broadcasted \"x\" array:\n > var bx = out[ 0 ]\n \n > sh = bx.shape\n [ 3, 2, 2 ]\n\n // Retrieve broadcasted elements...\n > var v = bx.get( 0, 0, 0 )\n 1\n > v = bx.get( 0, 0, 1 )\n 2\n > v = bx.get( 0, 1, 0 )\n 3\n > v = bx.get( 0, 1, 1 )\n 4\n > v = bx.get( 1, 0, 0 )\n 1\n > v = bx.get( 1, 1, 0 )\n 3\n > v = bx.get( 2, 0, 0 )\n 1\n > v = bx.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, ndarray, broadcastArrays, maybeBroadcastArray\n","memoize":"\nmemoize( fcn[, hashFunction] )\n Returns a memoized function.\n\n The function does not set the `length` property of the returned function.\n Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n The function serializes provided arguments as a string and stores results\n using the string as an identifier. To use a custom hash function, provide a\n hash function argument.\n\n Parameters\n ----------\n fcn: Function\n Function to memoize.\n\n hashFunction: Function (optional)\n Function to map a set of arguments to a single value identifying that\n set.\n\n Returns\n -------\n out: Function\n Memoized function.\n\n Examples\n --------\n > function factorial( n ) {\n ... var prod;\n ... var i;\n ... prod = 1;\n ... for ( i = n; i > 1; i-- ) {\n ... prod *= i;\n ... }\n ... return prod;\n ... };\n > var memoized = memoize( factorial );\n > var v = memoized( 5 )\n 120\n > v = memoized( 5 )\n 120\n\n","merge":"\nmerge( target, ...source )\n Merges objects into a target object.\n\n The target object is mutated.\n\n Only plain objects are merged and extended. Other values/types are either\n deep copied or assigned.\n\n Support for deep merging class instances is inherently fragile.\n\n `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n Functions are not deep copied.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n source: ...Object\n Source objects (i.e., objects to be merged into the target object).\n\n Returns\n -------\n out: Object\n Merged (target) object.\n\n Examples\n --------\n > var target = { 'a': 'beep' };\n > var source = { 'a': 'boop', 'b': 'bap' };\n > var out = merge( target, source )\n { 'a': 'boop', 'b': 'bap' }\n > var bool = ( out === target )\n true\n\n\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy\n","merge.factory":"\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var ms = days * MILLISECONDS_IN_DAY\n 271296000\n\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var ms = hrs * MILLISECONDS_IN_HOUR\n 11304000\n\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var ms = mins * MILLISECONDS_IN_MINUTE\n 188400\n\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var secs = 3.14;\n > var ms = secs * MILLISECONDS_IN_SECOND\n 3140\n\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var weeks = 3.14;\n > var ms = weeks * MILLISECONDS_IN_WEEK\n 1899072000\n\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n\n Data includes the following:\n\n - army: army size.\n - cities: cities.\n - labels: map labels.\n - temperature: temperature during the army's return from Russia.\n - rivers: river data.\n\n Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n to convert to Celsius.\n\n River data is formatted as GeoJSON.\n\n River data is incomplete, with portions of rivers missing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n Minard's data.\n\n Examples\n --------\n > var data = MINARD_NAPOLEONS_MARCH();\n > var army = data.army\n [...]\n > var cities = data.cities\n [...]\n > var labels = data.labels\n [...]\n > var rivers = data.rivers\n {...}\n > var t = data.temperature\n [...]\n\n References\n ----------\n - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n Ecole nationale des ponts et chaussées.\n - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n York. doi:10.1007/0-387-28695-0.\n\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var mins = days * MINUTES_IN_DAY\n 4521.6\n\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var mins = hrs * MINUTES_IN_HOUR\n 188.4\n\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var mins = wks * MINUTES_IN_WEEK\n 31651.2\n\n","minutesInMonth":"\nminutesInMonth( [month[, year]] )\n Returns the number of minutes in a month.\n\n By default, the function returns the number of minutes in the current month\n of the current year (according to local time). To determine the number of\n minutes for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Minutes in a month.\n\n Examples\n --------\n > var num = minutesInMonth()\n \n > num = minutesInMonth( 2 )\n \n > num = minutesInMonth( 2, 2016 )\n 41760\n > num = minutesInMonth( 2, 2017 )\n 40320\n\n // Other ways to supply month:\n > num = minutesInMonth( 'feb', 2016 )\n 41760\n > num = minutesInMonth( 'february', 2016 )\n 41760\n\n See Also\n --------\n minutesInYear\n","minutesInYear":"\nminutesInYear( [value] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n\n By default, the function returns the number of minutes in the current year\n (according to local time). To determine the number of minutes for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of minutes in a year.\n\n Examples\n --------\n > var num = minutesInYear()\n \n > num = minutesInYear( 2016 )\n 527040\n > num = minutesInYear( 2017 )\n 525600\n\n See Also\n --------\n minutesInMonth\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n\n Each array element has the following fields:\n\n - chapter: book chapter (number or identifier).\n - title: chapter title (if available; otherwise, empty).\n - text: chapter text.\n\n Returns\n -------\n out: Array\n Book text.\n\n Examples\n --------\n > var data = MOBY_DICK()\n [ {...}, {...}, ... ]\n\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n\n Returns\n -------\n out: Array\n List of month names.\n\n Examples\n --------\n > var list = MONTH_NAMES_EN()\n [ 'January', 'February', 'March', 'April', ... ]\n\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var yrs = 3.14;\n > var mons = yrs * MONTHS_IN_YEAR\n 37.68\n\n","moveProperty":"\nmoveProperty( source, prop, target )\n Moves a property from one object to another object.\n\n The property is deleted from the source object and the property's descriptor\n is preserved during transfer.\n\n If a source property is not configurable, the function throws an error, as\n the property cannot be deleted from the source object.\n\n Parameters\n ----------\n source: Object\n Source object.\n\n prop: string\n Property to move.\n\n target: Object\n Target object.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether operation was successful.\n\n Examples\n --------\n > var obj1 = { 'a': 'b' };\n > var obj2 = {};\n > var bool = moveProperty( obj1, 'a', obj2 )\n true\n > bool = moveProperty( obj1, 'c', obj2 )\n false\n\n","MultiSlice":"\nMultiSlice( ...slice )\n Returns a multi-slice.\n\n Parameters\n ----------\n ...slice: Slice|integer|null|undefined\n Slice arguments.\n\n Returns\n -------\n s: MultiSlice\n MultiSlice instance.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n\n\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n\n Returns\n -------\n ndims: integer\n Number of slice dimensions.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.ndims\n 3\n\n\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n\n Returns\n -------\n data: Array\n Slice data.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.data\n [ 2, , 1 ]\n\n\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n\n Returns\n -------\n str: string\n Serialized multi-slice string.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.toString()\n 'MultiSlice(2,Slice(2,10,null),1)'\n\n\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 2, 10, 1 );\n > var ms = new MultiSlice( 2, s );\n > ms.toJSON()\n {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n See Also\n --------\n ndarray, Slice\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n\n Returns\n -------\n ndims: integer\n Number of slice dimensions.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.ndims\n 3","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n\n Returns\n -------\n data: Array\n Slice data.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.data\n [ 2, , 1 ]","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n\n Returns\n -------\n str: string\n Serialized multi-slice string.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.toString()\n 'MultiSlice(2,Slice(2,10,null),1)'","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 2, 10, 1 );\n > var ms = new MultiSlice( 2, s );\n > ms.toJSON()\n {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n See Also\n --------\n ndarray, Slice","namedtypedtuple":"\nnamedtypedtuple( fields[, options] )\n Returns a named typed tuple factory.\n\n Named tuples assign a property name, and thus a meaning, to each position in\n a tuple and allow for more readable, self-documenting code.\n\n Named typed tuples can be used wherever typed arrays are used, with the\n added benefit that they allow accessing fields by both field name and\n position index.\n\n Named typed tuples may be one the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n fields: Array\n Field (property) names.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Default tuple data type. If a data type is not provided to a named typed\n tuple factory, this option specifies the underlying tuple data type.\n Default: 'float64'.\n\n options.name: string (optional)\n Tuple name. Default: 'tuple'.\n\n Returns\n -------\n factory: Function\n Named typed tuple factory.\n\n Examples\n --------\n > var opts = {};\n > opts.name = 'Point';\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var tuple = factory();\n\n\nfactory()\n Returns a named typed tuple of the default data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory();\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory( dtype )\n Returns a named typed tuple of the specified data type.\n\n Parameters\n ----------\n dtype: string\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( 'int32' );\n > p.x\n 0\n > p.y\n 0\n > p[ 0 ]\n 0\n > p[ 1 ]\n 0\n\n\nfactory( typedarray[, dtype] )\n Creates a named typed tuple from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a named typed tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var f = namedtypedtuple( [ 'x', 'y' ] );\n > var p = f( new Float64Array( [ 1.0, -1.0 ] ) );\n > p.x\n 1.0\n > p.y\n -1.0\n > p[ 0 ]\n 1.0\n > p[ 1 ]\n -1.0\n\n\nfactory( obj[, dtype] )\n Creates a named typed tuple from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a named typed\n tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( [ 1, -1 ], 'int32' );\n > p.x\n 1\n > p.y\n -1\n > p[ 0 ]\n 1\n > p[ 1 ]\n -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n Returns a named typed tuple view of an ArrayBuffer.\n\n The view length equals the number of tuple fields.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first tuple element.\n Default: 0.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var buf = new ArrayBuffer( 16 );\n > var p = factory( buf, 4, 'float32' );\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n Creates a new named typed tuple from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n - field: tuple field.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of tuple elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > function mapFcn( v ) { return v * 2.0; };\n > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n Creates a new named typed tuple from an object containing tuple fields.\n\n A callback is provided the following arguments:\n\n - value: source object tuple field value.\n - field: source object tuple field name.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n map: Function (optional)\n Callback to invoke for each source object tuple field.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.of( element0[, element1[, ...elementN]] )\n Creates a new named typed tuple from a variable number of arguments.\n\n The number of arguments *must* equal the number of tuple fields.\n\n Parameters\n ----------\n element0: number\n Tuple element.\n\n element1: number (optional)\n Tuple element.\n\n elementN: ...number (optional)\n Tuple elements.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.of( 2.0, -2.0 );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n Size (in bytes) of each tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.BYTES_PER_ELEMENT\n 8\n\n\ntuple.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.buffer\n \n\n\ntuple.byteLength\n Length (in bytes) of the tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteLength\n 16\n\n\ntuple.byteOffset\n Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteOffset\n 0\n\n\ntuple.length\n Tuple length (i.e., number of elements).\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.length\n 2\n\n\ntuple.name\n Tuple name.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.name\n 'Point'\n\n\ntuple.fields\n Returns the list of tuple fields.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fields\n [ 'x', 'y' ]\n\n\ntuple.orderedFields\n Returns the list of tuple fields in index order.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.sort();\n > p[ 0 ]\n -1.0\n > p.fields\n [ 'x', 'y' ]\n > p.orderedFields\n [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n Copies a sequence of elements within the tuple starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > p.copyWithin( 3, 0, 2 );\n > p.w\n 2.0\n > p.v\n -2.0\n\n\ntuple.entries()\n Returns an iterator for iterating over tuple key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple key-value pairs.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.entries();\n > it.next().value\n [ 0, 'x', 1.0 ]\n > it.next().value\n [ 1, 'y', -1.0 ]\n > it.next().done\n true\n\n\ntuple.every( predicate[, thisArg] )\n Tests whether all tuple elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all tuple elements pass.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > p.every( predicate )\n false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n Returns the field of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var f = p.fieldOf( 2.0 )\n undefined\n > f = p.fieldOf( -1.0 )\n 'z'\n\n\ntuple.fill( value[, start[, end]] )\n Fills a tuple from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last tuple element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fill( 2.0 );\n > p.x\n 2.0\n > p.y\n 2.0\n\n\ntuple.filter( predicate[, thisArg] )\n Creates a new tuple which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n If a predicate function does not return a truthy value for any tuple\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters tuple elements. If a predicate function\n returns a truthy value, a tuple element is included in the output tuple;\n otherwise, a tuple element is not included in the output tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var p2 = p1.filter( predicate );\n > p2.fields\n [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n Returns the first tuple element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = p.find( predicate )\n -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n Returns the field of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var f = p.findField( predicate )\n 'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n Returns the index of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = p.findIndex( predicate )\n 2\n\n\ntuple.forEach( fcn[, thisArg] )\n Invokes a callback for each tuple element.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each tuple element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > var str = ' ';\n > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n > p.forEach( fcn );\n > str\n ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether a tuple includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a tuple includes a search element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var bool = p.includes( 2.0 )\n false\n > bool = p.includes( -1.0 )\n true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n Returns the index of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var idx = p.indexOf( 2.0 )\n -1\n > idx = p.indexOf( -1.0 )\n 2\n\n\ntuple.ind2key( ind )\n Converts a tuple index to a field name.\n\n If provided an out-of-bounds index, the method returns `undefined`.\n\n Parameters\n ----------\n ind: integer\n Tuple index. If less than zero, the method resolves the index relative\n to the last tuple element.\n\n Returns\n -------\n field: string|undefined\n Field name.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.ind2key( 1 )\n 'y'\n > p.ind2key( 100 )\n undefined\n\n\ntuple.join( [separator] )\n Serializes a tuple by joining all tuple elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating tuple elements. Default: ','.\n\n Returns\n -------\n str: string\n Tuple serialized as a string.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > p.join( '|' )\n '1|0|-1'\n\n\ntuple.keys()\n Returns an iterator for iterating over tuple keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple keys.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.keys();\n > it.next().value\n [ 0, 'x' ]\n > it.next().value\n [ 1, 'y' ]\n > it.next().done\n true\n\n\ntuple.key2ind( field )\n Converts a field name to a tuple index.\n\n If provided an unknown field name, the method returns `-1`.\n\n Parameters\n ----------\n field: string\n Tuple field name.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.key2ind( 'y' )\n 1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n Returns the field of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var f = p.lastFieldOf( 2.0 )\n undefined\n > f = p.lastFieldOf( 0.0 )\n 'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = p.lastIndexOf( 2.0 )\n -1\n > idx = p.lastIndexOf( 0.0 )\n 3\n\n\ntuple.map( fcn[, thisArg] )\n Maps each tuple element to an element in a new tuple.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n Parameters\n ----------\n fcn: Function\n Function which maps tuple elements to elements in the new tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var p2 = p1.map( fcn );\n > p2.x\n 2.0\n > p2.y\n 0.0\n > p2.z\n -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first tuple element as the first argument and the second tuple\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduce( fcn, 0.0 )\n 2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last tuple element as the first argument and the second-to-last\n tuple element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduceRight( fcn, 0.0 )\n 2.0\n\n\ntuple.reverse()\n Reverses a tuple *in-place*.\n\n This method mutates the tuple on which the method is invoked.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.x\n 1.0\n > p.reverse();\n > p[ 0 ]\n -1.0\n > p.x\n 1.0\n\n\ntuple.set( arr[, offset] )\n Sets tuple elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing tuple values to set.\n\n offset: integer (optional)\n Tuple index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 1 ]\n 0.0\n > p.y\n 0.0\n > p.set( [ -2.0, 2.0 ], 1 );\n > p[ 1 ]\n -2.0\n > p.y\n -2.0\n > p[ 2 ]\n 2.0\n > p.z\n 2.0\n\n\ntuple.slice( [begin[, end]] )\n Copies tuple elements to a new tuple with the same underlying data type as\n the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > p1.fields\n [ 'x', 'y', 'z' ]\n > var p2 = p1.slice( 1 );\n > p2.fields\n [ 'y', 'z' ]\n > p2.y\n 0.0\n > p2.z\n -1.0\n\n\ntuple.some( predicate[, thisArg] )\n Tests whether at least one tuple element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one tuple element passes.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > p.some( predicate )\n true\n\n\ntuple.sort( [compareFunction] )\n Sorts a tuple *in-place*.\n\n Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n before and after sorting will always return the same tuple element. However,\n this behavior is generally not true when accessing tuple elements according\n to tuple index. In summary, sorting affects index order but not field\n assignments.\n\n The comparison function is provided two tuple elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the tuple on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > p.sort();\n > p.orderedFields\n [ 'v', 'y', 'z', 'x', 'w' ]\n > p[ 0 ]\n -2.0\n > p[ 1 ]\n -1.0\n > p.y\n -1.0\n > p.key2ind( 'x' )\n 3\n > p[ 3 ]\n 1.0\n\n\ntuple.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n arr: TypedArray\n A new typed array view.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr = p.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n > arr.length\n 3\n\n\ntuple.subtuple( [begin[, end]] )\n Creates a new named typed tuple over the same underlying ArrayBuffer and\n with the same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var p2 = p1.subtuple( 2 );\n > p2.fields\n [ 'z', 'w', 'v' ]\n > p2[ 0 ]\n 0.0\n > p2.z\n 0.0\n > p2[ 1 ]\n 2.0\n > p2.w\n 2.0\n > p2[ 2 ]\n -2.0\n > p2.v\n -2.0\n > p2.length\n 3\n\n\ntuple.toJSON()\n Serializes a tuple as JSON.\n\n Returns\n -------\n obj: Object\n A tuple JSON representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toJSON()\n { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n Serializes a tuple as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n > p.toLocaleString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.toString()\n Serializes a tuple as a string.\n\n Returns\n -------\n str: string\n A tuple string representation.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n Returns an iterator for iterating over tuple elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple elements.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n See Also\n --------\n typedarray\n","NAN":"\nNAN\n Double-precision floating-point NaN.\n\n Examples\n --------\n > NAN\n NaN\n\n See Also\n --------\n FLOAT32_NAN\n","naryFunction":"\nnaryFunction( fcn, arity[, thisArg] )\n Returns a function that applies a specified number of arguments to a\n provided function.\n\n The returned function *always* invokes the wrapped function with a specified\n number of arguments, even when the returned function is provided fewer\n arguments.\n\n The value for the missing arguments is equal to `undefined`.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n arity: integer\n Number of arguments.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = naryFunction( foo, 2 );\n > var out = bar( 1, 2, 3 )\n [ 1, 2, undefined ]\n\n See Also\n --------\n maskArguments, pickArguments\n","nativeClass":"\nnativeClass( value )\n Returns a string value indicating a specification defined classification of\n an object.\n\n The function is *not* robust for ES2015+ environments. In ES2015+,\n `Symbol.toStringTag` allows overriding the default description of an object.\n While measures are taken to uncover the default description, such measures\n can be thwarted. While this function remains useful for type-checking, be\n aware that value impersonation is possible. Where possible, prefer functions\n tailored to checking for particular value types, as specialized functions\n are better equipped to address `Symbol.toStringTag`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n String value indicating a specification defined classification of the\n input value.\n\n Examples\n --------\n > var str = nativeClass( 'a' )\n '[object String]'\n > str = nativeClass( 5 )\n '[object Number]'\n > function Beep(){};\n > str = nativeClass( new Beep() )\n '[object Object]'\n\n See Also\n --------\n constructorName, typeOf\n","ndarray":"\nndarray( dtype, buffer, shape, strides, offset, order[, options] )\n Returns an ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n ndarray: ndarray\n ndarray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nndarray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, FancyArray\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","ndarray.prototype.data":"\nndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","ndarray.prototype.flags":"\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","ndarray.prototype.length":"\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","ndarray.prototype.offset":"\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","ndarray.prototype.order":"\nndarray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","ndarray.prototype.shape":"\nndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","ndarray.prototype.strides":"\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","ndarray.prototype.get":"\nndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","ndarray.prototype.iget":"\nndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","ndarray.prototype.set":"\nndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","ndarray.prototype.iset":"\nndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","ndarray.prototype.toString":"\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, FancyArray","ndarray2array":"\nndarray2array( x )\n Converts an ndarray to a generic array.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: Array|Array\n Generic array (which may include nested arrays).\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarray2array( arr )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n array, ndarray, ndarray2json\n","ndarray2fancy":"\nndarray2fancy( x[, options] )\n Converts an ndarray to an object supporting fancy indexing.\n\n An ndarray supporting fancy indexing is an ndarray which supports slicing\n via indexing expressions for both retrieval and assignment.\n\n A fancy ndarray can be consumed by any API which supports ndarray instances.\n\n A fancy ndarray shares the *same* data as the provided input ndarray. Hence,\n any mutations to the returned ndarray will affect the underlying input\n ndarray and vice versa.\n\n A fancy ndarray supports indexing using positive and negative integers (both\n numeric literals and strings), Slice and MultiSlice instances, subsequence\n expressions, mask ndarrays, boolean ndarrays, and integer ndarrays.\n\n A fancy ndarray supports all properties and methods of the input ndarray,\n and, thus, a fancy ndarray can be consumed by any API which supports\n ndarray-like objects.\n\n For operations returning a new ndarray (e.g., when slicing or invoking an\n instance method), a fancy ndarray returns a new fancy ndarray having the\n same configuration as specified by provided options.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on ndarray views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use and\n scripting. For performance critical applications, prefer equivalent\n functional APIs supporting ndarray instances.\n\n Fancy ndarrays support broadcasting in which assigned scalars and ndarrays\n are repeated (without additional memory allocation) to match the dimensions\n of a target ndarray instance.\n\n When assigning ndarrays to slices, the ndarray on the right-hand-side must\n be broadcast-compatible with dimensions implied by the slice.\n\n Fancy ndarrays support (mostly) safe casts (i.e., any cast which can be\n performed without overflow or loss of precision, with the exception of\n floating-point ndarrays which are also allowed to downcast from higher\n precision to lower precision).\n\n When attempting to perform an unsafe cast, fancy ndarrays will raise an\n exception.\n\n When assigning a real-valued scalar to a complex number ndarray, a fancy\n ndarray will cast the real-valued scalar to a complex number argument having\n an imaginary component equal to zero.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n out: ndarray\n Output ndarray supporting fancy indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Convert to a fancy ndarray:\n > var arr = ndarray2fancy( x );\n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nndarray2fancy.factory( [options] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an ndarray to an object supporting fancy\n indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Create a function for converting ndarrays to fancy ndarrays:\n > var f = ndarray2fancy.factory();\n\n // Convert the normal ndarray to a fancy ndarray:\n > var y = f( x );\n\n\nndarray2fancy.idx( x[, options] )\n Wraps a provided ndarray as an ndarray index object.\n\n For documentation and usage, see `ndindex`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndarrayIndex\n ndarray index instance.\n\n Examples\n --------\n > var opts = { 'dtype': 'int32' };\n > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n > var arr = array( buf, opts );\n > var idx = ndarray2fancy.idx( arr );\n\n See Also\n --------\n array2fancy, array, ndarray, FancyArray\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an ndarray to an object supporting fancy\n indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Create a function for converting ndarrays to fancy ndarrays:\n > var f = ndarray2fancy.factory();\n\n // Convert the normal ndarray to a fancy ndarray:\n > var y = f( x );","ndarray2fancy.idx":"\nndarray2fancy.idx( x[, options] )\n Wraps a provided ndarray as an ndarray index object.\n\n For documentation and usage, see `ndindex`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndarrayIndex\n ndarray index instance.\n\n Examples\n --------\n > var opts = { 'dtype': 'int32' };\n > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n > var arr = array( buf, opts );\n > var idx = ndarray2fancy.idx( arr );\n\n See Also\n --------\n array2fancy, array, ndarray, FancyArray","ndarray2json":"\nndarray2json( x )\n Serializes an ndarray as a JSON object.\n\n This function does *not* serialize data outside of the buffer region defined\n by the ndarray view.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Object\n JSON object.\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarray2json( arr )\n {...}\n\n See Also\n --------\n array, ndarray, ndarray2array\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n\n The output array contains the following modes:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'mostly-safe': allow \"safe\" casts and, for floating-point data types,\n downcasts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers and\n floats).\n\n Returns\n -------\n out: Array\n List of ndarray casting modes.\n\n Examples\n --------\n > var out = ndarrayCastingModes()\n [ 'none', 'equiv', 'safe', 'mostly-safe', 'same-kind', 'unsafe' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x )\n Returns the underlying data buffer of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: ArrayLikeObject\n Underlying data buffer.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n \n\n See Also\n --------\n array, ndarray, ndarrayDataType\n","ndarrayDataType":"\nndarrayDataType( x )\n Returns the data type of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n dt: string\n Data type.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n 'float64'\n\n See Also\n --------\n array, ndarray, ndarrayDataTypes\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind] )\n Returns a list of ndarray data types.\n\n When not provided a data type \"kind\", the function returns an array\n containing the following data types:\n\n - float16: half-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex32: half-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int8: signed 8-bit integers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - binary: binary.\n\n The function supports the following data type \"kinds\":\n\n - floating_point: floating-point data types.\n - real_floating_point: real-valued floating-point data types.\n - complex_floating_point: complex-valued floating-point data types.\n - boolean: boolean data types.\n - integer: integer data types.\n - signed_integer: signed integer data types.\n - unsigned_integer: unsigned integer data types.\n - real: real-valued data types.\n - numeric: numeric data types.\n - typed: typed data types.\n - integer_index: integer index data types.\n - boolean_index: boolean index data types.\n - mask_index: mask index data types.\n - typed_index: typed index data types.\n - index: index data types.\n - all: all data types.\n\n Additionally, the function supports extending the \"kinds\" listed above by\n appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n Parameters\n ----------\n kind: string (optional)\n Data type kind.\n\n Returns\n -------\n out: Array\n List of ndarray data types.\n\n Examples\n --------\n > var out = ndarrayDataTypes()\n [...]\n > out = ndarrayDataTypes( 'floating_point' )\n [...]\n > out = ndarrayDataTypes( 'floating_point_and_generic' )\n [...]\n\n\nndarrayDataTypes.binary\n Read-only property returning a data type instance representing a binary data\n type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.binary\n \n\n\nndarrayDataTypes.boolean\n Read-only property returning a data type instance representing a boolean\n data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.boolean\n \n\n\nndarrayDataTypes.complex32\n Read-only property returning a data type instance representing a half-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex32\n \n\n\nndarrayDataTypes.complex64\n Read-only property returning a data type instance representing a single-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex64\n \n\n\nndarrayDataTypes.complex128\n Read-only property returning a data type instance representing a double-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex128\n \n\n\nndarrayDataTypes.float16\n Read-only property returning a data type instance representing a half-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float16\n \n\n\nndarrayDataTypes.float32\n Read-only property returning a data type instance representing a single-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float32\n \n\n\nndarrayDataTypes.float64\n Read-only property returning a data type instance representing a double-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float64\n \n\n\nndarrayDataTypes.generic\n Read-only property returning a data type instance representing a \"generic\"\n data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.generic\n \n\n\nndarrayDataTypes.int8\n Read-only property returning a data type instance representing a signed\n 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int8\n \n\n\nndarrayDataTypes.int16\n Read-only property returning a data type instance representing a signed\n 16-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int16\n \n\n\nndarrayDataTypes.int32\n Read-only property returning a data type instance representing a signed\n 32-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int32\n \n\n\nndarrayDataTypes.uint8\n Read-only property returning a data type instance representing an unsigned\n 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint8\n \n\n\nndarrayDataTypes.uint8c\n Read-only property returning a data type instance representing an unsigned\n clamped 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint8c\n \n\n\nndarrayDataTypes.uint16\n Read-only property returning a data type instance representing an unsigned\n 16-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint16\n \n\n\nndarrayDataTypes.uint32\n Read-only property returning a data type instance representing an unsigned\n 32-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint32\n \n\n See Also\n --------\n arrayDataTypes, array, ndarray, typedarrayDataTypes\n","ndarrayDataTypes.binary":"\nndarrayDataTypes.binary\n Read-only property returning a data type instance representing a binary data\n type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.binary\n ","ndarrayDataTypes.boolean":"\nndarrayDataTypes.boolean\n Read-only property returning a data type instance representing a boolean\n data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.boolean\n ","ndarrayDataTypes.complex32":"\nndarrayDataTypes.complex32\n Read-only property returning a data type instance representing a half-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex32\n ","ndarrayDataTypes.complex64":"\nndarrayDataTypes.complex64\n Read-only property returning a data type instance representing a single-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex64\n ","ndarrayDataTypes.complex128":"\nndarrayDataTypes.complex128\n Read-only property returning a data type instance representing a double-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex128\n ","ndarrayDataTypes.float16":"\nndarrayDataTypes.float16\n Read-only property returning a data type instance representing a half-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float16\n ","ndarrayDataTypes.float32":"\nndarrayDataTypes.float32\n Read-only property returning a data type instance representing a single-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float32\n ","ndarrayDataTypes.float64":"\nndarrayDataTypes.float64\n Read-only property returning a data type instance representing a double-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float64\n ","ndarrayDataTypes.generic":"\nndarrayDataTypes.generic\n Read-only property returning a data type instance representing a \"generic\"\n data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.generic\n ","ndarrayDataTypes.int8":"\nndarrayDataTypes.int8\n Read-only property returning a data type instance representing a signed\n 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int8\n ","ndarrayDataTypes.int16":"\nndarrayDataTypes.int16\n Read-only property returning a data type instance representing a signed\n 16-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int16\n ","ndarrayDataTypes.int32":"\nndarrayDataTypes.int32\n Read-only property returning a data type instance representing a signed\n 32-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int32\n ","ndarrayDataTypes.uint8":"\nndarrayDataTypes.uint8\n Read-only property returning a data type instance representing an unsigned\n 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint8\n ","ndarrayDataTypes.uint8c":"\nndarrayDataTypes.uint8c\n Read-only property returning a data type instance representing an unsigned\n clamped 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint8c\n ","ndarrayDataTypes.uint16":"\nndarrayDataTypes.uint16\n Read-only property returning a data type instance representing an unsigned\n 16-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint16\n ","ndarrayDataTypes.uint32":"\nndarrayDataTypes.uint32\n Read-only property returning a data type instance representing an unsigned\n 32-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint32\n \n\n See Also\n --------\n arrayDataTypes, array, ndarray, typedarrayDataTypes","ndarrayDispatch":"\nndarrayDispatch( fcns, types, data, nargs, nin, nout )\n Returns an ndarray function interface which performs multiple dispatch.\n\n An ndarray function interface has the following signature:\n\n f( x, y, ... )\n\n where\n\n - x: ndarray.\n - y: ndarray.\n - ...: additional ndarrays.\n\n The number of parameters is derived from `nargs`, the number of input\n ndarrays is derived from `nin`, and the number of output ndarrays is derived\n from `nout`.\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of ndarray functions. An ndarray function should have the following\n signature:\n\n f( arrays, data )\n\n where\n\n - arrays: array containing input and output ndarrays.\n - data: ndarray function data (e.g., a callback).\n\n For convenience, a single ndarray function may be provided which will be\n invoked whenever the ndarray argument data types match a sequence of\n types in `types`. Providing a single ndarray function is particularly\n convenient for the case where, regardless of array data types,\n traversing arrays remains the same, but the ndarray function `data`\n differs (e.g., callbacks which differ based on the array data types).\n\n types: ArrayLikeObject\n One-dimensional list of ndarray argument data types.\n\n data: ArrayLikeObject|null\n ndarray function data (e.g., callbacks). If `null`, a returned ndarray\n function interface does **not** provide a `data` argument to an invoked\n ndarray function.\n\n nargs: integer\n Total number of ndarray function interface arguments.\n\n nin: integer\n Number of input ndarrays.\n\n nout: integer\n Number of output ndarrays.\n\n Returns\n -------\n fcn: Function\n ndarray function interface.\n\n Examples\n --------\n // Define ndarray argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of ndarray function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create an ndarray function interface for applying unary callbacks:\n > var f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\n\n // Create an input ndarray:\n > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n // Create an output ndarray:\n > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n // Compute the element-wise absolute value:\n > f( x, y );\n > ybuf\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n array, ndarray\n","ndarrayFlag":"\nndarrayFlag( x, name )\n Returns a specified flag for a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n name: string|symbol\n Flag name.\n\n Returns\n -------\n out: any\n Flag value.\n\n Examples\n --------\n > var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n \n\n See Also\n --------\n array, ndarray, ndarrayFlags\n","ndarrayFlags":"\nndarrayFlags( x )\n Returns the flags of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Object\n Flags.\n\n Examples\n --------\n > var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n {...}\n\n See Also\n --------\n array, ndarray, ndarrayFlag\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n\n The output array contains the following modes:\n\n - throw: specifies that a function should throw an error when an index is\n outside a restricted interval.\n - normalize: specifies that a function should normalize negative indices and\n throw an error when an index is outside a restricted interval.\n - wrap: specifies that a function should wrap around an index using modulo\n arithmetic.\n - clamp: specifies that a function should set an index less than zero to\n zero (minimum index) and set an index greater than a maximum index value to\n the maximum possible index.\n\n Returns\n -------\n out: Array\n List of ndarray index modes.\n\n Examples\n --------\n > var out = ndarrayIndexModes()\n [ 'throw', 'normalize', 'clamp', 'wrap' ]\n\n See Also\n --------\n array, ndarray\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x[, options] )\n Converts an ndarray-like object to an ndarray.\n\n If provided a read-only ndarray, the function returns a read-only ndarray.\n\n Parameters\n ----------\n x: ndarrayLike\n Input ndarray-like object.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarraylike2ndarray( arr )\n \n\n See Also\n --------\n array, ndarray, ndemptyLike, ndzerosLike\n","ndarrayMinDataType":"\nndarrayMinDataType( value )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n ndarray data type.\n\n Examples\n --------\n > var dt = ndarrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = ndarrayMinDataType( 3 )\n 'uint8'\n > dt = ndarrayMinDataType( -3 )\n 'int8'\n > dt = ndarrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast and, for floating-point data types, can be downcast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be cast.\n\n Examples\n --------\n > var out = ndarrayMostlySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts, ndarraySameKindCasts\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype] )\n Returns the next larger ndarray data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = ndarrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayOffset":"\nndarrayOffset( x )\n Returns the index offset specifying the underlying buffer index of the first\n iterated ndarray element.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Index offset.\n\n Examples\n --------\n > var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n 0\n\n See Also\n --------\n array, ndarray, ndarrayShape, ndarrayStrides\n","ndarrayOrder":"\nndarrayOrder( x )\n Returns the layout order of a provided ndarray.\n\n If unable to resolve a layout order, the function returns `null`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: string|null\n Layout order.\n\n Examples\n --------\n > var opts = { 'order': 'row-major' };\n > var dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n 'row-major'\n\n See Also\n --------\n array, ndarray, ndarrayOrders, ndarrayShape, ndarrayStrides\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n\n The output array contains the following orders:\n\n - row-major: row-major (C-style) order.\n - column-major: column-major (Fortran-style) order.\n\n Returns\n -------\n out: Array\n List of ndarray orders.\n\n Examples\n --------\n > var out = ndarrayOrders()\n [ 'row-major', 'column-major' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1, dtype2] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: any (optional)\n ndarray data type value.\n\n dtype2: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = ndarrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = ndarraySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySameKindCasts\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast or cast\n within the same \"kind\".\n\n Examples\n --------\n > var out = ndarraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarrayShape":"\nndarrayShape( x )\n Returns the shape of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Array\n Shape.\n\n Examples\n --------\n > var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n [ 3, 3, 3 ]\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayStrides\n","ndarrayStride":"\nndarrayStride( x, dim )\n Returns the stride along a specified dimension for a provided ndarray.\n\n A \"stride\" is the linear distance (i.e., number of elements) between\n adjacent elements along a specified dimension.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n Returns\n -------\n out: integer\n Stride.\n\n Examples\n --------\n > var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n 9\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape, ndarrayStrides\n","ndarrayStrides":"\nndarrayStrides( x )\n Returns the strides of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Array\n Strides.\n\n Examples\n --------\n > var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n [ 9, 3, 1 ]\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape\n","ndat":"\nndat( x[, ...indices] )\n Returns an ndarray element.\n\n Negative indices are resolved relative to the last element along the\n respective dimension, with the last element corresponding to `-1`.\n\n If provided out-of-bounds indices, the function always returns `undefined`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n indices: ...integer (optional)\n Index arguments. The number of index arguments must equal the number of\n dimensions.\n\n Returns\n -------\n out: any\n Element value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > ndat( x, 0, 1 )\n 2\n > ndat( x, 1, 0 )\n 3\n\n See Also\n --------\n array, ndslice\n","ndempty":"\nndempty( shape[, options] )\n Returns an uninitialized ndarray having a specified shape and data type.\n\n In browser environments, the function always returns zero-filled ndarrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n For returned ndarrays whose underlying memory is *not* initialized, memory\n contents are unknown and may contain *sensitive* data.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Underlying data type. Default: 'float64'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = ndempty( [ 2, 2 ] )\n \n\n See Also\n --------\n ndemptyLike, ndzeros\n","ndemptyLike":"\nndemptyLike( x[, options] )\n Returns an uninitialized ndarray having the same shape and data type as a\n provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n In browser environments, the function always returns zero-filled ndarrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n For returned ndarrays whose underlying memory is *not* initialized, memory\n contents are unknown and may contain *sensitive* data.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string|DataType (optional)\n Array data type. Overrides the input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = ndzeros( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n > var y = ndemptyLike( x )\n \n\n See Also\n --------\n ndempty, ndzerosLike\n","ndfill":"\nndfill( x, value )\n Fills an input ndarray with a specified value.\n\n If `value` is a number and `x` has a complex data type, the function fills\n an input ndarray with a complex number whose real component equals the\n provided scalar `value` and whose imaginary component is zero.\n\n The function *mutates* the input ndarray.\n\n Parameters\n ----------\n x: ndarrayLike\n Input ndarray.\n\n value: any\n Scalar value. Must be able to safely cast to the input ndarray data\n type. Scalar values having floating-point data types (both real and\n complex) are allowed to downcast to a lower precision data type of the\n same kind (e.g., a scalar double-precision floating-point number can be\n used to fill a 'float32' input ndarray).\n\n Returns\n -------\n out: ndarrayLike\n Input ndarray.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var x = ndzeros( [ 2, 2 ], opts );\n > x.get( 0, 0 )\n 0.0\n > ndfill( x, 10.0 );\n > x.get( 0, 0 )\n 10.0\n\n See Also\n --------\n ndfillBy, ndmap, ndzeros\n","ndfillBy":"\nndfillBy( x, fcn[, thisArg] )\n Fills an input ndarray according to a callback function.\n\n The function *mutates* the input ndarray.\n\n The function assumes that each element in the underlying input ndarray data\n buffer has one, and only one, corresponding element in input ndarray view\n (i.e., a provided ndarray is not a broadcasted ndarray view).\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarrayLike\n Input ndarray.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n out: ndarrayLike\n Input ndarray.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var x = ndzeros( [ 2, 2 ], opts );\n > x.get( 0, 0 )\n 0.0\n > function fcn() { return 10.0; };\n > ndfillBy( x, fcn );\n > x.get( 0, 0 )\n 10.0\n > x.get( 0, 1 )\n 10.0\n > x.get( 1, 0 )\n 10.0\n > x.get( 1, 1 )\n 10.0\n\n See Also\n --------\n ndfill, ndmap, ndzeros\n","ndfilter":"\nndfilter( x[, options], predicate[, thisArg] )\n Returns a shallow copy of an ndarray containing only those elements which\n pass a test implemented by a predicate function.\n\n The predicate function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Predicate function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v > 2.0; };\n > var y = ndfilter( x, f )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n ndfilterMap, ndmap, ndreject, ndslice","ndfilterMap":"\nndfilterMap( x[, options], fcn[, thisArg] )\n Filters and maps elements in an input ndarray to elements in a new output\n ndarray according to a callback function.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n If a provided callback function returns `undefined`, the function skips the\n respective ndarray element. If the callback function returns a value other\n than `undefined`, the function stores the callback's return value in the\n output ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\n > var y = ndfilterMap( x, f )\n [ 30.0, 40.0 ]\n\n See Also\n --------\n ndfilter, ndmap, ndreject, ndslice","ndforEach":"\nndforEach( x, fcn[, thisArg] )\n Invokes a callback function once for each ndarray element.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\n > ndforEach( x, f );\n\n See Also\n --------\n ndmap","ndims":"\nndims( x )\n Returns the number of ndarray dimensions.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Number of dimensions.\n\n Examples\n --------\n > var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n 3\n\n See Also\n --------\n array, ndarray, numel, ndarrayShape\n","ndindex":"\nndindex( x[, options] )\n Wraps a provided array as an ndarray index object.\n\n ndarray index instances have no explicit functionality; however, they are\n used by \"fancy\" ndarrays for element retrieval and assignment.\n\n By default, an instance is invalidated and removed from an internal cache\n immediately after a consumer resolves the underlying data associated with an\n instance using the `get` static method. Immediate invalidation and cache\n removal ensures that references to the underlying ndarray are not the source\n of memory leaks.\n\n Because instances leverage an internal cache implementing the Singleton\n pattern, one must be sure to use the same constructor as consumers. If one\n uses a different constructor, the consumer will *not* be able to resolve the\n original wrapped ndarray, as the consumer will attempt to resolve an\n instance in the wrong internal cache.\n\n Because non-persisted instances are freed after first use, in order to avoid\n holding onto memory and to allow garbage collection, one should avoid\n scenarios in which an instance is never used.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n\n\nndindex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.free( idx.id )\n \n\n\nndindex.get( id )\n Returns the ndarray associated with the instance having a provided\n identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing ndarray data.\n\n out.data: ndarray\n The underlying ndarray associated with the provided identifier.\n\n out.type: string\n The type of ndarray index.\n\n out.dtype: string\n The data type of the underlying ndarray.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.get( idx.id )\n {...}\n\n\nndindex.cartesianIndex( x[, options] )\n Returns an ndarray index containing Cartesian indices.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'cartesian'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = ndindex.cartesianIndex( x );\n\n\nndindex.linearIndex( x[, options] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'linear'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n > var idx = ndindex.linearIndex( x );\n\n\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n\n Returns\n -------\n out: ndarray\n Array data.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.data\n \n\n\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.dtype\n 'int32'\n\n\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.id\n \n\n\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an ndarray index is actively cached.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.isCached\n true\n\n\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n\n Returns\n -------\n out: string\n Index kind.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n > idx.kind\n 'cartesian'\n\n\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n\n Returns\n -------\n out: string\n Index type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.type\n \n\n\nndindex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toString()\n \n\n\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toJSON()\n { 'type': 'ndindex', ... }\n\n See Also\n --------\n array, ndarray, FancyArray, ndslice, ndarray2fancy\n","ndindex.free":"\nndindex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.free( idx.id )\n ","ndindex.get":"\nndindex.get( id )\n Returns the ndarray associated with the instance having a provided\n identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing ndarray data.\n\n out.data: ndarray\n The underlying ndarray associated with the provided identifier.\n\n out.type: string\n The type of ndarray index.\n\n out.dtype: string\n The data type of the underlying ndarray.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.get( idx.id )\n {...}","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x[, options] )\n Returns an ndarray index containing Cartesian indices.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'cartesian'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = ndindex.cartesianIndex( x );","ndindex.linearIndex":"\nndindex.linearIndex( x[, options] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'linear'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n > var idx = ndindex.linearIndex( x );","ndindex.prototype.data":"\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n\n Returns\n -------\n out: ndarray\n Array data.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.data\n ","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.dtype\n 'int32'","ndindex.prototype.id":"\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.id\n ","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an ndarray index is actively cached.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.isCached\n true","ndindex.prototype.kind":"\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n\n Returns\n -------\n out: string\n Index kind.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n > idx.kind\n 'cartesian'","ndindex.prototype.type":"\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n\n Returns\n -------\n out: string\n Index type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.type\n ","ndindex.prototype.toString":"\nndindex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toString()\n ","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toJSON()\n { 'type': 'ndindex', ... }\n\n See Also\n --------\n array, ndarray, FancyArray, ndslice, ndarray2fancy","nditer2arrayEach":"\nnditer2arrayEach( iterator )\n Returns an iterator which converts each iterated ndarray to a generic array.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditer2arrayEach( nditerRows( x ) );\n > var v = it.next().value\n [ 1, 2 ]\n > v = it.next().value\n [ 3, 4 ]\n\n See Also\n --------\n ndarray, ndarray2array\n","nditerColumnEntries":"\nnditerColumnEntries( x[, options] )\n Returns an iterator which returns [index, column] pairs for each column in a\n matrix (or stack of matrices).\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerColumnEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ null, 0 ]\n > ndarray2array( v[ 1 ] )\n [ 1, 3 ]\n > v = it.next().value;\n > v[ 0 ]\n [ null, 1 ]\n > ndarray2array( v[ 1 ] )\n [ 2, 4 ]\n\n See Also\n --------\n nditerColumns, nditerEntries, nditerRowEntries, ndslice\n","nditerColumns":"\nnditerColumns( x[, options] )\n Returns an iterator which iterates over each column in a matrix (or stack of\n matrices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerColumns( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ 1, 3 ]\n > v = it.next().value;\n > ndarray2array( v )\n [ 2, 4 ]\n\n See Also\n --------\n nditerColumnEntries, nditerRows, ndslice\n","nditerEntries":"\nnditerEntries( x[, options] )\n Returns an iterator which returns [index, value] pairs for each element in a\n provided ndarray.\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator returns values\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerEntries( x );\n > var v = it.next().value\n [ [ 0, 0 ], 1 ]\n > v = it.next().value\n [ [ 0, 1 ], 2 ]\n\n See Also\n --------\n ndarray, nditerIndices, nditerValues\n","nditerIndices":"\nnditerIndices( shape[, options] )\n Returns an iterator which returns indices for use indexing into an ndarray\n having a specified shape.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n shape: Array\n Input shape.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator iterates over\n the last dimensions first, thus corresponding to iteration over\n contiguous data stored in row-major order. Must be either 'row-major'\n or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerIndices( x.shape );\n > var v = it.next().value\n [ 0, 0 ]\n > v = it.next().value\n [ 0, 1 ]\n\n See Also\n --------\n ndarray, nditerEntries, nditerValues\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr, ndims )\n Returns an iterator which iterates over interleaved subarrays.\n\n For input ndarrays supporting read-only views, the function returns\n *read-only* views of interleaved subarrays. As input ndarrays may be\n broadcasted, a view is typically *not* contiguous. As more than one element\n of a returned view may refer to the same memory location, writing to a view\n may affect multiple elements. If you need to write to a subarray, copy the\n subarray before attempting mutation.\n\n The function throws an error if a provided broadcast-incompatible ndarrays.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n arr: ArrayLike\n Input ndarrays. All ndarrays must be broadcast-compatible. After\n broadcasting, each broadcasted input ndarray must have at least\n `ndims+1` dimensions.\n\n ndims: integer\n Number of dimensions to stack after broadcasting.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerInterleaveSubarrays( [ x, x ], 2 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerSubarrays, ndslice\n","nditerMatrices":"\nnditerMatrices( x[, options] )\n Returns an iterator which iterates over each matrix in a stack of matrices.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerMatrices( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrixEntries, nditerRows, ndslice\n","nditerMatrixEntries":"\nnditerMatrixEntries( x[, options] )\n Returns an iterator which returns [index, matrix] pairs for each matrix in a\n stack of matrices.\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerMatrixEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ 0, null, null ]\n > ndarray2array( v[ 1 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumnEntries, nditerEntries, nditerMatrices, nditerRowEntries, ndslice\n","nditerRowEntries":"\nnditerRowEntries( x[, options] )\n Returns an iterator which returns [index, row] pairs for each row in a\n matrix (or stack of matrices).\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerRowEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ 0, null ]\n > ndarray2array( v[ 1 ] )\n [ 1, 2 ]\n > v = it.next().value;\n > v[ 0 ]\n [ 1, null ]\n > ndarray2array( v[ 1 ] )\n [ 3, 4 ]\n\n See Also\n --------\n nditerColumnEntries, nditerEntries, nditerRows, ndslice\n","nditerRows":"\nnditerRows( x[, options] )\n Returns an iterator which iterates over each row in a matrix (or stack of\n matrices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerRows( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ 1, 2 ]\n > v = it.next().value;\n > ndarray2array( v )\n [ 3, 4 ]\n\n See Also\n --------\n nditerColumns, nditerRowEntries, ndslice\n","nditerSelectDimension":"\nnditerSelectDimension( x, dim[, options] )\n Returns an iterator which iterates over each view along a specified\n dimension.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n options.keepdim: boolean (optional)\n Boolean indicating whether returned views should include the selected\n dimension as a singleton dimension. Including the selected dimension as\n a singleton dimension can be useful when wanting to ensure that returned\n views remain broadcast compatible with the input ndarray. Default:\n false.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerSelectDimension( x, 0 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, ndslice\n","nditerStacks":"\nnditerStacks( x, dims[, options] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays according to a list of specified stack dimensions.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator. Must have at least\n `dims.length+1` dimensions.\n\n dims: Array\n Indices of dimensions to stack. If a dimension index is less than zero,\n the index is resolved relative to the last dimension, with the last\n dimension corresponding to the value `-1`. The list of indices must be\n unique and resolve to dimension indices sorted in ascending order.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerStacks( x, [ 1, 2 ] );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, nditerSubarrays, ndslice\n","nditerSubarrays":"\nnditerSubarrays( x, ndims[, options] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator. Must have at least\n `ndims+1` dimensions.\n\n ndims: integer\n Number of dimensions to stack.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerSubarrays( x, 2 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, nditerStacks, ndslice\n","nditerValues":"\nnditerValues( x[, options] )\n Returns an iterator which returns individual elements from a provided\n ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator returns values\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerValues( x );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n ndarray, nditerEntries, nditerIndices\n","ndmap":"\nndmap( x[, options], fcn[, thisArg] )\n Applies a callback function to elements in an input ndarray and assigns\n results to elements in a new output ndarray.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v*10.0; };\n > var y = ndmap( x, f )\n [ [ 10.0, 20.0 ], [ 30.0, 40.0 ] ]\n\n See Also\n --------\n ndfilter, ndfilterMap, ndforEach, ndslice","ndreject":"\nndreject( x[, options], predicate[, thisArg] )\n Returns a shallow copy of an ndarray containing only those elements which\n fail a test implemented by a predicate function.\n\n The predicate function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Predicate function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v <= 2.0; };\n > var y = ndreject( x, f );\n > ndarray2array( y )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n ndfilter, ndfilterMap, ndmap, ndslice","ndslice":"\nndslice( x, ...s[, options] )\n Returns a read-only view of an input ndarray.\n\n The function supports three (mutually exclusive) means of providing slice\n arguments:\n\n 1. Providing a single MultiSlice object.\n 2. Providing a single array containing slice arguments.\n 3. Providing slice arguments as separate arguments.\n\n An individual slice argument must be either a Slice, an integer, null, or\n undefined.\n\n In all cases, the number of slice dimensions must match the number of array\n dimensions.\n\n If providing a MultiSlice object or an array of slice arguments, no other\n slice arguments should be provided.\n\n Mixing function invocation styles (e.g., providing multiple MultiSlice\n objects or providing an array of slice arguments followed by additional\n slice arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n Slice arguments.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var s = new MultiSlice( null, 1 )\n \n > var y = ndslice( x, s )\n \n > y.shape\n [ 2 ]\n > ndarray2array( y )\n [ 2, 4 ]\n\n See Also\n --------\n array, ndat, ndarray, ndsliceAssign, ndsliceDimension\n","ndsliceAssign":"\nndsliceAssign( x, y, ...s[, options] )\n Assigns element values from a broadcasted input ndarray to corresponding\n elements in an output ndarray view.\n\n The function supports three (mutually exclusive) means of providing slice\n arguments:\n\n 1. Providing a single MultiSlice object.\n 2. Providing a single array containing slice arguments.\n 3. Providing slice arguments as separate arguments.\n\n An individual slice argument must be either a Slice, an integer, null, or\n undefined.\n\n In all cases, the number of slice dimensions must match the number of output\n array dimensions.\n\n If providing a MultiSlice object or an array of slice arguments, no other\n slice arguments should be provided.\n\n Mixing function invocation styles (e.g., providing multiple MultiSlice\n objects or providing an array of slice arguments followed by additional\n slice arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array. The input array must be broadcast compatible with the\n output array view and must have a data type which can be safely cast to\n the output array data type. Floating-point data types (both real and\n complex) are allowed to downcast to a lower precision data type of the\n same kind (e.g., element values from a 'float64' input array can be\n assigned to corresponding elements in a 'float32' output array).\n\n y: ndarray\n Output array. The output array must be writable.\n\n s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n Slice arguments.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n true.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var y = ndzeros( [ 2, 2 ] )\n \n > var x = scalar2ndarray( 3.0 )\n \n > var s = new MultiSlice( null, 1 )\n \n > var out = ndsliceAssign( x, y, s )\n \n > var bool = ( out === y )\n true\n > ndarray2array( y )\n [ [ 0.0, 3.0 ], [ 0.0, 3.0 ] ]\n\n See Also\n --------\n array, ndarray, ndslice\n","ndsliceDimension":"\nndsliceDimension( x, dim, slice[, options] )\n Returns a read-only view of an input ndarray when sliced along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n slice: Slice|integer|null|undefined\n Slice object or an integer. If provided `null` or `undefined`, the\n returned view includes all elements along a specified dimension. If\n provided an integer less than zero, the corresponding element along the\n specified dimension is resolved relative to the last element along that\n dimension. For negative integers, the last element corresponds to the\n value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimension( x, 1, 1 )\n \n > y.shape\n [ 2 ]\n > ndarray2array( y )\n [ 2, 4 ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceDimensionTo\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x, dim, start[, options] )\n Returns a read-only shifted view of an input ndarray along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n start: integer\n Starting index (inclusive). If less than zero, the corresponding element\n along the specified dimension is resolved relative to the last element\n along that dimension. For negative integers, the last element\n corresponds to the value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimensionFrom( x, 1, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 2 ], [ 4 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionTo, ndsliceFrom\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x, dim, stop[, options] )\n Returns a read-only truncated view of an input ndarray along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n stop: integer\n Ending index (exclusive). If less than zero, the corresponding element\n along the specified dimension is resolved relative to the last element\n along that dimension. For negative integers, the last element\n corresponds to the value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimensionTo( x, 1, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 1 ], [ 3 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionFrom, ndsliceTo\n","ndsliceFrom":"\nndsliceFrom( x, ...start[, options] )\n Returns a read-only shifted view of an input ndarray.\n\n The function supports two (mutually exclusive) means of providing starting\n indices:\n\n 1. Providing a single array containing start arguments.\n 2. Providing start arguments as separate arguments.\n\n An individual start argument must be either an integer, null, or undefined.\n\n In all cases, the number of start indices must match the number of array\n dimensions.\n\n If providing an array of start arguments, no other start arguments should be\n provided.\n\n Mixing function invocation styles (e.g., providing an array of start\n arguments followed by additional start arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n start: ...null|void|integer\n Starting indices (inclusive). If an element is either `null` or\n `undefined`, the function returns a view containing all elements along\n that dimension. A negative integer indicates to resolve a starting index\n relative to the last element along a corresponding dimension, with the\n last element having index `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceFrom( x, 0, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 2 ], [ 4 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceTo\n","ndsliceTo":"\nndsliceTo( x, ...stop[, options] )\n Returns a read-only truncated view of an input ndarray.\n\n The function supports two (mutually exclusive) means of providing ending\n indices:\n\n 1. Providing a single array containing stop arguments.\n 2. Providing stop arguments as separate arguments.\n\n An individual stop argument must be either an integer, null, or undefined.\n\n In all cases, the number of stop indices must match the number of array\n dimensions.\n\n If providing an array of stop arguments, no other stop arguments should be\n provided.\n\n Mixing function invocation styles (e.g., providing an array of stop\n arguments followed by additional stop arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n stop: ...null|void|integer\n Ending indices (exclusive). If an ending index is either `null` or\n `undefined`, the function returns a view containing all elements along\n that dimension. A negative integer indicates to resolve an ending index\n relative to the last element along a corresponding dimension, with the\n last element having index `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceTo( x, 1, 1 )\n \n > y.shape\n [ 1, 1 ]\n > ndarray2array( y )\n [ [ 1 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionTo, ndsliceFrom\n","ndzeros":"\nndzeros( shape[, options] )\n Returns a zero-filled ndarray having a specified shape and data type.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Underlying data type. Must be a numeric or \"generic\" data type. Default:\n 'float64'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = ndzeros( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n ndempty, ndzerosLike\n","ndzerosLike":"\nndzerosLike( x[, options] )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a numeric or \"generic\" data type. Overrides the\n input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = ndzeros( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n > var y = ndzerosLike( x )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n ndemptyLike, ndzeros\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str[, fromIndex] )\n Returns the next extended grapheme cluster break in a string after a\n specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n fromIndex: integer (optional)\n Position. Default: 0.\n\n Returns\n -------\n out: integer\n Next extended grapheme cluster break position.\n\n Examples\n --------\n > var out = nextGraphemeClusterBreak( 'last man standing', 4 )\n 5\n > out = nextGraphemeClusterBreak( 'presidential election', 8 )\n 9\n > out = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\n 3\n > out = nextGraphemeClusterBreak( '🌷' )\n -1\n\n See Also\n --------\n numGraphemeClusters, prevGraphemeClusterBreak","nextTick":"\nnextTick( clbk[, ...args] )\n Adds a callback to the \"next tick queue\".\n\n The queue is fully drained after the current operation on the JavaScript\n stack runs to completion and before the event loop is allowed to continue.\n\n Parameters\n ----------\n clbk: Function\n Callback to invoke.\n\n ...args: any (optional)\n Arguments to provide to the callback upon invocation.\n\n Examples\n --------\n > function f() { console.log( 'beep' ); };\n > nextTick( f )\n\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n\n Returns\n -------\n out: Array\n Nightingale's data.\n\n Examples\n --------\n > var data = NIGHTINGALES_ROSE()\n [{...}, {...}, ...]\n\n References\n ----------\n - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n the British army during the late war with Russia*. London, United Kingdom:\n John W. Parker and Son..\n\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n\n Examples\n --------\n > NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_NINF, PINF\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n\n Examples\n --------\n > NODE_VERSION\n \n\n","none":"\nnone( collection )\n Tests whether all elements in a collection are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are falsy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0 ];\n > var bool = none( arr )\n true\n\n See Also\n --------\n any, every, forEach, noneBy, some\n","noneBy":"\nnoneBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = noneBy( arr, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, none, noneByRight, someBy\n","noneByAsync":"\nnoneByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync\n","noneByAsync.factory":"\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync","noneByRight":"\nnoneByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ -1, -2, -3, -4 ];\n > var bool = noneByRight( arr, positive )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, none, noneBy, someByRight\n","noneByRightAsync":"\nnoneByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync","noneInBy":"\nnoneInBy( object, predicate[, thisArg ] )\n Tests whether every property in an object fails a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 4 };\n > var bool = noneInBy( obj, negative )\n true\n\n See Also\n --------\n anyInBy, everyInBy, noneBy, someInBy\n","nonEnumerableProperties":"\nnonEnumerableProperties( value )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own non-enumerable properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var props = nonEnumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerableProperties, inheritedNonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited non-enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = nonEnumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerablePropertiesIn, inheritedNonEnumerableProperties, nonEnumerableProperties, propertiesIn\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value )\n Returns an array of an object's own non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNames( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n objectKeys, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNamesIn( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n keysIn, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNames, propertyNamesIn\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value )\n Returns an array of an object's own non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNames, nonEnumerablePropertySymbolsIn, propertySymbols\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertySymbolsIn\n","noneOwnBy":"\nnoneOwnBy( object, predicate[, thisArg ] )\n Tests whether every own property of an object fails a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all own properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function isUnderage( v ) { return ( v < 18 ); };\n > var obj = { 'a': 11, 'b': 12, 'c': 22 };\n > var bool = noneOwnBy( obj, isUnderage )\n false\n\n See Also\n --------\n anyOwnBy, everyOwnBy, noneBy, someOwnBy\n","nonIndexKeys":"\nnonIndexKeys( obj )\n Returns an array of an object's own enumerable property names which are not\n integer indices.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = nonIndexKeys( obj )\n e.g., [ 'beep' ]\n\n See Also\n --------\n objectEntries, objectKeys, objectValues\n","noop":"\nnoop()\n A function which does nothing.\n\n Examples\n --------\n > noop();\n\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n\n The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n Returns\n -------\n out: integer\n Time in seconds since the epoch.\n\n Examples\n --------\n > var ts = now()\n \n\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n\n In browser environments, the number of CPUs is determined by querying the\n hardware concurrency API.\n\n In Node.js environments, the number of CPUs is determined via the `os`\n module.\n\n Examples\n --------\n > NUM_CPUS\n \n\n","num2words":"\nnum2words( value[, options] )\n Converts a number to a word representation.\n\n Parameters\n ----------\n value: integer\n Input value.\n\n options: Object (optional)\n Options.\n\n options.lang: string (optional)\n Language code. Supported languages:\n\n - en: English.\n - de: German.\n\n Default: `'en'`.\n\n Returns\n -------\n out: string\n Word representation of number.\n\n Examples\n --------\n > var out = num2words( 123 )\n 'one hundred twenty-three'\n\n > out = num2words( 16.31 )\n 'sixteen point three one'\n\n > out = num2words( 123, { 'lang': 'de' } )\n 'einhundertdreiundzwanzig'\n\n","Number":"\nNumber( value )\n Returns a Number object.\n\n This constructor should be used sparingly. Always prefer number primitives.\n\n Parameters\n ----------\n value: number\n Value to wrap in a Number object.\n\n Returns\n -------\n out: Number\n Number object.\n\n Examples\n --------\n > var v = new Number( 5 )\n \n\n","numel":"\nnumel( x )\n Returns the number of elements in an ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Number of elements.\n\n Examples\n --------\n > var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n 27\n\n See Also\n --------\n array, ndarray, numelDimension\n","numelDimension":"\nnumelDimension( x, dim )\n Returns the size (i.e., number of elements) of a specified dimension for a\n provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n Returns\n -------\n out: integer\n Dimension size.\n\n Examples\n --------\n > var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n 4\n\n See Also\n --------\n array, ndarray, numel\n","numGraphemeClusters":"\nnumGraphemeClusters( str )\n Returns the number of grapheme clusters in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Number of grapheme clusters.\n\n Examples\n --------\n > var out = numGraphemeClusters( 'beep' )\n 4\n > out = numGraphemeClusters( '🌷' )\n 1\n\n See Also\n --------\n nextGraphemeClusterBreak\n","Object":"\nObject( value )\n Returns an object.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n If provided an existing object, the function returns the input value\n unchanged.\n\n Otherwise, if provided any other value (e.g., a number, string, etc), the\n function will return an object of the corresponding type.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > var o = new Object( null )\n {}\n > o = new Object( 5.0 )\n \n > o = new Object( 'beep' )\n \n\nObject.assign( target, ...sources )\n Assigns enumerable and own properties from source objects to a target\n object.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n sources: ...Object\n Source objects.\n\n Returns\n -------\n out: Object\n Target object.\n\n Examples\n --------\n > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n { 'a': 1, 'b': 2 }\n\nObject.create( prototype, properties )\n Creates a new object with a specified prototype object and properties.\n\n Parameters\n ----------\n prototype: Object\n Prototype object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }\n\nObject.defineProperties( obj, properties )\n Defines properties for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }\n\nObject.defineProperty( obj, key, descriptor )\n Defines a property for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n descriptor: Object\n Property descriptor.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperty( {}, 'a', {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': false\n })\n { 'a': 1 }\n\nObject.entries( obj )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of [key, value] pairs.\n\n Examples\n --------\n > var o = Object.entries( { 'a': 1, 'b': 2 } )\n [ [ 'a', 1 ], [ 'b', 2 ] ]\n\nObject.freeze( obj )\n Freezes an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.freeze( { 'a': 1 } )\n { 'a': 1 }\n\nObject.getOwnPropertyDescriptor( obj, key )\n Returns an object's own property descriptor.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n Returns\n -------\n out: Object\n Property descriptor.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }\n\nObject.getOwnPropertyDescriptors( obj )\n Returns an object's own property descriptors.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Property descriptors.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n {\n 'a': {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n },\n 'b': {\n 'value': 2,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n }\n }\n\nObject.getOwnPropertyNames( obj )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]\n\nObject.getOwnPropertySymbols( obj )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of symbol property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n []\n\nObject.getPrototypeOf( obj )\n Returns an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Prototype.\n\n Examples\n --------\n > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n \n\nObject.hasOwn( obj, p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n true\n\nObject.is( value1, value2 )\n Returns a boolean indicating whether two values are the same value.\n\n Parameters\n ----------\n value1: any\n First value.\n\n value2: any\n Second value.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether two values are the same value.\n\n Examples\n --------\n > var o = Object.is( 1, 1 )\n true\n > var o = Object.is( 1, '1' )\n false\n\nObject.isExtensible( obj )\n Returns a boolean indicating whether an object is extensible.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is extensible.\n\n Examples\n --------\n > var o = Object.isExtensible( { 'a': 1 } )\n true\n\nObject.isFrozen( obj )\n Returns a boolean indicating whether an object is frozen.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is frozen.\n\n Examples\n --------\n > var o = Object.isFrozen( { 'a': 1 } )\n false\n > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n true\n\nObject.isSealed( obj )\n Returns a boolean indicating whether an object is sealed.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is sealed.\n\n Examples\n --------\n > var o = Object.isSealed( { 'a': 1 } )\n false\n > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n true\n\nObject.keys( obj )\n Returns an array of an object's own enumerable string-keyed property\n names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.keys( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]\n\nObject.preventExtensions( obj )\n Prevents the addition of new properties to an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.preventExtensions( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n\nObject.seal( obj )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.seal( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n > delete o.a;\n > o\n { 'a': 1 }\n\nObject.setPrototypeOf( obj, proto )\n Sets an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n proto: Object\n Prototype.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n { 'a': 1 }\n > o.b\n 2\n\nObject.values( obj )\n Returns an array of an object's own enumerable property values.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property values.\n\n Examples\n --------\n > var o = Object.values( { 'a': 1, 'b': 2 } )\n [ 1, 2 ]\n\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n \n\nObject.prototype.toString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n \n\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n\n Returns\n -------\n out: any\n Primitive value of the object.\n\n Examples\n --------\n > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n {}\n\nObject.prototype.hasOwnProperty( p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n true\n\nObject.prototype.isPrototypeOf( obj )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object exists in another object's\n prototype chain.\n\n Examples\n --------\n > var p = { 'a': 1 };\n > var o = { '__proto__': p };\n > var b = o.isPrototypeOf( p );\n true\n\nObject.prototype.propertyIsEnumerable( p )\n Returns a boolean indicating whether an object's property is enumerable.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object's property is enumerable.\n\n Examples\n --------\n > var o = { 'a': 1, 'b': 2 };\n > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n true\n\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n\n Examples\n --------\n > var o = new Object( null );\n > var ctr = o.constructor;\n \n\n","Object.assign":"\nObject.assign( target, ...sources )\n Assigns enumerable and own properties from source objects to a target\n object.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n sources: ...Object\n Source objects.\n\n Returns\n -------\n out: Object\n Target object.\n\n Examples\n --------\n > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n { 'a': 1, 'b': 2 }","Object.create":"\nObject.create( prototype, properties )\n Creates a new object with a specified prototype object and properties.\n\n Parameters\n ----------\n prototype: Object\n Prototype object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }","Object.defineProperties":"\nObject.defineProperties( obj, properties )\n Defines properties for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }","Object.defineProperty":"\nObject.defineProperty( obj, key, descriptor )\n Defines a property for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n descriptor: Object\n Property descriptor.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperty( {}, 'a', {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': false\n })\n { 'a': 1 }","Object.entries":"\nObject.entries( obj )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of [key, value] pairs.\n\n Examples\n --------\n > var o = Object.entries( { 'a': 1, 'b': 2 } )\n [ [ 'a', 1 ], [ 'b', 2 ] ]","Object.freeze":"\nObject.freeze( obj )\n Freezes an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.freeze( { 'a': 1 } )\n { 'a': 1 }","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj, key )\n Returns an object's own property descriptor.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n Returns\n -------\n out: Object\n Property descriptor.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj )\n Returns an object's own property descriptors.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Property descriptors.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n {\n 'a': {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n },\n 'b': {\n 'value': 2,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n }\n }","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of symbol property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n []","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj )\n Returns an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Prototype.\n\n Examples\n --------\n > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n ","Object.hasOwn":"\nObject.hasOwn( obj, p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n true","Object.is":"\nObject.is( value1, value2 )\n Returns a boolean indicating whether two values are the same value.\n\n Parameters\n ----------\n value1: any\n First value.\n\n value2: any\n Second value.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether two values are the same value.\n\n Examples\n --------\n > var o = Object.is( 1, 1 )\n true\n > var o = Object.is( 1, '1' )\n false","Object.isExtensible":"\nObject.isExtensible( obj )\n Returns a boolean indicating whether an object is extensible.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is extensible.\n\n Examples\n --------\n > var o = Object.isExtensible( { 'a': 1 } )\n true","Object.isFrozen":"\nObject.isFrozen( obj )\n Returns a boolean indicating whether an object is frozen.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is frozen.\n\n Examples\n --------\n > var o = Object.isFrozen( { 'a': 1 } )\n false\n > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n true","Object.isSealed":"\nObject.isSealed( obj )\n Returns a boolean indicating whether an object is sealed.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is sealed.\n\n Examples\n --------\n > var o = Object.isSealed( { 'a': 1 } )\n false\n > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n true","Object.keys":"\nObject.keys( obj )\n Returns an array of an object's own enumerable string-keyed property\n names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.keys( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]","Object.preventExtensions":"\nObject.preventExtensions( obj )\n Prevents the addition of new properties to an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.preventExtensions( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }","Object.seal":"\nObject.seal( obj )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.seal( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n > delete o.a;\n > o\n { 'a': 1 }","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj, proto )\n Sets an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n proto: Object\n Prototype.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n { 'a': 1 }\n > o.b\n 2","Object.values":"\nObject.values( obj )\n Returns an array of an object's own enumerable property values.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property values.\n\n Examples\n --------\n > var o = Object.values( { 'a': 1, 'b': 2 } )\n [ 1, 2 ]","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n ","Object.prototype.toString":"\nObject.prototype.toString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n ","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n\n Returns\n -------\n out: any\n Primitive value of the object.\n\n Examples\n --------\n > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n {}","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n true","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object exists in another object's\n prototype chain.\n\n Examples\n --------\n > var p = { 'a': 1 };\n > var o = { '__proto__': p };\n > var b = o.isPrototypeOf( p );\n true","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p )\n Returns a boolean indicating whether an object's property is enumerable.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object's property is enumerable.\n\n Examples\n --------\n > var o = { 'a': 1, 'b': 2 };\n > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n true","Object.prototype.constructor":"\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n\n Examples\n --------\n > var o = new Object( null );\n > var ctr = o.constructor;\n ","objectEntries":"\nobjectEntries( obj )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var entries = objectEntries( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntriesIn, objectFromEntries, objectKeys, objectValues\n","objectEntriesIn":"\nobjectEntriesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var entries = objectEntriesIn( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntries, objectFromEntries, keysIn, objectValuesIn\n","objectFromEntries":"\nobjectFromEntries( entries )\n Creates an object from an array of key-value pairs.\n\n Parameters\n ----------\n entries: Array\n Input object.\n\n Returns\n -------\n out: Object\n Object created from `[key, value]` pairs.\n\n Examples\n --------\n > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n > var obj = objectFromEntries( entries )\n { 'beep': 'boop', 'foo': 'bar' }\n\n See Also\n --------\n objectEntries\n","objectInverse":"\nobjectInverse( obj[, options] )\n Inverts an object, such that keys become values and values become keys.\n\n Beware when providing objects having values which are themselves objects.\n The function relies on native object serialization (`#toString`) when\n converting values to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverse( obj )\n { 'beep': 'a', 'boop': 'b' }\n\n // Duplicate values:\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverse( obj )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverse( obj, { 'duplicates': false } )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverseBy\n","objectInverseBy":"\nobjectInverseBy( obj, [options,] transform )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n\n The transform function is provided three arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n\n The value returned by a transform function should be a value which can be\n serialized as an object key. Hence, beware when providing objects having\n values which are themselves objects. The function relies on native object\n serialization (`#toString`) when converting transform function return values\n to keys.\n\n In older JavaScript engines, insertion order is not guaranteed, as object\n key enumeration was not specified according to the ECMAScript specification\n in earlier editions. In practice, however, most older engines use insertion\n order to sort an object's keys, thus allowing for deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n transform: Function\n Transform function.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverseBy( obj, transform )\n { 'abeep': 'a', 'bboop': 'b' }\n\n // Duplicate values:\n > function transform( key, value ) { return value; };\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverseBy( obj, transform )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverse\n","objectKeys":"\nobjectKeys( value )\n Returns an array of an object's own enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = objectKeys( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectEntries, keysIn, nonIndexKeys, objectValues\n","objectValues":"\nobjectValues( obj )\n Returns an array of an object's own enumerable property values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var vals = objectValues( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntries, objectKeys\n","objectValuesIn":"\nobjectValuesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var values = objectValuesIn( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntriesIn, keysIn, objectValues\n","omit":"\nomit( obj, keys )\n Returns a partial object copy excluding specified keys.\n\n The function returns a shallow copy.\n\n The function ignores non-existent keys.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to exclude.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omit( obj1, 'b' )\n { 'a': 1 }\n\n See Also\n --------\n omitBy\n","omitBy":"\nomitBy( obj, predicate )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n\n The function returns a shallow copy.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) { return ( value > 1 ); };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omitBy( obj1, predicate )\n { 'a': 1 }\n\n See Also\n --------\n omit\n","open":"\nopen( path[, flags[, mode]], clbk )\n Asynchronously opens a file.\n\n Some characters, such as <>:\"/\\|?*, are reserved under Windows.\n Under NTFS, if the path contains a colon, Node.js will open a file system\n stream.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon opening a file.\n\n Examples\n --------\n > function onOpen( error, fd ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... close.sync( fd );\n ... }\n ... };\n > open( './beep/boop.txt', onOpen );\n\n\nopen.sync( path[, flags[, mode]] )\n Synchronously opens a file.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n Returns\n -------\n fd: Error|integer\n File descriptor.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.txt' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n close, exists, readFile\n","open.sync":"\nopen.sync( path[, flags[, mode]] )\n Synchronously opens a file.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n Returns\n -------\n fd: Error|integer\n File descriptor.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.txt' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n close, exists, readFile","openURL":"\nopenURL( url )\n Opens a URL in a user's default browser.\n\n In a non-browser environment, the function returns an unreferenced child\n process. In a browser environment, the function returns a reference to a\n `window` object.\n\n Parameters\n ----------\n url: string\n URL to open.\n\n Returns\n -------\n out: process|Window\n Child process or `window` object.\n\n Examples\n --------\n > var out = openURL( 'https://google.com' );\n\n","ordinalize":"\nordinalize( value[, options] )\n Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n\n Parameters\n ----------\n value: string|integer\n Input value.\n\n options: Object (optional)\n Options.\n\n options.lang: string (optional)\n Language code. Supported languages:\n\n - en: English.\n - es: Spanish.\n - fin: Finnish.\n - fr: French.\n - de: Dutch.\n - it: Italian.\n - pt: Portuguese.\n - swe: Swedish.\n\n Default: `'en'`.\n\n options.suffixOnly: boolean (optional)\n Boolean indicating whether to return only the suffix. Default: `false`.\n\n options.gender: string (optional)\n Grammatical gender (used if applicable); must be either 'masculine' or\n 'feminine'. Default: `'masculine'`.\n\n Returns\n -------\n out: string\n Ordinal string or suffix.\n\n Examples\n --------\n > var out = ordinalize( '1' )\n '1st'\n > out = ordinalize( 2, { 'suffixOnly': true } )\n 'nd'\n > out = ordinalize( '3', { 'lang': 'es' } )\n '3º'\n\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 21 attributes:\n\n - obs: observation number.\n - town: town name.\n - town_id: town identifier.\n - tract: tract identifier.\n - lon: longitude.\n - lat: latitude.\n - medv: median value of owner-occupied homes in $1000's.\n - cmedv: corrected median value of owner-occupied homes in $1000's.\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n - lstat: percent lower status of the population.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n by including geo-referencing and spatial estimation for each observation.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = PACE_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n Configuration of the Data to Improve Estimation.\" _The Journal of Real\n Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, HARRISON_BOSTON_HOUSE_PRICES_CORRECTED\n","pad":"\npad( str, len[, options] )\n Pads a `string` such that the padded `string` has length `len`.\n\n Any padding which does not evenly divide available space is trimmed such\n that the returned string length is always `len`.\n\n If `len < str.length`, the input string is trimmed.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n options: Object (optional)\n Options.\n\n options.lpad: string (optional)\n String used to left pad.\n\n options.rpad: string (optional)\n String used to right pad.\n\n options.centerRight: boolean (optional)\n Boolean indicating whether to center right in the event of a tie.\n Default: `false` (i.e., center left).\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n // Standard usage:\n > var out = pad( 'a', 5 )\n 'a '\n\n // Left pad:\n > out = pad( 'a', 10, { 'lpad': 'b' } )\n 'bbbbbbbbba'\n\n // Right pad:\n > out = pad( 'a', 12, { 'rpad': 'b' } )\n 'abbbbbbbbbbb'\n\n // Center an input string:\n > var opts = { 'lpad': 'a', 'rpad': 'c' };\n > out = pad( 'b', 11, opts )\n 'aaaaabccccc'\n\n // Left center:\n > opts.centerRight = false;\n > out = pad( 'b', 10, opts )\n 'aaaabccccc'\n\n // Right center:\n > opts.centerRight = true;\n > out = pad( 'b', 10, opts )\n 'aaaaabcccc'\n\n // Output string always length `len`:\n > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n > out = pad( 'beep', 10, opts )\n 'boobeepwoo'\n\n // Pad right, trim right:\n > out = pad( 'beep', 2 )\n 'be'\n\n // Pad left, trim left:\n > opts = { 'lpad': 'b' };\n > out = pad( 'beep', 2, opts )\n 'ep'\n\n // Pad both, trim both:\n > opts = { 'lpad': '@', 'rpad': '!' };\n > out = pad( 'beep', 2, opts )\n 'ee'\n\n // Pad both, trim both starting from left:\n > out = pad( 'abcdef', 3, opts )\n 'cde'\n\n // Pad both, trim both starting from right:\n > opts.centerRight = true;\n > out = pad( 'abcdef', 3, opts )\n 'bcd'\n\n See Also\n --------\n lpad, rpad\n","padjust":"\npadjust( pvals, method[, comparisons] )\n Adjusts supplied p-values for multiple comparisons via a specified method.\n\n The `method` parameter can be one of the following values:\n\n - bh: Benjamini-Hochberg procedure controlling the False Discovery\n Rate (FDR).\n - bonferroni: Bonferroni correction fixing the family-wise error rate\n by multiplying the p-values with the number of comparisons. The Bonferroni\n correction is usually a too conservative adjustment compared to the others.\n - by: Procedure by Benjamini & Yekutieli for controlling the False\n Discovery Rate (FDR) under dependence.\n - holm: Hommel's method controlling family-wise error rate. It is\n uniformly more powerful than the Bonferroni correction.\n - hommel: Hommel's method, which is valid when hypothesis tests are\n independent. It is more expensive to compute than the other methods.\n\n By default, the number of comparisons for which the p-values should be\n corrected is equal to the number of provided p-values. Alternatively, it is\n possible to set `comparisons` to a number greater than the length of\n `pvals`. In that case, the methods assume `comparisons - pvals.length`\n unobserved p-values that are greater than all observed p-values (for Holm's\n method and the Bonferroni correction) or equal to `1` for the remaining\n methods.\n\n Parameters\n ----------\n pvals: Array\n P-values to be adjusted.\n\n method: string\n Correction method.\n\n comparisons: integer (optional)\n Number of comparisons. Default value: `pvals.length`.\n\n Returns\n -------\n out: Array\n Array containing the corrected p-values.\n\n Examples\n --------\n > var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\n > var out = padjust( pvalues, 'bh' )\n [ 0.04, 0.075, ~0.205, 0.6, 0.25 ]\n\n > out = padjust( pvalues, 'bonferroni' )\n [ 0.04, 0.15, 0.615, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'by' )\n [ ~0.457, ~0.856, 1.0, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'holm' )\n [ 0.2, 0.6, 1.0, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'hommel' )\n [ 0.16, 0.6, 1.0, 1.0, 1.0 ]\n\n","papply":"\npapply( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var add2 = papply( add, 2 );\n > var sum = add2( 3 )\n 5\n\n See Also\n --------\n papplyRight\n","papplyRight":"\npapplyRight( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function say( text, name ) { return text + ', ' + name + '.'; };\n > var toGrace = papplyRight( say, 'Grace Hopper' );\n > var str = toGrace( 'Hello' )\n 'Hello, Grace Hopper.'\n > str = toGrace( 'Thank you' )\n 'Thank you, Grace Hopper.'\n\n See Also\n --------\n papply\n","parallel":"\nparallel( files, [options,] clbk )\n Executes scripts in parallel.\n\n Relative file paths are resolved relative to the current working directory.\n\n Ordered script output does not imply that scripts are executed in order. To\n preserve script order, execute the scripts sequentially via some other\n means.\n\n Parameters\n ----------\n files: Array\n Script file paths.\n\n options: Object (optional)\n Options.\n\n options.cmd: string (optional)\n Executable file/command. Default: `'node'`.\n\n options.concurrency: integer (optional)\n Number of scripts to execute concurrently. Script concurrency cannot\n exceed the number of scripts. By specifying a concurrency greater than\n the number of workers, a worker may be executing more than `1` script at\n any one time. While not likely to be advantageous for synchronous\n scripts, setting a higher concurrency may be advantageous for scripts\n performing asynchronous tasks. If the script concurrency is less than\n the number of workers, the number of workers is reduced to match the\n specified concurrency. Default: `options.workers`.\n\n options.workers: integer (optional)\n Number of workers. Default: number of CPUs minus `1`.\n\n options.ordered: boolean (optional)\n Boolean indicating whether to preserve the order of script output. By\n default, the `stdio` output for each script is interleaved; i.e., the\n `stdio` output from one script may be interleaved with the `stdio`\n output from one or more other scripts. To preserve the `stdio` output\n order for each script, set the `ordered` option to `true`. Default:\n `false`.\n\n options.uid: integer (optional)\n Process user identity.\n\n options.gid: integer (optional)\n Process group identity.\n\n options.maxBuffer: integer (optional)\n Max child process `stdio` buffer size. This option is only applied when\n `options.ordered = true`. Default: `200*1024*1024`.\n\n clbk: Function\n Callback to invoke after executing all scripts.\n\n","parseJSON":"\nparseJSON( str[, reviver] )\n Attempts to parse a string as JSON.\n\n Function behavior differs from `JSON.parse()` as follows:\n\n - throws a `TypeError` if provided any value which is not a string.\n - throws a `TypeError` if provided a `reviver` argument which is not a\n function.\n - returns, rather than throws, a `SyntaxError` if unable to parse a string\n as JSON.\n\n Parameters\n ----------\n str: string\n String to parse.\n\n reviver: Function (optional)\n Transformation function.\n\n Returns\n -------\n out: any|Error\n Parsed value or an error.\n\n Examples\n --------\n > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n { 'beep': 'boop' }\n\n // Provide a reviver:\n > function reviver( key, value ) {\n ... if ( key === '' ) { return value; }\n ... if ( key === 'beep' ) { return value; }\n ... };\n > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n > var out = parseJSON( str, reviver )\n { 'beep': 'boop' }\n\n","pascalcase":"\npascalcase( str )\n Converts a string to Pascal case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Pascal-cased string.\n\n Examples\n --------\n > var out = pascalcase( 'Hello World!' )\n 'HelloWorld'\n > out = pascalcase( 'beep boop' )\n 'BeepBoop'\n\n See Also\n --------\n camelcase, constantcase, kebabcase, snakecase","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER\n \n\n // POSIX environment:\n > var path = '/usr/bin:/bin:/usr/sbin';\n > var parts = path.split( PATH_DELIMITER )\n [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n // Windows environment:\n > path = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\n > parts = path.split( PATH_DELIMITER )\n [ 'C:\\\\Windows\\system32', 'C:\\\\Windows' ]\n\n See Also\n --------\n PATH_DELIMITER_POSIX, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_POSIX\n ':'\n > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n > var paths = PATH.split( PATH_DELIMITER_POSIX )\n [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_WIN32\n ';'\n > var PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\n > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n [ 'C:\\\\Windows\\\\system32', 'C:\\\\Windows', 'C:\\\\Program Files\\\\node\\\\' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_POSIX\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n\n Examples\n --------\n > PATH_SEP\n \n\n // Windows environment:\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n // POSIX environment:\n > parts = 'foo/bar/baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP_POSIX, PATH_SEP_WIN32\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n\n Examples\n --------\n > PATH_SEP_POSIX\n '/'\n > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_WIN32\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n\n Examples\n --------\n > PATH_SEP_WIN32\n '\\\\'\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_POSIX\n","pcorrtest":"\npcorrtest( x, y[, options] )\n Computes a Pearson product-moment correlation test between paired samples.\n\n By default, the function performs a t-test for the null hypothesis that the\n data in arrays or typed arrays `x` and `y` is not correlated. A test against\n a different population correlation can be carried out by supplying the `rho`\n option. In this case, a test using the Fisher's z transform is conducted.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Nnumber in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.rho: number (optional)\n Number denoting the correlation under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the Pearson product-moment correlation\n coefficient. The confidence interval is calculated using Fisher's\n z-transform.\n\n out.nullValue: number\n Assumed correlation under H0 (equal to the supplied `rho` option).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var rho = 0.5;\n > var x = new Array( 300 );\n > var y = new Array( 300 );\n > for ( var i = 0; i < 300; i++ ) {\n ... x[ i ] = base.random.normal( 0.0, 1.0 );\n ... y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n ... base.sqrt( 1.0 - (rho*rho) ) );\n ... }\n > var out = pcorrtest( x, y )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 10.115805615994121,\n ci: [ 0.4161679018930295, 0.5853122968949995 ],\n alternative: 'two-sided',\n method: 't-test for Pearson correlation coefficient',\n nullValue: 0,\n pcorr: 0.505582072355616,\n }\n\n // Print output:\n > var table = out.print()\n t-test for Pearson correlation coefficient\n\n Alternative hypothesis: True correlation coefficient is not equal to 0\n\n pValue: 0\n statistic: 9.2106\n 95% confidence interval: [0.3776,0.5544]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n","percentEncode":"\npercentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = percentEncode( '☃' )\n '%E2%98%83'\n\n","PHI":"\nPHI\n Golden ratio.\n\n Examples\n --------\n > PHI\n 1.618033988749895\n\n","PI":"\nPI\n The mathematical constant `π`.\n\n Examples\n --------\n > PI\n 3.141592653589793\n\n See Also\n --------\n TWO_PI\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n\n Examples\n --------\n > PI_SQUARED\n 9.869604401089358\n\n See Also\n --------\n PI\n","pick":"\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n See Also\n --------\n pickBy\n","pickArguments":"\npickArguments( fcn, indices[, thisArg] )\n Returns a function that applies specified arguments to a provided function.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > var bar = pickArguments( foo, [ 0, 2 ] );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n reorderArguments, reverseArguments\n","pickBy":"\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n See Also\n --------\n pick\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n See Also\n --------\n NINF\n","pkg2alias":"\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n The function supports both internal and standalone package names.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n \n > v = pkg2alias( '@stdlib/math-base-special-sin' )\n \n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","pkg2related":"\npkg2related( pkg )\n Returns package names related to a specified package name.\n\n The function supports both internal and standalone package names.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: Array|null\n Related package names.\n\n Examples\n --------\n > var v = pkg2related( '@stdlib/math/base/special/sin' )\n [...]\n > v = pkg2related( '@stdlib/math-base-special-sin' )\n [...]\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","pkg2standalone":"\npkg2standalone( pkg )\n Returns the standalone package name associated with a provided internal\n package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Standalone package name.\n\n Examples\n --------\n > var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n '@stdlib/math-base-special-sin'\n\n See Also\n --------\n alias2pkg, alias2standalone, aliases, pkg2alias, pkg2related\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n See Also\n --------\n ARCH\n","plot":"\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n See Also\n --------\n Plot\n","Plot":"\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n See Also\n --------\n plot\n","pluck":"\npluck( arr, prop[, options] )\n Extracts a property value from each element of an object array.\n\n The function skips `null` and `undefined` array elements.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n prop: string\n Property to access.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. To mutate the\n input data structure (e.g., when input values can be discarded or when\n optimizing memory usage), set the `copy` option to `false`. Default:\n true.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > var out = pluck( arr, 'a' )\n [ 1, 0.5 ]\n\n > arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > out = pluck( arr, 'a', { 'copy': false } )\n [ 1, 0.5 ]\n > var bool = ( arr[ 0 ] === out[ 0 ] )\n true\n\n See Also\n --------\n deepPluck, pick\n","pop":"\npop( collection )\n Removes and returns the last element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = pop( arr )\n [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = pop( arr )\n [ [ 1.0 ], 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = pop( arr )\n [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n See Also\n --------\n push, shift, unshift\n","porterStemmer":"\nporterStemmer( word )\n Extracts the stem of a given word.\n\n Parameters\n ----------\n word: string\n Input word.\n\n Returns\n -------\n out: string\n Word stem.\n\n Examples\n --------\n > var out = porterStemmer( 'walking' )\n 'walk'\n > out = porterStemmer( 'walked' )\n 'walk'\n > out = porterStemmer( 'walks' )\n 'walk'\n > out = porterStemmer( '' )\n ''\n\n","prepend":"\nprepend( collection1, collection2 )\n Adds the elements of one collection to the beginning of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = prepend( arr, [ 6.0, 7.0 ] )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = prepend( arr, [ 3.0, 4.0 ] )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = prepend( arr, [ 2.0, 3.0 ] )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n append, unshift\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str[, fromIndex] )\n Returns the previous extended grapheme cluster break in a string before a\n specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n fromIndex: integer (optional)\n Position. Default: str.length-1.\n\n Returns\n -------\n out: integer\n Previous extended grapheme cluster break position.\n\n Examples\n --------\n > var out = prevGraphemeClusterBreak( 'last man standing', 4 )\n 3\n > out = prevGraphemeClusterBreak( 'presidential election', 8 )\n 7\n > out = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\n 0\n > out = prevGraphemeClusterBreak( '🌷', 1 )\n -1\n\n See Also\n --------\n numGraphemeClusters, nextGraphemeClusterBreak","PRIMES_100K":"\nPRIMES_100K()\n Returns an array containing the first 100,000 prime numbers.\n\n Returns\n -------\n out: Array\n List of primes.\n\n Examples\n --------\n > var list = PRIMES_100K()\n [ 2, 3, 5, ... ]\n\n See Also\n --------\n iterPrimesSeq\n","properties":"\nproperties( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable and non-enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = properties( obj )\n [ 'beep' ]\n\n See Also\n --------\n defineProperties, inheritedProperties, propertiesIn, propertyNames, propertySymbols\n","propertiesIn":"\npropertiesIn( value )\n Returns an array of an object's own and inherited property names and\n symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited property names and symbols.\n\n Examples\n --------\n > var props = propertiesIn( [] )\n\n See Also\n --------\n defineProperties, inheritedProperties, properties, propertyNamesIn, propertySymbolsIn\n","propertyDescriptor":"\npropertyDescriptor( value, property )\n Returns a property descriptor for an object's own property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptor( obj, 'a' )\n {...}\n\n See Also\n --------\n hasOwnProp, defineProperty, propertyDescriptorIn, propertyDescriptors\n","propertyDescriptorIn":"\npropertyDescriptorIn( value, property )\n Returns a property descriptor for an object's own or inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptorIn( obj, 'a' )\n {...}\n\n See Also\n --------\n hasProp, defineProperty, propertyDescriptor, propertyDescriptorsIn\n","propertyDescriptors":"\npropertyDescriptors( value )\n Returns an object's own property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n Property descriptors.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptors( obj )\n { 'a': {...} }\n\n See Also\n --------\n defineProperty, defineProperties, propertyDescriptor, propertyDescriptorsIn, propertyNames, propertySymbols\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value )\n Returns an object's own and inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n An object's own and inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = propertyDescriptorsIn( obj )\n { 'beep': {...}, 'foo': {...}, ... }\n\n See Also\n --------\n defineProperties, propertyDescriptorIn, propertyDescriptors, propertyNamesIn, propertySymbolsIn\n","propertyNames":"\npropertyNames( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable and non-enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNames( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNames, propertyNamesIn, propertySymbols\n","propertyNamesIn":"\npropertyNamesIn( value )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable and non-enumerable\n property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNamesIn( obj )\n e.g., [ 'beep', 'foo', ... ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNamesIn, propertyNames, propertySymbolsIn\n","propertySymbols":"\npropertySymbols( value )\n Returns an array of an object's own symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own symbol properties.\n\n Examples\n --------\n > var s = propertySymbols( {} )\n\n See Also\n --------\n propertyNames, propertySymbolsIn\n","propertySymbolsIn":"\npropertySymbolsIn( value )\n Returns an array of an object's own and inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited symbol properties.\n\n Examples\n --------\n > var s = propertySymbolsIn( [] )\n\n See Also\n --------\n propertyNamesIn, propertySymbols\n","Proxy":"\nProxy( target, handlers )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n\n The following \"traps\" are supported:\n\n - getPrototypeOf( target )\n Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n `instanceof` operator. The method must return an object or `null`.\n\n - setPrototypeOf( target, prototype )\n Trap for `Object.setPrototypeOf()`. The method must return a boolean\n indicating if the prototype was successfully set.\n\n - isExtensible( target )\n Trap for `Object.isExtensible()`. The method must return a boolean.\n\n - preventExtensions( target )\n Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n - getOwnPropertyDescriptor( target, property )\n Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n object or `undefined`.\n\n - defineProperty( target, property, descriptor )\n Trap for `Object.defineProperty()`. The method must return a boolean\n indicating whether the operation succeeded.\n\n - has( target, property )\n Trap for the `in` operator. The method must return a boolean.\n\n - get( target, property, receiver )\n Trap for retrieving property values. The method can return any value.\n\n - set( target, property, value, receiver )\n Trap for setting property values. The method should return a boolean\n indicating whether assignment succeeded.\n\n - deleteProperty( target, property )\n Trap for the `delete` operator. The method must return a boolean\n indicating whether operation succeeded.\n\n - ownKeys( target )\n Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n `Object.getOwnPropertySymbols()`. The method must return an enumerable\n object.\n\n - apply( target, thisArg, argumentsList )\n Trap for a function call. The method can return any value.\n\n - construct( target, argumentsList, newTarget )\n Trap for the `new` operator. The method must return an object.\n\n All traps are optional. If a trap is not defined, the default behavior is to\n forward the operation to the target.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Proxy object.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = new Proxy( {}, h );\n > p.a = 3.14;\n > p.a\n 6.28\n\n\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();\n\n","Proxy.revocable":"\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();","push":"\npush( collection, ...items )\n Adds one or more elements to the end of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = push( arr, 6.0, 7.0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = push( arr, 3.0, 4.0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = push( arr, 1.0, 2.0 )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n pop, shift, unshift\n","quarterOfYear":"\nquarterOfYear( [month] )\n Returns the quarter of the year.\n\n By default, the function returns the quarter of the year for the current\n month in the current year (according to local time). To determine the\n quarter for a particular month, provide either a month or a `Date`\n object.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n Parameters\n ----------\n month: integer|string|Date (optional)\n Month (or `Date`).\n\n Returns\n -------\n out: integer\n Quarter of the year.\n\n Examples\n --------\n > var q = quarterOfYear( new Date() )\n \n > q = quarterOfYear( 4 )\n 2\n > q = quarterOfYear( 'June' )\n 2\n\n // Other ways to supply month:\n > q = quarterOfYear( 'April' )\n 2\n > q = quarterOfYear( 'apr' )\n 2\n\n See Also\n --------\n dayOfYear\n","random.array.arcsine":"\nrandom.array.arcsine( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from an arcsine\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.arcsine.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.arcsine.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.arcsine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.arcsine.PRNG;\n\n\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.arcsine.seed;\n\n\nrandom.array.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.arcsine.seedLength;\n\n\nrandom.array.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.arcsine.state\n \n\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.arcsine.stateLength;\n\n\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.arcsine.byteLength;\n\n See Also\n --------\n base.random.arcsine, random.strided.arcsine\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.arcsine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.arcsine.PRNG;","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.arcsine.seed;","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.arcsine.seedLength;","random.array.arcsine.state":"\nrandom.array.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.arcsine.state\n \n\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n ","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.arcsine.stateLength;","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.arcsine.byteLength;\n\n See Also\n --------\n base.random.arcsine, random.strided.arcsine","random.array.bernoulli":"\nrandom.array.bernoulli( len, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n\nrandom.array.bernoulli.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.bernoulli.assign( 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.bernoulli.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.bernoulli.factory();\n > var out = fcn( 3, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.bernoulli.factory( 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.bernoulli.PRNG;\n\n\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.bernoulli.seed;\n\n\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.bernoulli.seedLength;\n\n\nrandom.array.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.bernoulli.state\n \n\n > out = random.array.bernoulli( 3, 0.5 )\n \n > out = random.array.bernoulli( 3, 0.5 )\n \n\n // Set the state:\n > random.array.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.array.bernoulli( 3, 0.5 )\n \n\n\nrandom.array.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.bernoulli.stateLength;\n\n\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.strided.bernoulli\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.bernoulli.assign( 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.bernoulli.factory();\n > var out = fcn( 3, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.bernoulli.factory( 0.5 );\n > out = fcn( 3 )\n ","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.bernoulli.PRNG;","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.bernoulli.seed;","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.bernoulli.seedLength;","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.bernoulli.state\n \n\n > out = random.array.bernoulli( 3, 0.5 )\n \n > out = random.array.bernoulli( 3, 0.5 )\n \n\n // Set the state:\n > random.array.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.array.bernoulli( 3, 0.5 )\n ","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.bernoulli.stateLength;","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.strided.bernoulli","random.array.beta":"\nrandom.array.beta( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a beta\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n\nrandom.array.beta.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.beta.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.beta.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.beta.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.beta.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.beta.PRNG;\n\n\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.beta.seed;\n\n\nrandom.array.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.beta.seedLength;\n\n\nrandom.array.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.beta.state\n \n\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n\nrandom.array.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.beta.stateLength;\n\n\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.strided.beta\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.beta.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.beta.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.beta.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.beta.PRNG;","random.array.beta.seed":"\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.beta.seed;","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.beta.seedLength;","random.array.beta.state":"\nrandom.array.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.beta.state\n \n\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.array.beta( 3, 2.0, 5.0 )\n ","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.beta.stateLength;","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.strided.beta","random.array.betaprime":"\nrandom.array.betaprime( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n\nrandom.array.betaprime.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.betaprime.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.betaprime.PRNG;\n\n\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.betaprime.seed;\n\n\nrandom.array.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.betaprime.seedLength;\n\n\nrandom.array.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.betaprime.state\n \n\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n\nrandom.array.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.betaprime.stateLength;\n\n\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.strided.betaprime\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.betaprime.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.betaprime.PRNG;","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.betaprime.seed;","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.betaprime.seedLength;","random.array.betaprime.state":"\nrandom.array.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.betaprime.state\n \n\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n ","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.betaprime.stateLength;","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.strided.betaprime","random.array.binomial":"\nrandom.array.binomial( len, n, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a binomial\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n\nrandom.array.binomial.assign( n, p, out )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n Parameters\n ----------\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.binomial.assign( 17, 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.binomial.factory( [n, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n n: number (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.binomial.factory();\n > var out = fcn( 3, 17, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.binomial.factory( 17, 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.binomial.PRNG;\n\n\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.binomial.seed;\n\n\nrandom.array.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.binomial.seedLength;\n\n\nrandom.array.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.binomial.state\n \n\n > out = random.array.binomial( 3, 17, 0.5 )\n \n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Set the state:\n > random.array.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n\nrandom.array.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.binomial.stateLength;\n\n\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.binomial.byteLength;\n\n See Also\n --------\n random.array.negativeBinomial, base.random.binomial\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n, p, out )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n Parameters\n ----------\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.binomial.assign( 17, 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n n: number (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.binomial.factory();\n > var out = fcn( 3, 17, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.binomial.factory( 17, 0.5 );\n > out = fcn( 3 )\n ","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.binomial.PRNG;","random.array.binomial.seed":"\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.binomial.seed;","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.binomial.seedLength;","random.array.binomial.state":"\nrandom.array.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.binomial.state\n \n\n > out = random.array.binomial( 3, 17, 0.5 )\n \n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Set the state:\n > random.array.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.binomial( 3, 17, 0.5 )\n ","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.binomial.stateLength;","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.binomial.byteLength;\n\n See Also\n --------\n random.array.negativeBinomial, base.random.binomial","random.array.cauchy":"\nrandom.array.cauchy( len, x0, gamma[, options] )\n Returns an array containing pseudorandom numbers drawn from a Cauchy\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cauchy.assign( x0, gamma, out )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n gamma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cauchy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cauchy.PRNG;\n\n\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cauchy.seed;\n\n\nrandom.array.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cauchy.seedLength;\n\n\nrandom.array.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cauchy.state\n \n\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cauchy.stateLength;\n\n\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cauchy.byteLength;\n\n See Also\n --------\n base.random.cauchy\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0, gamma, out )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n gamma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cauchy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cauchy.PRNG;","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cauchy.seed;","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cauchy.seedLength;","random.array.cauchy.state":"\nrandom.array.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cauchy.state\n \n\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n ","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cauchy.stateLength;","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cauchy.byteLength;\n\n See Also\n --------\n base.random.cauchy","random.array.chi":"\nrandom.array.chi( len, k[, options] )\n Returns an array containing pseudorandom numbers drawn from a chi\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n\nrandom.array.chi.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chi.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.chi.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chi.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chi.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chi.PRNG;\n\n\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chi.seed;\n\n\nrandom.array.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chi.seedLength;\n\n\nrandom.array.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chi.state\n \n\n > out = random.array.chi( 3, 2.0 )\n \n > out = random.array.chi( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chi( 3, 2.0 )\n \n\n\nrandom.array.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chi.stateLength;\n\n\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.strided.chi\n","random.array.chi.assign":"\nrandom.array.chi.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chi.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.chi.factory":"\nrandom.array.chi.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chi.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chi.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chi.PRNG;","random.array.chi.seed":"\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chi.seed;","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chi.seedLength;","random.array.chi.state":"\nrandom.array.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chi.state\n \n\n > out = random.array.chi( 3, 2.0 )\n \n > out = random.array.chi( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chi( 3, 2.0 )\n ","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chi.stateLength;","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.strided.chi","random.array.chisquare":"\nrandom.array.chisquare( len, k[, options] )\n Returns an array containing pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n\nrandom.array.chisquare.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chisquare.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.chisquare.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chisquare.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chisquare.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chisquare.PRNG;\n\n\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chisquare.seed;\n\n\nrandom.array.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chisquare.seedLength;\n\n\nrandom.array.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chisquare.state\n \n\n > out = random.array.chisquare( 3, 2.0 )\n \n > out = random.array.chisquare( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chisquare( 3, 2.0 )\n \n\n\nrandom.array.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chisquare.stateLength;\n\n\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.strided.chisquare\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chisquare.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chisquare.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chisquare.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chisquare.PRNG;","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chisquare.seed;","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chisquare.seedLength;","random.array.chisquare.state":"\nrandom.array.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chisquare.state\n \n\n > out = random.array.chisquare( 3, 2.0 )\n \n > out = random.array.chisquare( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chisquare( 3, 2.0 )\n ","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chisquare.stateLength;","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.strided.chisquare","random.array.cosine":"\nrandom.array.cosine( len, mu, s[, options] )\n Returns an array containing pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cosine.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cosine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.cosine.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cosine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cosine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cosine.PRNG;\n\n\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cosine.seed;\n\n\nrandom.array.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cosine.seedLength;\n\n\nrandom.array.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cosine.state\n \n\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cosine.stateLength;\n\n\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cosine.byteLength;\n\n See Also\n --------\n base.random.cosine, random.strided.cosine\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cosine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cosine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cosine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cosine.PRNG;","random.array.cosine.seed":"\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cosine.seed;","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cosine.seedLength;","random.array.cosine.state":"\nrandom.array.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cosine.state\n \n\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cosine( 3, 2.0, 5.0 )\n ","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cosine.stateLength;","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cosine.byteLength;\n\n See Also\n --------\n base.random.cosine, random.strided.cosine","random.array.discreteUniform":"\nrandom.array.discreteUniform( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n\nrandom.array.discreteUniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.discreteUniform.assign( -10, 10, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.discreteUniform.factory();\n > var out = fcn( 3, -10, 10 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.discreteUniform.factory( -10, 10 );\n > out = fcn( 3 )\n \n\n\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.discreteUniform.PRNG;\n\n\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.discreteUniform.seed;\n\n\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.discreteUniform.seedLength;\n\n\nrandom.array.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.array.discreteUniform.state\n \n\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Set the state:\n > random.array.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.discreteUniform.stateLength;\n\n\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.discreteUniform.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.discreteUniform.assign( -10, 10, x )\n \n > var bool = ( out === x )\n true","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.discreteUniform.factory();\n > var out = fcn( 3, -10, 10 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.discreteUniform.factory( -10, 10 );\n > out = fcn( 3 )\n ","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.discreteUniform.PRNG;","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.discreteUniform.seed;","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.discreteUniform.seedLength;","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.array.discreteUniform.state\n \n\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Set the state:\n > random.array.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.discreteUniform( 3, -10, 10 )\n ","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.discreteUniform.stateLength;","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.discreteUniform.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform","random.array.erlang":"\nrandom.array.erlang( len, k, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from an Erlang\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n\nrandom.array.erlang.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.erlang.assign( 2, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.erlang.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.erlang.factory();\n > var out = fcn( 3, 2, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.erlang.factory( 2, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.erlang.PRNG;\n\n\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.erlang.seed;\n\n\nrandom.array.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.erlang.seedLength;\n\n\nrandom.array.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.erlang.state\n \n\n > out = random.array.erlang( 3, 2, 5.0 )\n \n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Set the state:\n > random.array.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n\nrandom.array.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.erlang.stateLength;\n\n\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.erlang.byteLength;\n\n See Also\n --------\n base.random.erlang\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.erlang.assign( 2, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.erlang.factory();\n > var out = fcn( 3, 2, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.erlang.factory( 2, 5.0 );\n > out = fcn( 3 )\n ","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.erlang.PRNG;","random.array.erlang.seed":"\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.erlang.seed;","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.erlang.seedLength;","random.array.erlang.state":"\nrandom.array.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.erlang.state\n \n\n > out = random.array.erlang( 3, 2, 5.0 )\n \n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Set the state:\n > random.array.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.array.erlang( 3, 2, 5.0 )\n ","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.erlang.stateLength;","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.erlang.byteLength;\n\n See Also\n --------\n base.random.erlang","random.array.exponential":"\nrandom.array.exponential( len, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n lambda: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n\nrandom.array.exponential.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.exponential.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.exponential.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.exponential.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.exponential.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.exponential.PRNG;\n\n\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.exponential.seed;\n\n\nrandom.array.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.exponential.seedLength;\n\n\nrandom.array.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.exponential.state\n \n\n > out = random.array.exponential( 3, 2.0 )\n \n > out = random.array.exponential( 3, 2.0 )\n \n\n // Set the state:\n > random.array.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.array.exponential( 3, 2.0 )\n \n\n\nrandom.array.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.exponential.stateLength;\n\n\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.strided.exponential\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.exponential.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.exponential.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.exponential.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.exponential.PRNG;","random.array.exponential.seed":"\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.exponential.seed;","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.exponential.seedLength;","random.array.exponential.state":"\nrandom.array.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.exponential.state\n \n\n > out = random.array.exponential( 3, 2.0 )\n \n > out = random.array.exponential( 3, 2.0 )\n \n\n // Set the state:\n > random.array.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.array.exponential( 3, 2.0 )\n ","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.exponential.stateLength;","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.strided.exponential","random.array.f":"\nrandom.array.f( len, d1, d2[, options] )\n Returns an array containing pseudorandom numbers drawn from an F\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n\nrandom.array.f.assign( d1, d2, out )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.f.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.f.factory( [d1, d2, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.f.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.f.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.f.PRNG;\n\n\nrandom.array.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.f.seed;\n\n\nrandom.array.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.f.seedLength;\n\n\nrandom.array.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.f.state\n \n\n > out = random.array.f( 3, 2.0, 5.0 )\n \n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.f.state = state;\n\n // Regenerate a previous array:\n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n\nrandom.array.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.f.stateLength;\n\n\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.f.byteLength;\n\n See Also\n --------\n base.random.f\n","random.array.f.assign":"\nrandom.array.f.assign( d1, d2, out )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.f.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.f.factory":"\nrandom.array.f.factory( [d1, d2, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.f.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.f.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.f.PRNG":"\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.f.PRNG;","random.array.f.seed":"\nrandom.array.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.f.seed;","random.array.f.seedLength":"\nrandom.array.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.f.seedLength;","random.array.f.state":"\nrandom.array.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.f.state\n \n\n > out = random.array.f( 3, 2.0, 5.0 )\n \n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.f.state = state;\n\n // Regenerate a previous array:\n > out = random.array.f( 3, 2.0, 5.0 )\n ","random.array.f.stateLength":"\nrandom.array.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.f.stateLength;","random.array.f.byteLength":"\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.f.byteLength;\n\n See Also\n --------\n base.random.f","random.array.frechet":"\nrandom.array.frechet( len, alpha, s, m[, options] )\n Returns an array containing pseudorandom numbers drawn from a Fréchet\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.frechet.assign( alpha, s, m, out )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.frechet.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.frechet.PRNG;\n\n\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.frechet.seed;\n\n\nrandom.array.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.frechet.seedLength;\n\n\nrandom.array.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.frechet.state\n \n\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.frechet.stateLength;\n\n\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha, s, m, out )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.frechet.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n ","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.frechet.PRNG;","random.array.frechet.seed":"\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.frechet.seed;","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.frechet.seedLength;","random.array.frechet.state":"\nrandom.array.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.frechet.state\n \n\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n ","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.frechet.stateLength;","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet","random.array.gamma":"\nrandom.array.gamma( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a gamma\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gamma.PRNG;\n\n\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gamma.seed;\n\n\nrandom.array.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gamma.seedLength;\n\n\nrandom.array.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gamma.state\n \n\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gamma.stateLength;\n\n\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gamma.byteLength;\n\n See Also\n --------\n base.random.gamma, random.strided.gamma\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gamma.PRNG;","random.array.gamma.seed":"\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gamma.seed;","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gamma.seedLength;","random.array.gamma.state":"\nrandom.array.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gamma.state\n \n\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gamma( 3, 2.0, 5.0 )\n ","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gamma.stateLength;","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gamma.byteLength;\n\n See Also\n --------\n base.random.gamma, random.strided.gamma","random.array.geometric":"\nrandom.array.geometric( len, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n\nrandom.array.geometric.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.geometric.assign( 0.01, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.geometric.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.geometric.factory();\n > var out = fcn( 3, 0.01 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.geometric.factory( 0.01 );\n > out = fcn( 3 )\n \n\n\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.geometric.PRNG;\n\n\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.geometric.seed;\n\n\nrandom.array.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.geometric.seedLength;\n\n\nrandom.array.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.array.geometric.state\n \n\n > out = random.array.geometric( 3, 0.01 )\n \n > out = random.array.geometric( 3, 0.01 )\n \n\n // Set the state:\n > random.array.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.geometric( 3, 0.01 )\n \n\n\nrandom.array.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.geometric.stateLength;\n\n\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.strided.geometric\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.geometric.assign( 0.01, x )\n \n > var bool = ( out === x )\n true","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.geometric.factory();\n > var out = fcn( 3, 0.01 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.geometric.factory( 0.01 );\n > out = fcn( 3 )\n ","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.geometric.PRNG;","random.array.geometric.seed":"\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.geometric.seed;","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.geometric.seedLength;","random.array.geometric.state":"\nrandom.array.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.array.geometric.state\n \n\n > out = random.array.geometric( 3, 0.01 )\n \n > out = random.array.geometric( 3, 0.01 )\n \n\n // Set the state:\n > random.array.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.geometric( 3, 0.01 )\n ","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.geometric.stateLength;","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.strided.geometric","random.array.gumbel":"\nrandom.array.gumbel( len, mu, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a Gumbel\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gumbel.assign( mu, beta, out )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gumbel.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gumbel.PRNG;\n\n\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gumbel.seed;\n\n\nrandom.array.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gumbel.seedLength;\n\n\nrandom.array.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gumbel.state\n \n\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gumbel.stateLength;\n\n\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gumbel.byteLength;\n\n See Also\n --------\n base.random.gumbel\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu, beta, out )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gumbel.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gumbel.PRNG;","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gumbel.seed;","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gumbel.seedLength;","random.array.gumbel.state":"\nrandom.array.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gumbel.state\n \n\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n ","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gumbel.stateLength;","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gumbel.byteLength;\n\n See Also\n --------\n base.random.gumbel","random.array.hypergeometric":"\nrandom.array.hypergeometric( len, N, K, n[, options] )\n Returns an array containing pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n\nrandom.array.hypergeometric.assign( N, K, n, out )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n N: number (optional)\n Population size.\n\n K: number (optional)\n Subpopulation size.\n\n n: number (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.hypergeometric.factory();\n > var out = fcn( 3, 20, 10, 7 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n > out = fcn( 3 )\n \n\n\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.hypergeometric.PRNG;\n\n\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.hypergeometric.seed;\n\n\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.hypergeometric.seedLength;\n\n\nrandom.array.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.array.hypergeometric.state\n \n\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Set the state:\n > random.array.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.hypergeometric.stateLength;\n\n\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N, K, n, out )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n \n > var bool = ( out === x )\n true","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n N: number (optional)\n Population size.\n\n K: number (optional)\n Subpopulation size.\n\n n: number (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.hypergeometric.factory();\n > var out = fcn( 3, 20, 10, 7 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n > out = fcn( 3 )\n ","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.hypergeometric.PRNG;","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.hypergeometric.seed;","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.hypergeometric.seedLength;","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.array.hypergeometric.state\n \n\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Set the state:\n > random.array.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n ","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.hypergeometric.stateLength;","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric","random.array.invgamma":"\nrandom.array.invgamma( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.invgamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.invgamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.invgamma.PRNG;\n\n\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.invgamma.seed;\n\n\nrandom.array.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.invgamma.seedLength;\n\n\nrandom.array.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.invgamma.state\n \n\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.invgamma.stateLength;\n\n\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.invgamma.byteLength;\n\n See Also\n --------\n base.random.invgamma, random.strided.invgamma\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.invgamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.invgamma.PRNG;","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.invgamma.seed;","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.invgamma.seedLength;","random.array.invgamma.state":"\nrandom.array.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.invgamma.state\n \n\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n ","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.invgamma.stateLength;","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.invgamma.byteLength;\n\n See Also\n --------\n base.random.invgamma, random.strided.invgamma","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n double bounded distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.kumaraswamy.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.kumaraswamy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.kumaraswamy.PRNG;\n\n\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.kumaraswamy.seed;\n\n\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.seedLength;\n\n\nrandom.array.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.kumaraswamy.state\n \n\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.stateLength;\n\n\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.kumaraswamy.byteLength;\n\n See Also\n --------\n base.random.kumaraswamy\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.kumaraswamy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.kumaraswamy.PRNG;","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.kumaraswamy.seed;","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.seedLength;","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.kumaraswamy.state\n \n\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n ","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.stateLength;","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.kumaraswamy.byteLength;\n\n See Also\n --------\n base.random.kumaraswamy","random.array.laplace":"\nrandom.array.laplace( len, mu, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n\nrandom.array.laplace.assign( mu, b, out )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.laplace.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.laplace.factory( [mu, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.laplace.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.laplace.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.laplace.PRNG;\n\n\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.laplace.seed;\n\n\nrandom.array.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.laplace.seedLength;\n\n\nrandom.array.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.laplace.state\n \n\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n\nrandom.array.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.laplace.stateLength;\n\n\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.laplace.byteLength;\n\n See Also\n --------\n base.random.laplace\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu, b, out )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.laplace.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.laplace.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.laplace.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.laplace.PRNG;","random.array.laplace.seed":"\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.laplace.seed;","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.laplace.seedLength;","random.array.laplace.state":"\nrandom.array.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.laplace.state\n \n\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.array.laplace( 3, 2.0, 5.0 )\n ","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.laplace.stateLength;","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.laplace.byteLength;\n\n See Also\n --------\n base.random.laplace","random.array.levy":"\nrandom.array.levy( len, mu, c[, options] )\n Returns an array containing pseudorandom numbers drawn from a Lévy\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.levy.assign( mu, c, out )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.levy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.levy.factory( [mu, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.levy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.levy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.levy.PRNG;\n\n\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.levy.seed;\n\n\nrandom.array.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.levy.seedLength;\n\n\nrandom.array.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.levy.state\n \n\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.levy.stateLength;\n\n\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.levy.byteLength;\n\n See Also\n --------\n base.random.levy\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu, c, out )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.levy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.levy.factory":"\nrandom.array.levy.factory( [mu, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.levy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.levy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.levy.PRNG;","random.array.levy.seed":"\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.levy.seed;","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.levy.seedLength;","random.array.levy.state":"\nrandom.array.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.levy.state\n \n\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.levy( 3, 2.0, 5.0 )\n ","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.levy.stateLength;","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.levy.byteLength;\n\n See Also\n --------\n base.random.levy","random.array.logistic":"\nrandom.array.logistic( len, mu, s[, options] )\n Returns an array containing pseudorandom numbers drawn from a logistic\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n\nrandom.array.logistic.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n Parameters\n ----------\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.logistic.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.logistic.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.logistic.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.logistic.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.logistic.PRNG;\n\n\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.logistic.seed;\n\n\nrandom.array.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.logistic.seedLength;\n\n\nrandom.array.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.logistic.state\n \n\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n\nrandom.array.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.logistic.stateLength;\n\n\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.logistic.byteLength;\n\n See Also\n --------\n base.random.logistic\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n Parameters\n ----------\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.logistic.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.logistic.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.logistic.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.logistic.PRNG;","random.array.logistic.seed":"\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.logistic.seed;","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.logistic.seedLength;","random.array.logistic.state":"\nrandom.array.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.logistic.state\n \n\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.array.logistic( 3, 2.0, 5.0 )\n ","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.logistic.stateLength;","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.logistic.byteLength;\n\n See Also\n --------\n base.random.logistic","random.array.lognormal":"\nrandom.array.lognormal( len, mu, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.lognormal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.lognormal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.lognormal.PRNG;\n\n\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.lognormal.seed;\n\n\nrandom.array.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.lognormal.seedLength;\n\n\nrandom.array.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.lognormal.state\n \n\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.lognormal.stateLength;\n\n\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.lognormal.byteLength;\n\n See Also\n --------\n base.random.lognormal, random.strided.lognormal\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.lognormal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.lognormal.PRNG;","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.lognormal.seed;","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.lognormal.seedLength;","random.array.lognormal.state":"\nrandom.array.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.lognormal.state\n \n\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n ","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.lognormal.stateLength;","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.lognormal.byteLength;\n\n See Also\n --------\n base.random.lognormal, random.strided.lognormal","random.array.minstd":"\nrandom.array.minstd( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n\nrandom.array.minstd.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd.normalized( 3 )\n \n\n\nrandom.array.minstd.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstd.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstd.PRNG;\n\n\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstd.seed;\n\n\nrandom.array.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstd.seedLength;\n\n\nrandom.array.minstd.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstd.state;\n\n > out = random.array.minstd( 3 )\n \n > out = random.array.minstd( 3 )\n \n\n // Set the state:\n > random.array.minstd.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstd( 3 )\n \n\n\nrandom.array.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstd.stateLength;\n\n\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstd.byteLength;\n\n See Also\n --------\n random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd.normalized( 3 )\n ","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstd.factory();\n > var out = fcn( 3 )\n ","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstd.PRNG;","random.array.minstd.seed":"\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstd.seed;","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstd.seedLength;","random.array.minstd.state":"\nrandom.array.minstd.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstd.state;\n\n > out = random.array.minstd( 3 )\n \n > out = random.array.minstd( 3 )\n \n\n // Set the state:\n > random.array.minstd.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstd( 3 )\n ","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstd.stateLength;","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstd.byteLength;\n\n See Also\n --------\n random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n\nrandom.array.minstdShuffle.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle.normalized( 3 )\n \n\n\nrandom.array.minstdShuffle.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstdShuffle.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstdShuffle.PRNG;\n\n\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstdShuffle.seed;\n\n\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.seedLength;\n\n\nrandom.array.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstdShuffle.state;\n\n > out = random.array.minstdShuffle( 3 )\n \n > out = random.array.minstdShuffle( 3 )\n \n\n // Set the state:\n > random.array.minstdShuffle.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstdShuffle( 3 )\n \n\n\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.stateLength;\n\n\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstdShuffle.byteLength;\n\n See Also\n --------\n random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle.normalized( 3 )\n ","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstdShuffle.factory();\n > var out = fcn( 3 )\n ","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstdShuffle.PRNG;","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstdShuffle.seed;","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.seedLength;","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstdShuffle.state;\n\n > out = random.array.minstdShuffle( 3 )\n \n > out = random.array.minstdShuffle( 3 )\n \n\n // Set the state:\n > random.array.minstdShuffle.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstdShuffle( 3 )\n ","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.stateLength;","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstdShuffle.byteLength;\n\n See Also\n --------\n random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle","random.array.mt19937":"\nrandom.array.mt19937( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[0, 4294967295]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n\nrandom.array.mt19937.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937.normalized( 3 )\n \n\n\nrandom.array.mt19937.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.mt19937.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.mt19937.PRNG;\n\n\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.mt19937.seed;\n\n\nrandom.array.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.mt19937.seedLength;\n\n\nrandom.array.mt19937.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.mt19937.state;\n\n > out = random.array.mt19937( 3 )\n \n > out = random.array.mt19937( 3 )\n \n\n // Set the state:\n > random.array.mt19937.state = state;\n\n // Regenerate a previous array:\n > out = random.array.mt19937( 3 )\n \n\n\nrandom.array.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.mt19937.stateLength;\n\n\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.mt19937.byteLength;\n\n See Also\n --------\n random.array.randu, base.random.mt19937, random.strided.mt19937\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937.normalized( 3 )\n ","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.mt19937.factory();\n > var out = fcn( 3 )\n ","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.mt19937.PRNG;","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.mt19937.seed;","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.mt19937.seedLength;","random.array.mt19937.state":"\nrandom.array.mt19937.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.mt19937.state;\n\n > out = random.array.mt19937( 3 )\n \n > out = random.array.mt19937( 3 )\n \n\n // Set the state:\n > random.array.mt19937.state = state;\n\n // Regenerate a previous array:\n > out = random.array.mt19937( 3 )\n ","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.mt19937.stateLength;","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.mt19937.byteLength;\n\n See Also\n --------\n random.array.randu, base.random.mt19937, random.strided.mt19937","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len, r, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a negative\n binomial distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n\nrandom.array.negativeBinomial.assign( r, p, out )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.negativeBinomial.factory();\n > var out = fcn( 3, 10, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.negativeBinomial.PRNG;\n\n\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.negativeBinomial.seed;\n\n\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.seedLength;\n\n\nrandom.array.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.negativeBinomial.state\n \n\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Set the state:\n > random.array.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.stateLength;\n\n\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.negativeBinomial.byteLength;\n\n See Also\n --------\n random.array.binomial, base.random.negativeBinomial\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r, p, out )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.negativeBinomial.factory();\n > var out = fcn( 3, 10, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n > out = fcn( 3 )\n ","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.negativeBinomial.PRNG;","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.negativeBinomial.seed;","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.seedLength;","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.negativeBinomial.state\n \n\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Set the state:\n > random.array.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n ","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.stateLength;","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.negativeBinomial.byteLength;\n\n See Also\n --------\n random.array.binomial, base.random.negativeBinomial","random.array.normal":"\nrandom.array.normal( len, mu, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a normal\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.normal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.normal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.normal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n sigma: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.normal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.normal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.normal.PRNG;\n\n\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.normal.seed;\n\n\nrandom.array.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.normal.seedLength;\n\n\nrandom.array.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.normal.state\n \n\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.normal.stateLength;\n\n\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.normal.byteLength;\n\n See Also\n --------\n base.random.normal, random.strided.normal\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.normal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.normal.factory":"\nrandom.array.normal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n sigma: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.normal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.normal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.normal.PRNG;","random.array.normal.seed":"\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.normal.seed;","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.normal.seedLength;","random.array.normal.state":"\nrandom.array.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.normal.state\n \n\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.normal( 3, 2.0, 5.0 )\n ","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.normal.stateLength;","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.normal.byteLength;\n\n See Also\n --------\n base.random.normal, random.strided.normal","random.array.pareto1":"\nrandom.array.pareto1( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n\nrandom.array.pareto1.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.pareto1.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.pareto1.PRNG;\n\n\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.pareto1.seed;\n\n\nrandom.array.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.pareto1.seedLength;\n\n\nrandom.array.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.pareto1.state\n \n\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n\nrandom.array.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.pareto1.stateLength;\n\n\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.pareto1.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.pareto1.PRNG;","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.pareto1.seed;","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.pareto1.seedLength;","random.array.pareto1.state":"\nrandom.array.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.pareto1.state\n \n\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n ","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.pareto1.stateLength;","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1","random.array.poisson":"\nrandom.array.poisson( len, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from a Poisson\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n lambda: number\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n\nrandom.array.poisson.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n Parameters\n ----------\n lambda: number\n Mean parameter.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.poisson.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.poisson.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.poisson.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.poisson.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.poisson.PRNG;\n\n\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.poisson.seed;\n\n\nrandom.array.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.poisson.seedLength;\n\n\nrandom.array.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.poisson.state\n \n\n > out = random.array.poisson( 3, 2.0 )\n \n > out = random.array.poisson( 3, 2.0 )\n \n\n // Set the state:\n > random.array.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.array.poisson( 3, 2.0 )\n \n\n\nrandom.array.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.poisson.stateLength;\n\n\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.strided.poisson\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n Parameters\n ----------\n lambda: number\n Mean parameter.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.poisson.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.poisson.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.poisson.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.poisson.PRNG;","random.array.poisson.seed":"\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.poisson.seed;","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.poisson.seedLength;","random.array.poisson.state":"\nrandom.array.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.poisson.state\n \n\n > out = random.array.poisson( 3, 2.0 )\n \n > out = random.array.poisson( 3, 2.0 )\n \n\n // Set the state:\n > random.array.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.array.poisson( 3, 2.0 )\n ","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.poisson.stateLength;","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.strided.poisson","random.array.randu":"\nrandom.array.randu( len[, options] )\n Returns an array containing uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n\nrandom.array.randu.factory( [options] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.randu.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.randu.PRNG;\n\n\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.randu.seed;\n\n\nrandom.array.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.randu.seedLength;\n\n\nrandom.array.randu.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.randu.state;\n\n > out = random.array.randu( 3 )\n \n > out = random.array.randu( 3 )\n \n\n // Set the state:\n > random.array.randu.state = state;\n\n // Regenerate a previous array:\n > out = random.array.randu( 3 )\n \n\n\nrandom.array.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.randu.stateLength;\n\n\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.randu.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.randu, random.strided.randu\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.randu.factory();\n > var out = fcn( 3 )\n ","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.randu.PRNG;","random.array.randu.seed":"\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.randu.seed;","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.randu.seedLength;","random.array.randu.state":"\nrandom.array.randu.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.randu.state;\n\n > out = random.array.randu( 3 )\n \n > out = random.array.randu( 3 )\n \n\n // Set the state:\n > random.array.randu.state = state;\n\n // Regenerate a previous array:\n > out = random.array.randu( 3 )\n ","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.randu.stateLength;","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.randu.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.randu, random.strided.randu","random.array.rayleigh":"\nrandom.array.rayleigh( len, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n sigma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n\nrandom.array.rayleigh.assign( sigma, out )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.rayleigh.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.rayleigh.factory( [sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.rayleigh.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.rayleigh.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.rayleigh.PRNG;\n\n\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.rayleigh.seed;\n\n\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.rayleigh.seedLength;\n\n\nrandom.array.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.rayleigh.state\n \n\n > out = random.array.rayleigh( 3, 2.0 )\n \n > out = random.array.rayleigh( 3, 2.0 )\n \n\n // Set the state:\n > random.array.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.array.rayleigh( 3, 2.0 )\n \n\n\nrandom.array.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.rayleigh.stateLength;\n\n\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.strided.rayleigh\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma, out )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.rayleigh.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.rayleigh.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.rayleigh.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.rayleigh.PRNG;","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.rayleigh.seed;","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.rayleigh.seedLength;","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.rayleigh.state\n \n\n > out = random.array.rayleigh( 3, 2.0 )\n \n > out = random.array.rayleigh( 3, 2.0 )\n \n\n // Set the state:\n > random.array.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.array.rayleigh( 3, 2.0 )\n ","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.rayleigh.stateLength;","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.strided.rayleigh","random.array.t":"\nrandom.array.t( len, v[, options] )\n Returns an array containing pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n\nrandom.array.t.assign( v, out )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.t.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.t.factory( [v, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.t.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.t.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.t.PRNG;\n\n\nrandom.array.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.t.seed;\n\n\nrandom.array.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.t.seedLength;\n\n\nrandom.array.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.t.state\n \n\n > out = random.array.t( 3, 2.0 )\n \n > out = random.array.t( 3, 2.0 )\n \n\n // Set the state:\n > random.array.t.state = state;\n\n // Regenerate a previous array:\n > out = random.array.t( 3, 2.0 )\n \n\n\nrandom.array.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.t.stateLength;\n\n\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.t.byteLength;\n\n See Also\n --------\n base.random.t, random.strided.t\n","random.array.t.assign":"\nrandom.array.t.assign( v, out )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.t.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.t.factory":"\nrandom.array.t.factory( [v, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.t.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.t.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.t.PRNG":"\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.t.PRNG;","random.array.t.seed":"\nrandom.array.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.t.seed;","random.array.t.seedLength":"\nrandom.array.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.t.seedLength;","random.array.t.state":"\nrandom.array.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.t.state\n \n\n > out = random.array.t( 3, 2.0 )\n \n > out = random.array.t( 3, 2.0 )\n \n\n // Set the state:\n > random.array.t.state = state;\n\n // Regenerate a previous array:\n > out = random.array.t( 3, 2.0 )\n ","random.array.t.stateLength":"\nrandom.array.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.t.stateLength;","random.array.t.byteLength":"\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.t.byteLength;\n\n See Also\n --------\n base.random.t, random.strided.t","random.array.triangular":"\nrandom.array.triangular( len, a, b, c[, options] )\n Returns an array containing pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.triangular.assign( a, b, c, out )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.triangular.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.triangular.PRNG;\n\n\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.triangular.seed;\n\n\nrandom.array.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.triangular.seedLength;\n\n\nrandom.array.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.triangular.state\n \n\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.triangular.stateLength;\n\n\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a, b, c, out )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.triangular.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n ","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.triangular.PRNG;","random.array.triangular.seed":"\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.triangular.seed;","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.triangular.seedLength;","random.array.triangular.state":"\nrandom.array.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.triangular.state\n \n\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n ","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.triangular.stateLength;","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular","random.array.uniform":"\nrandom.array.uniform( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n\nrandom.array.uniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.uniform.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.uniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.uniform.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.uniform.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.uniform.PRNG;\n\n\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.uniform.seed;\n\n\nrandom.array.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.uniform.seedLength;\n\n\nrandom.array.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.uniform.state\n \n\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n\nrandom.array.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.uniform.stateLength;\n\n\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.uniform.byteLength;\n\n See Also\n --------\n random.array.discreteUniform, base.random.uniform, random.strided.uniform\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.uniform.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.uniform.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.uniform.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.uniform.PRNG;","random.array.uniform.seed":"\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.uniform.seed;","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.uniform.seedLength;","random.array.uniform.state":"\nrandom.array.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.uniform.state\n \n\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.uniform( 3, 2.0, 5.0 )\n ","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.uniform.stateLength;","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.uniform.byteLength;\n\n See Also\n --------\n random.array.discreteUniform, base.random.uniform, random.strided.uniform","random.array.weibull":"\nrandom.array.weibull( len, k, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from a Weibull\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n\nrandom.array.weibull.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.weibull.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.weibull.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n lambda: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.weibull.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.weibull.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.weibull.PRNG;\n\n\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.weibull.seed;\n\n\nrandom.array.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.weibull.seedLength;\n\n\nrandom.array.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.weibull.state\n \n\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n\nrandom.array.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.weibull.stateLength;\n\n\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull, random.strided.weibull\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.weibull.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n lambda: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.weibull.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.weibull.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.weibull.PRNG;","random.array.weibull.seed":"\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.weibull.seed;","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.weibull.seedLength;","random.array.weibull.state":"\nrandom.array.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.weibull.state\n \n\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.array.weibull( 3, 2.0, 5.0 )\n ","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.weibull.stateLength;","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull, random.strided.weibull","random.iterators.arcsine":"\nrandom.iterators.arcsine( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.arcsine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.arcsine\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.bernoulli( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.bernoulli\n","random.iterators.beta":"\nrandom.iterators.beta( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.beta( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.beta\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.betaprime( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.betaprime\n","random.iterators.binomial":"\nrandom.iterators.binomial( n, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.binomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.binomial\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.boxMuller();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.boxMuller\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cauchy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cauchy\n","random.iterators.chi":"\nrandom.iterators.chi( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chi( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chi\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chisquare( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chisquare\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cosine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cosine\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned iterator, one must\n seed the provided `prng` (assuming the provided `prng` is seedable). The\n provided PRNG must have `MIN` and `MAX` properties specifying the\n minimum and maximum possible pseudorandom integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.discreteUniform( 0, 3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.discreteUniform\n","random.iterators.erlang":"\nrandom.iterators.erlang( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.erlang( 1, 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.erlang\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.exponential( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.exponential\n","random.iterators.f":"\nrandom.iterators.f( d1, d2[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.f( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.f\n","random.iterators.frechet":"\nrandom.iterators.frechet( α, s, m[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `s <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.frechet\n","random.iterators.gamma":"\nrandom.iterators.gamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gamma\n","random.iterators.geometric":"\nrandom.iterators.geometric( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.geometric( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.geometric\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gumbel( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gumbel\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n throws an error.\n\n If `n > N` or `K > N`, the function throws an error.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.hypergeometric( 20, 10, 7 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.hypergeometric\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.improvedZiggurat();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.improvedZiggurat\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.invgamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.invgamma\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `a <= 0` or `b <= 0`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.kumaraswamy\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.laplace( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.laplace\n","random.iterators.levy":"\nrandom.iterators.levy( μ, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.levy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.levy\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.logistic( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.logistic\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.lognormal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.lognormal\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstd();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstd, random.iterators.minstdShuffle, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstdShuffle();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstd, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Uint32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Uint32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.mt19937();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.mt19937, random.iterators.minstd, random.iterators.minstdShuffle, random.iterators.randi, random.iterators.randu\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.negativeBinomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.negativeBinomial\n","random.iterators.normal":"\nrandom.iterators.normal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.normal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.normal\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.pareto1( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.pareto1\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.poisson( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.poisson\n","random.iterators.randi":"\nrandom.iterators.randi( [options] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randi();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randi, random.iterators.randu\n","random.iterators.randn":"\nrandom.iterators.randn( [options] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: `'improved-ziggurat'`.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randn();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randn\n","random.iterators.randu":"\nrandom.iterators.randu( [options] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randu();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randu, random.iterators.randi\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.rayleigh( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.rayleigh\n","random.iterators.t":"\nrandom.iterators.t( v[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.t( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.t\n","random.iterators.triangular":"\nrandom.iterators.triangular( a, b, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.triangular\n","random.iterators.uniform":"\nrandom.iterators.uniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.uniform( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.uniform\n","random.iterators.weibull":"\nrandom.iterators.weibull( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `k <= 0` or `λ <= 0`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.weibull( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.weibull\n","random.streams.arcsine":"\nrandom.streams.arcsine( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine","random.streams.bernoulli":"\nrandom.streams.bernoulli( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli","random.streams.beta":"\nrandom.streams.beta( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta","random.streams.betaprime":"\nrandom.streams.betaprime( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime","random.streams.binomial":"\nrandom.streams.binomial( n, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial( 20, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn","random.streams.cauchy":"\nrandom.streams.cauchy( x0, γ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy","random.streams.chi":"\nrandom.streams.chi( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi","random.streams.chisquare":"\nrandom.streams.chisquare( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare","random.streams.cosine":"\nrandom.streams.cosine( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform( 2, 5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform","random.streams.erlang":"\nrandom.streams.erlang( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang( 2, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang","random.streams.exponential":"\nrandom.streams.exponential( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential","random.streams.f":"\nrandom.streams.f( d1, d2[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f","random.streams.frechet":"\nrandom.streams.frechet( α, s, m[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Fréchet distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.frechet.factory( [α, s, m,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.frechet.factory( opts );\n\n\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.frechet, random.iterators.frechet\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α, s, m,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.frechet.factory( opts );","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.frechet, random.iterators.frechet","random.streams.gamma":"\nrandom.streams.gamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma","random.streams.geometric":"\nrandom.streams.geometric( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric","random.streams.gumbel":"\nrandom.streams.gumbel( μ, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N, K, n[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric( 5, 3, 2, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.hypergeometric.factory( opts );\n\n\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.hypergeometric, random.iterators.hypergeometric\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.hypergeometric.factory( opts );","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.hypergeometric, random.iterators.hypergeometric","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn","random.streams.invgamma":"\nrandom.streams.invgamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy","random.streams.laplace":"\nrandom.streams.laplace( μ, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace","random.streams.levy":"\nrandom.streams.levy( μ, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy","random.streams.logistic":"\nrandom.streams.logistic( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic","random.streams.lognormal":"\nrandom.streams.lognormal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal","random.streams.minstd":"\nrandom.streams.minstd( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.mt19937":"\nrandom.streams.mt19937( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n Twister pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial","random.streams.normal":"\nrandom.streams.normal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal","random.streams.pareto1":"\nrandom.streams.pareto1( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1","random.streams.poisson":"\nrandom.streams.poisson( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson","random.streams.randi":"\nrandom.streams.randi( [options] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu","random.streams.randn":"\nrandom.streams.randn( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat","random.streams.randu":"\nrandom.streams.randu( [options] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh","random.streams.t":"\nrandom.streams.t( v[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t","random.streams.triangular":"\nrandom.streams.triangular( a, b, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.triangular.factory( opts );\n\n\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.triangular, random.iterators.triangular\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.triangular.factory( opts );","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.triangular, random.iterators.triangular","random.streams.uniform":"\nrandom.streams.uniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform","random.streams.weibull":"\nrandom.streams.weibull( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull","random.strided.arcsine":"\nrandom.strided.arcsine( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.arcsine, random.array.arcsine\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.arcsine, random.array.arcsine","random.strided.bernoulli":"\nrandom.strided.bernoulli( N, p, sp, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.bernoulli.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.bernoulli.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.bernoulli.PRNG;\n\n\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.bernoulli.seed;\n\n\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.bernoulli.seedLength;\n\n\nrandom.strided.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.bernoulli.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.bernoulli.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.bernoulli.stateLength;\n\n\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.array.bernoulli\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n [...]","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.bernoulli.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.5 ], 0, out, 1 )\n [...]","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.bernoulli.PRNG;","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.bernoulli.seed;","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.bernoulli.seedLength;","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.bernoulli.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.bernoulli.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.bernoulli.stateLength;","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.array.bernoulli","random.strided.beta":"\nrandom.strided.beta( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.beta, random.array.beta\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.beta, random.array.beta","random.strided.betaprime":"\nrandom.strided.betaprime( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime","random.strided.chi":"\nrandom.strided.chi( N, k, sk, out, so )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.chi.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chi.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chi.PRNG;\n\n\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chi.seed;\n\n\nrandom.strided.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chi.seedLength;\n\n\nrandom.strided.chi.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chi.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chi.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chi.stateLength;\n\n\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.array.chi\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chi.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chi.PRNG;","random.strided.chi.seed":"\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chi.seed;","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chi.seedLength;","random.strided.chi.state":"\nrandom.strided.chi.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chi.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chi.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chi.stateLength;","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.array.chi","random.strided.chisquare":"\nrandom.strided.chisquare( N, k, sk, out, so )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.chisquare.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chisquare.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chisquare.PRNG;\n\n\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chisquare.seed;\n\n\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chisquare.seedLength;\n\n\nrandom.strided.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chisquare.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chisquare.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chisquare.stateLength;\n\n\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.array.chisquare\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chisquare.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chisquare.PRNG;","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chisquare.seed;","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chisquare.seedLength;","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chisquare.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chisquare.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chisquare.stateLength;","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.array.chisquare","random.strided.cosine":"\nrandom.strided.cosine( N, mu, sm, s, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n [...]\n\n\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n os: integer\n Starting index for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.cosine, random.array.cosine\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n os: integer\n Starting index for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.cosine, random.array.cosine","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform","random.strided.exponential":"\nrandom.strided.exponential( N, lambda, sl, out, so )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.exponential.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.exponential.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.exponential.PRNG;\n\n\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.exponential.seed;\n\n\nrandom.strided.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.exponential.seedLength;\n\n\nrandom.strided.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.exponential.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.exponential.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.exponential.stateLength;\n\n\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.array.exponential\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.exponential.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.exponential.PRNG;","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.exponential.seed;","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.exponential.seedLength;","random.strided.exponential.state":"\nrandom.strided.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.exponential.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.exponential.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.exponential.stateLength;","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.array.exponential","random.strided.gamma":"\nrandom.strided.gamma( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.gamma, random.array.gamma\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.gamma, random.array.gamma","random.strided.geometric":"\nrandom.strided.geometric( N, p, sp, out, so )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.geometric.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.geometric.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.geometric.PRNG;\n\n\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.geometric.seed;\n\n\nrandom.strided.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.geometric.seedLength;\n\n\nrandom.strided.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.geometric.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.geometric.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.geometric.stateLength;\n\n\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.array.geometric\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n [...]","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.geometric.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.01 ], 0, out, 1 )\n [...]","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.geometric.PRNG;","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.geometric.seed;","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.geometric.seedLength;","random.strided.geometric.state":"\nrandom.strided.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.geometric.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.geometric.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.geometric.stateLength;","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.array.geometric","random.strided.invgamma":"\nrandom.strided.invgamma( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.invgamma, random.array.invgamma\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.invgamma, random.array.invgamma","random.strided.lognormal":"\nrandom.strided.lognormal( N, mu, sm, sigma, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n [...]\n\n\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.lognormal, random.array.lognormal\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.lognormal, random.array.lognormal","random.strided.minstd":"\nrandom.strided.minstd( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.minstd.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized( out.length, out, 1 )\n [...]","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n [...]","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu","random.strided.mt19937":"\nrandom.strided.mt19937( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937( out.length, out, 1 )\n [...]\n\n\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.mt19937, random.array.mt19937, random.strided.randu\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized( out.length, out, 1 )\n [...]","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.mt19937, random.array.mt19937, random.strided.randu","random.strided.normal":"\nrandom.strided.normal( N, mu, sm, sigma, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n [...]\n\n\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.normal, random.array.normal\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.normal, random.array.normal","random.strided.poisson":"\nrandom.strided.poisson( N, lambda, sl, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.poisson.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.poisson.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.poisson.PRNG;\n\n\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.poisson.seed;\n\n\nrandom.strided.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.poisson.seedLength;\n\n\nrandom.strided.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.poisson.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.poisson.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.poisson.stateLength;\n\n\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.array.poisson\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.poisson.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.poisson.PRNG;","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.poisson.seed;","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.poisson.seedLength;","random.strided.poisson.state":"\nrandom.strided.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.poisson.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.poisson.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.poisson.stateLength;","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.array.poisson","random.strided.randu":"\nrandom.strided.randu( N, out, so[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu( out.length, out, 1 )\n [...]\n\n\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.randu, random.array.randu, random.strided.uniform\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.randu, random.array.randu, random.strided.uniform","random.strided.rayleigh":"\nrandom.strided.rayleigh( N, sigma, ss, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.rayleigh.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.rayleigh.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.rayleigh.PRNG;\n\n\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.rayleigh.seed;\n\n\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.rayleigh.seedLength;\n\n\nrandom.strided.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.rayleigh.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.rayleigh.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.rayleigh.stateLength;\n\n\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.array.rayleigh\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.rayleigh.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.rayleigh.PRNG;","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.rayleigh.seed;","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.rayleigh.seedLength;","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.rayleigh.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.rayleigh.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.rayleigh.stateLength;","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.array.rayleigh","random.strided.t":"\nrandom.strided.t( N, v, sv, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n ov: integer\n Starting index for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.t.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.t.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.t.PRNG;\n\n\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.t.seed;\n\n\nrandom.strided.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.t.seedLength;\n\n\nrandom.strided.t.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.t.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.t.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.t.stateLength;\n\n\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.t.byteLength;\n\n See Also\n --------\n base.random.t, random.array.t\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n ov: integer\n Starting index for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.t.factory":"\nrandom.strided.t.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.t.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.t.PRNG;","random.strided.t.seed":"\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.t.seed;","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.t.seedLength;","random.strided.t.state":"\nrandom.strided.t.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.t.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.t.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.t.stateLength;","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.t.byteLength;\n\n See Also\n --------\n base.random.t, random.array.t","random.strided.uniform":"\nrandom.strided.uniform( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.uniform, random.array.uniform, random.strided.discreteUniform\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.uniform, random.array.uniform, random.strided.discreteUniform","random.strided.weibull":"\nrandom.strided.weibull( N, k, sk, lambda, sl, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.weibull, random.array.weibull\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.weibull, random.array.weibull","ranks":"\nranks( arr[, options] )\n Computes the sample ranks for the values of an array-like object.\n\n When all elements of the `array` are different, the ranks are uniquely\n determined. When there are equal elements (called *ties*), the `method`\n option determines how they are handled. The default, `'average'`, replaces\n the ranks of the ties by their mean. Other possible options are `'min'` and\n `'max'`, which replace the ranks of the ties by their minimum and maximum,\n respectively. `'dense'` works like `'min'`, with the difference that the\n next highest element after a tie is assigned the next smallest integer.\n Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n the position they appear in.\n\n The `missing` option is used to specify how to handle missing data.\n By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n that missing values are placed last, `'first'` that the are assigned the\n lowest ranks and `'remove'` means that they are removed from the array\n before the ranks are calculated.\n\n Parameters\n ----------\n arr: Array\n Input values.\n\n options: Object (optional)\n Function options.\n\n options.method (optional)\n Method name determining how ties are treated (`average`, `min`, `max`,\n `dense`, or `ordinal`). Default: `'average'`.\n\n options.missing (optional)\n Determines where missing values go (`first`, `last`, or `remove`).\n Default: `'last'`.\n\n options.encoding (optional)\n Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n Returns\n -------\n out: Array\n Array containing the computed ranks for the elements of the input array.\n\n Examples\n --------\n > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n > var out = ranks( arr )\n [ 2, 3, 5, 1, 4 ]\n\n // Ties are averaged:\n > arr = [ 2, 2, 1, 4, 3 ];\n > out = ranks( arr )\n [ 2.5, 2.5, 1, 5, 4 ]\n\n // Missing values are placed last:\n > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n > out = ranks( arr )\n [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n","readDir":"\nreadDir( path, clbk )\n Asynchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n clbk: Function\n Callback to invoke after reading directory contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile\n","readDir.sync":"\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile","readFile":"\nreadFile( file[, options], clbk )\n Asynchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, open, readDir, readJSON, writeFile\n","readFile.sync":"\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, open, readDir, readJSON, writeFile","readFileList":"\nreadFileList( filepaths[, options], clbk )\n Asynchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Each file is represented by an object with the following fields:\n\n - file: file path.\n - data: file contents as either a Buffer or string.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );\n\n","readFileList.sync":"\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );","readJSON":"\nreadJSON( file[, options], clbk )\n Asynchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile\n","readJSON.sync":"\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile","readWASM":"\nreadWASM( file[, options], clbk )\n Asynchronously reads a file as WebAssembly.\n\n The function returns file contents as a Uint8Array.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile\n","readWASM.sync":"\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile","real":"\nreal( z )\n Returns the real component of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var re = real( z )\n 5.0\n\n See Also\n --------\n imag, reim\n","realarray":"\nrealarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = realarray()\n \n > arr = realarray( 'float32' )\n \n\n\nrealarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = realarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = realarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\nrealarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = realarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\nrealarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = realarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\nrealarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = realarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","realarrayCtors":"\nrealarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = realarrayCtors( 'float64' )\n \n > ctor = realarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors, complexarrayCtors\n","realarrayDataTypes":"\nrealarrayDataTypes()\n Returns a list of typed array real-valued data types.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = realarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, complexarrayDataTypes\n","realf":"\nrealf( z )\n Returns the real component of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var re = realf( z )\n 5.0\n\n See Also\n --------\n imagf, real, reimf\n","realmax":"\nrealmax( dtype )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum finite value.\n\n Examples\n --------\n > var m = realmax( 'float16' )\n 65504.0\n > m = realmax( 'float32' )\n 3.4028234663852886e+38\n\n See Also\n --------\n realmin, typemax\n","realmin":"\nrealmin( dtype )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Smallest finite normal value.\n\n Examples\n --------\n > var m = realmin( 'float16' )\n 0.00006103515625\n > m = realmin( 'float32' )\n 1.1754943508222875e-38\n\n See Also\n --------\n realmax, typemin\n","reBasename":"\nreBasename( [platform] )\n Returns a regular expression to capture the last part of a path.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reBasename()\n \n > var RE_POSIX = reBasename( 'posix' );\n > var RE_WIN32 = reBasename( 'win32' );\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var RE = reBasename.REGEXP\n \n\n\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasenamePosix, reBasenameWindows\n","reBasename.REGEXP":"\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var RE = reBasename.REGEXP\n ","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasenamePosix, reBasenameWindows","reBasenamePosix":"\nreBasenamePosix()\n Returns a regular expression to capture the last part of a POSIX path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_BASENAME_POSIX = reBasenamePosix();\n > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n ''\n\n\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasename, reBasenameWindows\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasename, reBasenameWindows","reBasenameWindows":"\nreBasenameWindows()\n Returns a regular expression to capture the last part of a Windows path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_BASENAME_WINDOWS = reBasenameWindows();\n > var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n\n See Also\n --------\n reBasename, reBasenamePosix\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n\n See Also\n --------\n reBasename, reBasenamePosix","reColorHexadecimal":"\nreColorHexadecimal( [mode] )\n Returns a regular expression to match a hexadecimal color.\n\n Parameters\n ----------\n mode: string (optional)\n Color format (`full`, `shorthand`, or `either`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reColorHexadecimal();\n > var bool = RE.test( 'ffffff' )\n true\n > bool = RE.test( '000' )\n false\n > bool = RE.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP.test( '000' )\n false\n > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n false\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n false\n\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP.test( '000' )\n false\n > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n false","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n false\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n false","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n false","reDecimalNumber":"\nreDecimalNumber( [options] )\n Returns a regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to create a capture group for the match.\n Default: false.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDecimalNumber();\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true\n > bool = RE.test( '0.0' )\n true\n > bool = RE.test( '.0' )\n true\n > bool = RE.test( '0' )\n false\n > bool = RE.test( 'beep' )\n false\n\n // Create a RegExp to capture all decimal numbers:\n > var re = reDecimalNumber({ 'flags': 'g' });\n > var str = '1.234 5.6, 7.8';\n > var out = str.match( re )\n [ '1.234', '5.6', '7.8' ]\n\n\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP;\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true\n\n\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP_CAPTURE;\n > var str = '1.02';\n > var out = replace( str, RE, '$1 x $1' )\n '1.02 x 1.02'\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP;\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP_CAPTURE;\n > var str = '1.02';\n > var out = replace( str, RE, '$1 x $1' )\n '1.02 x 1.02'","reDirname":"\nreDirname( [platform] )\n Returns a regular expression to capture a path dirname.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirname()\n \n > var RE_POSIX = reDirname( 'posix' );\n > var dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > var RE_WIN32 = reDirname( 'win32' );\n > dir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n\n Examples\n --------\n > var RE = reDirname.REGEXP\n \n\n\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n reDirnamePosix, reDirnameWindows, dirname\n","reDirname.REGEXP":"\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n\n Examples\n --------\n > var RE = reDirname.REGEXP\n ","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n reDirnamePosix, reDirnameWindows, dirname","reDirnamePosix":"\nreDirnamePosix()\n Returns a regular expression to capture a POSIX path dirname.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirnamePosix();\n > var dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > dir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n './foo/bar'\n > dir = RE.exec( 'foo/file.pdf' )[ 1 ]\n 'foo'\n > dir = RE.exec( '/foo/bar/file' )[ 1 ]\n '/foo/bar'\n > dir = RE.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE.exec( '.' )[ 1 ]\n '.'\n > dir = RE.exec( './' )[ 1 ]\n '.'\n > dir = RE.exec( '' )[ 1 ]\n ''\n\n\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n See Also\n --------\n reDirname, reDirnameWindows, dirname\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n See Also\n --------\n reDirname, reDirnameWindows, dirname","reDirnameWindows":"\nreDirnameWindows()\n Returns a regular expression to capture a Windows path dirname.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirnameWindows();\n > var dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n > dir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n 'C:\\foo\\bar'\n > dir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'foo'\n > dir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n '\\foo\\bar'\n > dir = RE.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE.exec( '' )[ 1 ]\n ''\n\n\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n\n See Also\n --------\n reDirname, reDirnamePosix, dirname\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n\n See Also\n --------\n reDirname, reDirnamePosix, dirname","reduce":"\nreduce( arr, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a reduction over the entire\n input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input array.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var out = reduce( arr, 0.0, f )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = reduce( arr, 0.0, f )\n 21.0\n\n See Also\n --------\n forEach, map, reduceAsync, reduceRight\n","reduce2d":"\nreduce2d( arr, initial, reducer[, thisArg] )\n Reduces the number of dimensions by one of a two-dimensional nested array by\n applying a function against an accumulator and each element along the\n innermost dimension and returning the accumulation results as a one-\n dimensional array.\n\n The applied function is provided the following arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array of arrays.\n\n initial: ArrayLikeObject\n Initial values. Must have a length equal to the size of the outermost\n input array dimension.\n\n reducer: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array\n Accumulation results.\n\n Examples\n --------\n > var f = naryFunction( base.add, 2 );\n > var arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\n > var out = reduce2d( arr, [ 0, 0 ], f )\n [ 6, 15 ]\n\n See Also\n --------\n map2d, reduce\n","reduceAsync":"\nreduceAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - accumulator: accumulated value.\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - accumulator\n - value\n - next\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - accumulator\n - value\n - index\n - next\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - accumulator: accumulated value.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync\n","reduceAsync.factory":"\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync","reduceRight":"\nreduceRight( arr, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in an array while\n iterating from right to left and returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a reduction over the entire\n input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input array.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var out = reduceRight( arr, 0.0, f )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = reduceRight( arr, 0.0, f )\n 21.0\n\n See Also\n --------\n forEachRight, mapRight, reduce, reduceRightAsync\n","reduceRightAsync":"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - accumulator: accumulated value.\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - accumulator\n - value\n - next\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - accumulator\n - value\n - index\n - next\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - accumulator: accumulated value.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight","reDurationString":"\nreDurationString()\n Returns a regular expression to match a duration string.\n\n A duration string is a string containing a sequence of time units. A time\n unit is a nonnegative integer followed by a unit identifier. The following\n unit identifiers are supported:\n\n - d: days.\n - h: hours.\n - m: minutes.\n - s: seconds.\n - ms: milliseconds.\n\n For example, the string `1m3s10ms` is a duration string containing three\n time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n The string `60m` is a duration string containing a single time unit: `60m`\n (60 minutes). Time units must be supplied in descending order of magnitude\n (i.e., days, hours, minutes, seconds, milliseconds).\n\n Duration strings are case insensitive. For example, the string `1M3S10MS` is\n equivalent to `1m3s10ms`.\n\n The regular expression captures the following groups:\n\n 1. The days component.\n 2. The hours component.\n 3. The minutes component.\n 4. The seconds component.\n 5. The milliseconds component.\n\n Returns\n -------\n re: RegExp: Regular expression\n Regular expression to match a duration string.\n\n Examples\n --------\n > var RE = reDurationString();\n > var parts = RE.exec( '3d2ms' )\n [...]\n > parts = RE.exec( '4h3m20s' )\n [...]\n\n\nreDurationString.REGEXP\n Regular expression to match a duration string.\n\n Examples\n --------\n > var bool = reDurationString.REGEXP.test( '3d2ms' )\n true\n > bool = reDurationString.REGEXP.test( 'foo' )\n false\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n Regular expression to match a duration string.\n\n Examples\n --------\n > var bool = reDurationString.REGEXP.test( '3d2ms' )\n true\n > bool = reDurationString.REGEXP.test( 'foo' )\n false","reEOL":"\nreEOL( [options] )\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to create a capture group for the match.\n Default: false.\n\n Returns\n -------\n regexp: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_EOL = reEOL();\n > var bool = RE_EOL.test( '\\n' )\n true\n > bool = RE_EOL.test( '\\r\\n' )\n true\n > bool = RE_EOL.test( '\\\\r\\\\n' )\n false\n\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = reEOL.REGEXP.test( 'abc' )\n false\n\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n [ '\\n', '\\n' ]\n\n","reEOL.REGEXP":"\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = reEOL.REGEXP.test( 'abc' )\n false","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n [ '\\n', '\\n' ]","reExtendedLengthPath":"\nreExtendedLengthPath()\n Returns a regular expression to test if a string is an extended-length path.\n\n Extended-length paths are Windows paths which begin with `\\\\?\\`.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtendedLengthPath();\n > var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\n > var bool = RE.test( path )\n true\n > path = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\n > bool = RE.test( path )\n true\n > path = 'C:\\\\foo\\\\bar';\n > bool = RE.test( path )\n false\n > path = '/c/foo/bar';\n > bool = RE.test( path )\n false\n > path = '/foo/bar';\n > bool = RE.test( path )\n false\n\n\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n\n Examples\n --------\n > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n false\n\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n\n Examples\n --------\n > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n false","reExtname":"\nreExtname( [platform] )\n Returns a regular expression to capture a filename extension.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtname()\n \n > var RE_POSIX = reExtname( 'posix' );\n > var ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > var RE_WIN32 = reExtname( 'win32' );\n > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n\n Examples\n --------\n > var RE = reExtname.REGEXP\n \n\n\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtnamePosix, reExtnameWindows, extname\n","reExtname.REGEXP":"\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n\n Examples\n --------\n > var RE = reExtname.REGEXP\n ","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtnamePosix, reExtnameWindows, extname","reExtnamePosix":"\nreExtnamePosix\n Returns a regular expression to capture a POSIX filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtnamePosix();\n > var ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n ''\n > ext = RE.exec( 'foo/file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE.exec( '/foo/bar/file' )[ 1 ]\n ''\n > ext = RE.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( '.' )[ 1 ]\n ''\n > ext = RE.exec( './' )[ 1 ]\n ''\n > ext = RE.exec( '' )[ 1 ]\n ''\n\n\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnameWindows, extname\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnameWindows, extname","reExtnameWindows":"\nreExtnameWindows\n Returns a regular expression to capture a Windows filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtnameWindows();\n > var ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n ''\n > ext = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n ''\n > ext = RE.exec( 'beep\\\\boop.' )[ 1 ]\n '.'\n > ext = RE.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( '' )[ 1 ]\n ''\n\n\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnamePosix, extname\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnamePosix, extname","reFilename":"\nreFilename( [platform] )\n Regular expression to split a filename.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilename()\n \n > var RE_POSIX = reFilename( 'posix' );\n > var parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\n \n > var RE_WIN32 = reFilename( 'win32' );\n > parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n \n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreFilename.REGEXP\n Regular expression to split a filename.\n\n Examples\n --------\n > var RE = reFilename.REGEXP\n \n\n\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilenamePosix, reFilenameWindows\n","reFilename.REGEXP":"\nreFilename.REGEXP\n Regular expression to split a filename.\n\n Examples\n --------\n > var RE = reFilename.REGEXP\n ","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilenamePosix, reFilenameWindows","reFilenamePosix":"\nreFilenamePosix()\n Returns a regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilenamePosix();\n > var parts = RE.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n > parts = RE.exec( './foo/bar/.gitignore' ).slice()\n [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n > parts = RE.exec( 'foo/file.pdf' ).slice()\n [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n > parts = RE.exec( '/foo/bar/file' ).slice()\n [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n > parts = RE.exec( 'index.js' ).slice()\n [ 'index.js', '', '', 'index.js', '.js' ]\n > parts = RE.exec( '.' ).slice()\n [ '.', '', '', '.', '' ]\n > parts = RE.exec( './' ).slice()\n [ './', '', ..., '.', '' ]\n > parts = RE.exec( '' ).slice()\n [ '', '', '', '', '' ]\n\n\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n\n Examples\n --------\n > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenameWindows\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n\n Examples\n --------\n > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenameWindows","reFilenameWindows":"\nreFilenameWindows()\n Returns a regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilenameWindows();\n > var parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n > parts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\n [ '\\\\foo\\\\bar\\\\.gitignore', '', '\\\\', 'foo\\\\bar\\\\', '.gitignore', '' ]\n > parts = RE.exec( 'foo\\\\file.pdf' ).slice()\n [ 'foo\\\\file.pdf', '', '', 'foo\\\\', 'file.pdf', '.pdf' ]\n > parts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\n [ '\\\\foo\\\\bar\\\\file', '', '\\\\', 'foo\\\\bar\\\\', 'file', '' ]\n > parts = RE.exec( 'index.js' ).slice()\n [ 'index.js', '', '', '', 'index.js', '.js' ]\n > parts = RE.exec( '.' ).slice()\n [ '.', '', '', '', '.', '' ]\n > parts = RE.exec( './' ).slice()\n [ './', '', ..., '.', '' ]\n > parts = RE.exec( '' ).slice()\n [ '', '', '', '', '', '' ]\n\n\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n\n Examples\n --------\n > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenamePosix","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n\n Examples\n --------\n > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenamePosix","reFromString":"\nreFromString( str )\n Parses a regular expression string and returns a new regular expression.\n\n Provided strings should be properly escaped.\n\n If unable to parse a string as a regular expression, the function returns\n `null`.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: RegExp|null\n Regular expression or null.\n\n Examples\n --------\n > var re = reFromString( '/beep/' )\n /beep/\n > re = reFromString( '/beep' )\n null\n\n","reFunctionName":"\nreFunctionName()\n Return a regular expression to capture a function name.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_FUNCTION_NAME = reFunctionName();\n > function beep() { return 'boop'; };\n > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n 'beep'\n > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n ''\n\n\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n\n Examples\n --------\n > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n 'sqrt'\n\n See Also\n --------\n functionName\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n\n Examples\n --------\n > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n 'sqrt'\n\n See Also\n --------\n functionName","regexp2json":"\nregexp2json( re )\n Returns a JSON representation of a regular expression.\n\n Parameters\n ----------\n re: RegExp\n Regular expression to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n \n out.type: string\n Value type. The assigned value is always 'RegExp'.\n \n out.pattern: string\n Regular expression pattern.\n \n out.flags: string\n Regular expression flags.\n\n Examples\n --------\n > var json = regexp2json( /ab+c/ )\n {...}\n\n See Also\n --------\n reviveRegExp \n","reim":"\nreim( z )\n Returns the real and imaginary components of a double-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Float64Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var out = reim( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imag, real\n","reimf":"\nreimf( z )\n Returns the real and imaginary components of a single-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Float32Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var out = reimf( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imagf, realf, reim\n","rejectArguments":"\nrejectArguments( fcn, predicate[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n\n Only those arguments in which the predicate function returns a falsy value\n are applied to a provided function.\n\n The predicate function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > function predicate( v ) { return ( v === 2 ); };\n > var bar = rejectArguments( foo, predicate );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n filterArguments, maskArguments\n","removeFirst":"\nremoveFirst( str[, n][, options] )\n Removes the first character(s) of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to remove. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeFirst( 'beep' )\n 'eep'\n > out = removeFirst( 'Boop' )\n 'oop'\n > out = removeFirst( 'foo bar', 4 )\n 'bar'\n\n See Also\n --------\n removeLast\n","removeLast":"\nremoveLast( str[, n][, options] )\n Removes the last character(s) of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to remove. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to remove. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeLast( 'beep' )\n 'bee'\n > out = removeLast( 'Boop' )\n 'Boo'\n > out = removeLast( 'foo bar', 4 )\n 'foo'\n\n See Also\n --------\n removeFirst\n","removePunctuation":"\nremovePunctuation( str )\n Removes punctuation characters from a `string`.\n\n The function removes the following characters:\n\n - Apostrophe: `\n - Braces : { }\n - Brackets: [ ]\n - Colon: :\n - Comma: ,\n - Exclamation Mark: !\n - Fraction Slash: /\n - Guillemets: < >\n - Parentheses: ( )\n - Period: .\n - Semicolon: ;\n - Tilde: ~\n - Vertical Bar: |\n - Question Mark: ?\n - Quotation Marks: ' \"\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with punctuation characters removed.\n\n Examples\n --------\n > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n > var out = removePunctuation( str )\n 'Sun Tzu said A leader leads by example not by force'\n\n > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\n > out = removePunctuation( str )\n 'This function removes these characters '\n\n","removeUTF8BOM":"\nremoveUTF8BOM( str )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with BOM removed.\n\n Examples\n --------\n > var out = removeUTF8BOM( '\\ufeffbeep' )\n 'beep'\n\n","removeWords":"\nremoveWords( str, words[, ignoreCase] )\n Removes all occurrences of the given words from a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n words: Array\n Array of words to be removed.\n\n ignoreCase: boolean (optional)\n Boolean indicating whether to perform a case-insensitive operation.\n Default: `false`.\n\n Returns\n -------\n out: string\n String with words removed.\n\n Examples\n --------\n > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n 'beep Foo bar'\n\n // Case-insensitive:\n > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n 'beep bar'\n\n","rename":"\nrename( oldPath, newPath, clbk )\n Asynchronously renames a file.\n\n The old path can specify a directory. In this case, the new path must either\n not exist, or it must specify an empty directory.\n\n The old pathname should not name an ancestor directory of the new pathname.\n\n If the old path points to the pathname of a file that is not a directory,\n the new path should not point to the pathname of a directory.\n\n Write access permission is required for both the directory containing the\n old path and the directory containing the new path.\n\n If the link named by the new path exists, the new path is removed and the\n old path is renamed to the new path. The link named by the new path will\n remain visible to other threads throughout the renaming operation and refer\n to either the file referred to by the new path or to the file referred to by\n the old path before the operation began.\n\n If the old path and the new path resolve to either the same existing\n directory entry or to different directory entries for the same existing\n file, no action is taken, and no error is returned.\n\n If the old path points to a pathname of a symbolic link, the symbolic link\n is renamed. If the new path points to a pathname of a symbolic link, the\n symbolic link is removed.\n\n If a link named by the new path exists and the file's link count becomes 0\n when it is removed and no process has the file open, the space occupied by\n the file is freed and the file is no longer accessible. If one or more\n processes have the file open when the last link is removed, the link is\n removed before the function returns, but the removal of file contents is\n postponed until all references to the file are closed.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n clbk: Function\n Callback to invoke upon renaming a file.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink\n","rename.sync":"\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink","reNativeFunction":"\nreNativeFunction()\n Returns a regular expression to match a native function.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reNativeFunction();\n > var bool = RE.test( Date.toString() )\n true\n > bool = RE.test( (function noop() {}).toString() )\n false\n\n\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n true\n > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n reFunctionName, functionName\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n true\n > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n reFunctionName, functionName","reorderArguments":"\nreorderArguments( fcn, indices[, thisArg] )\n Returns a function that invokes a provided function with reordered\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reordered arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 3, 1, 2 ]\n\n See Also\n --------\n maskArguments, reverseArguments\n","repeat":"\nrepeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = repeat( 'a', 5 )\n 'aaaaa'\n > out = repeat( '', 100 )\n ''\n > out = repeat( 'beep', 0 )\n ''\n\n See Also\n --------\n pad\n","replace":"\nreplace( str, search, newval )\n Replaces search occurrences with a replacement string.\n\n When provided a string as the search value, the function replaces *all*\n occurrences. To remove only the first match, use a regular expression.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string|RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n // Standard usage:\n > var out = replace( 'beep', 'e', 'o' )\n 'boop'\n\n // Replacer function:\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > out = replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = replace( 'beep', /e/, 'o' )\n 'boep'\n\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n Replaces the substring before the first occurrence of a specified search\n string. \n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n \n replacement: string\n Replacement string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = replaceBefore( str, ' ', 'foo' )\n 'foo boop'\n > out = replaceBefore( str, 'o', 'foo' )\n 'foooop'\n\n","reRegExp":"\nreRegExp()\n Returns a regular expression to parse a regular expression string.\n\n Regular expression strings should be escaped.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reRegExp();\n > var bool = RE.test( '/^beep$/' )\n true\n > bool = RE.test( '/boop' )\n false\n\n // Escape regular expression strings:\n > bool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n false\n > bool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n true\n\n\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n\n Examples\n --------\n > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n true\n > bool = reRegExp.REGEXP.test( '/boop' )\n false\n\n See Also\n --------\n reFromString\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n\n Examples\n --------\n > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n true\n > bool = reRegExp.REGEXP.test( '/boop' )\n false\n\n See Also\n --------\n reFromString","rescape":"\nrescape( str )\n Escapes a regular expression string.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: string\n Escaped string.\n\n Examples\n --------\n > var str = rescape( '[A-Z]*' )\n '\\[A\\-Z\\]\\*'\n\n","reSemVer":"\nreSemVer()\n Returns a regular expression to match a semantic version string.\n\n Returns\n -------\n out: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_SEMVER = reSemVer()\n \n > var bool = RE_SEMVER.test( '1.0.0' )\n true\n > bool = RE_SEMVER.test( '1.0.0-alpha.1' )\n true\n > bool = RE_SEMVER.test( 'abc' )\n false\n > bool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n true\n\n\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n\n Examples\n --------\n > var bool = reSemVer.REGEXP.test( '1.0.0' )\n true\n > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n false\n\n\n See Also\n --------\n isSemVer","reSemVer.REGEXP":"\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n\n Examples\n --------\n > var bool = reSemVer.REGEXP.test( '1.0.0' )\n true\n > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n false\n\n\n See Also\n --------\n isSemVer","resolveParentPath":"\nresolveParentPath( path[, options], clbk )\n Asynchronously resolves a path by walking parent directories.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n See Also\n --------\n resolveParentPathBy\n","resolveParentPath.sync":"\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n See Also\n --------\n resolveParentPathBy","resolveParentPathBy":"\nresolveParentPathBy( path[, options], predicate, clbk )\n Asynchronously resolves a path according to a predicate function by walking\n parent directories.\n\n When invoked, the predicate function is provided two arguments:\n\n - path: a resolved path.\n - next: a callback to be invoked after processing a resolved path.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided predicate function calls the `next` callback with a truthy\n `error` argument, the function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n the resolved path as the second argument.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function predicate( path, next ) {\n ... setTimeout( onTimeout, path );\n ... function onTimeout() {\n ... console.log( path );\n ... next( null, false );\n ... }\n ... };\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPathBy( 'package.json', predicate, onPath );\n\n\nresolveParentPathBy.sync( path[, options], predicate )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n\n The predicate function is provided one argument:\n\n - path: a resolved path.\n\n The function immediately returns upon encountering a truthy return value.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > function predicate() { return false; };\n > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n See Also\n --------\n resolveParentPath\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path[, options], predicate )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n\n The predicate function is provided one argument:\n\n - path: a resolved path.\n\n The function immediately returns upon encountering a truthy return value.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > function predicate() { return false; };\n > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n See Also\n --------\n resolveParentPath","reUncPath":"\nreUncPath()\n Return a regular expression to parse a UNC path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUncPath();\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\\\\\share';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\\\\\\\\\server\\\\share';\n > bool = RE.test( path )\n false\n > path = 'beep boop \\\\\\\\server\\\\share';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server';\n > bool = RE.test( path )\n false\n > path = '\\\\';\n > bool = RE.test( path )\n false\n > path = '';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\n > bool = RE.test( path )\n false\n > path = '//server/share';\n > bool = RE.test( path )\n false\n > path = '/foo/bar';\n > bool = RE.test( path )\n false\n > path = 'foo/bar';\n > bool = RE.test( path )\n false\n > path = './foo/bar';\n > bool = RE.test( path )\n false\n > path = '/foo/../bar';\n > bool = RE.test( path )\n false\n\n\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = reUncPath.REGEXP.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = reUncPath.REGEXP.test( path )\n true\n\n See Also\n --------\n isUNCPath\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = reUncPath.REGEXP.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = reUncPath.REGEXP.test( path )\n true\n\n See Also\n --------\n isUNCPath","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n Returns a regular expression to match a UTF-16 surrogate pair.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair();\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair.REGEXP;\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n See Also\n --------\n reUtf16UnpairedSurrogate","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair.REGEXP;\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n See Also\n --------\n reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n Returns a regular expression to match an unpaired UTF-16 surrogate.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate();\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate.REGEXP;\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n See Also\n --------\n reUtf16SurrogatePair","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate.REGEXP;\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n See Also\n --------\n reUtf16SurrogatePair","reverseArguments":"\nreverseArguments( fcn[, thisArg] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reversed arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reverseArguments( foo );\n > var out = bar( 1, 2, 3 )\n [ 3, 2, 1 ]\n\n See Also\n --------\n maskArguments, reorderArguments\n","reverseString":"\nreverseString( str[, options] )\n Reverses a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to reverse. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Reversed string.\n\n Examples\n --------\n > var out = reverseString( 'foo' )\n 'oof'\n > out = reverseString( 'abcdef' )\n 'fedcba'\n\n","reviveBasePRNG":"\nreviveBasePRNG( key, value )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or PRNG.\n\n Examples\n --------\n > var str = JSON.stringify( base.random.mt19937 );\n > var r = parseJSON( str, reviveBasePRNG )\n \n\n","reviveBuffer":"\nreviveBuffer( key, value )\n Revives a JSON-serialized Buffer.\n\n The serialization format for a Buffer is an object having the following\n fields:\n\n - type: value type (Buffer).\n - data: buffer data as an array of integers.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or Buffer.\n\n Examples\n --------\n > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n > var buf = parseJSON( str, reviveBuffer )\n [ 5, 3 ]\n\n See Also\n --------\n buffer2json\n","reviveComplex":"\nreviveComplex( key, value )\n Revives a JSON-serialized complex number.\n\n The serialization format for complex numbers is an object having the\n following fields:\n\n - type: complex number type (e.g., \"Complex128\", \"Complex64\").\n - re: real component (number).\n - im: imaginary component (number).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex )\n \n\n See Also\n --------\n Complex128, Complex64, reviveComplex128, reviveComplex64\n","reviveComplex64":"\nreviveComplex64( key, value )\n Revives a JSON-serialized 64-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex64 )\n \n\n See Also\n --------\n Complex64, reviveComplex128, reviveComplex\n","reviveComplex128":"\nreviveComplex128( key, value )\n Revives a JSON-serialized 128-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex128 )\n \n\n See Also\n --------\n Complex128, reviveComplex64, reviveComplex\n","reviveError":"\nreviveError( key, value )\n Revives a JSON-serialized error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or error object.\n\n Examples\n --------\n > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n > var err = JSON.parse( str, reviveError )\n \n\n See Also\n --------\n error2json\n","reviveRegExp":"\nreviveRegExp( key, value )\n Revives a JSON-serialized regular expression.\n\n The serialization format for a regular expression is an object having the\n following fields:\n\n - type: value type (RegExp).\n - pattern: regular expression pattern.\n - flags: regular expression flags.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or regular expression.\n\n Examples\n --------\n > var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\n > var v = parseJSON( str, reviveRegExp )\n \n\n See Also\n --------\n regexp2json","reviveTypedArray":"\nreviveTypedArray( key, value )\n Revives a JSON-serialized typed array.\n\n The serialization format for typed array is an object having the following\n fields:\n\n - type: typed array type (e.g., \"Float64Array\", \"Int8Array\").\n - data: typed array data as an array of numbers.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or typed array.\n\n Examples\n --------\n > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n > var arr = parseJSON( str, reviveTypedArray )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n typedarray2json\n","reWhitespace":"\nreWhitespace( [options] )\n Returns a regular expression to match a white space character.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to wrap a regular expression matching a white\n space character with a capture group. Default: false.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reWhitespace();\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false\n\n\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP;\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false\n\n\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP_CAPTURE;\n > var str = 'Duplicate capture';\n > var out = replace( str, RE, '$1$1' )\n 'Duplicate capture'\n\n See Also\n --------\n isWhitespace","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP;\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP_CAPTURE;\n > var str = 'Duplicate capture';\n > var out = replace( str, RE, '$1$1' )\n 'Duplicate capture'\n\n See Also\n --------\n isWhitespace","rpad":"\nrpad( str, len[, pad] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = rpad( 'a', 5 )\n 'a '\n > out = rpad( 'beep', 10, 'p' )\n 'beeppppppp'\n > out = rpad( 'beep', 12, 'boop' )\n 'beepboopboop'\n\n See Also\n --------\n lpad, pad\n","rtrim":"\nrtrim( str )\n Trims whitespace from the end of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n See Also\n --------\n ltrim, trim\n","rtrimN":"\nrtrimN( str, n[, chars] )\n Trims `n` characters from the end of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of characters to trim.\n\n chars: Array|string (optional)\n Characters to trim. Default: whitespace characters.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrimN( ' abc ', 2 )\n ' abc'\n > var out = rtrimN( '!!!abc!!!', 2, '!' )\n '!!!abc!'\n\n See Also\n --------\n ltrimN, trim","safeintmax":"\nsafeintmax( dtype )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: integer\n Maximum safe integer.\n\n Examples\n --------\n > var m = safeintmax( 'float16' )\n 2047\n > m = safeintmax( 'float32' )\n 16777215\n\n See Also\n --------\n safeintmin, realmax, typemax\n","safeintmin":"\nsafeintmin( dtype )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: integer\n Minimum safe integer.\n\n Examples\n --------\n > var m = safeintmin( 'float16' )\n -2047\n > m = safeintmin( 'float32' )\n -16777215\n\n See Also\n --------\n safeintmax, realmin, typemin\n","sample":"\nsample( x[, options] )\n Samples elements from an array-like object.\n\n Parameters\n ----------\n x: ArrayLike\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.size: integer (optional)\n Sample size. By default, the function returns an array having the same\n length as `x`. Specify the `size` option to generate a sample of a\n different size.\n\n options.probs: Array (optional)\n Element probabilities. By default, the probability of sampling an\n element is the same for all elements. To assign elements different\n probabilities, set the `probs` option. The `probs` option must be a\n numeric array consisting of nonnegative values which sum to one. When\n sampling without replacement, note that the `probs` option denotes the\n initial element probabilities which are then updated after each draw.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. If the `replace`\n option is set to `false`, the `size` option cannot be an integer larger\n than the number of elements in `x`. Default: `true`.\n\n Returns\n -------\n out: Array\n Sample.\n\n Examples\n --------\n > var out = sample( 'abc' )\n e.g., [ 'a', 'a', 'b' ]\n > out = sample( [ 3, 6, 9 ] )\n e.g., [ 3, 9, 6 ]\n > var bool = ( out.length === 3 )\n true\n\n > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n e.g., [ 3, 'abc', null, 3, null ]\n\n // Set sample size:\n > out = sample( [ 3, 6, 9 ], { 'size': 10 } )\n e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n > out = sample( [ 0, 1 ], { 'size': 20 } )\n e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n // Draw without replacement:\n > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\n e.g., [ 6, 1, 5 ]\n > out = sample( [ 0, 1 ], { 'replace': false } )\n e.g., [ 0, 1 ]\n\n // Assigning non-uniform element probabilities:\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n > out = sample( x, { 'probs': probs } )\n e.g., [ 5, 6, 6, 5, 6, 4 ]\n > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 } );\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]\n\n","sample.factory":"\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 } );\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FIN()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FR()\n [ 'a', 'à', 'â', 'abord', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_GER()\n [ 'a', 'ab', 'aber', 'ach', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_IT()\n [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_POR()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SP()\n [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SWE()\n [ 'aderton', 'adertonde', 'adjö', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","scalar2array":"\nscalar2array( value[, dtype] )\n Returns a single-element array containing a provided scalar value.\n\n If `value` is a number and `dtype` is a complex number data type, the\n function returns a complex number array containing a complex number whose\n real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n dtype: string (optional)\n Data type. If not provided and `value`\n\n - is a number, the default data type is the default real-valued\n floating-point data type.\n - is a boolean, the default data type is the default boolean data type.\n - is a complex number object of a known complex data type, the data type\n is the same as the provided value.\n - is a complex number object of an unknown data type, the default data\n type is the default complex-valued floating-point data type.\n - is any other value type, the default data type is 'generic'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = scalar2array( 1.0 )\n [ 1.0 ]\n\n See Also\n --------\n iterator2array\n","scalar2ndarray":"\nscalar2ndarray( value[, options] )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n\n If `value` is a number and `options.dtype` is a complex number data type,\n the function returns a zero-dimensional ndarray containing a complex number\n whose real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Data type. If not provided and `value`\n\n - is a number, the default data type is the default real-valued\n floating-point data type.\n - is a boolean, the default data type is the default boolean data type.\n - is a complex number object of a known complex data type, the data type\n is the same as the provided value.\n - is a complex number object of an unknown data type, the default data\n type is the default complex-valued floating-point data type.\n - is any other value type, the default data type is 'generic'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = scalar2ndarray( 1.0 )\n \n > var sh = x.shape\n []\n > var dt = x.dtype\n 'float64'\n > var v = x.get()\n 1.0\n\n See Also\n --------\n array, ndarray\n","sdot":"\nsdot( x, y[, dim] )\n Computes the dot product of two single-precision floating-point vectors.\n\n If provided at least one input array having more than one dimension, the\n input arrays are broadcasted to a common shape.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function computes the dot product for each pair\n of vectors in `x` and `y` according to the specified dimension index.\n\n The size of the contracted dimension must be the same for both input arrays.\n\n The function resolves the dimension index for which to compute the dot\n product *before* broadcasting.\n\n If provided empty vectors, the dot product is `0`.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float32' data type. Must have at least\n one dimension and be broadcast-compatible with the second input array.\n\n y: ndarray\n Second input array. Must have a 'float32' data type. Must have at least\n one dimension and be broadcast-compatible with the first input array.\n\n dim: integer (optional)\n Dimension index for which to compute the dot product. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n out: ndarray\n The dot product. The output array has the same data type as the input\n arrays and has a shape which is determined by broadcasting and excludes\n the contracted dimension.\n\n Examples\n --------\n > var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var x = array( xbuf );\n > var ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var y = array( ybuf );\n > var z = sdot( x, y )\n \n > z.get()\n -5.0\n\n See Also\n --------\n base.strided.sdot, ddot, gdot\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var secs = days * SECONDS_IN_DAY\n 271296\n\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var secs = hrs * SECONDS_IN_HOUR\n 11304\n\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var secs = mins * SECONDS_IN_MINUTE\n 188.4\n\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n","secondsInMonth":"\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n See Also\n --------\n secondsInYear\n","secondsInYear":"\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n See Also\n --------\n secondsInMonth\n","sentencize":"\nsentencize( str )\n Splits a string into an array of sentences.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: Array\n Array of sentences.\n\n Examples\n --------\n > var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello Mrs. Maple, could you call me back?' ]\n\n > out = sentencize( 'Hello World! How are you?' )\n [ 'Hello World!', 'How are you?' ]\n\n See Also\n --------\n tokenize\n","seq2slice":"\nseq2slice( str, len, strict )\n Converts a subsequence string to a Slice object.\n\n A subsequence string has the following format:\n\n ::\n\n If an increment is not specified, the default increment is one. An increment\n of zero is not allowed.\n\n The start index is inclusive.\n\n The stop index is exclusive.\n\n Both start and stop indices are optional. If not provided, the start and\n stop indices default to index extremes. Which extremes correspond to which\n index depends on whether the increment is positive or negative.\n\n Both start and stop indices can be negative; in which case, the\n corresponding index is resolved by subtracting the respective value from the\n provided length.\n\n Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n 'end-3:', etc), which supports basic subtraction and division.\n\n The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n exception is when performing a division operation when the increment is less\n than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n user expectations when 'end/d' equals a whole number and slicing from right-\n to-left. The result from a division operation is rounded down to the nearest\n integer value.\n\n In non-strict mode, the resolved slice start is clamped to the slice index\n bounds [0, len).\n\n In non-strict mode, Tte resolved slice end is upper bound clamped to the\n provided length (i.e., one greater than the last possible index).\n\n When the increment is negative, the resolved slice end value may be `null`,\n thus indicating that a non-empty slice should include the first index.\n\n The function ensures that results satisfy the convention that ':n' combined\n with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n When the provided length is zero, the function always returns a slice object\n equivalent to '0:0:'.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new seq2slice( '1:10', 10, false );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new seq2slice( '2:5:2', 10, false );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n Slice\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setReadOnly\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj, prop, fcn )\n Defines a configurable memoized read-only object property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedConfigurableReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setMemoizedReadOnly, setReadOnly\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj, prop, fcn )\n Defines a memoized read-only object property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n defineMemoizedProperty, setReadOnly\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > objectKeys( obj )\n []\n\n See Also\n --------\n setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n Defines a non-enumerable property having read-write accessors.\n\n Non-enumerable read-write accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableWriteOnlyAccessor, setReadWriteAccessor\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n Defines a non-enumerable write-only accessor.\n\n Non-enumerable write-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnly":"\nsetReadOnly( obj, prop, value )\n Defines a read-only property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setReadOnlyAccessor, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj, prop, getter )\n Defines a read-only accessor.\n\n Read-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj, prop, getter, setter )\n Defines a property having read-write accessors.\n\n Read-write accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setWriteOnlyAccessor\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj, prop, setter )\n Defines a write-only accessor.\n\n Write-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setReadWriteAccessor\n","SharedArrayBuffer":"\nSharedArrayBuffer( size )\n Returns a shared array buffer having a specified number of bytes.\n\n A shared array buffer behaves similarly to a non-shared array buffer, except\n that a shared array buffer allows creating views of memory shared between\n threads.\n\n Buffer contents are initialized to 0.\n\n If an environment does not support shared array buffers, the function throws\n an error.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: SharedArrayBuffer\n A shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 )\n \n\n\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1\n\n\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","shift":"\nshift( collection )\n Removes and returns the first element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = shift( arr )\n [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = shift( arr )\n [ [ 2.0 ], 1.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = shift( arr )\n [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n See Also\n --------\n pop, push, unshift\n","shuffle":"\nshuffle( arr[, options] )\n Shuffles elements of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object to shuffle.\n\n options: Object (optional)\n Options.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n out: ArrayLike\n Shuffled array-like object.\n\n Examples\n --------\n > var data = [ 1, 2, 3 ];\n > var out = shuffle( data )\n e.g., [ 3, 1, 2 ]\n > out = shuffle( data, { 'copy': 'none' } );\n > var bool = ( data === out )\n true\n\n\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' } );\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample\n","shuffle.factory":"\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' } );\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample","sizeOf":"\nsizeOf( dtype )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - complex128: 128-bit complex numbers.\n - complex64: 64-bit complex numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Size (in bytes).\n\n Examples\n --------\n > var s = sizeOf( 'int8' )\n 1\n > s = sizeOf( 'uint32' )\n 4\n\n See Also\n --------\n realmax, typemax\n","Slice":"\nSlice( [stop] )\n Returns a Slice.\n\n Parameters\n ----------\n stop: integer|null|undefined (optional)\n Ending index (exclusive).\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new Slice();\n > s = new Slice( 10 );\n\n\nSlice( start, stop[, step] )\n Returns a Slice.\n\n Parameters\n ----------\n start: integer|null|undefined\n Starting index (inclusive).\n\n stop: integer|null|undefined\n Ending index (exclusive).\n\n step: integer|null|undefined (optional)\n Index increment. A numeric index increment argument should be a non-zero\n integer value. Default: null.\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > s = new Slice( 2, 10, 1 );\n\n\nSlice.prototype.start\n Read-only property returning the starting slice index.\n\n Returns\n -------\n start: integer|null\n Starting index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.start\n null\n > s = new Slice( 2, 10 );\n > s.start\n 2\n\n\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n\n Returns\n -------\n stop: integer|null\n Ending index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.stop\n 10\n > s = new Slice( 2, 10 );\n > s.stop\n 10\n\n\nSlice.prototype.step\n Read-only property returning the index increment.\n\n Returns\n -------\n step: integer|null\n Index increment.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.step\n null\n > s = new Slice( 2, 10 );\n > s.step\n null\n > s = new Slice( 2, 10, 1 );\n > s.step\n 1\n\n\nSlice.prototype.toString()\n Serializes a Slice as a string.\n\n Returns\n -------\n str: string\n Serialized Slice string.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toString()\n 'Slice(null,10,null)'\n > s = new Slice( 2, 10, 1 );\n > s.toString()\n 'Slice(2,10,1)'\n\n\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ null, 10, null ] }\n > s = new Slice( 2, 10, 1 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n See Also\n --------\n ndarray, MultiSlice\n","Slice.prototype.start":"\nSlice.prototype.start\n Read-only property returning the starting slice index.\n\n Returns\n -------\n start: integer|null\n Starting index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.start\n null\n > s = new Slice( 2, 10 );\n > s.start\n 2","Slice.prototype.stop":"\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n\n Returns\n -------\n stop: integer|null\n Ending index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.stop\n 10\n > s = new Slice( 2, 10 );\n > s.stop\n 10","Slice.prototype.step":"\nSlice.prototype.step\n Read-only property returning the index increment.\n\n Returns\n -------\n step: integer|null\n Index increment.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.step\n null\n > s = new Slice( 2, 10 );\n > s.step\n null\n > s = new Slice( 2, 10, 1 );\n > s.step\n 1","Slice.prototype.toString":"\nSlice.prototype.toString()\n Serializes a Slice as a string.\n\n Returns\n -------\n str: string\n Serialized Slice string.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toString()\n 'Slice(null,10,null)'\n > s = new Slice( 2, 10, 1 );\n > s.toString()\n 'Slice(2,10,1)'","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ null, 10, null ] }\n > s = new Slice( 2, 10, 1 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n See Also\n --------\n ndarray, MultiSlice","snakecase":"\nsnakecase( str )\n Converts a string to snake case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Snake-cased string.\n\n Examples\n --------\n > var out = snakecase( 'Hello World!' )\n 'hello_world'\n > out = snakecase( 'I am a tiny little teapot' )\n 'i_am_a_tiny_little_teapot'\n\n See Also\n --------\n camelcase, constantcase, kebabcase, pascalcase","some":"\nsome( collection, n )\n Tests whether at least `n` elements in a collection are truthy.\n\n The function immediately returns upon finding `n` truthy elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 1, 2, 3 ];\n > var bool = some( arr, 3 )\n true\n\n See Also\n --------\n any, every, forEach, none, someBy\n","someBy":"\nsomeBy( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, -3, 4, -1 ];\n > var bool = someBy( arr, 2, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, noneBy, someByAsync, someByRight\n","someByAsync":"\nsomeByAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync\n","someByAsync.factory":"\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync","someByRight":"\nsomeByRight( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, -2, 3, 4 ];\n > var bool = someByRight( arr, 2, negative )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, noneByRight, someBy, someByRightAsync\n","someByRightAsync":"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection value.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight","someInBy":"\nsomeInBy( obj, n, predicate[, thisArg ] )\n Tests whether an object contains at least `n` properties\n (own and inherited) which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - obj: the input object.\n\n The function immediately returns upon finding `n` successful properties.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n obj: Object\n Input object over which to iterate.\n\n n: number\n Minimum number of successful properties.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an object contains at least `n`\n successful properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\n > var bool = someInBy( obj, 2, negative )\n true\n\n See Also\n --------\n anyInBy, everyInBy, someBy, someOwnBy","someOwnBy":"\nsomeOwnBy( obj, n, predicate[, thisArg ] )\n Tests whether some `own` properties of a provided object\n satisfy a predicate function for at least `n` properties.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - obj: the input object.\n\n The function immediately returns upon finding `n` successful properties.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n obj: Object\n Input object over which to iterate.\n\n n: number\n Minimum number of successful properties.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an object's own properties satisfy a\n predicate for at least `n` properties; otherwise, the function\n returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\n > var bool = someOwnBy( obj, 2, negative )\n true\n\n See Also\n --------\n anyOwnBy, everyOwnBy, someBy, someInBy","SOTU":"\nSOTU( [options] )\n Returns State of the Union (SOTU) addresses.\n\n Each State of the Union address is represented by an object with the\n following fields:\n\n - year: speech year.\n - name: President name.\n - party: the President's political party.\n - text: speech text.\n\n The following political parties are recognized:\n\n - Democratic\n - Republican\n - Democratic-Republican\n - Federalist\n - National Union\n - Whig\n - Whig & Democratic\n - none\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.name: String|Array (optional)\n President name(s).\n\n options.party: String|Array (optional)\n Political party (or parties).\n\n options.year: integer|Array (optional)\n Year(s).\n\n options.range: Array (optional)\n Two-element array specifying a year range.\n\n Returns\n -------\n out: Array\n State of the Union addresses.\n\n Examples\n --------\n > var out = SOTU()\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more Presidents...\n > var opts = { 'name': 'Barack Obama' };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more political parties...\n > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses from one or more years...\n > opts = { 'year': [ 2008, 2009, 2011 ] };\n > out = SOTU( opts )\n [ {...}, {...}, {...} ]\n\n // Retrieve addresses from a range of consecutive years...\n > opts = { 'range': [ 2008, 2016 ] }\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n\n Returns\n -------\n out: Array\n List of simple American-English words.\n\n Examples\n --------\n > var list = SPACHE_REVISED()\n [ 'a', 'able', 'about', 'above', ... ]\n\n References\n ----------\n - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n 458513.\n - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n .\n - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n School Journal* 57 (1). University of Chicago Press: 36–41.\n .\n - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n .\n\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n\n Each array element has the following fields:\n\n - id: message id (relative to message group).\n - group: message group.\n - checksum: object containing checksum info.\n - text: message text (including headers).\n\n The message group may be one of the following:\n\n - easy-ham-1: easier to detect non-spam e-mails (2500 messages).\n - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n (1400 messages).\n - hard-ham-1: harder to detect non-spam e-mails (250 messages).\n - spam-1: spam e-mails (500 messages).\n - spam-2: spam e-mails collected at a later date (1396 messages).\n\n The checksum object contains the following fields:\n\n - type: checksum type (e.g., MD5).\n - value: checksum value.\n\n Returns\n -------\n out: Array\n Corpus.\n\n Examples\n --------\n > var data = SPAM_ASSASSIN()\n [ {...}, {...}, ... ]\n\n","SparklineBase":"\nSparklineBase( [data,] [options] )\n Returns a Sparkline instance.\n\n This constructor is a base Sparkline constructor from which constructors\n tailored to generating particular types of Sparkline graphics should be\n derived.\n\n At a minimum, descendants should implement a private `_render()` method\n which will be automatically invoked by the public `render()` method.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options.description: string (optional)\n Sparkline description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n sparkline: Sparkline\n Sparkline instance.\n\n sparkline.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n sparkline.bufferSize\n Data buffer size.\n\n sparkline.description\n Sparkline description.\n\n sparkline.data\n Sparkline data.\n\n sparkline.label\n Data label.\n\n sparkline.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n sparkline.render()\n Renders a sparkline. This method calls `_render()` which must be\n implemented by instances and child classes. The default behavior is\n throw an error.\n\n Examples\n --------\n > var sparkline = new SparklineBase()\n \n\n // Provide sparkline data at instantiation:\n > var data = [ 1, 2, 3 ];\n > sparkline = new SparklineBase( data )\n \n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","sparsearray2iterator":"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, sparsearray2iteratorRight\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, sparsearray2iterator\n","splitStream":"\nsplitStream( [options] )\n Returns a transform stream which splits streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream.Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = splitStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream\n","splitStream.factory":"\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();","splitStream.objectMode":"\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n\n Examples\n --------\n > SQRT_EPS\n 0.14901161193847656e-7\n\n See Also\n --------\n EPS\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n\n Examples\n --------\n > SQRT_HALF\n 0.7071067811865476\n\n See Also\n --------\n LN_HALF\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n\n Examples\n --------\n > SQRT_HALF_PI\n 1.2533141373155003\n\n See Also\n --------\n PI\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n\n Examples\n --------\n > SQRT_PHI\n 1.272019649514069\n\n See Also\n --------\n PHI\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n\n Examples\n --------\n > SQRT_PI\n 1.7724538509055160\n\n See Also\n --------\n PI\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n\n Examples\n --------\n > SQRT_THREE\n 1.7320508075688772\n\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n\n Examples\n --------\n > SQRT_TWO\n 1.4142135623730951\n\n See Also\n --------\n LN2\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n\n Examples\n --------\n > SQRT_TWO_PI\n 2.5066282746310007\n\n See Also\n --------\n TWO_PI\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n Returns US birth data from 2000 to 2014, as provided by the Social Security\n Administration.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = SSA_US_BIRTHS_2000_2014()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1969_1988, CDC_NCHS_US_BIRTHS_1994_2003\n","sswap":"\nsswap( x, y[, dim] )\n Interchanges two single-precision floating-point vectors.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function interchanges each pair of vectors in `x`\n and `y` according to the specified dimension index.\n\n Both input arrays must have the same shape.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float32' data type. Must have at least\n one dimension and must have the same shape as the second input array.\n\n y: ndarray\n Second input array. Must have a 'float32' data type. Must have at least\n one dimension and must have the same shape as the first input array.\n\n dim: integer (optional)\n Dimension index along which to interchange vectors. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n > var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > sswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.sswap, dswap, gswap\n","Stack":"\nStack()\n Stack constructor.\n\n A stack is also referred to as a \"last-in-first-out\" queue.\n\n Returns\n -------\n stack: Object\n Stack data structure.\n\n stack.clear: Function\n Clears the stack.\n\n stack.first: Function\n Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.iterator: Function\n Returns an iterator for iterating over a stack. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from stack mutation during\n iteration, a returned iterator **always** iterates over a stack\n \"snapshot\", which is defined as the list of stack elements at the time\n of the method's invocation.\n\n stack.last: Function\n Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.length: integer\n Stack length.\n\n stack.pop: Function\n Removes and returns the current \"first-out\" value from the stack. If the\n stack is empty, the returned value is `undefined`.\n\n stack.push: Function\n Adds a value to the stack.\n\n stack.toArray: Function\n Returns an array of stack values.\n\n stack.toJSON: Function\n Serializes a stack as JSON.\n\n Examples\n --------\n > var s = Stack();\n > s.push( 'foo' ).push( 'bar' );\n > s.length\n 2\n > s.pop()\n 'bar'\n > s.length\n 1\n > s.pop()\n 'foo'\n > s.length\n 0\n\n See Also\n --------\n FIFO\n","standalone2pkg":"\nstandalone2pkg( pkg )\n Returns the internal package name associated with a provided standalone\n package name.\n\n Parameters\n ----------\n pkg: string\n Standalone package name.\n\n Returns\n -------\n out: string|null\n Internal package name.\n\n Examples\n --------\n > var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2standalone, pkg2alias, pkg2standalone\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n Returns a string array containing two or three letter abbreviations for each\n card in a standard 52-card deck.\n\n Abbreviation format: \n\n Cards: A, 2, 3, 4, 5, 6, 7, 8, 9, 10, J, Q, K, where\n\n - A: ace\n - J: jack\n - Q: queen\n - K: king\n\n Suit abbreviations:\n\n - C: clubs\n - D: diamonds\n - H: hearts\n - S: spades\n\n Returns\n -------\n out: Array\n List of cards.\n\n Examples\n --------\n > var list = STANDARD_CARD_DECK()\n [ 'AC', '2C', '3C', ... ]\n\n","startcase":"\nstartcase( str )\n Capitalizes the first letter of each word in an input string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n lowercase, uppercase\n","startsWith":"\nstartsWith( str, search[, position] )\n Tests if a string starts with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer (optional)\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string starts with the characters of\n another string.\n\n Examples\n --------\n > var bool = startsWith( 'Beep', 'Be' )\n true\n > bool = startsWith( 'Beep', 'ep' )\n false\n > bool = startsWith( 'Beep', 'ee', 1 )\n true\n > bool = startsWith( 'Beep', 'ee', -3 )\n true\n > bool = startsWith( 'Beep', '' )\n true\n\n See Also\n --------\n endsWith\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = STOPWORDS_EN()\n [ 'a', 'about', 'above', 'across', ... ]\n\n","strided.abs":"\nstrided.abs( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs( 2, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs","strided.abs2":"\nstrided.abs2( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 9.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs2\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs2","strided.abs2By":"\nstrided.abs2By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By( x.length, x, 1, y, 1, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By( 2, x, 2, y, -1, clbk )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs2By( 2, x1, -2, y1, 1, clbk )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = [ -1.0, -2.0, -3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.absBy, strided.abs2\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = [ -1.0, -2.0, -3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.absBy, strided.abs2","strided.absBy":"\nstrided.absBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy( x.length, x, 1, y, 1, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy( 2, x, 2, y, -1, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.absBy( 2, x1, -2, y1, 1, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n strided.abs, strided.abs2By\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n strided.abs, strided.abs2By","strided.acosBy":"\nstrided.acosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy( 2, x, 2, y, -1, clbk )\n [ ~0.524, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acosBy( 2, x1, -2, y1, 1, clbk )\n [ ~2.356, ~0.786 ]\n > y0\n [ 0.0, 0.0, ~2.356, ~0.786 ]\n\n\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Advanced indexing:\n > x = [ 1.0, 0.707, 0.866, -0.707 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.356, ~0.786 ]\n\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Advanced indexing:\n > x = [ 1.0, 0.707, 0.866, -0.707 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.356, ~0.786 ]","strided.acoshBy":"\nstrided.acoshBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy( 2, x, 2, y, -1, clbk )\n [ ~1.317, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acoshBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.567, ~0.962 ]\n > y0\n [ 0.0, 0.0, ~1.567, ~0.962 ]\n\n\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Advanced indexing:\n > x = [ 1.0, 1.5, 2.0, 2.5 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.567, ~0.962 ]\n\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Advanced indexing:\n > x = [ 1.0, 1.5, 2.0, 2.5 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.567, ~0.962 ]","strided.acotBy":"\nstrided.acotBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy( x.length, x, 1, y, 1, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy( 2, x, 2, y, -1, clbk )\n [ ~-1.107, ~-0.381, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acotBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~-0.588 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Advanced indexing:\n > x = [ -2.5, -1.5, -0.5, 0.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Advanced indexing:\n > x = [ -2.5, -1.5, -0.5, 0.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~-0.588 ]","strided.acothBy":"\nstrided.acothBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy( x.length, x, 1, y, 1, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy( 2, x, 2, y, -1, clbk )\n [ ~-0.347, ~-0.203, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acothBy( 2, x1, -2, y1, 1, clbk )\n [ -Infinity, ~-0.255 ]\n > y0\n [ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Advanced indexing:\n > x = [ -5.0, -4.0, -3.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Advanced indexing:\n > x = [ -5.0, -4.0, -3.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, -Infinity, ~-0.255 ]","strided.acovercosBy":"\nstrided.acovercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy( x.length, x, 1, y, 1, clbk )\n [ ~-1.571, ~0.607, ~-0.524, 0.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy( 2, x, 2, y, -1, clbk )\n [ ~-0.524, ~-1.571, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acovercosBy( 2, x1, -2, y1, 1, clbk )\n [ 0.0, ~0.607 ]\n > y0\n [ 0.0, 0.0, 0.0, ~0.607 ]\n\n\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-1.571, ~0.607, ~-0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~0.607 ]\n\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-1.571, ~0.607, ~-0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~0.607 ]","strided.acoversinBy":"\nstrided.acoversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy( x.length, x, 1, y, 1, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy( 2, x, 2, y, -1, clbk )\n [ ~0.524, ~1.571, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acoversinBy( 2, x1, -2, y1, 1, clbk )\n [ 0.0, ~-0.607 ]\n > y0\n [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~-0.607 ]","strided.add":"\nstrided.add( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ 1.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -2.0, 5.0 ]\n > z0\n [ 0.0, 0.0, -2.0, 5.0 ]\n\n\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 5.0, -2.0, 0.0 ]\n\n See Also\n --------\n strided.mul, strided.sub\n","strided.add.ndarray":"\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 5.0, -2.0, 0.0 ]\n\n See Also\n --------\n strided.mul, strided.sub","strided.addBy":"\nstrided.addBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.addBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 13.0, 14.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 17.0, 16.0 ]\n > z0\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n See Also\n --------\n strided.add, strided.mulBy, strided.subBy\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n See Also\n --------\n strided.add, strided.mulBy, strided.subBy","strided.ahavercosBy":"\nstrided.ahavercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy( x.length, x, 1, y, 1, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy( 2, x, 2, y, -1, clbk )\n [ 0.0, ~3.142, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\n [ ~2.094, ~1.571 ]\n > y0\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n See Also\n --------\n strided.ahaversinBy\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n See Also\n --------\n strided.ahaversinBy","strided.ahaversinBy":"\nstrided.ahaversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy( 2, x, 2, y, -1, clbk )\n [ ~3.142, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.047, ~1.571 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n See Also\n --------\n strided.ahavercosBy\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n See Also\n --------\n strided.ahavercosBy","strided.asinBy":"\nstrided.asinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy( 2, x, 2, y, -1, clbk )\n [ ~1.571, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.asinBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.253, ~-0.524 ]\n > y0\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n See Also\n --------\n strided.asinhBy\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n See Also\n --------\n strided.asinhBy","strided.asinhBy":"\nstrided.asinhBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy( 2, x, 2, y, -1, clbk )\n [ ~1.444, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.asinhBy( 2, x1, -2, y1, 1, clbk )\n [ ~-1.444, 0.0 ]\n > y0\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.0, 2.0, -2.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n See Also\n --------\n strided.asinBy\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.0, 2.0, -2.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n See Also\n --------\n strided.asinBy","strided.atanBy":"\nstrided.atanBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy( 2, x, 2, y, -1, clbk )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.atanBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.896, ~-0.464 ]\n > y0\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -1.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n See Also\n --------\n strided.atanhBy\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -1.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n See Also\n --------\n strided.atanhBy","strided.atanhBy":"\nstrided.atanhBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy( 2, x, 2, y, -1, clbk )\n [ Infinity, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.atanhBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.255, ~-0.549 ]\n > y0\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n See Also\n --------\n strided.atanBy\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n See Also\n --------\n strided.atanBy","strided.avercosBy":"\nstrided.avercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy( 2, x, 2, y, -1, clbk )\n [ ~1.047, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.avercosBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~2.177 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, -1.57, -0.5, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, -1.57, -0.5, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.aversinBy":"\nstrided.aversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy( 2, x, 2, y, -1, clbk )\n [ ~1.047, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.aversinBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~2.177 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.besselj0By":"\nstrided.besselj0By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By( 2, x, 2, y, -1, clbk )\n [ ~0.998, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.besselj0By( 2, x1, -2, y1, 1, clbk )\n [ ~0.984, ~0.765 ]\n > y0\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n See Also\n --------\n strided.besselj1By, strided.bessely0By, strided.bessely1By\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n See Also\n --------\n strided.besselj1By, strided.bessely0By, strided.bessely1By","strided.besselj1By":"\nstrided.besselj1By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By( 2, x, 2, y, -1, clbk )\n [ ~0.05, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.besselj1By( 2, x1, -2, y1, 1, clbk )\n [ ~0.124, ~0.44 ]\n > y0\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n See Also\n --------\n strided.besselj0By, strided.bessely0By, strided.bessely1By\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n See Also\n --------\n strided.besselj0By, strided.bessely0By, strided.bessely1By","strided.bessely0By":"\nstrided.bessely0By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By( x.length, x, 1, y, 1, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By( 2, x, 2, y, -1, clbk )\n [ ~-1.534, -Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.bessely0By( 2, x1, -2, y1, 1, clbk )\n [ ~-0.932, ~0.088 ]\n > y0\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely1By\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely1By","strided.bessely1By":"\nstrided.bessely1By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By( x.length, x, 1, y, 1, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By( 2, x, 2, y, -1, clbk )\n [ ~-6.459, -Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.bessely1By( 2, x1, -2, y1, 1, clbk )\n [ ~-2.704, ~-0.781 ]\n > y0\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely0By\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely0By","strided.binetBy":"\nstrided.binetBy( N, x, sx, y, sy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy( 2, x, 2, y, -1, clbk )\n [ 1.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.binetBy( 2, x1, -2, y1, 1, clbk )\n [ 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 2.0, 1.0 ]\n\n\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 2.0, 3.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 2.0, 1.0 ]\n\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 2.0, 3.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 2.0, 1.0 ]","strided.cbrt":"\nstrided.cbrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.scbrt, strided.sqrt\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.scbrt, strided.sqrt","strided.cbrtBy":"\nstrided.cbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy( 2, x, 2, y, -1, clbk )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cbrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~4.327, ~2.08 ]\n > y0\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = [ 1.0, 9.0, -27.0, 81.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = [ 1.0, 9.0, -27.0, 81.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt","strided.ceil":"\nstrided.ceil( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil","strided.cosBy":"\nstrided.cosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy( 2, x, 2, y, -1, clbk )\n [ ~-1.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cosBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.839, ~-1.0 ]\n > y0\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]","strided.deg2rad":"\nstrided.deg2rad( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~1.571, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.sdeg2rad\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.sdeg2rad","strided.dataTypes":"\nstrided.dataTypes()\n Returns a list of strided array data types.\n\n The output array contains the following data types:\n\n - binary: binary.\n - bool: boolean values.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of strided array data types.\n\n Examples\n --------\n > var out = strided.dataTypes()\n \n\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy( 2, x, 2, y, -1, clbk )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~4.327, ~2.08 ]\n > y0\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt","strided.dispatch":"\nstrided.dispatch( fcns, types, data, nargs, nin, nout )\n Returns a strided array function interface which performs multiple dispatch.\n\n Without offsets, a strided array function interface has the following\n signature:\n\n f( N, dtypeX, x, strideX, dtypeY, y, strideY, ... )\n\n where\n\n - N: number of indexed elements.\n - dtypeX: data type for `x`.\n - x: strided array.\n - strideX: index increment for `x`.\n - dtypeY: data type for `y`.\n - y: strided array.\n - strideY: index increment for `y`.\n - ...: additional strided arrays, data types, and associated strides.\n\n The number of parameters is derived from `nargs`, the number of input\n strided arrays is derived from `nin`, and the number of output strided\n arrays is derived from `nout`.\n\n Without offsets, the number of parameters must obey the following relation:\n\n nargs = 3*(nout+nin) + 1\n\n With offsets, the number of parameters must obey the following relation:\n\n nargs = 4*(nout+nin) + 1\n\n With offsets, a strided array function interface has the following\n signature:\n\n f( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY, ... )\n\n where\n\n - N: number of indexed elements.\n - dtypeX: data type for `x`.\n - x: strided array.\n - strideX: index increment for `x`.\n - offsetX: starting index for `x`.\n - dtypeY: data type for `y`.\n - y: strided array.\n - strideY: index increment for `y`.\n - offsetY: starting index for `y`.\n - ...: additional strided arrays and associated data types, strides, and\n offsets.\n\n The choice of which strided array function interface to return depends on\n the use case. The former is suitable for typed array views; while the latter\n affords alternative indexing semantics more suitable for n-dimensional\n arrays (ndarrays).\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of strided array functions. Without offsets, a strided array\n function should have the following signature:\n\n f( arrays, shape, strides, data )\n\n where\n\n - arrays: array containing strided input and output arrays.\n - shape: array containing a single element, the number of indexed\n elements.\n - strides: array containing the stride lengths for the strided input and\n output arrays.\n - data: strided array function data (e.g., a callback).\n\n With offsets, a strided array function should have the following\n signature:\n\n f( arrays, shape, strides, offsets, data )\n\n where\n\n - offsets: array containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n For convenience, a single strided array function may be provided which\n will be invoked whenever the strided array argument data types match a\n sequence of types in `types`. Providing a single strided array function\n is particularly convenient for the case where, regardless of array data\n types, traversing arrays remains the same, but the strided array\n function `data` differs (e.g., callbacks which differ based on the array\n data types).\n\n types: ArrayLikeObject\n One-dimensional list of strided array argument data types.\n\n data: ArrayLikeObject|null\n Strided array function data (e.g., callbacks). If `null`, a returned\n strided array function interface does **not** provide a `data` argument\n to an invoked strided array function.\n\n nargs: integer\n Total number of strided array function interface arguments (including\n data types, strides, and offsets).\n\n nin: integer\n Number of input strided arrays.\n\n nout: integer\n Number of output strided arrays.\n\n Returns\n -------\n fcn: Function\n Strided array function interface.\n\n Examples\n --------\n // Define strided array argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of strided array function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create a strided array function interface for applying unary callbacks:\n > var f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\n\n // Create an input strided array:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value:\n > f( x.length, 'float64', x, 1, 'float64', y, 1 );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Create a strided array function interface supporting offsets:\n > f = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\n\n // Create an input strided array:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value starting from the third element:\n > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\n > y\n [ 0.0, 0.0, 3.0, 4.0 ]\n\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns, types, data, nargs, nin, nout )\n Returns a strided array function interface which accepts a callback function\n and performs multiple dispatch.\n\n Without offsets, a strided array function interface has the following\n signature:\n\n f( N, dx, x, sx, dy, y, sy, ..., clbk[, thisArg] )\n\n where\n\n - N: number of indexed elements.\n - dx: data type for `x`.\n - x: strided array.\n - sx: index increment for `x`.\n - dy: data type for `y`.\n - y: strided array.\n - sy: index increment for `y`.\n - ...: additional strided arrays, data types, and associated strides.\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n The number of parameters is derived from `nargs`, the number of input\n strided arrays is derived from `nin`, and the number of output strided\n arrays is derived from `nout`.\n\n Without offsets, the number of parameters must obey the following relation:\n\n nargs = 3*(nout+nin) + 2\n\n With offsets, the number of parameters must obey the following relation:\n\n nargs = 4*(nout+nin) + 2\n\n With offsets, a strided array function interface has the following\n signature:\n\n f( N, dx, x, sx, ox, dy, y, sy, oy, ..., clbk[, thisArg] )\n\n where\n\n - N: number of indexed elements.\n - dx: data type for `x`.\n - x: strided array.\n - sx: index increment for `x`.\n - ox: starting index for `x`.\n - dy: data type for `y`.\n - y: strided array.\n - sy: index increment for `y`.\n - oy: starting index for `y`.\n - ...: additional strided arrays and associated data types, strides, and\n offsets.\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n The choice of which strided array function interface to return depends on\n the use case. The former is suitable for typed array views; while the latter\n affords alternative indexing semantics more suitable for n-dimensional\n arrays (ndarrays).\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of strided array functions. Without offsets, a strided array\n function should have the following signature:\n\n f( arrays, shape, strides, data, clbk, thisArg )\n\n where\n\n - arrays: array containing strided input and output arrays.\n - shape: array containing a single element, the number of indexed\n elements.\n - strides: array containing the stride lengths for the strided input and\n output arrays.\n - data: strided array function data (e.g., a callback).\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n With offsets, a strided array function should have the following\n signature:\n\n f( arrays, shape, strides, offsets, data, clbk, thisArg )\n\n where\n\n - offsets: array containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n For convenience, a single strided array function may be provided which\n will be invoked whenever the strided array argument data types match a\n sequence of types in `types`. Providing a single strided array function\n is particularly convenient for the case where, regardless of array data\n types, traversing arrays remains the same, but the strided array\n function `data` differs (e.g., callbacks which differ based on the array\n data types).\n\n types: ArrayLikeObject\n One-dimensional list of strided array argument data types.\n\n data: ArrayLikeObject|null\n Strided array function data (e.g., callbacks). If `null`, a returned\n strided array function interface does **not** provide a `data` argument\n to an invoked strided array function.\n\n nargs: integer\n Total number of strided array function interface arguments (including\n data types, strides, offsets, and the callback function).\n\n nin: integer\n Number of input strided arrays.\n\n nout: integer\n Number of output strided arrays.\n\n Returns\n -------\n fcn: Function\n Strided array function interface.\n\n Examples\n --------\n // Define strided array argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of strided array function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create a strided array function interface for applying unary callbacks:\n > var f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\n\n // Create an input strided array:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value:\n > f( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Create a strided array function interface supporting offsets:\n > f = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\n\n // Create an input strided array:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value starting from the third element:\n > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\n > y\n [ 0.0, 0.0, 3.0, 4.0 ]\n\n See Also\n --------\n strided.dispatch\n","strided.floor":"\nstrided.floor( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -4.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor","strided.inv":"\nstrided.inv( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 0.5, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.sinv\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.sinv","strided.mul":"\nstrided.mul( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ -6.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -15.0, 4.0 ]\n > z0\n [ 0.0, 0.0, -15.0, 4.0 ]\n\n\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 4.0, -15.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.sub\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 4.0, -15.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.sub","strided.mulBy":"\nstrided.mulBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 12.0, 33.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 52.0, 28.0 ]\n > z0\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n See Also\n --------\n strided.mul, strided.addBy, strided.subBy\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n See Also\n --------\n strided.mul, strided.addBy, strided.subBy","strided.ramp":"\nstrided.ramp( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.sramp\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.sramp","strided.rsqrt":"\nstrided.rsqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.sqrt, base.strided.srsqrt\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.sqrt, base.strided.srsqrt","strided.sinBy":"\nstrided.sinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy( 2, x, 2, y, -1, clbk )\n [ ~-0.002, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sinBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.544, ~0.002 ]\n > y0\n [ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.544, ~0.002 ]","strided.sqrt":"\nstrided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt","strided.sqrtBy":"\nstrided.sqrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy( 2, x, 2, y, -1, clbk )\n [ ~11.045, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sqrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~7.071, 1.0 ]\n > y0\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 122.0, 50.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n See Also\n --------\n strided.sqrt\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 122.0, 50.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n See Also\n --------\n strided.sqrt","strided.sub":"\nstrided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ -5.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -8.0, -3.0 ]\n > z0\n [ 0.0, 0.0, -8.0, -3.0 ]\n\n\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, -3.0, -8.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.mul\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, -3.0, -8.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.mul","strided.subBy":"\nstrided.subBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.subBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 4.0, 5.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 8.0, 7.0 ]\n > z0\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Advanced indexing:\n > x = [ 11.0, 12.0, 13.0, 14.0 ];\n > y = [ 8.0, 7.0, 6.0, 5.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n See Also\n --------\n strided.sub, strided.addBy, strided.mulBy\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Advanced indexing:\n > x = [ 11.0, 12.0, 13.0, 14.0 ];\n > y = [ 8.0, 7.0, 6.0, 5.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n See Also\n --------\n strided.sub, strided.addBy, strided.mulBy","strided.trunc":"\nstrided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc","stridedarray2iterator":"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n N: integer\n Number of values to iterate.\n\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iterator\n","stridedArrayStream":"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n Creates a readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream","string2buffer":"\nstring2buffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = string2buffer( 'beep boop' )\n \n > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n > b.toString()\n 'this is a tést'\n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer\n","sub2ind":"\nsub2ind( shape, ...subscript[, options] )\n Converts subscripts to a linear index.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n subscript: ...integer\n Subscripts.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string|Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If\n equal to 'throw', the function throws an error when a subscript exceeds\n array dimensions. If equal to 'normalize', the function normalizes\n negative subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', the function wraps around subscripts\n exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', the function sets subscripts exceeding array dimensions to\n either `0` (minimum index) or the maximum index along a particular\n dimension. If provided a mode array, each array element specifies the\n mode for a corresponding array dimension. If provided fewer modes than\n dimensions, the function recycles modes using modulo arithmetic.\n Default: [ 'throw' ].\n\n Returns\n -------\n idx: integer\n Linear index.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var idx = sub2ind( d, 1, 2, 2 )\n 17\n\n See Also\n --------\n array, ndarray, ind2sub\n","substringAfter":"\nsubstringAfter( str, search[, fromIndex] )\n Returns the part of a string after a specified substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n fromIndex: integer (optional)\n Index from which to start the search. Default: `0`.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var out = substringAfter( 'Hello World!', 'World' )\n '!'\n > out = substringAfter( 'Hello World!', 'Hello ' )\n 'World!'\n > out = substringAfter( 'Hello World!', 'l', 5 )\n 'd!'\n\n See Also\n --------\n substringBefore, substringBeforeLast, substringAfterLast","substringAfterLast":"\nsubstringAfterLast( str, search[, fromIndex] )\n Returns the part of a string after the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n fromIndex: integer (optional)\n Index of last character to be considered beginning of a match.\n Default: `str.length`.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var out = substringAfterLast( 'beep boop beep baz', 'beep' )\n ' baz'\n > out = substringAfterLast( 'Hello World!', 'Hello ' )\n 'World!'\n > out = substringAfterLast( 'Hello World!', 'o', 5 )\n ' World!'\n\n See Also\n --------\n substringBefore, substringBeforeLast, substringAfter","substringBefore":"\nsubstringBefore( str, search )\n Returns the part of a string before a specified substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = substringBefore( str, ' ' )\n 'beep'\n > out = substringBefore( str, 'o' )\n 'beep b'\n\n See Also\n --------\n substringBeforeLast, substringAfter, substringAfterLast","substringBeforeLast":"\nsubstringBeforeLast( str, search )\n Returns the part of a string before the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'Beep Boop Beep';\n > var out = substringBeforeLast( str, 'Beep' )\n 'Beep Boop '\n > out = substringBeforeLast( str, 'Boop' )\n 'Beep '\n\n See Also\n --------\n substringBefore, substringAfter, substringAfterLast","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on July 10, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on May 9, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK\n","Symbol":"\nSymbol( [description] )\n Returns a symbol.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support symbols.\n\n Parameters\n ----------\n description: string (optional)\n Symbol description which can be used for debugging but not to access the\n symbol itself.\n\n Returns\n -------\n out: symbol\n Symbol.\n\n Examples\n --------\n > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n","tabulate":"\ntabulate( collection )\n Generates a frequency table.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulate( collection )\n [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulateBy\n","tabulateBy":"\ntabulateBy( collection, [options,] indicator )\n Generates a frequency table according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > function indicator( value ) { return value[ 0 ]; };\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulateBy( collection, indicator )\n [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulate\n","tabulateByAsync":"\ntabulateByAsync( collection, [options,] indicator, done )\n Generates a frequency table according to an indicator function.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, indicator, done )\n 750\n 1000\n 2500\n 3000\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n 750\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy","thunk":"\nthunk( fcn[, ...args] )\n Returns a thunk.\n\n Parameters\n ----------\n fcn: Function\n Function to convert to a thunk.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n out: Function\n Thunk.\n\n Examples\n --------\n > var fcn = thunk( base.add, 2, 3 );\n > var v = fcn()\n 5\n > v = fcn()\n 5\n\n","tic":"\ntic()\n Returns a high-resolution time.\n\n The returned array has the following format: `[seconds, nanoseconds]`.\n\n Returns\n -------\n out: Array\n High resolution time.\n\n Examples\n --------\n > var t = tic()\n [ , ]\n\n See Also\n --------\n toc\n","timeit":"\ntimeit( code, [options,] clbk )\n Times a snippet.\n\n If the `asynchronous` option is set to `true`, the implementation assumes\n that `before`, `after`, and `code` snippets are all asynchronous.\n Accordingly, these snippets should invoke a `next( [error] )` callback\n once complete. The implementation wraps the snippet within a function\n accepting two arguments: `state` and `next`.\n\n The `state` parameter is simply an empty object which allows the `before`,\n `after`, and `code` snippets to share state.\n\n Notes:\n\n - Snippets always run in strict mode.\n - Always verify results. Doing so prevents the compiler from performing dead\n code elimination and other optimization techniques, which would render\n timing results meaningless.\n - Executed code is not sandboxed and has access to the global state. You are\n strongly advised against timing untrusted code. To time untrusted code,\n do so in an isolated environment (e.g., a separate process with restricted\n access to both global state and the host environment).\n - Wrapping asynchronous code does add overhead, but, in most cases, the\n overhead should be negligible compared to the execution cost of the timed\n snippet.\n - When the `asynchronous` option is `true`, ensure that the main `code`\n snippet is actually asynchronous. If a snippet releases the zalgo, an\n error complaining about exceeding the maximum call stack size is highly\n likely.\n - While many benchmark frameworks calculate various statistics over raw\n timing results (e.g., mean and standard deviation), do not do this.\n Instead, consider the fastest time an approximate lower bound for how fast\n an environment can execute a snippet. Slower times are more likely\n attributable to other processes interfering with timing accuracy rather\n than attributable to variability in JavaScript's speed. In which case, the\n minimum time is most likely the only result of interest. When considering\n all raw timing results, apply common sense rather than statistics.\n\n Parameters\n ----------\n code: string\n Snippet to time.\n\n options: Object (optional)\n Options.\n\n options.before: string (optional)\n Setup code. Default: `''`.\n\n options.after: string (optional)\n Cleanup code. Default: `''`.\n\n options.iterations: integer|null (optional)\n Number of iterations. If `null`, the number of iterations is determined\n by trying successive powers of `10` until the total time is at least\n `0.1` seconds. Default: `1e6`.\n\n options.repeats: integer (optional)\n Number of repeats. Default: `3`.\n\n options.asynchronous: boolean (optional)\n Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n clbk: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > var code = 'var x = Math.pow( Math.random(), 3 );';\n > code += 'if ( x !== x ) {';\n > code += 'throw new Error( \\'Something went wrong.\\' );';\n > code += '}';\n > function done( error, results ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.dir( results );\n ... };\n > timeit( code, done )\n e.g.,\n {\n \"iterations\": 1000000,\n \"repeats\": 3,\n \"min\": [ 0, 135734733 ], // [seconds,nanoseconds]\n \"elapsed\": 0.135734733, // seconds\n \"rate\": 7367311.062526641, // iterations/second\n \"times\": [ // raw timing results\n [ 0, 145641393 ],\n [ 0, 135734733 ],\n [ 0, 140462721 ]\n ]\n }\n\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n\n Returns\n -------\n dir: string\n Directory for temporary files.\n\n Examples\n --------\n > var dir = tmpdir()\n e.g., '/path/to/temporary/files/directory'\n\n See Also\n --------\n configdir, homedir\n","toc":"\ntoc( time )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n\n Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n Parameters\n ----------\n time: Array\n High-resolution time.\n\n Returns\n -------\n out: Array\n High resolution time difference.\n\n Examples\n --------\n > var start = tic();\n > var delta = toc( start )\n [ , ]\n\n See Also\n --------\n tic\n","tokenize":"\ntokenize( str[, keepWhitespace] )\n Tokenizes a string.\n\n To include whitespace characters (spaces, tabs, line breaks) in the output\n array, set `keepWhitespace` to `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n keepWhitespace: boolean (optional)\n Boolean indicating whether whitespace characters should be returned as\n part of the token array. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of tokens.\n\n Examples\n --------\n > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n > out = tokenize( 'Hello World!', true )\n [ 'Hello', ' ', 'World', '!' ]\n\n","transformStream":"\ntransformStream( [options] )\n Returns a transform stream.\n\n If a transform function is not provided, the returned stream will be a\n simple pass through stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = transformStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n","transformStream.factory":"\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","transformStream.objectMode":"\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();","transformStream.ctor":"\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","trim":"\ntrim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n See Also\n --------\n ltrim, pad, rtrim\n","truncate":"\ntruncate( str, len[, ending] )\n Truncates a string to a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n ending: string (optional)\n Custom ending. Default: '...'.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = truncate( str, 5 )\n 'be...'\n\n > out = truncate( str, 5, '|' )\n 'beep|'\n\n See Also\n --------\n truncateMiddle","truncateMiddle":"\ntruncateMiddle( str, len[, seq] )\n Truncates a string in the middle to a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n seq: string (optional)\n Custom replacement sequence. Default: '...'.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = truncateMiddle( str, 5 )\n 'b...p'\n\n > out = truncateMiddle( str, 5, '|' )\n 'be|op'\n\n See Also\n --------\n truncate","trycatch":"\ntrycatch( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: any\n Value to return if a function throws an error.\n\n Returns\n -------\n z: any\n Either the return value of `x` or the provided argument `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > var z = trycatch( x, -1.0 )\n \n\n See Also\n --------\n trycatchAsync, trythen\n","trycatchAsync":"\ntrycatchAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts two arguments:\n\n - error: error object.\n - result: function result.\n\n The `done` callback is invoked upon function completion and is provided two\n arguments:\n\n - error: error object.\n - result: either the result of `x` or the provided argument `y`.\n\n If `x` invokes `clbk` with an error argument, the function invokes the\n `done` callback with both the error and the argument `y`.\n\n If `x` does not invoke `clbk` with an error argument, the function invokes\n the `done` callback with a first argument equal to `null` and the function\n `result`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: any\n Value to return if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... // process error...\n ... }\n ... console.log( result );\n ... };\n > trycatchAsync( x, 'boop', done )\n 'boop'\n\n See Also\n --------\n trycatch, trythenAsync\n","tryFunction":"\ntryFunction( fcn[, thisArg] )\n Wraps a function in a try/catch block.\n\n If provided an asynchronous function, the returned function only traps\n errors which occur during the current event loop tick.\n\n If a function throws a literal, the literal is serialized as a string and\n returned as an `Error` object.\n\n Parameters\n ----------\n fcn: Function\n Function to wrap.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Wrapped function.\n\n Examples\n --------\n > function fcn() { throw new Error( 'beep boop' ); };\n > var f = tryFunction( fcn );\n > var out = f();\n > out.message\n 'beep boop'\n\n","tryRequire":"\ntryRequire( id )\n Wraps `require` in a `try/catch` block.\n\n This function traps and returns any errors encountered when attempting to\n require a module.\n\n Use caution when attempting to resolve a relative path or a local module.\n This function attempts to resolve a module from its current path. Thus, the\n function is unable to resolve anything which is not along its search path.\n For local requires, use an absolute file path.\n\n Parameters\n ----------\n id: string\n Module id.\n\n Returns\n -------\n out: any|Error\n Resolved module or an `Error`.\n\n Examples\n --------\n > var out = tryRequire( '_unknown_module_id_' )\n \n\n","trythen":"\ntrythen( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n\n The function `y` is provided a single argument:\n\n - error: the error thrown by `x`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: Function\n Function to invoke if an initial function throws an error.\n\n Returns\n -------\n z: any\n The return value of either `x` or `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > function y() {\n ... return -1.0;\n ... };\n > var z = trythen( x, y )\n \n\n See Also\n --------\n trycatch, trythenAsync\n","trythenAsync":"\ntrythenAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the function invokes a `done` callback with\n its first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the function invokes a function `y`. The\n number of arguments provided to `y` depends on the function's length. If `y`\n is a unary function, `y` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n Otherwise, `y` is provided two arguments:\n\n - error: the error from `x`.\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument equal to `null` and all other arguments provided by `y`.\n\n If the error argument is truthy, the `done` callback is invoked with only\n the error argument provided by `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: Function\n Function to invoke if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > trythenAsync( x, y, done )\n 'boop'\n\n See Also\n --------\n trycatchAsync, trythen\n","ttest":"\nttest( x[, y][, options] )\n Computes a one-sample or paired Student's t test.\n\n When no `y` is supplied, the function performs a one-sample t-test for the\n null hypothesis that the data in array or typed array `x` is drawn from a\n normal distribution with mean zero and unknown variance.\n\n When array or typed array `y` is supplied, the function tests whether the\n differences `x - y` come from a normal distribution with mean zero and\n unknown variance via the paired t-test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n y: Array (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed mean under H0 (or difference in means when `y` is supplied).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.mean: number\n Sample mean of `x` or `x - y`, respectively.\n\n out.sd: number\n Standard error of the mean.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample t-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ttest( x )\n {\n rejected: false,\n pValue: ~0.722,\n statistic: ~0.357,\n ci: [~-0.333,~0.479],\n // ...\n }\n\n // Paired t-test:\n > rnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\n > x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... y[ i ] = rnorm();\n ... }\n > out = ttest( x, y )\n {\n rejected: false,\n pValue: ~0.191,\n statistic: ~1.315,\n ci: [ ~-0.196, ~0.964 ],\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.1916\n statistic: 1.3148\n df: 99\n 95% confidence interval: [-0.1955,0.9635]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose custom significance level:\n > var arr = [ 2, 4, 3, 1, 0 ];\n > out = ttest( arr, { 'alpha': 0.01 } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0474\n statistic: 2.8284\n df: 4\n 99% confidence interval: [-1.2556,5.2556]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n // Test for a mean equal to five:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'mu': 5 } )\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~3.758, ~6.242 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'alternative': 'less' } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is less than 0\n\n pValue: 0.9998\n statistic: 11.1803\n df: 4\n 95% confidence interval: [-Infinity,5.9534]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n > out = ttest( arr, { 'alternative': 'greater' } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is greater than 0\n\n pValue: 0.0002\n statistic: 11.1803\n df: 4\n 95% confidence interval: [4.0466,Infinity]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest2\n","ttest2":"\nttest2( x, y[, options] )\n Computes a two-sample Student's t test.\n\n By default, the function performs a two-sample t-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n options.variance: string (optional)\n String indicating if the test should be conducted under the assumption\n that the unknown variances of the normal distributions are `equal` or\n `unequal`. As a default choice, the function carries out the Welch test\n (using the Satterthwaite approximation for the degrees of freedom),\n which does not have the requirement that the variances of the underlying\n distributions are equal. If the equal variances assumption seems\n warranted, set the option to `equal`. Default: `unequal`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Student's sleep data:\n > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n > var out = ttest2( x, y )\n {\n rejected: false,\n pValue: ~0.079,\n statistic: ~-1.861,\n ci: [ ~-3.365, ~0.205 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 95% confidence interval: [-3.3655,0.2055]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ttest2( x, y, { 'alpha': 0.1 } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 90% confidence interval: [-3.0534,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 10% significance level\n\n // Perform one-sided tests:\n > out = ttest2( x, y, { 'alternative': 'less' } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.0397\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-Infinity,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n > out = ttest2( x, y, { 'alternative': 'greater' } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.9603\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-3.0534,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Run tests with equal variances assumption:\n > x = [ 2, 3, 1, 4 ];\n > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n > out = ttest2( x, y, { 'variance': 'equal' } );\n > table = out.print()\n Two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.8848\n statistic: -0.1486\n df: 10\n 95% confidence interval: [-1.9996,1.7496]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 3.0 );\n ... }\n > y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 1.0, 3.0 );\n ... }\n > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n {\n rejected: false,\n pValue: ~0.642,\n statistic: ~-0.466,\n ci: [ ~-0.0455, ~1.646 ],\n // ...\n }\n\n See Also\n --------\n ttest\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > TWO_PI\n 6.283185307179586\n\n See Also\n --------\n PI\n","typedarray":"\ntypedarray( [dtype] )\n Creates a typed array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray()\n \n > arr = typedarray( 'float32' )\n \n\n\ntypedarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = typedarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Complex128Array, Complex64Array, Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","typedarray2json":"\ntypedarray2json( arr )\n Returns a JSON representation of a typed array.\n\n The following typed array types are supported:\n\n - Float64Array\n - Float32Array\n - Int32Array\n - Uint32Array\n - Int16Array\n - Uint16Array\n - Int8Array\n - Uint8Array\n - Uint8ClampedArray\n - Complex64Array\n - Complex128Array\n - BooleanArray\n\n The returned JSON object has the following properties:\n\n - type: typed array type.\n - data: typed array data as a generic array.\n\n The implementation supports custom typed arrays and sets the `type` field to\n the closest known typed array type.\n\n Parameters\n ----------\n arr: TypedArray\n Typed array to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var arr = new Float64Array( 2 );\n > arr[ 0 ] = 5.0;\n > arr[ 1 ] = 3.0;\n > var json = typedarray2json( arr )\n { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n See Also\n --------\n reviveTypedArray\n","typedarrayCtors":"\ntypedarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayCtors( 'float64' )\n \n > ctor = typedarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = typedarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, ndarrayDataTypes\n","typedarraypool":"\ntypedarraypool( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n Memory is **uninitialized**, which means that the contents of a returned\n typed array may contain sensitive contents.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool()\n []\n > arr = typedarraypool( 'float32' )\n []\n\n\ntypedarraypool( length[, dtype] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > arr = typedarraypool( 5, 'int32' )\n \n\n\ntypedarraypool( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n \n\n\ntypedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n \n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []\n\n\ntypedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n\n\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear();\n\n\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n \n\n\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n \n\n\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n typedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n typedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]typedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []typedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]","typedarraypool.free":"\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );","typedarraypool.clear":"\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear();","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n ","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n ","typedarraypool.factory":"\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray","typemax":"\ntypemax( dtype )\n Returns the maximum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var m = typemax( 'int8' )\n 127\n > m = typemax( 'uint32' )\n 4294967295\n\n See Also\n --------\n realmax, typemin\n","typemin":"\ntypemin( dtype )\n Returns the minimum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var m = typemin( 'int8' )\n -128\n > m = typemin( 'uint32' )\n 0\n\n See Also\n --------\n realmin, typemax\n","typeOf":"\ntypeOf( value )\n Determines a value's type.\n\n The following values are not natively provided in older JavaScript engines:\n\n - Map\n - Set\n - WeakMap\n - WeakSet\n - Symbol\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n The value's type.\n\n Examples\n --------\n // Built-ins:\n > var t = typeOf( 'a' )\n 'string'\n > t = typeOf( 5 )\n 'number'\n > t = typeOf( NaN )\n 'number'\n > t = typeOf( true )\n 'boolean'\n > t = typeOf( false )\n 'boolean'\n > t = typeOf( null )\n 'null'\n > t = typeOf( undefined )\n 'undefined'\n > t = typeOf( [] )\n 'array'\n > t = typeOf( {} )\n 'object'\n > t = typeOf( function noop() {} )\n 'function'\n > t = typeOf( Symbol( 'beep' ) )\n 'symbol'\n > t = typeOf( /.+/ )\n 'regexp'\n > t = typeOf( new String( 'beep' ) )\n 'string'\n > t = typeOf( new Number( 5 ) )\n 'number'\n > t = typeOf( new Boolean( false ) )\n 'boolean'\n > t = typeOf( new Array() )\n 'array'\n > t = typeOf( new Object() )\n 'object'\n > t = typeOf( new Int8Array( 10 ) )\n 'int8array'\n > t = typeOf( new Uint8Array( 10 ) )\n 'uint8array'\n > t = typeOf( new Uint8ClampedArray( 10 ) )\n 'uint8clampedarray'\n > t = typeOf( new Int16Array( 10 ) )\n 'int16array'\n > t = typeOf( new Uint16Array( 10 ) )\n 'uint16array'\n > t = typeOf( new Int32Array( 10 ) )\n 'int32array'\n > t = typeOf( new Uint32Array( 10 ) )\n 'uint32array'\n > t = typeOf( new Float32Array( 10 ) )\n 'float32array'\n > t = typeOf( new Float64Array( 10 ) )\n 'float64array'\n > t = typeOf( new ArrayBuffer( 10 ) )\n 'arraybuffer'\n > t = typeOf( new Date() )\n 'date'\n > t = typeOf( new RegExp( '.+' ) )\n 'regexp'\n > t = typeOf( new Map() )\n 'map'\n > t = typeOf( new Set() )\n 'set'\n > t = typeOf( new WeakMap() )\n 'weakmap'\n > t = typeOf( new WeakSet() )\n 'weakset'\n > t = typeOf( new Error( 'beep' ) )\n 'error'\n > t = typeOf( new TypeError( 'beep' ) )\n 'typeerror'\n > t = typeOf( new SyntaxError( 'beep' ) )\n 'syntaxerror'\n > t = typeOf( new ReferenceError( 'beep' ) )\n 'referenceerror'\n > t = typeOf( new URIError( 'beep' ) )\n 'urierror'\n > t = typeOf( new RangeError( 'beep' ) )\n 'rangeerror'\n > t = typeOf( new EvalError( 'beep' ) )\n 'evalerror'\n > t = typeOf( Math )\n 'math'\n > t = typeOf( JSON )\n 'json'\n\n // Arguments object:\n > function beep() { return arguments; };\n > t = typeOf( beep() )\n 'arguments'\n\n // Node.js Buffer object:\n > t = typeOf( new Buffer( 10 ) )\n 'buffer'\n\n // Custom constructor:\n > function Person() { return this };\n > t = typeOf( new Person() )\n 'person'\n\n // Anonymous constructor:\n > var Foo = function () { return this; };\n > t = typeOf( new Foo() )\n '' || 'foo'\n\n See Also\n --------\n constructorName, nativeClass\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n\n The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n Examples\n --------\n > UINT8_MAX\n 255\n\n See Also\n --------\n INT8_MAX\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n\n Examples\n --------\n > UINT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT8_NUM_BYTES, UINT16_NUM_BYTES, UINT32_NUM_BYTES\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array()\n \n\n\nUint8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'\n\n\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n \n\n\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5\n\n\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray\n","Uint8Array.from":"\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint8Array.of":"\nUint8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1","Uint8Array.name":"\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n ","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray()\n \n\n\nUint8ClampedArray( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8ClampedArray( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n \n\n\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5\n\n\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns an empty array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n ","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns an empty array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n\n The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n Examples\n --------\n > UINT16_MAX\n 65535\n\n See Also\n --------\n INT16_MAX\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n\n Examples\n --------\n > UINT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT16_NUM_BYTES, UINT32_NUM_BYTES, UINT8_NUM_BYTES\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array()\n \n\n\nUint16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Uint16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'\n\n\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n \n\n\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10\n\n\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Uint16Array.from":"\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint16Array.of":"\nUint16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2","Uint16Array.name":"\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n ","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n\n The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n Examples\n --------\n > UINT32_MAX\n 4294967295\n\n See Also\n --------\n INT32_MAX\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n\n Examples\n --------\n > UINT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT32_NUM_BYTES, UINT16_NUM_BYTES, UINT8_NUM_BYTES\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array()\n \n\n\nUint32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Uint32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'\n\n\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n \n\n\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20\n\n\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray\n","Uint32Array.from":"\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint32Array.of":"\nUint32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4","Uint32Array.name":"\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n ","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray","umask":"\numask( [mask,] [options] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n\n A mask is a set of bits, each of which restricts how its corresponding\n permission is set for newly created files.\n\n On POSIX platforms, each file has a set of attributes that control who can\n read, write, or execute that file. Upon creating a file, file permissions\n must be set to an initial setting. The process mask restricts those\n permission settings.\n\n If the mask contains a bit set to \"1\", the corresponding initial file\n permission is disabled. If the mask contains a bit set to \"0\", the\n corresponding permission is left to be determined by the requesting process\n and the system.\n\n The process mask is thus a filter that removes permissions as a file is\n created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n In octal representation, a mask is a four digit number, e.g., 0077,\n comprised as follows:\n\n - 0: special permissions (setuid, setgid, sticky bit)\n - 0: (u)ser/owner permissions\n - 7: (g)roup permissions\n - 7: (o)thers/non-group permissions\n\n Octal codes correspond to the following permissions:\n\n - 0: read, write, execute\n - 1: read, write\n - 2: read, execute\n - 3: read\n - 4: write, execute\n - 5: write\n - 6: execute\n - 7: no permissions\n\n If provided fewer than four digits, the mask is left-padded with zeros.\n\n Note, however, that only the last three digits (i.e., the file permissions\n digits) of the mask are actually used when the mask is applied.\n\n Permissions can be represented using the following symbolic form:\n\n u=rwx,g=rwx,o=rwx\n\n where\n\n - u: user permissions\n - g: group permissions\n - o: other/non-group permissions\n - r: read\n - w: write\n - x: execute\n\n When setting permissions using symbolic notation, the function accepts a\n mask expression of the form:\n\n []\n\n where \"classes\" may be a combination of\n\n - u: user\n - g: group\n - o: other/non-group\n - a: all\n\n \"symbols\" may be a combination of\n\n - r: read\n - w: write\n - x: execute\n - X: special execute\n - s: setuid/gid on execution\n - t: sticky\n\n and \"operator\" may be one of\n\n - +: enable\n - -: disable\n - =: enable specified and disable unspecified permissions\n\n For example,\n\n - u-w: disable user write permissions\n - u+w: enable user write permissions\n - u=w: enable user write permissions and disable user read and execute\n\n To specify multiple changes, provide a comma-separated list of mask\n expressions. For example,\n\n u+rwx,g-x,o=r\n\n would enable user read, write, and execute permissions, disable group\n execute permissions, enable other read permissions, and disable other\n write and execute permissions.\n\n The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n is the default class if a class is omitted when specifying permissions. For\n example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n Parameters\n ----------\n mask: integer|string (optional)\n Mask or mask expression. If the mask is a string, the mask is assumed to\n be in symbolic notation.\n\n options: Object (optional)\n Options.\n\n options.symbolic: boolean (optional)\n Boolean indicating whether to return the mask using symbolic notation.\n\n Returns\n -------\n mask: integer|string\n Process mask. If provided a mask, the returned value is the previous\n mask; otherwise, the returned value is the current process mask.\n\n Examples\n --------\n > var mask = umask()\n \n > mask = umask( { 'symbolic': true } )\n \n\n","uncapitalize":"\nuncapitalize( str )\n Lowercases the first character of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = uncapitalize( 'Beep' )\n 'beep'\n > out = uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n capitalize, lowercase\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj )\n Converts the first letter of each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'AA': 1, 'BB': 2 };\n > var out = uncapitalizeKeys( obj )\n { 'aA': 1, 'bB': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","uncurry":"\nuncurry( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurry( addX );\n > var sum = fcn( 2, 3 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( x ) {\n ... return function add( y ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurry( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addX( x ) {\n ... this.x = x;\n ... return addY;\n ... };\n > function addY( y ) {\n ... return this.x + y;\n ... };\n > fcn = uncurry( addX, {} );\n > sum = fcn( 2, 3 )\n 5\n\n See Also\n --------\n curry, uncurryRight\n","uncurryRight":"\nuncurryRight( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Provided arguments are applied starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurryRight( addX );\n > var sum = fcn( 3, 2 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( y ) {\n ... return function add( x ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurryRight( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addY( y ) {\n ... this.y = y;\n ... return addX;\n ... };\n > function addX( x ) {\n ... return x + this.y;\n ... };\n > fcn = uncurryRight( addY, {} );\n > sum = fcn( 3, 2 )\n 5\n\n See Also\n --------\n curry, curryRight, uncurry\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n\n Examples\n --------\n > UNICODE_MAX\n 1114111\n\n See Also\n --------\n UNICODE_MAX_BMP\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n Examples\n --------\n > UNICODE_MAX_BMP\n 65535\n\n See Also\n --------\n UNICODE_MAX\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data,] [options] )\n Returns a sparkline column chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeColumnChartSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data,] [options] )\n Returns a sparkline line chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: LineChart\n Line chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a line chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeLineChartSparkline( data );\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeSparkline":"\nUnicodeSparkline( [data,] [options] )\n Returns a Unicode sparkline instance.\n\n The following chart types are supported:\n\n - column: column chart (e.g., ▃▆▂▄▁▅▅).\n - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.type: string (optional)\n Chart type. Default: 'column'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.type\n Chart type.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n > chart.type = 'line';\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data,] [options] )\n Returns a sparkline tristate chart instance.\n\n In a tristate chart, negative values are encoded as lower blocks, positive\n values are encoded as upper blocks, and values equal to zero are encoded as\n middle lines.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: TristateChart\n Tristate chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a tristate chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n > var chart = new UnicodeTristateChartSparkline( data );\n > chart.render()\n '▄▀──▀▄▄▀'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data,] [options] )\n Returns a sparkline up/down chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ↑ |\n | -1 | ↓ |\n\n If provided any other value other than 1 or -1, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: UpDownChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1 or -1.\n\n chart.render()\n Renders an up/down chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n > var chart = new UnicodeUpDownChartSparkline( data );\n > chart.render()\n '↓↑↑↑↑↓↓↑'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data,] [options] )\n Returns a sparkline win/loss chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ╵ |\n | -1 | ╷ |\n | 2 | └ |\n | -2 | ┌ |\n\n If a `2` or `-2` is preceded by a `2` or `-2`,\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 2 | ┴ |\n | -2 | ┬ |\n\n Based on the win/loss analogy,\n\n - 1: win away\n - 2: win at home\n - -1: loss away\n - -2: loss at home\n\n If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: WinLossChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n chart.render()\n Renders a win/loss chart sparkline.\n\n Examples\n --------\n > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n > var chart = new UnicodeWinLossChartSparkline( data );\n > chart.render()\n '┌╵└┴╵╷╷╵'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline\n","unlink":"\nunlink( path, clbk )\n Asynchronously removes a directory entry.\n\n If a provided path is a symbolic link, the function removes the symbolic\n link named by the path and does not affect any file or directory named by\n the contents of the symbolic link.\n\n Otherwise, the function removes the link named by the provided path and\n decrements the link count of the file referenced by the link.\n\n When a file's link count becomes 0 and no process has the file open, the\n space occupied by the file is freed and the file is no longer accessible.\n\n If one or more processes have the file open when the last link is removed,\n the link is removed before the function returns; however, the removal of\n file contents is postponed until all references to the file are closed.\n\n If the path refers to a socket, FIFO, or device, processes which have the\n object open may continue to use it.\n\n The path argument should *not* be a directory. To remove a directory, use\n rmdir().\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n clbk: Function\n Callback to invoke upon removing an entry.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists\n","unlink.sync":"\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists","unshift":"\nunshift( collection, ...items )\n Adds one or more elements to the beginning of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = unshift( arr, 6.0, 7.0 )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = unshift( arr, 3.0, 4.0 )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = unshift( arr, 2.0, 3.0 )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n pop, push, shift\n","until":"\nuntil( predicate, fcn[, thisArg] )\n Invokes a function until a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > until( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, untilAsync, untilEach, whilst\n","untilAsync":"\nuntilAsync( predicate, fcn, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from zero).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is falsy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > untilAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, until, whileAsync\n","untilEach":"\nuntilEach( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > untilEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEachRight, whileEach\n","untilEachRight":"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > untilEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n untilEach, whileEachRight\n","unzip":"\nunzip( arr[, idx] )\n Unzips a zipped array (i.e., a nested array of tuples).\n\n Parameters\n ----------\n arr: Array\n Zipped array.\n\n idx: Array (optional)\n Array of indices specifying which tuple elements to unzip.\n\n Returns\n -------\n out: Array\n Array of unzipped arrays.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > var out = unzip( arr )\n [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n // Provide indices:\n > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > out = unzip( arr, [ 0, 2 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n zip\n","uppercase":"\nuppercase( str )\n Converts a string to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n capitalize, lowercase\n","uppercaseKeys":"\nuppercaseKeys( obj )\n Converts each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'a': 1, 'b': 2 };\n > var out = uppercaseKeys( obj )\n { 'A': 1, 'B': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n\n Returns\n -------\n out: Array\n List of US state two-letter abbreviations.\n\n Examples\n --------\n > var list = US_STATES_ABBR()\n [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n\n Returns\n -------\n out: Array\n List of US state capitals.\n\n Examples\n --------\n > var list = US_STATES_CAPITALS()\n [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS_NAMES, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n\n Returns\n -------\n out: Object\n An object mapping US state capitals to state names.\n\n Examples\n --------\n > var out = US_STATES_CAPITALS_NAMES()\n { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n\n Returns\n -------\n out: Array\n List of US state names.\n\n Examples\n --------\n > var list = US_STATES_NAMES()\n [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS, US_STATES_CAPITALS_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n\n Returns\n -------\n out: Object\n An object mapping US state names to state capitals.\n\n Examples\n --------\n > var out = US_STATES_NAMES_CAPITALS()\n { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n\n The following byte sequences are used to represent a character. The sequence\n depends on the code point:\n\n 0x00000000 - 0x0000007F:\n 0xxxxxxx\n\n 0x00000080 - 0x000007FF:\n 110xxxxx 10xxxxxx\n\n 0x00000800 - 0x0000FFFF:\n 1110xxxx 10xxxxxx 10xxxxxx\n\n 0x00010000 - 0x001FFFFF:\n 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n The `x` bit positions correspond to code point bits.\n\n Only the shortest possible multi-byte sequence which can represent a code\n point is used.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: Array\n Array of integers.\n\n Examples\n --------\n > var str = '☃';\n > var out = utf16ToUTF8Array( str )\n [ 226, 152, 131 ]\n\n","vartest":"\nvartest( x, y[, options] )\n Computes a two-sample F-test for equal variances.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`.\n\n options.ratio: number (optional)\n Positive number denoting the ratio of the two population variances under\n the null hypothesis. Default: `1`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the ratio of variances.\n\n out.nullValue: number\n Assumed ratio of variances under H0.\n\n out.xvar: number\n Sample variance of `x`.\n\n out.yvar: number\n Sample variance of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.dfX: number\n Numerator degrees of freedom.\n\n out.dfY: number\n Denominator degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [ 610, 610, 550, 590, 565, 570 ];\n > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n > var out = vartest( x, y )\n {\n rejected: false,\n pValue: ~0.399,\n statistic: ~1.976,\n ci: [ ~0.374, ~13.542 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n F test for comparing two variances\n\n Alternative hypothesis: True ratio in variances is not equal to 1\n\n pValue: 0.3992\n statistic: 1.976\n variance of x: 617.5 (df of x: 5)\n variance of y: 312.5 (df of y: 7)\n 95% confidence interval: [0.3739,13.5417]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n See Also\n --------\n bartlettTest\n","waterfall":"\nwaterfall( fcns, clbk[, thisArg] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n\n The last argument applied to each waterfall function is a callback. The\n callback should be invoked upon a series function completion. The first\n argument is reserved as an error argument (which can be `null`). Any results\n which should be passed to the next function in the series should be provided\n beginning with the second argument.\n\n If any function calls the provided callback with a truthy `error` argument,\n the waterfall suspends execution and immediately calls the completion\n callback for subsequent error handling.\n\n Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n the completion callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();\n\n","waterfall.factory":"\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor )\n WebAssembly memory constructor.\n\n Parameters\n ----------\n descriptor: Object\n Memory descriptor object.\n\n descriptor.initial: integer\n Initial memory size in units of WebAssembly pages (i.e., 64KiB).\n\n descriptor.maximum: integer (optional)\n Maximum memory size in units of WebAssembly pages (i.e., 64KiB).\n\n descriptor.shared: boolean (optional)\n Boolean indicating whether the memory is shared. Default: false.\n\n Returns\n -------\n out: Memory\n WebAssembly memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } )\n \n\n\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.buffer\n \n\n\nWebAssemblyMemory.prototype.grow( delta )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n\n Upon increasing the size, the previous ArrayBuffer is detached, thus\n invalidating any typed arrays which were views over the previous\n ArrayBuffer.\n\n Detachment means that the previous ArrayBuffer byte length becomes zero, and\n it no longer has bytes accessible to JavaScript.\n\n ArrayBuffer detachment applies even when `delta` is zero.\n\n Detachment only applies for non-shared memory instances. For a shared memory\n instance, the initial buffer (which is a SharedArrayBuffer) will not become\n detached and, instead, its length will not be updated.\n\n Accesses to the `buffer` property after growing a SharedArrayBuffer will\n yield a larger SharedArrayBuffer which may access a larger span of memory\n than the buffer before growing memory.\n\n Every SharedArrayBuffer accessed via the `buffer` property will always refer\n to the start of the same memory address range and thus manipulate the same\n data.\n\n Parameters\n ----------\n delta: integer\n Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n underlying memory.\n\n Returns\n -------\n out: integer\n Size of the previous memory (in units of pages).\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.grow( 1 )\n \n\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.buffer\n ","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n\n Upon increasing the size, the previous ArrayBuffer is detached, thus\n invalidating any typed arrays which were views over the previous\n ArrayBuffer.\n\n Detachment means that the previous ArrayBuffer byte length becomes zero, and\n it no longer has bytes accessible to JavaScript.\n\n ArrayBuffer detachment applies even when `delta` is zero.\n\n Detachment only applies for non-shared memory instances. For a shared memory\n instance, the initial buffer (which is a SharedArrayBuffer) will not become\n detached and, instead, its length will not be updated.\n\n Accesses to the `buffer` property after growing a SharedArrayBuffer will\n yield a larger SharedArrayBuffer which may access a larger span of memory\n than the buffer before growing memory.\n\n Every SharedArrayBuffer accessed via the `buffer` property will always refer\n to the start of the same memory address range and thus manipulate the same\n data.\n\n Parameters\n ----------\n delta: integer\n Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n underlying memory.\n\n Returns\n -------\n out: integer\n Size of the previous memory (in units of pages).\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.grow( 1 )\n ","whileAsync":"\nwhileAsync( predicate, fcn, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from zero).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is truthy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > whileAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, untilAsync, whilst\n","whileEach":"\nwhileEach( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > whileEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEach, whileEachRight\n","whileEachRight":"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > whileEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n whileEach, untilEachRight\n","whilst":"\nwhilst( predicate, fcn[, thisArg] )\n Invokes a function while a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > whilst( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, until, whileAsync, whileEach\n","wilcoxon":"\nwilcoxon( x[, y][, options] )\n Computes a one-sample or paired Wilcoxon signed rank test.\n\n When no `y` is supplied, the function performs a one-sample Wilcoxon signed\n rank test for the null hypothesis that the data is drawn from a symmetric\n distribution around zero.\n\n When `y` is supplied, the function tests whether the\n differences `x - y` come from a symmetric distribution around zero.\n\n If `x` has less than fifty elements, an exact p-value is computed if there\n are no zero values or ties. Otherwise, a normal approximation is used.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array|TypedArray\n Data array.\n\n y: Array|TypedArray (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`), or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.correction: boolean (optional)\n Determines whether to apply continuity correction adjusting the Wilcoxon\n rank statistic by 0.5 towards the mean when using the normal\n approximation. Default: `true`.\n\n options.exact: boolean (optional)\n Determines whether to force use of the exact distribution instead of a\n normal approximation when there are more than fifty data points.\n Default: `false`.\n\n options.mu: number (optional)\n Hypothesized true location under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n options.zeroMethod: string (optional)\n Method governing how zero-differences are handled (`pratt`, `wilcox`, or\n `zsplit`). When set to `pratt`, differences of zero are used to\n calculate ranks but their ranks are then dropped. When set to `wilcox`,\n all zero-differences are discarded. When set to `zsplit`, differences of\n zero are used to rank and their ranks are then split between positive\n and negative ones. Default: `'wilcox'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.nullValue: number\n Assumed location parameter under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample test:\n > var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\n > var out = wilcoxon( x )\n {\n 'rejected': true,\n 'alpha': 0.05,\n 'pValue': 0.04125976562499978,\n 'statistic': 96\n // ...\n }\n\n // Paired test:\n > runif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\n > var x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = runif();\n ... y[ i ] = runif();\n ... }\n > out = wilcoxon( x, y )\n {\n 'rejected': false,\n 'alpha': 0.05,\n 'pValue': 0.21759090963694638,\n 'statistic': 2702.5,\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired Wilcoxon signed rank test\n\n Alternative hypothesis: Median of the difference `x - y` is not equal to 0\n\n pValue: 0.2176\n statistic: 2702.5\n\n Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n // Choose custom significance level:\n > out = wilcoxon( arr, { 'alpha': 0.01 });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is not equal to 0\n\n pValue: 0.0413\n statistic: 96\n\n Test Decision: Fail to reject null in favor of alternative at 1% significance level\n\n\n // Test for a median equal to ten:\n > out = wilcoxon( arr, { 'mu': 10 })\n {\n 'rejected': false,\n 'alpha': 0.05,\n 'pValue': 0.11169650413134602,\n 'statistic': 88.5,\n 'nullValue': 10,\n // ...\n }\n\n // Perform one-sided tests:\n > out = wilcoxon( arr, { 'alternative': 'less' });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is less than 0\n\n pValue: 0.9823\n statistic: 96\n\n Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n > out = wilcoxon( arr, { 'alternative': 'greater' });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is greater than 0\n\n pValue: 0.0206\n statistic: 96\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest, ztest\n","writableProperties":"\nwritableProperties( value )\n Returns an array of an object's own writable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own writable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = writableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n inheritedWritableProperties, writablePropertiesIn, properties\n","writablePropertiesIn":"\nwritablePropertiesIn( value )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited writable property names and\n symbols.\n\n Examples\n --------\n > var props = writablePropertiesIn( [] )\n\n See Also\n --------\n inheritedWritableProperties, writableProperties, propertiesIn\n","writablePropertyNames":"\nwritablePropertyNames( value )\n Returns an array of an object's own writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNames( obj )\n [ 'a' ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writableProperties, writablePropertyNamesIn, writablePropertySymbols, propertyNames\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value )\n Returns an array of an object's own and inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNamesIn( obj )\n e.g., [ 'a', ... ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertiesIn, writablePropertyNames, writablePropertySymbolsIn, propertyNamesIn\n","writablePropertySymbols":"\nwritablePropertySymbols( value )\n Returns an array of an object's own writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbols( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writableProperties, writablePropertyNames, writablePropertySymbolsIn, propertySymbols\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited writable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbolsIn( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertiesIn, writablePropertyNamesIn, writablePropertySymbols, propertySymbolsIn\n","writeFile":"\nwriteFile( file, data[, options], clbk )\n Asynchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon writing data to a file.\n\n Examples\n --------\n > function onWrite( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile\n","writeFile.sync":"\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile","zip":"\nzip( ...arr[, options] )\n Generates array tuples from input arrays.\n\n Parameters\n ----------\n arr: ...Array\n Input arrays to be zipped.\n\n options: Object (optional)\n Options.\n\n options.trunc: boolean (optional)\n Boolean indicating whether to truncate arrays longer than the shortest\n input array. Default: `true`.\n\n options.fill: any (optional)\n Fill value used for arrays of unequal length. Default: `null`.\n\n options.arrays: boolean (optional)\n Boolean indicating whether an input array should be interpreted as an\n array of arrays to be zipped. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n // Basic usage:\n > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n // Turn off truncation:\n > var opts = { 'trunc': false };\n > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n See Also\n --------\n unzip\n","ztest":"\nztest( x, sigma[, options] )\n Computes a one-sample z-test.\n\n The function performs a one-sample z-test for the null hypothesis that the\n data in array or typed array `x` is drawn from a normal distribution with\n mean zero and standard deviation `sigma`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n sigma: number\n Known standard deviation.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for mean.\n\n out.nullValue: number\n Assumed mean value under H0.\n\n out.sd: number\n Standard error.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test (`One-Sample z-test`).\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample z-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ztest( x, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.180,\n statistic: ~-1.34,\n ci: [ ~-0.66, ~0.124 ],\n ...\n }\n\n // Choose custom significance level and print output:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ztest( arr, 2.0, { 'alpha': 0.01 } );\n > table = out.print()\n One-sample z-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0253\n statistic: 2.2361\n 99% confidence interval: [-0.3039,4.3039]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'mu': 5 } )\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~4.123, ~5.877 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'alternative': 'less' } )\n {\n alpha: 0.05,\n rejected: false,\n pValue: 1,\n statistic: 11.180339887498949,\n ci: [ -Infinity, 5.735600904580115 ],\n // ...\n }\n > out = ztest( arr, 1.0, { 'alternative': 'greater' } )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 11.180339887498949,\n ci: [ 4.264399095419885, Infinity ],\n //...\n }\n\n See Also\n --------\n ztest2\n","ztest2":"\nztest2( x, y, sigmax, sigmay[, options] )\n Computes a two-sample z-test.\n\n By default, the function performs a two-sample z-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means and known\n standard deviations `sigmax` and `sigmay`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n sigmax: number\n Known standard deviation of first group.\n\n sigmay: number\n Known standard deviation of second group.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Drawn from Normal(0,2):\n > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n // Drawn from Normal(1,2):\n > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n > var out = ztest2( x, y, 2.0, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.398,\n statistic: ~-0.844\n ci: [ ~-2.508, ~0.988 ],\n alternative: 'two-sided',\n method: 'Two-sample z-test',\n nullValue: 0,\n xmean: ~0.573,\n ymean: ~1.328\n }\n\n // Print table output:\n > var table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 95% confidence interval: [-2.508,0.998]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 60% confidence interval: [-1.5078,-0.0022]\n\n Test Decision: Reject null in favor of alternative at 40% significance level\n\n // Perform one-sided tests:\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.1993\n statistic: -0.8441\n 95% confidence interval: [-Infinity,0.7162]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.8007\n statistic: -0.8441\n 95% confidence interval: [-2.2262,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 1.0 );\n ... }\n > y = new Array( 100 );\n ... for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 0.0, 2.0 );\n ... }\n > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n {\n rejected: false,\n pValue: ~0.35,\n statistic: ~-0.935\n ci: [ ~1.353, ~2.229 ],\n // ...\n }\n\n See Also\n --------\n ztest\n"} diff --git a/lib/node_modules/@stdlib/repl/info/data/data.csv b/lib/node_modules/@stdlib/repl/info/data/data.csv index fb28c69abc80..930cabb967d5 100644 --- a/lib/node_modules/@stdlib/repl/info/data/data.csv +++ b/lib/node_modules/@stdlib/repl/info/data/data.csv @@ -2445,8 +2445,8 @@ base.strided.ssort2ins,"\nbase.strided.ssort2ins( N:integer, order:number, x:Flo base.strided.ssort2ins.ndarray,"\nbase.strided.ssort2ins.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n" base.strided.ssort2sh,"\nbase.strided.ssort2sh( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n" base.strided.ssort2sh.ndarray,"\nbase.strided.ssort2sh.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n" -base.strided.ssorthp,"\nbase.strided.ssorthp( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using heapsort.\n" -base.strided.ssorthp.ndarray,"\nbase.strided.ssorthp.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n" +base.strided.ssorthp,"\nbase.strided.ssorthp( N:integer, order:number, x:Float32Array, strideX:integer )\n Sorts a single-precision floating-point strided array using heapsort.\n" +base.strided.ssorthp.ndarray,"\nbase.strided.ssorthp.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n" base.strided.ssortins,"\nbase.strided.ssortins( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using insertion sort.\n" base.strided.ssortins.ndarray,"\nbase.strided.ssortins.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n" base.strided.ssortsh,"\nbase.strided.ssortsh( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using Shellsort.\n" @@ -2713,7 +2713,7 @@ Complex128.prototype.byteLength,"\nComplex128.prototype.byteLength\n Length ( COMPLEX128_NAN,"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n" COMPLEX128_NUM_BYTES,"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n" COMPLEX128_ZERO,"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n" -Complex128Array,"\nComplex128Array()\n A 128-bit complex number array.\n\nComplex128Array( length:integer )\n Creates a 128-bit complex number array having a specified length.\n\nComplex128Array( complexarray:Complex128Array )\n Creates a 64-bit complex number array from another complex number array.\n\nComplex128Array( typedarray:TypedArray )\n Creates a 128-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\nComplex128Array( obj:Object )\n Creates a 128-bit complex number array from an array-like object or \n iterable.\n\nComplex128Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a 128-bit complex number array view of an ArrayBuffer.\n" +Complex128Array,"\nComplex128Array()\n A 128-bit complex number array.\n\nComplex128Array( length:integer )\n Creates a 128-bit complex number array having a specified length.\n\nComplex128Array( complexarray:Complex128Array )\n Creates a 64-bit complex number array from another complex number array.\n\nComplex128Array( typedarray:TypedArray )\n Creates a 128-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\nComplex128Array( obj:Object )\n Creates a 128-bit complex number array from an array-like object or\n iterable.\n\nComplex128Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a 128-bit complex number array view of an ArrayBuffer.\n" Complex128Array.from,"\nComplex128Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n" Complex128Array.of,"\nComplex128Array.of( element0:number|ComplexLike[, \n element1:number |ComplexLike[, ...elementN:number|ComplexLike]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n" Complex128Array.BYTES_PER_ELEMENT,"\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n" @@ -2724,7 +2724,7 @@ Complex128Array.prototype.byteOffset,"\nComplex128Array.prototype.byteOffset\n Complex128Array.prototype.BYTES_PER_ELEMENT,"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n" Complex128Array.prototype.length,"\nComplex128Array.prototype.length\n The number of array elements.\n" Complex128Array.prototype.at,"\nComplex128Array.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n" -Complex128Array.prototype.copyWithin,"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n" +Complex128Array.prototype.copyWithin,"\nComplex128Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n" Complex128Array.prototype.entries,"\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n" Complex128Array.prototype.every,"\nComplex128Array.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n" Complex128Array.prototype.fill,"\nComplex128Array.prototype.fill( value:Complex128[, start:integer[, \n end:integer]] )\n Returns a modified typed array filled with a fill value.\n" @@ -2746,15 +2746,15 @@ Complex128Array.prototype.reduceRight,"\nComplex128Array.prototype.reduceRight( Complex128Array.prototype.reverse,"\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n" Complex128Array.prototype.set,"\nComplex128Array.prototype.set( z:Complex128|Complex128Array|ArrayLikeObject[, \n i:integer] )\n Sets one or more array elements.\n" Complex128Array.prototype.slice,"\nComplex128Array.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n" -Complex128Array.prototype.some,"\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n" +Complex128Array.prototype.some,"\nComplex128Array.prototype.some( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether at least one element passes a test.\n" Complex128Array.prototype.sort,"\nComplex128Array.prototype.sort( compareFunction:Function )\n Sorts an array in-place.\n" Complex128Array.prototype.subarray,"\nComplex128Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n" -Complex128Array.prototype.toLocaleString,"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n" +Complex128Array.prototype.toLocaleString,"\nComplex128Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n" Complex128Array.prototype.toReversed,"\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n" Complex128Array.prototype.toSorted,"\nComplex128Array.prototype.toSorted( compareFcn:Function )\n Returns a new typed array containing the elements in sorted order.\n" Complex128Array.prototype.toString,"\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n" Complex128Array.prototype.values,"\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n" -Complex128Array.prototype.with,"\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n" +Complex128Array.prototype.with,"\nComplex128Array.prototype.with( index:integer, value:Complex128 )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n" complexarray,"\ncomplexarray( [dtype:string] )\n Creates a complex typed array.\n\ncomplexarray( length:integer[, dtype:string] )\n Returns a complex number typed array having a specified length.\n\ncomplexarray( complexarray:ComplexArray[, dtype:string] )\n Creates a complex number typed array from another complex number typed\n array.\n\ncomplexarray( obj:Object[, dtype:string] )\n Creates a complex number typed array from an array-like object or iterable.\n\ncomplexarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a complex number typed array view of an ArrayBuffer.\n" complexarrayCtors,"\ncomplexarrayCtors( dtype:string )\n Returns a complex typed array constructor.\n" complexarrayDataTypes,"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n" diff --git a/lib/node_modules/@stdlib/repl/info/data/data.json b/lib/node_modules/@stdlib/repl/info/data/data.json index 8ef714e70cf3..d99e3e54d817 100644 --- a/lib/node_modules/@stdlib/repl/info/data/data.json +++ b/lib/node_modules/@stdlib/repl/info/data/data.json @@ -1 +1 @@ -{"abs":"\nabs( x:ndarray[, options:Object] )\n Computes the absolute value for each element in an ndarray.\n","abs.assign":"\nabs.assign( x:ndarray, y:ndarray )\n Computes the absolute value for each element in an ndarray and assigns\n results to a provided output ndarray.\n","acartesianPower":"\nacartesianPower( x:ArrayLikeObject, n:integer )\n Returns the Cartesian power.\n","acartesianProduct":"\nacartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n Returns the Cartesian product.\n","acartesianSquare":"\nacartesianSquare( x:ArrayLikeObject )\n Returns the Cartesian square.\n","acronym":"\nacronym( str:string[, options:Object] )\n Generates an acronym for a given string.\n","aempty":"\naempty( length:integer[, dtype:string] )\n Creates an uninitialized array having a specified length.\n","aemptyLike":"\naemptyLike( x:TypedArray|Array[, dtype:string] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n","AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n","afull":"\nafull( length:integer, value:any[, dtype:string] )\n Returns a filled array having a specified length.\n","afullLike":"\nafullLike( x:TypedArray|Array[, dtype:string] )\n Returns a filled array having the same length and data type as a provided\n input array.\n","alias2pkg":"\nalias2pkg( alias:string )\n Returns the package name associated with a provided alias.\n","alias2related":"\nalias2related( alias:string )\n Returns aliases related to a specified alias.\n","alias2standalone":"\nalias2standalone( alias:string )\n Returns the standalone package name associated with a provided alias.\n","aliases":"\naliases( [namespace:string] )\n Returns a list of standard library aliases.\n","allocUnsafe":"\nallocUnsafe( size:integer )\n Allocates a buffer having a specified number of bytes.\n","amskfilter":"\namskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n","amskput":"\namskput( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n options:Object] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n","amskreject":"\namskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n","anans":"\nanans( length:integer[, dtype:string] )\n Returns an array filled with NaNs and having a specified length.\n","anansLike":"\nanansLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n","anova1":"\nanova1( x:Array, factor:Array[, options:Object] )\n Performs a one-way analysis of variance.\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n","any":"\nany( collection:Array|TypedArray|Object )\n Tests whether at least one element in a collection is truthy.\n","anyBy":"\nanyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n","anyByAsync":"\nanyByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n","anyByAsync.factory":"\nanyByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n","anyByRight":"\nanyByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n","anyByRightAsync":"\nanyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n","anyInBy":"\nanyInBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one value in an object passes a test implemented by\n a predicate function.\n","anyOwnBy":"\nanyOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one own property of an object passes a\n test implemented by a predicate function.\n","aones":"\naones( length:integer[, dtype:string] )\n Returns an array filled with ones and having a specified length.\n","aonesLike":"\naonesLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n","aoneTo":"\naoneTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n","aoneToLike":"\naoneToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n","APERY":"\nAPERY\n Apéry's constant.\n","aplace":"\naplace( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n options:Object] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n","append":"\nappend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the end of another collection.\n","aput":"\naput( x:ArrayLikeObject, indices:ArrayLikeObject, \n values:ArrayLikeObject[, options:Object] )\n Replaces specified elements of an array with provided values.\n","ARCH":"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n","argumentFunction":"\nargumentFunction( idx:integer )\n Returns a function which always returns a specified argument.\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n","array":"\narray( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )\n Returns a multidimensional array.\n","array2buffer":"\narray2buffer( arr:Array )\n Allocates a buffer using an octet array.\n","array2fancy":"\narray2fancy( x:Array|TypedArray|Object[, options:Object] )\n Converts an array to an object supporting fancy indexing.\n","array2fancy.factory":"\narray2fancy.factory( [options:Object] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n","array2fancy.idx":"\narray2fancy.idx( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n","array2iterator":"\narray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n","array2iteratorRight":"\narray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n","ArrayBuffer":"\nArrayBuffer( size:integer )\n Returns an array buffer having a specified number of bytes.\n","ArrayBuffer.length":"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n","ArrayBuffer.isView":"\nArrayBuffer.isView( arr:any )\n Returns a boolean indicating if provided an array buffer view.\n","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of an array buffer to a new array buffer.\n","arraybuffer2buffer":"\narraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Allocates a buffer from an ArrayBuffer.\n","arrayCtors":"\narrayCtors( dtype:string )\n Returns an array constructor.\n","arrayDataType":"\narrayDataType( array:any )\n Returns the data type of an array.\n","arrayDataTypes":"\narrayDataTypes( [kind:string] )\n Returns a list of array data types.\n","ArrayIndex":"\nArrayIndex( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n","ArrayIndex.free":"\nArrayIndex.free( id:string )\n Frees the instance associated with a provided identifier.\n","ArrayIndex.get":"\nArrayIndex.get( id:string )\n Returns the array associated with the instance having a provided identifier.\n","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n","arrayMinDataType":"\narrayMinDataType( value:any )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n","arrayNextDataType":"\narrayNextDataType( [dtype:string] )\n Returns the next larger array data type of the same kind.\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n","arraySafeCasts":"\narraySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n","arraySameKindCasts":"\narraySameKindCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n","arrayShape":"\narrayShape( arr:ArrayLikeObject )\n Determines array dimensions.\n","arrayStream":"\narrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object.\n","arrayStream.factory":"\narrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n","arrayStream.objectMode":"\narrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object.\n","arrayview2iterator":"\narrayview2iterator( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n","aslice":"\naslice( x:ArrayLikeObject[, start:integer[, end:integer]] )\n Returns a shallow copy of a portion of an array.\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n","atake":"\natake( x:Array|TypedArray|Object, indices:ArrayLikeObject[, \n options:Object] )\n Takes elements from an array.\n","azeros":"\nazeros( length:integer[, dtype:string] )\n Returns a zero-filled array having a specified length.\n","azerosLike":"\nazerosLike( x:TypedArray|Array[, dtype:string] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n","azeroTo":"\nazeroTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n","azeroToLike":"\nazeroToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n","bartlettTest":"\nbartlettTest( ...x:Array[, options:Object] )\n Computes Bartlett’s test for equal variances.\n","base.abs":"\nbase.abs( x:number )\n Computes the absolute value of a double-precision floating-point number `x`.\n","base.abs2":"\nbase.abs2( x:number )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n","base.abs2f":"\nbase.abs2f( x:number )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n","base.absdiff":"\nbase.absdiff( x:number, y:number )\n Computes the absolute difference.\n","base.absf":"\nbase.absf( x:number )\n Computes the absolute value of a single-precision floating-point number `x`.\n","base.acartesianPower":"\nbase.acartesianPower( x:ArrayLikeObject, n:integer )\n Returns the Cartesian power.\n","base.acartesianProduct":"\nbase.acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n Returns the Cartesian product.\n","base.acartesianSquare":"\nbase.acartesianSquare( x:ArrayLikeObject )\n Returns the Cartesian square.\n","base.acos":"\nbase.acos( x:number )\n Compute the arccosine of a double-precision floating-point number.\n","base.acosd":"\nbase.acosd( x:number )\n Computes the arccosine (in degrees) of a double-precision floating-point \n number.\n","base.acosdf":"\nbase.acosdf( x:number )\n Computes the arccosine (in degrees) of a single-precision floating-point\n number.\n","base.acosf":"\nbase.acosf( x:number )\n Computes the arccosine of a single-precision floating-point number.\n","base.acosh":"\nbase.acosh( x:number )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n","base.acot":"\nbase.acot( x:number )\n Computes the inverse cotangent of a double-precision floating-point number.\n","base.acotd":"\nbase.acotd( x:number )\n Computes the arccotangent (in degrees) of a double-precision floating-point\n number.\n","base.acotdf":"\nbase.acotdf( x:number )\n Computes the arccotangent (in degrees) of a single-precision floating-point\n number.\n","base.acotf":"\nbase.acotf( x:number )\n Computes the inverse cotangent of a single-precision floating-point number.\n","base.acoth":"\nbase.acoth( x:number )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n","base.acovercos":"\nbase.acovercos( x:number )\n Computes the inverse coversed cosine.\n","base.acoversin":"\nbase.acoversin( x:number )\n Computes the inverse coversed sine.\n","base.acsc":"\nbase.acsc( x:number )\n Computes the arccosecant of a number.\n","base.acscd":"\nbase.acscd( x:number )\n Computes the arccosecant of (in degrees) a double-precision floating-point\n number.\n","base.acscdf":"\nbase.acscdf( x:number )\n Computes the arccosecant (in degrees) of a single-precision floating-point\n number.\n","base.acscf":"\nbase.acscf( x:number )\n Computes the arccosecant of a single-precision floating-point number.\n","base.acsch":"\nbase.acsch( x:number )\n Computes the hyperbolic arccosecant of a number.\n","base.add":"\nbase.add( x:number, y:number )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n","base.add3":"\nbase.add3( x:number, y:number, z:number )\n Computes the sum of three double-precision floating-point numbers.\n","base.add4":"\nbase.add4( x:number, y:number, z:number, w:number )\n Computes the sum of four double-precision floating-point numbers.\n","base.add5":"\nbase.add5( x:number, y:number, z:number, w:number, u:number )\n Computes the sum of five double-precision floating-point numbers.\n","base.addf":"\nbase.addf( x:number, y:number )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n","base.afilled":"\nbase.afilled( value:any, len:integer )\n Returns a filled \"generic\" array.\n","base.afilled2d":"\nbase.afilled2d( value:any, shape:Array )\n Returns a filled two-dimensional nested array.\n","base.afilled2dBy":"\nbase.afilled2dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled two-dimensional nested array according to a provided\n callback function.\n","base.afilled3d":"\nbase.afilled3d( value:any, shape:Array )\n Returns a filled three-dimensional nested array.\n","base.afilled3dBy":"\nbase.afilled3dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled three-dimensional nested array according to a provided\n callback function.\n","base.afilled4d":"\nbase.afilled4d( value:any, shape:Array )\n Returns a filled four-dimensional nested array.\n","base.afilled4dBy":"\nbase.afilled4dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled four-dimensional nested array according to a provided\n callback function.\n","base.afilled5d":"\nbase.afilled5d( value:any, shape:Array )\n Returns a filled five-dimensional nested array.\n","base.afilled5dBy":"\nbase.afilled5dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled five-dimensional nested array according to a provided\n callback function.\n","base.afilledBy":"\nbase.afilledBy( len:integer, clbk:Function[, thisArg:any] )\n Returns a filled \"generic\" array according to a provided callback function.\n","base.afillednd":"\nbase.afillednd( value:any, shape:Array )\n Returns a filled n-dimensional nested array.\n","base.afilledndBy":"\nbase.afilledndBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled n-dimensional nested array according to a callback\n function.\n","base.afilter":"\nbase.afilter( x:Array|TypedArray|Object, predicate:Function[, thisArg:any] )\n Returns a shallow copy of an array containing only those elements which pass\n a test implemented by a predicate function.\n","base.afirst":"\nbase.afirst( arr:ArrayLikeObject )\n Returns the first element of an array-like object.\n","base.aflatten":"\nbase.aflatten( x:Array, shape:Array, colexicographic:boolean )\n Flattens an n-dimensional nested array.\n","base.aflatten.assign":"\nbase.aflatten.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten2d":"\nbase.aflatten2d( x:Array, shape:Array, colexicographic:boolean )\n Flattens a two-dimensional nested array.\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten2dBy":"\nbase.aflatten2dBy( x:Array, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a two-dimensional nested array according to a callback function.\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten3d":"\nbase.aflatten3d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a three-dimensional nested array.\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten3dBy":"\nbase.aflatten3dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a three-dimensional nested array according to a callback function.\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten4d":"\nbase.aflatten4d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a four-dimensional nested array.\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten4dBy":"\nbase.aflatten4dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a four-dimensional nested array according to a callback function.\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten5d":"\nbase.aflatten5d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a five-dimensional nested array.\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten5dBy":"\nbase.aflatten5dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a five-dimensional nested array according to a callback function.\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflattenBy":"\nbase.aflattenBy( x:Array, shape:Array, colex:boolean, clbk:Function[, \n thisArg:any] )\n Flattens an n-dimensional nested array according to a callback function.\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n","base.afliplr2d":"\nbase.afliplr2d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a two-dimensional\n nested input array.\n","base.afliplr3d":"\nbase.afliplr3d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a three-\n dimensional nested input array.\n","base.afliplr4d":"\nbase.afliplr4d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a four-\n dimensional nested input array.\n","base.afliplr5d":"\nbase.afliplr5d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a five-\n dimensional nested input array.\n","base.aflipud2d":"\nbase.aflipud2d( x:ArrayLikeObject )\n Reverses the order of elements along the first dimension of a two-\n dimensional nested input array.\n","base.aflipud3d":"\nbase.aflipud3d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a\n three-dimensional nested input array.\n","base.aflipud4d":"\nbase.aflipud4d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a four-\n dimensional nested input array.\n","base.aflipud5d":"\nbase.aflipud5d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a five-\n dimensional nested input array.\n","base.ahavercos":"\nbase.ahavercos( x:number )\n Computes the inverse half-value versed cosine.\n","base.ahaversin":"\nbase.ahaversin( x:number )\n Computes the inverse half-value versed sine.\n","base.altcase":"\nbase.altcase( str:string )\n Converts a string to alternate case.\n","base.aones":"\nbase.aones( len:integer )\n Returns a \"generic\" array filled with ones.\n","base.aones2d":"\nbase.aones2d( shape:Array )\n Returns a two-dimensional nested array filled with ones.\n","base.aones3d":"\nbase.aones3d( shape:Array )\n Returns a three-dimensional nested array filled with ones.\n","base.aones4d":"\nbase.aones4d( shape:Array )\n Returns a four-dimensional nested array filled with ones.\n","base.aones5d":"\nbase.aones5d( shape:Array )\n Returns a five-dimensional nested array filled with ones.\n","base.aonesnd":"\nbase.aonesnd( shape:Array )\n Returns an n-dimensional nested array filled with ones.\n","base.aoneTo":"\nbase.aoneTo( n:number )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n","base.args2multislice":"\nbase.args2multislice( args:Array )\n Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n","base.asec":"\nbase.asec( x:number )\n Computes the inverse (arc) secant of a number.\n","base.asecd":"\nbase.asecd( x:number )\n Computes the arcsecant (in degrees) of a double-precision floating-point\n number.\n","base.asecdf":"\nbase.asecdf( x:number )\n Computes the arcsecant (in degrees) of a single-precision floating-point\n number.\n","base.asecf":"\nbase.asecf( x:number )\n Computes the inverse (arc) secant of a single-precision\n floating-point number.\n","base.asech":"\nbase.asech( x:number )\n Computes the hyperbolic arcsecant of a number.\n","base.asin":"\nbase.asin( x:number )\n Computes the arcsine of a double-precision floating-point number.\n","base.asind":"\nbase.asind( x:number )\n Computes the arcsine (in degrees) of a double-precision floating-point\n number.\n","base.asindf":"\nbase.asindf( x:number )\n Computes the arcsine (in degrees) of a single-precision floating-point\n number.\n","base.asinf":"\nbase.asinf( x:number )\n Computes the arcsine of a single-precision floating-point number.\n","base.asinh":"\nbase.asinh( x:number )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n","base.atan":"\nbase.atan( x:number )\n Computes the arctangent of a double-precision floating-point number.\n","base.atan2":"\nbase.atan2( y:number, x:number )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n","base.atand":"\nbase.atand( x:number )\n Computes the arctangent (in degrees) of a double-precision floating-point\n number.\n","base.atanf":"\nbase.atanf( x:number )\n Computes the arctangent of a single-precision floating-point number.\n","base.atanh":"\nbase.atanh( x:number )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n","base.avercos":"\nbase.avercos( x:number )\n Computes the inverse versed cosine.\n","base.aversin":"\nbase.aversin( x:number )\n Computes the inverse versed sine.\n","base.azeros":"\nbase.azeros( len:integer )\n Returns a zero-filled \"generic\" array.\n","base.azeros2d":"\nbase.azeros2d( shape:Array )\n Returns a zero-filled two-dimensional nested array.\n","base.azeros3d":"\nbase.azeros3d( shape:Array )\n Returns a zero-filled three-dimensional nested array.\n","base.azeros4d":"\nbase.azeros4d( shape:Array )\n Returns a zero-filled four-dimensional nested array.\n","base.azeros5d":"\nbase.azeros5d( shape:Array )\n Returns a zero-filled five-dimensional nested array.\n","base.azerosnd":"\nbase.azerosnd( shape:Array )\n Returns a zero-filled n-dimensional nested array.\n","base.azeroTo":"\nbase.azeroTo( n:number )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n","base.bernoulli":"\nbase.bernoulli( n:integer )\n Computes the nth Bernoulli number.\n","base.besselj0":"\nbase.besselj0( x:number )\n Computes the Bessel function of the first kind of order zero.\n","base.besselj1":"\nbase.besselj1( x:number )\n Computes the Bessel function of the first kind of order one.\n","base.bessely0":"\nbase.bessely0( x:number )\n Computes the Bessel function of the second kind of order zero.\n","base.bessely1":"\nbase.bessely1( x:number )\n Computes the Bessel function of the second kind of order one.\n","base.beta":"\nbase.beta( x:number, y:number )\n Evaluates the beta function.\n","base.betainc":"\nbase.betainc( x:number, a:number, b:number[, regularized:boolean[, \n upper:boolean]] )\n Computes the regularized incomplete beta function.\n","base.betaincinv":"\nbase.betaincinv( p:number, a:number, b:number[, upper:boolean] )\n Computes the inverse of the lower incomplete beta function.\n","base.betaln":"\nbase.betaln( a:number, b:number )\n Evaluates the natural logarithm of the beta function.\n","base.binet":"\nbase.binet( x:number )\n Evaluates Binet's formula extended to real numbers.\n","base.binomcoef":"\nbase.binomcoef( n:integer, k:integer )\n Computes the binomial coefficient of two integers.\n","base.binomcoefln":"\nbase.binomcoefln( n:integer, k:integer )\n Computes the natural logarithm of the binomial coefficient of two integers.\n","base.boxcox":"\nbase.boxcox( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation.\n","base.boxcox1p":"\nbase.boxcox1p( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation of 1+x.\n","base.boxcox1pinv":"\nbase.boxcox1pinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n","base.boxcoxinv":"\nbase.boxcoxinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation.\n","base.cabs":"\nbase.cabs( z:Complex128 )\n Computes the absolute value of a double-precision complex floating-point\n number.\n","base.cabs2":"\nbase.cabs2( z:Complex128 )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n","base.cabs2f":"\nbase.cabs2f( z:Complex64 )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n","base.cabsf":"\nbase.cabsf( z:Complex64 )\n Computes the absolute value of a single-precision complex floating-point\n number.\n","base.cadd":"\nbase.cadd( z1:Complex128, z2:Complex128 )\n Adds two double-precision complex floating-point numbers.\n","base.cadd.assign":"\nbase.cadd.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Adds two double-precision complex floating-point numbers and assigns results\n to a provided output array.\n","base.cadd.strided":"\nbase.cadd.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Adds two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n","base.caddf":"\nbase.caddf( z1:Complex64, z2:Complex64 )\n Adds two single-precision complex floating-point numbers.\n","base.caddf.assign":"\nbase.caddf.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Adds two single-precision complex floating-point numbers and assigns results\n to a provided output array.\n","base.caddf.strided":"\nbase.caddf.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Adds two single-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n","base.camelcase":"\nbase.camelcase( str:string )\n Converts a string to camel case.\n","base.capitalize":"\nbase.capitalize( str:string )\n Capitalizes the first character in a string.\n","base.cbrt":"\nbase.cbrt( x:number )\n Computes the cube root of a double-precision floating-point number.\n","base.cbrtf":"\nbase.cbrtf( x:number )\n Computes the cube root of a single-precision floating-point number.\n","base.cceil":"\nbase.cceil( z:Complex128 )\n Rounds each component of a double-precision complex floating-point number\n toward positive infinity.\n","base.cceilf":"\nbase.cceilf( z:Complex64 )\n Rounds each component of a single-precision complex floating-point number\n toward positive infinity.\n","base.cceiln":"\nbase.cceiln( z:Complex128, n:integer )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n","base.ccis":"\nbase.ccis( z:Complex128 )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n","base.cdiv":"\nbase.cdiv( z1:Complex128, z2:Complex128 )\n Divides two double-precision complex floating-point numbers.\n","base.cdiv.assign":"\nbase.cdiv.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Divides two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n","base.cdiv.strided":"\nbase.cdiv.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Divides two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n","base.ceil":"\nbase.ceil( x:number )\n Rounds a double-precision floating-point number toward positive infinity.\n","base.ceil2":"\nbase.ceil2( x:number )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n","base.ceil10":"\nbase.ceil10( x:number )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n","base.ceilb":"\nbase.ceilb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n","base.ceilf":"\nbase.ceilf( x:number )\n Rounds a single-precision floating-point number toward positive infinity.\n","base.ceiln":"\nbase.ceiln( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n","base.ceilsd":"\nbase.ceilsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n","base.cexp":"\nbase.cexp( z:Complex128 )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n","base.cflipsign":"\nbase.cflipsign( z:Complex128, y:number )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n","base.cflipsignf":"\nbase.cflipsignf( z:Complex64, y:number )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n","base.cfloor":"\nbase.cfloor( z:Complex128 )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n","base.cfloorn":"\nbase.cfloorn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n","base.cidentity":"\nbase.cidentity( z:Complex128 )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n","base.cidentityf":"\nbase.cidentityf( z:Complex64 )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n","base.cinv":"\nbase.cinv( z:Complex128 )\n Computes the inverse of a double-precision complex floating-point number.\n","base.cinvf":"\nbase.cinvf( z:Complex64 )\n Computes the inverse of a single-precision complex floating-point number.\n","base.clamp":"\nbase.clamp( v:number, min:number, max:number )\n Restricts a double-precision floating-point number to a specified range.\n","base.clampf":"\nbase.clampf( v:number, min:number, max:number )\n Restricts a single-precision floating-point number to a specified range.\n","base.cmul":"\nbase.cmul( z1:Complex128, z2:Complex128 )\n Multiplies two double-precision complex floating-point numbers.\n","base.cmul.assign":"\nbase.cmul.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n","base.cmul.strided":"\nbase.cmul.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n","base.cmulf":"\nbase.cmulf( z1:Complex64, z2:Complex64 )\n Multiplies two single-precision complex floating-point numbers.\n","base.cmulf.assign":"\nbase.cmulf.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Multiplies two single-precision complex floating-point numbers and assigns\n results to a provided output array.\n","base.cmulf.strided":"\nbase.cmulf.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Multiplies two single-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n","base.cneg":"\nbase.cneg( z:Complex128 )\n Negates a double-precision complex floating-point number.\n","base.cnegf":"\nbase.cnegf( z:Complex64 )\n Negates a single-precision complex floating-point number.\n","base.codePointAt":"\nbase.codePointAt( str:string, idx:integer, backward:boolean )\n Returns a Unicode code point from a string at a specified position.\n","base.constantcase":"\nbase.constantcase( str:string )\n Converts a string to constant case.\n","base.continuedFraction":"\nbase.continuedFraction( generator:Function[, options:Object] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n","base.copysign":"\nbase.copysign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n","base.copysignf":"\nbase.copysignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n","base.cos":"\nbase.cos( x:number )\n Computes the cosine of a number.\n","base.cosd":"\nbase.cosd( x:number )\n Computes the cosine of an angle measured in degrees.\n","base.cosh":"\nbase.cosh( x:number )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n","base.cosm1":"\nbase.cosm1( x:number )\n Computes the cosine of a number minus one.\n","base.cospi":"\nbase.cospi( x:number )\n Computes the value of `cos(πx)`.\n","base.cot":"\nbase.cot( x:number )\n Computes the cotangent of a number.\n","base.cotd":"\nbase.cotd( x:number )\n Computes the cotangent of an angle measured in degrees.\n","base.coth":"\nbase.coth( x:number )\n Computes the hyperbolic cotangent of a number.\n","base.covercos":"\nbase.covercos( x:number )\n Computes the coversed cosine.\n","base.coversin":"\nbase.coversin( x:number )\n Computes the coversed sine.\n","base.cphase":"\nbase.cphase( z:Complex128 )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n","base.cpolar":"\nbase.cpolar( z:Complex128 )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n","base.cpolar.assign":"\nbase.cpolar.assign( z:Complex128, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n","base.cround":"\nbase.cround( z:Complex128 )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n","base.croundn":"\nbase.croundn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n","base.csc":"\nbase.csc( x:number )\n Computes the cosecant of a number.\n","base.cscd":"\nbase.cscd( x:number )\n Computes the cosecant of a degree.\n","base.csch":"\nbase.csch( x:number )\n Computes the hyperbolic cosecant of a number.\n","base.csignum":"\nbase.csignum( z:Complex128 )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n","base.csub":"\nbase.csub( z1:Complex128, z2:Complex128 )\n Subtracts two double-precision complex floating-point numbers.\n","base.csubf":"\nbase.csubf( z1:Complex64, z2:Complex64 )\n Subtracts two single-precision complex floating-point numbers.\n","base.deg2rad":"\nbase.deg2rad( x:number )\n Converts an angle from degrees to radians.\n","base.deg2radf":"\nbase.deg2radf( x:number )\n Converts an angle from degrees to radians (single-precision).\n","base.digamma":"\nbase.digamma( x:number )\n Evaluates the digamma function.\n","base.diracDelta":"\nbase.diracDelta( x:number )\n Evaluates the Dirac delta function.\n","base.div":"\nbase.div( x:number, y:number )\n Divides two double-precision floating-point numbers `x` and `y`.\n","base.divf":"\nbase.divf( x:number, y:number )\n Divides two single-precision floating-point numbers `x` and `y`.\n","base.dotcase":"\nbase.dotcase( str:string )\n Converts a string to dot case.\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a:number, b:number] )\n Returns an arcsine distribution object.\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a:number, b:number )\n Returns the differential entropy of an arcsine distribution (in nats).\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a:number, b:number )\n Returns the excess kurtosis of an arcsine distribution.\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x:number, a:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x:number, a:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a:number, b:number )\n Returns the expected value of an arcsine distribution.\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a:number, b:number )\n Returns the median of an arcsine distribution.\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a:number, b:number )\n Returns the mode of an arcsine distribution.\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a:number, b:number )\n Returns the skewness of an arcsine distribution.\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a:number, b:number )\n Returns the standard deviation of an arcsine distribution.\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a:number, b:number )\n Returns the variance of an arcsine distribution.\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p:number] )\n Returns a Bernoulli distribution object.\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p`.\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p:number )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p:number )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p:number )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p:number )\n Returns the median of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p:number )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r:number, p:number )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p:number )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p:number )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p:number )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α:number, β:number] )\n Returns a beta distribution object.\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α:number, β:number )\n Returns the differential entropy of a beta distribution.\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta distribution.\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n","base.dists.beta.mean":"\nbase.dists.beta.mean( α:number, β:number )\n Returns the expected value of a beta distribution.\n","base.dists.beta.median":"\nbase.dists.beta.median( α:number, β:number )\n Returns the median of a beta distribution.\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n","base.dists.beta.mode":"\nbase.dists.beta.mode( α:number, β:number )\n Returns the mode of a beta distribution.\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α:number, β:number )\n Returns the skewness of a beta distribution.\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α:number, β:number )\n Returns the standard deviation of a beta distribution.\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α:number, β:number )\n Returns the variance of a beta distribution.\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α:number, β:number] )\n Returns a beta prime distribution object.\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta prime distribution.\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α:number, β:number )\n Returns the expected value of a beta prime distribution.\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α:number, β:number )\n Returns the mode of a beta prime distribution.\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α:number, β:number )\n Returns the skewness of a beta prime distribution.\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α:number, β:number )\n Returns the standard deviation of a beta prime distribution.\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α:number, β:number )\n Returns the variance of a beta prime distribution.\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n:integer, p:number] )\n Returns a binomial distribution object.\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x:number, n:integer, p:number )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n:integer, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n:integer, p:number )\n Returns the entropy of a binomial distribution.\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n:integer, p:number )\n Returns the excess kurtosis of a binomial distribution.\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x:number, n:integer, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n:integer, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n:integer, p:number )\n Returns the expected value of a binomial distribution.\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n:integer, p:number )\n Returns the median of a binomial distribution.\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t:number, n:integer, p:number )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n:integer, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n:integer, p:number )\n Returns the mode of a binomial distribution.\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x:number, n:integer, p:number )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n:integer, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r:number, n:integer, p:number )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n:integer, p:number )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n:integer, p:number )\n Returns the skewness of a binomial distribution.\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n:integer, p:number )\n Returns the standard deviation of a binomial distribution.\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n:integer, p:number )\n Returns the variance of a binomial distribution.\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0:number, Ɣ:number] )\n Returns a Cauchy distribution object.\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x:number, x0:number, Ɣ:number )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0:number, Ɣ:number )\n Returns the differential entropy of a Cauchy distribution (in nats).\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0:number, Ɣ:number )\n Returns the median of a Cauchy distribution.\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0:number, Ɣ:number )\n Returns the mode of a Cauchy distribution.\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x:number, x0:number, Ɣ:number )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p:number, x0:number, Ɣ:number )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k:number] )\n Returns a chi distribution object.\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k:number )\n Returns the differential entropy of a chi distribution (in nats).\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k:number )\n Returns the excess kurtosis of a chi distribution.\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.mean":"\nbase.dists.chi.mean( k:number )\n Returns the expected value of a chi distribution.\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k:number )\n Returns the mode of a chi distribution.\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p:number, k:number )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k:number )\n Returns the skewness of a chi distribution.\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k:number )\n Returns the standard deviation of a chi distribution.\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k:number )\n Returns the variance of a chi distribution.\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k:number] )\n Returns a chi-squared distribution object.\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k:number )\n Returns the differential entropy of a chi-squared distribution (in nats).\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k:number )\n Returns the excess kurtosis of a chi-squared distribution.\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k:number )\n Returns the expected value of a chi-squared distribution.\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k:number )\n Returns the median of a chi-squared distribution.\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t:number, k:number )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k:number )\n Returns the mode of a chi-squared distribution.\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p:number, k:number )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k:number )\n Returns the skewness of a chi-squared distribution.\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k:number )\n Returns the standard deviation of a chi-squared distribution.\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k:number )\n Returns the variance of a chi-squared distribution.\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ:number, s:number] )\n Returns a raised cosine distribution object.\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x:number, μ:number, s:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ:number, s:number )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ:number, s:number )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ:number, s:number )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ:number, s:number )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ:number, s:number )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ:number, s:number )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x:number, μ:number )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ:number] )\n Returns a degenerate distribution object.\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ:number )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x:number, μ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x:number, μ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x:number, μ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ:number )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ:number )\n Returns the median of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x:number, μ:number )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ:number )\n Returns the mode of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x:number, μ:number )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x:number, μ:number )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p:number, μ:number )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ:number )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ:number )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ:number )\n Returns the variance of a degenerate distribution with constant value `μ`.\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x:number, a:integer, b:integer )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a:integer, b:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a:integer, b:integer] )\n Returns a discrete uniform distribution object.\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a:integer, b:integer )\n Returns the entropy of a discrete uniform distribution.\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a:integer, b:integer )\n Returns the excess kurtosis of a discrete uniform distribution.\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a:integer, b:integer )\n Returns the expected value of a discrete uniform distribution.\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a:integer, b:integer )\n Returns the median of a discrete uniform distribution.\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t:number, a:integer, b:integer )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a:integer, b:integer )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x:number, a:integer, b:integer )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a:integer, b:integer )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p:number, a:integer, b:integer )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a:integer, b:integer )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a:integer, b:integer )\n Returns the skewness of a discrete uniform distribution.\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a:integer, b:integer )\n Returns the standard deviation of a discrete uniform distribution.\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a:integer, b:integer )\n Returns the variance of a discrete uniform distribution.\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k:integer, λ:number )\n Returns the differential entropy of an Erlang distribution (in nats).\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k:number, λ:number] )\n Returns an Erlang distribution object.\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k:integer, λ:number )\n Returns the excess kurtosis of an Erlang distribution.\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x:number, k:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k:integer, λ:number )\n Returns the expected value of an Erlang distribution.\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k:integer, λ:number )\n Returns the mode of an Erlang distribution.\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k:integer, λ:number )\n Returns the skewness of an Erlang distribution.\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k:integer, λ:number )\n Returns the standard deviation of an Erlang distribution.\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k:integer, λ:number )\n Returns the variance of an Erlang distribution.\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ:number )\n Returns the differential entropy of an exponential distribution.\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ:number] )\n Returns an exponential distribution object.\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ:number )\n Returns the excess kurtosis of an exponential distribution.\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x:number, λ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ:number )\n Returns the expected value of an exponential distribution.\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ:number )\n Returns the median of an exponential distribution.\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t:number, λ:number )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ:number )\n Returns the mode of an exponential distribution.\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x:number, λ:number )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ:number )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p:number, λ:number )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ:number )\n Returns the skewness of an exponential distribution.\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ:number )\n Returns the standard deviation of an exponential distribution.\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ:number )\n Returns the variance of an exponential distribution.\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x:number, d1:number, d2:number )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1:number, d2:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n","base.dists.f.entropy":"\nbase.dists.f.entropy( d1:number, d2:number )\n Returns the differential entropy of an F distribution (in nats).\n","base.dists.f.F":"\nbase.dists.f.F( [d1:number, d2:number] )\n Returns an F distribution object.\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1:number, d2:number )\n Returns the excess kurtosis of an F distribution.\n","base.dists.f.mean":"\nbase.dists.f.mean( d1:number, d2:number )\n Returns the expected value of an F distribution.\n","base.dists.f.mode":"\nbase.dists.f.mode( d1:number, d2:number )\n Returns the mode of an F distribution.\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x:number, d1:number, d2:number )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1:number, d2:number )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n","base.dists.f.quantile":"\nbase.dists.f.quantile( p:number, d1:number, d2:number )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1:number, d2:number )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n","base.dists.f.skewness":"\nbase.dists.f.skewness( d1:number, d2:number )\n Returns the skewness of an F distribution.\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1:number, d2:number )\n Returns the standard deviation of an F distribution.\n","base.dists.f.variance":"\nbase.dists.f.variance( d1:number, d2:number )\n Returns the variance of an F distribution.\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x:number, α:number, s:number, m:number )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α:number, s:number, m:number )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α:number, s:number, m:number] )\n Returns a Fréchet distribution object.\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α:number, s:number, m:number )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x:number, α:number, s:number, m:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x:number, α:number, s:number, m:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α:number, s:number, m:number )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α:number, s:number, m:number )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α:number, s:number, m:number )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x:number, α:number, s:number, m:number )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p:number, α:number, s:number, m:number )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α:number, s:number, m:number )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α:number, s:number, m:number )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α:number, s:number, m:number )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α:number, s:number, m:number )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α:number, β:number )\n Returns the differential entropy of a gamma distribution.\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α:number, β:number] )\n Returns a gamma distribution object.\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a gamma distribution.\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x:number, α:number, β:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x:number, α:number, β:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α:number, β:number )\n Returns the expected value of a gamma distribution.\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α:number, β:number )\n Returns the mode of a gamma distribution.\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α:number, β:number )\n Returns the skewness of a gamma distribution.\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α:number, β:number )\n Returns the standard deviation of a gamma distribution.\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α:number, β:number )\n Returns the variance of a gamma distribution.\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p:number )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p:number] )\n Returns a geometric distribution object.\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p:number )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x:number, p:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x:number, p:number )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p:number )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p:number )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p:number )\n Returns the median of a geometric distribution with success probability `p`.\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p:number )\n Returns the mode of a geometric distribution with success probability `p`.\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r:number, p:number )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p:number )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p:number )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p:number )\n Returns the variance of a geometric distribution with success probability\n `p`.\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x:number, μ:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ:number, β:number )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ:number, β:number] )\n Returns a Gumbel distribution object.\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ:number, β:number )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x:number, μ:number, β:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x:number, μ:number, β:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ:number, β:number )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ:number, β:number )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t:number, μ:number, β:number )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ:number, β:number )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x:number, μ:number, β:number )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p:number, μ:number, β:number )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ:number, β:number )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ:number, β:number )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ:number, β:number )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ:number, β:number )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x:number, N:integer, K:integer, n:integer )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N:integer, K:integer, n:integer] )\n Returns a hypergeometric distribution object.\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N:integer, K:integer, n:integer )\n Returns the excess kurtosis of a hypergeometric distribution.\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N:integer, K:integer, n:integer )\n Returns the expected value of a hypergeometric distribution.\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N:integer, K:integer, n:integer )\n Returns the mode of a hypergeometric distribution.\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p:number, N:integer, K:integer, n:integer )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N:integer, K:integer, n:integer )\n Returns the skewness of a hypergeometric distribution.\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N:integer, K:integer, n:integer )\n Returns the standard deviation of a hypergeometric distribution.\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N:integer, K:integer, n:integer )\n Returns the variance of a hypergeometric distribution.\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α:number, β:number )\n Returns the differential entropy of an inverse gamma distribution.\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α:number, β:number] )\n Returns an inverse gamma distribution object.\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of an inverse gamma distribution.\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α:number, β:number )\n Returns the expected value of an inverse gamma distribution.\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α:number, β:number )\n Returns the mode of an inverse gamma distribution.\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α:number, β:number )\n Returns the skewness of an inverse gamma distribution.\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α:number, β:number )\n Returns the standard deviation of an inverse gamma distribution.\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α:number, β:number )\n Returns the variance of an inverse gamma distribution.\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a:number, b:number] )\n Returns a Kumaraswamy's double bounded distribution object.\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a:number, b:number )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a:number, b:number )\n Returns the median of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a:number, b:number )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a:number, b:number )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a:number, b:number )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a:number, b:number )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x:number, μ:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ:number, b:number )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ:number, b:number )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ:number, b:number] )\n Returns a Laplace distribution object.\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x:number, μ:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x:number, μ:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ:number, b:number )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ:number, b:number )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t:number, μ:number, b:number )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ:number, b:number )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x:number, μ:number, b:number )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p:number, μ:number, b:number )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ:number, b:number )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ:number, b:number )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ:number, b:number )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ:number, b:number )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x:number, μ:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ:number, c:number )\n Returns the differential entropy of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ:number, c:number] )\n Returns a Lévy distribution object.\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x:number, μ:number, c:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x:number, μ:number, c:number )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n","base.dists.levy.mean":"\nbase.dists.levy.mean( μ:number, c:number )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n","base.dists.levy.median":"\nbase.dists.levy.median( μ:number, c:number )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ:number, c:number )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x:number, μ:number, c:number )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p:number, μ:number, c:number )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ:number, c:number )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ:number, c:number )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ:number, c:number )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ:number, s:number )\n Returns the differential entropy of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ:number, s:number] )\n Returns a logistic distribution object.\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ:number, s:number )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ:number, s:number )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ:number, s:number )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ:number, s:number )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ:number, s:number )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ:number, s:number )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ:number, σ:number )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ:number, σ:number] )\n Returns a lognormal distribution object.\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n at a value `x`.\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ:number, σ:number )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ:number, σ:number )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ:number, σ:number )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ:number, σ:number )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ:number, σ:number )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ:number, σ:number )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x:number, r:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r:number, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r:integer, p:number )\n Returns the excess kurtosis of a negative binomial distribution.\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x:number, r:number, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r:number, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r:integer, p:number )\n Returns the expected value of a negative binomial distribution.\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x:number, r:number, p:number )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r:number, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r:integer, p:number )\n Returns the mode of a negative binomial distribution.\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r:number, p:number] )\n Returns a negative binomial distribution object.\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x:number, r:number, p:number )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r:number, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k:number, r:number, p:number )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r:number, p:number )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r:integer, p:number )\n Returns the skewness of a negative binomial distribution.\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r:integer, p:number )\n Returns the standard deviation of a negative binomial distribution.\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r:integer, p:number )\n Returns the variance of a negative binomial distribution.\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ:number, σ:number )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.mean":"\nbase.dists.normal.mean( μ:number, σ:number )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.median":"\nbase.dists.normal.median( μ:number, σ:number )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x:number, μ:number, σ:number )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ:number, σ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.mode":"\nbase.dists.normal.mode( μ:number, σ:number )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ:number, σ:number] )\n Returns a normal distribution object.\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ:number, σ:number )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ:number, σ:number )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ:number, σ:number )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α:number, β:number )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α:number, β:number )\n Returns the expected value of a Pareto (Type I) distribution.\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α:number, β:number )\n Returns the median of a Pareto (Type I) distribution.\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α:number, β:number )\n Returns the mode of a Pareto (Type I) distribution.\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α:number, β:number] )\n Returns a Pareto (Type I) distribution object.\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α:number, β:number )\n Returns the skewness of a Pareto (Type I) distribution.\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α:number, β:number )\n Returns the standard deviation of a Pareto (Type I) distribution.\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α:number, β:number )\n Returns the variance of a Pareto (Type I) distribution.\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ:number )\n Returns the entropy of a Poisson distribution.\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ:number )\n Returns the excess kurtosis of a Poisson distribution.\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x:number, λ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ:number )\n Returns the expected value of a Poisson distribution.\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ:number )\n Returns the median of a Poisson distribution.\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ:number )\n Returns the mode of a Poisson distribution.\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x:number, λ:number )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ:number )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ:number] )\n Returns a Poisson distribution object.\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p:number, λ:number )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ:number )\n Returns the skewness of a Poisson distribution.\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ:number )\n Returns the standard deviation of a Poisson distribution.\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ:number )\n Returns the variance of a Poisson distribution.\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x:number, sigma:number )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ:number )\n Returns the differential entropy of a Rayleigh distribution.\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ:number )\n Returns the excess kurtosis of a Rayleigh distribution.\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x:number, sigma:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x:number, sigma:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ:number )\n Returns the expected value of a Rayleigh distribution.\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ:number )\n Returns the median of a Rayleigh distribution.\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t:number, sigma:number )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ:number )\n Returns the mode of a Rayleigh distribution.\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x:number, sigma:number )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p:number, sigma:number )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma:number )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ:number] )\n Returns a Rayleigh distribution object.\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ:number )\n Returns the skewness of a Rayleigh distribution.\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ:number )\n Returns the standard deviation of a Rayleigh distribution.\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ:number )\n Returns the variance of a Rayleigh distribution.\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x:number, n:integer )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x:number, n:integer )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n:integer )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p:number, n:integer )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n:integer )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x:number, r:number, v:number[, \n nranges:integer] )\n Evaluates the cumulative distribution function (CDF) of a studentized range\n distribution.\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r:number, v:number[, nranges:integer] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p:number, r:number, v:number[, \n nranges:integer] )\n Evaluates the quantile function for a studentized range distribution.\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r:number, v:number[, \n nranges:integer] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n","base.dists.t.cdf":"\nbase.dists.t.cdf( x:number, v:number )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.entropy":"\nbase.dists.t.entropy( v:number )\n Returns the differential entropy of a Student's t distribution.\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v:number )\n Returns the excess kurtosis of a Student's t distribution.\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x:number, v:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n `x`.\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x:number, v:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Student's t distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n","base.dists.t.mean":"\nbase.dists.t.mean( v:number )\n Returns the expected value of a Student's t distribution.\n","base.dists.t.median":"\nbase.dists.t.median( v:number )\n Returns the median of a Student's t distribution.\n","base.dists.t.mode":"\nbase.dists.t.mode( v:number )\n Returns the mode of a Student's t distribution.\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x:number, v:number )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.quantile":"\nbase.dists.t.quantile( p:number, v:number )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v:number )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n","base.dists.t.skewness":"\nbase.dists.t.skewness( v:number )\n Returns the skewness of a Student's t distribution.\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v:number )\n Returns the standard deviation of a Student's t distribution.\n","base.dists.t.T":"\nbase.dists.t.T( [v:number] )\n Returns a Student's t distribution object.\n","base.dists.t.variance":"\nbase.dists.t.variance( v:number )\n Returns the variance of a Student's t distribution.\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x:number, a:number, b:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a:number, b:number, c:number )\n Returns the differential entropy of a triangular distribution (in nats).\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a:number, b:number, c:number )\n Returns the excess kurtosis of a triangular distribution.\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a:number, b:number, c:number )\n Returns the expected value of a triangular distribution.\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a:number, b:number, c:number )\n Returns the median of a triangular distribution.\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t:number, a:number, b:number, c:number )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a:number, b:number, c:number )\n Returns the mode of a triangular distribution.\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x:number, a:number, b:number, c:number )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p:number, a:number, b:number, c:number )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a:number, b:number, c:number )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a:number, b:number, c:number )\n Returns the skewness of a triangular distribution.\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a:number, b:number, c:number )\n Returns the standard deviation of a triangular distribution.\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a:number, b:number, c:number] )\n Returns a triangular distribution object.\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a:number, b:number, c:number )\n Returns the variance of a triangular distribution.\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a:number, b:number )\n Returns the differential entropy of a uniform distribution.\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a uniform distribution.\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x:number, a:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x:number, a:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a:number, b:number )\n Returns the expected value of a uniform distribution.\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a:number, b:number )\n Returns the median of a uniform distribution.\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t:number, a:number, b:number )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a:number, b:number )\n Returns the skewness of a uniform distribution.\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a:number, b:number )\n Returns the standard deviation of a uniform distribution.\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a:number, b:number] )\n Returns a uniform distribution object.\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a:number, b:number )\n Returns the variance of a uniform distribution.\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k:number, λ:number )\n Returns the differential entropy of a Weibull distribution (in nats).\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k:number, λ:number )\n Returns the excess kurtosis of a Weibull distribution.\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x:number, k:number, λ:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k:number, λ:number)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x:number, k:number, λ:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k:number, λ:number )\n Returns the expected value of a Weibull distribution.\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k:number, λ:number )\n Returns the median of a Weibull distribution.\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k:number, λ:number )\n Returns the mode of a Weibull distribution.\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k:number, λ:number )\n Returns the skewness of a Weibull distribution.\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k:number, λ:number )\n Returns the standard deviation of a Weibull distribution.\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k:number, λ:number )\n Returns the variance of a Weibull distribution.\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k:number, λ:number] )\n Returns a Weibull distribution object.\n","base.ellipe":"\nbase.ellipe( m:number )\n Computes the complete elliptic integral of the second kind.\n","base.ellipj":"\nbase.ellipj( u:number, m:number )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n","base.ellipj.assign":"\nbase.ellipj.assign( u:number, m:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n","base.ellipj.sn":"\nbase.ellipj.sn( u:number, m:number )\n Computes the Jacobi elliptic function sn.\n","base.ellipj.cn":"\nbase.ellipj.cn( u:number, m:number )\n Computes the Jacobi elliptic functions cn.\n","base.ellipj.dn":"\nbase.ellipj.dn( u:number, m:number )\n Computes the Jacobi elliptic function dn.\n","base.ellipj.am":"\nbase.ellipj.am( u:number, m:number )\n Computes the Jacobi amplitude am.\n","base.ellipk":"\nbase.ellipk( m:number )\n Computes the complete elliptic integral of the first kind.\n","base.endsWith":"\nbase.endsWith( str:string, search:string, len:integer )\n Tests if a string ends with the characters of another string.\n","base.epsdiff":"\nbase.epsdiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n","base.erf":"\nbase.erf( x:number )\n Evaluates the error function.\n","base.erfc":"\nbase.erfc( x:number )\n Evaluates the complementary error function.\n","base.erfcinv":"\nbase.erfcinv( x:number )\n Evaluates the inverse complementary error function.\n","base.erfcx":"\nbase.erfcx( x:number )\n Evaluates the scaled complementary error function.\n","base.erfinv":"\nbase.erfinv( x:number )\n Evaluates the inverse error function.\n","base.eta":"\nbase.eta( s:number )\n Evaluates the Dirichlet eta function for a double-precision\n floating-point number `s`.\n","base.evalpoly":"\nbase.evalpoly( c:Array, x:number )\n Evaluates a polynomial using double-precision floating-point arithmetic.\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c:Array )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n","base.evalrational":"\nbase.evalrational( P:Array, Q:Array, x:number )\n Evaluates a rational function using double-precision floating-point\n arithmetic.\n","base.evalrational.factory":"\nbase.evalrational.factory( P:Array, Q:Array )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n","base.exp":"\nbase.exp( x:number )\n Evaluates the natural exponential function.\n","base.exp2":"\nbase.exp2( x:number )\n Evaluates the base 2 exponential function.\n","base.exp10":"\nbase.exp10( x:number )\n Evaluates the base 10 exponential function.\n","base.expit":"\nbase.expit( x:number )\n Evaluates the standard logistic function.\n","base.expm1":"\nbase.expm1( x:number )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n","base.expm1rel":"\nbase.expm1rel( x:number )\n Relative error exponential.\n","base.exponent":"\nbase.exponent( x:number )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n","base.exponentf":"\nbase.exponentf( x:float )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n","base.factorial":"\nbase.factorial( x:number )\n Evaluates the factorial of `x`.\n","base.factorial2":"\nbase.factorial2( n:number )\n Evaluates the double factorial of `n`.\n","base.factorialln":"\nbase.factorialln( x:number )\n Evaluates the natural logarithm of the factorial of `x`.\n","base.fallingFactorial":"\nbase.fallingFactorial( x:number, n:integer )\n Computes the falling factorial of `x` and `n`.\n","base.fibonacci":"\nbase.fibonacci( n:integer )\n Computes the nth Fibonacci number.\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F:integer )\n Computes the Fibonacci number index.\n","base.fibpoly":"\nbase.fibpoly( n:integer, x:number )\n Evaluates a Fibonacci polynomial.\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n:integer )\n Returns a function for evaluating a Fibonacci polynomial.\n","base.firstCodePoint":"\nbase.firstCodePoint( str:string, n:integer )\n Returns the first `n` Unicode code points of a string.\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str:string, n:integer )\n Returns the first `n` UTF-16 code units of a string.\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str:string, n:integer )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n","base.flipsign":"\nbase.flipsign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n","base.flipsignf":"\nbase.flipsignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n","base.float32ToInt32":"\nbase.float32ToInt32( x:float )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n","base.float32ToUint32":"\nbase.float32ToUint32( x:float )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n","base.float64ToFloat32":"\nbase.float64ToFloat32( x:number )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n","base.float64ToInt32":"\nbase.float64ToInt32( x:number )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n","base.float64ToUint32":"\nbase.float64ToUint32( x:number )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n","base.floor":"\nbase.floor( x:number )\n Rounds a double-precision floating-point number toward negative infinity.\n","base.floor2":"\nbase.floor2( x:number )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n","base.floor10":"\nbase.floor10( x:number )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n","base.floorb":"\nbase.floorb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n","base.floorf":"\nbase.floorf( x:number )\n Rounds a single-precision floating-point number toward negative infinity.\n","base.floorn":"\nbase.floorn( x:number, n:integer )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n","base.floorsd":"\nbase.floorsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n","base.forEachChar":"\nbase.forEachChar( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each UTF-16 code unit in a string.\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each Unicode code point in a string.\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each Unicode code point in a string, iterating from\n right to left.\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n","base.forEachRight":"\nbase.forEachRight( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each UTF-16 code unit in a string, iterating from\n right to left.\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens:Array, ...args:any )\n Generate string from a token array by interpolating values.\n","base.formatTokenize":"\nbase.formatTokenize( str:string )\n Tokenize a string into an array of string parts and format identifier\n objects.\n","base.fresnel":"\nbase.fresnel( x:number )\n Computes the Fresnel integrals S(x) and C(x).\n","base.fresnel.assign":"\nbase.fresnel.assign( x:number, out:Array, stride:integer, \n offset:integer )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n","base.fresnelc":"\nbase.fresnelc( x:number )\n Computes the Fresnel integral C(x).\n","base.fresnels":"\nbase.fresnels( x:number )\n Computes the Fresnel integral S(x).\n","base.frexp":"\nbase.frexp( x:number )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n","base.frexp.assign":"\nbase.frexp.assign( x:number, out:Array, stride:integer, offset:integer )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n","base.fromBinaryString":"\nbase.fromBinaryString( bstr:string )\n Creates a double-precision floating-point number from a literal bit\n representation.\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr:string )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr:string )\n Creates an unsigned 8-bit integer from a literal bit representation.\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr:string )\n Creates an unsigned 16-bit integer from a literal bit representation.\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr:string )\n Creates an unsigned 32-bit integer from a literal bit representation.\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Converts a signed 64-bit integer byte array to a double-precision floating-\n point number.\n","base.fromWordf":"\nbase.fromWordf( word:integer )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n","base.fromWords":"\nbase.fromWords( high:integer, low:integer )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.gamma":"\nbase.gamma( x:number )\n Evaluates the gamma function.\n","base.gamma1pm1":"\nbase.gamma1pm1( x:number )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z:number, delta:number )\n Computes the ratio of two gamma functions.\n","base.gammainc":"\nbase.gammainc( x:number, s:number[, regularized:boolean[, upper:boolean]] )\n Computes the regularized incomplete gamma function.\n","base.gammaincinv":"\nbase.gammaincinv( p:number, a:number[, upper:boolean] )\n Computes the inverse of the lower incomplete gamma function.\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x:number )\n Calculates the Lanczos sum for the approximation of the gamma function.\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x:number )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n","base.gammaln":"\nbase.gammaln( x:number )\n Evaluates the natural logarithm of the gamma function.\n","base.gammasgn":"\nbase.gammasgn( x:number )\n Computes the sign of the gamma function.\n","base.gcd":"\nbase.gcd( a:integer, b:integer )\n Computes the greatest common divisor (gcd).\n","base.getHighWord":"\nbase.getHighWord( x:number )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n","base.getLowWord":"\nbase.getLowWord( x:number )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n","base.hacovercos":"\nbase.hacovercos( x:number )\n Computes the half-value coversed cosine.\n","base.hacoversin":"\nbase.hacoversin( x:number )\n Computes the half-value coversed sine.\n","base.havercos":"\nbase.havercos( x:number )\n Computes the half-value versed cosine.\n","base.haversin":"\nbase.haversin( x:number )\n Computes the half-value versed sine.\n","base.headercase":"\nbase.headercase( str:string )\n Converts a string to HTTP header case.\n","base.heaviside":"\nbase.heaviside( x:number[, continuity:string] )\n Evaluates the Heaviside function.\n","base.hermitepoly":"\nbase.hermitepoly( n:integer, x:number )\n Evaluates a physicist's Hermite polynomial.\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n:integer )\n Returns a function for evaluating a physicist's Hermite polynomial.\n","base.hypot":"\nbase.hypot( x:number, y:number )\n Computes the hypotenuse avoiding overflow and underflow.\n","base.hypotf":"\nbase.hypotf( x:number, y:number )\n Computes the hypotenuse avoiding overflow and underflow (single-precision).\n","base.identity":"\nbase.identity( x:number )\n Evaluates the identity function for a double-precision floating-point number\n `x`.\n","base.identityf":"\nbase.identityf( x:number )\n Evaluates the identity function for a single-precision floating-point number\n `x`.\n","base.imul":"\nbase.imul( a:integer, b:integer )\n Performs C-like multiplication of two signed 32-bit integers.\n","base.imuldw":"\nbase.imuldw( a:integer, b:integer )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n","base.imuldw.assign":"\nbase.imuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n","base.int2slice":"\nbase.int2slice( value:integer, max:integer, strict:boolean )\n Converts an integer to a Slice object.\n","base.int32ToUint32":"\nbase.int32ToUint32( x:integer )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n","base.inv":"\nbase.inv( x:number )\n Computes the multiplicative inverse of a double-precision floating-point\n number `x`.\n","base.invcase":"\nbase.invcase( str:string )\n Converts a string to inverse case.\n","base.invf":"\nbase.invf( x:number )\n Computes the multiplicative inverse of a single-precision floating-point\n number `x`.\n","base.isComposite":"\nbase.isComposite( x:number )\n Tests if a number is composite.\n","base.isCoprime":"\nbase.isCoprime( a:number, b:number )\n Tests if two numbers are coprime.\n","base.isEven":"\nbase.isEven( x:number )\n Tests if a finite numeric value is an even number.\n","base.isEvenInt32":"\nbase.isEvenInt32( x:integer )\n Tests if a 32-bit integer is even.\n","base.isFinite":"\nbase.isFinite( x:number )\n Tests if a double-precision floating-point numeric value is finite.\n","base.isFinitef":"\nbase.isFinitef( x:number )\n Tests if a single-precision floating-point numeric value is finite.\n","base.isInfinite":"\nbase.isInfinite( x:number )\n Tests if a double-precision floating-point numeric value is infinite.\n","base.isInfinitef":"\nbase.isInfinitef( x:number )\n Tests if a single-precision floating-point numeric value is infinite.\n","base.isInteger":"\nbase.isInteger( x:number )\n Tests if a finite double-precision floating-point number is an integer.\n","base.isnan":"\nbase.isnan( x:number )\n Tests if a double-precision floating-point numeric value is `NaN`.\n","base.isnanf":"\nbase.isnanf( x:number )\n Tests if a single-precision floating-point numeric value is `NaN`.\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x:number )\n Tests if a double-precision floating-point numeric value is a negative\n finite number.\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x:number )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n","base.isNegativeZero":"\nbase.isNegativeZero( x:number )\n Tests if a double-precision floating-point numeric value is negative zero.\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x:number )\n Tests if a single-precision floating-point numeric value is negative zero.\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x:number )\n Tests if a double-precision floating-point numeric value is a nonnegative\n finite number.\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x:number )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x:number )\n Tests if a double-precision floating-point numeric value is a nonpositive\n finite number.\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x:number )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n","base.isOdd":"\nbase.isOdd( x:number )\n Tests if a finite numeric value is an odd number.\n","base.isOddInt32":"\nbase.isOddInt32( x:integer )\n Tests if a 32-bit integer is odd.\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x:number )\n Tests if a double-precision floating-point numeric value is a positive\n finite number.\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x:number )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n","base.isPositiveZero":"\nbase.isPositiveZero( x:number )\n Tests if a double-precision floating-point numeric value is positive zero.\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x:number )\n Tests if a single-precision floating-point numeric value is positive zero.\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x:integer )\n Tests whether an unsigned integer is a power of 2.\n","base.isPrime":"\nbase.isPrime( x:number )\n Tests if a number is prime.\n","base.isProbability":"\nbase.isProbability( x:number )\n Tests if a double-precision floating-point number value is a probability.\n","base.isSafeInteger":"\nbase.isSafeInteger( x:number )\n Tests if a finite double-precision floating-point number is a safe integer.\n","base.kebabcase":"\nbase.kebabcase( str:string )\n Converts a string to kebab case.\n","base.kernelBetainc":"\nbase.kernelBetainc( x:number, a:number, b:number, regularized:boolean, \n upper:boolean )\n Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x:number, a:number, b:number, regularized:boolean, \n upper:boolean, out:Array|TypedArray|Object, stride:integer, offset:integer )\n Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a:number, b:number, p:number, q:number )\n Computes the inverse of the lower incomplete beta function.\n","base.kernelCos":"\nbase.kernelCos( x:number, y:number )\n Computes the cosine of a double-precision floating-point number on the\n interval [-π/4, π/4].\n","base.kernelLog1p":"\nbase.kernelLog1p( f:number )\n Evaluates a correction term for double-precision base-2 and base-10\n logarithms when `1+f` is in `[√2/2, √2]`.\n","base.kernelSin":"\nbase.kernelSin( x:number, y:number )\n Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n","base.kernelTan":"\nbase.kernelTan( x:number, y:number, k:integer )\n Computes the tangent of a double-precision floating-point number on the\n interval [-π/4, π/4].\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i:number, j:number )\n Evaluates the Kronecker delta.\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i:number, j:number )\n Evaluates the Kronecker delta (single-precision).\n","base.labs":"\nbase.labs( x:integer )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n","base.last":"\nbase.last( str:string, n:integer )\n Returns the last `n` UTF-16 code units of a string.\n","base.lastCodePoint":"\nbase.lastCodePoint( str:string, n:integer )\n Returns the last `n` Unicode code points of a string.\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str:string, n:integer )\n Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n","base.lcm":"\nbase.lcm( a:integer, b:integer )\n Computes the least common multiple (lcm).\n","base.ldexp":"\nbase.ldexp( frac:number, exp:number )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n","base.leftPad":"\nbase.leftPad( str:string, len:integer, pad:string )\n Left pads a string such that the padded string has a length of at least\n `len`.\n","base.leftTrim":"\nbase.leftTrim( str:string )\n Trims whitespace from the beginning of a string.\n","base.ln":"\nbase.ln( x:number )\n Evaluates the natural logarithm of a double-precision floating-point number.\n","base.log":"\nbase.log( x:number, b:number )\n Computes the base `b` logarithm of a double-precision floating-point number.\n","base.log1mexp":"\nbase.log1mexp( x:number )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n","base.log1p":"\nbase.log1p( x:number )\n Evaluates the natural logarithm of `1+x`.\n","base.log1pexp":"\nbase.log1pexp( x:number )\n Evaluates the natural logarithm of `1+exp(x)`.\n","base.log1pmx":"\nbase.log1pmx( x:number )\n Evaluates `ln(1+x) - x`.\n","base.log2":"\nbase.log2( x:number )\n Evaluates the binary logarithm (base two).\n","base.log10":"\nbase.log10( x:number )\n Evaluates the common logarithm (base 10).\n","base.logaddexp":"\nbase.logaddexp( x:number, y:number )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n","base.logit":"\nbase.logit( p:number )\n Evaluates the logit function.\n","base.lowercase":"\nbase.lowercase( str:string )\n Converts a string to lowercase.\n","base.lucas":"\nbase.lucas( n:integer )\n Computes the nth Lucas number.\n","base.lucaspoly":"\nbase.lucaspoly( n:integer, x:number )\n Evaluates a Lucas polynomial.\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n:integer )\n Returns a function for evaluating a Lucas polynomial.\n","base.max":"\nbase.max( x:number, y:number )\n Returns the maximum value.\n","base.maxabs":"\nbase.maxabs( x:number, y:number )\n Returns the maximum absolute value.\n","base.maxabsn":"\nbase.maxabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the maximum absolute value.\n","base.maxn":"\nbase.maxn( [x:number[, y:number[, ...args:number]]] )\n Returns the maximum value.\n","base.min":"\nbase.min( x:number, y:number )\n Returns the minimum value.\n","base.minabs":"\nbase.minabs( x:number, y:number )\n Returns the minimum absolute value.\n","base.minabsn":"\nbase.minabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum absolute value.\n","base.minmax":"\nbase.minmax( x:number, y:number )\n Returns the minimum and maximum values.\n","base.minmax.assign":"\nbase.minmax.assign( x:number, y:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n","base.minmaxabs":"\nbase.minmaxabs( x:number, y:number )\n Returns the minimum and maximum absolute values.\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x:number, y:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Returns the minimum and maximum absolute values and assigns results to a\n provided output array.\n","base.minmaxabsn":"\nbase.minmaxabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum and maximum absolute values.\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x:number[, y:number[, ...args:number]]], \n out:Array|TypedArray|Object, stride:integer, offset:integer )\n Returns the minimum and maximum absolute values.\n","base.minmaxn":"\nbase.minmaxn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum and maximum values.\n","base.minmaxn.assign":"\nbase.minmaxn.assign( [x:number[, y:number[, ...args:number]]], \n out:Array|TypedArray|Object, stride:integer, offset:integer )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n","base.minn":"\nbase.minn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum value.\n","base.modf":"\nbase.modf( x:number )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n","base.modf.assign":"\nbase.modf.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n","base.mul":"\nbase.mul( x:number, y:number )\n Multiplies two double-precision floating-point numbers `x` and `y`.\n","base.mulf":"\nbase.mulf( x:number, y:number )\n Multiplies two single-precision floating-point numbers `x` and `y`.\n","base.ndarray":"\nbase.ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string )\n Returns an ndarray.\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n Underlying data type.\n","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n Number of dimensions.\n","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n Array order.\n","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n Array shape.\n","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","base.ndarray.prototype.toLocaleString":"\nbase.ndarray.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an ndarray as a locale-aware string.\n","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in an input ndarray and assigns results\n to elements in an output ndarray.\n","base.ndzeros":"\nbase.ndzeros( dtype:string|DataType, shape:ArrayLikeObject, \n order:string )\n Returns a zero-filled ndarray having a specified shape and data type.\n","base.ndzerosLike":"\nbase.ndzerosLike( x:ndarray )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n","base.negafibonacci":"\nbase.negafibonacci( n:integer )\n Computes the nth negaFibonacci number.\n","base.negalucas":"\nbase.negalucas( n:integer )\n Computes the nth negaLucas number.\n","base.nonfibonacci":"\nbase.nonfibonacci( n:integer )\n Computes the nth non-Fibonacci number.\n","base.normalize":"\nbase.normalize( x:number )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n","base.normalize.assign":"\nbase.normalize.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n","base.normalizef":"\nbase.normalizef( x:float )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n","base.normalizef.assign":"\nbase.normalizef.assign( x:float, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n","base.normalizeMultiSlice":"\nbase.normalizeMultiSlice( slice:MultiSlice, shape:Array, \n strict:boolean )\n Returns a normalized MultiSlice object.\n","base.normalizeSlice":"\nbase.normalizeSlice( slice:Slice, len:integer, strict:boolean )\n Returns a normalized Slice object.\n","base.normhermitepoly":"\nbase.normhermitepoly( n:integer, x:number )\n Evaluates a normalized Hermite polynomial using double-precision floating-\n point arithmetic.\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n:integer )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n","base.pascalcase":"\nbase.pascalcase( str:string )\n Converts a string to Pascal case.\n","base.pdiff":"\nbase.pdiff( x:number, y:number )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n","base.pdifff":"\nbase.pdifff( x:number, y:number )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n","base.percentEncode":"\nbase.percentEncode( str:string )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","base.polygamma":"\nbase.polygamma( n:integer, x:number )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n","base.pow":"\nbase.pow( b:number, x:number )\n Evaluates the exponential function `bˣ`.\n","base.powm1":"\nbase.powm1( b:number, x:number )\n Evaluates `bˣ - 1`.\n","base.rad2deg":"\nbase.rad2deg( x:number )\n Converts an angle from radians to degrees.\n","base.rad2degf":"\nbase.rad2degf( x:number )\n Converts an angle from radians to degrees (single-precision).\n","base.ramp":"\nbase.ramp( x:number )\n Evaluates the ramp function.\n","base.rampf":"\nbase.rampf( x:number )\n Evaluates the ramp function (single-precision).\n","base.random.arcsine":"\nbase.random.arcsine( a:number, b:number )\n Returns a pseudorandom number drawn from an arcsine distribution.\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n Generator name.\n","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n Length of generator seed.\n","base.random.arcsine.state":"\nbase.random.arcsine.state\n Generator state.\n","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n Length of generator state.\n","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.bernoulli":"\nbase.random.bernoulli( p:number )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n Generator name.\n","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n Length of generator seed.\n","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n Generator state.\n","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n Length of generator state.\n","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.beta":"\nbase.random.beta( α:number, β:number )\n Returns a pseudorandom number drawn from a beta distribution.\n","base.random.beta.factory":"\nbase.random.beta.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n","base.random.beta.NAME":"\nbase.random.beta.NAME\n Generator name.\n","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n","base.random.beta.seed":"\nbase.random.beta.seed\n Pseudorandom number generator seed.\n","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n Length of generator seed.\n","base.random.beta.state":"\nbase.random.beta.state\n Generator state.\n","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n Length of generator state.\n","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.betaprime":"\nbase.random.betaprime( α:number, β:number )\n Returns a pseudorandom number drawn from a beta prime distribution.\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n Generator name.\n","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n Length of generator seed.\n","base.random.betaprime.state":"\nbase.random.betaprime.state\n Generator state.\n","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n Length of generator state.\n","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.binomial":"\nbase.random.binomial( n:integer, p:number )\n Returns a pseudorandom number drawn from a binomial distribution.\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n:integer, p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n Generator name.\n","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n","base.random.binomial.seed":"\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n Length of generator seed.\n","base.random.binomial.state":"\nbase.random.binomial.state\n Generator state.\n","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n Length of generator state.\n","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n Size of generator state.\n","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n Generator name.\n","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n Length of generator seed.\n","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n Generator state.\n","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n Length of generator state.\n","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.cauchy":"\nbase.random.cauchy( x0:number, Ɣ:number )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0:number, Ɣ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n Generator name.\n","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n Length of generator seed.\n","base.random.cauchy.state":"\nbase.random.cauchy.state\n Generator state.\n","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n Length of generator state.\n","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.chi":"\nbase.random.chi( k:number )\n Returns a pseudorandom number drawn from a chi distribution.\n","base.random.chi.factory":"\nbase.random.chi.factory( [k:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n","base.random.chi.NAME":"\nbase.random.chi.NAME\n Generator name.\n","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n","base.random.chi.seed":"\nbase.random.chi.seed\n Pseudorandom number generator seed.\n","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n Length of generator seed.\n","base.random.chi.state":"\nbase.random.chi.state\n Generator state.\n","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n Length of generator state.\n","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.chisquare":"\nbase.random.chisquare( k:number )\n Returns a pseudorandom number drawn from a chi-square distribution.\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n Generator name.\n","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n Length of generator seed.\n","base.random.chisquare.state":"\nbase.random.chisquare.state\n Generator state.\n","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n Length of generator state.\n","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.cosine":"\nbase.random.cosine( μ:number, s:number )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ:number, s:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n Generator name.\n","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n","base.random.cosine.seed":"\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n Length of generator seed.\n","base.random.cosine.state":"\nbase.random.cosine.state\n Generator state.\n","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n Length of generator state.\n","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.discreteUniform":"\nbase.random.discreteUniform( a:integer, b:integer )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a:integer, b:integer, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n Generator name.\n","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n Generator state.\n","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n Length of generator state.\n","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.erlang":"\nbase.random.erlang( k:integer, λ:number )\n Returns a pseudorandom number drawn from an Erlang distribution.\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k:integer, λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n Generator name.\n","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n","base.random.erlang.seed":"\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n Length of generator seed.\n","base.random.erlang.state":"\nbase.random.erlang.state\n Generator state.\n","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n Length of generator state.\n","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.exponential":"\nbase.random.exponential( λ:number )\n Returns a pseudorandom number drawn from an exponential distribution.\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n Generator name.\n","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n","base.random.exponential.seed":"\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n Length of generator seed.\n","base.random.exponential.state":"\nbase.random.exponential.state\n Generator state.\n","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n Length of generator state.\n","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.f":"\nbase.random.f( d1:number, d2:number )\n Returns a pseudorandom number drawn from an F distribution.\n","base.random.f.factory":"\nbase.random.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n","base.random.f.NAME":"\nbase.random.f.NAME\n Generator name.\n","base.random.f.PRNG":"\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n","base.random.f.seed":"\nbase.random.f.seed\n Pseudorandom number generator seed.\n","base.random.f.seedLength":"\nbase.random.f.seedLength\n Length of generator seed.\n","base.random.f.state":"\nbase.random.f.state\n Generator state.\n","base.random.f.stateLength":"\nbase.random.f.stateLength\n Length of generator state.\n","base.random.f.byteLength":"\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n","base.random.f.toJSON":"\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.frechet":"\nbase.random.frechet( α:number, s:number, m:number )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α:number, s:number, m:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n Generator name.\n","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n","base.random.frechet.seed":"\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n Length of generator seed.\n","base.random.frechet.state":"\nbase.random.frechet.state\n Generator state.\n","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n Length of generator state.\n","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.gamma":"\nbase.random.gamma( α:number, β:number )\n Returns a pseudorandom number drawn from a gamma distribution.\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n Generator name.\n","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n","base.random.gamma.seed":"\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n Length of generator seed.\n","base.random.gamma.state":"\nbase.random.gamma.state\n Generator state.\n","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n Length of generator state.\n","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n Size of generator state.\n","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.geometric":"\nbase.random.geometric( p:number )\n Returns a pseudorandom number drawn from a geometric distribution.\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n Generator name.\n","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n","base.random.geometric.seed":"\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n Length of generator seed.\n","base.random.geometric.state":"\nbase.random.geometric.state\n Generator state.\n","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n Length of generator state.\n","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.gumbel":"\nbase.random.gumbel( μ:number, β:number )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n Generator name.\n","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n Length of generator seed.\n","base.random.gumbel.state":"\nbase.random.gumbel.state\n Generator state.\n","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n Length of generator state.\n","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.hypergeometric":"\nbase.random.hypergeometric( N:integer, K:integer, n:integer )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N:integer, K:integer, n:integer, ]\n [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n Generator name.\n","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n Generator state.\n","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n Length of generator state.\n","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n Generator name.\n","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n Generator state.\n","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.invgamma":"\nbase.random.invgamma( α:number, β:number )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n Generator name.\n","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n Length of generator seed.\n","base.random.invgamma.state":"\nbase.random.invgamma.state\n Generator state.\n","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n Length of generator state.\n","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n Size of generator state.\n","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a:number, b:number )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n Generator name.\n","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n Generator state.\n","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.laplace":"\nbase.random.laplace( μ:number, b:number )\n Returns a pseudorandom number drawn from a Laplace distribution.\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n Generator name.\n","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n","base.random.laplace.seed":"\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n Length of generator seed.\n","base.random.laplace.state":"\nbase.random.laplace.state\n Generator state.\n","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n Length of generator state.\n","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.levy":"\nbase.random.levy( μ:number, c:number )\n Returns a pseudorandom number drawn from a Lévy distribution.\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ:number, c:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n","base.random.levy.NAME":"\nbase.random.levy.NAME\n Generator name.\n","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n","base.random.levy.seed":"\nbase.random.levy.seed\n Pseudorandom number generator seed.\n","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n Length of generator seed.\n","base.random.levy.state":"\nbase.random.levy.state\n Generator state.\n","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n Length of generator state.\n","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.logistic":"\nbase.random.logistic( μ:number, s:number )\n Returns a pseudorandom number drawn from a logistic distribution.\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ:number, s:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n Generator name.\n","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n","base.random.logistic.seed":"\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n Length of generator seed.\n","base.random.logistic.state":"\nbase.random.logistic.state\n Generator state.\n","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n Length of generator state.\n","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.lognormal":"\nbase.random.lognormal( μ:number, σ:number )\n Returns a pseudorandom number drawn from a lognormal distribution.\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n Generator name.\n","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n Length of generator seed.\n","base.random.lognormal.state":"\nbase.random.lognormal.state\n Generator state.\n","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n Length of generator state.\n","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstd.factory":"\nbase.random.minstd.factory( [options:Object] )\n Returns a linear congruential pseudorandom number generator (LCG).\n","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n Generator name.\n","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n Minimum possible value.\n","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n Maximum possible value.\n","base.random.minstd.seed":"\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n Length of generator seed.\n","base.random.minstd.state":"\nbase.random.minstd.state\n Generator state.\n","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n Length of generator state.\n","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options:Object] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n Generator name.\n","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n Generator state.\n","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options:Object] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n Generator name.\n","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n Minimum possible value.\n","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n Maximum possible value.\n","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n Length of generator seed.\n","base.random.mt19937.state":"\nbase.random.mt19937.state\n Generator state.\n","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n Length of generator state.\n","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r:number, p:number )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n Generator name.\n","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n Generator state.\n","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.normal":"\nbase.random.normal( μ:number, σ:number )\n Returns a pseudorandom number drawn from a normal distribution.\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n","base.random.normal.NAME":"\nbase.random.normal.NAME\n Generator name.\n","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n","base.random.normal.seed":"\nbase.random.normal.seed\n Pseudorandom number generator seed.\n","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n Length of generator seed.\n","base.random.normal.state":"\nbase.random.normal.state\n Generator state.\n","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n Length of generator state.\n","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n Size of generator state.\n","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.pareto1":"\nbase.random.pareto1( α:number, β:number )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n Generator name.\n","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n Length of generator seed.\n","base.random.pareto1.state":"\nbase.random.pareto1.state\n Generator state.\n","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n Length of generator state.\n","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.poisson":"\nbase.random.poisson( λ:number )\n Returns a pseudorandom number drawn from a Poisson distribution.\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n Generator name.\n","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n","base.random.poisson.seed":"\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n Length of generator seed.\n","base.random.poisson.state":"\nbase.random.poisson.state\n Generator state.\n","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n Length of generator state.\n","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n","base.random.randi.factory":"\nbase.random.randi.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n","base.random.randi.NAME":"\nbase.random.randi.NAME\n Generator name.\n","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n","base.random.randi.MIN":"\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n","base.random.randi.MAX":"\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n","base.random.randi.seed":"\nbase.random.randi.seed\n Pseudorandom number generator seed.\n","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n Length of generator seed.\n","base.random.randi.state":"\nbase.random.randi.state\n Generator state.\n","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n Length of generator state.\n","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.randn.factory":"\nbase.random.randn.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.randn.NAME":"\nbase.random.randn.NAME\n Generator name.\n","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n","base.random.randn.seed":"\nbase.random.randn.seed\n Pseudorandom number generator seed.\n","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n Length of generator seed.\n","base.random.randn.state":"\nbase.random.randn.state\n Generator state.\n","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n Length of generator state.\n","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n","base.random.randu.factory":"\nbase.random.randu.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n","base.random.randu.NAME":"\nbase.random.randu.NAME\n Generator name.\n","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n","base.random.randu.MIN":"\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n","base.random.randu.MAX":"\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n","base.random.randu.seed":"\nbase.random.randu.seed\n Pseudorandom number generator seed.\n","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n Length of generator seed.\n","base.random.randu.state":"\nbase.random.randu.state\n Generator state.\n","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n Length of generator state.\n","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.rayleigh":"\nbase.random.rayleigh( σ:number )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n Generator name.\n","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n Length of generator seed.\n","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n Generator state.\n","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n Length of generator state.\n","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.t":"\nbase.random.t( v:number )\n Returns a pseudorandom number drawn from a Student's t distribution.\n","base.random.t.factory":"\nbase.random.t.factory( [v:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n","base.random.t.NAME":"\nbase.random.t.NAME\n Generator name.\n","base.random.t.PRNG":"\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n","base.random.t.seed":"\nbase.random.t.seed\n Pseudorandom number generator seed.\n","base.random.t.seedLength":"\nbase.random.t.seedLength\n Length of generator seed.\n","base.random.t.state":"\nbase.random.t.state\n Generator state.\n","base.random.t.stateLength":"\nbase.random.t.stateLength\n Length of generator state.\n","base.random.t.byteLength":"\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n","base.random.t.toJSON":"\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.triangular":"\nbase.random.triangular( a:number, b:number, c:number )\n Returns a pseudorandom number drawn from a triangular distribution.\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n Generator name.\n","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n","base.random.triangular.seed":"\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n Length of generator seed.\n","base.random.triangular.state":"\nbase.random.triangular.state\n Generator state.\n","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n Length of generator state.\n","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.uniform":"\nbase.random.uniform( a:number, b:number )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n Generator name.\n","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n","base.random.uniform.seed":"\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n Length of generator seed.\n","base.random.uniform.state":"\nbase.random.uniform.state\n Generator state.\n","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n Length of generator state.\n","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.weibull":"\nbase.random.weibull( k:number, λ:number )\n Returns a pseudorandom number drawn from a Weibull distribution.\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k:number, λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n Generator name.\n","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n","base.random.weibull.seed":"\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n Length of generator seed.\n","base.random.weibull.state":"\nbase.random.weibull.state\n Generator state.\n","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n Length of generator state.\n","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.rcbrt":"\nbase.rcbrt( x:number )\n Computes the reciprocal cube root of a double-precision floating-point\n number.\n","base.rcbrtf":"\nbase.rcbrtf( x:number )\n Computes the reciprocal cube root of a single-precision floating-point\n number.\n","base.reldiff":"\nbase.reldiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers.\n","base.removeFirst":"\nbase.removeFirst( str:string, n:integer )\n Removes the first `n` UTF-16 code units of a string.\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str:string, n:integer )\n Removes the first `n` Unicode code points of a string.\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str:string, n:integer )\n Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n","base.removeLast":"\nbase.removeLast( str:string, n:integer )\n Removes the last `n` UTF-16 code units of a string.\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str:string, n:integer )\n Removes the last `n` Unicode code points of a string.\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str:string, n:integer )\n Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n","base.rempio2":"\nbase.rempio2( x:number, y:Array|TypedArray|Object )\n Computes `x - nπ/2 = r`.\n","base.repeat":"\nbase.repeat( str:string, n:integer )\n Repeats a string `n` times and returns the concatenated result.\n","base.replace":"\nbase.replace( str:string, search:RegExp, newval:string|Function )\n Replaces search occurrences with a replacement string.\n","base.replaceAfter":"\nbase.replaceAfter( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring after the first occurrence of a specified search\n string.\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring after the last occurrence of a specified search\n string.\n","base.replaceBefore":"\nbase.replaceBefore( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring before the first occurrence of a specified search\n string.\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring before the last occurrence of a specified search\n string.\n","base.reverse":"\nbase.reverse( str:string )\n Reverses the UTF-16 code units of a string.\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str:string )\n Reverses the Unicode code points of a string.\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str:string )\n Reverses the grapheme clusters (i.e., user-perceived characters) of a\n string.\n","base.rightPad":"\nbase.rightPad( str:string, len:integer, pad:string )\n Right pads a string such that the padded string has a length of at least\n `len`.\n","base.rightTrim":"\nbase.rightTrim( str:string )\n Trims whitespace from the end of a string.\n","base.risingFactorial":"\nbase.risingFactorial( x:number, n:integer )\n Computes the rising factorial of `x` and `n`.\n","base.rotl32":"\nbase.rotl32( x:integer, shift:integer )\n Performs a bitwise rotation to the left.\n","base.rotr32":"\nbase.rotr32( x:integer, shift:integer )\n Performs a bitwise rotation to the right.\n","base.round":"\nbase.round( x:number )\n Rounds a numeric value to the nearest integer.\n","base.round2":"\nbase.round2( x:number )\n Rounds a numeric value to the nearest power of two on a linear scale.\n","base.round10":"\nbase.round10( x:number )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n","base.roundb":"\nbase.roundb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n","base.roundn":"\nbase.roundn( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n`.\n","base.roundsd":"\nbase.roundsd( x:number, n:integer[, b:integer] )\n Rounds a double-precision floating-point number to the nearest value with\n `n` significant figures.\n","base.rsqrt":"\nbase.rsqrt( x:number )\n Computes the reciprocal square root of a double-precision floating-point\n number.\n","base.rsqrtf":"\nbase.rsqrtf( x:number )\n Computes the reciprocal square root of a single-precision floating-point\n number.\n","base.sargs2multislice":"\nbase.sargs2multislice( str:string )\n Creates a MultiSlice object from a comma-separated list of string-serialized\n MultiSlice constructor arguments.\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value:any, dtype:string|DataType, order:string )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n","base.secd":"\nbase.secd( x:number )\n Computes the secant of an angle measured in degrees.\n","base.seq2multislice":"\nbase.seq2multislice( str:string, shape:Array, strict:boolean )\n Converts a multidimensional subsequence string to a MultiSlice object.\n","base.seq2slice":"\nbase.seq2slice( str:string, len:integer, strict:boolean )\n Converts a subsequence string to a Slice object.\n","base.setHighWord":"\nbase.setHighWord( x:number, high:integer )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n","base.setLowWord":"\nbase.setLowWord( x:number, low:integer )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n","base.sici":"\nbase.sici( x:number )\n Computes the sine and cosine integrals.\n","base.sici.assign":"\nbase.sici.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n","base.signbit":"\nbase.signbit( x:number )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.signbitf":"\nbase.signbitf( x:float )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.significandf":"\nbase.significandf( x:float )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n","base.signum":"\nbase.signum( x:number )\n Evaluates the signum function for a double-precision floating-point number.\n","base.signumf":"\nbase.signumf( x:number )\n Evaluates the signum function for a single-precision floating-point number.\n","base.sin":"\nbase.sin( x:number )\n Computes the sine of a number.\n","base.sinc":"\nbase.sinc( x:number )\n Computes the normalized cardinal sine of a number.\n","base.sincos":"\nbase.sincos( x:number )\n Simultaneously computes the sine and cosine of an angle measured in radians.\n","base.sincos.assign":"\nbase.sincos.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Simultaneously computes the sine and cosine of an angle measured in radians\n and assigns the results to a provided output array.\n","base.sincospi":"\nbase.sincospi( x:number )\n Simultaneously computes the sine and cosine of a number times π.\n","base.sincospi.assign":"\nbase.sincospi.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n","base.sinh":"\nbase.sinh( x:number )\n Computes the hyperbolic sine of a double-precision floating-point number.\n","base.sinpi":"\nbase.sinpi( x:number )\n Computes the value of `sin(πx)`.\n","base.slice2seq":"\nbase.slice2seq( slice:Slice )\n Converts a Slice object to a subsequence string.\n","base.sliceLength":"\nbase.sliceLength( slice:Slice )\n Returns the number of elements in a normalized slice.\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice:MultiSlice )\n Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice:MultiSlice )\n Returns a list of reduced dimensions in an un-normalized multi-slice.\n","base.sliceShape":"\nbase.sliceShape( slice:MultiSlice )\n Returns the shape of a normalized multi-slice.\n","base.snakecase":"\nbase.snakecase( str:string )\n Converts a string to snake case.\n","base.spence":"\nbase.spence( x:number )\n Evaluates Spence's function, which is also known as the dilogarithm.\n","base.sqrt":"\nbase.sqrt( x:number )\n Computes the principal square root of a double-precision floating-point\n number.\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x:number )\n Computes the principal square root of `1+x` minus one.\n","base.sqrtf":"\nbase.sqrtf( x:number )\n Computes the principal square root of a single-precision floating-point\n number.\n","base.sqrtpi":"\nbase.sqrtpi( x:number )\n Computes the principal square root of the product of π and a positive\n double-precision floating-point number.\n","base.startcase":"\nbase.startcase( str:string )\n Capitalizes the first letter of each word in an input string.\n","base.startsWith":"\nbase.startsWith( str:string, search:string, position:integer )\n Tests if a string starts with the characters of another string.\n","base.stickycase":"\nbase.stickycase( str[, p] )\n Converts a string to sticky case.\n","base.strided.binary":"\nbase.strided.binary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike, dtypes3:ArrayLike[, options:Object] )\n Generates a list of binary interface signatures from strided array data\n types.\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table:Object, signatures:ArrayLike )\n Assigns callbacks to binary interfaces according to type promotion rules.\n","base.strided.ccopy":"\nbase.strided.ccopy( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector.\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n","base.strided.cmap":"\nbase.strided.cmap( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer, fcn:Function )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array.\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n","base.strided.cswap":"\nbase.strided.cswap( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer )\n Interchanges two complex single-precision floating-point vectors.\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n","base.strided.cumax":"\nbase.strided.cumax( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative maximum of a strided array.\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative maximum absolute value of a strided array.\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n","base.strided.cumin":"\nbase.strided.cumin( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative minimum of a strided array.\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n","base.strided.cuminabs":"\nbase.strided.cuminabs( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative minimum absolute value of a strided array.\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n","base.strided.dabs":"\nbase.strided.dabs( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dabs2":"\nbase.strided.dabs2( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dapx":"\nbase.strided.dapx( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array.\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dapxsum":"\nbase.strided.dapxsum( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum.\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation.\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n","base.strided.dasum":"\nbase.strided.dasum( N:integer, x:Float64Array, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.dasumpw":"\nbase.strided.dasumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation.\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n","base.strided.daxpy":"\nbase.strided.daxpy( N:integer, alpha:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n","base.strided.dcbrt":"\nbase.strided.dcbrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dceil":"\nbase.strided.dceil( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dcopy":"\nbase.strided.dcopy( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.dcumax":"\nbase.strided.dcumax( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.dcumin":"\nbase.strided.dcumin( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.dcusum":"\nbase.strided.dcusum( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N:integer, sum:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dcusumors":"\nbase.strided.dcusumors( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation.\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation.\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.ddot":"\nbase.strided.ddot( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the dot product of two double-precision floating-point vectors.\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n","base.strided.dfill":"\nbase.strided.dfill( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Fills a double-precision floating-point strided array with a specified\n scalar constant.\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Fills a double-precision floating-point strided array with a specified\n scalar constant using alternative indexing semantics.\n","base.strided.dfloor":"\nbase.strided.dfloor( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dinv":"\nbase.strided.dinv( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dmap":"\nbase.strided.dmap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array.\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.dmap2":"\nbase.strided.dmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, z:Float64Array, sz:integer, fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays and assigns results to a double-precision floating-point strided\n output array.\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n y:Float64Array, sy:integer, oy:integer, z:Float64Array, sz:integer, \n oz:integer, fcn:Function )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.dmax":"\nbase.strided.dmax( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array.\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmean":"\nbase.strided.dmean( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.dmeanli":"\nbase.strided.dmeanli( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n","base.strided.dmeanors":"\nbase.strided.dmeanors( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N:integer, c:number, x:Float64Array, \n strideX:integer, out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array.\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmidrange":"\nbase.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )\n Computes the mid-range of a double-precision floating-point strided array.\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.dmin":"\nbase.strided.dmin( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array.\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dminabs":"\nbase.strided.dminabs( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dminsorted":"\nbase.strided.dminsorted( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmskabs":"\nbase.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.dmskceil":"\nbase.strided.dmskceil( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskinv":"\nbase.strided.dmskinv( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmskmap":"\nbase.strided.dmskmap( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float64Array, sy:integer, \n oy:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, m:Uint8Array, sm:integer, z:Float64Array, sz:integer, \n fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, y:Float64Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n om:integer, z:Float64Array, sz:integer, oz:integer, fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.dmskmax":"\nbase.strided.dmskmax( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.dmskmin":"\nbase.strided.dmskmin( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.dmskramp":"\nbase.strided.dmskramp( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskrange":"\nbase.strided.dmskrange( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y`.\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.dnanasum":"\nbase.strided.dnanasum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values.\n","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n","base.strided.dnanmax":"\nbase.strided.dnanmax( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnanmean":"\nbase.strided.dnanmean( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.dnanmin":"\nbase.strided.dnanmin( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnannsum":"\nbase.strided.dnannsum( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.dnanrange":"\nbase.strided.dnanrange( N:integer, x:Float64Array, strideX:integer )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n","base.strided.dnansum":"\nbase.strided.dnansum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dnansumors":"\nbase.strided.dnansumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values.\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n","base.strided.dnrm2":"\nbase.strided.dnrm2( N:integer, x:Float64Array, stride:integer )\n Computes the L2-norm of a double-precision floating-point vector.\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n","base.strided.dramp":"\nbase.strided.dramp( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.drange":"\nbase.strided.drange( N:integer, x:Float64Array, strideX:integer )\n Computes the range of a double-precision floating-point strided array.\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n","base.strided.drev":"\nbase.strided.drev( N:integer, x:Float64Array, strideX:integer )\n Reverses a double-precision floating-point strided array in-place.\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n","base.strided.drsqrt":"\nbase.strided.drsqrt( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using extended accumulation and returning\n an extended precision result.\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n","base.strided.dscal":"\nbase.strided.dscal( N:integer, alpha:number, x:Float64Array, stride:integer )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n","base.strided.dsdot":"\nbase.strided.dsdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation and result.\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n","base.strided.dsem":"\nbase.strided.dsem( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dsemch":"\nbase.strided.dsemch( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n","base.strided.dsempn":"\nbase.strided.dsempn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n","base.strided.dsemtk":"\nbase.strided.dsemtk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n","base.strided.dsemwd":"\nbase.strided.dsemwd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.dsemyc":"\nbase.strided.dsemyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n","base.strided.dsmean":"\nbase.strided.dsmean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using a two-pass error correction algorithm\n with extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using Welford's algorithm with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N:integer, x:Float32Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n","base.strided.dsnansum":"\nbase.strided.dsnansum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation,\n and returning an extended precision result.\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n","base.strided.dsorthp":"\nbase.strided.dsorthp( N:integer, order:number, x:Float64Array, strideX:integer )\n Sorts a double-precision floating-point strided array using heapsort.\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n","base.strided.dsortins":"\nbase.strided.dsortins( N:integer, order:number, x:Float64Array, \n strideX:integer )\n Sorts a double-precision floating-point strided array using insertion sort.\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n","base.strided.dsortsh":"\nbase.strided.dsortsh( N:integer, order:number, x:Float64Array, stride:integer )\n Sorts a double-precision floating-point strided array using Shellsort.\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N:integer, order:number, x:Float64Array, \n stride:integer, offset:integer )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n","base.strided.dsqrt":"\nbase.strided.dsqrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dssum":"\nbase.strided.dssum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and returning an extended precision result.\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n","base.strided.dssumors":"\nbase.strided.dssumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and returning\n an extended precision result.\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n","base.strided.dssumpw":"\nbase.strided.dssumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and returning an\n extended precision result.\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n","base.strided.dstdev":"\nbase.strided.dstdev( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dstdevch":"\nbase.strided.dstdevch( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n","base.strided.dsum":"\nbase.strided.dsum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements.\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.dsumors":"\nbase.strided.dsumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dsumpw":"\nbase.strided.dsumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.dsvariance":"\nbase.strided.dsvariance( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N:integer, correction:number, \n x:Float32Array, strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dswap":"\nbase.strided.dswap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Interchanges two double-precision floating-point vectors.\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n","base.strided.dtrunc":"\nbase.strided.dtrunc( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype:integer )\n Returns the data type string associated with a strided array data type\n enumeration constant.\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype:any )\n Returns the enumeration constant associated with a supported strided array\n data type value.\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype:any )\n Returns the data type string associated with a supported data type value.\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype:string )\n Returns the enumeration constant associated with a strided array data type\n string.\n","base.strided.dvariance":"\nbase.strided.dvariance( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array.\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.dvariancech":"\nbase.strided.dvariancech( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.dvarm":"\nbase.strided.dvarm( N:integer, correction:number, mean:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.gapx":"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each element in a strided array.\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n","base.strided.gapxsum":"\nbase.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum.\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation.\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation.\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n","base.strided.gasum":"\nbase.strided.gasum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.gasumpw":"\nbase.strided.gasumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.gaxpy":"\nbase.strided.gaxpy( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n","base.strided.gcopy":"\nbase.strided.gcopy( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.gcusum":"\nbase.strided.gcusum( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements.\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumors":"\nbase.strided.gcusumors( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n","base.strided.gdot":"\nbase.strided.gdot( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the dot product of two vectors.\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n","base.strided.gfill":"\nbase.strided.gfill( N:integer, alpha:any, x:ArrayLikeObject, strideX:integer )\n Fills a strided array with a specified scalar constant.\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N:integer, alpha:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n","base.strided.gfillBy":"\nbase.strided.gfillBy( N:integer, x:ArrayLikeObject, strideX:integer, \n clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function.\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N:integer, x:Array|TypedArray, strideX:integer, \n out:Array|TypedArray, strideOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, out:Array|TypedArray, strideOut:integer, \n offsetOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansum":"\nbase.strided.gnansum( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values.\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.gnansumors":"\nbase.strided.gnansumors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n","base.strided.gnrm2":"\nbase.strided.gnrm2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the L2-norm of a vector.\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the L2-norm of a vector using alternative indexing semantics.\n","base.strided.grev":"\nbase.strided.grev( N:integer, x:ArrayLikeObject, strideX:integer )\n Reverses a strided array in-place.\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer )\n Reverses a strided array in-place using alternative indexing semantics.\n","base.strided.gscal":"\nbase.strided.gscal( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Multiplies a vector by a scalar constant.\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Multiplies a vector by a scalar constant using alternative indexing\n semantics.\n","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort.\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort.\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n","base.strided.gsorthp":"\nbase.strided.gsorthp( N:integer, order:number, x:Array|TypedArray, \n strideX:integer )\n Sorts a strided array using heapsort.\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Sorts a strided array using heapsort and alternative indexing semantics.\n","base.strided.gsortins":"\nbase.strided.gsortins( N:integer, order:number, x:Array|TypedArray, \n strideX:integer )\n Sorts a strided array using insertion sort.\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n","base.strided.gsortsh":"\nbase.strided.gsortsh( N:integer, order:number, x:Array|TypedArray, \n strideX:integer )\n Sorts a strided array using Shellsort.\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n","base.strided.gsum":"\nbase.strided.gsum( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements.\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gsumors":"\nbase.strided.gsumors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n","base.strided.gsumpw":"\nbase.strided.gsumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using pairwise summation.\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n","base.strided.gswap":"\nbase.strided.gswap( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Interchanges vectors `x` and `y`.\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n","base.strided.mapBy":"\nbase.strided.mapBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, fcn:Function, clbk:Function[, \n thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, fcn:Function, \n clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.mapBy2":"\nbase.strided.mapBy2( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n fcn:Function, clbk:Function[, thisArg:any] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array.\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, fcn:Function, \n clbk:Function[, thisArg:any] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n","base.strided.max":"\nbase.strided.max( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum value of a strided array.\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n","base.strided.maxabs":"\nbase.strided.maxabs( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum absolute value of a strided array.\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n","base.strided.maxBy":"\nbase.strided.maxBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the maximum value of a strided array via a callback function.\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n","base.strided.maxsorted":"\nbase.strided.maxsorted( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum value of a sorted strided array.\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N:integer, stride:integer, offset:integer )\n Returns the maximum accessible index based on a set of provided strided\n array parameters.\n","base.strided.mean":"\nbase.strided.mean( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array.\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n","base.strided.meankbn":"\nbase.strided.meankbn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm.\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n","base.strided.meankbn2":"\nbase.strided.meankbn2( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm.\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.meanors":"\nbase.strided.meanors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation.\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n","base.strided.meanpn":"\nbase.strided.meanpn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm.\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n","base.strided.meanpw":"\nbase.strided.meanpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using pairwise summation.\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n","base.strided.meanwd":"\nbase.strided.meanwd( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n","base.strided.mediansorted":"\nbase.strided.mediansorted( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the median value of a sorted strided array.\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta:Object, dtypes:ArrayLikeObject, \n obj:Object|Function, bool:boolean )\n Defines non-enumerable read-only properties which expose strided array\n function meta data.\n","base.strided.min":"\nbase.strided.min( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum value of a strided array.\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n","base.strided.minabs":"\nbase.strided.minabs( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum absolute value of a strided array.\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n","base.strided.minBy":"\nbase.strided.minBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the minimum value of a strided array via a callback function.\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n","base.strided.minsorted":"\nbase.strided.minsorted( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum value of a sorted strided array.\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N:integer, stride:integer, offset:integer )\n Returns the minimum accessible index based on a set of provided strided\n array parameters.\n","base.strided.mskmax":"\nbase.strided.mskmax( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the maximum value of a strided array according to a mask.\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskmin":"\nbase.strided.mskmin( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the minimum value of a strided array according to a mask.\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskrange":"\nbase.strided.mskrange( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the range of a strided array according to a mask.\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskunary":"\nbase.strided.mskunary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array and assigns results to elements in a\n strided output array.\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike[, options:Object] )\n Generates a list of masked unary interface signatures from strided array\n data types.\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table:Object, \n signatures:ArrayLike )\n Assigns callbacks to masked unary interfaces according to type promotion\n rules.\n","base.strided.nanmax":"\nbase.strided.nanmax( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values.\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the maximum value of strided array via a callback function,\n ignoring `NaN` values.\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Computes the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmean":"\nbase.strided.nanmean( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation.\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm.\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm.\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanmin":"\nbase.strided.nanmin( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanminabs":"\nbase.strided.nanminabs( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values.\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanminBy":"\nbase.strided.nanminBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values.\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the maximum value of a strided array according to a mask and\n ignoring `NaN` values.\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the minimum value of a strided array according to a mask and\n ignoring `NaN` values.\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the range of a strided array according to a mask and ignoring `NaN`\n values.\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanrange":"\nbase.strided.nanrange( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the range of a strided array, ignoring `NaN` values.\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the range of a strided array via a callback function, ignoring\n `NaN` values.\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n","base.strided.nanstdev":"\nbase.strided.nanstdev( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values.\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm.\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm.\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm.\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm.\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.nanvariance":"\nbase.strided.nanvariance( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values.\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm.\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n","base.strided.nullary":"\nbase.strided.nullary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a nullary callback and assigns results to elements in a strided\n output array.\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n","base.strided.offsetView":"\nbase.strided.offsetView( x:TypedArray, offset:integer )\n Returns a typed array view having the same data type as a provided input\n typed array and starting at a specified index offset.\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.quinary":"\nbase.strided.quinary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.range":"\nbase.strided.range( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the range of a strided array.\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the range of a strided array using alternative indexing semantics.\n","base.strided.rangeBy":"\nbase.strided.rangeBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the range of a strided array via a callback function.\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x:Complex128Array|Complex64Array, \n offset:integer )\n Returns a real-valued floating-point array view of a complex-valued\n floating-point array having the same precision.\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x:Complex64Array, offset:integer )\n Returns a Float32Array view of a Complex64Array.\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x:Complex128Array, offset:integer )\n Returns a Float64Array view of a Complex128Array.\n","base.strided.sabs":"\nbase.strided.sabs( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sabs2":"\nbase.strided.sabs2( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sapx":"\nbase.strided.sapx( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array.\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.sapxsum":"\nbase.strided.sapxsum( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum.\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm.\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation.\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n","base.strided.sasum":"\nbase.strided.sasum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.sasumpw":"\nbase.strided.sasumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n","base.strided.saxpy":"\nbase.strided.saxpy( N:integer, alpha:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n","base.strided.scbrt":"\nbase.strided.scbrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.sceil":"\nbase.strided.sceil( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.scopy":"\nbase.strided.scopy( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.scumax":"\nbase.strided.scumax( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.scumin":"\nbase.strided.scumin( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.scuminabs":"\nbase.strided.scuminabs( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.scusum":"\nbase.strided.scusum( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N:integer, sum:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.scusumors":"\nbase.strided.scusumors( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n","base.strided.scusumpw":"\nbase.strided.scusumpw( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sdot":"\nbase.strided.sdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the dot product of two single-precision floating-point vectors.\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.sdsdot":"\nbase.strided.sdsdot( N:integer, scalar:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N:integer, scalar:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n","base.strided.sdsmean":"\nbase.strided.sdsmean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignore `NaN` values and using extended accumulation.\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation.\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.sdssum":"\nbase.strided.sdssum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation.\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation.\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n","base.strided.sfill":"\nbase.strided.sfill( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Fills a single-precision floating-point strided array with a specified\n scalar value.\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n","base.strided.sfloor":"\nbase.strided.sfloor( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sinv":"\nbase.strided.sinv( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.smap":"\nbase.strided.smap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array.\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.smap2":"\nbase.strided.smap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n sy:integer, z:Float32Array, sz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, \n y:Float32Array, sy:integer, oy:integer, z:Float32Array, sz:integer, \n oz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.smax":"\nbase.strided.smax( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array.\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.smaxabs":"\nbase.strided.smaxabs( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smean":"\nbase.strided.smean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.smeankbn":"\nbase.strided.smeankbn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.smeanli":"\nbase.strided.smeanli( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n","base.strided.smeanors":"\nbase.strided.smeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.smeanpn":"\nbase.strided.smeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm.\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.smeanpw":"\nbase.strided.smeanpw( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n","base.strided.smeanwd":"\nbase.strided.smeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.smediansorted":"\nbase.strided.smediansorted( N:integer, x:Float32Array, strideX:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smidrange":"\nbase.strided.smidrange( N:integer, x:Float32Array, strideX:integer )\n Computes the mid-range of a single-precision floating-point strided array.\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.smin":"\nbase.strided.smin( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array.\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sminabs":"\nbase.strided.sminabs( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.sminsorted":"\nbase.strided.sminsorted( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smskabs":"\nbase.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskabs2":"\nbase.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.smskceil":"\nbase.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskfloor":"\nbase.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskinv":"\nbase.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smskmap":"\nbase.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, \n oy:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.smskmap2":"\nbase.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, \n fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.smskmax":"\nbase.strided.smskmax( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.smskmin":"\nbase.strided.smskmin( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.smskramp":"\nbase.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskrange":"\nbase.strided.smskrange( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.snanmax":"\nbase.strided.snanmax( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanmean":"\nbase.strided.snanmean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.snanmin":"\nbase.strided.snanmin( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanminabs":"\nbase.strided.snanminabs( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanrange":"\nbase.strided.snanrange( N:integer, x:Float32Array, strideX:integer )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanstdev":"\nbase.strided.snanstdev( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n","base.strided.snansum":"\nbase.strided.snansum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.snansumors":"\nbase.strided.snansumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.snansumpw":"\nbase.strided.snansumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.snanvariance":"\nbase.strided.snanvariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values.\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n","base.strided.snrm2":"\nbase.strided.snrm2( N:integer, x:Float32Array, stride:integer )\n Computes the L2-norm of a single-precision floating-point vector.\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n","base.strided.sramp":"\nbase.strided.sramp( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.srange":"\nbase.strided.srange( N:integer, x:Float32Array, strideX:integer )\n Computes the range of a single-precision floating-point strided array.\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n","base.strided.srev":"\nbase.strided.srev( N:integer, x:Float32Array, strideX:integer )\n Reverses a single-precision floating-point strided array in-place.\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n","base.strided.srsqrt":"\nbase.strided.srsqrt( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sscal":"\nbase.strided.sscal( N:integer, alpha:number, x:Float32Array, stride:integer )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha`.\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n","base.strided.ssorthp":"\nbase.strided.ssorthp( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using heapsort.\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n","base.strided.ssortins":"\nbase.strided.ssortins( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using insertion sort.\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n","base.strided.ssortsh":"\nbase.strided.ssortsh( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using Shellsort.\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n","base.strided.ssqrt":"\nbase.strided.ssqrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sstdev":"\nbase.strided.sstdev( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sstdevch":"\nbase.strided.sstdevch( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n","base.strided.ssum":"\nbase.strided.ssum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements.\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.ssumors":"\nbase.strided.ssumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.ssumpw":"\nbase.strided.ssumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.sswap":"\nbase.strided.sswap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Interchanges two single-precision floating-point vectors.\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n","base.strided.stdev":"\nbase.strided.stdev( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array.\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n","base.strided.stdevch":"\nbase.strided.stdevch( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n","base.strided.stdevpn":"\nbase.strided.stdevpn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n","base.strided.stdevtk":"\nbase.strided.stdevtk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n","base.strided.stdevwd":"\nbase.strided.stdevwd( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n","base.strided.stdevyc":"\nbase.strided.stdevyc( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer.\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n","base.strided.strunc":"\nbase.strided.strunc( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y`.\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.svariance":"\nbase.strided.svariance( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array.\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.svariancech":"\nbase.strided.svariancech( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.svariancepn":"\nbase.strided.svariancepn( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.svariancetk":"\nbase.strided.svariancetk( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.svariancewd":"\nbase.strided.svariancewd( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.ternary":"\nbase.strided.ternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.unary":"\nbase.strided.unary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function, clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function, clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike[, options:Object] )\n Generates a list of unary interface signatures from strided array data\n types.\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table:Object, signatures:ArrayLike )\n Assigns callbacks to unary interfaces according to type promotion rules.\n","base.strided.variance":"\nbase.strided.variance( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array.\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using alternative indexing\n semantics.\n","base.strided.variancech":"\nbase.strided.variancech( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n","base.strided.variancepn":"\nbase.strided.variancepn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a two-pass algorithm.\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n","base.strided.variancetk":"\nbase.strided.variancetk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n","base.strided.variancewd":"\nbase.strided.variancewd( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using Welford's algorithm.\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n","base.strided.varianceyc":"\nbase.strided.varianceyc( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer.\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n","base.strided.zmap":"\nbase.strided.zmap( N:integer, x:Complex128Array, strideX:integer, \n y:Complex128Array, strideY:integer, fcn:Function )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array.\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N:integer, x:Complex128Array, strideX:integer, \n offsetX:integer, y:Complex128Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n","base.str2multislice":"\nbase.str2multislice( str:string )\n Parses a string-serialized MultiSlice object.\n","base.str2slice":"\nbase.str2slice( str:string )\n Parses a string-serialized Slice object.\n","base.sub":"\nbase.sub( x:number, y:number )\n Subtracts two double-precision floating-point numbers `x` and `y`.\n","base.subf":"\nbase.subf( x:number, y:number )\n Subtracts two single-precision floating-point numbers `x` and `y`.\n","base.sumSeries":"\nbase.sumSeries( generator:Function[, options:Object] )\n Sum the elements of the series given by the supplied function.\n","base.tan":"\nbase.tan( x:number )\n Computes the tangent of a number.\n","base.tand":"\nbase.tand( x:number )\n Computes the tangent of an angle measured in degrees.\n","base.tanh":"\nbase.tanh( x:number )\n Computes the hyperbolic tangent of a double-precision floating-point number.\n","base.toBinaryString":"\nbase.toBinaryString( x:number )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x:float )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x:integer )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x:integer )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x:integer )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n","base.toWordf":"\nbase.toWordf( x:float )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n","base.toWords":"\nbase.toWords( x:number )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.toWords.assign":"\nbase.toWords.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n","base.transpose":"\nbase.transpose( x:ndarray, writable:boolean )\n Transposes a matrix (or a stack of matrices).\n","base.tribonacci":"\nbase.tribonacci( n:integer )\n Computes the nth Tribonacci number.\n","base.trigamma":"\nbase.trigamma( x:number )\n Evaluates the trigamma function.\n","base.trim":"\nbase.trim( str:string )\n Trims whitespace from the beginning and end of a `string`.\n","base.trunc":"\nbase.trunc( x:number )\n Rounds a double-precision floating-point number toward zero.\n","base.trunc2":"\nbase.trunc2( x:number )\n Rounds a numeric value to the nearest power of two toward zero.\n","base.trunc10":"\nbase.trunc10( x:number )\n Rounds a numeric value to the nearest power of ten toward zero.\n","base.truncateMiddle":"\nbase.truncateMiddle( str:string, len:integer, seq:string )\n Truncates the middle UTF-16 code units of a string to return a string\n having a specified length.\n","base.truncb":"\nbase.truncb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n","base.truncf":"\nbase.truncf( x:number )\n Rounds a single-precision floating-point number toward zero.\n","base.truncn":"\nbase.truncn( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n","base.truncsd":"\nbase.truncsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x:integer )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n","base.umul":"\nbase.umul( x:integer, y:integer )\n Multiples two unsigned 32-bit integers.\n","base.umuldw":"\nbase.umuldw( a:integer, b:integer )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n","base.umuldw.assign":"\nbase.umuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n","base.uncapitalize":"\nbase.uncapitalize( str:string )\n Lowercases the first character of a string.\n","base.uppercase":"\nbase.uppercase( str:string )\n Converts a string to uppercase.\n","base.vercos":"\nbase.vercos( x:number )\n Computes the versed cosine.\n","base.versin":"\nbase.versin( x:number )\n Computes the versed sine.\n","base.wrap":"\nbase.wrap( v:number, min:number, max:number )\n Wraps a value to the half-open interval `[min,max)`.\n","base.xlog1py":"\nbase.xlog1py( x:number, y:number )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n","base.xlogy":"\nbase.xlogy( x:number, y:number )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n","base.zeta":"\nbase.zeta( s:number )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and other characteristics.\n","bifurcate":"\nbifurcate( collection:Array|TypedArray|Object, [options:Object,] \n filter:Array|TypedArray|Object )\n Splits values into two groups.\n","bifurcateBy":"\nbifurcateBy( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateByAsync":"\nbifurcateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which splits values into two groups according to an\n predicate function.\n","bifurcateIn":"\nbifurcateIn( obj:Object|Array|TypedArray, [options:Object,] predicate:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateOwn":"\nbifurcateOwn( obj:Object|Array|TypedArray, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n","BigInt":"\nBigInt( value:integer|string )\n Returns a BigInt.\n","binomialTest":"\nbinomialTest( x:(number|Array[, n:Array][, options:Object] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n","Boolean":"\nBoolean( value:any )\n Returns a boolean.\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n","BooleanArray":"\nBooleanArray()\n A Boolean array.\n\nBooleanArray( length:integer )\n Creates a boolean array having a specified length.\n\nBooleanArray( booleanarray:BooleanArray )\n Creates a boolean array from another boolean array.\n\nBooleanArray( typedarray:TypedArray )\n Creates a boolean array from a typed array.\n\nBooleanArray( obj:Object )\n Creates a boolean array from an array-like object or iterable.\n\nBooleanArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a boolean array view of an ArrayBuffer.\n","BooleanArray.from":"\nBooleanArray.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new boolean array from an array-like object or an iterable.\n","BooleanArray.of":"\nBooleanArray.of( element0:bool[, element1:bool[, ...elementN:bool]] )\n Creates a new boolean array from a variable number of arguments.\n","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","BooleanArray.name":"\nBooleanArray.name\n Typed array constructor name.\n","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n The number of array elements.\n","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value:boolean[, start:integer[, end:integer]] )\n Returns a modified typed array filled with a fill value.\n","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement:boolean[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement:boolean[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement:boolean[, fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v:bool|BooleanArray|ArrayLikeObject[, i:integer] )\n Sets one or more array elements.\n","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether at least one element passes a test.\n","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction:Function] )\n Sorts an array in-place.\n","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction:Function] )\n Returns a new typed array containing the elements in sorted order.\n","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index:integer, value:boolean )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n","broadcastArray":"\nbroadcastArray( x:ndarray, shape:ArrayLikeObject )\n Broadcasts an ndarray to a specified shape.\n","broadcastArrays":"\nbroadcastArrays( ...arrays:ndarray|ArrayLikeObject )\n Broadcasts ndarrays to a common shape.\n","Buffer":"\nBuffer\n\nBuffer( size:integer )\n Allocates a buffer having a specified number of bytes.\n\nBuffer( buffer:Buffer )\n Copies buffer data to a new Buffer instance.\n\nBuffer( array:Array )\n Allocates a buffer using an array of octets.\n\nBuffer( str:string[, encoding:string] )\n Allocates a buffer containing a provided string.\n","buffer2json":"\nbuffer2json( buffer:Buffer )\n Returns a JSON representation of a buffer.\n","BYTE_ORDER":"\nBYTE_ORDER\n Platform byte order.\n","camelcase":"\ncamelcase( str:string )\n Converts a string to camel case.\n","capitalize":"\ncapitalize( str:string )\n Capitalizes the first character in a string.\n","capitalizeKeys":"\ncapitalizeKeys( obj:Object )\n Converts the first letter of each object key to uppercase.\n","CATALAN":"\nCATALAN\n Catalan's constant.\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n Returns US birth data from 1969 to 1988, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n Returns US birth data from 1994 to 2003, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n the Center for Disease Control and Prevention's National Center for Health\n Statistics.\n","chdir":"\nchdir( path:string )\n Changes the current working directory.\n","chi2gof":"\nchi2gof( x:ndarray|Array|TypedArray, y:ndarray|Array|TypedArray|string[, \n ...args:number][, options:Object] )\n Performs a chi-square goodness-of-fit test.\n","chi2test":"\nchi2test( x:ndarray|Array[, options:Object] )\n Performs a chi-square independence test.\n","circarray2iterator":"\ncircarray2iterator( src:ArrayLikeObject[, options:Object][, mapFcn:Function[, \n thisArg:any]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n","circularArrayStream":"\ncircularArrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n","CircularBuffer":"\nCircularBuffer( buffer:integer|ArrayLike )\n Circular buffer constructor.\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n Clears a buffer.\n","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters:integer] )\n Returns an iterator for iterating over a circular buffer.\n","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value:any )\n Adds a value to a circular buffer.\n","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n","close":"\nclose( fd:integer, clbk:Function )\n Asynchronously closes a file descriptor, so that the file descriptor no\n longer refers to any file and may be reused.\n","close.sync":"\nclose.sync( fd:integer )\n Synchronously closes a file descriptor.\n","CMUDICT":"\nCMUDICT( [options:Object] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n","codePointAt":"\ncodePointAt( str:string, idx:integer[, backward:boolean] )\n Returns a Unicode code point from a string at a specified position.\n","commonKeys":"\ncommonKeys( obj1:any, obj2:any[, ...obj:any] )\n Returns the common own property names of two or more objects.\n","commonKeysIn":"\ncommonKeysIn( obj1:any, obj2:any[, ...obj:any] )\n Returns the common own and inherited property names of two or more objects.\n","complex":"\ncomplex( real:number, imag:number[, dtype:string] )\n Creates a complex number.\n","Complex64":"\nComplex64( real:number, imag:number )\n 64-bit complex number constructor.\n","Complex64.name":"\nComplex64.name\n Constructor name.\n","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n Canonical single-precision complex floating-point NaN.\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n Single-precision complex floating-point zero.\n","Complex64Array":"\nComplex64Array()\n A 64-bit complex number array.\n\nComplex64Array( length:integer )\n Creates a 64-bit complex number array having a specified length.\n\nComplex64Array( complexarray:Complex64Array )\n Creates a 64-bit complex number array from another complex number array.\n\nComplex64Array( typedarray:TypedArray )\n Creates a 64-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\nComplex64Array( obj:Object )\n Creates a 64-bit complex number array from an array-like object or iterable.\n\nComplex64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a 64-bit complex number array view of an ArrayBuffer.\n","Complex64Array.from":"\nComplex64Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n","Complex64Array.of":"\nComplex64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","Complex64Array.name":"\nComplex64Array.name\n Typed array constructor name.\n","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n The number of array elements.\n","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value:Complex64[, start:integer[, end:integer]] )\n Returns a modified typed array filled with a fill value.\n","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement:Complex64[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement:Complex64[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement:Complex64[, \n fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z:Complex64|Complex64Array|ArrayLikeObject[, \n i:integer] )\n Sets one or more array elements.\n","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction:Function )\n Sorts an array in-place.\n","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn:Function )\n Returns a new typed array containing the elements in sorted order.\n","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n","Complex128":"\nComplex128( real:number, imag:number )\n 128-bit complex number constructor.\n","Complex128.name":"\nComplex128.name\n Constructor name.\n","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n","Complex128Array":"\nComplex128Array()\n A 128-bit complex number array.\n\nComplex128Array( length:integer )\n Creates a 128-bit complex number array having a specified length.\n\nComplex128Array( complexarray:Complex128Array )\n Creates a 64-bit complex number array from another complex number array.\n\nComplex128Array( typedarray:TypedArray )\n Creates a 128-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\nComplex128Array( obj:Object )\n Creates a 128-bit complex number array from an array-like object or \n iterable.\n\nComplex128Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a 128-bit complex number array view of an ArrayBuffer.\n","Complex128Array.from":"\nComplex128Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n","Complex128Array.of":"\nComplex128Array.of( element0:number|ComplexLike[, \n element1:number |ComplexLike[, ...elementN:number|ComplexLike]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","Complex128Array.name":"\nComplex128Array.name\n Typed array constructor name.\n","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n The number of array elements.\n","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value:Complex128[, start:integer[, \n end:integer]] )\n Returns a modified typed array filled with a fill value.\n","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement:Complex128[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement:Complex128[, \n fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement:Complex128[, \n fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z:Complex128|Complex128Array|ArrayLikeObject[, \n i:integer] )\n Sets one or more array elements.\n","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction:Function )\n Sorts an array in-place.\n","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn:Function )\n Returns a new typed array containing the elements in sorted order.\n","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n","complexarray":"\ncomplexarray( [dtype:string] )\n Creates a complex typed array.\n\ncomplexarray( length:integer[, dtype:string] )\n Returns a complex number typed array having a specified length.\n\ncomplexarray( complexarray:ComplexArray[, dtype:string] )\n Creates a complex number typed array from another complex number typed\n array.\n\ncomplexarray( obj:Object[, dtype:string] )\n Creates a complex number typed array from an array-like object or iterable.\n\ncomplexarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a complex number typed array view of an ArrayBuffer.\n","complexarrayCtors":"\ncomplexarrayCtors( dtype:string )\n Returns a complex typed array constructor.\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n","complexCtors":"\ncomplexCtors( dtype:string )\n Returns a complex number constructor.\n","complexDataType":"\ncomplexDataType( value:any )\n Returns the data type of a complex number object.\n","complexDataTypes":"\ncomplexDataTypes()\n Returns a list of complex number data types.\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1:string, dtype2:string] )\n Returns the complex number data type with the smallest size and closest\n \"kind\" to which data types can be safely cast.\n","compose":"\ncompose( ...f:Function )\n Function composition.\n","composeAsync":"\ncomposeAsync( ...f:Function )\n Function composition.\n","configdir":"\nconfigdir( [p:string] )\n Returns a directory for user-specific configuration files.\n","conj":"\nconj( z:Complex128 )\n Returns the complex conjugate of a double-precision complex floating-point\n number.\n","conjf":"\nconjf( z:Complex64 )\n Returns the complex conjugate of a single-precision complex floating-point\n number.\n","constantcase":"\nconstantcase( str:string )\n Converts a string to constant case.\n","constantFunction":"\nconstantFunction( val:any )\n Creates a function which always returns the same value.\n","constantStream":"\nconstantStream( value:string|Buffer|Uint8Array|any[, options:Object] )\n Returns a readable stream which always streams the same value.\n","constantStream.factory":"\nconstantStream.factory( [value:string|Buffer|Uint8Array|any, ][options:Object] )\n Returns a function for creating readable streams which always stream the\n same value.\n","constantStream.objectMode":"\nconstantStream.objectMode( value:any[, options:Object] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n","constructorName":"\nconstructorName( val:any )\n Determines the name of a value's constructor.\n","contains":"\ncontains( value:ArrayLike, searchValue:any[, position:integer] )\n Tests if an array-like value contains a search value.\n","convertArray":"\nconvertArray( arr:ArrayLikeObject, dtype:string )\n Converts an input array to an array of a different data type.\n","convertArraySame":"\nconvertArraySame( x:ArrayLikeObject, y:Array|TypedArray )\n Converts an input array to the same data type as a second input array.\n","convertPath":"\nconvertPath( from:string, to:string )\n Converts between POSIX and Windows paths.\n","copy":"\ncopy( value:any[, level:integer] )\n Copy or deep clone a value to an arbitrary depth.\n","copyBuffer":"\ncopyBuffer( buffer:Buffer )\n Copies buffer data to a new Buffer instance.\n","countBy":"\ncountBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Groups values according to an indicator function and returns group counts.\n","countByAsync":"\ncountByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Groups values according to an indicator function and returns group counts.\n","countByAsync.factory":"\ncountByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n","currentYear":"\ncurrentYear()\n Returns the current year.\n","curry":"\ncurry( fcn:Function[, arity:integer][, thisArg:any] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n","curryRight":"\ncurryRight( fcn:Function[, arity:integer][, thisArg:any] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n","cwd":"\ncwd()\n Returns the current working directory.\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar American-English words.\n","datasets":"\ndatasets( name:string[, options:Object] )\n Returns a dataset.\n","DataType":"\nDataType( value:any[, options:Object] )\n Data type constructor.\n","DataType.name":"\nDataType.name\n Constructor name.\n","DataType.prototype.alignment":"\nDataType.prototype.alignment\n Alignment (in bytes) for the data type.\n","DataType.prototype.byteLength":"\nDataType.prototype.byteLength\n Size (in bytes) of the data type.\n","DataType.prototype.byteOrder":"\nDataType.prototype.byteOrder\n Data type byte order.\n","DataType.prototype.char":"\nDataType.prototype.char\n Single letter character abbreviation for the data type.\n","DataType.prototype.description":"\nDataType.prototype.description\n Data type description.\n","DataType.prototype.enum":"\nDataType.prototype.enum\n Enumeration constant for the data type.\n","DataType.prototype.value":"\nDataType.prototype.value\n Raw (original) data type value.\n","DataType.prototype.toJSON":"\nDataType.prototype.toJSON()\n Serializes a data type instance as a JSON object.\n","DataType.prototype.toString":"\nDataType.prototype.toString()\n Serializes a data type instance to a string.\n","DataType.prototype.valueOf":"\nDataType.prototype.valueOf()\n Converts a data type instance to a primitive.\n","DataView":"\nDataView( buffer:ArrayBuffer|SharedArrayBuffer[, byteOffset:integer[, \n byteLength:integer]] )\n Returns a data view representing a provided array buffer.\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n Read-only property which returns the underlying array buffer.\n","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n","datespace":"\ndatespace( start:number, stop:number[, length:integer][ , options:Object] )\n Generates an array of linearly spaced dates.\n","dayOfQuarter":"\ndayOfQuarter( [month:string|integer|Date[, day:integer, year:integer]] )\n Returns the day of the quarter.\n","dayOfYear":"\ndayOfYear( [month:string|integer|Date[, day:integer, year:integer]] )\n Returns the day of the year.\n","daysInMonth":"\ndaysInMonth( [month:string|integer|Date[, year:integer]] )\n Returns the number of days in a month.\n","daysInYear":"\ndaysInYear( [value:integer|Date] )\n Returns the number of days in a year according to the Gregorian calendar.\n","ddot":"\nddot( x:ndarray, y:ndarray[, dim:integer] )\n Computes the dot product of two double-precision floating-point vectors.\n","debugSinkStream":"\ndebugSinkStream( [options:Object,] [clbk:Function] )\n Returns a writable stream for debugging stream pipelines.\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options:Object] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options:Object,] [clbk:Function] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n","debugStream":"\ndebugStream( [options:Object,] [clbk:Function] )\n Returns a transform stream for debugging stream pipelines.\n","debugStream.factory":"\ndebugStream.factory( [options:Object] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n","debugStream.objectMode":"\ndebugStream.objectMode( [options:Object,] [clbk:Function] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n","decorateAfter":"\ndecorateAfter( fcn:Function, arity:integer, after:Function[, thisArg:any] )\n Decorates a provided function such that the function's return value is\n provided as an argument to another function.\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn:Function, arity:integer, after:Function[, \n thisArg:any] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n","deepEqual":"\ndeepEqual( a:any, b:any )\n Tests for deep equality between two values.\n","deepGet":"\ndeepGet( obj:ObjectLike, path:string|Array[, options:Object] )\n Returns a nested property value.\n","deepGet.factory":"\ndeepGet.factory( path:string|Array[, options:Object] )\n Creates a reusable deep get function.\n","deepHasOwnProp":"\ndeepHasOwnProp( value:any, path:string|Array[, options:Object] )\n Returns a boolean indicating whether an object contains a nested key path.\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path:string|Array[, options:Object] )\n Returns a function which tests whether an object contains a nested key path.\n","deepHasProp":"\ndeepHasProp( value:any, path:string|Array[, options:Object] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n","deepHasProp.factory":"\ndeepHasProp.factory( path:string|Array[, options:Object] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n","deepPluck":"\ndeepPluck( arr:Array, path:string|Array[, options:Object] )\n Extracts a nested property value from each element of an object array.\n","deepSet":"\ndeepSet( obj:ObjectLike, path:string|Array, value:any[, options:Object] )\n Sets a nested property value.\n","deepSet.factory":"\ndeepSet.factory( path:string|Array[, options:Object] )\n Creates a reusable deep set function.\n","defineMemoizedProperty":"\ndefineMemoizedProperty( obj:Object, prop:string|symbol, descriptor:Object )\n Defines a memoized object property.\n","defineProperties":"\ndefineProperties( obj:Object, properties:Object )\n Defines (and/or modifies) object properties.\n","defineProperty":"\ndefineProperty( obj:Object, prop:string|symbol, descriptor:Object )\n Defines (or modifies) an object property.\n","dirname":"\ndirname( path:string )\n Returns a directory name.\n","dotcase":"\ndotcase( str:string )\n Converts a string to dot case.\n","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n","doUntil":"\ndoUntil( fcn:Function, predicate:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","doUntilAsync":"\ndoUntilAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","doUntilEach":"\ndoUntilEach( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n","doUntilEachRight":"\ndoUntilEachRight( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","doWhile":"\ndoWhile( fcn:Function, predicate:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","doWhileAsync":"\ndoWhileAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","doWhileEach":"\ndoWhileEach( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection.\n","doWhileEachRight":"\ndoWhileEachRight( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","dswap":"\ndswap( x:ndarray, y:ndarray[, dim:integer] )\n Interchanges two double-precision floating-point vectors.\n","E":"\nE\n Euler's number.\n","EMOJI":"\nEMOJI()\n Returns an emoji database.\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n Returns an object mapping emoji codes to pictographs.\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n Returns an object mapping emoji pictographs to codes.\n","emptyStream":"\nemptyStream( [options:Object] )\n Returns an \"empty\" readable stream.\n","emptyStream.factory":"\nemptyStream.factory( [options:Object] )\n Returns a function for creating empty readable streams.\n","emptyStream.objectMode":"\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n","endsWith":"\nendsWith( str:string, search:string[, len:integer] )\n Tests if a string ends with the characters of another string.\n","enumerableProperties":"\nenumerableProperties( value:any )\n Returns an array of an object's own enumerable property names and symbols.\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value:any )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value:any )\n Returns an array of an object's own enumerable symbol properties.\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n","ENV":"\nENV\n An object containing the user environment.\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n","error2json":"\nerror2json( error:Error )\n Returns a JSON representation of an error object.\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n","every":"\nevery( collection:Array|TypedArray|Object )\n Tests whether all elements in a collection are truthy.\n","everyBy":"\neveryBy( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n","everyByAsync":"\neveryByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n","everyByAsync.factory":"\neveryByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n","everyByRight":"\neveryByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n","everyByRightAsync":"\neveryByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n","everyInBy":"\neveryInBy( object:Object, predicate:Function[, thisArg:any ] )\n Test whether all properties (own and inherited) of an object pass a\n test implemented by a predicate function.\n","everyOwnBy":"\neveryOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every own property of an object pass a test implemented by a\n predicate function.\n","evil":"\nevil( str:string )\n Alias for `eval` global.\n","EXEC_PATH":"\nEXEC_PATH\n Absolute pathname of the executable which started the current Node.js\n process.\n","exists":"\nexists( path:string|Buffer, clbk:Function )\n Asynchronously tests whether a path exists on the filesystem.\n","exists.sync":"\nexists.sync( path:string|Buffer )\n Synchronously tests whether a path exists on the filesystem.\n","expandAcronyms":"\nexpandAcronyms( str:string )\n Expands acronyms in a string.\n","expandContractions":"\nexpandContractions( str:string )\n Expands all contractions to their formal equivalents.\n","extname":"\nextname( filename:string )\n Returns a filename extension.\n","FancyArray":"\nFancyArray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string[, options:Object] )\n Returns a FancyArray instance.\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","FancyArray.prototype.data":"\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n Underlying data type.\n","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","FancyArray.prototype.length":"\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n Number of dimensions.\n","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","FancyArray.prototype.order":"\nFancyArray.prototype.order\n Array order.\n","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n Array shape.\n","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n","fastmath.abs":"\nfastmath.abs( x:number )\n Computes an absolute value.\n","fastmath.acosh":"\nfastmath.acosh( x:number )\n Computes the hyperbolic arccosine of a number.\n","fastmath.ampbm":"\nfastmath.ampbm( x:number, y:number )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha:number, beta:number, [nonnegative:boolean[, \n ints:boolean]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n","fastmath.asinh":"\nfastmath.asinh( x:number )\n Computes the hyperbolic arcsine of a number.\n","fastmath.atanh":"\nfastmath.atanh( x:number )\n Computes the hyperbolic arctangent of a number.\n","fastmath.hypot":"\nfastmath.hypot( x:number, y:number )\n Computes the hypotenuse.\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x:uinteger )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n","fastmath.max":"\nfastmath.max( x:number, y:number )\n Returns the maximum value.\n","fastmath.min":"\nfastmath.min( x:number, y:number )\n Returns the minimum value.\n","fastmath.powint":"\nfastmath.powint( x:number, y:integer )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x:uinteger )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n","filledarray":"\nfilledarray( [dtype:string] )\n Creates a filled array.\n\nfilledarray( value:any, length:integer[, dtype:string] )\n Returns a filled array having a specified length.\n\nfilledarray( value:any, array:ArrayLikeObject[, dtype:string] )\n Creates a filled array from another array (or array-like object).\n\nfilledarray( value:any, iterable:Iterable[, dtype:string] )\n Creates a filled array from an iterable.\n\nfilledarray( value:any, buffer:ArrayBuffer[, byteOffset:integer[, \n length:integer]][, dtype:string] )\n Returns a filled typed array view of an ArrayBuffer.\n","filledarrayBy":"\nfilledarrayBy( [dtype:string] )\n Creates a filled array.\n\nfilledarrayBy( length:integer[, dtype:string], clbk:Function[, thisArg:any] )\n Returns a filled array according to a provided callback function and having\n a specified length.\n\nfilledarrayBy( array:ArrayLikeObject[, dtype:string], clbk:Function[, \n thisArg:any] )\n Creates a filled array from another array (or array-like object) according\n to a provided callback function.\n\nfilledarrayBy( iterable:Iterable[, dtype:string], clbk:Function[, thisArg:any] )\n Creates a filled array from an iterable according to a provided callback\n function.\n\nfilledarrayBy( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string], clbk:Function[, thisArg:any] )\n Returns a filled typed array view of an ArrayBuffer according to a provided\n callback function.\n","filterArguments":"\nfilterArguments( fcn:Function, predicate:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n","find":"\nfind( arr:Array|TypedArray|string, [options:Object,] clbk:Function )\n Finds elements in an array-like object that satisfy a test condition.\n","firstChar":"\nfirstChar( str:string[, n:integer][, options:Object] )\n Returns the first character(s) of a string.\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n Returns FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n","flattenArray":"\nflattenArray( arr:ArrayLikeObject[, options:Object] )\n Flattens an array.\n","flattenArray.factory":"\nflattenArray.factory( dims:ArrayLike[, options:Object] )\n Returns a function for flattening arrays having specified dimensions.\n","flattenObject":"\nflattenObject( obj:ObjectLike[, options:Object] )\n Flattens an object.\n","flattenObject.factory":"\nflattenObject.factory( [options:Object] )\n Returns a function to flatten an object.\n","flignerTest":"\nflignerTest( ...x:Array[, options:Object] )\n Computes the Fligner-Killeen test for equal variances.\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n Platform float word order.\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n Mask for excluding the sign bit of a single-precision floating-point number.\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n","FLOAT32_E":"\nFLOAT32_E\n Euler's number.\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n Mask for the exponent of a single-precision floating-point number.\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n One fourth times the mathematical constant `π`.\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n One half times the natural logarithm of 2 as a single-precision\n floating-point number.\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n One half times the mathematical constant `π`.\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n Natural logarithm of `1/2` as a single-precision floating-point number.\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n Natural logarithm of the mathematical constant `π` as a single-precision\n floating-point number.\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n Natural logarithm of `10` as a single-precision floating-point number.\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n Natural logarithm of `2` as a single-precision floating-point number.\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a single-precision floating-point\n number.\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a single-precision floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal single-precision floating-point\n number.\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in single-precision floating-point\n format.\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n Maximum safe nth factorial when stored in single-precision floating-\n point format.\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in single-precision floating-\n point format.\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in single-precision floating-point\n format.\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized single-precision\n floating-point number.\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normal single-precision floating-\n point number.\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal single-precision floating-\n point number.\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n","FLOAT32_NAN":"\nFLOAT32_NAN\n Single-precision floating-point NaN.\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n","FLOAT32_PHI":"\nFLOAT32_PHI\n Golden ratio.\n","FLOAT32_PI":"\nFLOAT32_PI\n The mathematical constant `π`.\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n Mask for the sign bit of a single-precision floating-point number.\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n Mask for the significand of a single-precision floating-point number.\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n Square root of `1/2` as a single-precision floating-point number.\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n Square root of `π` divided by `2` as a single-precision \n floating-point number.\n","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n Square root of the golden ratio as a single-precision floating-point number.\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n Square root of the mathematical constant `π` as a single-precision\n floating-point number.\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n Square root of `3` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n Square root of `2` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n Square root of the mathematical constant `π` times `2` as a single-precision\n floating-point number.\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n The mathematical constant `π` times `2`.\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\nFloat32Array( length:integer )\n Returns a typed array having a specified length.\n\nFloat32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nFloat32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nFloat32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Float32Array.from":"\nFloat32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Float32Array.of":"\nFloat32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float32Array.name":"\nFloat32Array.name\n Typed array constructor name.\n","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n High word mask for excluding the sign bit of a double-precision floating-\n point number.\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n High word mask for the sign bit of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\nFloat64Array( length:integer )\n Returns a typed array having a specified length.\n\nFloat64Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nFloat64Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nFloat64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Float64Array.from":"\nFloat64Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Float64Array.of":"\nFloat64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float64Array.name":"\nFloat64Array.name\n Typed array constructor name.\n","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","forEach":"\nforEach( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection.\n","forEachAsync":"\nforEachAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection.\n","forEachAsync.factory":"\nforEachAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection.\n","forEachChar":"\nforEachChar( str:string, [options:Object,] clbk:Function[, thisArg:any] )\n Invokes a function for each character in a string.\n","forEachRight":"\nforEachRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n","forEachRightAsync":"\nforEachRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n","forIn":"\nforIn( obj:Object, fcn:Function[, thisArg:any] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n","format":"\nformat( str:string, ...args:any )\n Insert supplied variable values into a format string.\n","forOwn":"\nforOwn( obj:Object, fcn:Function[, thisArg:any] )\n Invokes a function for each own enumerable property of an object.\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n","fromCodePoint":"\nfromCodePoint( ...pt:integer )\n Creates a string from a sequence of Unicode code points.\n","Function":"\nFunction( [...argNames:any,] body:string )\n Returns a Function object.\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg:any, args:Array )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n","Function.prototype.call":"\nFunction.prototype.call( thisArg:any, ...args:any )\n Calls a function with a given `this` value and arguments provided\n individually.\n","Function.prototype.bind":"\nFunction.prototype.bind( thisArg:any, ...args:any )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n","Function.prototype.toString":"\nFunction.prototype.toString()\n Returns a string representation of the function.\n","Function.prototype.length":"\nFunction.prototype.length\n The number of arguments expected by the function.\n","Function.prototype.name":"\nFunction.prototype.name\n The name of the function.\n","Function.prototype.prototype":"\nFunction.prototype.prototype\n The prototype of the function.\n","function2string":"\nfunction2string( fcn:Function )\n Returns a string representing the source code of a provided function.\n","functionName":"\nfunctionName( fcn:Function )\n Returns the name of a function.\n","functionSequence":"\nfunctionSequence( ...fcn:Function )\n Returns a pipeline function.\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn:Function )\n Returns a pipeline function.\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n","gdot":"\ngdot( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Computes the dot product of two vectors.\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n","getGlobal":"\ngetGlobal( [codegen:boolean] )\n Returns the global object.\n","getPrototypeOf":"\ngetPrototypeOf( value:any )\n Returns the prototype of a provided object.\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src:string[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over each grapheme cluster in a string.\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src:string[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over each grapheme\n cluster in a string.\n","group":"\ngroup( collection:Array|TypedArray|Object, [options:Object,] \n groups:Array|TypedArray|Object )\n Groups values as arrays associated with distinct keys.\n","groupBy":"\ngroupBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Groups values according to an indicator function.\n","groupByAsync":"\ngroupByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Groups values according to an indicator function.\n","groupByAsync.factory":"\ngroupByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which groups values according to an indicator function.\n","groupIn":"\ngroupIn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n Group values according to an indicator function.\n","groupOwn":"\ngroupOwn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n Group values according to an indicator function.\n","gswap":"\ngswap( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Interchanges two vectors.\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n Tests whether an environment supports native arrow functions.\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n","hasAtobSupport":"\nhasAtobSupport()\n Tests for native `atob` support.\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n Tests for native `BigInt64Array` support.\n","hasBigIntSupport":"\nhasBigIntSupport()\n Tests for native `BigInt` support.\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n Tests for native `BigUint64Array` support.\n","hasBtoaSupport":"\nhasBtoaSupport()\n Tests for native `btoa` support.\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n","hasDataViewSupport":"\nhasDataViewSupport()\n Tests for native `DataView` support.\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n Tests for `globalThis` support.\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n","hasOwnProp":"\nhasOwnProp( value:any, property:any )\n Tests if an object has a specified property.\n","hasProp":"\nhasProp( value:any, property:any )\n Tests if an object has a specified property, either own or inherited.\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `Symbol.toStringTag` support.\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str:string, pos:integer )\n Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n","headercase":"\nheadercase( str:string )\n Converts a string to HTTP header case.\n","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n","hoursInMonth":"\nhoursInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of hours in a month.\n","hoursInYear":"\nhoursInYear( [value:integer|Date] )\n Returns the number of hours in a year according to the Gregorian calendar.\n","httpServerFactory":"\nhttpServerFactory( [options:Object,] [requestListener:Function] )\n Returns a function to create an HTTP server.\n","identity":"\nidentity( x:any )\n Identity function.\n","ifelse":"\nifelse( bool:boolean, x:any, y:any )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n","ifelseAsync":"\nifelseAsync( predicate:Function, x:any, y:any, done:Function )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n","ifthen":"\nifthen( bool:boolean, x:Function, y:Function )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n","ifthenAsync":"\nifthenAsync( predicate:Function, x:Function, y:Function, done:Function )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n","imag":"\nimag( z:Complex128 )\n Returns the imaginary component of a double-precision complex floating-point\n number.\n","imagf":"\nimagf( z:Complex64 )\n Returns the imaginary component of a single-precision complex floating-point\n number.\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium oreophilum*.\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n","incrapcorr":"\nincrapcorr( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n","incrBinaryClassification":"\nincrBinaryClassification( N:integer[, options:Object] )\n Returns an accumulator function which incrementally performs binary\n classification using stochastic gradient descent (SGD).\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n","incrcovariance":"\nincrcovariance( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n","incrcovmat":"\nincrcovmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n","incrcv":"\nincrcv( [mean:number] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n","increwmean":"\nincrewmean( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n","increwstdev":"\nincrewstdev( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n","increwvariance":"\nincrewvariance( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n","incrgrubbs":"\nincrgrubbs( [options:Object] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n","incrkmeans":"\nincrkmeans( k:integer|ndarray[, ndims:integer][, options:Object] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n","incrmapcorr":"\nincrmapcorr( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n","incrmcovariance":"\nincrmcovariance( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n","incrmcv":"\nincrmcv( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n","incrmeanstdev":"\nincrmeanstdev( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n","incrmeanvar":"\nincrmeanvar( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n","incrmgmean":"\nincrmgmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n","incrmgrubbs":"\nincrmgrubbs( W:integer[, options:Object] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n","incrmhmean":"\nincrmhmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n","incrminmax":"\nincrminmax( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n","incrminmaxabs":"\nincrminmaxabs( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n","incrmmaape":"\nincrmmaape( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n","incrmmae":"\nincrmmae( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n","incrmmape":"\nincrmmape( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n","incrmmax":"\nincrmmax( W:integer )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n","incrmmaxabs":"\nincrmmaxabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n","incrmmda":"\nincrmmda( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n","incrmme":"\nincrmme( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n","incrmmean":"\nincrmmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n","incrmmeanabs":"\nincrmmeanabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n","incrmmeanabs2":"\nincrmmeanabs2( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n","incrmmeanstdev":"\nincrmmeanstdev( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n","incrmmeanvar":"\nincrmmeanvar( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n","incrmmidrange":"\nincrmmidrange( W:integer )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n","incrmmin":"\nincrmmin( W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n","incrmminabs":"\nincrmminabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n","incrmminmax":"\nincrmminmax( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n","incrmminmaxabs":"\nincrmminmaxabs( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n","incrmmpe":"\nincrmmpe( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n","incrmmse":"\nincrmmse( W:integer )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n","incrmpcorr":"\nincrmpcorr( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n","incrmpcorr2":"\nincrmpcorr2( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n","incrmpcorrdist":"\nincrmpcorrdist( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n","incrmprod":"\nincrmprod( W:integer )\n Returns an accumulator function which incrementally computes a moving\n product.\n","incrmrange":"\nincrmrange( W:integer )\n Returns an accumulator function which incrementally computes a moving range.\n","incrmrmse":"\nincrmrmse( W:integer )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n","incrmrss":"\nincrmrss( W:integer )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n","incrmstdev":"\nincrmstdev( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n","incrmsum":"\nincrmsum( W:integer )\n Returns an accumulator function which incrementally computes a moving sum.\n","incrmsumabs":"\nincrmsumabs( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n","incrmsumabs2":"\nincrmsumabs2( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n","incrmsummary":"\nincrmsummary( W:integer )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n","incrmsumprod":"\nincrmsumprod( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n","incrmvariance":"\nincrmvariance( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n","incrmvmr":"\nincrmvmr( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n","incrnancount":"\nincrnancount()\n Returns an accumulator function which incrementally updates a count,\n ignoring `NaN` values.\n","incrnansum":"\nincrnansum()\n Returns an accumulator function which incrementally computes a sum, ignoring\n `NaN` values.\n","incrnansumabs":"\nincrnansumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values, ignoring NaN values.\n","incrnansumabs2":"\nincrnansumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values, ignoring NaN values.\n","incrpcorr":"\nincrpcorr( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n","incrpcorr2":"\nincrpcorr2( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n","incrpcorrdist":"\nincrpcorrdist( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n","incrpcorrdistmat":"\nincrpcorrdistmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n","incrpcorrmat":"\nincrpcorrmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n","incrspace":"\nincrspace( start:number, stop:number[, increment:number] )\n Generates a linearly spaced numeric array using a provided increment.\n","incrstdev":"\nincrstdev( [mean:number] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n","incrvariance":"\nincrvariance( [mean:number] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n","incrvmr":"\nincrvmr( [mean:number] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n","ind2sub":"\nind2sub( shape:ArrayLike, idx:integer[, options:Object] )\n Converts a linear index to an array of subscripts.\n","ind2sub.assign":"\nind2sub.assign( shape:ArrayLike, idx:integer[, options:Object], \n out:Array|TypedArray|Object )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n","indexOf":"\nindexOf( arr:ArrayLike, searchElement:any[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","inherit":"\ninherit( ctor:Object|Function, superCtor:Object|Function )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable symbol properties.\n","inheritedKeys":"\ninheritedKeys( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable property names.\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable property names.\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n","inheritedProperties":"\ninheritedProperties( value:any[, level:integer] )\n Returns an array of an object's inherited property names and symbols.\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value:any, property:string|symbol[, \n level:integer] )\n Returns a property descriptor for an object's inherited property.\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value:any[, level:integer] )\n Returns an object's inherited property descriptors.\n","inheritedPropertyNames":"\ninheritedPropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited symbol properties.\n","inheritedWritableProperties":"\ninheritedWritableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited writable property names and\n symbols.\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited writable property names.\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited writable symbol properties.\n","inmap":"\ninmap( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n","inmapAsync":"\ninmapAsync( collection:Array|TypedArray|Object, [options:Object,] fcn:Function, \n done:Function )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n","inmapAsync.factory":"\ninmapAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n","inmapRight":"\ninmapRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n","inmapRightAsync":"\ninmapRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n","inspectSinkStream":"\ninspectSinkStream( [options:Object,] clbk:Function )\n Returns a writable stream for inspecting stream data.\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options:Object] )\n Returns a function for creating writable streams for inspecting stream data.\n","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options:Object,] clbk:Function )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n","inspectStream":"\ninspectStream( [options:Object,] clbk:Function )\n Returns a transform stream for inspecting stream data.\n","inspectStream.factory":"\ninspectStream.factory( [options:Object] )\n Returns a function for creating transform streams for inspecting stream\n data.\n","inspectStream.objectMode":"\ninspectStream.objectMode( [options:Object,] clbk:Function )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n","instanceOf":"\ninstanceOf( value:any, constructor:Function )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\nInt8Array( length:integer )\n Returns a typed array having a specified length.\n\nInt8Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt8Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int8Array.from":"\nInt8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int8Array.of":"\nInt8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int8Array.name":"\nInt8Array.name\n Typed array constructor name.\n","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int8Array.prototype.length":"\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n Serializes an array as a string.\n","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\nInt16Array( length:integer )\n Returns a typed array having a specified length.\n\nInt16Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt16Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int16Array.from":"\nInt16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int16Array.of":"\nInt16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int16Array.name":"\nInt16Array.name\n Typed array constructor name.\n","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int16Array.prototype.length":"\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n Serializes an array as a string.\n","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\nInt32Array( length:integer )\n Returns a typed array having a specified length.\n\nInt32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int32Array.from":"\nInt32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int32Array.of":"\nInt32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int32Array.name":"\nInt32Array.name\n Typed array constructor name.\n","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int32Array.prototype.length":"\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n Serializes an array as a string.\n","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n","IS_DOCKER":"\nIS_DOCKER\n Boolean indicating if the process is running in a Docker container.\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n","IS_MOBILE":"\nIS_MOBILE\n Boolean indicating if the current environment is a mobile device.\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n Boolean indicating if the current environment is a touch device.\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value:any )\n Tests whether a value is an absolute HTTP(S) URI.\n","isAbsolutePath":"\nisAbsolutePath( value:any )\n Tests if a value is an absolute path.\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value:any )\n Tests if a value is a POSIX absolute path.\n","isAbsolutePath.win32":"\nisAbsolutePath.win32( value:any )\n Tests if a value is a Windows absolute path.\n","isAbsoluteURI":"\nisAbsoluteURI( value:any )\n Tests whether a value is an absolute URI.\n","isAccessorArray":"\nisAccessorArray( value:any )\n Tests if a value is an array-like object supporting the accessor (get/set)\n protocol.\n","isAccessorProperty":"\nisAccessorProperty( value:any, property:any )\n Tests if an object's own property has an accessor descriptor.\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property has an accessor descriptor.\n","isAlphagram":"\nisAlphagram( value:any )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n","isAlphaNumeric":"\nisAlphaNumeric( str:string )\n Tests whether a string contains only alphanumeric characters.\n","isAnagram":"\nisAnagram( str:string, value:any )\n Tests if a value is an anagram.\n","isArguments":"\nisArguments( value:any )\n Tests if a value is an arguments object.\n","isArray":"\nisArray( value:any )\n Tests if a value is an array.\n","isArrayArray":"\nisArrayArray( value:any )\n Tests if a value is an array of arrays.\n","isArrayBuffer":"\nisArrayBuffer( value:any )\n Tests if a value is an ArrayBuffer.\n","isArrayBufferView":"\nisArrayBufferView( value:any )\n Tests if a value is a `ArrayBuffer` view.\n","isArrayLength":"\nisArrayLength( value:any )\n Tests if a value is a valid array length.\n","isArrayLike":"\nisArrayLike( value:any )\n Tests if a value is array-like.\n","isArrayLikeObject":"\nisArrayLikeObject( value:any )\n Tests if a value is an array-like object.\n","isArrowFunction":"\nisArrowFunction( value:any )\n Tests if a value is an arrow function.\n","isASCII":"\nisASCII( str:string )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n","isBetween":"\nisBetween( value:any, a:any, b:any[, left:string, right:string] )\n Tests if a value is between two values.\n","isBetweenArray":"\nisBetweenArray( value:any, a:any, b:any[, left:string, right:string] )\n Tests if a value is an array-like object where every element is between two\n values.\n","isBigInt":"\nisBigInt( value:any )\n Tests if a value is a BigInt.\n","isBigInt64Array":"\nisBigInt64Array( value:any )\n Tests if a value is a BigInt64Array.\n","isBigUint64Array":"\nisBigUint64Array( value:any )\n Tests if a value is a BigUint64Array.\n","isBinaryString":"\nisBinaryString( value:any )\n Tests if a value is a binary string.\n","isBlankString":"\nisBlankString( value:any )\n Tests if a value is a blank string (i.e., an empty string or a string\n consisting only of whitespace characters).\n","isBoolean":"\nisBoolean( value:any )\n Tests if a value is a boolean.\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value:any )\n Tests if a value is a boolean primitive.\n","isBoolean.isObject":"\nisBoolean.isObject( value:any )\n Tests if a value is a boolean object.\n","isBooleanArray":"\nisBooleanArray( value:any )\n Tests if a value is an array-like object of booleans.\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value:any )\n Tests if a value is an array-like object containing only boolean primitives.\n","isBooleanArray.objects":"\nisBooleanArray.objects( value:any )\n Tests if a value is an array-like object containing only Boolean objects.\n","isBoxedPrimitive":"\nisBoxedPrimitive( value:any )\n Tests if a value is a JavaScript boxed primitive.\n","isBuffer":"\nisBuffer( value:any )\n Tests if a value is a Buffer instance.\n","isCamelcase":"\nisCamelcase( value:any )\n Tests if a value is a camelcase string.\n","isCapitalized":"\nisCapitalized( value:any )\n Tests if a value is a string having an uppercase first character.\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value:any )\n Tests if a value is a matrix which is symmetric about its center.\n","isCircular":"\nisCircular( value:any )\n Tests if an object-like value contains a circular reference.\n","isCircularArray":"\nisCircularArray( value:any )\n Tests if a value is an array containing a circular reference.\n","isCircularPlainObject":"\nisCircularPlainObject( value:any )\n Tests if a value is a plain object containing a circular reference.\n","isClass":"\nisClass( value:any )\n Tests if a value is a class.\n","isCollection":"\nisCollection( value:any )\n Tests if a value is a collection.\n","isComplex":"\nisComplex( value:any )\n Tests if a value is a 64-bit or 128-bit complex number.\n","isComplex64":"\nisComplex64( value:any )\n Tests if a value is a 64-bit complex number.\n","isComplex64Array":"\nisComplex64Array( value:any )\n Tests if a value is a Complex64Array.\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing single-precision\n complex floating-point numbers.\n","isComplex64VectorLike":"\nisComplex64VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n","isComplex128":"\nisComplex128( value:any )\n Tests if a value is a 128-bit complex number.\n","isComplex128Array":"\nisComplex128Array( value:any )\n Tests if a value is a Complex128Array.\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing double-precision\n complex floating-point numbers.\n","isComplex128VectorLike":"\nisComplex128VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n","isComplexLike":"\nisComplexLike( value:any )\n Tests if a value is a complex number-like object.\n","isComplexTypedArray":"\nisComplexTypedArray( value:any )\n Tests if a value is a complex typed array.\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value:any )\n Tests if a value is complex-typed-array-like.\n","isComposite":"\nisComposite( value:any )\n Tests if a value is a composite number.\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value:any )\n Tests if a value is a number primitive which is a composite number.\n","isComposite.isObject":"\nisComposite.isObject( value:any )\n Tests if a value is a number object having a value which is a composite\n number.\n","isConfigurableProperty":"\nisConfigurableProperty( value:any, property:any )\n Tests if an object's own property is configurable.\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is configurable.\n","isConstantcase":"\nisConstantcase( value:any )\n Tests if a value is a constantcase string.\n","isCubeNumber":"\nisCubeNumber( value:any )\n Tests if a value is a cube number.\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a cube number.\n","isCubeNumber.isObject":"\nisCubeNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a cube number.\n","isCurrentYear":"\nisCurrentYear( value:any )\n Tests if a value is the current year.\n","isDataProperty":"\nisDataProperty( value:any, property:any )\n Tests if an object's own property has a data descriptor.\n","isDataPropertyIn":"\nisDataPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property has a data descriptor.\n","isDataView":"\nisDataView( value:any )\n Tests if a value is a DataView.\n","isDateObject":"\nisDateObject( value:any )\n Tests if a value is a Date object.\n","isDateObjectArray":"\nisDateObjectArray( value:any )\n Tests if a value is an array-like object containing only Date objects.\n","isDigitString":"\nisDigitString( str:string )\n Tests whether a string contains only numeric digits.\n","isDomainName":"\nisDomainName( value:any )\n Tests if a value is a domain name.\n","isDurationString":"\nisDurationString( value:any )\n Tests if a value is a duration string.\n","isEmailAddress":"\nisEmailAddress( value:any )\n Tests if a value is an email address.\n","isEmptyArray":"\nisEmptyArray( value:any )\n Tests if a value is an empty array.\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value:any )\n Tests if a value is an empty array-like object.\n","isEmptyCollection":"\nisEmptyCollection( value:any )\n Tests if a value is an empty collection.\n","isEmptyObject":"\nisEmptyObject( value:any )\n Tests if a value is an empty object.\n","isEmptyString":"\nisEmptyString( value:any )\n Tests if a value is an empty string.\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value:any )\n Tests if a value is an empty string primitive.\n","isEmptyString.isObject":"\nisEmptyString.isObject( value:any )\n Tests if a value is an empty `String` object.\n","isEnumerableProperty":"\nisEnumerableProperty( value:any, property:any )\n Tests if an object's own property is enumerable.\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is enumerable.\n","isEqualArray":"\nisEqualArray( v1:any, v2:any )\n Tests if two arguments are both generic arrays and have equal values.\n","isEqualDateObject":"\nisEqualDateObject( d1, d2 )\n Tests if two values are both Date objects corresponding to the same date\n and time.\n","isError":"\nisError( value:any )\n Tests if a value is an Error object.\n","isEvalError":"\nisEvalError( value:any )\n Tests if a value is an EvalError object.\n","isEven":"\nisEven( value:any )\n Tests if a value is an even number.\n","isEven.isPrimitive":"\nisEven.isPrimitive( value:any )\n Tests if a value is a number primitive that is an even number.\n","isEven.isObject":"\nisEven.isObject( value:any )\n Tests if a value is a number object that is an even number.\n","isFalsy":"\nisFalsy( value:any )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n","isFalsyArray":"\nisFalsyArray( value:any )\n Tests if a value is an array-like object containing only falsy values.\n","isFinite":"\nisFinite( value:any )\n Tests if a value is a finite number.\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a finite value.\n","isFinite.isObject":"\nisFinite.isObject( value:any )\n Tests if a value is a number object having a finite value.\n","isFiniteArray":"\nisFiniteArray( value:any )\n Tests if a value is an array-like object of finite numbers.\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n","isFiniteArray.objects":"\nisFiniteArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n","isFloat32Array":"\nisFloat32Array( value:any )\n Tests if a value is a Float32Array.\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing single-precision\n floating-point numbers.\n","isFloat32VectorLike":"\nisFloat32VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n","isFloat64Array":"\nisFloat64Array( value:any )\n Tests if a value is a Float64Array.\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing double-precision\n floating-point numbers.\n","isFloat64VectorLike":"\nisFloat64VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n","isFunction":"\nisFunction( value:any )\n Tests if a value is a function.\n","isFunctionArray":"\nisFunctionArray( value:any )\n Tests if a value is an array-like object containing only functions.\n","isGeneratorObject":"\nisGeneratorObject( value:any )\n Tests if a value is a generator object.\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value:any )\n Tests if a value is generator object-like.\n","isgzipBuffer":"\nisgzipBuffer( value:any )\n Tests if a value is a gzip buffer.\n","isHexString":"\nisHexString( str:string )\n Tests whether a string contains only hexadecimal digits.\n","isInfinite":"\nisInfinite( value:any )\n Tests if a value is an infinite number.\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value:any )\n Tests if a value is a number primitive having an infinite value.\n","isInfinite.isObject":"\nisInfinite.isObject( value:any )\n Tests if a value is a number object having an infinite value.\n","isInheritedProperty":"\nisInheritedProperty( value:any, property:any )\n Tests if an object has an inherited property.\n","isInt8Array":"\nisInt8Array( value:any )\n Tests if a value is an Int8Array.\n","isInt16Array":"\nisInt16Array( value:any )\n Tests if a value is an Int16Array.\n","isInt32Array":"\nisInt32Array( value:any )\n Tests if a value is an Int32Array.\n","isInteger":"\nisInteger( value:any )\n Tests if a value is an integer.\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having an integer value.\n","isInteger.isObject":"\nisInteger.isObject( value:any )\n Tests if a value is a number object having an integer value.\n","isIntegerArray":"\nisIntegerArray( value:any )\n Tests if a value is an array-like object of integer values.\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive integer\n values.\n","isIntegerArray.objects":"\nisIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n","isIterableLike":"\nisIterableLike( value:any )\n Tests if a value is iterable-like.\n","isIteratorLike":"\nisIteratorLike( value:any )\n Tests if a value is iterator-like.\n","isJSON":"\nisJSON( value:any )\n Tests if a value is a parseable JSON string.\n","isKebabcase":"\nisKebabcase( value:any )\n Tests if a value is a string in kebab case.\n","isLeapYear":"\nisLeapYear( value:any )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n","isLocalhost":"\nisLocalhost( value:any )\n Tests whether a value is a localhost hostname.\n","isLowercase":"\nisLowercase( value:any )\n Tests if a value is a lowercase string.\n","isMatrixLike":"\nisMatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object.\n","isMethod":"\nisMethod( value:any, property:any )\n Tests if an object has a specified method name.\n","isMethodIn":"\nisMethodIn( value:any, property:any )\n Tests if an object has a specified method name, either own or inherited.\n","isMultiSlice":"\nisMultiSlice( value:any )\n Tests if a value is a MultiSlice object.\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value:any )\n Tests if a value is named typed tuple-like.\n","isnan":"\nisnan( value:any )\n Tests if a value is NaN.\n","isnan.isPrimitive":"\nisnan.isPrimitive( value:any )\n Tests if a value is a NaN number primitive.\n","isnan.isObject":"\nisnan.isObject( value:any )\n Tests if a value is a number object having a value of NaN.\n","isNaNArray":"\nisNaNArray( value:any )\n Tests if a value is an array-like object containing only NaN values.\n","isNaNArray.primitives":"\nisNaNArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n","isNaNArray.objects":"\nisNaNArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n","isNativeFunction":"\nisNativeFunction( value:any )\n Tests if a value is a native function.\n","isndarrayLike":"\nisndarrayLike( value:any )\n Tests if a value is ndarray-like.\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value:any, dtype:any )\n Tests if a value is an ndarray-like object having a specified data type.\n","isNegativeFinite":"\nisNegativeFinite( value:any )\n Tests if a value is a finite negative number.\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a finite negative value.\n","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value:any )\n Tests if a value is a number object having a finite negative value.\n","isNegativeInteger":"\nisNegativeInteger( value:any )\n Tests if a value is a negative integer.\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a negative integer value.\n","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value:any )\n Tests if a value is a number object having a negative integer value.\n","isNegativeIntegerArray":"\nisNegativeIntegerArray( value:any )\n Tests if a value is an array-like object containing only negative integers.\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n","isNegativeNumber":"\nisNegativeNumber( value:any )\n Tests if a value is a negative number.\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a negative value.\n","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value:any )\n Tests if a value is a number object having a negative value.\n","isNegativeNumberArray":"\nisNegativeNumberArray( value:any )\n Tests if a value is an array-like object containing only negative numbers.\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n","isNegativeZero":"\nisNegativeZero( value:any )\n Tests if a value is negative zero.\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value:any )\n Tests if a value is a number primitive equal to negative zero.\n","isNegativeZero.isObject":"\nisNegativeZero.isObject( value:any )\n Tests if a value is a number object having a value equal to negative zero.\n","isNodeBuiltin":"\nisNodeBuiltin( str:string )\n Tests whether a string matches a Node.js built-in module name.\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value:any )\n Tests if a value is Node duplex stream-like.\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value:any )\n Tests if a value is Node readable stream-like.\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n","isNodeStreamLike":"\nisNodeStreamLike( value:any )\n Tests if a value is Node stream-like.\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value:any )\n Tests if a value is Node transform stream-like.\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value:any )\n Tests if a value is Node writable stream-like.\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value:any, property:any )\n Tests if an object's own property is non-configurable.\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is non-configurable.\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value:any, property:any )\n Tests if an object's own property is non-enumerable.\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is non-enumerable.\n","isNonNegativeFinite":"\nisNonNegativeFinite( value:any )\n Tests if a value is a nonnegative finite number.\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative finite value.\n","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value:any )\n Tests if a value is a number object having a nonnegative finite value.\n","isNonNegativeInteger":"\nisNonNegativeInteger( value:any )\n Tests if a value is a nonnegative integer.\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative integer value.\n","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value:any )\n Tests if a value is a number object having a nonnegative integer value.\n","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value:any )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n","isNonNegativeNumber":"\nisNonNegativeNumber( value:any )\n Tests if a value is a nonnegative number.\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative value.\n","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value:any )\n Tests if a value is a number object having a nonnegative value.\n","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value:any )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n","isNonPositiveFinite":"\nisNonPositiveFinite( value:any )\n Tests if a value is a nonpositive finite number.\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive finite value.\n","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value:any )\n Tests if a value is a number object having a nonpositive finite value.\n","isNonPositiveInteger":"\nisNonPositiveInteger( value:any )\n Tests if a value is a nonpositive integer.\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive integer value.\n","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value:any )\n Tests if a value is a number object having a nonpositive integer value.\n","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value:any )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n","isNonPositiveNumber":"\nisNonPositiveNumber( value:any )\n Tests if a value is a nonpositive number.\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive value.\n","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value:any )\n Tests if a value is a number object having a nonpositive value.\n","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value:any )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value:any )\n Tests if a value is a non-symmetric matrix.\n","isNull":"\nisNull( value:any )\n Tests if a value is null.\n","isNullArray":"\nisNullArray( value:any )\n Tests if a value is an array-like object containing only null values.\n","isNumber":"\nisNumber( value:any )\n Tests if a value is a number.\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value:any )\n Tests if a value is a number primitive.\n","isNumber.isObject":"\nisNumber.isObject( value:any )\n Tests if a value is a `Number` object.\n","isNumberArray":"\nisNumberArray( value:any )\n Tests if a value is an array-like object containing only numbers.\n","isNumberArray.primitives":"\nisNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only number primitives.\n","isNumberArray.objects":"\nisNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only `Number` objects.\n","isNumericArray":"\nisNumericArray( value:any )\n Tests if a value is a numeric array.\n","isObject":"\nisObject( value:any )\n Tests if a value is an object; e.g., `{}`.\n","isObjectArray":"\nisObjectArray( value:any )\n Tests if a value is an array-like object containing only objects.\n","isObjectLike":"\nisObjectLike( value:any )\n Tests if a value is object-like.\n","isOdd":"\nisOdd( value:any )\n Tests if a value is an odd number.\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value:any )\n Tests if a value is a number primitive that is an odd number.\n","isOdd.isObject":"\nisOdd.isObject( value:any )\n Tests if a value is a number object that has an odd number value.\n","isoWeeksInYear":"\nisoWeeksInYear( [year:integer] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n","isPascalcase":"\nisPascalcase( value:any )\n Tests if a value is a string in Pascal case.\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value:any )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n","isPlainObject":"\nisPlainObject( value:any )\n Tests if a value is a plain object.\n","isPlainObjectArray":"\nisPlainObjectArray( value:any )\n Tests if a value is an array-like object containing only plain objects.\n","isPositiveFinite":"\nisPositiveFinite( value:any )\n Tests if a value is a positive finite number.\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive finite value.\n","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value:any )\n Tests if a value is a number object having a positive finite value.\n","isPositiveInteger":"\nisPositiveInteger( value:any )\n Tests if a value is a positive integer.\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive integer value.\n","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value:any )\n Tests if a value is a number object having a positive integer value.\n","isPositiveIntegerArray":"\nisPositiveIntegerArray( value:any )\n Tests if a value is an array-like object containing only positive integers.\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n","isPositiveNumber":"\nisPositiveNumber( value:any )\n Tests if a value is a positive number.\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive value.\n","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value:any )\n Tests if a value is a number object having a positive value.\n","isPositiveNumberArray":"\nisPositiveNumberArray( value:any )\n Tests if a value is an array-like object containing only positive numbers.\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n","isPositiveZero":"\nisPositiveZero( value:any )\n Tests if a value is positive zero.\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value:any )\n Tests if a value is a number primitive equal to positive zero.\n","isPositiveZero.isObject":"\nisPositiveZero.isObject( value:any )\n Tests if a value is a number object having a value equal to positive zero.\n","isPrime":"\nisPrime( value:any )\n Tests if a value is a prime number.\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value:any )\n Tests if a value is a number primitive which is a prime number.\n","isPrime.isObject":"\nisPrime.isObject( value:any )\n Tests if a value is a number object having a value which is a prime number.\n","isPrimitive":"\nisPrimitive( value:any )\n Tests if a value is a JavaScript primitive.\n","isPrimitiveArray":"\nisPrimitiveArray( value:any )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n","isPRNGLike":"\nisPRNGLike( value:any )\n Tests if a value is PRNG-like.\n","isProbability":"\nisProbability( value:any )\n Tests if a value is a probability.\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value:any )\n Tests if a value is a number primitive which is a probability.\n","isProbability.isObject":"\nisProbability.isObject( value:any )\n Tests if a value is a number object having a value which is a probability.\n","isProbabilityArray":"\nisProbabilityArray( value:any )\n Tests if a value is an array-like object containing only probabilities.\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n","isProbabilityArray.objects":"\nisProbabilityArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n","isPropertyKey":"\nisPropertyKey( value:any )\n Tests whether a value is a property key.\n","isPrototypeOf":"\nisPrototypeOf( value:any, proto:Object|Function )\n Tests if an object's prototype chain contains a provided prototype.\n","isRaggedNestedArray":"\nisRaggedNestedArray( value:any )\n Tests if a value is a ragged nested array. \n","isRangeError":"\nisRangeError( value:any )\n Tests if a value is a RangeError object.\n","isReadableProperty":"\nisReadableProperty( value:any, property:any )\n Tests if an object's own property is readable.\n","isReadablePropertyIn":"\nisReadablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is readable.\n","isReadOnlyProperty":"\nisReadOnlyProperty( value:any, property:any )\n Tests if an object's own property is read-only.\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is read-only.\n","isReadWriteProperty":"\nisReadWriteProperty( value:any, property:any )\n Tests if an object's own property is readable and writable.\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is readable and writable.\n","isReferenceError":"\nisReferenceError( value:any )\n Tests if a value is a ReferenceError object.\n","isRegExp":"\nisRegExp( value:any )\n Tests if a value is a regular expression.\n","isRegExpString":"\nisRegExpString( value:any )\n Tests if a value is a regular expression string.\n","isRelativePath":"\nisRelativePath( value:any )\n Tests if a value is a relative path.\n","isRelativePath.posix":"\nisRelativePath.posix( value:any )\n Tests if a value is a POSIX relative path.\n","isRelativePath.win32":"\nisRelativePath.win32( value:any )\n Tests if a value is a Windows relative path.\n","isRelativeURI":"\nisRelativeURI( value:any )\n Tests whether a value is a relative URI.\n","isSafeInteger":"\nisSafeInteger( value:any )\n Tests if a value is a safe integer.\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a safe integer value.\n","isSafeInteger.isObject":"\nisSafeInteger.isObject( value:any )\n Tests if a value is a `Number` object having a safe integer value.\n","isSafeIntegerArray":"\nisSafeIntegerArray( value:any )\n Tests if a value is an array-like object containing only safe integers.\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n","isSameArray":"\nisSameArray( v1:any, v2:any )\n Tests if two arguments are both generic arrays and have the same values.\n","isSameArrayLike":"\nisSameArrayLike( v1:any, v2:any )\n Tests if two arguments are both array-like and have the same values.\n","isSameComplex64":"\nisSameComplex64( v1:any, v2:any )\n Tests if two arguments are both single-precision complex floating-point\n numbers and have the same value.\n","isSameComplex64Array":"\nisSameComplex64Array( v1:any, v2:any )\n Tests if two arguments are both Complex64Arrays and have the same values.\n","isSameComplex128":"\nisSameComplex128( v1:any, v2:any )\n Tests if two arguments are both double-precision complex floating-point\n numbers and have the same value.\n","isSameComplex128Array":"\nisSameComplex128Array( v1:any, v2:any )\n Tests if two arguments are both Complex128Arrays and have the same values.\n","isSameFloat32Array":"\nisSameFloat32Array( v1:any, v2:any )\n Tests if two arguments are both Float32Arrays and have the same values.\n","isSameFloat64Array":"\nisSameFloat64Array( v1:any, v2:any )\n Tests if two arguments are both Float64Arrays and have the same values.\n","isSameNativeClass":"\nisSameNativeClass( a:any, b:any )\n Tests if two arguments have the same native class.\n","isSameType":"\nisSameType( a:any, b:any )\n Tests if two arguments have the same type.\n","isSameValue":"\nisSameValue( a:any, b:any )\n Tests if two arguments are the same value.\n","isSameValueZero":"\nisSameValueZero( a:any, b:any )\n Tests if two arguments are the same value.\n","isSemVer":"\nisSemVer( value:any )\n Tests if a value is a semantic version string.\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value:any )\n Tests if a value is a SharedArrayBuffer.\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value:any )\n Tests if a value is a skew-centrosymmetric matrix.\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value:any )\n Tests if a value is a skew-persymmetric matrix.\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value:any )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n","isSlice":"\nisSlice( value:any )\n Tests if a value is a Slice object.\n","isSnakecase":"\nisSnakecase( value:any )\n Tests if a value is a string in snake case.\n","isSquareMatrix":"\nisSquareMatrix( value:any )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n","isSquareNumber":"\nisSquareNumber( value:any )\n Tests if a value is a square number.\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a square number.\n","isSquareNumber.isObject":"\nisSquareNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a square number.\n","isSquareTriangularNumber":"\nisSquareTriangularNumber( value:any )\n Tests if a value is a square triangular number.\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a square triangular number.\n","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a square\n triangular number.\n","isStartcase":"\nisStartcase( value:any )\n Tests if a value is a startcase string.\n","isStrictEqual":"\nisStrictEqual( a:any, b:any )\n Tests if two arguments are strictly equal.\n","isString":"\nisString( value:any )\n Tests if a value is a string.\n","isString.isPrimitive":"\nisString.isPrimitive( value:any )\n Tests if a value is a string primitive.\n","isString.isObject":"\nisString.isObject( value:any )\n Tests if a value is a `String` object.\n","isStringArray":"\nisStringArray( value:any )\n Tests if a value is an array of strings.\n","isStringArray.primitives":"\nisStringArray.primitives( value:any )\n Tests if a value is an array containing only string primitives.\n","isStringArray.objects":"\nisStringArray.objects( value:any )\n Tests if a value is an array containing only `String` objects.\n","isStruct":"\nisStruct( value:any )\n Tests if a value is a `struct` instance.\n","isStructConstructorLike":"\nisStructConstructorLike( value:any )\n Tests if a value is struct constructor-like.\n","isSymbol":"\nisSymbol( value:any )\n Tests if a value is a symbol.\n","isSymbolArray":"\nisSymbolArray( value:any )\n Tests if a value is an array-like object containing only symbols.\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value:any )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n","isSymbolArray.objects":"\nisSymbolArray.objects( value:any )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n","isSymmetricMatrix":"\nisSymmetricMatrix( value:any )\n Tests if a value is a square matrix which equals its transpose.\n","isSyntaxError":"\nisSyntaxError( value:any )\n Tests if a value is a SyntaxError object.\n","isTriangularNumber":"\nisTriangularNumber( value:any )\n Tests if a value is a triangular number.\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a triangular number.\n","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a triangular\n number.\n","isTruthy":"\nisTruthy( value:any )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n","isTruthyArray":"\nisTruthyArray( value:any )\n Tests if a value is an array-like object containing only truthy values.\n","isTypedArray":"\nisTypedArray( value:any )\n Tests if a value is a typed array.\n","isTypedArrayLength":"\nisTypedArrayLength( value:any )\n Tests if a value is a valid typed array length.\n","isTypedArrayLike":"\nisTypedArrayLike( value:any )\n Tests if a value is typed-array-like.\n","isTypeError":"\nisTypeError( value:any )\n Tests if a value is a TypeError object.\n","isUint8Array":"\nisUint8Array( value:any )\n Tests if a value is a Uint8Array.\n","isUint8ClampedArray":"\nisUint8ClampedArray( value:any )\n Tests if a value is a Uint8ClampedArray.\n","isUint16Array":"\nisUint16Array( value:any )\n Tests if a value is a Uint16Array.\n","isUint32Array":"\nisUint32Array( value:any )\n Tests if a value is a Uint32Array.\n","isUNCPath":"\nisUNCPath( value:any )\n Tests if a value is a UNC path.\n","isUndefined":"\nisUndefined( value:any )\n Tests if a value is undefined.\n","isUndefinedOrNull":"\nisUndefinedOrNull( value:any )\n Tests if a value is undefined or null.\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value:any )\n Tests if a value is an array of probabilities that sum to one.\n","isUppercase":"\nisUppercase( value:any )\n Tests if a value is an uppercase string.\n","isURI":"\nisURI( value:any )\n Tests if a value is a URI.\n","isURIError":"\nisURIError( value:any )\n Tests if a value is a URIError object.\n","isVectorLike":"\nisVectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object.\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value:any )\n Tests if a value is a WebAssembly memory instance.\n","isWellFormedString":"\nisWellFormedString( str:any )\n Tests if a string is well-formed.\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str:any )\n Tests if a string is a well-formed string primitive.\n","isWellFormedString.isObject":"\nisWellFormedString.isObject( str:any )\n Tests if a string is a well-formed string object.\n","isWhitespace":"\nisWhitespace( str:string )\n Tests whether a string contains only white space characters.\n","isWritableProperty":"\nisWritableProperty( value:any, property:any )\n Tests if an object's own property is writable.\n","isWritablePropertyIn":"\nisWritablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is writable.\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value:any, property:any )\n Tests if an object's own property is write-only.\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is write-only.\n","iterAbs":"\niterAbs( iterator:Object )\n Returns an iterator which iteratively computes the absolute value.\n","iterAbs2":"\niterAbs2( iterator:Object )\n Returns an iterator which iteratively computes the squared absolute value.\n","iterAcos":"\niterAcos( iterator:Object )\n Returns an iterator which iteratively computes the arccosine.\n","iterAcosh":"\niterAcosh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arccosine.\n","iterAcot":"\niterAcot( iterator:Object )\n Returns an iterator which iteratively computes the inverse cotangent.\n","iterAcoth":"\niterAcoth( iterator:Object )\n Returns an iterator which iteratively computes the inverse hyperbolic\n cotangent.\n","iterAcovercos":"\niterAcovercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse coversed cosine.\n","iterAcoversin":"\niterAcoversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse coversed sine.\n","iterAdd":"\niterAdd( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n","iterAdvance":"\niterAdvance( iterator:Object[, n:integer] )\n Advances an entire iterator.\n","iterAhavercos":"\niterAhavercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse half-value versed\n cosine.\n","iterAhaversin":"\niterAhaversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse half-value versed\n sine.\n","iterAny":"\niterAny( iterator:Object )\n Tests whether at least one iterated value is truthy.\n","iterAnyBy":"\niterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n","iterAsin":"\niterAsin( iterator:Object )\n Returns an iterator which iteratively computes the arcsine.\n","iterAsinh":"\niterAsinh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arcsine.\n","iterAtan":"\niterAtan( iterator:Object )\n Returns an iterator which iteratively computes the arctangent.\n","iterAtan2":"\niterAtan2( y:Object|number, x:Object|number )\n Returns an iterator which iteratively computes the angle in the plane (in\n radians) between the positive x-axis and the ray from (0,0) to the point\n (x,y).\n","iterAtanh":"\niterAtanh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arctangent.\n","iterator2array":"\niterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, \n thisArg:any]] )\n Creates (or fills) an array from an iterator.\n","iterator2arrayview":"\niterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, \n end:integer]][, mapFcn:Function[, thisArg:any]] )\n Fills an array-like object view with values returned from an iterator.\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, \n begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n","iteratorStream":"\niteratorStream( iterator:Object[, options:Object] )\n Creates a readable stream from an iterator.\n","iteratorStream.factory":"\niteratorStream.factory( [options:Object] )\n Returns a function for creating readable streams from iterators.\n","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator:Object[, options:Object] )\n Returns an \"objectMode\" readable stream from an iterator.\n","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n","iterAvercos":"\niterAvercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse versed cosine.\n","iterAversin":"\niterAversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse versed sine.\n","iterawgn":"\niterawgn( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n","iterawln":"\niterawln( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n","iterawun":"\niterawun( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options:Object] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n","iterBartlettPulse":"\niterBartlettPulse( [options:Object] )\n Returns an iterator which generates a Bartlett pulse waveform.\n","iterBesselj0":"\niterBesselj0( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order zero.\n","iterBesselj1":"\niterBesselj1( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order one.\n","iterBessely0":"\niterBessely0( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order zero.\n","iterBessely1":"\niterBessely1( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order one.\n","iterBeta":"\niterBeta( x:Object|number, y:Object|number )\n Returns an iterator which iteratively evaluates the beta function.\n","iterBetaln":"\niterBetaln( x:Object|number, y:Object|number )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n beta function.\n","iterBinet":"\niterBinet( iterator:Object )\n Returns an iterator which iteratively evaluates Binet's formula extended to\n real numbers.\n","iterCbrt":"\niterCbrt( iterator:Object )\n Returns an iterator which iteratively computes the cube root.\n","iterCeil":"\niterCeil( iterator:Object )\n Returns an iterator which rounds each iterated value toward positive\n infinity.\n","iterCeil2":"\niterCeil2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward positive infinity.\n","iterCeil10":"\niterCeil10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward positive infinity.\n","iterCompositesSeq":"\niterCompositesSeq( [options:Object] )\n Returns an iterator which generates a sequence of composite numbers.\n","iterConcat":"\niterConcat( iter0:Object, ...iterator:Object )\n Returns an iterator which iterates over the values of two or more iterators.\n","iterConstant":"\niterConstant( value:any[, options:Object] )\n Returns an iterator which always returns the same value.\n","iterContinuedFraction":"\niterContinuedFraction( iterator:Object[, options:Object] )\n Evaluates the terms of a continued fraction.\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x:number[, options:Object] )\n Returns an iterator which generates a list of all continued fraction terms\n which can be obtained given the precision of `x`.\n","iterCos":"\niterCos( iterator:Object )\n Returns an iterator which iteratively computes the cosine.\n","iterCosh":"\niterCosh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic cosine.\n","iterCosineWave":"\niterCosineWave( [options:Object] )\n Returns an iterator which generates a cosine wave.\n","iterCosm1":"\niterCosm1( iterator:Object )\n Returns an iterator which iteratively computes `cos(x) - 1`.\n","iterCospi":"\niterCospi( iterator:Object )\n Returns an iterator which computes the cosine of each iterated value times\n π.\n","iterCounter":"\niterCounter( iterator:Object )\n Returns an iterator which iteratively computes the number of iterated\n values.\n","iterCovercos":"\niterCovercos( iterator:Object )\n Returns an iterator which iteratively computes the coversed cosine.\n","iterCoversin":"\niterCoversin( iterator:Object )\n Returns an iterator which iteratively computes the coversed sine.\n","iterCubesSeq":"\niterCubesSeq( [options:Object] )\n Returns an iterator which generates a sequence of cubes.\n","itercugmean":"\nitercugmean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n","itercuhmean":"\nitercuhmean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n","itercumax":"\nitercumax( iterator:Object )\n Returns an iterator which iteratively computes a cumulative maximum value.\n","itercumaxabs":"\nitercumaxabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n","itercumean":"\nitercumean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n","itercumeanabs":"\nitercumeanabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n","itercumeanabs2":"\nitercumeanabs2( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n","itercumidrange":"\nitercumidrange( iterator:Object )\n Returns an iterator which iteratively computes a cumulative mid-range.\n","itercumin":"\nitercumin( iterator:Object )\n Returns an iterator which iteratively computes a cumulative minimum value.\n","itercuminabs":"\nitercuminabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n","itercuprod":"\nitercuprod( iterator:Object )\n Returns an iterator which iteratively computes a cumulative product.\n","itercurange":"\nitercurange( iterator:Object )\n Returns an iterator which iteratively computes a cumulative range.\n","itercusum":"\nitercusum( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum.\n","itercusumabs":"\nitercusumabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n","itercusumabs2":"\nitercusumabs2( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n","iterDatespace":"\niterDatespace( start:integer|string|Date, stop:integer|string|Date[, \n N:integer][, options:Object] )\n Returns an iterator which returns evenly spaced dates over a specified\n interval.\n","iterDedupe":"\niterDedupe( iterator:Object[, limit:integer] )\n Returns an iterator which removes consecutive duplicated values.\n","iterDedupeBy":"\niterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n","iterDeg2rad":"\niterDeg2rad( iterator:Object )\n Returns an iterator which iteratively converts an angle from degrees to\n radians.\n","iterDigamma":"\niterDigamma( iterator:Object )\n Returns an iterator which iteratively evaluates the digamma function.\n","iterDiracComb":"\niterDiracComb( [options:Object] )\n Returns an iterator which generates a Dirac comb.\n","iterDiracDelta":"\niterDiracDelta( iterator:Object )\n Returns an iterator which iteratively evaluates the Dirac delta function.\n","iterDivide":"\niterDivide( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n","iterDoUntilEach":"\niterDoUntilEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n","iterDoWhileEach":"\niterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n","iterEllipe":"\niterEllipe( iterator:Object )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the second kind.\n","iterEllipk":"\niterEllipk( iterator:Object )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the first kind.\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n","iterErf":"\niterErf( iterator:Object )\n Returns an iterator which iteratively evaluates the error function.\n","iterErfc":"\niterErfc( iterator:Object )\n Returns an iterator which iteratively evaluates the complementary error\n function.\n","iterErfcinv":"\niterErfcinv( iterator:Object )\n Returns an iterator which iteratively evaluates the inverse complementary\n error function.\n","iterErfinv":"\niterErfinv( iterator:Object )\n Returns an iterator which iteratively evaluates the inverse error function.\n","iterEta":"\niterEta( iterator:Object )\n Returns an iterator which iteratively evaluates the Dirichlet eta function.\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved sequence of even\n integers.\n","iterEvery":"\niterEvery( iterator:Object )\n Tests whether all iterated values are truthy.\n","iterEveryBy":"\niterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n","iterExp":"\niterExp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural exponential\n function.\n","iterExp2":"\niterExp2( iterator:Object )\n Returns an iterator which iteratively evaluates the base `2` exponential\n function.\n","iterExp10":"\niterExp10( iterator:Object )\n Returns an iterator which iteratively evaluates the base `10` exponential\n function.\n","iterExpit":"\niterExpit( iterator:Object )\n Returns an iterator which iteratively evaluates the standard logistic\n function.\n","iterExpm1":"\niterExpm1( iterator:Object )\n Returns an iterator which iteratively computes `exp(x) - 1`.\n","iterExpm1rel":"\niterExpm1rel( iterator:Object )\n Returns an iterator which iteratively evaluates the relative error\n exponential.\n","iterFactorial":"\niterFactorial( iterator:Object )\n Returns an iterator which iteratively evaluates the factorial function.\n","iterFactorialln":"\niterFactorialln( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n factorial function.\n","iterFactorialsSeq":"\niterFactorialsSeq( [options:Object] )\n Returns an iterator which generates a sequence of factorials.\n","iterFibonacciSeq":"\niterFibonacciSeq( [options:Object] )\n Returns an iterator which generates a Fibonacci sequence.\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options:Object] )\n Returns an iterator which generates a sequence of fifth powers.\n","iterFill":"\niterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n","iterFilter":"\niterFilter( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n","iterFilterMap":"\niterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n","iterFirst":"\niterFirst( iterator:Object )\n Returns the first iterated value.\n","iterFlatTopPulse":"\niterFlatTopPulse( [options:Object] )\n Returns an iterator which generates a flat top pulse waveform.\n","iterFloor":"\niterFloor( iterator:Object )\n Returns an iterator which rounds each iterated value toward negative\n infinity.\n","iterFloor2":"\niterFloor2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward negative infinity.\n","iterFloor10":"\niterFloor10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward negative infinity.\n","iterFlow":"\niterFlow( methods:Object )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n","iterForEach":"\niterForEach( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options:Object] )\n Returns an iterator which generates a sequence of fourth powers.\n","iterFresnelc":"\niterFresnelc( iterator:Object )\n Returns an iterator which iteratively computes the Fresnel integral C(x).\n","iterFresnels":"\niterFresnels( iterator:Object )\n Returns an iterator which iteratively computes the Fresnel integral S(x).\n","iterGamma":"\niterGamma( iterator:Object )\n Returns an iterator which iteratively evaluates the gamma function.\n","iterGamma1pm1":"\niterGamma1pm1( iterator:Object )\n Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n cancellation errors for small `x`.\n","iterGammaln":"\niterGammaln( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n gamma function.\n","iterHacovercos":"\niterHacovercos( iterator:Object )\n Returns an iterator which iteratively computes the half-value coversed\n cosine.\n","iterHacoversin":"\niterHacoversin( iterator:Object )\n Returns an iterator which iteratively computes the half-value coversed sine.\n","iterHannPulse":"\niterHannPulse( [options:Object] )\n Returns an iterator which generates a Hann pulse waveform.\n","iterHavercos":"\niterHavercos( iterator:Object )\n Returns an iterator which iteratively computes the half-value versed cosine.\n","iterHaversin":"\niterHaversin( iterator:Object )\n Returns an iterator which iteratively computes the half-value versed sine.\n","iterHead":"\niterHead( iterator:Object, n:integer )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n","iterIncrspace":"\niterIncrspace( start:number, stop:number[, increment:number] )\n Returns an iterator which returns evenly spaced numbers according to a\n specified increment.\n","iterIntegersSeq":"\niterIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved integer sequence.\n","iterIntersection":"\niterIntersection( iter0:Object, ...iterator:Object )\n Returns an iterator which returns the intersection of two or more iterators.\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, \n thisArg:any] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n","iterInv":"\niterInv( iterator:Object )\n Returns an iterator which iteratively computes the multiplicative inverse.\n","iterLanczosPulse":"\niterLanczosPulse( [options:Object] )\n Returns an iterator which generates a Lanczos pulse waveform.\n","iterLast":"\niterLast( iterator:Object )\n Consumes an entire iterator and returns the last iterated value.\n","iterLength":"\niterLength( iterator:Object )\n Consumes an entire iterator and returns the number of iterated values.\n","iterLinspace":"\niterLinspace( start:number, stop:number[, N:integer] )\n Returns an iterator which returns evenly spaced numbers over a specified\n interval.\n","iterLn":"\niterLn( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm.\n","iterLog":"\niterLog( x:Object|number, b:Object|number )\n Returns an iterator which iteratively computes the base `b` logarithm.\n","iterLog1mexp":"\niterLog1mexp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1-exp(-|x|)`.\n","iterLog1p":"\niterLog1p( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+x`.\n","iterLog1pexp":"\niterLog1pexp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+exp(x)`.\n","iterLog2":"\niterLog2( iterator:Object )\n Returns an iterator which iteratively evaluates the binary logarithm.\n","iterLog10":"\niterLog10( iterator:Object )\n Returns an iterator which iteratively evaluates the common logarithm\n (logarithm with base 10).\n","iterLogit":"\niterLogit( iterator:Object )\n Returns an iterator which iteratively evaluates the logit function.\n","iterLogspace":"\niterLogspace( start:number, stop:number[, N:integer][, options:Object] )\n Returns an iterator which returns evenly spaced numbers on a log scale.\n","iterLucasSeq":"\niterLucasSeq( [options:Object] )\n Returns an iterator which generates a Lucas sequence.\n","iterMap":"\niterMap( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which invokes a function for each iterated value.\n","iterMapN":"\niterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n","itermax":"\nitermax( iterator:Object )\n Computes the maximum value of all iterated values.\n","itermaxabs":"\nitermaxabs( iterator:Object )\n Computes the maximum absolute value of all iterated values.\n","itermean":"\nitermean( iterator:Object )\n Computes an arithmetic mean over all iterated values.\n","itermeanabs":"\nitermeanabs( iterator:Object )\n Computes an arithmetic mean of absolute values for all iterated values.\n","itermeanabs2":"\nitermeanabs2( iterator:Object )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n","itermidrange":"\nitermidrange( iterator:Object )\n Computes the mid-range of all iterated values.\n","itermin":"\nitermin( iterator:Object )\n Computes the minimum value of all iterated values.\n","iterminabs":"\niterminabs( iterator:Object )\n Computes the minimum absolute value of all iterated values.\n","itermmax":"\nitermmax( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving maximum value.\n","itermmaxabs":"\nitermmaxabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n","itermmean":"\nitermmean( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n","itermmeanabs":"\nitermmeanabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n","itermmeanabs2":"\nitermmeanabs2( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n","itermmidrange":"\nitermmidrange( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving mid-range.\n","itermmin":"\nitermmin( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving minimum value.\n","itermminabs":"\nitermminabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n","iterMod":"\niterMod( iter0:Object, ...iterator:Object )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n","itermprod":"\nitermprod( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving product.\n","itermrange":"\nitermrange( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving range.\n","itermsum":"\nitermsum( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum.\n","itermsumabs":"\nitermsumabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n","itermsumabs2":"\nitermsumabs2( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n","iterMultiply":"\niterMultiply( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options:Object] )\n Returns an iterator which generates a negaFibonacci sequence.\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options:Object] )\n Returns an iterator which generates a negaLucas sequence.\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of negative even integers.\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options:Object] )\n Returns an iterator which generates a negative integer sequence.\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of negative odd integers.\n","iterNone":"\niterNone( iterator:Object )\n Tests whether all iterated values are falsy.\n","iterNoneBy":"\niterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options:Object] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonnegative even integers.\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options:Object] )\n Returns an iterator which generates a nonnegative integer sequence.\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonpositive even integers.\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options:Object] )\n Returns an iterator which generates a nonpositive integer sequence.\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonsquares.\n","iterNth":"\niterNth( iterator:Object, n:integer )\n Returns the nth iterated value.\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved sequence of odd integers.\n","iterPeriodicSinc":"\niterPeriodicSinc( n:integer[, options:Object] )\n Returns an iterator which generates a periodic sinc waveform.\n","iterPipeline":"\niterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )\n Returns an iterator pipeline.\n","iterPop":"\niterPop( iterator:Object[, clbk:Function[, thisArg:any]] )\n Returns an iterator which skips the last value of a provided iterator.\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of positive even integers.\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options:Object] )\n Returns an iterator which generates a positive integer sequence.\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of positive odd integers.\n","iterPow":"\niterPow( base:Object|number, exponent:Object|number )\n Returns an iterator which iteratively evaluates the exponential function.\n","iterPrimesSeq":"\niterPrimesSeq( [options:Object] )\n Returns an iterator which generates a sequence of prime numbers.\n","iterprod":"\niterprod( iterator:Object )\n Computes the product of all iterated values.\n","iterPulse":"\niterPulse( [options:Object] )\n Returns an iterator which generates a pulse waveform.\n","iterPush":"\niterPush( iterator:Object, ...items:any )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n","iterRad2deg":"\niterRad2deg( iterator:Object )\n Returns an iterator which iteratively converts an angle from radians to\n degrees.\n","iterRamp":"\niterRamp( iterator:Object )\n Returns an iterator which iteratively evaluates the ramp function.\n","iterrange":"\niterrange( iterator:Object )\n Computes the range of all iterated values.\n","iterReject":"\niterReject( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n","iterReplicate":"\niterReplicate( iterator:Object, n:integer )\n Returns an iterator which replicates each iterated value `n` times.\n","iterReplicateBy":"\niterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n","iterRound":"\niterRound( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest integer.\n","iterRound2":"\niterRound2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two on a linear scale.\n","iterRound10":"\niterRound10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 on a linear scale.\n","iterRsqrt":"\niterRsqrt( iterator:Object )\n Returns an iterator which iteratively computes the reciprocal (inverse)\n square root.\n","iterSawtoothWave":"\niterSawtoothWave( [options:Object] )\n Returns an iterator which generates a sawtooth wave.\n","iterShift":"\niterShift( iterator:Object[, clbk:Function[, thisArg:any]] )\n Returns an iterator which skips the first value of a provided iterator.\n","iterSignum":"\niterSignum( iterator:Object )\n Returns an iterator which iteratively evaluates the signum function.\n","iterSin":"\niterSin( iterator:Object )\n Returns an iterator which iteratively computes the sine.\n","iterSinc":"\niterSinc( iterator:Object )\n Returns an iterator which iteratively computes the normalized cardinal sine.\n","iterSineWave":"\niterSineWave( [options:Object] )\n Returns an iterator which generates a sine wave.\n","iterSinh":"\niterSinh( iterator:Object )\n Returns an iterator which iteratively evaluates the hyperbolic sine.\n","iterSinpi":"\niterSinpi( iterator:Object )\n Returns an iterator which computes the sine of each iterated value times π.\n","iterSlice":"\niterSlice( iterator:Object[, begin:integer[, end:integer]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n","iterSome":"\niterSome( iterator:Object, n:number )\n Tests whether at least `n` iterated values are truthy.\n","iterSomeBy":"\niterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n","iterSpence":"\niterSpence( iterator:Object )\n Returns an iterator which iteratively evaluates Spence's function.\n","iterSqrt":"\niterSqrt( iterator:Object )\n Returns an iterator which iteratively computes the principal square root.\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator:Object )\n Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n accurately for small `x`.\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options:Object] )\n Returns an iterator which generates a sequence of squared triangular\n numbers.\n","iterSquaresSeq":"\niterSquaresSeq( [options:Object] )\n Returns an iterator which generates a sequence of squares.\n","iterSquareWave":"\niterSquareWave( [options:Object] )\n Returns an iterator which generates a square wave.\n","iterstdev":"\niterstdev( iterator:Object[, mean:number] )\n Computes a correct sample standard deviation over all iterated values.\n","iterStep":"\niterStep( start:number, increment:number[, N:number] )\n Returns an iterator which returns a sequence of numbers according to a\n specified increment.\n","iterStrided":"\niterStrided( iterator:Object, stride:integer[, offset:integer[, \n eager:boolean]] )\n Returns an iterator which steps by a specified amount.\n","iterStridedBy":"\niterStridedBy( iterator:Object, fcn:Function[, offset:integer[, \n eager:boolean]][, thisArg:any] )\n Returns an iterator which steps according to a provided callback function.\n","iterSubtract":"\niterSubtract( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n","itersum":"\nitersum( iterator:Object )\n Computes the sum of all iterated values.\n","itersumabs":"\nitersumabs( iterator:Object )\n Computes the sum of absolute values for all iterated values.\n","itersumabs2":"\nitersumabs2( iterator:Object )\n Computes the sum of squared absolute values for all iterated values.\n","iterTan":"\niterTan( iterator:Object )\n Returns an iterator which iteratively evaluates the tangent.\n","iterTanh":"\niterTanh( iterator:Object )\n Returns an iterator which iteratively evaluates the hyperbolic tangent.\n","iterThunk":"\niterThunk( iterFcn:Function[, ...args:any] )\n Returns an iterator \"thunk\".\n","iterTriangleWave":"\niterTriangleWave( [options:Object] )\n Returns an iterator which generates a triangle wave.\n","iterTriangularSeq":"\niterTriangularSeq( [options:Object] )\n Returns an iterator which generates a sequence of triangular numbers.\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options:Object] )\n Returns an iterator which generates a Tribonacci sequence.\n \n The returned iterator can only generate the first 64 Tribonacci numbers, as\n larger Tribonacci numbers cannot be safely represented in double-precision\n floating-point format.\n","iterTrigamma":"\niterTrigamma( iterator:Object )\n Returns an iterator which iteratively evaluates the trigamma function.\n","iterTrunc":"\niterTrunc( iterator:Object )\n Returns an iterator which rounds each iterated value toward zero.\n","iterTrunc2":"\niterTrunc2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward zero.\n","iterTrunc10":"\niterTrunc10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward zero.\n","iterUnion":"\niterUnion( iter0:Object, ...iterator:Object )\n Returns an iterator which returns the union of two or more iterators.\n","iterUnique":"\niterUnique( iterator:Object )\n Returns an iterator which returns unique values.\n","iterUniqueBy":"\niterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which returns unique values according to a predicate\n function.\n","iterUniqueByHash":"\niterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )\n Returns an iterator which returns unique values according to a hash\n function.\n","iterUnitspace":"\niterUnitspace( start:number[, stop:number] )\n Returns an iterator which returns numbers incremented by one.\n","iterUnshift":"\niterUnshift( iterator:Object, ...items:any )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n","iterUntilEach":"\niterUntilEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n","itervariance":"\nitervariance( iterator:Object[, mean:number] )\n Computes an unbiased sample variance over all iterated values.\n","iterVercos":"\niterVercos( iterator:Object )\n Returns an iterator which iteratively computes the versed cosine.\n","iterVersin":"\niterVersin( iterator:Object )\n Returns an iterator which iteratively computes the versed sine.\n","iterWhileEach":"\niterWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n","iterZeta":"\niterZeta( iterator:Object )\n Returns an iterator which iteratively evaluates the Riemann zeta function.\n","joinStream":"\njoinStream( [options:Object] )\n Returns a transform stream which joins streamed data.\n","joinStream.factory":"\njoinStream.factory( [options:Object] )\n Returns a function for creating transform streams for joined streamed data.\n","joinStream.objectMode":"\njoinStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n","kde2d":"\nkde2d( x:Array, y:Array[, options:Object] )\n Two-dimensional kernel density estimation.\n","kebabcase":"\nkebabcase( str:string )\n Converts a string to kebab case.\n","keyBy":"\nkeyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n","keyByRight":"\nkeyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n","keysIn":"\nkeysIn( obj:any )\n Returns an array of an object's own and inherited enumerable property\n names.\n","kruskalTest":"\nkruskalTest( ...x:Array[, options:Object] )\n Computes the Kruskal-Wallis test for equal medians.\n","kstest":"\nkstest( x:Array, y:Function|string[, ...params:number][, \n options:Object] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n","last":"\nlast( str:string[, n:integer][, options:Object] )\n Returns the last character(s) of a string.\n","leveneTest":"\nleveneTest( x:Array[, ...y:Array[, options:Object]] )\n Computes Levene's test for equal variances.\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n","linspace":"\nlinspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, \n options:Object] )\n Generates a linearly spaced array over a specified interval.\n","linspace.assign":"\nlinspace.assign( start:number|ComplexLike, stop:number|ComplexLike, \n out:ArrayLikeObject[, options:Object] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n","LN2":"\nLN2\n Natural logarithm of `2`.\n","LN10":"\nLN10\n Natural logarithm of `10`.\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n","logspace":"\nlogspace( a:number, b:number[, length:integer] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n","lowercase":"\nlowercase( str:string )\n Converts a string to lowercase.\n","lowercaseKeys":"\nlowercaseKeys( obj:Object )\n Converts each object key to lowercase.\n","lowess":"\nlowess( x:Array, y:Array[, options:Object] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n","lpad":"\nlpad( str:string, len:integer[, pad:string] )\n Left pads a string such that the padded string has a length of at least\n `len`.\n","ltrim":"\nltrim( str:string )\n Trims whitespace from the beginning of a string.\n","ltrimN":"\nltrimN( str:string, n:integer[, chars:Array|string] )\n Trims `n` characters from the beginning of a string.\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n","map":"\nmap( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array.\n","map.assign":"\nmap.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n","map2":"\nmap2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n thisArg:any] )\n Applies a function to elements in two input arrays and assigns the results\n to a new array.\n","map2.assign":"\nmap2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n","map2d":"\nmap2d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in an array of arrays and assigns\n the result to a nested element in a new array of arrays.\n","map2Right":"\nmap2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n thisArg:any] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to a new array.\n","map2Right.assign":"\nmap2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n","map3d":"\nmap3d( arr:ArrayLikeObject>, fcn:Function[, \n thisArg:any] )\n Applies a function to each nested element in a three-dimensional nested\n array and assigns the result to a nested element in a new three-dimensional\n nested array.\n","map4d":"\nmap4d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in a four-dimensional nested array\n and assigns the result to a nested element in a new four-dimensional nested\n array.\n","map5d":"\nmap5d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in a five-dimensional nested array\n and assigns the result to a nested element in a new five-dimensional nested\n array.\n","mapArguments":"\nmapArguments( fcn:Function, clbk:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function after\n transforming arguments according to a callback function.\n","mapFun":"\nmapFun( fcn:Function, n:integer[, thisArg:any] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n","mapFunAsync":"\nmapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n","mapKeys":"\nmapKeys( obj:Object, transform:Function )\n Maps keys from one object to a new object having the same values.\n","mapKeysAsync":"\nmapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )\n Maps keys from one object to a new object having the same values.\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options:Object,] transform:Function )\n Returns a function which maps keys from one object to a new object having\n the same values.\n","mapReduce":"\nmapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n reducer:Function[, thisArg:any] )\n Performs a map-reduce operation for each element in an array and returns the\n accumulated result.\n","mapReduceRight":"\nmapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n reducer:Function[, thisArg:any] )\n Performs a map-reduce operation for each element in an array while iterating\n from right to left and returns the accumulated result.\n","mapRight":"\nmapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array, iterating from right to left.\n","mapRight.assign":"\nmapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n","mapValues":"\nmapValues( obj:Object, transform:Function )\n Maps values from one object to a new object having the same keys.\n","mapValuesAsync":"\nmapValuesAsync( obj:Object, [options:Object,] transform:Function, \n done:Function )\n Maps values from one object to a new object having the same keys.\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options:Object,] transform:Function )\n Returns a function which maps values from one object to a new object having\n the same keys.\n","maskArguments":"\nmaskArguments( fcn:Function, mask:ArrayLikeObject[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a specified mask.\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x:ndarray, shape:ArrayLikeObject )\n Broadcasts an ndarray to a specified shape if and only if the specified\n shape differs from the provided ndarray's shape.\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays:ndarray|ArrayLikeObject )\n Broadcasts ndarrays to a common shape.\n","memoize":"\nmemoize( fcn:Function[, hashFunction:Function] )\n Returns a memoized function.\n","merge":"\nmerge( target:Object, ...source:Object )\n Merges objects into a target object.\n","merge.factory":"\nmerge.factory( options:Object )\n Returns a function for merging and extending objects.\n","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options:Object] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n","minutesInMonth":"\nminutesInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of minutes in a month.\n","minutesInYear":"\nminutesInYear( [value:integer|Date] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n","moveProperty":"\nmoveProperty( source:Object, prop:string, target:Object )\n Moves a property from one object to another object.\n","MultiSlice":"\nMultiSlice( ...slice )\n Returns a multi-slice.\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n","namedtypedtuple":"\nnamedtypedtuple( fields:Array[, options:Object] )\n Returns a named typed tuple factory.\n","NAN":"\nNAN\n Double-precision floating-point NaN.\n","naryFunction":"\nnaryFunction( fcn:Function, arity:integer[, thisArg:any] )\n Returns a function that applies a specified number of arguments to a\n provided function.\n","nativeClass":"\nnativeClass( value:any )\n Returns a string value indicating a specification defined classification of\n an object.\n","ndarray":"\nndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string[, options:Object] )\n Returns an ndarray.\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","ndarray.prototype.data":"\nndarray.prototype.data\n Pointer to the underlying data buffer.\n","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n Underlying data type.\n","ndarray.prototype.flags":"\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","ndarray.prototype.length":"\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n Number of dimensions.\n","ndarray.prototype.offset":"\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","ndarray.prototype.order":"\nndarray.prototype.order\n Array order.\n","ndarray.prototype.shape":"\nndarray.prototype.shape\n Array shape.\n","ndarray.prototype.strides":"\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","ndarray.prototype.get":"\nndarray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","ndarray.prototype.iget":"\nndarray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","ndarray.prototype.set":"\nndarray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","ndarray.prototype.iset":"\nndarray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","ndarray.prototype.toString":"\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n","ndarray2array":"\nndarray2array( x:ndarray )\n Converts an ndarray to a generic array.\n","ndarray2fancy":"\nndarray2fancy( x:ndarray[, options:Object] )\n Converts an ndarray to an object supporting fancy indexing.\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options:Object] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n","ndarray2fancy.idx":"\nndarray2fancy.idx( x:ndarray[, options:Object] )\n Wraps a provided ndarray as an ndarray index object.\n","ndarray2json":"\nndarray2json( x:ndarray )\n Serializes an ndarray as a JSON object.\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x:ndarray )\n Returns the underlying data buffer of a provided ndarray.\n","ndarrayDataType":"\nndarrayDataType( x:ndarray )\n Returns the data type of a provided ndarray.\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind:string] )\n Returns a list of ndarray data types.\n","ndarrayDataTypes.binary":"\nndarrayDataTypes.binary\n Read-only property returning a data type instance representing a binary data\n type.\n","ndarrayDataTypes.boolean":"\nndarrayDataTypes.boolean\n Read-only property returning a data type instance representing a boolean\n data type.\n","ndarrayDataTypes.complex32":"\nndarrayDataTypes.complex32\n Read-only property returning a data type instance representing a half-\n precision complex floating-point number data type.\n","ndarrayDataTypes.complex64":"\nndarrayDataTypes.complex64\n Read-only property returning a data type instance representing a single-\n precision complex floating-point number data type.\n","ndarrayDataTypes.complex128":"\nndarrayDataTypes.complex128\n Read-only property returning a data type instance representing a double-\n precision complex floating-point number data type.\n","ndarrayDataTypes.float16":"\nndarrayDataTypes.float16\n Read-only property returning a data type instance representing a half-\n precision real-valued floating-point number data type.\n","ndarrayDataTypes.float32":"\nndarrayDataTypes.float32\n Read-only property returning a data type instance representing a single-\n precision real-valued floating-point number data type.\n","ndarrayDataTypes.float64":"\nndarrayDataTypes.float64\n Read-only property returning a data type instance representing a double-\n precision real-valued floating-point number data type.\n","ndarrayDataTypes.generic":"\nndarrayDataTypes.generic\n Read-only property returning a data type instance representing a \"generic\"\n data type.\n","ndarrayDataTypes.int8":"\nndarrayDataTypes.int8\n Read-only property returning a data type instance representing a signed\n 8-bit integer data type.\n","ndarrayDataTypes.int16":"\nndarrayDataTypes.int16\n Read-only property returning a data type instance representing a signed\n 16-bit integer data type.\n","ndarrayDataTypes.int32":"\nndarrayDataTypes.int32\n Read-only property returning a data type instance representing a signed\n 32-bit integer data type.\n","ndarrayDataTypes.uint8":"\nndarrayDataTypes.uint8\n Read-only property returning a data type instance representing an unsigned\n 8-bit integer data type.\n","ndarrayDataTypes.uint8c":"\nndarrayDataTypes.uint8c\n Read-only property returning a data type instance representing an unsigned\n clamped 8-bit integer data type.\n","ndarrayDataTypes.uint16":"\nndarrayDataTypes.uint16\n Read-only property returning a data type instance representing an unsigned\n 16-bit integer data type.\n","ndarrayDataTypes.uint32":"\nndarrayDataTypes.uint32\n Read-only property returning a data type instance representing an unsigned\n 32-bit integer data type.\n","ndarrayDispatch":"\nndarrayDispatch( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns an ndarray function interface which performs multiple dispatch.\n","ndarrayFlag":"\nndarrayFlag( x:ndarray, name:string|symbol )\n Returns a specified flag for a provided ndarray.\n","ndarrayFlags":"\nndarrayFlags( x:ndarray )\n Returns the flags of a provided ndarray.\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x:ndarrayLike[, options:Object] )\n Converts an ndarray-like object to an ndarray.\n","ndarrayMinDataType":"\nndarrayMinDataType( value:any )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast and, for floating-point data types, can be downcast.\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype:any] )\n Returns the next larger ndarray data type of the same kind.\n","ndarrayOffset":"\nndarrayOffset( x:ndarray )\n Returns the index offset specifying the underlying buffer index of the first\n iterated ndarray element.\n","ndarrayOrder":"\nndarrayOrder( x:ndarray )\n Returns the layout order of a provided ndarray.\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n","ndarrayShape":"\nndarrayShape( x:ndarray )\n Returns the shape of a provided ndarray.\n","ndarrayStride":"\nndarrayStride( x:ndarray, dim:integer )\n Returns the stride along a specified dimension for a provided ndarray.\n","ndarrayStrides":"\nndarrayStrides( x:ndarray )\n Returns the strides of a provided ndarray.\n","ndat":"\nndat( x:ndarray[, ...indices:integer] )\n Returns an ndarray element.\n","ndempty":"\nndempty( shape:ArrayLikeObject|integer[, options:Object] )\n Returns an uninitialized ndarray having a specified shape and data type.\n","ndemptyLike":"\nndemptyLike( x:ndarray[, options:Object] )\n Returns an uninitialized ndarray having the same shape and data type as a\n provided input ndarray.\n","ndfill":"\nndfill( x:ndarrayLike, value:any )\n Fills an input ndarray with a specified value.\n","ndfillBy":"\nndfillBy( x:ndarrayLike, fcn:Function[, thisArg:any] )\n Fills an input ndarray according to a callback function.\n","ndfilter":"\nndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n Returns a shallow copy of an ndarray containing only those elements which\n pass a test implemented by a predicate function.\n","ndfilterMap":"\nndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n Filters and maps elements in an input ndarray to elements in a new output\n ndarray according to a callback function.\n","ndforEach":"\nndforEach( x:ndarray, fcn:Function[, thisArg:any] )\n Invokes a callback function once for each ndarray element.\n","ndims":"\nndims( x:ndarray )\n Returns the number of ndarray dimensions.\n","ndindex":"\nndindex( x:ndarray[, options:Object] )\n Wraps a provided array as an ndarray index object.\n","ndindex.free":"\nndindex.free( id:string )\n Frees the instance associated with a provided identifier.\n","ndindex.get":"\nndindex.get( id:string )\n Returns the ndarray associated with the instance having a provided\n identifier.\n","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x:ndarray[, options:Object] )\n Returns an ndarray index containing Cartesian indices.\n","ndindex.linearIndex":"\nndindex.linearIndex( x:ndarray[, options:Object] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n","ndindex.prototype.data":"\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n","ndindex.prototype.id":"\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n","ndindex.prototype.kind":"\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n","ndindex.prototype.type":"\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n","ndindex.prototype.toString":"\nndindex.prototype.toString()\n Serializes an instance as a string.\n","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n","nditer2arrayEach":"\nnditer2arrayEach( iterator:Object )\n Returns an iterator which converts each iterated ndarray to a generic array.\n","nditerColumnEntries":"\nnditerColumnEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, column] pairs for each column in a\n matrix (or stack of matrices).\n","nditerColumns":"\nnditerColumns( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each column in a matrix (or stack of\n matrices).\n","nditerEntries":"\nnditerEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, value] pairs for each element in a\n provided ndarray.\n","nditerIndices":"\nnditerIndices( shape:Array[, options:Object] )\n Returns an iterator which returns indices for use indexing into an ndarray\n having a specified shape.\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr:ArrayLike, ndims:integer )\n Returns an iterator which iterates over interleaved subarrays.\n","nditerMatrices":"\nnditerMatrices( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each matrix in a stack of matrices.\n","nditerMatrixEntries":"\nnditerMatrixEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, matrix] pairs for each matrix in a\n stack of matrices.\n","nditerRowEntries":"\nnditerRowEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, row] pairs for each row in a\n matrix (or stack of matrices).\n","nditerRows":"\nnditerRows( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each row in a matrix (or stack of\n matrices).\n","nditerSelectDimension":"\nnditerSelectDimension( x:ndarray, dim:integer[, options:Object] )\n Returns an iterator which iterates over each view along a specified\n dimension.\n","nditerStacks":"\nnditerStacks( x:ndarray, dims:Array[, options:Object] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays according to a list of specified stack dimensions.\n","nditerSubarrays":"\nnditerSubarrays( x:ndarray, ndims:integer[, options:Object] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays.\n","nditerValues":"\nnditerValues( x:ndarray[, options:Object] )\n Returns an iterator which returns individual elements from a provided\n ndarray.\n","ndmap":"\nndmap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n Applies a callback function to elements in an input ndarray and assigns\n results to elements in a new output ndarray.\n","ndreject":"\nndreject( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n Returns a shallow copy of an ndarray containing only those elements which\n fail a test implemented by a predicate function.\n","ndslice":"\nndslice( x:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, \n options:Object] )\n Returns a read-only view of an input ndarray.\n","ndsliceAssign":"\nndsliceAssign( x:ndarray, y:ndarray, \n ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )\n Assigns element values from a broadcasted input ndarray to corresponding\n elements in an output ndarray view.\n","ndsliceDimension":"\nndsliceDimension( x:ndarray, dim:integer, slice:Slice|integer|null|undefined[, \n options:Object] )\n Returns a read-only view of an input ndarray when sliced along a specified\n dimension.\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x:ndarray, dim:integer, start:integer[, options:Object] )\n Returns a read-only shifted view of an input ndarray along a specified\n dimension.\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x:ndarray, dim:integer, stop:integer[, options:Object] )\n Returns a read-only truncated view of an input ndarray along a specified\n dimension.\n","ndsliceFrom":"\nndsliceFrom( x:ndarray, ...start:null|void|integer[, options:Object] )\n Returns a read-only shifted view of an input ndarray.\n","ndsliceTo":"\nndsliceTo( x:ndarray, ...stop:null|void|integer[, options:Object] )\n Returns a read-only truncated view of an input ndarray.\n","ndzeros":"\nndzeros( shape:ArrayLikeObject|integer[, options:Object] )\n Returns a zero-filled ndarray having a specified shape and data type.\n","ndzerosLike":"\nndzerosLike( x:ndarray[, options:Object] )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str:string[, fromIndex:integer] )\n Returns the next extended grapheme cluster break in a string after a\n specified position.\n","nextTick":"\nnextTick( clbk[, ...args] )\n Adds a callback to the \"next tick queue\".\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n","none":"\nnone( collection:Array|TypedArray|Object )\n Tests whether all elements in a collection are falsy.\n","noneBy":"\nnoneBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n","noneByAsync":"\nnoneByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n","noneByAsync.factory":"\nnoneByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n","noneByRight":"\nnoneByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n","noneByRightAsync":"\nnoneByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n","noneInBy":"\nnoneInBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every property in an object fails a test implemented by a\n predicate function.\n","nonEnumerableProperties":"\nnonEnumerableProperties( value:any )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value:any )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value:any )\n Returns an array of an object's own non-enumerable property names.\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value:any )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value:any )\n Returns an array of an object's own non-enumerable symbol properties.\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n","noneOwnBy":"\nnoneOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every own property of an object fails a test implemented\n by a predicate function.\n","nonIndexKeys":"\nnonIndexKeys( obj:any )\n Returns an array of an object's own enumerable property names which are not\n integer indices.\n","noop":"\nnoop()\n A function which does nothing.\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n","num2words":"\nnum2words( value:integer[, options:Object] )\n Converts a number to a word representation.\n","Number":"\nNumber( value:number )\n Returns a Number object.\n","numel":"\nnumel( x:ndarray )\n Returns the number of elements in an ndarray.\n","numelDimension":"\nnumelDimension( x:ndarray, dim:integer )\n Returns the size (i.e., number of elements) of a specified dimension for a\n provided ndarray.\n","numGraphemeClusters":"\nnumGraphemeClusters( str:string )\n Returns the number of grapheme clusters in a string.\n","Object":"\nObject( value:any )\n Returns an object.\n","Object.assign":"\nObject.assign( target:Object, ...sources:Object )\n Assigns enumerable and own properties from source objects to a target\n object.\n","Object.create":"\nObject.create( prototype:Object, properties:Object )\n Creates a new object with a specified prototype object and properties.\n","Object.defineProperties":"\nObject.defineProperties( obj:Object, properties:Object )\n Defines properties for an object.\n","Object.defineProperty":"\nObject.defineProperty( obj:Object, key:string, descriptor:Object )\n Defines a property for an object.\n","Object.entries":"\nObject.entries( obj:Object )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n","Object.freeze":"\nObject.freeze( obj:Object )\n Freezes an object.\n","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj:Object, key:string )\n Returns an object's own property descriptor.\n","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj:Object )\n Returns an object's own property descriptors.\n","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj:Object )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj:Object )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj:Object )\n Returns an object's prototype.\n","Object.hasOwn":"\nObject.hasOwn( obj:Object, p:string )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n","Object.is":"\nObject.is( value1:any, value2:any )\n Returns a boolean indicating whether two values are the same value.\n","Object.isExtensible":"\nObject.isExtensible( obj:Object )\n Returns a boolean indicating whether an object is extensible.\n","Object.isFrozen":"\nObject.isFrozen( obj:Object )\n Returns a boolean indicating whether an object is frozen.\n","Object.isSealed":"\nObject.isSealed( obj:Object )\n Returns a boolean indicating whether an object is sealed.\n","Object.keys":"\nObject.keys( obj:Object )\n Returns an array of an object's own enumerable string-keyed property\n names.\n","Object.preventExtensions":"\nObject.preventExtensions( obj:Object )\n Prevents the addition of new properties to an object.\n","Object.seal":"\nObject.seal( obj:Object )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj:Object, proto:Object )\n Sets an object's prototype.\n","Object.values":"\nObject.values( obj:Object )\n Returns an array of an object's own enumerable property values.\n","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n","Object.prototype.toString":"\nObject.prototype.toString()\n Returns a string representing the object.\n","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p:string )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj:Object )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p:string )\n Returns a boolean indicating whether an object's property is enumerable.\n","Object.prototype.constructor":"\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n","objectEntries":"\nobjectEntries( obj:ObjectLike )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n","objectEntriesIn":"\nobjectEntriesIn( obj:ObjectLike )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n","objectFromEntries":"\nobjectFromEntries( entries:Array )\n Creates an object from an array of key-value pairs.\n","objectInverse":"\nobjectInverse( obj:ObjectLike[, options:Object] )\n Inverts an object, such that keys become values and values become keys.\n","objectInverseBy":"\nobjectInverseBy( obj:ObjectLike, [options:Object,] transform:Function )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n","objectKeys":"\nobjectKeys( value:any )\n Returns an array of an object's own enumerable property names.\n","objectValues":"\nobjectValues( obj:ObjectLike )\n Returns an array of an object's own enumerable property values.\n","objectValuesIn":"\nobjectValuesIn( obj:ObjectLike )\n Returns an array of an object's own and inherited enumerable property\n values.\n","omit":"\nomit( obj:Object, keys:string|Array )\n Returns a partial object copy excluding specified keys.\n","omitBy":"\nomitBy( obj:Object, predicate:Function )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n","open":"\nopen( path:string|Buffer[, flags:string|number[, mode:integer]], clbk:Function )\n Asynchronously opens a file.\n","open.sync":"\nopen.sync( path:string|Buffer[, flags:string|number[, mode:integer]] )\n Synchronously opens a file.\n","openURL":"\nopenURL( url:string )\n Opens a URL in a user's default browser.\n","ordinalize":"\nordinalize( value:string|integer[, options:Object] )\n Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n","pad":"\npad( str:string, len:integer[, options:Object] )\n Pads a `string` such that the padded `string` has length `len`.\n","padjust":"\npadjust( pvals:Array, method:string[, comparisons:integer] )\n Adjusts supplied p-values for multiple comparisons via a specified method.\n","papply":"\npapply( fcn:Function, ...args:any )\n Returns a function of smaller arity by partially applying arguments.\n","papplyRight":"\npapplyRight( fcn:Function, ...args:any )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n","parallel":"\nparallel( files:Array, [options:Object,] clbk:Function )\n Executes scripts in parallel.\n","parseJSON":"\nparseJSON( str:string[, reviver:Function] )\n Attempts to parse a string as JSON.\n","pascalcase":"\npascalcase( str:string )\n Converts a string to Pascal case.\n","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n","pcorrtest":"\npcorrtest( x:Array, y:Array[, options:Object] )\n Computes a Pearson product-moment correlation test between paired samples.\n","percentEncode":"\npercentEncode( str:string )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","PHI":"\nPHI\n Golden ratio.\n","PI":"\nPI\n The mathematical constant `π`.\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n","pick":"\npick( obj:Object, keys:string|Array )\n Returns a partial object copy containing only specified keys.\n","pickArguments":"\npickArguments( fcn:Function, indices:Array[, thisArg:any] )\n Returns a function that applies specified arguments to a provided function.\n","pickBy":"\npickBy( obj:Object, predicate:Function )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n","pkg2alias":"\npkg2alias( pkg:string )\n Returns the alias associated with a specified package name.\n","pkg2related":"\npkg2related( pkg:string )\n Returns package names related to a specified package name.\n","pkg2standalone":"\npkg2standalone( pkg:string )\n Returns the standalone package name associated with a provided internal\n package name.\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n","plot":"\nplot( [x:Array|Array, y:Array|Array,] [options:Object] )\n Returns a plot instance for creating 2-dimensional plots.\n","Plot":"\nPlot( [x:Array|Array, y:Array|Array,] [options:Object] )\n Returns a plot instance for creating 2-dimensional plots.\n","pluck":"\npluck( arr:Array, prop:string[, options:Object] )\n Extracts a property value from each element of an object array.\n","pop":"\npop( collection:Array|TypedArray|Object )\n Removes and returns the last element of a collection.\n","porterStemmer":"\nporterStemmer( word:string )\n Extracts the stem of a given word.\n","prepend":"\nprepend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the beginning of another collection.\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str:string[, fromIndex:integer] )\n Returns the previous extended grapheme cluster break in a string before a\n specified position.\n","PRIMES_100K":"\nPRIMES_100K()\n Returns an array containing the first 100,000 prime numbers.\n","properties":"\nproperties( value:any )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n","propertiesIn":"\npropertiesIn( value:any )\n Returns an array of an object's own and inherited property names and\n symbols.\n","propertyDescriptor":"\npropertyDescriptor( value:any, property:string|symbol )\n Returns a property descriptor for an object's own property.\n","propertyDescriptorIn":"\npropertyDescriptorIn( value:any, property:string|symbol )\n Returns a property descriptor for an object's own or inherited property.\n","propertyDescriptors":"\npropertyDescriptors( value:any )\n Returns an object's own property descriptors.\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value:any )\n Returns an object's own and inherited property descriptors.\n","propertyNames":"\npropertyNames( value:any )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n","propertyNamesIn":"\npropertyNamesIn( value:any )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n","propertySymbols":"\npropertySymbols( value:any )\n Returns an array of an object's own symbol properties.\n","propertySymbolsIn":"\npropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited symbol properties.\n","Proxy":"\nProxy( target:Object, handlers:Object )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n","Proxy.revocable":"\nProxy.revocable( target:Object, handlers:Object )\n Returns a revocable proxy object.\n","push":"\npush( collection:Array|TypedArray|Object, ...items:any )\n Adds one or more elements to the end of a collection.\n","quarterOfYear":"\nquarterOfYear( [month:integer|string|Date] )\n Returns the quarter of the year.\n","random.array.arcsine":"\nrandom.array.arcsine( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an arcsine\n distribution.\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n Length of generator seed.\n","random.array.arcsine.state":"\nrandom.array.arcsine.state\n Generator state.\n","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n Length of generator state.\n","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n","random.array.bernoulli":"\nrandom.array.bernoulli( len:integer, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n Generator state.\n","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n Length of generator state.\n","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.array.beta":"\nrandom.array.beta( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a beta\n distribution.\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n","random.array.beta.seed":"\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n Length of generator seed.\n","random.array.beta.state":"\nrandom.array.beta.state\n Generator state.\n","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n Length of generator state.\n","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n","random.array.betaprime":"\nrandom.array.betaprime( len:integer, alpha:number, beta:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a beta prime\n distribution.\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n Length of generator seed.\n","random.array.betaprime.state":"\nrandom.array.betaprime.state\n Generator state.\n","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n Length of generator state.\n","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n","random.array.binomial":"\nrandom.array.binomial( len:integer, n:number, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a binomial\n distribution.\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n:number, p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n:number, p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n","random.array.binomial.seed":"\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n Length of generator seed.\n","random.array.binomial.state":"\nrandom.array.binomial.state\n Generator state.\n","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n Length of generator state.\n","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n","random.array.cauchy":"\nrandom.array.cauchy( len:integer, x0:number, gamma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Cauchy\n distribution.\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0:number, gamma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0:number, gamma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n Length of generator seed.\n","random.array.cauchy.state":"\nrandom.array.cauchy.state\n Generator state.\n","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n Length of generator state.\n","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n","random.array.chi":"\nrandom.array.chi( len:integer, k:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a chi\n distribution.\n","random.array.chi.assign":"\nrandom.array.chi.assign( k:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n","random.array.chi.factory":"\nrandom.array.chi.factory( [k:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n","random.array.chi.seed":"\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n Length of generator seed.\n","random.array.chi.state":"\nrandom.array.chi.state\n Generator state.\n","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n Length of generator state.\n","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n","random.array.chisquare":"\nrandom.array.chisquare( len:integer, k:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a chi-square\n distribution.\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n Length of generator seed.\n","random.array.chisquare.state":"\nrandom.array.chisquare.state\n Generator state.\n","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n Length of generator state.\n","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.array.cosine":"\nrandom.array.cosine( len:integer, mu:number, s:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu:number, s:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu:number, s:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n","random.array.cosine.seed":"\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n Length of generator seed.\n","random.array.cosine.state":"\nrandom.array.cosine.state\n Generator state.\n","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n Length of generator state.\n","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n","random.array.discreteUniform":"\nrandom.array.discreteUniform( len:integer, a:number, b:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a:number, b:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n Generator state.\n","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","random.array.erlang":"\nrandom.array.erlang( len:integer, k:number, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an Erlang\n distribution.\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k:number, lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k:number, lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n","random.array.erlang.seed":"\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n Length of generator seed.\n","random.array.erlang.state":"\nrandom.array.erlang.state\n Generator state.\n","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n Length of generator state.\n","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n","random.array.exponential":"\nrandom.array.exponential( len:integer, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an exponential\n distribution.\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.array.exponential.seed":"\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n Length of generator seed.\n","random.array.exponential.state":"\nrandom.array.exponential.state\n Generator state.\n","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n Length of generator state.\n","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n","random.array.f":"\nrandom.array.f( len:integer, d1:number, d2:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an F\n distribution.\n","random.array.f.assign":"\nrandom.array.f.assign( d1:number, d2:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n","random.array.f.factory":"\nrandom.array.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n","random.array.f.PRNG":"\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n","random.array.f.seed":"\nrandom.array.f.seed\n Pseudorandom number generator seed.\n","random.array.f.seedLength":"\nrandom.array.f.seedLength\n Length of generator seed.\n","random.array.f.state":"\nrandom.array.f.state\n Generator state.\n","random.array.f.stateLength":"\nrandom.array.f.stateLength\n Length of generator state.\n","random.array.f.byteLength":"\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n","random.array.frechet":"\nrandom.array.frechet( len:integer, alpha:number, s:number, m:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha:number, s:number, m:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha:number, s:number, m:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n","random.array.frechet.seed":"\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n Length of generator seed.\n","random.array.frechet.state":"\nrandom.array.frechet.state\n Generator state.\n","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n Length of generator state.\n","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n","random.array.gamma":"\nrandom.array.gamma( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a gamma\n distribution.\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n","random.array.gamma.seed":"\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n Length of generator seed.\n","random.array.gamma.state":"\nrandom.array.gamma.state\n Generator state.\n","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n Length of generator state.\n","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n","random.array.geometric":"\nrandom.array.geometric( len:integer, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a geometric\n distribution.\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.array.geometric.seed":"\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n Length of generator seed.\n","random.array.geometric.state":"\nrandom.array.geometric.state\n Generator state.\n","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n Length of generator state.\n","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n","random.array.gumbel":"\nrandom.array.gumbel( len:integer, mu:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n Length of generator seed.\n","random.array.gumbel.state":"\nrandom.array.gumbel.state\n Generator state.\n","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n Length of generator state.\n","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n","random.array.hypergeometric":"\nrandom.array.hypergeometric( len:integer, N:number, K:number, n:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N:number, K:number, n:number, \n out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N:number, K:number, n:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n Generator state.\n","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","random.array.invgamma":"\nrandom.array.invgamma( len:integer, alpha:number, beta:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n Length of generator seed.\n","random.array.invgamma.state":"\nrandom.array.invgamma.state\n Generator state.\n","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n Length of generator state.\n","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n double bounded distribution.\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n Generator state.\n","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","random.array.laplace":"\nrandom.array.laplace( len:integer, mu:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n","random.array.laplace.seed":"\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n Length of generator seed.\n","random.array.laplace.state":"\nrandom.array.laplace.state\n Generator state.\n","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n Length of generator state.\n","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n","random.array.levy":"\nrandom.array.levy( len:integer, mu:number, c:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Lévy\n distribution.\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu:number, c:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n","random.array.levy.factory":"\nrandom.array.levy.factory( [mu:number, c:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n","random.array.levy.seed":"\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n Length of generator seed.\n","random.array.levy.state":"\nrandom.array.levy.state\n Generator state.\n","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n Length of generator state.\n","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n","random.array.logistic":"\nrandom.array.logistic( len:integer, mu:number, s:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a logistic\n distribution.\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu:number, s:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu:number, s:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n","random.array.logistic.seed":"\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n Length of generator seed.\n","random.array.logistic.state":"\nrandom.array.logistic.state\n Generator state.\n","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n Length of generator state.\n","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n","random.array.lognormal":"\nrandom.array.lognormal( len:integer, mu:number, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a lognormal\n distribution.\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu:number, sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu:number, sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n Length of generator seed.\n","random.array.lognormal.state":"\nrandom.array.lognormal.state\n Generator state.\n","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n Length of generator state.\n","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n","random.array.minstd":"\nrandom.array.minstd( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n","random.array.minstd.seed":"\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n Length of generator seed.\n","random.array.minstd.state":"\nrandom.array.minstd.state\n Generator state.\n","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n Length of generator state.\n","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n Generator state.\n","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n","random.array.mt19937":"\nrandom.array.mt19937( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[0, 4294967295]`.\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n Length of generator seed.\n","random.array.mt19937.state":"\nrandom.array.mt19937.state\n Generator state.\n","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n Length of generator state.\n","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len:integer, r:number, p:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a negative\n binomial distribution.\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r:number, p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n Generator state.\n","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","random.array.normal":"\nrandom.array.normal( len:integer, mu:number, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a normal\n distribution.\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu:number, sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n","random.array.normal.factory":"\nrandom.array.normal.factory( [mu:number, sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n","random.array.normal.seed":"\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n Length of generator seed.\n","random.array.normal.state":"\nrandom.array.normal.state\n Generator state.\n","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n Length of generator state.\n","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n","random.array.pareto1":"\nrandom.array.pareto1( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n Length of generator seed.\n","random.array.pareto1.state":"\nrandom.array.pareto1.state\n Generator state.\n","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n Length of generator state.\n","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n","random.array.poisson":"\nrandom.array.poisson( len:integer, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Poisson\n distribution.\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.array.poisson.seed":"\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n Length of generator seed.\n","random.array.poisson.state":"\nrandom.array.poisson.state\n Generator state.\n","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n Length of generator state.\n","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n","random.array.randu":"\nrandom.array.randu( len:integer[, options:Object] )\n Returns an array containing uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options:Object] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n","random.array.randu.seed":"\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n Length of generator seed.\n","random.array.randu.state":"\nrandom.array.randu.state\n Generator state.\n","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n Length of generator state.\n","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n","random.array.rayleigh":"\nrandom.array.rayleigh( len:integer, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n Generator state.\n","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n Length of generator state.\n","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.array.t":"\nrandom.array.t( len:integer, v:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Student's t\n distribution.\n","random.array.t.assign":"\nrandom.array.t.assign( v:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n","random.array.t.factory":"\nrandom.array.t.factory( [v:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n","random.array.t.PRNG":"\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n","random.array.t.seed":"\nrandom.array.t.seed\n Pseudorandom number generator seed.\n","random.array.t.seedLength":"\nrandom.array.t.seedLength\n Length of generator seed.\n","random.array.t.state":"\nrandom.array.t.state\n Generator state.\n","random.array.t.stateLength":"\nrandom.array.t.stateLength\n Length of generator state.\n","random.array.t.byteLength":"\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n","random.array.triangular":"\nrandom.array.triangular( len:integer, a:number, b:number, c:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a triangular\n distribution.\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a:number, b:number, c:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n","random.array.triangular.seed":"\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n Length of generator seed.\n","random.array.triangular.state":"\nrandom.array.triangular.state\n Generator state.\n","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n Length of generator state.\n","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n","random.array.uniform":"\nrandom.array.uniform( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n","random.array.uniform.seed":"\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n Length of generator seed.\n","random.array.uniform.state":"\nrandom.array.uniform.state\n Generator state.\n","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n Length of generator state.\n","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n","random.array.weibull":"\nrandom.array.weibull( len:integer, k:number, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Weibull\n distribution.\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k:number, lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k:number, lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n","random.array.weibull.seed":"\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n Length of generator seed.\n","random.array.weibull.state":"\nrandom.array.weibull.state\n Generator state.\n","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n Length of generator state.\n","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n","random.iterators.arcsine":"\nrandom.iterators.arcsine( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.iterators.beta":"\nrandom.iterators.beta( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.iterators.binomial":"\nrandom.iterators.binomial( n:integer, p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0:number, Ɣ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n","random.iterators.chi":"\nrandom.iterators.chi( k:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ:number, s:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a:integer, b:integer[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n","random.iterators.erlang":"\nrandom.iterators.erlang( k:integer, λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.iterators.f":"\nrandom.iterators.f( d1:number, d2:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n","random.iterators.frechet":"\nrandom.iterators.frechet( α:number, s:number, m:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.iterators.gamma":"\nrandom.iterators.gamma( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n","random.iterators.geometric":"\nrandom.iterators.geometric( p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.iterators.levy":"\nrandom.iterators.levy( μ:number, c:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ:number, s:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ:number, σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r:number, p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n","random.iterators.normal":"\nrandom.iterators.normal( μ:number, σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n","random.iterators.randi":"\nrandom.iterators.randi( [options:Object] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n","random.iterators.randn":"\nrandom.iterators.randn( [options:Object] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n","random.iterators.randu":"\nrandom.iterators.randu( [options:Object] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n","random.iterators.t":"\nrandom.iterators.t( v:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n","random.iterators.triangular":"\nrandom.iterators.triangular( a:number, b:number, c:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.iterators.uniform":"\nrandom.iterators.uniform( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n","random.iterators.weibull":"\nrandom.iterators.weibull( k:number, λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n","random.streams.arcsine":"\nrandom.streams.arcsine( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n","random.streams.bernoulli":"\nrandom.streams.bernoulli( p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n","random.streams.beta":"\nrandom.streams.beta( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n","random.streams.betaprime":"\nrandom.streams.betaprime( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n","random.streams.binomial":"\nrandom.streams.binomial( n:integer, p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n:integer, p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n:integer, p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n","random.streams.cauchy":"\nrandom.streams.cauchy( x0:number, γ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0:number, γ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0:number, γ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n","random.streams.chi":"\nrandom.streams.chi( k:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n","random.streams.chisquare":"\nrandom.streams.chisquare( k:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n","random.streams.cosine":"\nrandom.streams.cosine( μ:number, s:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ:number, s:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ:number, s:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a:integer, b:integer[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a:integer, b:integer, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a:integer, b:integer[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n","random.streams.erlang":"\nrandom.streams.erlang( k:integer, λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k:number, λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k:number, λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n","random.streams.exponential":"\nrandom.streams.exponential( λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n","random.streams.f":"\nrandom.streams.f( d1:number, d2:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1:number, d2:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n","random.streams.frechet":"\nrandom.streams.frechet( α:number, s:number, m:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Fréchet distribution.\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α:number, s:number, m:number,]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α:number, s:number, m:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n","random.streams.gamma":"\nrandom.streams.gamma( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n","random.streams.geometric":"\nrandom.streams.geometric( p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n","random.streams.gumbel":"\nrandom.streams.gumbel( μ:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N:integer, K:integer, n:integer,]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n","random.streams.invgamma":"\nrandom.streams.invgamma( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.laplace":"\nrandom.streams.laplace( μ:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n","random.streams.levy":"\nrandom.streams.levy( μ:number, c:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ:number, c:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ:number, c:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n","random.streams.logistic":"\nrandom.streams.logistic( μ:number, s:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ:number, s:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ:number, s:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n","random.streams.lognormal":"\nrandom.streams.lognormal( μ:number, σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ:number, σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n","random.streams.minstd":"\nrandom.streams.minstd( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n","random.streams.mt19937":"\nrandom.streams.mt19937( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r:number, p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r:number, p:number, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r:integer, p:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n","random.streams.normal":"\nrandom.streams.normal( μ:number, σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ:number, σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n","random.streams.pareto1":"\nrandom.streams.pareto1( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n","random.streams.poisson":"\nrandom.streams.poisson( λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n","random.streams.randi":"\nrandom.streams.randi( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n","random.streams.randn":"\nrandom.streams.randn( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n","random.streams.randu":"\nrandom.streams.randu( [options:Object] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n","random.streams.t":"\nrandom.streams.t( v:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n","random.streams.triangular":"\nrandom.streams.triangular( a:number, b:number, c:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a:number, b:number, c:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n","random.streams.uniform":"\nrandom.streams.uniform( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n","random.streams.weibull":"\nrandom.streams.weibull( k:number, λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k:number, λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k:number, λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n","random.strided.arcsine":"\nrandom.strided.arcsine( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution.\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n","random.strided.bernoulli":"\nrandom.strided.bernoulli( N:integer, p:ArrayLikeObject, sp:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n Generator state.\n","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.strided.beta":"\nrandom.strided.beta( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution.\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n","random.strided.betaprime":"\nrandom.strided.betaprime( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n","random.strided.chi":"\nrandom.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution.\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n","random.strided.chi.seed":"\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n Length of generator seed.\n","random.strided.chi.state":"\nrandom.strided.chi.state\n Generator state.\n","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n Length of generator state.\n","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n","random.strided.chisquare":"\nrandom.strided.chisquare( N:integer, k:ArrayLikeObject, sk:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n Generator state.\n","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n Length of generator state.\n","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.strided.cosine":"\nrandom.strided.cosine( N:integer, mu:ArrayLikeObject, sm:integer, \n s:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution.\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, s:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, \n sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n","random.strided.exponential":"\nrandom.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution.\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, \n sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n Length of generator seed.\n","random.strided.exponential.state":"\nrandom.strided.exponential.state\n Generator state.\n","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n Length of generator state.\n","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n","random.strided.gamma":"\nrandom.strided.gamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution.\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n","random.strided.geometric":"\nrandom.strided.geometric( N:integer, p:ArrayLikeObject, sp:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution.\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n Length of generator seed.\n","random.strided.geometric.state":"\nrandom.strided.geometric.state\n Generator state.\n","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n Length of generator state.\n","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n","random.strided.invgamma":"\nrandom.strided.invgamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n","random.strided.lognormal":"\nrandom.strided.lognormal( N:integer, mu:ArrayLikeObject, sm:integer, \n sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n","random.strided.minstd":"\nrandom.strided.minstd( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N:integer, out:ArrayLikeObject, \n so:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.mt19937":"\nrandom.strided.mt19937( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive).\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.normal":"\nrandom.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, \n sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution.\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n","random.strided.poisson":"\nrandom.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution.\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, \n ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n Length of generator seed.\n","random.strided.poisson.state":"\nrandom.strided.poisson.state\n Generator state.\n","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n Length of generator state.\n","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n","random.strided.randu":"\nrandom.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n","random.strided.rayleigh":"\nrandom.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N:integer, sigma:ArrayLikeObject, ss:integer, \n os:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n Generator state.\n","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.strided.t":"\nrandom.strided.t( N:integer, v:ArrayLikeObject, sv:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution.\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N:integer, v:ArrayLikeObject, sv:integer, ov:integer, \n out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n","random.strided.t.factory":"\nrandom.strided.t.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n","random.strided.t.seed":"\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n Length of generator seed.\n","random.strided.t.state":"\nrandom.strided.t.state\n Generator state.\n","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n Length of generator state.\n","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n","random.strided.uniform":"\nrandom.strided.uniform( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n","random.strided.weibull":"\nrandom.strided.weibull( N:integer, k:ArrayLikeObject, sk:integer, \n lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution.\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n","ranks":"\nranks( arr:Array[, options:Object] )\n Computes the sample ranks for the values of an array-like object.\n","readDir":"\nreadDir( path:string|Buffer, clbk:Function )\n Asynchronously reads the contents of a directory.\n","readDir.sync":"\nreadDir.sync( path:string|Buffer )\n Synchronously reads the contents of a directory.\n","readFile":"\nreadFile( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n Asynchronously reads the entire contents of a file.\n","readFile.sync":"\nreadFile.sync( file:string|Buffer|integer[, options:Object|string] )\n Synchronously reads the entire contents of a file.\n","readFileList":"\nreadFileList( filepaths:Array[, options:Object|string], clbk:Function )\n Asynchronously reads the entire contents of each file in a file list.\n","readFileList.sync":"\nreadFileList.sync( filepaths:Array[, options:Object|string] )\n Synchronously reads the entire contents of each file in a file list.\n","readJSON":"\nreadJSON( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n Asynchronously reads a file as JSON.\n","readJSON.sync":"\nreadJSON.sync( file:string|Buffer|integer[, options:Object|string] )\n Synchronously reads a file as JSON.\n","readWASM":"\nreadWASM( file:string|Buffer|integer[, options:Object], clbk:Function )\n Asynchronously reads a file as WebAssembly.\n","readWASM.sync":"\nreadWASM.sync( file:string|Buffer|integer[, options:Object] )\n Synchronously reads a file as WebAssembly.\n","real":"\nreal( z:Complex128 )\n Returns the real component of a double-precision complex floating-point\n number.\n","realarray":"\nrealarray( [dtype:string] )\n Creates a typed array.\n\nrealarray( length:integer[, dtype:string] )\n Returns a typed array having a specified length.\n\nrealarray( typedarray:TypedArray[, dtype:string] )\n Creates a typed array from another typed array.\n\nrealarray( obj:Object[, dtype:string] )\n Creates a typed array from an array-like object or iterable.\n\nrealarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a typed array view of an ArrayBuffer.\n","realarrayCtors":"\nrealarrayCtors( dtype:string )\n Returns a typed array constructor.\n","realarrayDataTypes":"\nrealarrayDataTypes()\n Returns a list of typed array real-valued data types.\n","realf":"\nrealf( z:Complex64 )\n Returns the real component of a single-precision complex floating-point\n number.\n","realmax":"\nrealmax( dtype:string )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n","realmin":"\nrealmin( dtype:string )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n","reBasename":"\nreBasename( [platform:string] )\n Returns a regular expression to capture the last part of a path.\n","reBasename.REGEXP":"\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n","reBasenamePosix":"\nreBasenamePosix()\n Returns a regular expression to capture the last part of a POSIX path.\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n","reBasenameWindows":"\nreBasenameWindows()\n Returns a regular expression to capture the last part of a Windows path.\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n","reColorHexadecimal":"\nreColorHexadecimal( [mode:string] )\n Returns a regular expression to match a hexadecimal color.\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n","reDecimalNumber":"\nreDecimalNumber( [options:Object] )\n Returns a regular expression to match a decimal number.\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n","reDirname":"\nreDirname( [platform:string] )\n Returns a regular expression to capture a path dirname.\n","reDirname.REGEXP":"\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n","reDirnamePosix":"\nreDirnamePosix()\n Returns a regular expression to capture a POSIX path dirname.\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n","reDirnameWindows":"\nreDirnameWindows()\n Returns a regular expression to capture a Windows path dirname.\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n","reduce":"\nreduce( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n thisArg:any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","reduce2d":"\nreduce2d( arr:ArrayLikeObject, initial:ArrayLikeObject, \n reducer:Function[, thisArg:any] )\n Reduces the number of dimensions by one of a two-dimensional nested array by\n applying a function against an accumulator and each element along the\n innermost dimension and returning the accumulation results as a one-\n dimensional array.\n","reduceAsync":"\nreduceAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] \n reducer:Function, done:Function )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n","reduceAsync.factory":"\nreduceAsync.factory( [options:Object,] fcn:Function )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n","reduceRight":"\nreduceRight( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n thisArg:any] )\n Applies a function against an accumulator and each element in an array while\n iterating from right to left and returns the accumulated result.\n","reduceRightAsync":"\nreduceRightAsync( collection:Array|TypedArray|Object, initial:any, \n [options:Object,] reducer:Function, done:Function )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n","reDurationString":"\nreDurationString()\n Returns a regular expression to match a duration string.\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n Regular expression to match a duration string.\n","reEOL":"\nreEOL( [options:Object] )\n Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP":"\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n","reExtendedLengthPath":"\nreExtendedLengthPath()\n Returns a regular expression to test if a string is an extended-length path.\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n","reExtname":"\nreExtname( [platform:string] )\n Returns a regular expression to capture a filename extension.\n","reExtname.REGEXP":"\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n","reExtnamePosix":"\nreExtnamePosix\n Returns a regular expression to capture a POSIX filename extension.\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n","reExtnameWindows":"\nreExtnameWindows\n Returns a regular expression to capture a Windows filename extension.\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n","reFilename":"\nreFilename( [platform:string] )\n Regular expression to split a filename.\n","reFilename.REGEXP":"\nreFilename.REGEXP\n Regular expression to split a filename.\n","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n","reFilenamePosix":"\nreFilenamePosix()\n Returns a regular expression to split a POSIX filename.\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n","reFilenameWindows":"\nreFilenameWindows()\n Returns a regular expression to split a Windows filename.\n","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n","reFromString":"\nreFromString( str:string )\n Parses a regular expression string and returns a new regular expression.\n","reFunctionName":"\nreFunctionName()\n Return a regular expression to capture a function name.\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n","regexp2json":"\nregexp2json( re:RegExp )\n Returns a JSON representation of a regular expression.\n","reim":"\nreim( z:Complex128 )\n Returns the real and imaginary components of a double-precision complex\n floating-point number.\n","reimf":"\nreimf( z:Complex64 )\n Returns the real and imaginary components of a single-precision complex\n floating-point number.\n","rejectArguments":"\nrejectArguments( fcn:Function, predicate:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n","removeFirst":"\nremoveFirst( str:string[, n:integer][, options:Object] )\n Removes the first character(s) of a `string`.\n","removeLast":"\nremoveLast( str:string[, n:integer][, options:Object] )\n Removes the last character(s) of a `string`.\n","removePunctuation":"\nremovePunctuation( str:string )\n Removes punctuation characters from a `string`.\n","removeUTF8BOM":"\nremoveUTF8BOM( str:string )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n","removeWords":"\nremoveWords( str:string, words:Array[, ignoreCase:boolean] )\n Removes all occurrences of the given words from a `string`.\n","rename":"\nrename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )\n Asynchronously renames a file.\n","rename.sync":"\nrename.sync( oldPath:string|Buffer, newPath:string|Buffer )\n Synchronously renames a file.\n","reNativeFunction":"\nreNativeFunction()\n Returns a regular expression to match a native function.\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n","reorderArguments":"\nreorderArguments( fcn:Function, indices:Array[, thisArg:any] )\n Returns a function that invokes a provided function with reordered\n arguments.\n","repeat":"\nrepeat( str:string, n:integer )\n Repeats a string `n` times and returns the concatenated result.\n","replace":"\nreplace( str:string, search:string|RegExp, newval:string|Function )\n Replaces search occurrences with a replacement string.\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n Replaces the substring before the first occurrence of a specified search\n string. \n","reRegExp":"\nreRegExp()\n Returns a regular expression to parse a regular expression string.\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n","rescape":"\nrescape( str:string )\n Escapes a regular expression string.\n","reSemVer":"\nreSemVer()\n Returns a regular expression to match a semantic version string.\n","reSemVer.REGEXP":"\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n","resolveParentPath":"\nresolveParentPath( path:string[, options:Object], clbk:Function )\n Asynchronously resolves a path by walking parent directories.\n","resolveParentPath.sync":"\nresolveParentPath.sync( path:string[, options:Object] )\n Synchronously resolves a path by walking parent directories.\n","resolveParentPathBy":"\nresolveParentPathBy( path:string[, options:Object], predicate:Function, \n clbk:Function )\n Asynchronously resolves a path according to a predicate function by walking\n parent directories.\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path:string[, options:Object], predicate:Function )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n","reUncPath":"\nreUncPath()\n Return a regular expression to parse a UNC path.\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n Returns a regular expression to match a UTF-16 surrogate pair.\n","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n Returns a regular expression to match an unpaired UTF-16 surrogate.\n","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n","reverseArguments":"\nreverseArguments( fcn:Function[, thisArg:any] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n","reverseString":"\nreverseString( str:string[, options:Object] )\n Reverses a string.\n","reviveBasePRNG":"\nreviveBasePRNG( key:string, value:any )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n","reviveBuffer":"\nreviveBuffer( key:string, value:any )\n Revives a JSON-serialized Buffer.\n","reviveComplex":"\nreviveComplex( key:string, value:any )\n Revives a JSON-serialized complex number.\n","reviveComplex64":"\nreviveComplex64( key:string, value:any )\n Revives a JSON-serialized 64-bit complex number.\n","reviveComplex128":"\nreviveComplex128( key:string, value:any )\n Revives a JSON-serialized 128-bit complex number.\n","reviveError":"\nreviveError( key:string, value:any )\n Revives a JSON-serialized error object.\n","reviveRegExp":"\nreviveRegExp( key:string, value:any )\n Revives a JSON-serialized regular expression.\n","reviveTypedArray":"\nreviveTypedArray( key:string, value:any )\n Revives a JSON-serialized typed array.\n","reWhitespace":"\nreWhitespace( [options:Object] )\n Returns a regular expression to match a white space character.\n","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n","rpad":"\nrpad( str:string, len:integer[, pad:string] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n","rtrim":"\nrtrim( str:string )\n Trims whitespace from the end of a string.\n","rtrimN":"\nrtrimN( str:string, n:integer[, chars:Array|string] )\n Trims `n` characters from the end of a string.\n","safeintmax":"\nsafeintmax( dtype:string )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n","safeintmin":"\nsafeintmin( dtype:string )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n","sample":"\nsample( x:ArrayLike[, options:Object] )\n Samples elements from an array-like object.\n","sample.factory":"\nsample.factory( [pool:ArrayLike, ][options:Object] )\n Returns a function to sample elements from an array-like object.\n","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n","scalar2array":"\nscalar2array( value:any[, dtype:string] )\n Returns a single-element array containing a provided scalar value.\n","scalar2ndarray":"\nscalar2ndarray( value:any[, options:Object] )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n","sdot":"\nsdot( x:ndarray, y:ndarray[, dim:integer] )\n Computes the dot product of two single-precision floating-point vectors.\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n","secondsInMonth":"\nsecondsInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of seconds in a month.\n","secondsInYear":"\nsecondsInYear( [value:integer|Date] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n","sentencize":"\nsentencize( str:string )\n Splits a string into an array of sentences.\n","seq2slice":"\nseq2slice( str:string, len:integer, strict:boolean )\n Converts a subsequence string to a Slice object.\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a configurable read-only property.\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj:Object, prop:string|symbol, \n getter:Function )\n Defines a configurable read-only accessor.\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj:Object, prop:string|symbol, \n getter:Function, setter:Function )\n Defines a configurable property having read-write accessors.\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n setter:Function )\n Defines a configurable write-only accessor.\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n Defines a configurable memoized read-only object property.\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n Defines a memoized read-only object property.\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )\n Defines a non-enumerable property.\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a non-enumerable read-only property.\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, \n getter:Function )\n Defines a non-enumerable read-only accessor.\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, \n getter:Function, setter:Function )\n Defines a non-enumerable property having read-write accessors.\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n setter:Function )\n Defines a non-enumerable write-only accessor.\n","setReadOnly":"\nsetReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a read-only property.\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )\n Defines a read-only accessor.\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, \n setter:Function )\n Defines a property having read-write accessors.\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )\n Defines a write-only accessor.\n","SharedArrayBuffer":"\nSharedArrayBuffer( size:integer )\n Returns a shared array buffer having a specified number of bytes.\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n","shift":"\nshift( collection:Array|TypedArray|Object )\n Removes and returns the first element of a collection.\n","shuffle":"\nshuffle( arr:ArrayLike[, options:Object] )\n Shuffles elements of an array-like object.\n","shuffle.factory":"\nshuffle.factory( [options:Object] )\n Returns a function to shuffle elements of array-like objects.\n","sizeOf":"\nsizeOf( dtype:string )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n","Slice":"\nSlice( [stop:integer|null|undefined] )\n Returns a Slice.\n\nSlice( start:integer|null|undefined, stop:integer|null|undefined[, \n step:integer|null|undefined] )\n Returns a Slice.\n","Slice.prototype.start":"\nSlice.prototype.start\n Read-only property returning the starting slice index.\n","Slice.prototype.stop":"\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n","Slice.prototype.step":"\nSlice.prototype.step\n Read-only property returning the index increment.\n","Slice.prototype.toString":"\nSlice.prototype.toString()\n Serializes a Slice as a string.\n","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n","snakecase":"\nsnakecase( str:string )\n Converts a string to snake case.\n","some":"\nsome( collection:Array|TypedArray|Object, n:number )\n Tests whether at least `n` elements in a collection are truthy.\n","someBy":"\nsomeBy( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n thisArg:any ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n","someByAsync":"\nsomeByAsync( collection:Array|TypedArray|Object, n:number, [options:Object,] \n predicate:Function, done:Function )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n","someByAsync.factory":"\nsomeByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n","someByRight":"\nsomeByRight( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n thisArg:any ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n","someByRightAsync":"\nsomeByRightAsync( collection:Array|TypedArray|Object, n:number, \n [options:Object,] predicate:Function, done:Function )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n","someInBy":"\nsomeInBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n Tests whether an object contains at least `n` properties\n (own and inherited) which pass a test\n implemented by a predicate function.\n","someOwnBy":"\nsomeOwnBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n Tests whether some `own` properties of a provided object\n satisfy a predicate function for at least `n` properties.\n","SOTU":"\nSOTU( [options:Object] )\n Returns State of the Union (SOTU) addresses.\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n","SparklineBase":"\nSparklineBase( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a Sparkline instance.\n","sparsearray2iterator":"\nsparsearray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, \n thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n","splitStream":"\nsplitStream( [options:Object] )\n Returns a transform stream which splits streamed data.\n","splitStream.factory":"\nsplitStream.factory( [options:Object] )\n Returns a function for creating transform streams for splitting streamed\n data.\n","splitStream.objectMode":"\nsplitStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n Returns US birth data from 2000 to 2014, as provided by the Social Security\n Administration.\n","sswap":"\nsswap( x:ndarray, y:ndarray[, dim:integer] )\n Interchanges two single-precision floating-point vectors.\n","Stack":"\nStack()\n Stack constructor.\n","standalone2pkg":"\nstandalone2pkg( pkg:string )\n Returns the internal package name associated with a provided standalone\n package name.\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n Returns a string array containing two or three letter abbreviations for each\n card in a standard 52-card deck.\n","startcase":"\nstartcase( str:string )\n Capitalizes the first letter of each word in an input string.\n","startsWith":"\nstartsWith( str:string, search:string[, position:integer] )\n Tests if a string starts with the characters of another string.\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n","strided.abs":"\nstrided.abs( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n offsetY:integer )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.abs2":"\nstrided.abs2( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.abs2By":"\nstrided.abs2By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n","strided.absBy":"\nstrided.absBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y`.\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n","strided.acosBy":"\nstrided.acosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.acoshBy":"\nstrided.acoshBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acotBy":"\nstrided.acotBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acothBy":"\nstrided.acothBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y`.\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acovercosBy":"\nstrided.acovercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acoversinBy":"\nstrided.acoversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.add":"\nstrided.add( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.add.ndarray":"\nstrided.add.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.addBy":"\nstrided.addBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array.\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n","strided.ahavercosBy":"\nstrided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.ahaversinBy":"\nstrided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.asinBy":"\nstrided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.asinhBy":"\nstrided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.atanBy":"\nstrided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y`.\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n","strided.atanhBy":"\nstrided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.avercosBy":"\nstrided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.aversinBy":"\nstrided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.besselj0By":"\nstrided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.besselj1By":"\nstrided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.bessely0By":"\nstrided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.bessely1By":"\nstrided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.binetBy":"\nstrided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.cbrt":"\nstrided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y`.\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n","strided.cbrtBy":"\nstrided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.ceil":"\nstrided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y`.\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.cosBy":"\nstrided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.deg2rad":"\nstrided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y`.\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.dataTypes":"\nstrided.dataTypes()\n Returns a list of strided array data types.\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array.\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n","strided.dispatch":"\nstrided.dispatch( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns a strided array function interface which performs multiple dispatch.\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns a strided array function interface which accepts a callback function\n and performs multiple dispatch.\n","strided.floor":"\nstrided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y`.\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.inv":"\nstrided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n offsetY:integer )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.mul":"\nstrided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.mulBy":"\nstrided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n","strided.ramp":"\nstrided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.rsqrt":"\nstrided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.sinBy":"\nstrided.sinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y`.\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n","strided.sqrt":"\nstrided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.sqrtBy":"\nstrided.sqrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n","strided.sub":"\nstrided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.subBy":"\nstrided.subBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n","strided.trunc":"\nstrided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y`.\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n","stridedarray2iterator":"\nstridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, \n offset:integer[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n","stridedArrayStream":"\nstridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, \n offset:integer[, options:Object] )\n Creates a readable stream from a strided array-like object.\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, \n stride:integer, offset:integer[, options:Object] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n","string2buffer":"\nstring2buffer( str:string[, encoding:string] )\n Allocates a buffer containing a provided string.\n","sub2ind":"\nsub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )\n Converts subscripts to a linear index.\n","substringAfter":"\nsubstringAfter( str:string, search:string[, fromIndex:integer] )\n Returns the part of a string after a specified substring.\n","substringAfterLast":"\nsubstringAfterLast( str:string, search:string[, fromIndex:integer] )\n Returns the part of a string after the last occurrence of a specified\n substring.\n","substringBefore":"\nsubstringBefore( str:string, search:string )\n Returns the part of a string before a specified substring.\n","substringBeforeLast":"\nsubstringBeforeLast( str:string, search:string )\n Returns the part of a string before the last occurrence of a specified\n substring.\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n","Symbol":"\nSymbol( [description:string] )\n Returns a symbol.\n","tabulate":"\ntabulate( collection:Array|TypedArray|Object )\n Generates a frequency table.\n","tabulateBy":"\ntabulateBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Generates a frequency table according to an indicator function.\n","tabulateByAsync":"\ntabulateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Generates a frequency table according to an indicator function.\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which generates a frequency table according to an\n indicator function.\n","thunk":"\nthunk( fcn:Function[, ...args:any] )\n Returns a thunk.\n","tic":"\ntic()\n Returns a high-resolution time.\n","timeit":"\ntimeit( code:string, [options:Object,] clbk:Function )\n Times a snippet.\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n","toc":"\ntoc( time:Array )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n","tokenize":"\ntokenize( str:string[, keepWhitespace:boolean] )\n Tokenizes a string.\n","transformStream":"\ntransformStream( [options:Object] )\n Returns a transform stream.\n","transformStream.factory":"\ntransformStream.factory( [options:Object] )\n Returns a function for creating transform streams.\n","transformStream.objectMode":"\ntransformStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream.\n","transformStream.ctor":"\ntransformStream.ctor( [options:Object] )\n Returns a custom transform stream constructor.\n","trim":"\ntrim( str:string )\n Trims whitespace from the beginning and end of a `string`.\n","truncate":"\ntruncate( str:string, len:integer[, ending:string] )\n Truncates a string to a specified length.\n","truncateMiddle":"\ntruncateMiddle( str:string, len:integer[, seq:string] )\n Truncates a string in the middle to a specified length.\n","trycatch":"\ntrycatch( x:Function, y:any )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n","trycatchAsync":"\ntrycatchAsync( x:Function, y:any, done:Function )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n","tryFunction":"\ntryFunction( fcn:Function[, thisArg:any] )\n Wraps a function in a try/catch block.\n","tryRequire":"\ntryRequire( id:string )\n Wraps `require` in a `try/catch` block.\n","trythen":"\ntrythen( x:Function, y:Function )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n","trythenAsync":"\ntrythenAsync( x:Function, y:Function, done:Function )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n","ttest":"\nttest( x:Array[, y:Array][, options:Object] )\n Computes a one-sample or paired Student's t test.\n","ttest2":"\nttest2( x:Array, y:Array[, options:Object] )\n Computes a two-sample Student's t test.\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n","typedarray":"\ntypedarray( [dtype:string] )\n Creates a typed array.\n\ntypedarray( length:integer[, dtype:string] )\n Returns a typed array having a specified length.\n\ntypedarray( typedarray:TypedArray[, dtype:string] )\n Creates a typed array from another typed array.\n\ntypedarray( obj:Object[, dtype:string] )\n Creates a typed array from an array-like object or iterable.\n\ntypedarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a typed array view of an ArrayBuffer.\n","typedarray2json":"\ntypedarray2json( arr:TypedArray )\n Returns a JSON representation of a typed array.\n","typedarrayCtors":"\ntypedarrayCtors( dtype:string )\n Returns a typed array constructor.\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n","typedarraypool":"\ntypedarraypool( [dtype:string] )\n Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool( length:integer[, dtype:string] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\ntypedarraypool( typedarray:TypedArray[, dtype:string] )\n Creates a pooled typed array from another typed array.\n\ntypedarraypool( obj:Object[, dtype:string] )\n Creates a pooled typed array from an array-like object.\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype:string] )\n Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool.malloc( length:integer[, dtype:string] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\ntypedarraypool.malloc( typedarray:TypedArray[, dtype:string] )\n Creates a pooled typed array from another typed array.\n\ntypedarraypool.malloc( obj:Object[, dtype:string] )\n Creates a pooled typed array from an array-like object.\n","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype:string] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\ntypedarraypool.calloc( length:integer[, dtype:string] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n","typedarraypool.free":"\ntypedarraypool.free( buf:TypedArray|ArrayBuffer )\n Frees a typed array or typed array buffer for use in a future allocation.\n","typedarraypool.clear":"\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n","typedarraypool.factory":"\ntypedarraypool.factory( [options:Object] )\n Creates a typed array pool.\n","typemax":"\ntypemax( dtype:string )\n Returns the maximum value of a specified numeric type.\n","typemin":"\ntypemin( dtype:string )\n Returns the minimum value of a specified numeric type.\n","typeOf":"\ntypeOf( value:any )\n Determines a value's type.\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\nUint8Array( length:integer )\n Returns a typed array having a specified length.\n\nUint8Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint8Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint8Array.from":"\nUint8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint8Array.of":"\nUint8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8Array.name":"\nUint8Array.name\n Typed array constructor name.\n","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n Serializes an array as a string.\n","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\nUint8ClampedArray( length:integer )\n Returns a typed array having a specified length.\n\nUint8ClampedArray( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint8ClampedArray( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint8ClampedArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n Typed array constructor name.\n","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement:number[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement:number[, \n fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\nUint16Array( length:integer )\n Returns a typed array having a specified length.\n\nUint16Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint16Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint16Array.from":"\nUint16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint16Array.of":"\nUint16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint16Array.name":"\nUint16Array.name\n Typed array constructor name.\n","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n Serializes an array as a string.\n","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\nUint32Array( length:integer )\n Returns a typed array having a specified length.\n\nUint32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint32Array.from":"\nUint32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint32Array.of":"\nUint32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint32Array.name":"\nUint32Array.name\n Typed array constructor name.\n","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","umask":"\numask( [mask:integer|string,] [options:Object] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n","uncapitalize":"\nuncapitalize( str:string )\n Lowercases the first character of a string.\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj:Object )\n Converts the first letter of each object key to lowercase.\n","uncurry":"\nuncurry( fcn:Function[, arity:integer, ][thisArg:any] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n","uncurryRight":"\nuncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline column chart instance.\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline line chart instance.\n","UnicodeSparkline":"\nUnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a Unicode sparkline instance.\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline tristate chart instance.\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline up/down chart instance.\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline win/loss chart instance.\n","unlink":"\nunlink( path:string|Buffer|integer, clbk:Function )\n Asynchronously removes a directory entry.\n","unlink.sync":"\nunlink.sync( path:string|Buffer|integer )\n Synchronously removes a directory entry.\n","unshift":"\nunshift( collection:Array|TypedArray|Object, ...items:any )\n Adds one or more elements to the beginning of a collection.\n","until":"\nuntil( predicate:Function, fcn:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","untilAsync":"\nuntilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","untilEach":"\nuntilEach( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n","untilEachRight":"\nuntilEachRight( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","unzip":"\nunzip( arr:Array[, idx:Array] )\n Unzips a zipped array (i.e., a nested array of tuples).\n","uppercase":"\nuppercase( str:string )\n Converts a string to uppercase.\n","uppercaseKeys":"\nuppercaseKeys( obj:Object )\n Converts each object key to uppercase.\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str:string )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n","vartest":"\nvartest( x:Array, y:Array[, options:Object] )\n Computes a two-sample F-test for equal variances.\n","waterfall":"\nwaterfall( fcns:Array, clbk:Function[, thisArg:any] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n","waterfall.factory":"\nwaterfall.factory( fcns:Array, clbk:Function[, thisArg:any] )\n Returns a reusable waterfall function.\n","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor:Object )\n WebAssembly memory constructor.\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta:integer )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n","whileAsync":"\nwhileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","whileEach":"\nwhileEach( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection.\n","whileEachRight":"\nwhileEachRight( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","whilst":"\nwhilst( predicate:Function, fcn:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","wilcoxon":"\nwilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )\n Computes a one-sample or paired Wilcoxon signed rank test.\n","writableProperties":"\nwritableProperties( value:any )\n Returns an array of an object's own writable property names and symbols.\n","writablePropertiesIn":"\nwritablePropertiesIn( value:any )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n","writablePropertyNames":"\nwritablePropertyNames( value:any )\n Returns an array of an object's own writable property names.\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value:any )\n Returns an array of an object's own and inherited writable property names.\n","writablePropertySymbols":"\nwritablePropertySymbols( value:any )\n Returns an array of an object's own writable symbol properties.\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited writable symbol\n properties.\n","writeFile":"\nwriteFile( file:string|Buffer|integer, data:string|Buffer[, \n options:Object|string], clbk:Function )\n Asynchronously writes data to a file.\n","writeFile.sync":"\nwriteFile.sync( file:string|Buffer|integer, data:string|Buffer[, \n options:Object|string] )\n Synchronously writes data to a file.\n","zip":"\nzip( ...arr:Array[, options:Object] )\n Generates array tuples from input arrays.\n","ztest":"\nztest( x:Array, sigma:number[, options:Object] )\n Computes a one-sample z-test.\n","ztest2":"\nztest2( x:Array, y:Array, sigmax:number, sigmay:number[, \n options:Object] )\n Computes a two-sample z-test.\n"} +{"abs":"\nabs( x:ndarray[, options:Object] )\n Computes the absolute value for each element in an ndarray.\n","abs.assign":"\nabs.assign( x:ndarray, y:ndarray )\n Computes the absolute value for each element in an ndarray and assigns\n results to a provided output ndarray.\n","acartesianPower":"\nacartesianPower( x:ArrayLikeObject, n:integer )\n Returns the Cartesian power.\n","acartesianProduct":"\nacartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n Returns the Cartesian product.\n","acartesianSquare":"\nacartesianSquare( x:ArrayLikeObject )\n Returns the Cartesian square.\n","acronym":"\nacronym( str:string[, options:Object] )\n Generates an acronym for a given string.\n","aempty":"\naempty( length:integer[, dtype:string] )\n Creates an uninitialized array having a specified length.\n","aemptyLike":"\naemptyLike( x:TypedArray|Array[, dtype:string] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n","AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n","afull":"\nafull( length:integer, value:any[, dtype:string] )\n Returns a filled array having a specified length.\n","afullLike":"\nafullLike( x:TypedArray|Array[, dtype:string] )\n Returns a filled array having the same length and data type as a provided\n input array.\n","alias2pkg":"\nalias2pkg( alias:string )\n Returns the package name associated with a provided alias.\n","alias2related":"\nalias2related( alias:string )\n Returns aliases related to a specified alias.\n","alias2standalone":"\nalias2standalone( alias:string )\n Returns the standalone package name associated with a provided alias.\n","aliases":"\naliases( [namespace:string] )\n Returns a list of standard library aliases.\n","allocUnsafe":"\nallocUnsafe( size:integer )\n Allocates a buffer having a specified number of bytes.\n","amskfilter":"\namskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n","amskput":"\namskput( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n options:Object] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n","amskreject":"\namskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n","anans":"\nanans( length:integer[, dtype:string] )\n Returns an array filled with NaNs and having a specified length.\n","anansLike":"\nanansLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n","anova1":"\nanova1( x:Array, factor:Array[, options:Object] )\n Performs a one-way analysis of variance.\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n","any":"\nany( collection:Array|TypedArray|Object )\n Tests whether at least one element in a collection is truthy.\n","anyBy":"\nanyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n","anyByAsync":"\nanyByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n","anyByAsync.factory":"\nanyByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n","anyByRight":"\nanyByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n","anyByRightAsync":"\nanyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n","anyInBy":"\nanyInBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one value in an object passes a test implemented by\n a predicate function.\n","anyOwnBy":"\nanyOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one own property of an object passes a\n test implemented by a predicate function.\n","aones":"\naones( length:integer[, dtype:string] )\n Returns an array filled with ones and having a specified length.\n","aonesLike":"\naonesLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n","aoneTo":"\naoneTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n","aoneToLike":"\naoneToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n","APERY":"\nAPERY\n Apéry's constant.\n","aplace":"\naplace( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n options:Object] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n","append":"\nappend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the end of another collection.\n","aput":"\naput( x:ArrayLikeObject, indices:ArrayLikeObject, \n values:ArrayLikeObject[, options:Object] )\n Replaces specified elements of an array with provided values.\n","ARCH":"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n","argumentFunction":"\nargumentFunction( idx:integer )\n Returns a function which always returns a specified argument.\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n","array":"\narray( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )\n Returns a multidimensional array.\n","array2buffer":"\narray2buffer( arr:Array )\n Allocates a buffer using an octet array.\n","array2fancy":"\narray2fancy( x:Array|TypedArray|Object[, options:Object] )\n Converts an array to an object supporting fancy indexing.\n","array2fancy.factory":"\narray2fancy.factory( [options:Object] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n","array2fancy.idx":"\narray2fancy.idx( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n","array2iterator":"\narray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n","array2iteratorRight":"\narray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n","ArrayBuffer":"\nArrayBuffer( size:integer )\n Returns an array buffer having a specified number of bytes.\n","ArrayBuffer.length":"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n","ArrayBuffer.isView":"\nArrayBuffer.isView( arr:any )\n Returns a boolean indicating if provided an array buffer view.\n","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of an array buffer to a new array buffer.\n","arraybuffer2buffer":"\narraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Allocates a buffer from an ArrayBuffer.\n","arrayCtors":"\narrayCtors( dtype:string )\n Returns an array constructor.\n","arrayDataType":"\narrayDataType( array:any )\n Returns the data type of an array.\n","arrayDataTypes":"\narrayDataTypes( [kind:string] )\n Returns a list of array data types.\n","ArrayIndex":"\nArrayIndex( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n","ArrayIndex.free":"\nArrayIndex.free( id:string )\n Frees the instance associated with a provided identifier.\n","ArrayIndex.get":"\nArrayIndex.get( id:string )\n Returns the array associated with the instance having a provided identifier.\n","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n","arrayMinDataType":"\narrayMinDataType( value:any )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n","arrayNextDataType":"\narrayNextDataType( [dtype:string] )\n Returns the next larger array data type of the same kind.\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n","arraySafeCasts":"\narraySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n","arraySameKindCasts":"\narraySameKindCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n","arrayShape":"\narrayShape( arr:ArrayLikeObject )\n Determines array dimensions.\n","arrayStream":"\narrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object.\n","arrayStream.factory":"\narrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n","arrayStream.objectMode":"\narrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object.\n","arrayview2iterator":"\narrayview2iterator( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n","aslice":"\naslice( x:ArrayLikeObject[, start:integer[, end:integer]] )\n Returns a shallow copy of a portion of an array.\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n","atake":"\natake( x:Array|TypedArray|Object, indices:ArrayLikeObject[, \n options:Object] )\n Takes elements from an array.\n","azeros":"\nazeros( length:integer[, dtype:string] )\n Returns a zero-filled array having a specified length.\n","azerosLike":"\nazerosLike( x:TypedArray|Array[, dtype:string] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n","azeroTo":"\nazeroTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n","azeroToLike":"\nazeroToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n","bartlettTest":"\nbartlettTest( ...x:Array[, options:Object] )\n Computes Bartlett’s test for equal variances.\n","base.abs":"\nbase.abs( x:number )\n Computes the absolute value of a double-precision floating-point number `x`.\n","base.abs2":"\nbase.abs2( x:number )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n","base.abs2f":"\nbase.abs2f( x:number )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n","base.absdiff":"\nbase.absdiff( x:number, y:number )\n Computes the absolute difference.\n","base.absf":"\nbase.absf( x:number )\n Computes the absolute value of a single-precision floating-point number `x`.\n","base.acartesianPower":"\nbase.acartesianPower( x:ArrayLikeObject, n:integer )\n Returns the Cartesian power.\n","base.acartesianProduct":"\nbase.acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n Returns the Cartesian product.\n","base.acartesianSquare":"\nbase.acartesianSquare( x:ArrayLikeObject )\n Returns the Cartesian square.\n","base.acos":"\nbase.acos( x:number )\n Compute the arccosine of a double-precision floating-point number.\n","base.acosd":"\nbase.acosd( x:number )\n Computes the arccosine (in degrees) of a double-precision floating-point \n number.\n","base.acosdf":"\nbase.acosdf( x:number )\n Computes the arccosine (in degrees) of a single-precision floating-point\n number.\n","base.acosf":"\nbase.acosf( x:number )\n Computes the arccosine of a single-precision floating-point number.\n","base.acosh":"\nbase.acosh( x:number )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n","base.acot":"\nbase.acot( x:number )\n Computes the inverse cotangent of a double-precision floating-point number.\n","base.acotd":"\nbase.acotd( x:number )\n Computes the arccotangent (in degrees) of a double-precision floating-point\n number.\n","base.acotdf":"\nbase.acotdf( x:number )\n Computes the arccotangent (in degrees) of a single-precision floating-point\n number.\n","base.acotf":"\nbase.acotf( x:number )\n Computes the inverse cotangent of a single-precision floating-point number.\n","base.acoth":"\nbase.acoth( x:number )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n","base.acovercos":"\nbase.acovercos( x:number )\n Computes the inverse coversed cosine.\n","base.acoversin":"\nbase.acoversin( x:number )\n Computes the inverse coversed sine.\n","base.acsc":"\nbase.acsc( x:number )\n Computes the arccosecant of a number.\n","base.acscd":"\nbase.acscd( x:number )\n Computes the arccosecant of (in degrees) a double-precision floating-point\n number.\n","base.acscdf":"\nbase.acscdf( x:number )\n Computes the arccosecant (in degrees) of a single-precision floating-point\n number.\n","base.acscf":"\nbase.acscf( x:number )\n Computes the arccosecant of a single-precision floating-point number.\n","base.acsch":"\nbase.acsch( x:number )\n Computes the hyperbolic arccosecant of a number.\n","base.add":"\nbase.add( x:number, y:number )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n","base.add3":"\nbase.add3( x:number, y:number, z:number )\n Computes the sum of three double-precision floating-point numbers.\n","base.add4":"\nbase.add4( x:number, y:number, z:number, w:number )\n Computes the sum of four double-precision floating-point numbers.\n","base.add5":"\nbase.add5( x:number, y:number, z:number, w:number, u:number )\n Computes the sum of five double-precision floating-point numbers.\n","base.addf":"\nbase.addf( x:number, y:number )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n","base.afilled":"\nbase.afilled( value:any, len:integer )\n Returns a filled \"generic\" array.\n","base.afilled2d":"\nbase.afilled2d( value:any, shape:Array )\n Returns a filled two-dimensional nested array.\n","base.afilled2dBy":"\nbase.afilled2dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled two-dimensional nested array according to a provided\n callback function.\n","base.afilled3d":"\nbase.afilled3d( value:any, shape:Array )\n Returns a filled three-dimensional nested array.\n","base.afilled3dBy":"\nbase.afilled3dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled three-dimensional nested array according to a provided\n callback function.\n","base.afilled4d":"\nbase.afilled4d( value:any, shape:Array )\n Returns a filled four-dimensional nested array.\n","base.afilled4dBy":"\nbase.afilled4dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled four-dimensional nested array according to a provided\n callback function.\n","base.afilled5d":"\nbase.afilled5d( value:any, shape:Array )\n Returns a filled five-dimensional nested array.\n","base.afilled5dBy":"\nbase.afilled5dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled five-dimensional nested array according to a provided\n callback function.\n","base.afilledBy":"\nbase.afilledBy( len:integer, clbk:Function[, thisArg:any] )\n Returns a filled \"generic\" array according to a provided callback function.\n","base.afillednd":"\nbase.afillednd( value:any, shape:Array )\n Returns a filled n-dimensional nested array.\n","base.afilledndBy":"\nbase.afilledndBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled n-dimensional nested array according to a callback\n function.\n","base.afilter":"\nbase.afilter( x:Array|TypedArray|Object, predicate:Function[, thisArg:any] )\n Returns a shallow copy of an array containing only those elements which pass\n a test implemented by a predicate function.\n","base.afirst":"\nbase.afirst( arr:ArrayLikeObject )\n Returns the first element of an array-like object.\n","base.aflatten":"\nbase.aflatten( x:Array, shape:Array, colexicographic:boolean )\n Flattens an n-dimensional nested array.\n","base.aflatten.assign":"\nbase.aflatten.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten2d":"\nbase.aflatten2d( x:Array, shape:Array, colexicographic:boolean )\n Flattens a two-dimensional nested array.\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten2dBy":"\nbase.aflatten2dBy( x:Array, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a two-dimensional nested array according to a callback function.\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten3d":"\nbase.aflatten3d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a three-dimensional nested array.\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten3dBy":"\nbase.aflatten3dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a three-dimensional nested array according to a callback function.\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten4d":"\nbase.aflatten4d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a four-dimensional nested array.\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten4dBy":"\nbase.aflatten4dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a four-dimensional nested array according to a callback function.\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten5d":"\nbase.aflatten5d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a five-dimensional nested array.\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten5dBy":"\nbase.aflatten5dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a five-dimensional nested array according to a callback function.\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflattenBy":"\nbase.aflattenBy( x:Array, shape:Array, colex:boolean, clbk:Function[, \n thisArg:any] )\n Flattens an n-dimensional nested array according to a callback function.\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n","base.afliplr2d":"\nbase.afliplr2d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a two-dimensional\n nested input array.\n","base.afliplr3d":"\nbase.afliplr3d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a three-\n dimensional nested input array.\n","base.afliplr4d":"\nbase.afliplr4d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a four-\n dimensional nested input array.\n","base.afliplr5d":"\nbase.afliplr5d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a five-\n dimensional nested input array.\n","base.aflipud2d":"\nbase.aflipud2d( x:ArrayLikeObject )\n Reverses the order of elements along the first dimension of a two-\n dimensional nested input array.\n","base.aflipud3d":"\nbase.aflipud3d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a\n three-dimensional nested input array.\n","base.aflipud4d":"\nbase.aflipud4d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a four-\n dimensional nested input array.\n","base.aflipud5d":"\nbase.aflipud5d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a five-\n dimensional nested input array.\n","base.ahavercos":"\nbase.ahavercos( x:number )\n Computes the inverse half-value versed cosine.\n","base.ahaversin":"\nbase.ahaversin( x:number )\n Computes the inverse half-value versed sine.\n","base.altcase":"\nbase.altcase( str:string )\n Converts a string to alternate case.\n","base.aones":"\nbase.aones( len:integer )\n Returns a \"generic\" array filled with ones.\n","base.aones2d":"\nbase.aones2d( shape:Array )\n Returns a two-dimensional nested array filled with ones.\n","base.aones3d":"\nbase.aones3d( shape:Array )\n Returns a three-dimensional nested array filled with ones.\n","base.aones4d":"\nbase.aones4d( shape:Array )\n Returns a four-dimensional nested array filled with ones.\n","base.aones5d":"\nbase.aones5d( shape:Array )\n Returns a five-dimensional nested array filled with ones.\n","base.aonesnd":"\nbase.aonesnd( shape:Array )\n Returns an n-dimensional nested array filled with ones.\n","base.aoneTo":"\nbase.aoneTo( n:number )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n","base.args2multislice":"\nbase.args2multislice( args:Array )\n Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n","base.asec":"\nbase.asec( x:number )\n Computes the inverse (arc) secant of a number.\n","base.asecd":"\nbase.asecd( x:number )\n Computes the arcsecant (in degrees) of a double-precision floating-point\n number.\n","base.asecdf":"\nbase.asecdf( x:number )\n Computes the arcsecant (in degrees) of a single-precision floating-point\n number.\n","base.asecf":"\nbase.asecf( x:number )\n Computes the inverse (arc) secant of a single-precision\n floating-point number.\n","base.asech":"\nbase.asech( x:number )\n Computes the hyperbolic arcsecant of a number.\n","base.asin":"\nbase.asin( x:number )\n Computes the arcsine of a double-precision floating-point number.\n","base.asind":"\nbase.asind( x:number )\n Computes the arcsine (in degrees) of a double-precision floating-point\n number.\n","base.asindf":"\nbase.asindf( x:number )\n Computes the arcsine (in degrees) of a single-precision floating-point\n number.\n","base.asinf":"\nbase.asinf( x:number )\n Computes the arcsine of a single-precision floating-point number.\n","base.asinh":"\nbase.asinh( x:number )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n","base.atan":"\nbase.atan( x:number )\n Computes the arctangent of a double-precision floating-point number.\n","base.atan2":"\nbase.atan2( y:number, x:number )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n","base.atand":"\nbase.atand( x:number )\n Computes the arctangent (in degrees) of a double-precision floating-point\n number.\n","base.atanf":"\nbase.atanf( x:number )\n Computes the arctangent of a single-precision floating-point number.\n","base.atanh":"\nbase.atanh( x:number )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n","base.avercos":"\nbase.avercos( x:number )\n Computes the inverse versed cosine.\n","base.aversin":"\nbase.aversin( x:number )\n Computes the inverse versed sine.\n","base.azeros":"\nbase.azeros( len:integer )\n Returns a zero-filled \"generic\" array.\n","base.azeros2d":"\nbase.azeros2d( shape:Array )\n Returns a zero-filled two-dimensional nested array.\n","base.azeros3d":"\nbase.azeros3d( shape:Array )\n Returns a zero-filled three-dimensional nested array.\n","base.azeros4d":"\nbase.azeros4d( shape:Array )\n Returns a zero-filled four-dimensional nested array.\n","base.azeros5d":"\nbase.azeros5d( shape:Array )\n Returns a zero-filled five-dimensional nested array.\n","base.azerosnd":"\nbase.azerosnd( shape:Array )\n Returns a zero-filled n-dimensional nested array.\n","base.azeroTo":"\nbase.azeroTo( n:number )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n","base.bernoulli":"\nbase.bernoulli( n:integer )\n Computes the nth Bernoulli number.\n","base.besselj0":"\nbase.besselj0( x:number )\n Computes the Bessel function of the first kind of order zero.\n","base.besselj1":"\nbase.besselj1( x:number )\n Computes the Bessel function of the first kind of order one.\n","base.bessely0":"\nbase.bessely0( x:number )\n Computes the Bessel function of the second kind of order zero.\n","base.bessely1":"\nbase.bessely1( x:number )\n Computes the Bessel function of the second kind of order one.\n","base.beta":"\nbase.beta( x:number, y:number )\n Evaluates the beta function.\n","base.betainc":"\nbase.betainc( x:number, a:number, b:number[, regularized:boolean[, \n upper:boolean]] )\n Computes the regularized incomplete beta function.\n","base.betaincinv":"\nbase.betaincinv( p:number, a:number, b:number[, upper:boolean] )\n Computes the inverse of the lower incomplete beta function.\n","base.betaln":"\nbase.betaln( a:number, b:number )\n Evaluates the natural logarithm of the beta function.\n","base.binet":"\nbase.binet( x:number )\n Evaluates Binet's formula extended to real numbers.\n","base.binomcoef":"\nbase.binomcoef( n:integer, k:integer )\n Computes the binomial coefficient of two integers.\n","base.binomcoefln":"\nbase.binomcoefln( n:integer, k:integer )\n Computes the natural logarithm of the binomial coefficient of two integers.\n","base.boxcox":"\nbase.boxcox( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation.\n","base.boxcox1p":"\nbase.boxcox1p( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation of 1+x.\n","base.boxcox1pinv":"\nbase.boxcox1pinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n","base.boxcoxinv":"\nbase.boxcoxinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation.\n","base.cabs":"\nbase.cabs( z:Complex128 )\n Computes the absolute value of a double-precision complex floating-point\n number.\n","base.cabs2":"\nbase.cabs2( z:Complex128 )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n","base.cabs2f":"\nbase.cabs2f( z:Complex64 )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n","base.cabsf":"\nbase.cabsf( z:Complex64 )\n Computes the absolute value of a single-precision complex floating-point\n number.\n","base.cadd":"\nbase.cadd( z1:Complex128, z2:Complex128 )\n Adds two double-precision complex floating-point numbers.\n","base.cadd.assign":"\nbase.cadd.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Adds two double-precision complex floating-point numbers and assigns results\n to a provided output array.\n","base.cadd.strided":"\nbase.cadd.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Adds two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n","base.caddf":"\nbase.caddf( z1:Complex64, z2:Complex64 )\n Adds two single-precision complex floating-point numbers.\n","base.caddf.assign":"\nbase.caddf.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Adds two single-precision complex floating-point numbers and assigns results\n to a provided output array.\n","base.caddf.strided":"\nbase.caddf.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Adds two single-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n","base.camelcase":"\nbase.camelcase( str:string )\n Converts a string to camel case.\n","base.capitalize":"\nbase.capitalize( str:string )\n Capitalizes the first character in a string.\n","base.cbrt":"\nbase.cbrt( x:number )\n Computes the cube root of a double-precision floating-point number.\n","base.cbrtf":"\nbase.cbrtf( x:number )\n Computes the cube root of a single-precision floating-point number.\n","base.cceil":"\nbase.cceil( z:Complex128 )\n Rounds each component of a double-precision complex floating-point number\n toward positive infinity.\n","base.cceilf":"\nbase.cceilf( z:Complex64 )\n Rounds each component of a single-precision complex floating-point number\n toward positive infinity.\n","base.cceiln":"\nbase.cceiln( z:Complex128, n:integer )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n","base.ccis":"\nbase.ccis( z:Complex128 )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n","base.cdiv":"\nbase.cdiv( z1:Complex128, z2:Complex128 )\n Divides two double-precision complex floating-point numbers.\n","base.cdiv.assign":"\nbase.cdiv.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Divides two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n","base.cdiv.strided":"\nbase.cdiv.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Divides two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n","base.ceil":"\nbase.ceil( x:number )\n Rounds a double-precision floating-point number toward positive infinity.\n","base.ceil2":"\nbase.ceil2( x:number )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n","base.ceil10":"\nbase.ceil10( x:number )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n","base.ceilb":"\nbase.ceilb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n","base.ceilf":"\nbase.ceilf( x:number )\n Rounds a single-precision floating-point number toward positive infinity.\n","base.ceiln":"\nbase.ceiln( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n","base.ceilsd":"\nbase.ceilsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n","base.cexp":"\nbase.cexp( z:Complex128 )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n","base.cflipsign":"\nbase.cflipsign( z:Complex128, y:number )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n","base.cflipsignf":"\nbase.cflipsignf( z:Complex64, y:number )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n","base.cfloor":"\nbase.cfloor( z:Complex128 )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n","base.cfloorn":"\nbase.cfloorn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n","base.cidentity":"\nbase.cidentity( z:Complex128 )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n","base.cidentityf":"\nbase.cidentityf( z:Complex64 )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n","base.cinv":"\nbase.cinv( z:Complex128 )\n Computes the inverse of a double-precision complex floating-point number.\n","base.cinvf":"\nbase.cinvf( z:Complex64 )\n Computes the inverse of a single-precision complex floating-point number.\n","base.clamp":"\nbase.clamp( v:number, min:number, max:number )\n Restricts a double-precision floating-point number to a specified range.\n","base.clampf":"\nbase.clampf( v:number, min:number, max:number )\n Restricts a single-precision floating-point number to a specified range.\n","base.cmul":"\nbase.cmul( z1:Complex128, z2:Complex128 )\n Multiplies two double-precision complex floating-point numbers.\n","base.cmul.assign":"\nbase.cmul.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n","base.cmul.strided":"\nbase.cmul.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n","base.cmulf":"\nbase.cmulf( z1:Complex64, z2:Complex64 )\n Multiplies two single-precision complex floating-point numbers.\n","base.cmulf.assign":"\nbase.cmulf.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Multiplies two single-precision complex floating-point numbers and assigns\n results to a provided output array.\n","base.cmulf.strided":"\nbase.cmulf.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Multiplies two single-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n","base.cneg":"\nbase.cneg( z:Complex128 )\n Negates a double-precision complex floating-point number.\n","base.cnegf":"\nbase.cnegf( z:Complex64 )\n Negates a single-precision complex floating-point number.\n","base.codePointAt":"\nbase.codePointAt( str:string, idx:integer, backward:boolean )\n Returns a Unicode code point from a string at a specified position.\n","base.constantcase":"\nbase.constantcase( str:string )\n Converts a string to constant case.\n","base.continuedFraction":"\nbase.continuedFraction( generator:Function[, options:Object] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n","base.copysign":"\nbase.copysign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n","base.copysignf":"\nbase.copysignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n","base.cos":"\nbase.cos( x:number )\n Computes the cosine of a number.\n","base.cosd":"\nbase.cosd( x:number )\n Computes the cosine of an angle measured in degrees.\n","base.cosh":"\nbase.cosh( x:number )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n","base.cosm1":"\nbase.cosm1( x:number )\n Computes the cosine of a number minus one.\n","base.cospi":"\nbase.cospi( x:number )\n Computes the value of `cos(πx)`.\n","base.cot":"\nbase.cot( x:number )\n Computes the cotangent of a number.\n","base.cotd":"\nbase.cotd( x:number )\n Computes the cotangent of an angle measured in degrees.\n","base.coth":"\nbase.coth( x:number )\n Computes the hyperbolic cotangent of a number.\n","base.covercos":"\nbase.covercos( x:number )\n Computes the coversed cosine.\n","base.coversin":"\nbase.coversin( x:number )\n Computes the coversed sine.\n","base.cphase":"\nbase.cphase( z:Complex128 )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n","base.cpolar":"\nbase.cpolar( z:Complex128 )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n","base.cpolar.assign":"\nbase.cpolar.assign( z:Complex128, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n","base.cround":"\nbase.cround( z:Complex128 )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n","base.croundn":"\nbase.croundn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n","base.csc":"\nbase.csc( x:number )\n Computes the cosecant of a number.\n","base.cscd":"\nbase.cscd( x:number )\n Computes the cosecant of a degree.\n","base.csch":"\nbase.csch( x:number )\n Computes the hyperbolic cosecant of a number.\n","base.csignum":"\nbase.csignum( z:Complex128 )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n","base.csub":"\nbase.csub( z1:Complex128, z2:Complex128 )\n Subtracts two double-precision complex floating-point numbers.\n","base.csubf":"\nbase.csubf( z1:Complex64, z2:Complex64 )\n Subtracts two single-precision complex floating-point numbers.\n","base.deg2rad":"\nbase.deg2rad( x:number )\n Converts an angle from degrees to radians.\n","base.deg2radf":"\nbase.deg2radf( x:number )\n Converts an angle from degrees to radians (single-precision).\n","base.digamma":"\nbase.digamma( x:number )\n Evaluates the digamma function.\n","base.diracDelta":"\nbase.diracDelta( x:number )\n Evaluates the Dirac delta function.\n","base.div":"\nbase.div( x:number, y:number )\n Divides two double-precision floating-point numbers `x` and `y`.\n","base.divf":"\nbase.divf( x:number, y:number )\n Divides two single-precision floating-point numbers `x` and `y`.\n","base.dotcase":"\nbase.dotcase( str:string )\n Converts a string to dot case.\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a:number, b:number] )\n Returns an arcsine distribution object.\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a:number, b:number )\n Returns the differential entropy of an arcsine distribution (in nats).\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a:number, b:number )\n Returns the excess kurtosis of an arcsine distribution.\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x:number, a:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x:number, a:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a:number, b:number )\n Returns the expected value of an arcsine distribution.\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a:number, b:number )\n Returns the median of an arcsine distribution.\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a:number, b:number )\n Returns the mode of an arcsine distribution.\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a:number, b:number )\n Returns the skewness of an arcsine distribution.\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a:number, b:number )\n Returns the standard deviation of an arcsine distribution.\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a:number, b:number )\n Returns the variance of an arcsine distribution.\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p:number] )\n Returns a Bernoulli distribution object.\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p`.\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p:number )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p:number )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p:number )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p:number )\n Returns the median of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p:number )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r:number, p:number )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p:number )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p:number )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p:number )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α:number, β:number] )\n Returns a beta distribution object.\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α:number, β:number )\n Returns the differential entropy of a beta distribution.\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta distribution.\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n","base.dists.beta.mean":"\nbase.dists.beta.mean( α:number, β:number )\n Returns the expected value of a beta distribution.\n","base.dists.beta.median":"\nbase.dists.beta.median( α:number, β:number )\n Returns the median of a beta distribution.\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n","base.dists.beta.mode":"\nbase.dists.beta.mode( α:number, β:number )\n Returns the mode of a beta distribution.\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α:number, β:number )\n Returns the skewness of a beta distribution.\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α:number, β:number )\n Returns the standard deviation of a beta distribution.\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α:number, β:number )\n Returns the variance of a beta distribution.\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α:number, β:number] )\n Returns a beta prime distribution object.\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta prime distribution.\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α:number, β:number )\n Returns the expected value of a beta prime distribution.\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α:number, β:number )\n Returns the mode of a beta prime distribution.\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α:number, β:number )\n Returns the skewness of a beta prime distribution.\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α:number, β:number )\n Returns the standard deviation of a beta prime distribution.\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α:number, β:number )\n Returns the variance of a beta prime distribution.\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n:integer, p:number] )\n Returns a binomial distribution object.\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x:number, n:integer, p:number )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n:integer, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n:integer, p:number )\n Returns the entropy of a binomial distribution.\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n:integer, p:number )\n Returns the excess kurtosis of a binomial distribution.\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x:number, n:integer, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n:integer, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n:integer, p:number )\n Returns the expected value of a binomial distribution.\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n:integer, p:number )\n Returns the median of a binomial distribution.\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t:number, n:integer, p:number )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n:integer, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n:integer, p:number )\n Returns the mode of a binomial distribution.\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x:number, n:integer, p:number )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n:integer, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r:number, n:integer, p:number )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n:integer, p:number )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n:integer, p:number )\n Returns the skewness of a binomial distribution.\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n:integer, p:number )\n Returns the standard deviation of a binomial distribution.\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n:integer, p:number )\n Returns the variance of a binomial distribution.\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0:number, Ɣ:number] )\n Returns a Cauchy distribution object.\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x:number, x0:number, Ɣ:number )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0:number, Ɣ:number )\n Returns the differential entropy of a Cauchy distribution (in nats).\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0:number, Ɣ:number )\n Returns the median of a Cauchy distribution.\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0:number, Ɣ:number )\n Returns the mode of a Cauchy distribution.\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x:number, x0:number, Ɣ:number )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p:number, x0:number, Ɣ:number )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k:number] )\n Returns a chi distribution object.\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k:number )\n Returns the differential entropy of a chi distribution (in nats).\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k:number )\n Returns the excess kurtosis of a chi distribution.\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.mean":"\nbase.dists.chi.mean( k:number )\n Returns the expected value of a chi distribution.\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k:number )\n Returns the mode of a chi distribution.\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p:number, k:number )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k:number )\n Returns the skewness of a chi distribution.\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k:number )\n Returns the standard deviation of a chi distribution.\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k:number )\n Returns the variance of a chi distribution.\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k:number] )\n Returns a chi-squared distribution object.\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k:number )\n Returns the differential entropy of a chi-squared distribution (in nats).\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k:number )\n Returns the excess kurtosis of a chi-squared distribution.\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k:number )\n Returns the expected value of a chi-squared distribution.\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k:number )\n Returns the median of a chi-squared distribution.\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t:number, k:number )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k:number )\n Returns the mode of a chi-squared distribution.\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p:number, k:number )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k:number )\n Returns the skewness of a chi-squared distribution.\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k:number )\n Returns the standard deviation of a chi-squared distribution.\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k:number )\n Returns the variance of a chi-squared distribution.\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ:number, s:number] )\n Returns a raised cosine distribution object.\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x:number, μ:number, s:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ:number, s:number )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ:number, s:number )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ:number, s:number )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ:number, s:number )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ:number, s:number )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ:number, s:number )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x:number, μ:number )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ:number] )\n Returns a degenerate distribution object.\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ:number )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x:number, μ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x:number, μ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x:number, μ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ:number )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ:number )\n Returns the median of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x:number, μ:number )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ:number )\n Returns the mode of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x:number, μ:number )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x:number, μ:number )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p:number, μ:number )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ:number )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ:number )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ:number )\n Returns the variance of a degenerate distribution with constant value `μ`.\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x:number, a:integer, b:integer )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a:integer, b:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a:integer, b:integer] )\n Returns a discrete uniform distribution object.\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a:integer, b:integer )\n Returns the entropy of a discrete uniform distribution.\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a:integer, b:integer )\n Returns the excess kurtosis of a discrete uniform distribution.\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a:integer, b:integer )\n Returns the expected value of a discrete uniform distribution.\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a:integer, b:integer )\n Returns the median of a discrete uniform distribution.\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t:number, a:integer, b:integer )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a:integer, b:integer )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x:number, a:integer, b:integer )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a:integer, b:integer )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p:number, a:integer, b:integer )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a:integer, b:integer )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a:integer, b:integer )\n Returns the skewness of a discrete uniform distribution.\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a:integer, b:integer )\n Returns the standard deviation of a discrete uniform distribution.\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a:integer, b:integer )\n Returns the variance of a discrete uniform distribution.\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k:integer, λ:number )\n Returns the differential entropy of an Erlang distribution (in nats).\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k:number, λ:number] )\n Returns an Erlang distribution object.\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k:integer, λ:number )\n Returns the excess kurtosis of an Erlang distribution.\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x:number, k:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k:integer, λ:number )\n Returns the expected value of an Erlang distribution.\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k:integer, λ:number )\n Returns the mode of an Erlang distribution.\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k:integer, λ:number )\n Returns the skewness of an Erlang distribution.\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k:integer, λ:number )\n Returns the standard deviation of an Erlang distribution.\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k:integer, λ:number )\n Returns the variance of an Erlang distribution.\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ:number )\n Returns the differential entropy of an exponential distribution.\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ:number] )\n Returns an exponential distribution object.\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ:number )\n Returns the excess kurtosis of an exponential distribution.\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x:number, λ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ:number )\n Returns the expected value of an exponential distribution.\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ:number )\n Returns the median of an exponential distribution.\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t:number, λ:number )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ:number )\n Returns the mode of an exponential distribution.\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x:number, λ:number )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ:number )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p:number, λ:number )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ:number )\n Returns the skewness of an exponential distribution.\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ:number )\n Returns the standard deviation of an exponential distribution.\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ:number )\n Returns the variance of an exponential distribution.\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x:number, d1:number, d2:number )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1:number, d2:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n","base.dists.f.entropy":"\nbase.dists.f.entropy( d1:number, d2:number )\n Returns the differential entropy of an F distribution (in nats).\n","base.dists.f.F":"\nbase.dists.f.F( [d1:number, d2:number] )\n Returns an F distribution object.\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1:number, d2:number )\n Returns the excess kurtosis of an F distribution.\n","base.dists.f.mean":"\nbase.dists.f.mean( d1:number, d2:number )\n Returns the expected value of an F distribution.\n","base.dists.f.mode":"\nbase.dists.f.mode( d1:number, d2:number )\n Returns the mode of an F distribution.\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x:number, d1:number, d2:number )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1:number, d2:number )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n","base.dists.f.quantile":"\nbase.dists.f.quantile( p:number, d1:number, d2:number )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1:number, d2:number )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n","base.dists.f.skewness":"\nbase.dists.f.skewness( d1:number, d2:number )\n Returns the skewness of an F distribution.\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1:number, d2:number )\n Returns the standard deviation of an F distribution.\n","base.dists.f.variance":"\nbase.dists.f.variance( d1:number, d2:number )\n Returns the variance of an F distribution.\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x:number, α:number, s:number, m:number )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α:number, s:number, m:number )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α:number, s:number, m:number] )\n Returns a Fréchet distribution object.\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α:number, s:number, m:number )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x:number, α:number, s:number, m:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x:number, α:number, s:number, m:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α:number, s:number, m:number )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α:number, s:number, m:number )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α:number, s:number, m:number )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x:number, α:number, s:number, m:number )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p:number, α:number, s:number, m:number )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α:number, s:number, m:number )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α:number, s:number, m:number )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α:number, s:number, m:number )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α:number, s:number, m:number )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α:number, β:number )\n Returns the differential entropy of a gamma distribution.\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α:number, β:number] )\n Returns a gamma distribution object.\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a gamma distribution.\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x:number, α:number, β:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x:number, α:number, β:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α:number, β:number )\n Returns the expected value of a gamma distribution.\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α:number, β:number )\n Returns the mode of a gamma distribution.\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α:number, β:number )\n Returns the skewness of a gamma distribution.\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α:number, β:number )\n Returns the standard deviation of a gamma distribution.\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α:number, β:number )\n Returns the variance of a gamma distribution.\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p:number )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p:number] )\n Returns a geometric distribution object.\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p:number )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x:number, p:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x:number, p:number )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p:number )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p:number )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p:number )\n Returns the median of a geometric distribution with success probability `p`.\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p:number )\n Returns the mode of a geometric distribution with success probability `p`.\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r:number, p:number )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p:number )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p:number )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p:number )\n Returns the variance of a geometric distribution with success probability\n `p`.\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x:number, μ:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ:number, β:number )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ:number, β:number] )\n Returns a Gumbel distribution object.\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ:number, β:number )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x:number, μ:number, β:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x:number, μ:number, β:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ:number, β:number )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ:number, β:number )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t:number, μ:number, β:number )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ:number, β:number )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x:number, μ:number, β:number )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p:number, μ:number, β:number )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ:number, β:number )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ:number, β:number )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ:number, β:number )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ:number, β:number )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x:number, N:integer, K:integer, n:integer )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N:integer, K:integer, n:integer] )\n Returns a hypergeometric distribution object.\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N:integer, K:integer, n:integer )\n Returns the excess kurtosis of a hypergeometric distribution.\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N:integer, K:integer, n:integer )\n Returns the expected value of a hypergeometric distribution.\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N:integer, K:integer, n:integer )\n Returns the mode of a hypergeometric distribution.\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p:number, N:integer, K:integer, n:integer )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N:integer, K:integer, n:integer )\n Returns the skewness of a hypergeometric distribution.\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N:integer, K:integer, n:integer )\n Returns the standard deviation of a hypergeometric distribution.\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N:integer, K:integer, n:integer )\n Returns the variance of a hypergeometric distribution.\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α:number, β:number )\n Returns the differential entropy of an inverse gamma distribution.\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α:number, β:number] )\n Returns an inverse gamma distribution object.\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of an inverse gamma distribution.\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α:number, β:number )\n Returns the expected value of an inverse gamma distribution.\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α:number, β:number )\n Returns the mode of an inverse gamma distribution.\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α:number, β:number )\n Returns the skewness of an inverse gamma distribution.\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α:number, β:number )\n Returns the standard deviation of an inverse gamma distribution.\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α:number, β:number )\n Returns the variance of an inverse gamma distribution.\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a:number, b:number] )\n Returns a Kumaraswamy's double bounded distribution object.\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a:number, b:number )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a:number, b:number )\n Returns the median of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a:number, b:number )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a:number, b:number )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a:number, b:number )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a:number, b:number )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x:number, μ:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ:number, b:number )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ:number, b:number )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ:number, b:number] )\n Returns a Laplace distribution object.\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x:number, μ:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x:number, μ:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ:number, b:number )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ:number, b:number )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t:number, μ:number, b:number )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ:number, b:number )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x:number, μ:number, b:number )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p:number, μ:number, b:number )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ:number, b:number )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ:number, b:number )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ:number, b:number )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ:number, b:number )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x:number, μ:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ:number, c:number )\n Returns the differential entropy of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ:number, c:number] )\n Returns a Lévy distribution object.\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x:number, μ:number, c:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x:number, μ:number, c:number )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n","base.dists.levy.mean":"\nbase.dists.levy.mean( μ:number, c:number )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n","base.dists.levy.median":"\nbase.dists.levy.median( μ:number, c:number )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ:number, c:number )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x:number, μ:number, c:number )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p:number, μ:number, c:number )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ:number, c:number )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ:number, c:number )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ:number, c:number )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ:number, s:number )\n Returns the differential entropy of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ:number, s:number] )\n Returns a logistic distribution object.\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ:number, s:number )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ:number, s:number )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ:number, s:number )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ:number, s:number )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ:number, s:number )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ:number, s:number )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ:number, σ:number )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ:number, σ:number] )\n Returns a lognormal distribution object.\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n at a value `x`.\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ:number, σ:number )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ:number, σ:number )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ:number, σ:number )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ:number, σ:number )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ:number, σ:number )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ:number, σ:number )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x:number, r:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r:number, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r:integer, p:number )\n Returns the excess kurtosis of a negative binomial distribution.\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x:number, r:number, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r:number, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r:integer, p:number )\n Returns the expected value of a negative binomial distribution.\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x:number, r:number, p:number )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r:number, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r:integer, p:number )\n Returns the mode of a negative binomial distribution.\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r:number, p:number] )\n Returns a negative binomial distribution object.\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x:number, r:number, p:number )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r:number, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k:number, r:number, p:number )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r:number, p:number )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r:integer, p:number )\n Returns the skewness of a negative binomial distribution.\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r:integer, p:number )\n Returns the standard deviation of a negative binomial distribution.\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r:integer, p:number )\n Returns the variance of a negative binomial distribution.\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ:number, σ:number )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.mean":"\nbase.dists.normal.mean( μ:number, σ:number )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.median":"\nbase.dists.normal.median( μ:number, σ:number )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x:number, μ:number, σ:number )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ:number, σ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.mode":"\nbase.dists.normal.mode( μ:number, σ:number )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ:number, σ:number] )\n Returns a normal distribution object.\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ:number, σ:number )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ:number, σ:number )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ:number, σ:number )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α:number, β:number )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α:number, β:number )\n Returns the expected value of a Pareto (Type I) distribution.\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α:number, β:number )\n Returns the median of a Pareto (Type I) distribution.\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α:number, β:number )\n Returns the mode of a Pareto (Type I) distribution.\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α:number, β:number] )\n Returns a Pareto (Type I) distribution object.\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α:number, β:number )\n Returns the skewness of a Pareto (Type I) distribution.\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α:number, β:number )\n Returns the standard deviation of a Pareto (Type I) distribution.\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α:number, β:number )\n Returns the variance of a Pareto (Type I) distribution.\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ:number )\n Returns the entropy of a Poisson distribution.\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ:number )\n Returns the excess kurtosis of a Poisson distribution.\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x:number, λ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ:number )\n Returns the expected value of a Poisson distribution.\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ:number )\n Returns the median of a Poisson distribution.\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ:number )\n Returns the mode of a Poisson distribution.\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x:number, λ:number )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ:number )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ:number] )\n Returns a Poisson distribution object.\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p:number, λ:number )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ:number )\n Returns the skewness of a Poisson distribution.\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ:number )\n Returns the standard deviation of a Poisson distribution.\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ:number )\n Returns the variance of a Poisson distribution.\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x:number, sigma:number )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ:number )\n Returns the differential entropy of a Rayleigh distribution.\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ:number )\n Returns the excess kurtosis of a Rayleigh distribution.\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x:number, sigma:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x:number, sigma:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ:number )\n Returns the expected value of a Rayleigh distribution.\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ:number )\n Returns the median of a Rayleigh distribution.\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t:number, sigma:number )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ:number )\n Returns the mode of a Rayleigh distribution.\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x:number, sigma:number )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p:number, sigma:number )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma:number )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ:number] )\n Returns a Rayleigh distribution object.\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ:number )\n Returns the skewness of a Rayleigh distribution.\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ:number )\n Returns the standard deviation of a Rayleigh distribution.\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ:number )\n Returns the variance of a Rayleigh distribution.\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x:number, n:integer )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x:number, n:integer )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n:integer )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p:number, n:integer )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n:integer )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x:number, r:number, v:number[, \n nranges:integer] )\n Evaluates the cumulative distribution function (CDF) of a studentized range\n distribution.\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r:number, v:number[, nranges:integer] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p:number, r:number, v:number[, \n nranges:integer] )\n Evaluates the quantile function for a studentized range distribution.\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r:number, v:number[, \n nranges:integer] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n","base.dists.t.cdf":"\nbase.dists.t.cdf( x:number, v:number )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.entropy":"\nbase.dists.t.entropy( v:number )\n Returns the differential entropy of a Student's t distribution.\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v:number )\n Returns the excess kurtosis of a Student's t distribution.\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x:number, v:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n `x`.\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x:number, v:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Student's t distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n","base.dists.t.mean":"\nbase.dists.t.mean( v:number )\n Returns the expected value of a Student's t distribution.\n","base.dists.t.median":"\nbase.dists.t.median( v:number )\n Returns the median of a Student's t distribution.\n","base.dists.t.mode":"\nbase.dists.t.mode( v:number )\n Returns the mode of a Student's t distribution.\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x:number, v:number )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.quantile":"\nbase.dists.t.quantile( p:number, v:number )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v:number )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n","base.dists.t.skewness":"\nbase.dists.t.skewness( v:number )\n Returns the skewness of a Student's t distribution.\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v:number )\n Returns the standard deviation of a Student's t distribution.\n","base.dists.t.T":"\nbase.dists.t.T( [v:number] )\n Returns a Student's t distribution object.\n","base.dists.t.variance":"\nbase.dists.t.variance( v:number )\n Returns the variance of a Student's t distribution.\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x:number, a:number, b:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a:number, b:number, c:number )\n Returns the differential entropy of a triangular distribution (in nats).\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a:number, b:number, c:number )\n Returns the excess kurtosis of a triangular distribution.\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a:number, b:number, c:number )\n Returns the expected value of a triangular distribution.\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a:number, b:number, c:number )\n Returns the median of a triangular distribution.\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t:number, a:number, b:number, c:number )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a:number, b:number, c:number )\n Returns the mode of a triangular distribution.\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x:number, a:number, b:number, c:number )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p:number, a:number, b:number, c:number )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a:number, b:number, c:number )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a:number, b:number, c:number )\n Returns the skewness of a triangular distribution.\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a:number, b:number, c:number )\n Returns the standard deviation of a triangular distribution.\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a:number, b:number, c:number] )\n Returns a triangular distribution object.\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a:number, b:number, c:number )\n Returns the variance of a triangular distribution.\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a:number, b:number )\n Returns the differential entropy of a uniform distribution.\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a uniform distribution.\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x:number, a:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x:number, a:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a:number, b:number )\n Returns the expected value of a uniform distribution.\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a:number, b:number )\n Returns the median of a uniform distribution.\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t:number, a:number, b:number )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a:number, b:number )\n Returns the skewness of a uniform distribution.\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a:number, b:number )\n Returns the standard deviation of a uniform distribution.\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a:number, b:number] )\n Returns a uniform distribution object.\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a:number, b:number )\n Returns the variance of a uniform distribution.\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k:number, λ:number )\n Returns the differential entropy of a Weibull distribution (in nats).\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k:number, λ:number )\n Returns the excess kurtosis of a Weibull distribution.\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x:number, k:number, λ:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k:number, λ:number)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x:number, k:number, λ:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k:number, λ:number )\n Returns the expected value of a Weibull distribution.\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k:number, λ:number )\n Returns the median of a Weibull distribution.\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k:number, λ:number )\n Returns the mode of a Weibull distribution.\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k:number, λ:number )\n Returns the skewness of a Weibull distribution.\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k:number, λ:number )\n Returns the standard deviation of a Weibull distribution.\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k:number, λ:number )\n Returns the variance of a Weibull distribution.\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k:number, λ:number] )\n Returns a Weibull distribution object.\n","base.ellipe":"\nbase.ellipe( m:number )\n Computes the complete elliptic integral of the second kind.\n","base.ellipj":"\nbase.ellipj( u:number, m:number )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n","base.ellipj.assign":"\nbase.ellipj.assign( u:number, m:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n","base.ellipj.sn":"\nbase.ellipj.sn( u:number, m:number )\n Computes the Jacobi elliptic function sn.\n","base.ellipj.cn":"\nbase.ellipj.cn( u:number, m:number )\n Computes the Jacobi elliptic functions cn.\n","base.ellipj.dn":"\nbase.ellipj.dn( u:number, m:number )\n Computes the Jacobi elliptic function dn.\n","base.ellipj.am":"\nbase.ellipj.am( u:number, m:number )\n Computes the Jacobi amplitude am.\n","base.ellipk":"\nbase.ellipk( m:number )\n Computes the complete elliptic integral of the first kind.\n","base.endsWith":"\nbase.endsWith( str:string, search:string, len:integer )\n Tests if a string ends with the characters of another string.\n","base.epsdiff":"\nbase.epsdiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n","base.erf":"\nbase.erf( x:number )\n Evaluates the error function.\n","base.erfc":"\nbase.erfc( x:number )\n Evaluates the complementary error function.\n","base.erfcinv":"\nbase.erfcinv( x:number )\n Evaluates the inverse complementary error function.\n","base.erfcx":"\nbase.erfcx( x:number )\n Evaluates the scaled complementary error function.\n","base.erfinv":"\nbase.erfinv( x:number )\n Evaluates the inverse error function.\n","base.eta":"\nbase.eta( s:number )\n Evaluates the Dirichlet eta function for a double-precision\n floating-point number `s`.\n","base.evalpoly":"\nbase.evalpoly( c:Array, x:number )\n Evaluates a polynomial using double-precision floating-point arithmetic.\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c:Array )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n","base.evalrational":"\nbase.evalrational( P:Array, Q:Array, x:number )\n Evaluates a rational function using double-precision floating-point\n arithmetic.\n","base.evalrational.factory":"\nbase.evalrational.factory( P:Array, Q:Array )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n","base.exp":"\nbase.exp( x:number )\n Evaluates the natural exponential function.\n","base.exp2":"\nbase.exp2( x:number )\n Evaluates the base 2 exponential function.\n","base.exp10":"\nbase.exp10( x:number )\n Evaluates the base 10 exponential function.\n","base.expit":"\nbase.expit( x:number )\n Evaluates the standard logistic function.\n","base.expm1":"\nbase.expm1( x:number )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n","base.expm1rel":"\nbase.expm1rel( x:number )\n Relative error exponential.\n","base.exponent":"\nbase.exponent( x:number )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n","base.exponentf":"\nbase.exponentf( x:float )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n","base.factorial":"\nbase.factorial( x:number )\n Evaluates the factorial of `x`.\n","base.factorial2":"\nbase.factorial2( n:number )\n Evaluates the double factorial of `n`.\n","base.factorialln":"\nbase.factorialln( x:number )\n Evaluates the natural logarithm of the factorial of `x`.\n","base.fallingFactorial":"\nbase.fallingFactorial( x:number, n:integer )\n Computes the falling factorial of `x` and `n`.\n","base.fibonacci":"\nbase.fibonacci( n:integer )\n Computes the nth Fibonacci number.\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F:integer )\n Computes the Fibonacci number index.\n","base.fibpoly":"\nbase.fibpoly( n:integer, x:number )\n Evaluates a Fibonacci polynomial.\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n:integer )\n Returns a function for evaluating a Fibonacci polynomial.\n","base.firstCodePoint":"\nbase.firstCodePoint( str:string, n:integer )\n Returns the first `n` Unicode code points of a string.\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str:string, n:integer )\n Returns the first `n` UTF-16 code units of a string.\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str:string, n:integer )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n","base.flipsign":"\nbase.flipsign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n","base.flipsignf":"\nbase.flipsignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n","base.float32ToInt32":"\nbase.float32ToInt32( x:float )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n","base.float32ToUint32":"\nbase.float32ToUint32( x:float )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n","base.float64ToFloat32":"\nbase.float64ToFloat32( x:number )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n","base.float64ToInt32":"\nbase.float64ToInt32( x:number )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n","base.float64ToUint32":"\nbase.float64ToUint32( x:number )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n","base.floor":"\nbase.floor( x:number )\n Rounds a double-precision floating-point number toward negative infinity.\n","base.floor2":"\nbase.floor2( x:number )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n","base.floor10":"\nbase.floor10( x:number )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n","base.floorb":"\nbase.floorb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n","base.floorf":"\nbase.floorf( x:number )\n Rounds a single-precision floating-point number toward negative infinity.\n","base.floorn":"\nbase.floorn( x:number, n:integer )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n","base.floorsd":"\nbase.floorsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n","base.forEachChar":"\nbase.forEachChar( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each UTF-16 code unit in a string.\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each Unicode code point in a string.\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each Unicode code point in a string, iterating from\n right to left.\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n","base.forEachRight":"\nbase.forEachRight( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each UTF-16 code unit in a string, iterating from\n right to left.\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens:Array, ...args:any )\n Generate string from a token array by interpolating values.\n","base.formatTokenize":"\nbase.formatTokenize( str:string )\n Tokenize a string into an array of string parts and format identifier\n objects.\n","base.fresnel":"\nbase.fresnel( x:number )\n Computes the Fresnel integrals S(x) and C(x).\n","base.fresnel.assign":"\nbase.fresnel.assign( x:number, out:Array, stride:integer, \n offset:integer )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n","base.fresnelc":"\nbase.fresnelc( x:number )\n Computes the Fresnel integral C(x).\n","base.fresnels":"\nbase.fresnels( x:number )\n Computes the Fresnel integral S(x).\n","base.frexp":"\nbase.frexp( x:number )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n","base.frexp.assign":"\nbase.frexp.assign( x:number, out:Array, stride:integer, offset:integer )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n","base.fromBinaryString":"\nbase.fromBinaryString( bstr:string )\n Creates a double-precision floating-point number from a literal bit\n representation.\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr:string )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr:string )\n Creates an unsigned 8-bit integer from a literal bit representation.\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr:string )\n Creates an unsigned 16-bit integer from a literal bit representation.\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr:string )\n Creates an unsigned 32-bit integer from a literal bit representation.\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Converts a signed 64-bit integer byte array to a double-precision floating-\n point number.\n","base.fromWordf":"\nbase.fromWordf( word:integer )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n","base.fromWords":"\nbase.fromWords( high:integer, low:integer )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.gamma":"\nbase.gamma( x:number )\n Evaluates the gamma function.\n","base.gamma1pm1":"\nbase.gamma1pm1( x:number )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z:number, delta:number )\n Computes the ratio of two gamma functions.\n","base.gammainc":"\nbase.gammainc( x:number, s:number[, regularized:boolean[, upper:boolean]] )\n Computes the regularized incomplete gamma function.\n","base.gammaincinv":"\nbase.gammaincinv( p:number, a:number[, upper:boolean] )\n Computes the inverse of the lower incomplete gamma function.\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x:number )\n Calculates the Lanczos sum for the approximation of the gamma function.\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x:number )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n","base.gammaln":"\nbase.gammaln( x:number )\n Evaluates the natural logarithm of the gamma function.\n","base.gammasgn":"\nbase.gammasgn( x:number )\n Computes the sign of the gamma function.\n","base.gcd":"\nbase.gcd( a:integer, b:integer )\n Computes the greatest common divisor (gcd).\n","base.getHighWord":"\nbase.getHighWord( x:number )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n","base.getLowWord":"\nbase.getLowWord( x:number )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n","base.hacovercos":"\nbase.hacovercos( x:number )\n Computes the half-value coversed cosine.\n","base.hacoversin":"\nbase.hacoversin( x:number )\n Computes the half-value coversed sine.\n","base.havercos":"\nbase.havercos( x:number )\n Computes the half-value versed cosine.\n","base.haversin":"\nbase.haversin( x:number )\n Computes the half-value versed sine.\n","base.headercase":"\nbase.headercase( str:string )\n Converts a string to HTTP header case.\n","base.heaviside":"\nbase.heaviside( x:number[, continuity:string] )\n Evaluates the Heaviside function.\n","base.hermitepoly":"\nbase.hermitepoly( n:integer, x:number )\n Evaluates a physicist's Hermite polynomial.\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n:integer )\n Returns a function for evaluating a physicist's Hermite polynomial.\n","base.hypot":"\nbase.hypot( x:number, y:number )\n Computes the hypotenuse avoiding overflow and underflow.\n","base.hypotf":"\nbase.hypotf( x:number, y:number )\n Computes the hypotenuse avoiding overflow and underflow (single-precision).\n","base.identity":"\nbase.identity( x:number )\n Evaluates the identity function for a double-precision floating-point number\n `x`.\n","base.identityf":"\nbase.identityf( x:number )\n Evaluates the identity function for a single-precision floating-point number\n `x`.\n","base.imul":"\nbase.imul( a:integer, b:integer )\n Performs C-like multiplication of two signed 32-bit integers.\n","base.imuldw":"\nbase.imuldw( a:integer, b:integer )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n","base.imuldw.assign":"\nbase.imuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n","base.int2slice":"\nbase.int2slice( value:integer, max:integer, strict:boolean )\n Converts an integer to a Slice object.\n","base.int32ToUint32":"\nbase.int32ToUint32( x:integer )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n","base.inv":"\nbase.inv( x:number )\n Computes the multiplicative inverse of a double-precision floating-point\n number `x`.\n","base.invcase":"\nbase.invcase( str:string )\n Converts a string to inverse case.\n","base.invf":"\nbase.invf( x:number )\n Computes the multiplicative inverse of a single-precision floating-point\n number `x`.\n","base.isComposite":"\nbase.isComposite( x:number )\n Tests if a number is composite.\n","base.isCoprime":"\nbase.isCoprime( a:number, b:number )\n Tests if two numbers are coprime.\n","base.isEven":"\nbase.isEven( x:number )\n Tests if a finite numeric value is an even number.\n","base.isEvenInt32":"\nbase.isEvenInt32( x:integer )\n Tests if a 32-bit integer is even.\n","base.isFinite":"\nbase.isFinite( x:number )\n Tests if a double-precision floating-point numeric value is finite.\n","base.isFinitef":"\nbase.isFinitef( x:number )\n Tests if a single-precision floating-point numeric value is finite.\n","base.isInfinite":"\nbase.isInfinite( x:number )\n Tests if a double-precision floating-point numeric value is infinite.\n","base.isInfinitef":"\nbase.isInfinitef( x:number )\n Tests if a single-precision floating-point numeric value is infinite.\n","base.isInteger":"\nbase.isInteger( x:number )\n Tests if a finite double-precision floating-point number is an integer.\n","base.isnan":"\nbase.isnan( x:number )\n Tests if a double-precision floating-point numeric value is `NaN`.\n","base.isnanf":"\nbase.isnanf( x:number )\n Tests if a single-precision floating-point numeric value is `NaN`.\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x:number )\n Tests if a double-precision floating-point numeric value is a negative\n finite number.\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x:number )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n","base.isNegativeZero":"\nbase.isNegativeZero( x:number )\n Tests if a double-precision floating-point numeric value is negative zero.\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x:number )\n Tests if a single-precision floating-point numeric value is negative zero.\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x:number )\n Tests if a double-precision floating-point numeric value is a nonnegative\n finite number.\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x:number )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x:number )\n Tests if a double-precision floating-point numeric value is a nonpositive\n finite number.\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x:number )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n","base.isOdd":"\nbase.isOdd( x:number )\n Tests if a finite numeric value is an odd number.\n","base.isOddInt32":"\nbase.isOddInt32( x:integer )\n Tests if a 32-bit integer is odd.\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x:number )\n Tests if a double-precision floating-point numeric value is a positive\n finite number.\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x:number )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n","base.isPositiveZero":"\nbase.isPositiveZero( x:number )\n Tests if a double-precision floating-point numeric value is positive zero.\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x:number )\n Tests if a single-precision floating-point numeric value is positive zero.\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x:integer )\n Tests whether an unsigned integer is a power of 2.\n","base.isPrime":"\nbase.isPrime( x:number )\n Tests if a number is prime.\n","base.isProbability":"\nbase.isProbability( x:number )\n Tests if a double-precision floating-point number value is a probability.\n","base.isSafeInteger":"\nbase.isSafeInteger( x:number )\n Tests if a finite double-precision floating-point number is a safe integer.\n","base.kebabcase":"\nbase.kebabcase( str:string )\n Converts a string to kebab case.\n","base.kernelBetainc":"\nbase.kernelBetainc( x:number, a:number, b:number, regularized:boolean, \n upper:boolean )\n Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x:number, a:number, b:number, regularized:boolean, \n upper:boolean, out:Array|TypedArray|Object, stride:integer, offset:integer )\n Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a:number, b:number, p:number, q:number )\n Computes the inverse of the lower incomplete beta function.\n","base.kernelCos":"\nbase.kernelCos( x:number, y:number )\n Computes the cosine of a double-precision floating-point number on the\n interval [-π/4, π/4].\n","base.kernelLog1p":"\nbase.kernelLog1p( f:number )\n Evaluates a correction term for double-precision base-2 and base-10\n logarithms when `1+f` is in `[√2/2, √2]`.\n","base.kernelSin":"\nbase.kernelSin( x:number, y:number )\n Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n","base.kernelTan":"\nbase.kernelTan( x:number, y:number, k:integer )\n Computes the tangent of a double-precision floating-point number on the\n interval [-π/4, π/4].\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i:number, j:number )\n Evaluates the Kronecker delta.\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i:number, j:number )\n Evaluates the Kronecker delta (single-precision).\n","base.labs":"\nbase.labs( x:integer )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n","base.last":"\nbase.last( str:string, n:integer )\n Returns the last `n` UTF-16 code units of a string.\n","base.lastCodePoint":"\nbase.lastCodePoint( str:string, n:integer )\n Returns the last `n` Unicode code points of a string.\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str:string, n:integer )\n Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n","base.lcm":"\nbase.lcm( a:integer, b:integer )\n Computes the least common multiple (lcm).\n","base.ldexp":"\nbase.ldexp( frac:number, exp:number )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n","base.leftPad":"\nbase.leftPad( str:string, len:integer, pad:string )\n Left pads a string such that the padded string has a length of at least\n `len`.\n","base.leftTrim":"\nbase.leftTrim( str:string )\n Trims whitespace from the beginning of a string.\n","base.ln":"\nbase.ln( x:number )\n Evaluates the natural logarithm of a double-precision floating-point number.\n","base.log":"\nbase.log( x:number, b:number )\n Computes the base `b` logarithm of a double-precision floating-point number.\n","base.log1mexp":"\nbase.log1mexp( x:number )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n","base.log1p":"\nbase.log1p( x:number )\n Evaluates the natural logarithm of `1+x`.\n","base.log1pexp":"\nbase.log1pexp( x:number )\n Evaluates the natural logarithm of `1+exp(x)`.\n","base.log1pmx":"\nbase.log1pmx( x:number )\n Evaluates `ln(1+x) - x`.\n","base.log2":"\nbase.log2( x:number )\n Evaluates the binary logarithm (base two).\n","base.log10":"\nbase.log10( x:number )\n Evaluates the common logarithm (base 10).\n","base.logaddexp":"\nbase.logaddexp( x:number, y:number )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n","base.logit":"\nbase.logit( p:number )\n Evaluates the logit function.\n","base.lowercase":"\nbase.lowercase( str:string )\n Converts a string to lowercase.\n","base.lucas":"\nbase.lucas( n:integer )\n Computes the nth Lucas number.\n","base.lucaspoly":"\nbase.lucaspoly( n:integer, x:number )\n Evaluates a Lucas polynomial.\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n:integer )\n Returns a function for evaluating a Lucas polynomial.\n","base.max":"\nbase.max( x:number, y:number )\n Returns the maximum value.\n","base.maxabs":"\nbase.maxabs( x:number, y:number )\n Returns the maximum absolute value.\n","base.maxabsn":"\nbase.maxabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the maximum absolute value.\n","base.maxn":"\nbase.maxn( [x:number[, y:number[, ...args:number]]] )\n Returns the maximum value.\n","base.min":"\nbase.min( x:number, y:number )\n Returns the minimum value.\n","base.minabs":"\nbase.minabs( x:number, y:number )\n Returns the minimum absolute value.\n","base.minabsn":"\nbase.minabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum absolute value.\n","base.minmax":"\nbase.minmax( x:number, y:number )\n Returns the minimum and maximum values.\n","base.minmax.assign":"\nbase.minmax.assign( x:number, y:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n","base.minmaxabs":"\nbase.minmaxabs( x:number, y:number )\n Returns the minimum and maximum absolute values.\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x:number, y:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Returns the minimum and maximum absolute values and assigns results to a\n provided output array.\n","base.minmaxabsn":"\nbase.minmaxabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum and maximum absolute values.\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x:number[, y:number[, ...args:number]]], \n out:Array|TypedArray|Object, stride:integer, offset:integer )\n Returns the minimum and maximum absolute values.\n","base.minmaxn":"\nbase.minmaxn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum and maximum values.\n","base.minmaxn.assign":"\nbase.minmaxn.assign( [x:number[, y:number[, ...args:number]]], \n out:Array|TypedArray|Object, stride:integer, offset:integer )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n","base.minn":"\nbase.minn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum value.\n","base.modf":"\nbase.modf( x:number )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n","base.modf.assign":"\nbase.modf.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n","base.mul":"\nbase.mul( x:number, y:number )\n Multiplies two double-precision floating-point numbers `x` and `y`.\n","base.mulf":"\nbase.mulf( x:number, y:number )\n Multiplies two single-precision floating-point numbers `x` and `y`.\n","base.ndarray":"\nbase.ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string )\n Returns an ndarray.\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n Underlying data type.\n","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n Number of dimensions.\n","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n Array order.\n","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n Array shape.\n","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","base.ndarray.prototype.toLocaleString":"\nbase.ndarray.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an ndarray as a locale-aware string.\n","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in an input ndarray and assigns results\n to elements in an output ndarray.\n","base.ndzeros":"\nbase.ndzeros( dtype:string|DataType, shape:ArrayLikeObject, \n order:string )\n Returns a zero-filled ndarray having a specified shape and data type.\n","base.ndzerosLike":"\nbase.ndzerosLike( x:ndarray )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n","base.negafibonacci":"\nbase.negafibonacci( n:integer )\n Computes the nth negaFibonacci number.\n","base.negalucas":"\nbase.negalucas( n:integer )\n Computes the nth negaLucas number.\n","base.nonfibonacci":"\nbase.nonfibonacci( n:integer )\n Computes the nth non-Fibonacci number.\n","base.normalize":"\nbase.normalize( x:number )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n","base.normalize.assign":"\nbase.normalize.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n","base.normalizef":"\nbase.normalizef( x:float )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n","base.normalizef.assign":"\nbase.normalizef.assign( x:float, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n","base.normalizeMultiSlice":"\nbase.normalizeMultiSlice( slice:MultiSlice, shape:Array, \n strict:boolean )\n Returns a normalized MultiSlice object.\n","base.normalizeSlice":"\nbase.normalizeSlice( slice:Slice, len:integer, strict:boolean )\n Returns a normalized Slice object.\n","base.normhermitepoly":"\nbase.normhermitepoly( n:integer, x:number )\n Evaluates a normalized Hermite polynomial using double-precision floating-\n point arithmetic.\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n:integer )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n","base.pascalcase":"\nbase.pascalcase( str:string )\n Converts a string to Pascal case.\n","base.pdiff":"\nbase.pdiff( x:number, y:number )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n","base.pdifff":"\nbase.pdifff( x:number, y:number )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n","base.percentEncode":"\nbase.percentEncode( str:string )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","base.polygamma":"\nbase.polygamma( n:integer, x:number )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n","base.pow":"\nbase.pow( b:number, x:number )\n Evaluates the exponential function `bˣ`.\n","base.powm1":"\nbase.powm1( b:number, x:number )\n Evaluates `bˣ - 1`.\n","base.rad2deg":"\nbase.rad2deg( x:number )\n Converts an angle from radians to degrees.\n","base.rad2degf":"\nbase.rad2degf( x:number )\n Converts an angle from radians to degrees (single-precision).\n","base.ramp":"\nbase.ramp( x:number )\n Evaluates the ramp function.\n","base.rampf":"\nbase.rampf( x:number )\n Evaluates the ramp function (single-precision).\n","base.random.arcsine":"\nbase.random.arcsine( a:number, b:number )\n Returns a pseudorandom number drawn from an arcsine distribution.\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n Generator name.\n","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n Length of generator seed.\n","base.random.arcsine.state":"\nbase.random.arcsine.state\n Generator state.\n","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n Length of generator state.\n","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.bernoulli":"\nbase.random.bernoulli( p:number )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n Generator name.\n","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n Length of generator seed.\n","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n Generator state.\n","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n Length of generator state.\n","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.beta":"\nbase.random.beta( α:number, β:number )\n Returns a pseudorandom number drawn from a beta distribution.\n","base.random.beta.factory":"\nbase.random.beta.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n","base.random.beta.NAME":"\nbase.random.beta.NAME\n Generator name.\n","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n","base.random.beta.seed":"\nbase.random.beta.seed\n Pseudorandom number generator seed.\n","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n Length of generator seed.\n","base.random.beta.state":"\nbase.random.beta.state\n Generator state.\n","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n Length of generator state.\n","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.betaprime":"\nbase.random.betaprime( α:number, β:number )\n Returns a pseudorandom number drawn from a beta prime distribution.\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n Generator name.\n","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n Length of generator seed.\n","base.random.betaprime.state":"\nbase.random.betaprime.state\n Generator state.\n","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n Length of generator state.\n","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.binomial":"\nbase.random.binomial( n:integer, p:number )\n Returns a pseudorandom number drawn from a binomial distribution.\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n:integer, p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n Generator name.\n","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n","base.random.binomial.seed":"\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n Length of generator seed.\n","base.random.binomial.state":"\nbase.random.binomial.state\n Generator state.\n","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n Length of generator state.\n","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n Size of generator state.\n","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n Generator name.\n","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n Length of generator seed.\n","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n Generator state.\n","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n Length of generator state.\n","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.cauchy":"\nbase.random.cauchy( x0:number, Ɣ:number )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0:number, Ɣ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n Generator name.\n","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n Length of generator seed.\n","base.random.cauchy.state":"\nbase.random.cauchy.state\n Generator state.\n","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n Length of generator state.\n","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.chi":"\nbase.random.chi( k:number )\n Returns a pseudorandom number drawn from a chi distribution.\n","base.random.chi.factory":"\nbase.random.chi.factory( [k:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n","base.random.chi.NAME":"\nbase.random.chi.NAME\n Generator name.\n","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n","base.random.chi.seed":"\nbase.random.chi.seed\n Pseudorandom number generator seed.\n","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n Length of generator seed.\n","base.random.chi.state":"\nbase.random.chi.state\n Generator state.\n","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n Length of generator state.\n","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.chisquare":"\nbase.random.chisquare( k:number )\n Returns a pseudorandom number drawn from a chi-square distribution.\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n Generator name.\n","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n Length of generator seed.\n","base.random.chisquare.state":"\nbase.random.chisquare.state\n Generator state.\n","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n Length of generator state.\n","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.cosine":"\nbase.random.cosine( μ:number, s:number )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ:number, s:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n Generator name.\n","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n","base.random.cosine.seed":"\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n Length of generator seed.\n","base.random.cosine.state":"\nbase.random.cosine.state\n Generator state.\n","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n Length of generator state.\n","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.discreteUniform":"\nbase.random.discreteUniform( a:integer, b:integer )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a:integer, b:integer, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n Generator name.\n","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n Generator state.\n","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n Length of generator state.\n","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.erlang":"\nbase.random.erlang( k:integer, λ:number )\n Returns a pseudorandom number drawn from an Erlang distribution.\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k:integer, λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n Generator name.\n","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n","base.random.erlang.seed":"\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n Length of generator seed.\n","base.random.erlang.state":"\nbase.random.erlang.state\n Generator state.\n","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n Length of generator state.\n","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.exponential":"\nbase.random.exponential( λ:number )\n Returns a pseudorandom number drawn from an exponential distribution.\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n Generator name.\n","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n","base.random.exponential.seed":"\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n Length of generator seed.\n","base.random.exponential.state":"\nbase.random.exponential.state\n Generator state.\n","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n Length of generator state.\n","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.f":"\nbase.random.f( d1:number, d2:number )\n Returns a pseudorandom number drawn from an F distribution.\n","base.random.f.factory":"\nbase.random.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n","base.random.f.NAME":"\nbase.random.f.NAME\n Generator name.\n","base.random.f.PRNG":"\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n","base.random.f.seed":"\nbase.random.f.seed\n Pseudorandom number generator seed.\n","base.random.f.seedLength":"\nbase.random.f.seedLength\n Length of generator seed.\n","base.random.f.state":"\nbase.random.f.state\n Generator state.\n","base.random.f.stateLength":"\nbase.random.f.stateLength\n Length of generator state.\n","base.random.f.byteLength":"\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n","base.random.f.toJSON":"\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.frechet":"\nbase.random.frechet( α:number, s:number, m:number )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α:number, s:number, m:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n Generator name.\n","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n","base.random.frechet.seed":"\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n Length of generator seed.\n","base.random.frechet.state":"\nbase.random.frechet.state\n Generator state.\n","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n Length of generator state.\n","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.gamma":"\nbase.random.gamma( α:number, β:number )\n Returns a pseudorandom number drawn from a gamma distribution.\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n Generator name.\n","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n","base.random.gamma.seed":"\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n Length of generator seed.\n","base.random.gamma.state":"\nbase.random.gamma.state\n Generator state.\n","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n Length of generator state.\n","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n Size of generator state.\n","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.geometric":"\nbase.random.geometric( p:number )\n Returns a pseudorandom number drawn from a geometric distribution.\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n Generator name.\n","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n","base.random.geometric.seed":"\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n Length of generator seed.\n","base.random.geometric.state":"\nbase.random.geometric.state\n Generator state.\n","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n Length of generator state.\n","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.gumbel":"\nbase.random.gumbel( μ:number, β:number )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n Generator name.\n","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n Length of generator seed.\n","base.random.gumbel.state":"\nbase.random.gumbel.state\n Generator state.\n","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n Length of generator state.\n","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.hypergeometric":"\nbase.random.hypergeometric( N:integer, K:integer, n:integer )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N:integer, K:integer, n:integer, ]\n [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n Generator name.\n","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n Generator state.\n","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n Length of generator state.\n","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n Generator name.\n","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n Generator state.\n","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.invgamma":"\nbase.random.invgamma( α:number, β:number )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n Generator name.\n","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n Length of generator seed.\n","base.random.invgamma.state":"\nbase.random.invgamma.state\n Generator state.\n","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n Length of generator state.\n","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n Size of generator state.\n","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a:number, b:number )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n Generator name.\n","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n Generator state.\n","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.laplace":"\nbase.random.laplace( μ:number, b:number )\n Returns a pseudorandom number drawn from a Laplace distribution.\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n Generator name.\n","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n","base.random.laplace.seed":"\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n Length of generator seed.\n","base.random.laplace.state":"\nbase.random.laplace.state\n Generator state.\n","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n Length of generator state.\n","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.levy":"\nbase.random.levy( μ:number, c:number )\n Returns a pseudorandom number drawn from a Lévy distribution.\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ:number, c:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n","base.random.levy.NAME":"\nbase.random.levy.NAME\n Generator name.\n","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n","base.random.levy.seed":"\nbase.random.levy.seed\n Pseudorandom number generator seed.\n","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n Length of generator seed.\n","base.random.levy.state":"\nbase.random.levy.state\n Generator state.\n","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n Length of generator state.\n","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.logistic":"\nbase.random.logistic( μ:number, s:number )\n Returns a pseudorandom number drawn from a logistic distribution.\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ:number, s:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n Generator name.\n","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n","base.random.logistic.seed":"\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n Length of generator seed.\n","base.random.logistic.state":"\nbase.random.logistic.state\n Generator state.\n","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n Length of generator state.\n","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.lognormal":"\nbase.random.lognormal( μ:number, σ:number )\n Returns a pseudorandom number drawn from a lognormal distribution.\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n Generator name.\n","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n Length of generator seed.\n","base.random.lognormal.state":"\nbase.random.lognormal.state\n Generator state.\n","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n Length of generator state.\n","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstd.factory":"\nbase.random.minstd.factory( [options:Object] )\n Returns a linear congruential pseudorandom number generator (LCG).\n","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n Generator name.\n","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n Minimum possible value.\n","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n Maximum possible value.\n","base.random.minstd.seed":"\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n Length of generator seed.\n","base.random.minstd.state":"\nbase.random.minstd.state\n Generator state.\n","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n Length of generator state.\n","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options:Object] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n Generator name.\n","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n Generator state.\n","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options:Object] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n Generator name.\n","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n Minimum possible value.\n","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n Maximum possible value.\n","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n Length of generator seed.\n","base.random.mt19937.state":"\nbase.random.mt19937.state\n Generator state.\n","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n Length of generator state.\n","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r:number, p:number )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n Generator name.\n","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n Generator state.\n","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.normal":"\nbase.random.normal( μ:number, σ:number )\n Returns a pseudorandom number drawn from a normal distribution.\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n","base.random.normal.NAME":"\nbase.random.normal.NAME\n Generator name.\n","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n","base.random.normal.seed":"\nbase.random.normal.seed\n Pseudorandom number generator seed.\n","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n Length of generator seed.\n","base.random.normal.state":"\nbase.random.normal.state\n Generator state.\n","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n Length of generator state.\n","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n Size of generator state.\n","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.pareto1":"\nbase.random.pareto1( α:number, β:number )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n Generator name.\n","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n Length of generator seed.\n","base.random.pareto1.state":"\nbase.random.pareto1.state\n Generator state.\n","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n Length of generator state.\n","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.poisson":"\nbase.random.poisson( λ:number )\n Returns a pseudorandom number drawn from a Poisson distribution.\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n Generator name.\n","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n","base.random.poisson.seed":"\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n Length of generator seed.\n","base.random.poisson.state":"\nbase.random.poisson.state\n Generator state.\n","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n Length of generator state.\n","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n","base.random.randi.factory":"\nbase.random.randi.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n","base.random.randi.NAME":"\nbase.random.randi.NAME\n Generator name.\n","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n","base.random.randi.MIN":"\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n","base.random.randi.MAX":"\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n","base.random.randi.seed":"\nbase.random.randi.seed\n Pseudorandom number generator seed.\n","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n Length of generator seed.\n","base.random.randi.state":"\nbase.random.randi.state\n Generator state.\n","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n Length of generator state.\n","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.randn.factory":"\nbase.random.randn.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.randn.NAME":"\nbase.random.randn.NAME\n Generator name.\n","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n","base.random.randn.seed":"\nbase.random.randn.seed\n Pseudorandom number generator seed.\n","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n Length of generator seed.\n","base.random.randn.state":"\nbase.random.randn.state\n Generator state.\n","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n Length of generator state.\n","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n","base.random.randu.factory":"\nbase.random.randu.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n","base.random.randu.NAME":"\nbase.random.randu.NAME\n Generator name.\n","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n","base.random.randu.MIN":"\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n","base.random.randu.MAX":"\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n","base.random.randu.seed":"\nbase.random.randu.seed\n Pseudorandom number generator seed.\n","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n Length of generator seed.\n","base.random.randu.state":"\nbase.random.randu.state\n Generator state.\n","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n Length of generator state.\n","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.rayleigh":"\nbase.random.rayleigh( σ:number )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n Generator name.\n","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n Length of generator seed.\n","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n Generator state.\n","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n Length of generator state.\n","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.t":"\nbase.random.t( v:number )\n Returns a pseudorandom number drawn from a Student's t distribution.\n","base.random.t.factory":"\nbase.random.t.factory( [v:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n","base.random.t.NAME":"\nbase.random.t.NAME\n Generator name.\n","base.random.t.PRNG":"\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n","base.random.t.seed":"\nbase.random.t.seed\n Pseudorandom number generator seed.\n","base.random.t.seedLength":"\nbase.random.t.seedLength\n Length of generator seed.\n","base.random.t.state":"\nbase.random.t.state\n Generator state.\n","base.random.t.stateLength":"\nbase.random.t.stateLength\n Length of generator state.\n","base.random.t.byteLength":"\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n","base.random.t.toJSON":"\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.triangular":"\nbase.random.triangular( a:number, b:number, c:number )\n Returns a pseudorandom number drawn from a triangular distribution.\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n Generator name.\n","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n","base.random.triangular.seed":"\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n Length of generator seed.\n","base.random.triangular.state":"\nbase.random.triangular.state\n Generator state.\n","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n Length of generator state.\n","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.uniform":"\nbase.random.uniform( a:number, b:number )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n Generator name.\n","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n","base.random.uniform.seed":"\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n Length of generator seed.\n","base.random.uniform.state":"\nbase.random.uniform.state\n Generator state.\n","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n Length of generator state.\n","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.weibull":"\nbase.random.weibull( k:number, λ:number )\n Returns a pseudorandom number drawn from a Weibull distribution.\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k:number, λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n Generator name.\n","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n","base.random.weibull.seed":"\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n Length of generator seed.\n","base.random.weibull.state":"\nbase.random.weibull.state\n Generator state.\n","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n Length of generator state.\n","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.rcbrt":"\nbase.rcbrt( x:number )\n Computes the reciprocal cube root of a double-precision floating-point\n number.\n","base.rcbrtf":"\nbase.rcbrtf( x:number )\n Computes the reciprocal cube root of a single-precision floating-point\n number.\n","base.reldiff":"\nbase.reldiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers.\n","base.removeFirst":"\nbase.removeFirst( str:string, n:integer )\n Removes the first `n` UTF-16 code units of a string.\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str:string, n:integer )\n Removes the first `n` Unicode code points of a string.\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str:string, n:integer )\n Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n","base.removeLast":"\nbase.removeLast( str:string, n:integer )\n Removes the last `n` UTF-16 code units of a string.\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str:string, n:integer )\n Removes the last `n` Unicode code points of a string.\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str:string, n:integer )\n Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n","base.rempio2":"\nbase.rempio2( x:number, y:Array|TypedArray|Object )\n Computes `x - nπ/2 = r`.\n","base.repeat":"\nbase.repeat( str:string, n:integer )\n Repeats a string `n` times and returns the concatenated result.\n","base.replace":"\nbase.replace( str:string, search:RegExp, newval:string|Function )\n Replaces search occurrences with a replacement string.\n","base.replaceAfter":"\nbase.replaceAfter( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring after the first occurrence of a specified search\n string.\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring after the last occurrence of a specified search\n string.\n","base.replaceBefore":"\nbase.replaceBefore( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring before the first occurrence of a specified search\n string.\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring before the last occurrence of a specified search\n string.\n","base.reverse":"\nbase.reverse( str:string )\n Reverses the UTF-16 code units of a string.\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str:string )\n Reverses the Unicode code points of a string.\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str:string )\n Reverses the grapheme clusters (i.e., user-perceived characters) of a\n string.\n","base.rightPad":"\nbase.rightPad( str:string, len:integer, pad:string )\n Right pads a string such that the padded string has a length of at least\n `len`.\n","base.rightTrim":"\nbase.rightTrim( str:string )\n Trims whitespace from the end of a string.\n","base.risingFactorial":"\nbase.risingFactorial( x:number, n:integer )\n Computes the rising factorial of `x` and `n`.\n","base.rotl32":"\nbase.rotl32( x:integer, shift:integer )\n Performs a bitwise rotation to the left.\n","base.rotr32":"\nbase.rotr32( x:integer, shift:integer )\n Performs a bitwise rotation to the right.\n","base.round":"\nbase.round( x:number )\n Rounds a numeric value to the nearest integer.\n","base.round2":"\nbase.round2( x:number )\n Rounds a numeric value to the nearest power of two on a linear scale.\n","base.round10":"\nbase.round10( x:number )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n","base.roundb":"\nbase.roundb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n","base.roundn":"\nbase.roundn( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n`.\n","base.roundsd":"\nbase.roundsd( x:number, n:integer[, b:integer] )\n Rounds a double-precision floating-point number to the nearest value with\n `n` significant figures.\n","base.rsqrt":"\nbase.rsqrt( x:number )\n Computes the reciprocal square root of a double-precision floating-point\n number.\n","base.rsqrtf":"\nbase.rsqrtf( x:number )\n Computes the reciprocal square root of a single-precision floating-point\n number.\n","base.sargs2multislice":"\nbase.sargs2multislice( str:string )\n Creates a MultiSlice object from a comma-separated list of string-serialized\n MultiSlice constructor arguments.\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value:any, dtype:string|DataType, order:string )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n","base.secd":"\nbase.secd( x:number )\n Computes the secant of an angle measured in degrees.\n","base.seq2multislice":"\nbase.seq2multislice( str:string, shape:Array, strict:boolean )\n Converts a multidimensional subsequence string to a MultiSlice object.\n","base.seq2slice":"\nbase.seq2slice( str:string, len:integer, strict:boolean )\n Converts a subsequence string to a Slice object.\n","base.setHighWord":"\nbase.setHighWord( x:number, high:integer )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n","base.setLowWord":"\nbase.setLowWord( x:number, low:integer )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n","base.sici":"\nbase.sici( x:number )\n Computes the sine and cosine integrals.\n","base.sici.assign":"\nbase.sici.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n","base.signbit":"\nbase.signbit( x:number )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.signbitf":"\nbase.signbitf( x:float )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.significandf":"\nbase.significandf( x:float )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n","base.signum":"\nbase.signum( x:number )\n Evaluates the signum function for a double-precision floating-point number.\n","base.signumf":"\nbase.signumf( x:number )\n Evaluates the signum function for a single-precision floating-point number.\n","base.sin":"\nbase.sin( x:number )\n Computes the sine of a number.\n","base.sinc":"\nbase.sinc( x:number )\n Computes the normalized cardinal sine of a number.\n","base.sincos":"\nbase.sincos( x:number )\n Simultaneously computes the sine and cosine of an angle measured in radians.\n","base.sincos.assign":"\nbase.sincos.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Simultaneously computes the sine and cosine of an angle measured in radians\n and assigns the results to a provided output array.\n","base.sincospi":"\nbase.sincospi( x:number )\n Simultaneously computes the sine and cosine of a number times π.\n","base.sincospi.assign":"\nbase.sincospi.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n","base.sinh":"\nbase.sinh( x:number )\n Computes the hyperbolic sine of a double-precision floating-point number.\n","base.sinpi":"\nbase.sinpi( x:number )\n Computes the value of `sin(πx)`.\n","base.slice2seq":"\nbase.slice2seq( slice:Slice )\n Converts a Slice object to a subsequence string.\n","base.sliceLength":"\nbase.sliceLength( slice:Slice )\n Returns the number of elements in a normalized slice.\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice:MultiSlice )\n Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice:MultiSlice )\n Returns a list of reduced dimensions in an un-normalized multi-slice.\n","base.sliceShape":"\nbase.sliceShape( slice:MultiSlice )\n Returns the shape of a normalized multi-slice.\n","base.snakecase":"\nbase.snakecase( str:string )\n Converts a string to snake case.\n","base.spence":"\nbase.spence( x:number )\n Evaluates Spence's function, which is also known as the dilogarithm.\n","base.sqrt":"\nbase.sqrt( x:number )\n Computes the principal square root of a double-precision floating-point\n number.\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x:number )\n Computes the principal square root of `1+x` minus one.\n","base.sqrtf":"\nbase.sqrtf( x:number )\n Computes the principal square root of a single-precision floating-point\n number.\n","base.sqrtpi":"\nbase.sqrtpi( x:number )\n Computes the principal square root of the product of π and a positive\n double-precision floating-point number.\n","base.startcase":"\nbase.startcase( str:string )\n Capitalizes the first letter of each word in an input string.\n","base.startsWith":"\nbase.startsWith( str:string, search:string, position:integer )\n Tests if a string starts with the characters of another string.\n","base.stickycase":"\nbase.stickycase( str[, p] )\n Converts a string to sticky case.\n","base.strided.binary":"\nbase.strided.binary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike, dtypes3:ArrayLike[, options:Object] )\n Generates a list of binary interface signatures from strided array data\n types.\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table:Object, signatures:ArrayLike )\n Assigns callbacks to binary interfaces according to type promotion rules.\n","base.strided.ccopy":"\nbase.strided.ccopy( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector.\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n","base.strided.cmap":"\nbase.strided.cmap( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer, fcn:Function )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array.\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n","base.strided.cswap":"\nbase.strided.cswap( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer )\n Interchanges two complex single-precision floating-point vectors.\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n","base.strided.cumax":"\nbase.strided.cumax( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative maximum of a strided array.\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative maximum absolute value of a strided array.\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n","base.strided.cumin":"\nbase.strided.cumin( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative minimum of a strided array.\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n","base.strided.cuminabs":"\nbase.strided.cuminabs( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative minimum absolute value of a strided array.\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n","base.strided.dabs":"\nbase.strided.dabs( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dabs2":"\nbase.strided.dabs2( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dapx":"\nbase.strided.dapx( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array.\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dapxsum":"\nbase.strided.dapxsum( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum.\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation.\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n","base.strided.dasum":"\nbase.strided.dasum( N:integer, x:Float64Array, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.dasumpw":"\nbase.strided.dasumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation.\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n","base.strided.daxpy":"\nbase.strided.daxpy( N:integer, alpha:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n","base.strided.dcbrt":"\nbase.strided.dcbrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dceil":"\nbase.strided.dceil( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dcopy":"\nbase.strided.dcopy( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.dcumax":"\nbase.strided.dcumax( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.dcumin":"\nbase.strided.dcumin( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.dcusum":"\nbase.strided.dcusum( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N:integer, sum:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dcusumors":"\nbase.strided.dcusumors( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation.\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation.\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.ddot":"\nbase.strided.ddot( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the dot product of two double-precision floating-point vectors.\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n","base.strided.dfill":"\nbase.strided.dfill( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Fills a double-precision floating-point strided array with a specified\n scalar constant.\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Fills a double-precision floating-point strided array with a specified\n scalar constant using alternative indexing semantics.\n","base.strided.dfloor":"\nbase.strided.dfloor( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dinv":"\nbase.strided.dinv( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dmap":"\nbase.strided.dmap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array.\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.dmap2":"\nbase.strided.dmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, z:Float64Array, sz:integer, fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays and assigns results to a double-precision floating-point strided\n output array.\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n y:Float64Array, sy:integer, oy:integer, z:Float64Array, sz:integer, \n oz:integer, fcn:Function )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.dmax":"\nbase.strided.dmax( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array.\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmean":"\nbase.strided.dmean( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.dmeanli":"\nbase.strided.dmeanli( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n","base.strided.dmeanors":"\nbase.strided.dmeanors( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N:integer, c:number, x:Float64Array, \n strideX:integer, out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array.\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmidrange":"\nbase.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )\n Computes the mid-range of a double-precision floating-point strided array.\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.dmin":"\nbase.strided.dmin( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array.\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dminabs":"\nbase.strided.dminabs( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dminsorted":"\nbase.strided.dminsorted( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmskabs":"\nbase.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.dmskceil":"\nbase.strided.dmskceil( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskinv":"\nbase.strided.dmskinv( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmskmap":"\nbase.strided.dmskmap( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float64Array, sy:integer, \n oy:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, m:Uint8Array, sm:integer, z:Float64Array, sz:integer, \n fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, y:Float64Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n om:integer, z:Float64Array, sz:integer, oz:integer, fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.dmskmax":"\nbase.strided.dmskmax( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.dmskmin":"\nbase.strided.dmskmin( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.dmskramp":"\nbase.strided.dmskramp( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskrange":"\nbase.strided.dmskrange( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y`.\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.dnanasum":"\nbase.strided.dnanasum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values.\n","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n","base.strided.dnanmax":"\nbase.strided.dnanmax( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnanmean":"\nbase.strided.dnanmean( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.dnanmin":"\nbase.strided.dnanmin( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnannsum":"\nbase.strided.dnannsum( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.dnanrange":"\nbase.strided.dnanrange( N:integer, x:Float64Array, strideX:integer )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n","base.strided.dnansum":"\nbase.strided.dnansum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dnansumors":"\nbase.strided.dnansumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values.\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n","base.strided.dnrm2":"\nbase.strided.dnrm2( N:integer, x:Float64Array, stride:integer )\n Computes the L2-norm of a double-precision floating-point vector.\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n","base.strided.dramp":"\nbase.strided.dramp( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.drange":"\nbase.strided.drange( N:integer, x:Float64Array, strideX:integer )\n Computes the range of a double-precision floating-point strided array.\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n","base.strided.drev":"\nbase.strided.drev( N:integer, x:Float64Array, strideX:integer )\n Reverses a double-precision floating-point strided array in-place.\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n","base.strided.drsqrt":"\nbase.strided.drsqrt( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using extended accumulation and returning\n an extended precision result.\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n","base.strided.dscal":"\nbase.strided.dscal( N:integer, alpha:number, x:Float64Array, stride:integer )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n","base.strided.dsdot":"\nbase.strided.dsdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation and result.\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n","base.strided.dsem":"\nbase.strided.dsem( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dsemch":"\nbase.strided.dsemch( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n","base.strided.dsempn":"\nbase.strided.dsempn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n","base.strided.dsemtk":"\nbase.strided.dsemtk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n","base.strided.dsemwd":"\nbase.strided.dsemwd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.dsemyc":"\nbase.strided.dsemyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n","base.strided.dsmean":"\nbase.strided.dsmean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using a two-pass error correction algorithm\n with extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using Welford's algorithm with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N:integer, x:Float32Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n","base.strided.dsnansum":"\nbase.strided.dsnansum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation,\n and returning an extended precision result.\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n","base.strided.dsorthp":"\nbase.strided.dsorthp( N:integer, order:number, x:Float64Array, strideX:integer )\n Sorts a double-precision floating-point strided array using heapsort.\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n","base.strided.dsortins":"\nbase.strided.dsortins( N:integer, order:number, x:Float64Array, \n strideX:integer )\n Sorts a double-precision floating-point strided array using insertion sort.\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n","base.strided.dsortsh":"\nbase.strided.dsortsh( N:integer, order:number, x:Float64Array, stride:integer )\n Sorts a double-precision floating-point strided array using Shellsort.\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N:integer, order:number, x:Float64Array, \n stride:integer, offset:integer )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n","base.strided.dsqrt":"\nbase.strided.dsqrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dssum":"\nbase.strided.dssum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and returning an extended precision result.\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n","base.strided.dssumors":"\nbase.strided.dssumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and returning\n an extended precision result.\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n","base.strided.dssumpw":"\nbase.strided.dssumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and returning an\n extended precision result.\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n","base.strided.dstdev":"\nbase.strided.dstdev( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dstdevch":"\nbase.strided.dstdevch( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n","base.strided.dsum":"\nbase.strided.dsum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements.\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.dsumors":"\nbase.strided.dsumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dsumpw":"\nbase.strided.dsumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.dsvariance":"\nbase.strided.dsvariance( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N:integer, correction:number, \n x:Float32Array, strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dswap":"\nbase.strided.dswap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Interchanges two double-precision floating-point vectors.\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n","base.strided.dtrunc":"\nbase.strided.dtrunc( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype:integer )\n Returns the data type string associated with a strided array data type\n enumeration constant.\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype:any )\n Returns the enumeration constant associated with a supported strided array\n data type value.\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype:any )\n Returns the data type string associated with a supported data type value.\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype:string )\n Returns the enumeration constant associated with a strided array data type\n string.\n","base.strided.dvariance":"\nbase.strided.dvariance( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array.\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.dvariancech":"\nbase.strided.dvariancech( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.dvarm":"\nbase.strided.dvarm( N:integer, correction:number, mean:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.gapx":"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each element in a strided array.\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n","base.strided.gapxsum":"\nbase.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum.\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation.\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation.\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n","base.strided.gasum":"\nbase.strided.gasum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.gasumpw":"\nbase.strided.gasumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.gaxpy":"\nbase.strided.gaxpy( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n","base.strided.gcopy":"\nbase.strided.gcopy( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.gcusum":"\nbase.strided.gcusum( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements.\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumors":"\nbase.strided.gcusumors( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n","base.strided.gdot":"\nbase.strided.gdot( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the dot product of two vectors.\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n","base.strided.gfill":"\nbase.strided.gfill( N:integer, alpha:any, x:ArrayLikeObject, strideX:integer )\n Fills a strided array with a specified scalar constant.\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N:integer, alpha:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n","base.strided.gfillBy":"\nbase.strided.gfillBy( N:integer, x:ArrayLikeObject, strideX:integer, \n clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function.\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N:integer, x:Array|TypedArray, strideX:integer, \n out:Array|TypedArray, strideOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, out:Array|TypedArray, strideOut:integer, \n offsetOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansum":"\nbase.strided.gnansum( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values.\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.gnansumors":"\nbase.strided.gnansumors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n","base.strided.gnrm2":"\nbase.strided.gnrm2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the L2-norm of a vector.\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the L2-norm of a vector using alternative indexing semantics.\n","base.strided.grev":"\nbase.strided.grev( N:integer, x:ArrayLikeObject, strideX:integer )\n Reverses a strided array in-place.\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer )\n Reverses a strided array in-place using alternative indexing semantics.\n","base.strided.gscal":"\nbase.strided.gscal( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Multiplies a vector by a scalar constant.\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Multiplies a vector by a scalar constant using alternative indexing\n semantics.\n","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort.\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort.\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n","base.strided.gsorthp":"\nbase.strided.gsorthp( N:integer, order:number, x:Array|TypedArray, \n strideX:integer )\n Sorts a strided array using heapsort.\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Sorts a strided array using heapsort and alternative indexing semantics.\n","base.strided.gsortins":"\nbase.strided.gsortins( N:integer, order:number, x:Array|TypedArray, \n strideX:integer )\n Sorts a strided array using insertion sort.\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n","base.strided.gsortsh":"\nbase.strided.gsortsh( N:integer, order:number, x:Array|TypedArray, \n strideX:integer )\n Sorts a strided array using Shellsort.\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n","base.strided.gsum":"\nbase.strided.gsum( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements.\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gsumors":"\nbase.strided.gsumors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n","base.strided.gsumpw":"\nbase.strided.gsumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using pairwise summation.\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n","base.strided.gswap":"\nbase.strided.gswap( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Interchanges vectors `x` and `y`.\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n","base.strided.mapBy":"\nbase.strided.mapBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, fcn:Function, clbk:Function[, \n thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, fcn:Function, \n clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.mapBy2":"\nbase.strided.mapBy2( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n fcn:Function, clbk:Function[, thisArg:any] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array.\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, fcn:Function, \n clbk:Function[, thisArg:any] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n","base.strided.max":"\nbase.strided.max( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum value of a strided array.\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n","base.strided.maxabs":"\nbase.strided.maxabs( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum absolute value of a strided array.\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n","base.strided.maxBy":"\nbase.strided.maxBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the maximum value of a strided array via a callback function.\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n","base.strided.maxsorted":"\nbase.strided.maxsorted( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum value of a sorted strided array.\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N:integer, stride:integer, offset:integer )\n Returns the maximum accessible index based on a set of provided strided\n array parameters.\n","base.strided.mean":"\nbase.strided.mean( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array.\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n","base.strided.meankbn":"\nbase.strided.meankbn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm.\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n","base.strided.meankbn2":"\nbase.strided.meankbn2( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm.\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.meanors":"\nbase.strided.meanors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation.\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n","base.strided.meanpn":"\nbase.strided.meanpn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm.\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n","base.strided.meanpw":"\nbase.strided.meanpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using pairwise summation.\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n","base.strided.meanwd":"\nbase.strided.meanwd( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n","base.strided.mediansorted":"\nbase.strided.mediansorted( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the median value of a sorted strided array.\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta:Object, dtypes:ArrayLikeObject, \n obj:Object|Function, bool:boolean )\n Defines non-enumerable read-only properties which expose strided array\n function meta data.\n","base.strided.min":"\nbase.strided.min( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum value of a strided array.\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n","base.strided.minabs":"\nbase.strided.minabs( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum absolute value of a strided array.\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n","base.strided.minBy":"\nbase.strided.minBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the minimum value of a strided array via a callback function.\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n","base.strided.minsorted":"\nbase.strided.minsorted( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum value of a sorted strided array.\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N:integer, stride:integer, offset:integer )\n Returns the minimum accessible index based on a set of provided strided\n array parameters.\n","base.strided.mskmax":"\nbase.strided.mskmax( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the maximum value of a strided array according to a mask.\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskmin":"\nbase.strided.mskmin( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the minimum value of a strided array according to a mask.\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskrange":"\nbase.strided.mskrange( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the range of a strided array according to a mask.\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskunary":"\nbase.strided.mskunary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array and assigns results to elements in a\n strided output array.\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike[, options:Object] )\n Generates a list of masked unary interface signatures from strided array\n data types.\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table:Object, \n signatures:ArrayLike )\n Assigns callbacks to masked unary interfaces according to type promotion\n rules.\n","base.strided.nanmax":"\nbase.strided.nanmax( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values.\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the maximum value of strided array via a callback function,\n ignoring `NaN` values.\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Computes the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmean":"\nbase.strided.nanmean( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation.\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm.\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm.\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanmin":"\nbase.strided.nanmin( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanminabs":"\nbase.strided.nanminabs( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values.\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanminBy":"\nbase.strided.nanminBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values.\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the maximum value of a strided array according to a mask and\n ignoring `NaN` values.\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the minimum value of a strided array according to a mask and\n ignoring `NaN` values.\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the range of a strided array according to a mask and ignoring `NaN`\n values.\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanrange":"\nbase.strided.nanrange( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the range of a strided array, ignoring `NaN` values.\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the range of a strided array via a callback function, ignoring\n `NaN` values.\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n","base.strided.nanstdev":"\nbase.strided.nanstdev( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values.\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm.\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm.\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm.\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm.\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.nanvariance":"\nbase.strided.nanvariance( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values.\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm.\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n","base.strided.nullary":"\nbase.strided.nullary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a nullary callback and assigns results to elements in a strided\n output array.\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n","base.strided.offsetView":"\nbase.strided.offsetView( x:TypedArray, offset:integer )\n Returns a typed array view having the same data type as a provided input\n typed array and starting at a specified index offset.\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.quinary":"\nbase.strided.quinary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.range":"\nbase.strided.range( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the range of a strided array.\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the range of a strided array using alternative indexing semantics.\n","base.strided.rangeBy":"\nbase.strided.rangeBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the range of a strided array via a callback function.\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x:Complex128Array|Complex64Array, \n offset:integer )\n Returns a real-valued floating-point array view of a complex-valued\n floating-point array having the same precision.\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x:Complex64Array, offset:integer )\n Returns a Float32Array view of a Complex64Array.\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x:Complex128Array, offset:integer )\n Returns a Float64Array view of a Complex128Array.\n","base.strided.sabs":"\nbase.strided.sabs( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sabs2":"\nbase.strided.sabs2( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sapx":"\nbase.strided.sapx( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array.\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.sapxsum":"\nbase.strided.sapxsum( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum.\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm.\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation.\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n","base.strided.sasum":"\nbase.strided.sasum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.sasumpw":"\nbase.strided.sasumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n","base.strided.saxpy":"\nbase.strided.saxpy( N:integer, alpha:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n","base.strided.scbrt":"\nbase.strided.scbrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.sceil":"\nbase.strided.sceil( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.scopy":"\nbase.strided.scopy( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.scumax":"\nbase.strided.scumax( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.scumin":"\nbase.strided.scumin( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.scuminabs":"\nbase.strided.scuminabs( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.scusum":"\nbase.strided.scusum( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N:integer, sum:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.scusumors":"\nbase.strided.scusumors( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n","base.strided.scusumpw":"\nbase.strided.scusumpw( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sdot":"\nbase.strided.sdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the dot product of two single-precision floating-point vectors.\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.sdsdot":"\nbase.strided.sdsdot( N:integer, scalar:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N:integer, scalar:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n","base.strided.sdsmean":"\nbase.strided.sdsmean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignore `NaN` values and using extended accumulation.\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation.\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.sdssum":"\nbase.strided.sdssum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation.\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation.\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n","base.strided.sfill":"\nbase.strided.sfill( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Fills a single-precision floating-point strided array with a specified\n scalar value.\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n","base.strided.sfloor":"\nbase.strided.sfloor( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sinv":"\nbase.strided.sinv( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.smap":"\nbase.strided.smap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array.\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.smap2":"\nbase.strided.smap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n sy:integer, z:Float32Array, sz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, \n y:Float32Array, sy:integer, oy:integer, z:Float32Array, sz:integer, \n oz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.smax":"\nbase.strided.smax( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array.\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.smaxabs":"\nbase.strided.smaxabs( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smean":"\nbase.strided.smean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.smeankbn":"\nbase.strided.smeankbn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.smeanli":"\nbase.strided.smeanli( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n","base.strided.smeanors":"\nbase.strided.smeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.smeanpn":"\nbase.strided.smeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm.\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.smeanpw":"\nbase.strided.smeanpw( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n","base.strided.smeanwd":"\nbase.strided.smeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.smediansorted":"\nbase.strided.smediansorted( N:integer, x:Float32Array, strideX:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smidrange":"\nbase.strided.smidrange( N:integer, x:Float32Array, strideX:integer )\n Computes the mid-range of a single-precision floating-point strided array.\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.smin":"\nbase.strided.smin( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array.\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sminabs":"\nbase.strided.sminabs( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.sminsorted":"\nbase.strided.sminsorted( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smskabs":"\nbase.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskabs2":"\nbase.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.smskceil":"\nbase.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskfloor":"\nbase.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskinv":"\nbase.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smskmap":"\nbase.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, \n oy:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.smskmap2":"\nbase.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, \n fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.smskmax":"\nbase.strided.smskmax( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.smskmin":"\nbase.strided.smskmin( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.smskramp":"\nbase.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskrange":"\nbase.strided.smskrange( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.snanmax":"\nbase.strided.snanmax( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanmean":"\nbase.strided.snanmean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.snanmin":"\nbase.strided.snanmin( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanminabs":"\nbase.strided.snanminabs( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanrange":"\nbase.strided.snanrange( N:integer, x:Float32Array, strideX:integer )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanstdev":"\nbase.strided.snanstdev( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n","base.strided.snansum":"\nbase.strided.snansum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.snansumors":"\nbase.strided.snansumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.snansumpw":"\nbase.strided.snansumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.snanvariance":"\nbase.strided.snanvariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values.\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n","base.strided.snrm2":"\nbase.strided.snrm2( N:integer, x:Float32Array, stride:integer )\n Computes the L2-norm of a single-precision floating-point vector.\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n","base.strided.sramp":"\nbase.strided.sramp( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.srange":"\nbase.strided.srange( N:integer, x:Float32Array, strideX:integer )\n Computes the range of a single-precision floating-point strided array.\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n","base.strided.srev":"\nbase.strided.srev( N:integer, x:Float32Array, strideX:integer )\n Reverses a single-precision floating-point strided array in-place.\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n","base.strided.srsqrt":"\nbase.strided.srsqrt( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sscal":"\nbase.strided.sscal( N:integer, alpha:number, x:Float32Array, stride:integer )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha`.\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n","base.strided.ssorthp":"\nbase.strided.ssorthp( N:integer, order:number, x:Float32Array, strideX:integer )\n Sorts a single-precision floating-point strided array using heapsort.\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n","base.strided.ssortins":"\nbase.strided.ssortins( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using insertion sort.\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n","base.strided.ssortsh":"\nbase.strided.ssortsh( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using Shellsort.\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n","base.strided.ssqrt":"\nbase.strided.ssqrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sstdev":"\nbase.strided.sstdev( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sstdevch":"\nbase.strided.sstdevch( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n","base.strided.ssum":"\nbase.strided.ssum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements.\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.ssumors":"\nbase.strided.ssumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.ssumpw":"\nbase.strided.ssumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.sswap":"\nbase.strided.sswap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Interchanges two single-precision floating-point vectors.\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n","base.strided.stdev":"\nbase.strided.stdev( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array.\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n","base.strided.stdevch":"\nbase.strided.stdevch( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n","base.strided.stdevpn":"\nbase.strided.stdevpn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n","base.strided.stdevtk":"\nbase.strided.stdevtk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n","base.strided.stdevwd":"\nbase.strided.stdevwd( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n","base.strided.stdevyc":"\nbase.strided.stdevyc( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer.\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n","base.strided.strunc":"\nbase.strided.strunc( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y`.\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.svariance":"\nbase.strided.svariance( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array.\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.svariancech":"\nbase.strided.svariancech( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.svariancepn":"\nbase.strided.svariancepn( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.svariancetk":"\nbase.strided.svariancetk( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.svariancewd":"\nbase.strided.svariancewd( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.ternary":"\nbase.strided.ternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.unary":"\nbase.strided.unary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function, clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function, clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike[, options:Object] )\n Generates a list of unary interface signatures from strided array data\n types.\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table:Object, signatures:ArrayLike )\n Assigns callbacks to unary interfaces according to type promotion rules.\n","base.strided.variance":"\nbase.strided.variance( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array.\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using alternative indexing\n semantics.\n","base.strided.variancech":"\nbase.strided.variancech( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n","base.strided.variancepn":"\nbase.strided.variancepn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a two-pass algorithm.\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n","base.strided.variancetk":"\nbase.strided.variancetk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n","base.strided.variancewd":"\nbase.strided.variancewd( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using Welford's algorithm.\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n","base.strided.varianceyc":"\nbase.strided.varianceyc( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer.\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n","base.strided.zmap":"\nbase.strided.zmap( N:integer, x:Complex128Array, strideX:integer, \n y:Complex128Array, strideY:integer, fcn:Function )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array.\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N:integer, x:Complex128Array, strideX:integer, \n offsetX:integer, y:Complex128Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n","base.str2multislice":"\nbase.str2multislice( str:string )\n Parses a string-serialized MultiSlice object.\n","base.str2slice":"\nbase.str2slice( str:string )\n Parses a string-serialized Slice object.\n","base.sub":"\nbase.sub( x:number, y:number )\n Subtracts two double-precision floating-point numbers `x` and `y`.\n","base.subf":"\nbase.subf( x:number, y:number )\n Subtracts two single-precision floating-point numbers `x` and `y`.\n","base.sumSeries":"\nbase.sumSeries( generator:Function[, options:Object] )\n Sum the elements of the series given by the supplied function.\n","base.tan":"\nbase.tan( x:number )\n Computes the tangent of a number.\n","base.tand":"\nbase.tand( x:number )\n Computes the tangent of an angle measured in degrees.\n","base.tanh":"\nbase.tanh( x:number )\n Computes the hyperbolic tangent of a double-precision floating-point number.\n","base.toBinaryString":"\nbase.toBinaryString( x:number )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x:float )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x:integer )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x:integer )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x:integer )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n","base.toWordf":"\nbase.toWordf( x:float )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n","base.toWords":"\nbase.toWords( x:number )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.toWords.assign":"\nbase.toWords.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n","base.transpose":"\nbase.transpose( x:ndarray, writable:boolean )\n Transposes a matrix (or a stack of matrices).\n","base.tribonacci":"\nbase.tribonacci( n:integer )\n Computes the nth Tribonacci number.\n","base.trigamma":"\nbase.trigamma( x:number )\n Evaluates the trigamma function.\n","base.trim":"\nbase.trim( str:string )\n Trims whitespace from the beginning and end of a `string`.\n","base.trunc":"\nbase.trunc( x:number )\n Rounds a double-precision floating-point number toward zero.\n","base.trunc2":"\nbase.trunc2( x:number )\n Rounds a numeric value to the nearest power of two toward zero.\n","base.trunc10":"\nbase.trunc10( x:number )\n Rounds a numeric value to the nearest power of ten toward zero.\n","base.truncateMiddle":"\nbase.truncateMiddle( str:string, len:integer, seq:string )\n Truncates the middle UTF-16 code units of a string to return a string\n having a specified length.\n","base.truncb":"\nbase.truncb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n","base.truncf":"\nbase.truncf( x:number )\n Rounds a single-precision floating-point number toward zero.\n","base.truncn":"\nbase.truncn( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n","base.truncsd":"\nbase.truncsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x:integer )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n","base.umul":"\nbase.umul( x:integer, y:integer )\n Multiples two unsigned 32-bit integers.\n","base.umuldw":"\nbase.umuldw( a:integer, b:integer )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n","base.umuldw.assign":"\nbase.umuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n","base.uncapitalize":"\nbase.uncapitalize( str:string )\n Lowercases the first character of a string.\n","base.uppercase":"\nbase.uppercase( str:string )\n Converts a string to uppercase.\n","base.vercos":"\nbase.vercos( x:number )\n Computes the versed cosine.\n","base.versin":"\nbase.versin( x:number )\n Computes the versed sine.\n","base.wrap":"\nbase.wrap( v:number, min:number, max:number )\n Wraps a value to the half-open interval `[min,max)`.\n","base.xlog1py":"\nbase.xlog1py( x:number, y:number )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n","base.xlogy":"\nbase.xlogy( x:number, y:number )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n","base.zeta":"\nbase.zeta( s:number )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and other characteristics.\n","bifurcate":"\nbifurcate( collection:Array|TypedArray|Object, [options:Object,] \n filter:Array|TypedArray|Object )\n Splits values into two groups.\n","bifurcateBy":"\nbifurcateBy( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateByAsync":"\nbifurcateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which splits values into two groups according to an\n predicate function.\n","bifurcateIn":"\nbifurcateIn( obj:Object|Array|TypedArray, [options:Object,] predicate:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateOwn":"\nbifurcateOwn( obj:Object|Array|TypedArray, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n","BigInt":"\nBigInt( value:integer|string )\n Returns a BigInt.\n","binomialTest":"\nbinomialTest( x:(number|Array[, n:Array][, options:Object] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n","Boolean":"\nBoolean( value:any )\n Returns a boolean.\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n","BooleanArray":"\nBooleanArray()\n A Boolean array.\n\nBooleanArray( length:integer )\n Creates a boolean array having a specified length.\n\nBooleanArray( booleanarray:BooleanArray )\n Creates a boolean array from another boolean array.\n\nBooleanArray( typedarray:TypedArray )\n Creates a boolean array from a typed array.\n\nBooleanArray( obj:Object )\n Creates a boolean array from an array-like object or iterable.\n\nBooleanArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a boolean array view of an ArrayBuffer.\n","BooleanArray.from":"\nBooleanArray.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new boolean array from an array-like object or an iterable.\n","BooleanArray.of":"\nBooleanArray.of( element0:bool[, element1:bool[, ...elementN:bool]] )\n Creates a new boolean array from a variable number of arguments.\n","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","BooleanArray.name":"\nBooleanArray.name\n Typed array constructor name.\n","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n The number of array elements.\n","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value:boolean[, start:integer[, end:integer]] )\n Returns a modified typed array filled with a fill value.\n","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement:boolean[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement:boolean[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement:boolean[, fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v:bool|BooleanArray|ArrayLikeObject[, i:integer] )\n Sets one or more array elements.\n","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether at least one element passes a test.\n","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction:Function] )\n Sorts an array in-place.\n","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction:Function] )\n Returns a new typed array containing the elements in sorted order.\n","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index:integer, value:boolean )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n","broadcastArray":"\nbroadcastArray( x:ndarray, shape:ArrayLikeObject )\n Broadcasts an ndarray to a specified shape.\n","broadcastArrays":"\nbroadcastArrays( ...arrays:ndarray|ArrayLikeObject )\n Broadcasts ndarrays to a common shape.\n","Buffer":"\nBuffer\n\nBuffer( size:integer )\n Allocates a buffer having a specified number of bytes.\n\nBuffer( buffer:Buffer )\n Copies buffer data to a new Buffer instance.\n\nBuffer( array:Array )\n Allocates a buffer using an array of octets.\n\nBuffer( str:string[, encoding:string] )\n Allocates a buffer containing a provided string.\n","buffer2json":"\nbuffer2json( buffer:Buffer )\n Returns a JSON representation of a buffer.\n","BYTE_ORDER":"\nBYTE_ORDER\n Platform byte order.\n","camelcase":"\ncamelcase( str:string )\n Converts a string to camel case.\n","capitalize":"\ncapitalize( str:string )\n Capitalizes the first character in a string.\n","capitalizeKeys":"\ncapitalizeKeys( obj:Object )\n Converts the first letter of each object key to uppercase.\n","CATALAN":"\nCATALAN\n Catalan's constant.\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n Returns US birth data from 1969 to 1988, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n Returns US birth data from 1994 to 2003, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n the Center for Disease Control and Prevention's National Center for Health\n Statistics.\n","chdir":"\nchdir( path:string )\n Changes the current working directory.\n","chi2gof":"\nchi2gof( x:ndarray|Array|TypedArray, y:ndarray|Array|TypedArray|string[, \n ...args:number][, options:Object] )\n Performs a chi-square goodness-of-fit test.\n","chi2test":"\nchi2test( x:ndarray|Array[, options:Object] )\n Performs a chi-square independence test.\n","circarray2iterator":"\ncircarray2iterator( src:ArrayLikeObject[, options:Object][, mapFcn:Function[, \n thisArg:any]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n","circularArrayStream":"\ncircularArrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n","CircularBuffer":"\nCircularBuffer( buffer:integer|ArrayLike )\n Circular buffer constructor.\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n Clears a buffer.\n","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters:integer] )\n Returns an iterator for iterating over a circular buffer.\n","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value:any )\n Adds a value to a circular buffer.\n","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n","close":"\nclose( fd:integer, clbk:Function )\n Asynchronously closes a file descriptor, so that the file descriptor no\n longer refers to any file and may be reused.\n","close.sync":"\nclose.sync( fd:integer )\n Synchronously closes a file descriptor.\n","CMUDICT":"\nCMUDICT( [options:Object] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n","codePointAt":"\ncodePointAt( str:string, idx:integer[, backward:boolean] )\n Returns a Unicode code point from a string at a specified position.\n","commonKeys":"\ncommonKeys( obj1:any, obj2:any[, ...obj:any] )\n Returns the common own property names of two or more objects.\n","commonKeysIn":"\ncommonKeysIn( obj1:any, obj2:any[, ...obj:any] )\n Returns the common own and inherited property names of two or more objects.\n","complex":"\ncomplex( real:number, imag:number[, dtype:string] )\n Creates a complex number.\n","Complex64":"\nComplex64( real:number, imag:number )\n 64-bit complex number constructor.\n","Complex64.name":"\nComplex64.name\n Constructor name.\n","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n Canonical single-precision complex floating-point NaN.\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n Single-precision complex floating-point zero.\n","Complex64Array":"\nComplex64Array()\n A 64-bit complex number array.\n\nComplex64Array( length:integer )\n Creates a 64-bit complex number array having a specified length.\n\nComplex64Array( complexarray:Complex64Array )\n Creates a 64-bit complex number array from another complex number array.\n\nComplex64Array( typedarray:TypedArray )\n Creates a 64-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\nComplex64Array( obj:Object )\n Creates a 64-bit complex number array from an array-like object or iterable.\n\nComplex64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a 64-bit complex number array view of an ArrayBuffer.\n","Complex64Array.from":"\nComplex64Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n","Complex64Array.of":"\nComplex64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","Complex64Array.name":"\nComplex64Array.name\n Typed array constructor name.\n","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n The number of array elements.\n","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value:Complex64[, start:integer[, end:integer]] )\n Returns a modified typed array filled with a fill value.\n","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement:Complex64[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement:Complex64[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement:Complex64[, \n fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z:Complex64|Complex64Array|ArrayLikeObject[, \n i:integer] )\n Sets one or more array elements.\n","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction:Function )\n Sorts an array in-place.\n","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn:Function )\n Returns a new typed array containing the elements in sorted order.\n","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n","Complex128":"\nComplex128( real:number, imag:number )\n 128-bit complex number constructor.\n","Complex128.name":"\nComplex128.name\n Constructor name.\n","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n","Complex128Array":"\nComplex128Array()\n A 128-bit complex number array.\n\nComplex128Array( length:integer )\n Creates a 128-bit complex number array having a specified length.\n\nComplex128Array( complexarray:Complex128Array )\n Creates a 64-bit complex number array from another complex number array.\n\nComplex128Array( typedarray:TypedArray )\n Creates a 128-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\nComplex128Array( obj:Object )\n Creates a 128-bit complex number array from an array-like object or\n iterable.\n\nComplex128Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a 128-bit complex number array view of an ArrayBuffer.\n","Complex128Array.from":"\nComplex128Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n","Complex128Array.of":"\nComplex128Array.of( element0:number|ComplexLike[, \n element1:number |ComplexLike[, ...elementN:number|ComplexLike]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","Complex128Array.name":"\nComplex128Array.name\n Typed array constructor name.\n","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n The number of array elements.\n","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value:Complex128[, start:integer[, \n end:integer]] )\n Returns a modified typed array filled with a fill value.\n","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement:Complex128[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement:Complex128[, \n fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement:Complex128[, \n fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z:Complex128|Complex128Array|ArrayLikeObject[, \n i:integer] )\n Sets one or more array elements.\n","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether at least one element passes a test.\n","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction:Function )\n Sorts an array in-place.\n","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn:Function )\n Returns a new typed array containing the elements in sorted order.\n","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index:integer, value:Complex128 )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n","complexarray":"\ncomplexarray( [dtype:string] )\n Creates a complex typed array.\n\ncomplexarray( length:integer[, dtype:string] )\n Returns a complex number typed array having a specified length.\n\ncomplexarray( complexarray:ComplexArray[, dtype:string] )\n Creates a complex number typed array from another complex number typed\n array.\n\ncomplexarray( obj:Object[, dtype:string] )\n Creates a complex number typed array from an array-like object or iterable.\n\ncomplexarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a complex number typed array view of an ArrayBuffer.\n","complexarrayCtors":"\ncomplexarrayCtors( dtype:string )\n Returns a complex typed array constructor.\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n","complexCtors":"\ncomplexCtors( dtype:string )\n Returns a complex number constructor.\n","complexDataType":"\ncomplexDataType( value:any )\n Returns the data type of a complex number object.\n","complexDataTypes":"\ncomplexDataTypes()\n Returns a list of complex number data types.\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1:string, dtype2:string] )\n Returns the complex number data type with the smallest size and closest\n \"kind\" to which data types can be safely cast.\n","compose":"\ncompose( ...f:Function )\n Function composition.\n","composeAsync":"\ncomposeAsync( ...f:Function )\n Function composition.\n","configdir":"\nconfigdir( [p:string] )\n Returns a directory for user-specific configuration files.\n","conj":"\nconj( z:Complex128 )\n Returns the complex conjugate of a double-precision complex floating-point\n number.\n","conjf":"\nconjf( z:Complex64 )\n Returns the complex conjugate of a single-precision complex floating-point\n number.\n","constantcase":"\nconstantcase( str:string )\n Converts a string to constant case.\n","constantFunction":"\nconstantFunction( val:any )\n Creates a function which always returns the same value.\n","constantStream":"\nconstantStream( value:string|Buffer|Uint8Array|any[, options:Object] )\n Returns a readable stream which always streams the same value.\n","constantStream.factory":"\nconstantStream.factory( [value:string|Buffer|Uint8Array|any, ][options:Object] )\n Returns a function for creating readable streams which always stream the\n same value.\n","constantStream.objectMode":"\nconstantStream.objectMode( value:any[, options:Object] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n","constructorName":"\nconstructorName( val:any )\n Determines the name of a value's constructor.\n","contains":"\ncontains( value:ArrayLike, searchValue:any[, position:integer] )\n Tests if an array-like value contains a search value.\n","convertArray":"\nconvertArray( arr:ArrayLikeObject, dtype:string )\n Converts an input array to an array of a different data type.\n","convertArraySame":"\nconvertArraySame( x:ArrayLikeObject, y:Array|TypedArray )\n Converts an input array to the same data type as a second input array.\n","convertPath":"\nconvertPath( from:string, to:string )\n Converts between POSIX and Windows paths.\n","copy":"\ncopy( value:any[, level:integer] )\n Copy or deep clone a value to an arbitrary depth.\n","copyBuffer":"\ncopyBuffer( buffer:Buffer )\n Copies buffer data to a new Buffer instance.\n","countBy":"\ncountBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Groups values according to an indicator function and returns group counts.\n","countByAsync":"\ncountByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Groups values according to an indicator function and returns group counts.\n","countByAsync.factory":"\ncountByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n","currentYear":"\ncurrentYear()\n Returns the current year.\n","curry":"\ncurry( fcn:Function[, arity:integer][, thisArg:any] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n","curryRight":"\ncurryRight( fcn:Function[, arity:integer][, thisArg:any] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n","cwd":"\ncwd()\n Returns the current working directory.\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar American-English words.\n","datasets":"\ndatasets( name:string[, options:Object] )\n Returns a dataset.\n","DataType":"\nDataType( value:any[, options:Object] )\n Data type constructor.\n","DataType.name":"\nDataType.name\n Constructor name.\n","DataType.prototype.alignment":"\nDataType.prototype.alignment\n Alignment (in bytes) for the data type.\n","DataType.prototype.byteLength":"\nDataType.prototype.byteLength\n Size (in bytes) of the data type.\n","DataType.prototype.byteOrder":"\nDataType.prototype.byteOrder\n Data type byte order.\n","DataType.prototype.char":"\nDataType.prototype.char\n Single letter character abbreviation for the data type.\n","DataType.prototype.description":"\nDataType.prototype.description\n Data type description.\n","DataType.prototype.enum":"\nDataType.prototype.enum\n Enumeration constant for the data type.\n","DataType.prototype.value":"\nDataType.prototype.value\n Raw (original) data type value.\n","DataType.prototype.toJSON":"\nDataType.prototype.toJSON()\n Serializes a data type instance as a JSON object.\n","DataType.prototype.toString":"\nDataType.prototype.toString()\n Serializes a data type instance to a string.\n","DataType.prototype.valueOf":"\nDataType.prototype.valueOf()\n Converts a data type instance to a primitive.\n","DataView":"\nDataView( buffer:ArrayBuffer|SharedArrayBuffer[, byteOffset:integer[, \n byteLength:integer]] )\n Returns a data view representing a provided array buffer.\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n Read-only property which returns the underlying array buffer.\n","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n","datespace":"\ndatespace( start:number, stop:number[, length:integer][ , options:Object] )\n Generates an array of linearly spaced dates.\n","dayOfQuarter":"\ndayOfQuarter( [month:string|integer|Date[, day:integer, year:integer]] )\n Returns the day of the quarter.\n","dayOfYear":"\ndayOfYear( [month:string|integer|Date[, day:integer, year:integer]] )\n Returns the day of the year.\n","daysInMonth":"\ndaysInMonth( [month:string|integer|Date[, year:integer]] )\n Returns the number of days in a month.\n","daysInYear":"\ndaysInYear( [value:integer|Date] )\n Returns the number of days in a year according to the Gregorian calendar.\n","ddot":"\nddot( x:ndarray, y:ndarray[, dim:integer] )\n Computes the dot product of two double-precision floating-point vectors.\n","debugSinkStream":"\ndebugSinkStream( [options:Object,] [clbk:Function] )\n Returns a writable stream for debugging stream pipelines.\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options:Object] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options:Object,] [clbk:Function] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n","debugStream":"\ndebugStream( [options:Object,] [clbk:Function] )\n Returns a transform stream for debugging stream pipelines.\n","debugStream.factory":"\ndebugStream.factory( [options:Object] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n","debugStream.objectMode":"\ndebugStream.objectMode( [options:Object,] [clbk:Function] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n","decorateAfter":"\ndecorateAfter( fcn:Function, arity:integer, after:Function[, thisArg:any] )\n Decorates a provided function such that the function's return value is\n provided as an argument to another function.\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn:Function, arity:integer, after:Function[, \n thisArg:any] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n","deepEqual":"\ndeepEqual( a:any, b:any )\n Tests for deep equality between two values.\n","deepGet":"\ndeepGet( obj:ObjectLike, path:string|Array[, options:Object] )\n Returns a nested property value.\n","deepGet.factory":"\ndeepGet.factory( path:string|Array[, options:Object] )\n Creates a reusable deep get function.\n","deepHasOwnProp":"\ndeepHasOwnProp( value:any, path:string|Array[, options:Object] )\n Returns a boolean indicating whether an object contains a nested key path.\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path:string|Array[, options:Object] )\n Returns a function which tests whether an object contains a nested key path.\n","deepHasProp":"\ndeepHasProp( value:any, path:string|Array[, options:Object] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n","deepHasProp.factory":"\ndeepHasProp.factory( path:string|Array[, options:Object] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n","deepPluck":"\ndeepPluck( arr:Array, path:string|Array[, options:Object] )\n Extracts a nested property value from each element of an object array.\n","deepSet":"\ndeepSet( obj:ObjectLike, path:string|Array, value:any[, options:Object] )\n Sets a nested property value.\n","deepSet.factory":"\ndeepSet.factory( path:string|Array[, options:Object] )\n Creates a reusable deep set function.\n","defineMemoizedProperty":"\ndefineMemoizedProperty( obj:Object, prop:string|symbol, descriptor:Object )\n Defines a memoized object property.\n","defineProperties":"\ndefineProperties( obj:Object, properties:Object )\n Defines (and/or modifies) object properties.\n","defineProperty":"\ndefineProperty( obj:Object, prop:string|symbol, descriptor:Object )\n Defines (or modifies) an object property.\n","dirname":"\ndirname( path:string )\n Returns a directory name.\n","dotcase":"\ndotcase( str:string )\n Converts a string to dot case.\n","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n","doUntil":"\ndoUntil( fcn:Function, predicate:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","doUntilAsync":"\ndoUntilAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","doUntilEach":"\ndoUntilEach( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n","doUntilEachRight":"\ndoUntilEachRight( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","doWhile":"\ndoWhile( fcn:Function, predicate:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","doWhileAsync":"\ndoWhileAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","doWhileEach":"\ndoWhileEach( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection.\n","doWhileEachRight":"\ndoWhileEachRight( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","dswap":"\ndswap( x:ndarray, y:ndarray[, dim:integer] )\n Interchanges two double-precision floating-point vectors.\n","E":"\nE\n Euler's number.\n","EMOJI":"\nEMOJI()\n Returns an emoji database.\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n Returns an object mapping emoji codes to pictographs.\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n Returns an object mapping emoji pictographs to codes.\n","emptyStream":"\nemptyStream( [options:Object] )\n Returns an \"empty\" readable stream.\n","emptyStream.factory":"\nemptyStream.factory( [options:Object] )\n Returns a function for creating empty readable streams.\n","emptyStream.objectMode":"\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n","endsWith":"\nendsWith( str:string, search:string[, len:integer] )\n Tests if a string ends with the characters of another string.\n","enumerableProperties":"\nenumerableProperties( value:any )\n Returns an array of an object's own enumerable property names and symbols.\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value:any )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value:any )\n Returns an array of an object's own enumerable symbol properties.\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n","ENV":"\nENV\n An object containing the user environment.\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n","error2json":"\nerror2json( error:Error )\n Returns a JSON representation of an error object.\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n","every":"\nevery( collection:Array|TypedArray|Object )\n Tests whether all elements in a collection are truthy.\n","everyBy":"\neveryBy( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n","everyByAsync":"\neveryByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n","everyByAsync.factory":"\neveryByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n","everyByRight":"\neveryByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n","everyByRightAsync":"\neveryByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n","everyInBy":"\neveryInBy( object:Object, predicate:Function[, thisArg:any ] )\n Test whether all properties (own and inherited) of an object pass a\n test implemented by a predicate function.\n","everyOwnBy":"\neveryOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every own property of an object pass a test implemented by a\n predicate function.\n","evil":"\nevil( str:string )\n Alias for `eval` global.\n","EXEC_PATH":"\nEXEC_PATH\n Absolute pathname of the executable which started the current Node.js\n process.\n","exists":"\nexists( path:string|Buffer, clbk:Function )\n Asynchronously tests whether a path exists on the filesystem.\n","exists.sync":"\nexists.sync( path:string|Buffer )\n Synchronously tests whether a path exists on the filesystem.\n","expandAcronyms":"\nexpandAcronyms( str:string )\n Expands acronyms in a string.\n","expandContractions":"\nexpandContractions( str:string )\n Expands all contractions to their formal equivalents.\n","extname":"\nextname( filename:string )\n Returns a filename extension.\n","FancyArray":"\nFancyArray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string[, options:Object] )\n Returns a FancyArray instance.\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","FancyArray.prototype.data":"\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n Underlying data type.\n","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","FancyArray.prototype.length":"\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n Number of dimensions.\n","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","FancyArray.prototype.order":"\nFancyArray.prototype.order\n Array order.\n","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n Array shape.\n","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n","fastmath.abs":"\nfastmath.abs( x:number )\n Computes an absolute value.\n","fastmath.acosh":"\nfastmath.acosh( x:number )\n Computes the hyperbolic arccosine of a number.\n","fastmath.ampbm":"\nfastmath.ampbm( x:number, y:number )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha:number, beta:number, [nonnegative:boolean[, \n ints:boolean]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n","fastmath.asinh":"\nfastmath.asinh( x:number )\n Computes the hyperbolic arcsine of a number.\n","fastmath.atanh":"\nfastmath.atanh( x:number )\n Computes the hyperbolic arctangent of a number.\n","fastmath.hypot":"\nfastmath.hypot( x:number, y:number )\n Computes the hypotenuse.\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x:uinteger )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n","fastmath.max":"\nfastmath.max( x:number, y:number )\n Returns the maximum value.\n","fastmath.min":"\nfastmath.min( x:number, y:number )\n Returns the minimum value.\n","fastmath.powint":"\nfastmath.powint( x:number, y:integer )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x:uinteger )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n","filledarray":"\nfilledarray( [dtype:string] )\n Creates a filled array.\n\nfilledarray( value:any, length:integer[, dtype:string] )\n Returns a filled array having a specified length.\n\nfilledarray( value:any, array:ArrayLikeObject[, dtype:string] )\n Creates a filled array from another array (or array-like object).\n\nfilledarray( value:any, iterable:Iterable[, dtype:string] )\n Creates a filled array from an iterable.\n\nfilledarray( value:any, buffer:ArrayBuffer[, byteOffset:integer[, \n length:integer]][, dtype:string] )\n Returns a filled typed array view of an ArrayBuffer.\n","filledarrayBy":"\nfilledarrayBy( [dtype:string] )\n Creates a filled array.\n\nfilledarrayBy( length:integer[, dtype:string], clbk:Function[, thisArg:any] )\n Returns a filled array according to a provided callback function and having\n a specified length.\n\nfilledarrayBy( array:ArrayLikeObject[, dtype:string], clbk:Function[, \n thisArg:any] )\n Creates a filled array from another array (or array-like object) according\n to a provided callback function.\n\nfilledarrayBy( iterable:Iterable[, dtype:string], clbk:Function[, thisArg:any] )\n Creates a filled array from an iterable according to a provided callback\n function.\n\nfilledarrayBy( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string], clbk:Function[, thisArg:any] )\n Returns a filled typed array view of an ArrayBuffer according to a provided\n callback function.\n","filterArguments":"\nfilterArguments( fcn:Function, predicate:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n","find":"\nfind( arr:Array|TypedArray|string, [options:Object,] clbk:Function )\n Finds elements in an array-like object that satisfy a test condition.\n","firstChar":"\nfirstChar( str:string[, n:integer][, options:Object] )\n Returns the first character(s) of a string.\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n Returns FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n","flattenArray":"\nflattenArray( arr:ArrayLikeObject[, options:Object] )\n Flattens an array.\n","flattenArray.factory":"\nflattenArray.factory( dims:ArrayLike[, options:Object] )\n Returns a function for flattening arrays having specified dimensions.\n","flattenObject":"\nflattenObject( obj:ObjectLike[, options:Object] )\n Flattens an object.\n","flattenObject.factory":"\nflattenObject.factory( [options:Object] )\n Returns a function to flatten an object.\n","flignerTest":"\nflignerTest( ...x:Array[, options:Object] )\n Computes the Fligner-Killeen test for equal variances.\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n Platform float word order.\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n Mask for excluding the sign bit of a single-precision floating-point number.\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n","FLOAT32_E":"\nFLOAT32_E\n Euler's number.\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n Mask for the exponent of a single-precision floating-point number.\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n One fourth times the mathematical constant `π`.\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n One half times the natural logarithm of 2 as a single-precision\n floating-point number.\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n One half times the mathematical constant `π`.\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n Natural logarithm of `1/2` as a single-precision floating-point number.\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n Natural logarithm of the mathematical constant `π` as a single-precision\n floating-point number.\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n Natural logarithm of `10` as a single-precision floating-point number.\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n Natural logarithm of `2` as a single-precision floating-point number.\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a single-precision floating-point\n number.\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a single-precision floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal single-precision floating-point\n number.\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in single-precision floating-point\n format.\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n Maximum safe nth factorial when stored in single-precision floating-\n point format.\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in single-precision floating-\n point format.\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in single-precision floating-point\n format.\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized single-precision\n floating-point number.\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normal single-precision floating-\n point number.\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal single-precision floating-\n point number.\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n","FLOAT32_NAN":"\nFLOAT32_NAN\n Single-precision floating-point NaN.\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n","FLOAT32_PHI":"\nFLOAT32_PHI\n Golden ratio.\n","FLOAT32_PI":"\nFLOAT32_PI\n The mathematical constant `π`.\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n Mask for the sign bit of a single-precision floating-point number.\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n Mask for the significand of a single-precision floating-point number.\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n Square root of `1/2` as a single-precision floating-point number.\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n Square root of `π` divided by `2` as a single-precision \n floating-point number.\n","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n Square root of the golden ratio as a single-precision floating-point number.\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n Square root of the mathematical constant `π` as a single-precision\n floating-point number.\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n Square root of `3` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n Square root of `2` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n Square root of the mathematical constant `π` times `2` as a single-precision\n floating-point number.\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n The mathematical constant `π` times `2`.\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\nFloat32Array( length:integer )\n Returns a typed array having a specified length.\n\nFloat32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nFloat32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nFloat32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Float32Array.from":"\nFloat32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Float32Array.of":"\nFloat32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float32Array.name":"\nFloat32Array.name\n Typed array constructor name.\n","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n High word mask for excluding the sign bit of a double-precision floating-\n point number.\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n High word mask for the sign bit of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\nFloat64Array( length:integer )\n Returns a typed array having a specified length.\n\nFloat64Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nFloat64Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nFloat64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Float64Array.from":"\nFloat64Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Float64Array.of":"\nFloat64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float64Array.name":"\nFloat64Array.name\n Typed array constructor name.\n","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","forEach":"\nforEach( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection.\n","forEachAsync":"\nforEachAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection.\n","forEachAsync.factory":"\nforEachAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection.\n","forEachChar":"\nforEachChar( str:string, [options:Object,] clbk:Function[, thisArg:any] )\n Invokes a function for each character in a string.\n","forEachRight":"\nforEachRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n","forEachRightAsync":"\nforEachRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n","forIn":"\nforIn( obj:Object, fcn:Function[, thisArg:any] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n","format":"\nformat( str:string, ...args:any )\n Insert supplied variable values into a format string.\n","forOwn":"\nforOwn( obj:Object, fcn:Function[, thisArg:any] )\n Invokes a function for each own enumerable property of an object.\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n","fromCodePoint":"\nfromCodePoint( ...pt:integer )\n Creates a string from a sequence of Unicode code points.\n","Function":"\nFunction( [...argNames:any,] body:string )\n Returns a Function object.\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg:any, args:Array )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n","Function.prototype.call":"\nFunction.prototype.call( thisArg:any, ...args:any )\n Calls a function with a given `this` value and arguments provided\n individually.\n","Function.prototype.bind":"\nFunction.prototype.bind( thisArg:any, ...args:any )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n","Function.prototype.toString":"\nFunction.prototype.toString()\n Returns a string representation of the function.\n","Function.prototype.length":"\nFunction.prototype.length\n The number of arguments expected by the function.\n","Function.prototype.name":"\nFunction.prototype.name\n The name of the function.\n","Function.prototype.prototype":"\nFunction.prototype.prototype\n The prototype of the function.\n","function2string":"\nfunction2string( fcn:Function )\n Returns a string representing the source code of a provided function.\n","functionName":"\nfunctionName( fcn:Function )\n Returns the name of a function.\n","functionSequence":"\nfunctionSequence( ...fcn:Function )\n Returns a pipeline function.\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn:Function )\n Returns a pipeline function.\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n","gdot":"\ngdot( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Computes the dot product of two vectors.\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n","getGlobal":"\ngetGlobal( [codegen:boolean] )\n Returns the global object.\n","getPrototypeOf":"\ngetPrototypeOf( value:any )\n Returns the prototype of a provided object.\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src:string[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over each grapheme cluster in a string.\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src:string[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over each grapheme\n cluster in a string.\n","group":"\ngroup( collection:Array|TypedArray|Object, [options:Object,] \n groups:Array|TypedArray|Object )\n Groups values as arrays associated with distinct keys.\n","groupBy":"\ngroupBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Groups values according to an indicator function.\n","groupByAsync":"\ngroupByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Groups values according to an indicator function.\n","groupByAsync.factory":"\ngroupByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which groups values according to an indicator function.\n","groupIn":"\ngroupIn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n Group values according to an indicator function.\n","groupOwn":"\ngroupOwn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n Group values according to an indicator function.\n","gswap":"\ngswap( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Interchanges two vectors.\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n Tests whether an environment supports native arrow functions.\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n","hasAtobSupport":"\nhasAtobSupport()\n Tests for native `atob` support.\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n Tests for native `BigInt64Array` support.\n","hasBigIntSupport":"\nhasBigIntSupport()\n Tests for native `BigInt` support.\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n Tests for native `BigUint64Array` support.\n","hasBtoaSupport":"\nhasBtoaSupport()\n Tests for native `btoa` support.\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n","hasDataViewSupport":"\nhasDataViewSupport()\n Tests for native `DataView` support.\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n Tests for `globalThis` support.\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n","hasOwnProp":"\nhasOwnProp( value:any, property:any )\n Tests if an object has a specified property.\n","hasProp":"\nhasProp( value:any, property:any )\n Tests if an object has a specified property, either own or inherited.\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `Symbol.toStringTag` support.\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str:string, pos:integer )\n Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n","headercase":"\nheadercase( str:string )\n Converts a string to HTTP header case.\n","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n","hoursInMonth":"\nhoursInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of hours in a month.\n","hoursInYear":"\nhoursInYear( [value:integer|Date] )\n Returns the number of hours in a year according to the Gregorian calendar.\n","httpServerFactory":"\nhttpServerFactory( [options:Object,] [requestListener:Function] )\n Returns a function to create an HTTP server.\n","identity":"\nidentity( x:any )\n Identity function.\n","ifelse":"\nifelse( bool:boolean, x:any, y:any )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n","ifelseAsync":"\nifelseAsync( predicate:Function, x:any, y:any, done:Function )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n","ifthen":"\nifthen( bool:boolean, x:Function, y:Function )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n","ifthenAsync":"\nifthenAsync( predicate:Function, x:Function, y:Function, done:Function )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n","imag":"\nimag( z:Complex128 )\n Returns the imaginary component of a double-precision complex floating-point\n number.\n","imagf":"\nimagf( z:Complex64 )\n Returns the imaginary component of a single-precision complex floating-point\n number.\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium oreophilum*.\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n","incrapcorr":"\nincrapcorr( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n","incrBinaryClassification":"\nincrBinaryClassification( N:integer[, options:Object] )\n Returns an accumulator function which incrementally performs binary\n classification using stochastic gradient descent (SGD).\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n","incrcovariance":"\nincrcovariance( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n","incrcovmat":"\nincrcovmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n","incrcv":"\nincrcv( [mean:number] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n","increwmean":"\nincrewmean( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n","increwstdev":"\nincrewstdev( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n","increwvariance":"\nincrewvariance( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n","incrgrubbs":"\nincrgrubbs( [options:Object] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n","incrkmeans":"\nincrkmeans( k:integer|ndarray[, ndims:integer][, options:Object] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n","incrmapcorr":"\nincrmapcorr( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n","incrmcovariance":"\nincrmcovariance( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n","incrmcv":"\nincrmcv( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n","incrmeanstdev":"\nincrmeanstdev( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n","incrmeanvar":"\nincrmeanvar( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n","incrmgmean":"\nincrmgmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n","incrmgrubbs":"\nincrmgrubbs( W:integer[, options:Object] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n","incrmhmean":"\nincrmhmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n","incrminmax":"\nincrminmax( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n","incrminmaxabs":"\nincrminmaxabs( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n","incrmmaape":"\nincrmmaape( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n","incrmmae":"\nincrmmae( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n","incrmmape":"\nincrmmape( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n","incrmmax":"\nincrmmax( W:integer )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n","incrmmaxabs":"\nincrmmaxabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n","incrmmda":"\nincrmmda( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n","incrmme":"\nincrmme( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n","incrmmean":"\nincrmmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n","incrmmeanabs":"\nincrmmeanabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n","incrmmeanabs2":"\nincrmmeanabs2( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n","incrmmeanstdev":"\nincrmmeanstdev( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n","incrmmeanvar":"\nincrmmeanvar( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n","incrmmidrange":"\nincrmmidrange( W:integer )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n","incrmmin":"\nincrmmin( W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n","incrmminabs":"\nincrmminabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n","incrmminmax":"\nincrmminmax( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n","incrmminmaxabs":"\nincrmminmaxabs( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n","incrmmpe":"\nincrmmpe( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n","incrmmse":"\nincrmmse( W:integer )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n","incrmpcorr":"\nincrmpcorr( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n","incrmpcorr2":"\nincrmpcorr2( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n","incrmpcorrdist":"\nincrmpcorrdist( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n","incrmprod":"\nincrmprod( W:integer )\n Returns an accumulator function which incrementally computes a moving\n product.\n","incrmrange":"\nincrmrange( W:integer )\n Returns an accumulator function which incrementally computes a moving range.\n","incrmrmse":"\nincrmrmse( W:integer )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n","incrmrss":"\nincrmrss( W:integer )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n","incrmstdev":"\nincrmstdev( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n","incrmsum":"\nincrmsum( W:integer )\n Returns an accumulator function which incrementally computes a moving sum.\n","incrmsumabs":"\nincrmsumabs( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n","incrmsumabs2":"\nincrmsumabs2( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n","incrmsummary":"\nincrmsummary( W:integer )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n","incrmsumprod":"\nincrmsumprod( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n","incrmvariance":"\nincrmvariance( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n","incrmvmr":"\nincrmvmr( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n","incrnancount":"\nincrnancount()\n Returns an accumulator function which incrementally updates a count,\n ignoring `NaN` values.\n","incrnansum":"\nincrnansum()\n Returns an accumulator function which incrementally computes a sum, ignoring\n `NaN` values.\n","incrnansumabs":"\nincrnansumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values, ignoring NaN values.\n","incrnansumabs2":"\nincrnansumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values, ignoring NaN values.\n","incrpcorr":"\nincrpcorr( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n","incrpcorr2":"\nincrpcorr2( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n","incrpcorrdist":"\nincrpcorrdist( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n","incrpcorrdistmat":"\nincrpcorrdistmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n","incrpcorrmat":"\nincrpcorrmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n","incrspace":"\nincrspace( start:number, stop:number[, increment:number] )\n Generates a linearly spaced numeric array using a provided increment.\n","incrstdev":"\nincrstdev( [mean:number] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n","incrvariance":"\nincrvariance( [mean:number] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n","incrvmr":"\nincrvmr( [mean:number] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n","ind2sub":"\nind2sub( shape:ArrayLike, idx:integer[, options:Object] )\n Converts a linear index to an array of subscripts.\n","ind2sub.assign":"\nind2sub.assign( shape:ArrayLike, idx:integer[, options:Object], \n out:Array|TypedArray|Object )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n","indexOf":"\nindexOf( arr:ArrayLike, searchElement:any[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","inherit":"\ninherit( ctor:Object|Function, superCtor:Object|Function )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable symbol properties.\n","inheritedKeys":"\ninheritedKeys( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable property names.\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable property names.\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n","inheritedProperties":"\ninheritedProperties( value:any[, level:integer] )\n Returns an array of an object's inherited property names and symbols.\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value:any, property:string|symbol[, \n level:integer] )\n Returns a property descriptor for an object's inherited property.\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value:any[, level:integer] )\n Returns an object's inherited property descriptors.\n","inheritedPropertyNames":"\ninheritedPropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited symbol properties.\n","inheritedWritableProperties":"\ninheritedWritableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited writable property names and\n symbols.\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited writable property names.\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited writable symbol properties.\n","inmap":"\ninmap( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n","inmapAsync":"\ninmapAsync( collection:Array|TypedArray|Object, [options:Object,] fcn:Function, \n done:Function )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n","inmapAsync.factory":"\ninmapAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n","inmapRight":"\ninmapRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n","inmapRightAsync":"\ninmapRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n","inspectSinkStream":"\ninspectSinkStream( [options:Object,] clbk:Function )\n Returns a writable stream for inspecting stream data.\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options:Object] )\n Returns a function for creating writable streams for inspecting stream data.\n","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options:Object,] clbk:Function )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n","inspectStream":"\ninspectStream( [options:Object,] clbk:Function )\n Returns a transform stream for inspecting stream data.\n","inspectStream.factory":"\ninspectStream.factory( [options:Object] )\n Returns a function for creating transform streams for inspecting stream\n data.\n","inspectStream.objectMode":"\ninspectStream.objectMode( [options:Object,] clbk:Function )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n","instanceOf":"\ninstanceOf( value:any, constructor:Function )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\nInt8Array( length:integer )\n Returns a typed array having a specified length.\n\nInt8Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt8Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int8Array.from":"\nInt8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int8Array.of":"\nInt8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int8Array.name":"\nInt8Array.name\n Typed array constructor name.\n","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int8Array.prototype.length":"\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n Serializes an array as a string.\n","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\nInt16Array( length:integer )\n Returns a typed array having a specified length.\n\nInt16Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt16Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int16Array.from":"\nInt16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int16Array.of":"\nInt16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int16Array.name":"\nInt16Array.name\n Typed array constructor name.\n","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int16Array.prototype.length":"\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n Serializes an array as a string.\n","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\nInt32Array( length:integer )\n Returns a typed array having a specified length.\n\nInt32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int32Array.from":"\nInt32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int32Array.of":"\nInt32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int32Array.name":"\nInt32Array.name\n Typed array constructor name.\n","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int32Array.prototype.length":"\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n Serializes an array as a string.\n","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n","IS_DOCKER":"\nIS_DOCKER\n Boolean indicating if the process is running in a Docker container.\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n","IS_MOBILE":"\nIS_MOBILE\n Boolean indicating if the current environment is a mobile device.\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n Boolean indicating if the current environment is a touch device.\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value:any )\n Tests whether a value is an absolute HTTP(S) URI.\n","isAbsolutePath":"\nisAbsolutePath( value:any )\n Tests if a value is an absolute path.\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value:any )\n Tests if a value is a POSIX absolute path.\n","isAbsolutePath.win32":"\nisAbsolutePath.win32( value:any )\n Tests if a value is a Windows absolute path.\n","isAbsoluteURI":"\nisAbsoluteURI( value:any )\n Tests whether a value is an absolute URI.\n","isAccessorArray":"\nisAccessorArray( value:any )\n Tests if a value is an array-like object supporting the accessor (get/set)\n protocol.\n","isAccessorProperty":"\nisAccessorProperty( value:any, property:any )\n Tests if an object's own property has an accessor descriptor.\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property has an accessor descriptor.\n","isAlphagram":"\nisAlphagram( value:any )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n","isAlphaNumeric":"\nisAlphaNumeric( str:string )\n Tests whether a string contains only alphanumeric characters.\n","isAnagram":"\nisAnagram( str:string, value:any )\n Tests if a value is an anagram.\n","isArguments":"\nisArguments( value:any )\n Tests if a value is an arguments object.\n","isArray":"\nisArray( value:any )\n Tests if a value is an array.\n","isArrayArray":"\nisArrayArray( value:any )\n Tests if a value is an array of arrays.\n","isArrayBuffer":"\nisArrayBuffer( value:any )\n Tests if a value is an ArrayBuffer.\n","isArrayBufferView":"\nisArrayBufferView( value:any )\n Tests if a value is a `ArrayBuffer` view.\n","isArrayLength":"\nisArrayLength( value:any )\n Tests if a value is a valid array length.\n","isArrayLike":"\nisArrayLike( value:any )\n Tests if a value is array-like.\n","isArrayLikeObject":"\nisArrayLikeObject( value:any )\n Tests if a value is an array-like object.\n","isArrowFunction":"\nisArrowFunction( value:any )\n Tests if a value is an arrow function.\n","isASCII":"\nisASCII( str:string )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n","isBetween":"\nisBetween( value:any, a:any, b:any[, left:string, right:string] )\n Tests if a value is between two values.\n","isBetweenArray":"\nisBetweenArray( value:any, a:any, b:any[, left:string, right:string] )\n Tests if a value is an array-like object where every element is between two\n values.\n","isBigInt":"\nisBigInt( value:any )\n Tests if a value is a BigInt.\n","isBigInt64Array":"\nisBigInt64Array( value:any )\n Tests if a value is a BigInt64Array.\n","isBigUint64Array":"\nisBigUint64Array( value:any )\n Tests if a value is a BigUint64Array.\n","isBinaryString":"\nisBinaryString( value:any )\n Tests if a value is a binary string.\n","isBlankString":"\nisBlankString( value:any )\n Tests if a value is a blank string (i.e., an empty string or a string\n consisting only of whitespace characters).\n","isBoolean":"\nisBoolean( value:any )\n Tests if a value is a boolean.\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value:any )\n Tests if a value is a boolean primitive.\n","isBoolean.isObject":"\nisBoolean.isObject( value:any )\n Tests if a value is a boolean object.\n","isBooleanArray":"\nisBooleanArray( value:any )\n Tests if a value is an array-like object of booleans.\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value:any )\n Tests if a value is an array-like object containing only boolean primitives.\n","isBooleanArray.objects":"\nisBooleanArray.objects( value:any )\n Tests if a value is an array-like object containing only Boolean objects.\n","isBoxedPrimitive":"\nisBoxedPrimitive( value:any )\n Tests if a value is a JavaScript boxed primitive.\n","isBuffer":"\nisBuffer( value:any )\n Tests if a value is a Buffer instance.\n","isCamelcase":"\nisCamelcase( value:any )\n Tests if a value is a camelcase string.\n","isCapitalized":"\nisCapitalized( value:any )\n Tests if a value is a string having an uppercase first character.\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value:any )\n Tests if a value is a matrix which is symmetric about its center.\n","isCircular":"\nisCircular( value:any )\n Tests if an object-like value contains a circular reference.\n","isCircularArray":"\nisCircularArray( value:any )\n Tests if a value is an array containing a circular reference.\n","isCircularPlainObject":"\nisCircularPlainObject( value:any )\n Tests if a value is a plain object containing a circular reference.\n","isClass":"\nisClass( value:any )\n Tests if a value is a class.\n","isCollection":"\nisCollection( value:any )\n Tests if a value is a collection.\n","isComplex":"\nisComplex( value:any )\n Tests if a value is a 64-bit or 128-bit complex number.\n","isComplex64":"\nisComplex64( value:any )\n Tests if a value is a 64-bit complex number.\n","isComplex64Array":"\nisComplex64Array( value:any )\n Tests if a value is a Complex64Array.\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing single-precision\n complex floating-point numbers.\n","isComplex64VectorLike":"\nisComplex64VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n","isComplex128":"\nisComplex128( value:any )\n Tests if a value is a 128-bit complex number.\n","isComplex128Array":"\nisComplex128Array( value:any )\n Tests if a value is a Complex128Array.\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing double-precision\n complex floating-point numbers.\n","isComplex128VectorLike":"\nisComplex128VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n","isComplexLike":"\nisComplexLike( value:any )\n Tests if a value is a complex number-like object.\n","isComplexTypedArray":"\nisComplexTypedArray( value:any )\n Tests if a value is a complex typed array.\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value:any )\n Tests if a value is complex-typed-array-like.\n","isComposite":"\nisComposite( value:any )\n Tests if a value is a composite number.\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value:any )\n Tests if a value is a number primitive which is a composite number.\n","isComposite.isObject":"\nisComposite.isObject( value:any )\n Tests if a value is a number object having a value which is a composite\n number.\n","isConfigurableProperty":"\nisConfigurableProperty( value:any, property:any )\n Tests if an object's own property is configurable.\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is configurable.\n","isConstantcase":"\nisConstantcase( value:any )\n Tests if a value is a constantcase string.\n","isCubeNumber":"\nisCubeNumber( value:any )\n Tests if a value is a cube number.\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a cube number.\n","isCubeNumber.isObject":"\nisCubeNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a cube number.\n","isCurrentYear":"\nisCurrentYear( value:any )\n Tests if a value is the current year.\n","isDataProperty":"\nisDataProperty( value:any, property:any )\n Tests if an object's own property has a data descriptor.\n","isDataPropertyIn":"\nisDataPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property has a data descriptor.\n","isDataView":"\nisDataView( value:any )\n Tests if a value is a DataView.\n","isDateObject":"\nisDateObject( value:any )\n Tests if a value is a Date object.\n","isDateObjectArray":"\nisDateObjectArray( value:any )\n Tests if a value is an array-like object containing only Date objects.\n","isDigitString":"\nisDigitString( str:string )\n Tests whether a string contains only numeric digits.\n","isDomainName":"\nisDomainName( value:any )\n Tests if a value is a domain name.\n","isDurationString":"\nisDurationString( value:any )\n Tests if a value is a duration string.\n","isEmailAddress":"\nisEmailAddress( value:any )\n Tests if a value is an email address.\n","isEmptyArray":"\nisEmptyArray( value:any )\n Tests if a value is an empty array.\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value:any )\n Tests if a value is an empty array-like object.\n","isEmptyCollection":"\nisEmptyCollection( value:any )\n Tests if a value is an empty collection.\n","isEmptyObject":"\nisEmptyObject( value:any )\n Tests if a value is an empty object.\n","isEmptyString":"\nisEmptyString( value:any )\n Tests if a value is an empty string.\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value:any )\n Tests if a value is an empty string primitive.\n","isEmptyString.isObject":"\nisEmptyString.isObject( value:any )\n Tests if a value is an empty `String` object.\n","isEnumerableProperty":"\nisEnumerableProperty( value:any, property:any )\n Tests if an object's own property is enumerable.\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is enumerable.\n","isEqualArray":"\nisEqualArray( v1:any, v2:any )\n Tests if two arguments are both generic arrays and have equal values.\n","isEqualDateObject":"\nisEqualDateObject( d1, d2 )\n Tests if two values are both Date objects corresponding to the same date\n and time.\n","isError":"\nisError( value:any )\n Tests if a value is an Error object.\n","isEvalError":"\nisEvalError( value:any )\n Tests if a value is an EvalError object.\n","isEven":"\nisEven( value:any )\n Tests if a value is an even number.\n","isEven.isPrimitive":"\nisEven.isPrimitive( value:any )\n Tests if a value is a number primitive that is an even number.\n","isEven.isObject":"\nisEven.isObject( value:any )\n Tests if a value is a number object that is an even number.\n","isFalsy":"\nisFalsy( value:any )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n","isFalsyArray":"\nisFalsyArray( value:any )\n Tests if a value is an array-like object containing only falsy values.\n","isFinite":"\nisFinite( value:any )\n Tests if a value is a finite number.\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a finite value.\n","isFinite.isObject":"\nisFinite.isObject( value:any )\n Tests if a value is a number object having a finite value.\n","isFiniteArray":"\nisFiniteArray( value:any )\n Tests if a value is an array-like object of finite numbers.\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n","isFiniteArray.objects":"\nisFiniteArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n","isFloat32Array":"\nisFloat32Array( value:any )\n Tests if a value is a Float32Array.\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing single-precision\n floating-point numbers.\n","isFloat32VectorLike":"\nisFloat32VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n","isFloat64Array":"\nisFloat64Array( value:any )\n Tests if a value is a Float64Array.\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing double-precision\n floating-point numbers.\n","isFloat64VectorLike":"\nisFloat64VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n","isFunction":"\nisFunction( value:any )\n Tests if a value is a function.\n","isFunctionArray":"\nisFunctionArray( value:any )\n Tests if a value is an array-like object containing only functions.\n","isGeneratorObject":"\nisGeneratorObject( value:any )\n Tests if a value is a generator object.\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value:any )\n Tests if a value is generator object-like.\n","isgzipBuffer":"\nisgzipBuffer( value:any )\n Tests if a value is a gzip buffer.\n","isHexString":"\nisHexString( str:string )\n Tests whether a string contains only hexadecimal digits.\n","isInfinite":"\nisInfinite( value:any )\n Tests if a value is an infinite number.\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value:any )\n Tests if a value is a number primitive having an infinite value.\n","isInfinite.isObject":"\nisInfinite.isObject( value:any )\n Tests if a value is a number object having an infinite value.\n","isInheritedProperty":"\nisInheritedProperty( value:any, property:any )\n Tests if an object has an inherited property.\n","isInt8Array":"\nisInt8Array( value:any )\n Tests if a value is an Int8Array.\n","isInt16Array":"\nisInt16Array( value:any )\n Tests if a value is an Int16Array.\n","isInt32Array":"\nisInt32Array( value:any )\n Tests if a value is an Int32Array.\n","isInteger":"\nisInteger( value:any )\n Tests if a value is an integer.\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having an integer value.\n","isInteger.isObject":"\nisInteger.isObject( value:any )\n Tests if a value is a number object having an integer value.\n","isIntegerArray":"\nisIntegerArray( value:any )\n Tests if a value is an array-like object of integer values.\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive integer\n values.\n","isIntegerArray.objects":"\nisIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n","isIterableLike":"\nisIterableLike( value:any )\n Tests if a value is iterable-like.\n","isIteratorLike":"\nisIteratorLike( value:any )\n Tests if a value is iterator-like.\n","isJSON":"\nisJSON( value:any )\n Tests if a value is a parseable JSON string.\n","isKebabcase":"\nisKebabcase( value:any )\n Tests if a value is a string in kebab case.\n","isLeapYear":"\nisLeapYear( value:any )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n","isLocalhost":"\nisLocalhost( value:any )\n Tests whether a value is a localhost hostname.\n","isLowercase":"\nisLowercase( value:any )\n Tests if a value is a lowercase string.\n","isMatrixLike":"\nisMatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object.\n","isMethod":"\nisMethod( value:any, property:any )\n Tests if an object has a specified method name.\n","isMethodIn":"\nisMethodIn( value:any, property:any )\n Tests if an object has a specified method name, either own or inherited.\n","isMultiSlice":"\nisMultiSlice( value:any )\n Tests if a value is a MultiSlice object.\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value:any )\n Tests if a value is named typed tuple-like.\n","isnan":"\nisnan( value:any )\n Tests if a value is NaN.\n","isnan.isPrimitive":"\nisnan.isPrimitive( value:any )\n Tests if a value is a NaN number primitive.\n","isnan.isObject":"\nisnan.isObject( value:any )\n Tests if a value is a number object having a value of NaN.\n","isNaNArray":"\nisNaNArray( value:any )\n Tests if a value is an array-like object containing only NaN values.\n","isNaNArray.primitives":"\nisNaNArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n","isNaNArray.objects":"\nisNaNArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n","isNativeFunction":"\nisNativeFunction( value:any )\n Tests if a value is a native function.\n","isndarrayLike":"\nisndarrayLike( value:any )\n Tests if a value is ndarray-like.\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value:any, dtype:any )\n Tests if a value is an ndarray-like object having a specified data type.\n","isNegativeFinite":"\nisNegativeFinite( value:any )\n Tests if a value is a finite negative number.\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a finite negative value.\n","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value:any )\n Tests if a value is a number object having a finite negative value.\n","isNegativeInteger":"\nisNegativeInteger( value:any )\n Tests if a value is a negative integer.\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a negative integer value.\n","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value:any )\n Tests if a value is a number object having a negative integer value.\n","isNegativeIntegerArray":"\nisNegativeIntegerArray( value:any )\n Tests if a value is an array-like object containing only negative integers.\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n","isNegativeNumber":"\nisNegativeNumber( value:any )\n Tests if a value is a negative number.\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a negative value.\n","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value:any )\n Tests if a value is a number object having a negative value.\n","isNegativeNumberArray":"\nisNegativeNumberArray( value:any )\n Tests if a value is an array-like object containing only negative numbers.\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n","isNegativeZero":"\nisNegativeZero( value:any )\n Tests if a value is negative zero.\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value:any )\n Tests if a value is a number primitive equal to negative zero.\n","isNegativeZero.isObject":"\nisNegativeZero.isObject( value:any )\n Tests if a value is a number object having a value equal to negative zero.\n","isNodeBuiltin":"\nisNodeBuiltin( str:string )\n Tests whether a string matches a Node.js built-in module name.\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value:any )\n Tests if a value is Node duplex stream-like.\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value:any )\n Tests if a value is Node readable stream-like.\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n","isNodeStreamLike":"\nisNodeStreamLike( value:any )\n Tests if a value is Node stream-like.\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value:any )\n Tests if a value is Node transform stream-like.\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value:any )\n Tests if a value is Node writable stream-like.\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value:any, property:any )\n Tests if an object's own property is non-configurable.\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is non-configurable.\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value:any, property:any )\n Tests if an object's own property is non-enumerable.\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is non-enumerable.\n","isNonNegativeFinite":"\nisNonNegativeFinite( value:any )\n Tests if a value is a nonnegative finite number.\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative finite value.\n","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value:any )\n Tests if a value is a number object having a nonnegative finite value.\n","isNonNegativeInteger":"\nisNonNegativeInteger( value:any )\n Tests if a value is a nonnegative integer.\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative integer value.\n","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value:any )\n Tests if a value is a number object having a nonnegative integer value.\n","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value:any )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n","isNonNegativeNumber":"\nisNonNegativeNumber( value:any )\n Tests if a value is a nonnegative number.\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative value.\n","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value:any )\n Tests if a value is a number object having a nonnegative value.\n","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value:any )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n","isNonPositiveFinite":"\nisNonPositiveFinite( value:any )\n Tests if a value is a nonpositive finite number.\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive finite value.\n","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value:any )\n Tests if a value is a number object having a nonpositive finite value.\n","isNonPositiveInteger":"\nisNonPositiveInteger( value:any )\n Tests if a value is a nonpositive integer.\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive integer value.\n","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value:any )\n Tests if a value is a number object having a nonpositive integer value.\n","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value:any )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n","isNonPositiveNumber":"\nisNonPositiveNumber( value:any )\n Tests if a value is a nonpositive number.\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive value.\n","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value:any )\n Tests if a value is a number object having a nonpositive value.\n","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value:any )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value:any )\n Tests if a value is a non-symmetric matrix.\n","isNull":"\nisNull( value:any )\n Tests if a value is null.\n","isNullArray":"\nisNullArray( value:any )\n Tests if a value is an array-like object containing only null values.\n","isNumber":"\nisNumber( value:any )\n Tests if a value is a number.\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value:any )\n Tests if a value is a number primitive.\n","isNumber.isObject":"\nisNumber.isObject( value:any )\n Tests if a value is a `Number` object.\n","isNumberArray":"\nisNumberArray( value:any )\n Tests if a value is an array-like object containing only numbers.\n","isNumberArray.primitives":"\nisNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only number primitives.\n","isNumberArray.objects":"\nisNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only `Number` objects.\n","isNumericArray":"\nisNumericArray( value:any )\n Tests if a value is a numeric array.\n","isObject":"\nisObject( value:any )\n Tests if a value is an object; e.g., `{}`.\n","isObjectArray":"\nisObjectArray( value:any )\n Tests if a value is an array-like object containing only objects.\n","isObjectLike":"\nisObjectLike( value:any )\n Tests if a value is object-like.\n","isOdd":"\nisOdd( value:any )\n Tests if a value is an odd number.\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value:any )\n Tests if a value is a number primitive that is an odd number.\n","isOdd.isObject":"\nisOdd.isObject( value:any )\n Tests if a value is a number object that has an odd number value.\n","isoWeeksInYear":"\nisoWeeksInYear( [year:integer] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n","isPascalcase":"\nisPascalcase( value:any )\n Tests if a value is a string in Pascal case.\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value:any )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n","isPlainObject":"\nisPlainObject( value:any )\n Tests if a value is a plain object.\n","isPlainObjectArray":"\nisPlainObjectArray( value:any )\n Tests if a value is an array-like object containing only plain objects.\n","isPositiveFinite":"\nisPositiveFinite( value:any )\n Tests if a value is a positive finite number.\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive finite value.\n","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value:any )\n Tests if a value is a number object having a positive finite value.\n","isPositiveInteger":"\nisPositiveInteger( value:any )\n Tests if a value is a positive integer.\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive integer value.\n","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value:any )\n Tests if a value is a number object having a positive integer value.\n","isPositiveIntegerArray":"\nisPositiveIntegerArray( value:any )\n Tests if a value is an array-like object containing only positive integers.\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n","isPositiveNumber":"\nisPositiveNumber( value:any )\n Tests if a value is a positive number.\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive value.\n","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value:any )\n Tests if a value is a number object having a positive value.\n","isPositiveNumberArray":"\nisPositiveNumberArray( value:any )\n Tests if a value is an array-like object containing only positive numbers.\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n","isPositiveZero":"\nisPositiveZero( value:any )\n Tests if a value is positive zero.\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value:any )\n Tests if a value is a number primitive equal to positive zero.\n","isPositiveZero.isObject":"\nisPositiveZero.isObject( value:any )\n Tests if a value is a number object having a value equal to positive zero.\n","isPrime":"\nisPrime( value:any )\n Tests if a value is a prime number.\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value:any )\n Tests if a value is a number primitive which is a prime number.\n","isPrime.isObject":"\nisPrime.isObject( value:any )\n Tests if a value is a number object having a value which is a prime number.\n","isPrimitive":"\nisPrimitive( value:any )\n Tests if a value is a JavaScript primitive.\n","isPrimitiveArray":"\nisPrimitiveArray( value:any )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n","isPRNGLike":"\nisPRNGLike( value:any )\n Tests if a value is PRNG-like.\n","isProbability":"\nisProbability( value:any )\n Tests if a value is a probability.\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value:any )\n Tests if a value is a number primitive which is a probability.\n","isProbability.isObject":"\nisProbability.isObject( value:any )\n Tests if a value is a number object having a value which is a probability.\n","isProbabilityArray":"\nisProbabilityArray( value:any )\n Tests if a value is an array-like object containing only probabilities.\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n","isProbabilityArray.objects":"\nisProbabilityArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n","isPropertyKey":"\nisPropertyKey( value:any )\n Tests whether a value is a property key.\n","isPrototypeOf":"\nisPrototypeOf( value:any, proto:Object|Function )\n Tests if an object's prototype chain contains a provided prototype.\n","isRaggedNestedArray":"\nisRaggedNestedArray( value:any )\n Tests if a value is a ragged nested array. \n","isRangeError":"\nisRangeError( value:any )\n Tests if a value is a RangeError object.\n","isReadableProperty":"\nisReadableProperty( value:any, property:any )\n Tests if an object's own property is readable.\n","isReadablePropertyIn":"\nisReadablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is readable.\n","isReadOnlyProperty":"\nisReadOnlyProperty( value:any, property:any )\n Tests if an object's own property is read-only.\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is read-only.\n","isReadWriteProperty":"\nisReadWriteProperty( value:any, property:any )\n Tests if an object's own property is readable and writable.\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is readable and writable.\n","isReferenceError":"\nisReferenceError( value:any )\n Tests if a value is a ReferenceError object.\n","isRegExp":"\nisRegExp( value:any )\n Tests if a value is a regular expression.\n","isRegExpString":"\nisRegExpString( value:any )\n Tests if a value is a regular expression string.\n","isRelativePath":"\nisRelativePath( value:any )\n Tests if a value is a relative path.\n","isRelativePath.posix":"\nisRelativePath.posix( value:any )\n Tests if a value is a POSIX relative path.\n","isRelativePath.win32":"\nisRelativePath.win32( value:any )\n Tests if a value is a Windows relative path.\n","isRelativeURI":"\nisRelativeURI( value:any )\n Tests whether a value is a relative URI.\n","isSafeInteger":"\nisSafeInteger( value:any )\n Tests if a value is a safe integer.\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a safe integer value.\n","isSafeInteger.isObject":"\nisSafeInteger.isObject( value:any )\n Tests if a value is a `Number` object having a safe integer value.\n","isSafeIntegerArray":"\nisSafeIntegerArray( value:any )\n Tests if a value is an array-like object containing only safe integers.\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n","isSameArray":"\nisSameArray( v1:any, v2:any )\n Tests if two arguments are both generic arrays and have the same values.\n","isSameArrayLike":"\nisSameArrayLike( v1:any, v2:any )\n Tests if two arguments are both array-like and have the same values.\n","isSameComplex64":"\nisSameComplex64( v1:any, v2:any )\n Tests if two arguments are both single-precision complex floating-point\n numbers and have the same value.\n","isSameComplex64Array":"\nisSameComplex64Array( v1:any, v2:any )\n Tests if two arguments are both Complex64Arrays and have the same values.\n","isSameComplex128":"\nisSameComplex128( v1:any, v2:any )\n Tests if two arguments are both double-precision complex floating-point\n numbers and have the same value.\n","isSameComplex128Array":"\nisSameComplex128Array( v1:any, v2:any )\n Tests if two arguments are both Complex128Arrays and have the same values.\n","isSameFloat32Array":"\nisSameFloat32Array( v1:any, v2:any )\n Tests if two arguments are both Float32Arrays and have the same values.\n","isSameFloat64Array":"\nisSameFloat64Array( v1:any, v2:any )\n Tests if two arguments are both Float64Arrays and have the same values.\n","isSameNativeClass":"\nisSameNativeClass( a:any, b:any )\n Tests if two arguments have the same native class.\n","isSameType":"\nisSameType( a:any, b:any )\n Tests if two arguments have the same type.\n","isSameValue":"\nisSameValue( a:any, b:any )\n Tests if two arguments are the same value.\n","isSameValueZero":"\nisSameValueZero( a:any, b:any )\n Tests if two arguments are the same value.\n","isSemVer":"\nisSemVer( value:any )\n Tests if a value is a semantic version string.\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value:any )\n Tests if a value is a SharedArrayBuffer.\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value:any )\n Tests if a value is a skew-centrosymmetric matrix.\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value:any )\n Tests if a value is a skew-persymmetric matrix.\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value:any )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n","isSlice":"\nisSlice( value:any )\n Tests if a value is a Slice object.\n","isSnakecase":"\nisSnakecase( value:any )\n Tests if a value is a string in snake case.\n","isSquareMatrix":"\nisSquareMatrix( value:any )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n","isSquareNumber":"\nisSquareNumber( value:any )\n Tests if a value is a square number.\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a square number.\n","isSquareNumber.isObject":"\nisSquareNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a square number.\n","isSquareTriangularNumber":"\nisSquareTriangularNumber( value:any )\n Tests if a value is a square triangular number.\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a square triangular number.\n","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a square\n triangular number.\n","isStartcase":"\nisStartcase( value:any )\n Tests if a value is a startcase string.\n","isStrictEqual":"\nisStrictEqual( a:any, b:any )\n Tests if two arguments are strictly equal.\n","isString":"\nisString( value:any )\n Tests if a value is a string.\n","isString.isPrimitive":"\nisString.isPrimitive( value:any )\n Tests if a value is a string primitive.\n","isString.isObject":"\nisString.isObject( value:any )\n Tests if a value is a `String` object.\n","isStringArray":"\nisStringArray( value:any )\n Tests if a value is an array of strings.\n","isStringArray.primitives":"\nisStringArray.primitives( value:any )\n Tests if a value is an array containing only string primitives.\n","isStringArray.objects":"\nisStringArray.objects( value:any )\n Tests if a value is an array containing only `String` objects.\n","isStruct":"\nisStruct( value:any )\n Tests if a value is a `struct` instance.\n","isStructConstructorLike":"\nisStructConstructorLike( value:any )\n Tests if a value is struct constructor-like.\n","isSymbol":"\nisSymbol( value:any )\n Tests if a value is a symbol.\n","isSymbolArray":"\nisSymbolArray( value:any )\n Tests if a value is an array-like object containing only symbols.\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value:any )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n","isSymbolArray.objects":"\nisSymbolArray.objects( value:any )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n","isSymmetricMatrix":"\nisSymmetricMatrix( value:any )\n Tests if a value is a square matrix which equals its transpose.\n","isSyntaxError":"\nisSyntaxError( value:any )\n Tests if a value is a SyntaxError object.\n","isTriangularNumber":"\nisTriangularNumber( value:any )\n Tests if a value is a triangular number.\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a triangular number.\n","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a triangular\n number.\n","isTruthy":"\nisTruthy( value:any )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n","isTruthyArray":"\nisTruthyArray( value:any )\n Tests if a value is an array-like object containing only truthy values.\n","isTypedArray":"\nisTypedArray( value:any )\n Tests if a value is a typed array.\n","isTypedArrayLength":"\nisTypedArrayLength( value:any )\n Tests if a value is a valid typed array length.\n","isTypedArrayLike":"\nisTypedArrayLike( value:any )\n Tests if a value is typed-array-like.\n","isTypeError":"\nisTypeError( value:any )\n Tests if a value is a TypeError object.\n","isUint8Array":"\nisUint8Array( value:any )\n Tests if a value is a Uint8Array.\n","isUint8ClampedArray":"\nisUint8ClampedArray( value:any )\n Tests if a value is a Uint8ClampedArray.\n","isUint16Array":"\nisUint16Array( value:any )\n Tests if a value is a Uint16Array.\n","isUint32Array":"\nisUint32Array( value:any )\n Tests if a value is a Uint32Array.\n","isUNCPath":"\nisUNCPath( value:any )\n Tests if a value is a UNC path.\n","isUndefined":"\nisUndefined( value:any )\n Tests if a value is undefined.\n","isUndefinedOrNull":"\nisUndefinedOrNull( value:any )\n Tests if a value is undefined or null.\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value:any )\n Tests if a value is an array of probabilities that sum to one.\n","isUppercase":"\nisUppercase( value:any )\n Tests if a value is an uppercase string.\n","isURI":"\nisURI( value:any )\n Tests if a value is a URI.\n","isURIError":"\nisURIError( value:any )\n Tests if a value is a URIError object.\n","isVectorLike":"\nisVectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object.\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value:any )\n Tests if a value is a WebAssembly memory instance.\n","isWellFormedString":"\nisWellFormedString( str:any )\n Tests if a string is well-formed.\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str:any )\n Tests if a string is a well-formed string primitive.\n","isWellFormedString.isObject":"\nisWellFormedString.isObject( str:any )\n Tests if a string is a well-formed string object.\n","isWhitespace":"\nisWhitespace( str:string )\n Tests whether a string contains only white space characters.\n","isWritableProperty":"\nisWritableProperty( value:any, property:any )\n Tests if an object's own property is writable.\n","isWritablePropertyIn":"\nisWritablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is writable.\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value:any, property:any )\n Tests if an object's own property is write-only.\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is write-only.\n","iterAbs":"\niterAbs( iterator:Object )\n Returns an iterator which iteratively computes the absolute value.\n","iterAbs2":"\niterAbs2( iterator:Object )\n Returns an iterator which iteratively computes the squared absolute value.\n","iterAcos":"\niterAcos( iterator:Object )\n Returns an iterator which iteratively computes the arccosine.\n","iterAcosh":"\niterAcosh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arccosine.\n","iterAcot":"\niterAcot( iterator:Object )\n Returns an iterator which iteratively computes the inverse cotangent.\n","iterAcoth":"\niterAcoth( iterator:Object )\n Returns an iterator which iteratively computes the inverse hyperbolic\n cotangent.\n","iterAcovercos":"\niterAcovercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse coversed cosine.\n","iterAcoversin":"\niterAcoversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse coversed sine.\n","iterAdd":"\niterAdd( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n","iterAdvance":"\niterAdvance( iterator:Object[, n:integer] )\n Advances an entire iterator.\n","iterAhavercos":"\niterAhavercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse half-value versed\n cosine.\n","iterAhaversin":"\niterAhaversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse half-value versed\n sine.\n","iterAny":"\niterAny( iterator:Object )\n Tests whether at least one iterated value is truthy.\n","iterAnyBy":"\niterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n","iterAsin":"\niterAsin( iterator:Object )\n Returns an iterator which iteratively computes the arcsine.\n","iterAsinh":"\niterAsinh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arcsine.\n","iterAtan":"\niterAtan( iterator:Object )\n Returns an iterator which iteratively computes the arctangent.\n","iterAtan2":"\niterAtan2( y:Object|number, x:Object|number )\n Returns an iterator which iteratively computes the angle in the plane (in\n radians) between the positive x-axis and the ray from (0,0) to the point\n (x,y).\n","iterAtanh":"\niterAtanh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arctangent.\n","iterator2array":"\niterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, \n thisArg:any]] )\n Creates (or fills) an array from an iterator.\n","iterator2arrayview":"\niterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, \n end:integer]][, mapFcn:Function[, thisArg:any]] )\n Fills an array-like object view with values returned from an iterator.\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, \n begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n","iteratorStream":"\niteratorStream( iterator:Object[, options:Object] )\n Creates a readable stream from an iterator.\n","iteratorStream.factory":"\niteratorStream.factory( [options:Object] )\n Returns a function for creating readable streams from iterators.\n","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator:Object[, options:Object] )\n Returns an \"objectMode\" readable stream from an iterator.\n","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n","iterAvercos":"\niterAvercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse versed cosine.\n","iterAversin":"\niterAversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse versed sine.\n","iterawgn":"\niterawgn( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n","iterawln":"\niterawln( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n","iterawun":"\niterawun( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options:Object] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n","iterBartlettPulse":"\niterBartlettPulse( [options:Object] )\n Returns an iterator which generates a Bartlett pulse waveform.\n","iterBesselj0":"\niterBesselj0( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order zero.\n","iterBesselj1":"\niterBesselj1( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order one.\n","iterBessely0":"\niterBessely0( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order zero.\n","iterBessely1":"\niterBessely1( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order one.\n","iterBeta":"\niterBeta( x:Object|number, y:Object|number )\n Returns an iterator which iteratively evaluates the beta function.\n","iterBetaln":"\niterBetaln( x:Object|number, y:Object|number )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n beta function.\n","iterBinet":"\niterBinet( iterator:Object )\n Returns an iterator which iteratively evaluates Binet's formula extended to\n real numbers.\n","iterCbrt":"\niterCbrt( iterator:Object )\n Returns an iterator which iteratively computes the cube root.\n","iterCeil":"\niterCeil( iterator:Object )\n Returns an iterator which rounds each iterated value toward positive\n infinity.\n","iterCeil2":"\niterCeil2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward positive infinity.\n","iterCeil10":"\niterCeil10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward positive infinity.\n","iterCompositesSeq":"\niterCompositesSeq( [options:Object] )\n Returns an iterator which generates a sequence of composite numbers.\n","iterConcat":"\niterConcat( iter0:Object, ...iterator:Object )\n Returns an iterator which iterates over the values of two or more iterators.\n","iterConstant":"\niterConstant( value:any[, options:Object] )\n Returns an iterator which always returns the same value.\n","iterContinuedFraction":"\niterContinuedFraction( iterator:Object[, options:Object] )\n Evaluates the terms of a continued fraction.\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x:number[, options:Object] )\n Returns an iterator which generates a list of all continued fraction terms\n which can be obtained given the precision of `x`.\n","iterCos":"\niterCos( iterator:Object )\n Returns an iterator which iteratively computes the cosine.\n","iterCosh":"\niterCosh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic cosine.\n","iterCosineWave":"\niterCosineWave( [options:Object] )\n Returns an iterator which generates a cosine wave.\n","iterCosm1":"\niterCosm1( iterator:Object )\n Returns an iterator which iteratively computes `cos(x) - 1`.\n","iterCospi":"\niterCospi( iterator:Object )\n Returns an iterator which computes the cosine of each iterated value times\n π.\n","iterCounter":"\niterCounter( iterator:Object )\n Returns an iterator which iteratively computes the number of iterated\n values.\n","iterCovercos":"\niterCovercos( iterator:Object )\n Returns an iterator which iteratively computes the coversed cosine.\n","iterCoversin":"\niterCoversin( iterator:Object )\n Returns an iterator which iteratively computes the coversed sine.\n","iterCubesSeq":"\niterCubesSeq( [options:Object] )\n Returns an iterator which generates a sequence of cubes.\n","itercugmean":"\nitercugmean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n","itercuhmean":"\nitercuhmean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n","itercumax":"\nitercumax( iterator:Object )\n Returns an iterator which iteratively computes a cumulative maximum value.\n","itercumaxabs":"\nitercumaxabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n","itercumean":"\nitercumean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n","itercumeanabs":"\nitercumeanabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n","itercumeanabs2":"\nitercumeanabs2( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n","itercumidrange":"\nitercumidrange( iterator:Object )\n Returns an iterator which iteratively computes a cumulative mid-range.\n","itercumin":"\nitercumin( iterator:Object )\n Returns an iterator which iteratively computes a cumulative minimum value.\n","itercuminabs":"\nitercuminabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n","itercuprod":"\nitercuprod( iterator:Object )\n Returns an iterator which iteratively computes a cumulative product.\n","itercurange":"\nitercurange( iterator:Object )\n Returns an iterator which iteratively computes a cumulative range.\n","itercusum":"\nitercusum( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum.\n","itercusumabs":"\nitercusumabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n","itercusumabs2":"\nitercusumabs2( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n","iterDatespace":"\niterDatespace( start:integer|string|Date, stop:integer|string|Date[, \n N:integer][, options:Object] )\n Returns an iterator which returns evenly spaced dates over a specified\n interval.\n","iterDedupe":"\niterDedupe( iterator:Object[, limit:integer] )\n Returns an iterator which removes consecutive duplicated values.\n","iterDedupeBy":"\niterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n","iterDeg2rad":"\niterDeg2rad( iterator:Object )\n Returns an iterator which iteratively converts an angle from degrees to\n radians.\n","iterDigamma":"\niterDigamma( iterator:Object )\n Returns an iterator which iteratively evaluates the digamma function.\n","iterDiracComb":"\niterDiracComb( [options:Object] )\n Returns an iterator which generates a Dirac comb.\n","iterDiracDelta":"\niterDiracDelta( iterator:Object )\n Returns an iterator which iteratively evaluates the Dirac delta function.\n","iterDivide":"\niterDivide( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n","iterDoUntilEach":"\niterDoUntilEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n","iterDoWhileEach":"\niterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n","iterEllipe":"\niterEllipe( iterator:Object )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the second kind.\n","iterEllipk":"\niterEllipk( iterator:Object )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the first kind.\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n","iterErf":"\niterErf( iterator:Object )\n Returns an iterator which iteratively evaluates the error function.\n","iterErfc":"\niterErfc( iterator:Object )\n Returns an iterator which iteratively evaluates the complementary error\n function.\n","iterErfcinv":"\niterErfcinv( iterator:Object )\n Returns an iterator which iteratively evaluates the inverse complementary\n error function.\n","iterErfinv":"\niterErfinv( iterator:Object )\n Returns an iterator which iteratively evaluates the inverse error function.\n","iterEta":"\niterEta( iterator:Object )\n Returns an iterator which iteratively evaluates the Dirichlet eta function.\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved sequence of even\n integers.\n","iterEvery":"\niterEvery( iterator:Object )\n Tests whether all iterated values are truthy.\n","iterEveryBy":"\niterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n","iterExp":"\niterExp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural exponential\n function.\n","iterExp2":"\niterExp2( iterator:Object )\n Returns an iterator which iteratively evaluates the base `2` exponential\n function.\n","iterExp10":"\niterExp10( iterator:Object )\n Returns an iterator which iteratively evaluates the base `10` exponential\n function.\n","iterExpit":"\niterExpit( iterator:Object )\n Returns an iterator which iteratively evaluates the standard logistic\n function.\n","iterExpm1":"\niterExpm1( iterator:Object )\n Returns an iterator which iteratively computes `exp(x) - 1`.\n","iterExpm1rel":"\niterExpm1rel( iterator:Object )\n Returns an iterator which iteratively evaluates the relative error\n exponential.\n","iterFactorial":"\niterFactorial( iterator:Object )\n Returns an iterator which iteratively evaluates the factorial function.\n","iterFactorialln":"\niterFactorialln( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n factorial function.\n","iterFactorialsSeq":"\niterFactorialsSeq( [options:Object] )\n Returns an iterator which generates a sequence of factorials.\n","iterFibonacciSeq":"\niterFibonacciSeq( [options:Object] )\n Returns an iterator which generates a Fibonacci sequence.\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options:Object] )\n Returns an iterator which generates a sequence of fifth powers.\n","iterFill":"\niterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n","iterFilter":"\niterFilter( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n","iterFilterMap":"\niterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n","iterFirst":"\niterFirst( iterator:Object )\n Returns the first iterated value.\n","iterFlatTopPulse":"\niterFlatTopPulse( [options:Object] )\n Returns an iterator which generates a flat top pulse waveform.\n","iterFloor":"\niterFloor( iterator:Object )\n Returns an iterator which rounds each iterated value toward negative\n infinity.\n","iterFloor2":"\niterFloor2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward negative infinity.\n","iterFloor10":"\niterFloor10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward negative infinity.\n","iterFlow":"\niterFlow( methods:Object )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n","iterForEach":"\niterForEach( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options:Object] )\n Returns an iterator which generates a sequence of fourth powers.\n","iterFresnelc":"\niterFresnelc( iterator:Object )\n Returns an iterator which iteratively computes the Fresnel integral C(x).\n","iterFresnels":"\niterFresnels( iterator:Object )\n Returns an iterator which iteratively computes the Fresnel integral S(x).\n","iterGamma":"\niterGamma( iterator:Object )\n Returns an iterator which iteratively evaluates the gamma function.\n","iterGamma1pm1":"\niterGamma1pm1( iterator:Object )\n Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n cancellation errors for small `x`.\n","iterGammaln":"\niterGammaln( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n gamma function.\n","iterHacovercos":"\niterHacovercos( iterator:Object )\n Returns an iterator which iteratively computes the half-value coversed\n cosine.\n","iterHacoversin":"\niterHacoversin( iterator:Object )\n Returns an iterator which iteratively computes the half-value coversed sine.\n","iterHannPulse":"\niterHannPulse( [options:Object] )\n Returns an iterator which generates a Hann pulse waveform.\n","iterHavercos":"\niterHavercos( iterator:Object )\n Returns an iterator which iteratively computes the half-value versed cosine.\n","iterHaversin":"\niterHaversin( iterator:Object )\n Returns an iterator which iteratively computes the half-value versed sine.\n","iterHead":"\niterHead( iterator:Object, n:integer )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n","iterIncrspace":"\niterIncrspace( start:number, stop:number[, increment:number] )\n Returns an iterator which returns evenly spaced numbers according to a\n specified increment.\n","iterIntegersSeq":"\niterIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved integer sequence.\n","iterIntersection":"\niterIntersection( iter0:Object, ...iterator:Object )\n Returns an iterator which returns the intersection of two or more iterators.\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, \n thisArg:any] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n","iterInv":"\niterInv( iterator:Object )\n Returns an iterator which iteratively computes the multiplicative inverse.\n","iterLanczosPulse":"\niterLanczosPulse( [options:Object] )\n Returns an iterator which generates a Lanczos pulse waveform.\n","iterLast":"\niterLast( iterator:Object )\n Consumes an entire iterator and returns the last iterated value.\n","iterLength":"\niterLength( iterator:Object )\n Consumes an entire iterator and returns the number of iterated values.\n","iterLinspace":"\niterLinspace( start:number, stop:number[, N:integer] )\n Returns an iterator which returns evenly spaced numbers over a specified\n interval.\n","iterLn":"\niterLn( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm.\n","iterLog":"\niterLog( x:Object|number, b:Object|number )\n Returns an iterator which iteratively computes the base `b` logarithm.\n","iterLog1mexp":"\niterLog1mexp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1-exp(-|x|)`.\n","iterLog1p":"\niterLog1p( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+x`.\n","iterLog1pexp":"\niterLog1pexp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+exp(x)`.\n","iterLog2":"\niterLog2( iterator:Object )\n Returns an iterator which iteratively evaluates the binary logarithm.\n","iterLog10":"\niterLog10( iterator:Object )\n Returns an iterator which iteratively evaluates the common logarithm\n (logarithm with base 10).\n","iterLogit":"\niterLogit( iterator:Object )\n Returns an iterator which iteratively evaluates the logit function.\n","iterLogspace":"\niterLogspace( start:number, stop:number[, N:integer][, options:Object] )\n Returns an iterator which returns evenly spaced numbers on a log scale.\n","iterLucasSeq":"\niterLucasSeq( [options:Object] )\n Returns an iterator which generates a Lucas sequence.\n","iterMap":"\niterMap( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which invokes a function for each iterated value.\n","iterMapN":"\niterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n","itermax":"\nitermax( iterator:Object )\n Computes the maximum value of all iterated values.\n","itermaxabs":"\nitermaxabs( iterator:Object )\n Computes the maximum absolute value of all iterated values.\n","itermean":"\nitermean( iterator:Object )\n Computes an arithmetic mean over all iterated values.\n","itermeanabs":"\nitermeanabs( iterator:Object )\n Computes an arithmetic mean of absolute values for all iterated values.\n","itermeanabs2":"\nitermeanabs2( iterator:Object )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n","itermidrange":"\nitermidrange( iterator:Object )\n Computes the mid-range of all iterated values.\n","itermin":"\nitermin( iterator:Object )\n Computes the minimum value of all iterated values.\n","iterminabs":"\niterminabs( iterator:Object )\n Computes the minimum absolute value of all iterated values.\n","itermmax":"\nitermmax( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving maximum value.\n","itermmaxabs":"\nitermmaxabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n","itermmean":"\nitermmean( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n","itermmeanabs":"\nitermmeanabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n","itermmeanabs2":"\nitermmeanabs2( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n","itermmidrange":"\nitermmidrange( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving mid-range.\n","itermmin":"\nitermmin( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving minimum value.\n","itermminabs":"\nitermminabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n","iterMod":"\niterMod( iter0:Object, ...iterator:Object )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n","itermprod":"\nitermprod( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving product.\n","itermrange":"\nitermrange( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving range.\n","itermsum":"\nitermsum( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum.\n","itermsumabs":"\nitermsumabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n","itermsumabs2":"\nitermsumabs2( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n","iterMultiply":"\niterMultiply( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options:Object] )\n Returns an iterator which generates a negaFibonacci sequence.\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options:Object] )\n Returns an iterator which generates a negaLucas sequence.\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of negative even integers.\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options:Object] )\n Returns an iterator which generates a negative integer sequence.\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of negative odd integers.\n","iterNone":"\niterNone( iterator:Object )\n Tests whether all iterated values are falsy.\n","iterNoneBy":"\niterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options:Object] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonnegative even integers.\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options:Object] )\n Returns an iterator which generates a nonnegative integer sequence.\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonpositive even integers.\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options:Object] )\n Returns an iterator which generates a nonpositive integer sequence.\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonsquares.\n","iterNth":"\niterNth( iterator:Object, n:integer )\n Returns the nth iterated value.\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved sequence of odd integers.\n","iterPeriodicSinc":"\niterPeriodicSinc( n:integer[, options:Object] )\n Returns an iterator which generates a periodic sinc waveform.\n","iterPipeline":"\niterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )\n Returns an iterator pipeline.\n","iterPop":"\niterPop( iterator:Object[, clbk:Function[, thisArg:any]] )\n Returns an iterator which skips the last value of a provided iterator.\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of positive even integers.\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options:Object] )\n Returns an iterator which generates a positive integer sequence.\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of positive odd integers.\n","iterPow":"\niterPow( base:Object|number, exponent:Object|number )\n Returns an iterator which iteratively evaluates the exponential function.\n","iterPrimesSeq":"\niterPrimesSeq( [options:Object] )\n Returns an iterator which generates a sequence of prime numbers.\n","iterprod":"\niterprod( iterator:Object )\n Computes the product of all iterated values.\n","iterPulse":"\niterPulse( [options:Object] )\n Returns an iterator which generates a pulse waveform.\n","iterPush":"\niterPush( iterator:Object, ...items:any )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n","iterRad2deg":"\niterRad2deg( iterator:Object )\n Returns an iterator which iteratively converts an angle from radians to\n degrees.\n","iterRamp":"\niterRamp( iterator:Object )\n Returns an iterator which iteratively evaluates the ramp function.\n","iterrange":"\niterrange( iterator:Object )\n Computes the range of all iterated values.\n","iterReject":"\niterReject( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n","iterReplicate":"\niterReplicate( iterator:Object, n:integer )\n Returns an iterator which replicates each iterated value `n` times.\n","iterReplicateBy":"\niterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n","iterRound":"\niterRound( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest integer.\n","iterRound2":"\niterRound2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two on a linear scale.\n","iterRound10":"\niterRound10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 on a linear scale.\n","iterRsqrt":"\niterRsqrt( iterator:Object )\n Returns an iterator which iteratively computes the reciprocal (inverse)\n square root.\n","iterSawtoothWave":"\niterSawtoothWave( [options:Object] )\n Returns an iterator which generates a sawtooth wave.\n","iterShift":"\niterShift( iterator:Object[, clbk:Function[, thisArg:any]] )\n Returns an iterator which skips the first value of a provided iterator.\n","iterSignum":"\niterSignum( iterator:Object )\n Returns an iterator which iteratively evaluates the signum function.\n","iterSin":"\niterSin( iterator:Object )\n Returns an iterator which iteratively computes the sine.\n","iterSinc":"\niterSinc( iterator:Object )\n Returns an iterator which iteratively computes the normalized cardinal sine.\n","iterSineWave":"\niterSineWave( [options:Object] )\n Returns an iterator which generates a sine wave.\n","iterSinh":"\niterSinh( iterator:Object )\n Returns an iterator which iteratively evaluates the hyperbolic sine.\n","iterSinpi":"\niterSinpi( iterator:Object )\n Returns an iterator which computes the sine of each iterated value times π.\n","iterSlice":"\niterSlice( iterator:Object[, begin:integer[, end:integer]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n","iterSome":"\niterSome( iterator:Object, n:number )\n Tests whether at least `n` iterated values are truthy.\n","iterSomeBy":"\niterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n","iterSpence":"\niterSpence( iterator:Object )\n Returns an iterator which iteratively evaluates Spence's function.\n","iterSqrt":"\niterSqrt( iterator:Object )\n Returns an iterator which iteratively computes the principal square root.\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator:Object )\n Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n accurately for small `x`.\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options:Object] )\n Returns an iterator which generates a sequence of squared triangular\n numbers.\n","iterSquaresSeq":"\niterSquaresSeq( [options:Object] )\n Returns an iterator which generates a sequence of squares.\n","iterSquareWave":"\niterSquareWave( [options:Object] )\n Returns an iterator which generates a square wave.\n","iterstdev":"\niterstdev( iterator:Object[, mean:number] )\n Computes a correct sample standard deviation over all iterated values.\n","iterStep":"\niterStep( start:number, increment:number[, N:number] )\n Returns an iterator which returns a sequence of numbers according to a\n specified increment.\n","iterStrided":"\niterStrided( iterator:Object, stride:integer[, offset:integer[, \n eager:boolean]] )\n Returns an iterator which steps by a specified amount.\n","iterStridedBy":"\niterStridedBy( iterator:Object, fcn:Function[, offset:integer[, \n eager:boolean]][, thisArg:any] )\n Returns an iterator which steps according to a provided callback function.\n","iterSubtract":"\niterSubtract( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n","itersum":"\nitersum( iterator:Object )\n Computes the sum of all iterated values.\n","itersumabs":"\nitersumabs( iterator:Object )\n Computes the sum of absolute values for all iterated values.\n","itersumabs2":"\nitersumabs2( iterator:Object )\n Computes the sum of squared absolute values for all iterated values.\n","iterTan":"\niterTan( iterator:Object )\n Returns an iterator which iteratively evaluates the tangent.\n","iterTanh":"\niterTanh( iterator:Object )\n Returns an iterator which iteratively evaluates the hyperbolic tangent.\n","iterThunk":"\niterThunk( iterFcn:Function[, ...args:any] )\n Returns an iterator \"thunk\".\n","iterTriangleWave":"\niterTriangleWave( [options:Object] )\n Returns an iterator which generates a triangle wave.\n","iterTriangularSeq":"\niterTriangularSeq( [options:Object] )\n Returns an iterator which generates a sequence of triangular numbers.\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options:Object] )\n Returns an iterator which generates a Tribonacci sequence.\n \n The returned iterator can only generate the first 64 Tribonacci numbers, as\n larger Tribonacci numbers cannot be safely represented in double-precision\n floating-point format.\n","iterTrigamma":"\niterTrigamma( iterator:Object )\n Returns an iterator which iteratively evaluates the trigamma function.\n","iterTrunc":"\niterTrunc( iterator:Object )\n Returns an iterator which rounds each iterated value toward zero.\n","iterTrunc2":"\niterTrunc2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward zero.\n","iterTrunc10":"\niterTrunc10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward zero.\n","iterUnion":"\niterUnion( iter0:Object, ...iterator:Object )\n Returns an iterator which returns the union of two or more iterators.\n","iterUnique":"\niterUnique( iterator:Object )\n Returns an iterator which returns unique values.\n","iterUniqueBy":"\niterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which returns unique values according to a predicate\n function.\n","iterUniqueByHash":"\niterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )\n Returns an iterator which returns unique values according to a hash\n function.\n","iterUnitspace":"\niterUnitspace( start:number[, stop:number] )\n Returns an iterator which returns numbers incremented by one.\n","iterUnshift":"\niterUnshift( iterator:Object, ...items:any )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n","iterUntilEach":"\niterUntilEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n","itervariance":"\nitervariance( iterator:Object[, mean:number] )\n Computes an unbiased sample variance over all iterated values.\n","iterVercos":"\niterVercos( iterator:Object )\n Returns an iterator which iteratively computes the versed cosine.\n","iterVersin":"\niterVersin( iterator:Object )\n Returns an iterator which iteratively computes the versed sine.\n","iterWhileEach":"\niterWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n","iterZeta":"\niterZeta( iterator:Object )\n Returns an iterator which iteratively evaluates the Riemann zeta function.\n","joinStream":"\njoinStream( [options:Object] )\n Returns a transform stream which joins streamed data.\n","joinStream.factory":"\njoinStream.factory( [options:Object] )\n Returns a function for creating transform streams for joined streamed data.\n","joinStream.objectMode":"\njoinStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n","kde2d":"\nkde2d( x:Array, y:Array[, options:Object] )\n Two-dimensional kernel density estimation.\n","kebabcase":"\nkebabcase( str:string )\n Converts a string to kebab case.\n","keyBy":"\nkeyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n","keyByRight":"\nkeyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n","keysIn":"\nkeysIn( obj:any )\n Returns an array of an object's own and inherited enumerable property\n names.\n","kruskalTest":"\nkruskalTest( ...x:Array[, options:Object] )\n Computes the Kruskal-Wallis test for equal medians.\n","kstest":"\nkstest( x:Array, y:Function|string[, ...params:number][, \n options:Object] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n","last":"\nlast( str:string[, n:integer][, options:Object] )\n Returns the last character(s) of a string.\n","leveneTest":"\nleveneTest( x:Array[, ...y:Array[, options:Object]] )\n Computes Levene's test for equal variances.\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n","linspace":"\nlinspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, \n options:Object] )\n Generates a linearly spaced array over a specified interval.\n","linspace.assign":"\nlinspace.assign( start:number|ComplexLike, stop:number|ComplexLike, \n out:ArrayLikeObject[, options:Object] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n","LN2":"\nLN2\n Natural logarithm of `2`.\n","LN10":"\nLN10\n Natural logarithm of `10`.\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n","logspace":"\nlogspace( a:number, b:number[, length:integer] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n","lowercase":"\nlowercase( str:string )\n Converts a string to lowercase.\n","lowercaseKeys":"\nlowercaseKeys( obj:Object )\n Converts each object key to lowercase.\n","lowess":"\nlowess( x:Array, y:Array[, options:Object] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n","lpad":"\nlpad( str:string, len:integer[, pad:string] )\n Left pads a string such that the padded string has a length of at least\n `len`.\n","ltrim":"\nltrim( str:string )\n Trims whitespace from the beginning of a string.\n","ltrimN":"\nltrimN( str:string, n:integer[, chars:Array|string] )\n Trims `n` characters from the beginning of a string.\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n","map":"\nmap( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array.\n","map.assign":"\nmap.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n","map2":"\nmap2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n thisArg:any] )\n Applies a function to elements in two input arrays and assigns the results\n to a new array.\n","map2.assign":"\nmap2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n","map2d":"\nmap2d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in an array of arrays and assigns\n the result to a nested element in a new array of arrays.\n","map2Right":"\nmap2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n thisArg:any] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to a new array.\n","map2Right.assign":"\nmap2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n","map3d":"\nmap3d( arr:ArrayLikeObject>, fcn:Function[, \n thisArg:any] )\n Applies a function to each nested element in a three-dimensional nested\n array and assigns the result to a nested element in a new three-dimensional\n nested array.\n","map4d":"\nmap4d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in a four-dimensional nested array\n and assigns the result to a nested element in a new four-dimensional nested\n array.\n","map5d":"\nmap5d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in a five-dimensional nested array\n and assigns the result to a nested element in a new five-dimensional nested\n array.\n","mapArguments":"\nmapArguments( fcn:Function, clbk:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function after\n transforming arguments according to a callback function.\n","mapFun":"\nmapFun( fcn:Function, n:integer[, thisArg:any] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n","mapFunAsync":"\nmapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n","mapKeys":"\nmapKeys( obj:Object, transform:Function )\n Maps keys from one object to a new object having the same values.\n","mapKeysAsync":"\nmapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )\n Maps keys from one object to a new object having the same values.\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options:Object,] transform:Function )\n Returns a function which maps keys from one object to a new object having\n the same values.\n","mapReduce":"\nmapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n reducer:Function[, thisArg:any] )\n Performs a map-reduce operation for each element in an array and returns the\n accumulated result.\n","mapReduceRight":"\nmapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n reducer:Function[, thisArg:any] )\n Performs a map-reduce operation for each element in an array while iterating\n from right to left and returns the accumulated result.\n","mapRight":"\nmapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array, iterating from right to left.\n","mapRight.assign":"\nmapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n","mapValues":"\nmapValues( obj:Object, transform:Function )\n Maps values from one object to a new object having the same keys.\n","mapValuesAsync":"\nmapValuesAsync( obj:Object, [options:Object,] transform:Function, \n done:Function )\n Maps values from one object to a new object having the same keys.\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options:Object,] transform:Function )\n Returns a function which maps values from one object to a new object having\n the same keys.\n","maskArguments":"\nmaskArguments( fcn:Function, mask:ArrayLikeObject[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a specified mask.\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x:ndarray, shape:ArrayLikeObject )\n Broadcasts an ndarray to a specified shape if and only if the specified\n shape differs from the provided ndarray's shape.\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays:ndarray|ArrayLikeObject )\n Broadcasts ndarrays to a common shape.\n","memoize":"\nmemoize( fcn:Function[, hashFunction:Function] )\n Returns a memoized function.\n","merge":"\nmerge( target:Object, ...source:Object )\n Merges objects into a target object.\n","merge.factory":"\nmerge.factory( options:Object )\n Returns a function for merging and extending objects.\n","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options:Object] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n","minutesInMonth":"\nminutesInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of minutes in a month.\n","minutesInYear":"\nminutesInYear( [value:integer|Date] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n","moveProperty":"\nmoveProperty( source:Object, prop:string, target:Object )\n Moves a property from one object to another object.\n","MultiSlice":"\nMultiSlice( ...slice )\n Returns a multi-slice.\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n","namedtypedtuple":"\nnamedtypedtuple( fields:Array[, options:Object] )\n Returns a named typed tuple factory.\n","NAN":"\nNAN\n Double-precision floating-point NaN.\n","naryFunction":"\nnaryFunction( fcn:Function, arity:integer[, thisArg:any] )\n Returns a function that applies a specified number of arguments to a\n provided function.\n","nativeClass":"\nnativeClass( value:any )\n Returns a string value indicating a specification defined classification of\n an object.\n","ndarray":"\nndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string[, options:Object] )\n Returns an ndarray.\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","ndarray.prototype.data":"\nndarray.prototype.data\n Pointer to the underlying data buffer.\n","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n Underlying data type.\n","ndarray.prototype.flags":"\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","ndarray.prototype.length":"\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n Number of dimensions.\n","ndarray.prototype.offset":"\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","ndarray.prototype.order":"\nndarray.prototype.order\n Array order.\n","ndarray.prototype.shape":"\nndarray.prototype.shape\n Array shape.\n","ndarray.prototype.strides":"\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","ndarray.prototype.get":"\nndarray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","ndarray.prototype.iget":"\nndarray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","ndarray.prototype.set":"\nndarray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","ndarray.prototype.iset":"\nndarray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","ndarray.prototype.toString":"\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n","ndarray2array":"\nndarray2array( x:ndarray )\n Converts an ndarray to a generic array.\n","ndarray2fancy":"\nndarray2fancy( x:ndarray[, options:Object] )\n Converts an ndarray to an object supporting fancy indexing.\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options:Object] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n","ndarray2fancy.idx":"\nndarray2fancy.idx( x:ndarray[, options:Object] )\n Wraps a provided ndarray as an ndarray index object.\n","ndarray2json":"\nndarray2json( x:ndarray )\n Serializes an ndarray as a JSON object.\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x:ndarray )\n Returns the underlying data buffer of a provided ndarray.\n","ndarrayDataType":"\nndarrayDataType( x:ndarray )\n Returns the data type of a provided ndarray.\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind:string] )\n Returns a list of ndarray data types.\n","ndarrayDataTypes.binary":"\nndarrayDataTypes.binary\n Read-only property returning a data type instance representing a binary data\n type.\n","ndarrayDataTypes.boolean":"\nndarrayDataTypes.boolean\n Read-only property returning a data type instance representing a boolean\n data type.\n","ndarrayDataTypes.complex32":"\nndarrayDataTypes.complex32\n Read-only property returning a data type instance representing a half-\n precision complex floating-point number data type.\n","ndarrayDataTypes.complex64":"\nndarrayDataTypes.complex64\n Read-only property returning a data type instance representing a single-\n precision complex floating-point number data type.\n","ndarrayDataTypes.complex128":"\nndarrayDataTypes.complex128\n Read-only property returning a data type instance representing a double-\n precision complex floating-point number data type.\n","ndarrayDataTypes.float16":"\nndarrayDataTypes.float16\n Read-only property returning a data type instance representing a half-\n precision real-valued floating-point number data type.\n","ndarrayDataTypes.float32":"\nndarrayDataTypes.float32\n Read-only property returning a data type instance representing a single-\n precision real-valued floating-point number data type.\n","ndarrayDataTypes.float64":"\nndarrayDataTypes.float64\n Read-only property returning a data type instance representing a double-\n precision real-valued floating-point number data type.\n","ndarrayDataTypes.generic":"\nndarrayDataTypes.generic\n Read-only property returning a data type instance representing a \"generic\"\n data type.\n","ndarrayDataTypes.int8":"\nndarrayDataTypes.int8\n Read-only property returning a data type instance representing a signed\n 8-bit integer data type.\n","ndarrayDataTypes.int16":"\nndarrayDataTypes.int16\n Read-only property returning a data type instance representing a signed\n 16-bit integer data type.\n","ndarrayDataTypes.int32":"\nndarrayDataTypes.int32\n Read-only property returning a data type instance representing a signed\n 32-bit integer data type.\n","ndarrayDataTypes.uint8":"\nndarrayDataTypes.uint8\n Read-only property returning a data type instance representing an unsigned\n 8-bit integer data type.\n","ndarrayDataTypes.uint8c":"\nndarrayDataTypes.uint8c\n Read-only property returning a data type instance representing an unsigned\n clamped 8-bit integer data type.\n","ndarrayDataTypes.uint16":"\nndarrayDataTypes.uint16\n Read-only property returning a data type instance representing an unsigned\n 16-bit integer data type.\n","ndarrayDataTypes.uint32":"\nndarrayDataTypes.uint32\n Read-only property returning a data type instance representing an unsigned\n 32-bit integer data type.\n","ndarrayDispatch":"\nndarrayDispatch( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns an ndarray function interface which performs multiple dispatch.\n","ndarrayFlag":"\nndarrayFlag( x:ndarray, name:string|symbol )\n Returns a specified flag for a provided ndarray.\n","ndarrayFlags":"\nndarrayFlags( x:ndarray )\n Returns the flags of a provided ndarray.\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x:ndarrayLike[, options:Object] )\n Converts an ndarray-like object to an ndarray.\n","ndarrayMinDataType":"\nndarrayMinDataType( value:any )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast and, for floating-point data types, can be downcast.\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype:any] )\n Returns the next larger ndarray data type of the same kind.\n","ndarrayOffset":"\nndarrayOffset( x:ndarray )\n Returns the index offset specifying the underlying buffer index of the first\n iterated ndarray element.\n","ndarrayOrder":"\nndarrayOrder( x:ndarray )\n Returns the layout order of a provided ndarray.\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n","ndarrayShape":"\nndarrayShape( x:ndarray )\n Returns the shape of a provided ndarray.\n","ndarrayStride":"\nndarrayStride( x:ndarray, dim:integer )\n Returns the stride along a specified dimension for a provided ndarray.\n","ndarrayStrides":"\nndarrayStrides( x:ndarray )\n Returns the strides of a provided ndarray.\n","ndat":"\nndat( x:ndarray[, ...indices:integer] )\n Returns an ndarray element.\n","ndempty":"\nndempty( shape:ArrayLikeObject|integer[, options:Object] )\n Returns an uninitialized ndarray having a specified shape and data type.\n","ndemptyLike":"\nndemptyLike( x:ndarray[, options:Object] )\n Returns an uninitialized ndarray having the same shape and data type as a\n provided input ndarray.\n","ndfill":"\nndfill( x:ndarrayLike, value:any )\n Fills an input ndarray with a specified value.\n","ndfillBy":"\nndfillBy( x:ndarrayLike, fcn:Function[, thisArg:any] )\n Fills an input ndarray according to a callback function.\n","ndfilter":"\nndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n Returns a shallow copy of an ndarray containing only those elements which\n pass a test implemented by a predicate function.\n","ndfilterMap":"\nndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n Filters and maps elements in an input ndarray to elements in a new output\n ndarray according to a callback function.\n","ndforEach":"\nndforEach( x:ndarray, fcn:Function[, thisArg:any] )\n Invokes a callback function once for each ndarray element.\n","ndims":"\nndims( x:ndarray )\n Returns the number of ndarray dimensions.\n","ndindex":"\nndindex( x:ndarray[, options:Object] )\n Wraps a provided array as an ndarray index object.\n","ndindex.free":"\nndindex.free( id:string )\n Frees the instance associated with a provided identifier.\n","ndindex.get":"\nndindex.get( id:string )\n Returns the ndarray associated with the instance having a provided\n identifier.\n","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x:ndarray[, options:Object] )\n Returns an ndarray index containing Cartesian indices.\n","ndindex.linearIndex":"\nndindex.linearIndex( x:ndarray[, options:Object] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n","ndindex.prototype.data":"\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n","ndindex.prototype.id":"\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n","ndindex.prototype.kind":"\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n","ndindex.prototype.type":"\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n","ndindex.prototype.toString":"\nndindex.prototype.toString()\n Serializes an instance as a string.\n","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n","nditer2arrayEach":"\nnditer2arrayEach( iterator:Object )\n Returns an iterator which converts each iterated ndarray to a generic array.\n","nditerColumnEntries":"\nnditerColumnEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, column] pairs for each column in a\n matrix (or stack of matrices).\n","nditerColumns":"\nnditerColumns( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each column in a matrix (or stack of\n matrices).\n","nditerEntries":"\nnditerEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, value] pairs for each element in a\n provided ndarray.\n","nditerIndices":"\nnditerIndices( shape:Array[, options:Object] )\n Returns an iterator which returns indices for use indexing into an ndarray\n having a specified shape.\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr:ArrayLike, ndims:integer )\n Returns an iterator which iterates over interleaved subarrays.\n","nditerMatrices":"\nnditerMatrices( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each matrix in a stack of matrices.\n","nditerMatrixEntries":"\nnditerMatrixEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, matrix] pairs for each matrix in a\n stack of matrices.\n","nditerRowEntries":"\nnditerRowEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, row] pairs for each row in a\n matrix (or stack of matrices).\n","nditerRows":"\nnditerRows( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each row in a matrix (or stack of\n matrices).\n","nditerSelectDimension":"\nnditerSelectDimension( x:ndarray, dim:integer[, options:Object] )\n Returns an iterator which iterates over each view along a specified\n dimension.\n","nditerStacks":"\nnditerStacks( x:ndarray, dims:Array[, options:Object] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays according to a list of specified stack dimensions.\n","nditerSubarrays":"\nnditerSubarrays( x:ndarray, ndims:integer[, options:Object] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays.\n","nditerValues":"\nnditerValues( x:ndarray[, options:Object] )\n Returns an iterator which returns individual elements from a provided\n ndarray.\n","ndmap":"\nndmap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n Applies a callback function to elements in an input ndarray and assigns\n results to elements in a new output ndarray.\n","ndreject":"\nndreject( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n Returns a shallow copy of an ndarray containing only those elements which\n fail a test implemented by a predicate function.\n","ndslice":"\nndslice( x:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, \n options:Object] )\n Returns a read-only view of an input ndarray.\n","ndsliceAssign":"\nndsliceAssign( x:ndarray, y:ndarray, \n ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )\n Assigns element values from a broadcasted input ndarray to corresponding\n elements in an output ndarray view.\n","ndsliceDimension":"\nndsliceDimension( x:ndarray, dim:integer, slice:Slice|integer|null|undefined[, \n options:Object] )\n Returns a read-only view of an input ndarray when sliced along a specified\n dimension.\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x:ndarray, dim:integer, start:integer[, options:Object] )\n Returns a read-only shifted view of an input ndarray along a specified\n dimension.\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x:ndarray, dim:integer, stop:integer[, options:Object] )\n Returns a read-only truncated view of an input ndarray along a specified\n dimension.\n","ndsliceFrom":"\nndsliceFrom( x:ndarray, ...start:null|void|integer[, options:Object] )\n Returns a read-only shifted view of an input ndarray.\n","ndsliceTo":"\nndsliceTo( x:ndarray, ...stop:null|void|integer[, options:Object] )\n Returns a read-only truncated view of an input ndarray.\n","ndzeros":"\nndzeros( shape:ArrayLikeObject|integer[, options:Object] )\n Returns a zero-filled ndarray having a specified shape and data type.\n","ndzerosLike":"\nndzerosLike( x:ndarray[, options:Object] )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str:string[, fromIndex:integer] )\n Returns the next extended grapheme cluster break in a string after a\n specified position.\n","nextTick":"\nnextTick( clbk[, ...args] )\n Adds a callback to the \"next tick queue\".\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n","none":"\nnone( collection:Array|TypedArray|Object )\n Tests whether all elements in a collection are falsy.\n","noneBy":"\nnoneBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n","noneByAsync":"\nnoneByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n","noneByAsync.factory":"\nnoneByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n","noneByRight":"\nnoneByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n","noneByRightAsync":"\nnoneByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n","noneInBy":"\nnoneInBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every property in an object fails a test implemented by a\n predicate function.\n","nonEnumerableProperties":"\nnonEnumerableProperties( value:any )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value:any )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value:any )\n Returns an array of an object's own non-enumerable property names.\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value:any )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value:any )\n Returns an array of an object's own non-enumerable symbol properties.\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n","noneOwnBy":"\nnoneOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every own property of an object fails a test implemented\n by a predicate function.\n","nonIndexKeys":"\nnonIndexKeys( obj:any )\n Returns an array of an object's own enumerable property names which are not\n integer indices.\n","noop":"\nnoop()\n A function which does nothing.\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n","num2words":"\nnum2words( value:integer[, options:Object] )\n Converts a number to a word representation.\n","Number":"\nNumber( value:number )\n Returns a Number object.\n","numel":"\nnumel( x:ndarray )\n Returns the number of elements in an ndarray.\n","numelDimension":"\nnumelDimension( x:ndarray, dim:integer )\n Returns the size (i.e., number of elements) of a specified dimension for a\n provided ndarray.\n","numGraphemeClusters":"\nnumGraphemeClusters( str:string )\n Returns the number of grapheme clusters in a string.\n","Object":"\nObject( value:any )\n Returns an object.\n","Object.assign":"\nObject.assign( target:Object, ...sources:Object )\n Assigns enumerable and own properties from source objects to a target\n object.\n","Object.create":"\nObject.create( prototype:Object, properties:Object )\n Creates a new object with a specified prototype object and properties.\n","Object.defineProperties":"\nObject.defineProperties( obj:Object, properties:Object )\n Defines properties for an object.\n","Object.defineProperty":"\nObject.defineProperty( obj:Object, key:string, descriptor:Object )\n Defines a property for an object.\n","Object.entries":"\nObject.entries( obj:Object )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n","Object.freeze":"\nObject.freeze( obj:Object )\n Freezes an object.\n","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj:Object, key:string )\n Returns an object's own property descriptor.\n","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj:Object )\n Returns an object's own property descriptors.\n","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj:Object )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj:Object )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj:Object )\n Returns an object's prototype.\n","Object.hasOwn":"\nObject.hasOwn( obj:Object, p:string )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n","Object.is":"\nObject.is( value1:any, value2:any )\n Returns a boolean indicating whether two values are the same value.\n","Object.isExtensible":"\nObject.isExtensible( obj:Object )\n Returns a boolean indicating whether an object is extensible.\n","Object.isFrozen":"\nObject.isFrozen( obj:Object )\n Returns a boolean indicating whether an object is frozen.\n","Object.isSealed":"\nObject.isSealed( obj:Object )\n Returns a boolean indicating whether an object is sealed.\n","Object.keys":"\nObject.keys( obj:Object )\n Returns an array of an object's own enumerable string-keyed property\n names.\n","Object.preventExtensions":"\nObject.preventExtensions( obj:Object )\n Prevents the addition of new properties to an object.\n","Object.seal":"\nObject.seal( obj:Object )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj:Object, proto:Object )\n Sets an object's prototype.\n","Object.values":"\nObject.values( obj:Object )\n Returns an array of an object's own enumerable property values.\n","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n","Object.prototype.toString":"\nObject.prototype.toString()\n Returns a string representing the object.\n","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p:string )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj:Object )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p:string )\n Returns a boolean indicating whether an object's property is enumerable.\n","Object.prototype.constructor":"\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n","objectEntries":"\nobjectEntries( obj:ObjectLike )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n","objectEntriesIn":"\nobjectEntriesIn( obj:ObjectLike )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n","objectFromEntries":"\nobjectFromEntries( entries:Array )\n Creates an object from an array of key-value pairs.\n","objectInverse":"\nobjectInverse( obj:ObjectLike[, options:Object] )\n Inverts an object, such that keys become values and values become keys.\n","objectInverseBy":"\nobjectInverseBy( obj:ObjectLike, [options:Object,] transform:Function )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n","objectKeys":"\nobjectKeys( value:any )\n Returns an array of an object's own enumerable property names.\n","objectValues":"\nobjectValues( obj:ObjectLike )\n Returns an array of an object's own enumerable property values.\n","objectValuesIn":"\nobjectValuesIn( obj:ObjectLike )\n Returns an array of an object's own and inherited enumerable property\n values.\n","omit":"\nomit( obj:Object, keys:string|Array )\n Returns a partial object copy excluding specified keys.\n","omitBy":"\nomitBy( obj:Object, predicate:Function )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n","open":"\nopen( path:string|Buffer[, flags:string|number[, mode:integer]], clbk:Function )\n Asynchronously opens a file.\n","open.sync":"\nopen.sync( path:string|Buffer[, flags:string|number[, mode:integer]] )\n Synchronously opens a file.\n","openURL":"\nopenURL( url:string )\n Opens a URL in a user's default browser.\n","ordinalize":"\nordinalize( value:string|integer[, options:Object] )\n Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n","pad":"\npad( str:string, len:integer[, options:Object] )\n Pads a `string` such that the padded `string` has length `len`.\n","padjust":"\npadjust( pvals:Array, method:string[, comparisons:integer] )\n Adjusts supplied p-values for multiple comparisons via a specified method.\n","papply":"\npapply( fcn:Function, ...args:any )\n Returns a function of smaller arity by partially applying arguments.\n","papplyRight":"\npapplyRight( fcn:Function, ...args:any )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n","parallel":"\nparallel( files:Array, [options:Object,] clbk:Function )\n Executes scripts in parallel.\n","parseJSON":"\nparseJSON( str:string[, reviver:Function] )\n Attempts to parse a string as JSON.\n","pascalcase":"\npascalcase( str:string )\n Converts a string to Pascal case.\n","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n","pcorrtest":"\npcorrtest( x:Array, y:Array[, options:Object] )\n Computes a Pearson product-moment correlation test between paired samples.\n","percentEncode":"\npercentEncode( str:string )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","PHI":"\nPHI\n Golden ratio.\n","PI":"\nPI\n The mathematical constant `π`.\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n","pick":"\npick( obj:Object, keys:string|Array )\n Returns a partial object copy containing only specified keys.\n","pickArguments":"\npickArguments( fcn:Function, indices:Array[, thisArg:any] )\n Returns a function that applies specified arguments to a provided function.\n","pickBy":"\npickBy( obj:Object, predicate:Function )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n","pkg2alias":"\npkg2alias( pkg:string )\n Returns the alias associated with a specified package name.\n","pkg2related":"\npkg2related( pkg:string )\n Returns package names related to a specified package name.\n","pkg2standalone":"\npkg2standalone( pkg:string )\n Returns the standalone package name associated with a provided internal\n package name.\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n","plot":"\nplot( [x:Array|Array, y:Array|Array,] [options:Object] )\n Returns a plot instance for creating 2-dimensional plots.\n","Plot":"\nPlot( [x:Array|Array, y:Array|Array,] [options:Object] )\n Returns a plot instance for creating 2-dimensional plots.\n","pluck":"\npluck( arr:Array, prop:string[, options:Object] )\n Extracts a property value from each element of an object array.\n","pop":"\npop( collection:Array|TypedArray|Object )\n Removes and returns the last element of a collection.\n","porterStemmer":"\nporterStemmer( word:string )\n Extracts the stem of a given word.\n","prepend":"\nprepend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the beginning of another collection.\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str:string[, fromIndex:integer] )\n Returns the previous extended grapheme cluster break in a string before a\n specified position.\n","PRIMES_100K":"\nPRIMES_100K()\n Returns an array containing the first 100,000 prime numbers.\n","properties":"\nproperties( value:any )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n","propertiesIn":"\npropertiesIn( value:any )\n Returns an array of an object's own and inherited property names and\n symbols.\n","propertyDescriptor":"\npropertyDescriptor( value:any, property:string|symbol )\n Returns a property descriptor for an object's own property.\n","propertyDescriptorIn":"\npropertyDescriptorIn( value:any, property:string|symbol )\n Returns a property descriptor for an object's own or inherited property.\n","propertyDescriptors":"\npropertyDescriptors( value:any )\n Returns an object's own property descriptors.\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value:any )\n Returns an object's own and inherited property descriptors.\n","propertyNames":"\npropertyNames( value:any )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n","propertyNamesIn":"\npropertyNamesIn( value:any )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n","propertySymbols":"\npropertySymbols( value:any )\n Returns an array of an object's own symbol properties.\n","propertySymbolsIn":"\npropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited symbol properties.\n","Proxy":"\nProxy( target:Object, handlers:Object )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n","Proxy.revocable":"\nProxy.revocable( target:Object, handlers:Object )\n Returns a revocable proxy object.\n","push":"\npush( collection:Array|TypedArray|Object, ...items:any )\n Adds one or more elements to the end of a collection.\n","quarterOfYear":"\nquarterOfYear( [month:integer|string|Date] )\n Returns the quarter of the year.\n","random.array.arcsine":"\nrandom.array.arcsine( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an arcsine\n distribution.\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n Length of generator seed.\n","random.array.arcsine.state":"\nrandom.array.arcsine.state\n Generator state.\n","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n Length of generator state.\n","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n","random.array.bernoulli":"\nrandom.array.bernoulli( len:integer, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n Generator state.\n","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n Length of generator state.\n","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.array.beta":"\nrandom.array.beta( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a beta\n distribution.\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n","random.array.beta.seed":"\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n Length of generator seed.\n","random.array.beta.state":"\nrandom.array.beta.state\n Generator state.\n","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n Length of generator state.\n","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n","random.array.betaprime":"\nrandom.array.betaprime( len:integer, alpha:number, beta:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a beta prime\n distribution.\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n Length of generator seed.\n","random.array.betaprime.state":"\nrandom.array.betaprime.state\n Generator state.\n","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n Length of generator state.\n","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n","random.array.binomial":"\nrandom.array.binomial( len:integer, n:number, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a binomial\n distribution.\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n:number, p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n:number, p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n","random.array.binomial.seed":"\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n Length of generator seed.\n","random.array.binomial.state":"\nrandom.array.binomial.state\n Generator state.\n","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n Length of generator state.\n","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n","random.array.cauchy":"\nrandom.array.cauchy( len:integer, x0:number, gamma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Cauchy\n distribution.\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0:number, gamma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0:number, gamma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n Length of generator seed.\n","random.array.cauchy.state":"\nrandom.array.cauchy.state\n Generator state.\n","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n Length of generator state.\n","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n","random.array.chi":"\nrandom.array.chi( len:integer, k:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a chi\n distribution.\n","random.array.chi.assign":"\nrandom.array.chi.assign( k:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n","random.array.chi.factory":"\nrandom.array.chi.factory( [k:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n","random.array.chi.seed":"\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n Length of generator seed.\n","random.array.chi.state":"\nrandom.array.chi.state\n Generator state.\n","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n Length of generator state.\n","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n","random.array.chisquare":"\nrandom.array.chisquare( len:integer, k:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a chi-square\n distribution.\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n Length of generator seed.\n","random.array.chisquare.state":"\nrandom.array.chisquare.state\n Generator state.\n","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n Length of generator state.\n","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.array.cosine":"\nrandom.array.cosine( len:integer, mu:number, s:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu:number, s:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu:number, s:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n","random.array.cosine.seed":"\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n Length of generator seed.\n","random.array.cosine.state":"\nrandom.array.cosine.state\n Generator state.\n","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n Length of generator state.\n","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n","random.array.discreteUniform":"\nrandom.array.discreteUniform( len:integer, a:number, b:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a:number, b:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n Generator state.\n","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","random.array.erlang":"\nrandom.array.erlang( len:integer, k:number, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an Erlang\n distribution.\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k:number, lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k:number, lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n","random.array.erlang.seed":"\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n Length of generator seed.\n","random.array.erlang.state":"\nrandom.array.erlang.state\n Generator state.\n","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n Length of generator state.\n","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n","random.array.exponential":"\nrandom.array.exponential( len:integer, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an exponential\n distribution.\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.array.exponential.seed":"\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n Length of generator seed.\n","random.array.exponential.state":"\nrandom.array.exponential.state\n Generator state.\n","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n Length of generator state.\n","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n","random.array.f":"\nrandom.array.f( len:integer, d1:number, d2:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an F\n distribution.\n","random.array.f.assign":"\nrandom.array.f.assign( d1:number, d2:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n","random.array.f.factory":"\nrandom.array.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n","random.array.f.PRNG":"\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n","random.array.f.seed":"\nrandom.array.f.seed\n Pseudorandom number generator seed.\n","random.array.f.seedLength":"\nrandom.array.f.seedLength\n Length of generator seed.\n","random.array.f.state":"\nrandom.array.f.state\n Generator state.\n","random.array.f.stateLength":"\nrandom.array.f.stateLength\n Length of generator state.\n","random.array.f.byteLength":"\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n","random.array.frechet":"\nrandom.array.frechet( len:integer, alpha:number, s:number, m:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha:number, s:number, m:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha:number, s:number, m:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n","random.array.frechet.seed":"\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n Length of generator seed.\n","random.array.frechet.state":"\nrandom.array.frechet.state\n Generator state.\n","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n Length of generator state.\n","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n","random.array.gamma":"\nrandom.array.gamma( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a gamma\n distribution.\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n","random.array.gamma.seed":"\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n Length of generator seed.\n","random.array.gamma.state":"\nrandom.array.gamma.state\n Generator state.\n","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n Length of generator state.\n","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n","random.array.geometric":"\nrandom.array.geometric( len:integer, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a geometric\n distribution.\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.array.geometric.seed":"\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n Length of generator seed.\n","random.array.geometric.state":"\nrandom.array.geometric.state\n Generator state.\n","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n Length of generator state.\n","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n","random.array.gumbel":"\nrandom.array.gumbel( len:integer, mu:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n Length of generator seed.\n","random.array.gumbel.state":"\nrandom.array.gumbel.state\n Generator state.\n","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n Length of generator state.\n","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n","random.array.hypergeometric":"\nrandom.array.hypergeometric( len:integer, N:number, K:number, n:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N:number, K:number, n:number, \n out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N:number, K:number, n:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n Generator state.\n","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","random.array.invgamma":"\nrandom.array.invgamma( len:integer, alpha:number, beta:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n Length of generator seed.\n","random.array.invgamma.state":"\nrandom.array.invgamma.state\n Generator state.\n","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n Length of generator state.\n","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n double bounded distribution.\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n Generator state.\n","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","random.array.laplace":"\nrandom.array.laplace( len:integer, mu:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n","random.array.laplace.seed":"\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n Length of generator seed.\n","random.array.laplace.state":"\nrandom.array.laplace.state\n Generator state.\n","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n Length of generator state.\n","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n","random.array.levy":"\nrandom.array.levy( len:integer, mu:number, c:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Lévy\n distribution.\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu:number, c:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n","random.array.levy.factory":"\nrandom.array.levy.factory( [mu:number, c:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n","random.array.levy.seed":"\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n Length of generator seed.\n","random.array.levy.state":"\nrandom.array.levy.state\n Generator state.\n","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n Length of generator state.\n","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n","random.array.logistic":"\nrandom.array.logistic( len:integer, mu:number, s:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a logistic\n distribution.\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu:number, s:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu:number, s:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n","random.array.logistic.seed":"\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n Length of generator seed.\n","random.array.logistic.state":"\nrandom.array.logistic.state\n Generator state.\n","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n Length of generator state.\n","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n","random.array.lognormal":"\nrandom.array.lognormal( len:integer, mu:number, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a lognormal\n distribution.\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu:number, sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu:number, sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n Length of generator seed.\n","random.array.lognormal.state":"\nrandom.array.lognormal.state\n Generator state.\n","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n Length of generator state.\n","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n","random.array.minstd":"\nrandom.array.minstd( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n","random.array.minstd.seed":"\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n Length of generator seed.\n","random.array.minstd.state":"\nrandom.array.minstd.state\n Generator state.\n","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n Length of generator state.\n","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n Generator state.\n","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n","random.array.mt19937":"\nrandom.array.mt19937( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[0, 4294967295]`.\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n Length of generator seed.\n","random.array.mt19937.state":"\nrandom.array.mt19937.state\n Generator state.\n","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n Length of generator state.\n","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len:integer, r:number, p:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a negative\n binomial distribution.\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r:number, p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n Generator state.\n","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","random.array.normal":"\nrandom.array.normal( len:integer, mu:number, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a normal\n distribution.\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu:number, sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n","random.array.normal.factory":"\nrandom.array.normal.factory( [mu:number, sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n","random.array.normal.seed":"\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n Length of generator seed.\n","random.array.normal.state":"\nrandom.array.normal.state\n Generator state.\n","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n Length of generator state.\n","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n","random.array.pareto1":"\nrandom.array.pareto1( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n Length of generator seed.\n","random.array.pareto1.state":"\nrandom.array.pareto1.state\n Generator state.\n","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n Length of generator state.\n","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n","random.array.poisson":"\nrandom.array.poisson( len:integer, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Poisson\n distribution.\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.array.poisson.seed":"\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n Length of generator seed.\n","random.array.poisson.state":"\nrandom.array.poisson.state\n Generator state.\n","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n Length of generator state.\n","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n","random.array.randu":"\nrandom.array.randu( len:integer[, options:Object] )\n Returns an array containing uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options:Object] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n","random.array.randu.seed":"\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n Length of generator seed.\n","random.array.randu.state":"\nrandom.array.randu.state\n Generator state.\n","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n Length of generator state.\n","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n","random.array.rayleigh":"\nrandom.array.rayleigh( len:integer, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n Generator state.\n","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n Length of generator state.\n","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.array.t":"\nrandom.array.t( len:integer, v:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Student's t\n distribution.\n","random.array.t.assign":"\nrandom.array.t.assign( v:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n","random.array.t.factory":"\nrandom.array.t.factory( [v:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n","random.array.t.PRNG":"\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n","random.array.t.seed":"\nrandom.array.t.seed\n Pseudorandom number generator seed.\n","random.array.t.seedLength":"\nrandom.array.t.seedLength\n Length of generator seed.\n","random.array.t.state":"\nrandom.array.t.state\n Generator state.\n","random.array.t.stateLength":"\nrandom.array.t.stateLength\n Length of generator state.\n","random.array.t.byteLength":"\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n","random.array.triangular":"\nrandom.array.triangular( len:integer, a:number, b:number, c:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a triangular\n distribution.\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a:number, b:number, c:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n","random.array.triangular.seed":"\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n Length of generator seed.\n","random.array.triangular.state":"\nrandom.array.triangular.state\n Generator state.\n","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n Length of generator state.\n","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n","random.array.uniform":"\nrandom.array.uniform( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n","random.array.uniform.seed":"\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n Length of generator seed.\n","random.array.uniform.state":"\nrandom.array.uniform.state\n Generator state.\n","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n Length of generator state.\n","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n","random.array.weibull":"\nrandom.array.weibull( len:integer, k:number, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Weibull\n distribution.\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k:number, lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k:number, lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n","random.array.weibull.seed":"\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n Length of generator seed.\n","random.array.weibull.state":"\nrandom.array.weibull.state\n Generator state.\n","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n Length of generator state.\n","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n","random.iterators.arcsine":"\nrandom.iterators.arcsine( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.iterators.beta":"\nrandom.iterators.beta( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.iterators.binomial":"\nrandom.iterators.binomial( n:integer, p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0:number, Ɣ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n","random.iterators.chi":"\nrandom.iterators.chi( k:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ:number, s:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a:integer, b:integer[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n","random.iterators.erlang":"\nrandom.iterators.erlang( k:integer, λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.iterators.f":"\nrandom.iterators.f( d1:number, d2:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n","random.iterators.frechet":"\nrandom.iterators.frechet( α:number, s:number, m:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.iterators.gamma":"\nrandom.iterators.gamma( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n","random.iterators.geometric":"\nrandom.iterators.geometric( p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.iterators.levy":"\nrandom.iterators.levy( μ:number, c:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ:number, s:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ:number, σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r:number, p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n","random.iterators.normal":"\nrandom.iterators.normal( μ:number, σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n","random.iterators.randi":"\nrandom.iterators.randi( [options:Object] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n","random.iterators.randn":"\nrandom.iterators.randn( [options:Object] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n","random.iterators.randu":"\nrandom.iterators.randu( [options:Object] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n","random.iterators.t":"\nrandom.iterators.t( v:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n","random.iterators.triangular":"\nrandom.iterators.triangular( a:number, b:number, c:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.iterators.uniform":"\nrandom.iterators.uniform( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n","random.iterators.weibull":"\nrandom.iterators.weibull( k:number, λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n","random.streams.arcsine":"\nrandom.streams.arcsine( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n","random.streams.bernoulli":"\nrandom.streams.bernoulli( p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n","random.streams.beta":"\nrandom.streams.beta( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n","random.streams.betaprime":"\nrandom.streams.betaprime( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n","random.streams.binomial":"\nrandom.streams.binomial( n:integer, p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n:integer, p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n:integer, p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n","random.streams.cauchy":"\nrandom.streams.cauchy( x0:number, γ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0:number, γ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0:number, γ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n","random.streams.chi":"\nrandom.streams.chi( k:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n","random.streams.chisquare":"\nrandom.streams.chisquare( k:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n","random.streams.cosine":"\nrandom.streams.cosine( μ:number, s:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ:number, s:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ:number, s:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a:integer, b:integer[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a:integer, b:integer, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a:integer, b:integer[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n","random.streams.erlang":"\nrandom.streams.erlang( k:integer, λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k:number, λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k:number, λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n","random.streams.exponential":"\nrandom.streams.exponential( λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n","random.streams.f":"\nrandom.streams.f( d1:number, d2:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1:number, d2:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n","random.streams.frechet":"\nrandom.streams.frechet( α:number, s:number, m:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Fréchet distribution.\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α:number, s:number, m:number,]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α:number, s:number, m:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n","random.streams.gamma":"\nrandom.streams.gamma( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n","random.streams.geometric":"\nrandom.streams.geometric( p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n","random.streams.gumbel":"\nrandom.streams.gumbel( μ:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N:integer, K:integer, n:integer,]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n","random.streams.invgamma":"\nrandom.streams.invgamma( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.laplace":"\nrandom.streams.laplace( μ:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n","random.streams.levy":"\nrandom.streams.levy( μ:number, c:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ:number, c:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ:number, c:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n","random.streams.logistic":"\nrandom.streams.logistic( μ:number, s:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ:number, s:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ:number, s:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n","random.streams.lognormal":"\nrandom.streams.lognormal( μ:number, σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ:number, σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n","random.streams.minstd":"\nrandom.streams.minstd( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n","random.streams.mt19937":"\nrandom.streams.mt19937( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r:number, p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r:number, p:number, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r:integer, p:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n","random.streams.normal":"\nrandom.streams.normal( μ:number, σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ:number, σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n","random.streams.pareto1":"\nrandom.streams.pareto1( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n","random.streams.poisson":"\nrandom.streams.poisson( λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n","random.streams.randi":"\nrandom.streams.randi( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n","random.streams.randn":"\nrandom.streams.randn( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n","random.streams.randu":"\nrandom.streams.randu( [options:Object] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n","random.streams.t":"\nrandom.streams.t( v:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n","random.streams.triangular":"\nrandom.streams.triangular( a:number, b:number, c:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a:number, b:number, c:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n","random.streams.uniform":"\nrandom.streams.uniform( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n","random.streams.weibull":"\nrandom.streams.weibull( k:number, λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k:number, λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k:number, λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n","random.strided.arcsine":"\nrandom.strided.arcsine( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution.\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n","random.strided.bernoulli":"\nrandom.strided.bernoulli( N:integer, p:ArrayLikeObject, sp:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n Generator state.\n","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.strided.beta":"\nrandom.strided.beta( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution.\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n","random.strided.betaprime":"\nrandom.strided.betaprime( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n","random.strided.chi":"\nrandom.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution.\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n","random.strided.chi.seed":"\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n Length of generator seed.\n","random.strided.chi.state":"\nrandom.strided.chi.state\n Generator state.\n","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n Length of generator state.\n","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n","random.strided.chisquare":"\nrandom.strided.chisquare( N:integer, k:ArrayLikeObject, sk:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n Generator state.\n","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n Length of generator state.\n","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.strided.cosine":"\nrandom.strided.cosine( N:integer, mu:ArrayLikeObject, sm:integer, \n s:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution.\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, s:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, \n sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n","random.strided.exponential":"\nrandom.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution.\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, \n sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n Length of generator seed.\n","random.strided.exponential.state":"\nrandom.strided.exponential.state\n Generator state.\n","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n Length of generator state.\n","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n","random.strided.gamma":"\nrandom.strided.gamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution.\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n","random.strided.geometric":"\nrandom.strided.geometric( N:integer, p:ArrayLikeObject, sp:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution.\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n Length of generator seed.\n","random.strided.geometric.state":"\nrandom.strided.geometric.state\n Generator state.\n","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n Length of generator state.\n","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n","random.strided.invgamma":"\nrandom.strided.invgamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n","random.strided.lognormal":"\nrandom.strided.lognormal( N:integer, mu:ArrayLikeObject, sm:integer, \n sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n","random.strided.minstd":"\nrandom.strided.minstd( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N:integer, out:ArrayLikeObject, \n so:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.mt19937":"\nrandom.strided.mt19937( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive).\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.normal":"\nrandom.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, \n sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution.\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n","random.strided.poisson":"\nrandom.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution.\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, \n ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n Length of generator seed.\n","random.strided.poisson.state":"\nrandom.strided.poisson.state\n Generator state.\n","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n Length of generator state.\n","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n","random.strided.randu":"\nrandom.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n","random.strided.rayleigh":"\nrandom.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N:integer, sigma:ArrayLikeObject, ss:integer, \n os:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n Generator state.\n","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.strided.t":"\nrandom.strided.t( N:integer, v:ArrayLikeObject, sv:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution.\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N:integer, v:ArrayLikeObject, sv:integer, ov:integer, \n out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n","random.strided.t.factory":"\nrandom.strided.t.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n","random.strided.t.seed":"\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n Length of generator seed.\n","random.strided.t.state":"\nrandom.strided.t.state\n Generator state.\n","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n Length of generator state.\n","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n","random.strided.uniform":"\nrandom.strided.uniform( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n","random.strided.weibull":"\nrandom.strided.weibull( N:integer, k:ArrayLikeObject, sk:integer, \n lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution.\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n","ranks":"\nranks( arr:Array[, options:Object] )\n Computes the sample ranks for the values of an array-like object.\n","readDir":"\nreadDir( path:string|Buffer, clbk:Function )\n Asynchronously reads the contents of a directory.\n","readDir.sync":"\nreadDir.sync( path:string|Buffer )\n Synchronously reads the contents of a directory.\n","readFile":"\nreadFile( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n Asynchronously reads the entire contents of a file.\n","readFile.sync":"\nreadFile.sync( file:string|Buffer|integer[, options:Object|string] )\n Synchronously reads the entire contents of a file.\n","readFileList":"\nreadFileList( filepaths:Array[, options:Object|string], clbk:Function )\n Asynchronously reads the entire contents of each file in a file list.\n","readFileList.sync":"\nreadFileList.sync( filepaths:Array[, options:Object|string] )\n Synchronously reads the entire contents of each file in a file list.\n","readJSON":"\nreadJSON( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n Asynchronously reads a file as JSON.\n","readJSON.sync":"\nreadJSON.sync( file:string|Buffer|integer[, options:Object|string] )\n Synchronously reads a file as JSON.\n","readWASM":"\nreadWASM( file:string|Buffer|integer[, options:Object], clbk:Function )\n Asynchronously reads a file as WebAssembly.\n","readWASM.sync":"\nreadWASM.sync( file:string|Buffer|integer[, options:Object] )\n Synchronously reads a file as WebAssembly.\n","real":"\nreal( z:Complex128 )\n Returns the real component of a double-precision complex floating-point\n number.\n","realarray":"\nrealarray( [dtype:string] )\n Creates a typed array.\n\nrealarray( length:integer[, dtype:string] )\n Returns a typed array having a specified length.\n\nrealarray( typedarray:TypedArray[, dtype:string] )\n Creates a typed array from another typed array.\n\nrealarray( obj:Object[, dtype:string] )\n Creates a typed array from an array-like object or iterable.\n\nrealarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a typed array view of an ArrayBuffer.\n","realarrayCtors":"\nrealarrayCtors( dtype:string )\n Returns a typed array constructor.\n","realarrayDataTypes":"\nrealarrayDataTypes()\n Returns a list of typed array real-valued data types.\n","realf":"\nrealf( z:Complex64 )\n Returns the real component of a single-precision complex floating-point\n number.\n","realmax":"\nrealmax( dtype:string )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n","realmin":"\nrealmin( dtype:string )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n","reBasename":"\nreBasename( [platform:string] )\n Returns a regular expression to capture the last part of a path.\n","reBasename.REGEXP":"\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n","reBasenamePosix":"\nreBasenamePosix()\n Returns a regular expression to capture the last part of a POSIX path.\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n","reBasenameWindows":"\nreBasenameWindows()\n Returns a regular expression to capture the last part of a Windows path.\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n","reColorHexadecimal":"\nreColorHexadecimal( [mode:string] )\n Returns a regular expression to match a hexadecimal color.\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n","reDecimalNumber":"\nreDecimalNumber( [options:Object] )\n Returns a regular expression to match a decimal number.\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n","reDirname":"\nreDirname( [platform:string] )\n Returns a regular expression to capture a path dirname.\n","reDirname.REGEXP":"\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n","reDirnamePosix":"\nreDirnamePosix()\n Returns a regular expression to capture a POSIX path dirname.\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n","reDirnameWindows":"\nreDirnameWindows()\n Returns a regular expression to capture a Windows path dirname.\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n","reduce":"\nreduce( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n thisArg:any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","reduce2d":"\nreduce2d( arr:ArrayLikeObject, initial:ArrayLikeObject, \n reducer:Function[, thisArg:any] )\n Reduces the number of dimensions by one of a two-dimensional nested array by\n applying a function against an accumulator and each element along the\n innermost dimension and returning the accumulation results as a one-\n dimensional array.\n","reduceAsync":"\nreduceAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] \n reducer:Function, done:Function )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n","reduceAsync.factory":"\nreduceAsync.factory( [options:Object,] fcn:Function )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n","reduceRight":"\nreduceRight( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n thisArg:any] )\n Applies a function against an accumulator and each element in an array while\n iterating from right to left and returns the accumulated result.\n","reduceRightAsync":"\nreduceRightAsync( collection:Array|TypedArray|Object, initial:any, \n [options:Object,] reducer:Function, done:Function )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n","reDurationString":"\nreDurationString()\n Returns a regular expression to match a duration string.\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n Regular expression to match a duration string.\n","reEOL":"\nreEOL( [options:Object] )\n Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP":"\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n","reExtendedLengthPath":"\nreExtendedLengthPath()\n Returns a regular expression to test if a string is an extended-length path.\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n","reExtname":"\nreExtname( [platform:string] )\n Returns a regular expression to capture a filename extension.\n","reExtname.REGEXP":"\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n","reExtnamePosix":"\nreExtnamePosix\n Returns a regular expression to capture a POSIX filename extension.\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n","reExtnameWindows":"\nreExtnameWindows\n Returns a regular expression to capture a Windows filename extension.\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n","reFilename":"\nreFilename( [platform:string] )\n Regular expression to split a filename.\n","reFilename.REGEXP":"\nreFilename.REGEXP\n Regular expression to split a filename.\n","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n","reFilenamePosix":"\nreFilenamePosix()\n Returns a regular expression to split a POSIX filename.\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n","reFilenameWindows":"\nreFilenameWindows()\n Returns a regular expression to split a Windows filename.\n","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n","reFromString":"\nreFromString( str:string )\n Parses a regular expression string and returns a new regular expression.\n","reFunctionName":"\nreFunctionName()\n Return a regular expression to capture a function name.\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n","regexp2json":"\nregexp2json( re:RegExp )\n Returns a JSON representation of a regular expression.\n","reim":"\nreim( z:Complex128 )\n Returns the real and imaginary components of a double-precision complex\n floating-point number.\n","reimf":"\nreimf( z:Complex64 )\n Returns the real and imaginary components of a single-precision complex\n floating-point number.\n","rejectArguments":"\nrejectArguments( fcn:Function, predicate:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n","removeFirst":"\nremoveFirst( str:string[, n:integer][, options:Object] )\n Removes the first character(s) of a `string`.\n","removeLast":"\nremoveLast( str:string[, n:integer][, options:Object] )\n Removes the last character(s) of a `string`.\n","removePunctuation":"\nremovePunctuation( str:string )\n Removes punctuation characters from a `string`.\n","removeUTF8BOM":"\nremoveUTF8BOM( str:string )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n","removeWords":"\nremoveWords( str:string, words:Array[, ignoreCase:boolean] )\n Removes all occurrences of the given words from a `string`.\n","rename":"\nrename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )\n Asynchronously renames a file.\n","rename.sync":"\nrename.sync( oldPath:string|Buffer, newPath:string|Buffer )\n Synchronously renames a file.\n","reNativeFunction":"\nreNativeFunction()\n Returns a regular expression to match a native function.\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n","reorderArguments":"\nreorderArguments( fcn:Function, indices:Array[, thisArg:any] )\n Returns a function that invokes a provided function with reordered\n arguments.\n","repeat":"\nrepeat( str:string, n:integer )\n Repeats a string `n` times and returns the concatenated result.\n","replace":"\nreplace( str:string, search:string|RegExp, newval:string|Function )\n Replaces search occurrences with a replacement string.\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n Replaces the substring before the first occurrence of a specified search\n string. \n","reRegExp":"\nreRegExp()\n Returns a regular expression to parse a regular expression string.\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n","rescape":"\nrescape( str:string )\n Escapes a regular expression string.\n","reSemVer":"\nreSemVer()\n Returns a regular expression to match a semantic version string.\n","reSemVer.REGEXP":"\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n","resolveParentPath":"\nresolveParentPath( path:string[, options:Object], clbk:Function )\n Asynchronously resolves a path by walking parent directories.\n","resolveParentPath.sync":"\nresolveParentPath.sync( path:string[, options:Object] )\n Synchronously resolves a path by walking parent directories.\n","resolveParentPathBy":"\nresolveParentPathBy( path:string[, options:Object], predicate:Function, \n clbk:Function )\n Asynchronously resolves a path according to a predicate function by walking\n parent directories.\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path:string[, options:Object], predicate:Function )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n","reUncPath":"\nreUncPath()\n Return a regular expression to parse a UNC path.\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n Returns a regular expression to match a UTF-16 surrogate pair.\n","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n Returns a regular expression to match an unpaired UTF-16 surrogate.\n","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n","reverseArguments":"\nreverseArguments( fcn:Function[, thisArg:any] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n","reverseString":"\nreverseString( str:string[, options:Object] )\n Reverses a string.\n","reviveBasePRNG":"\nreviveBasePRNG( key:string, value:any )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n","reviveBuffer":"\nreviveBuffer( key:string, value:any )\n Revives a JSON-serialized Buffer.\n","reviveComplex":"\nreviveComplex( key:string, value:any )\n Revives a JSON-serialized complex number.\n","reviveComplex64":"\nreviveComplex64( key:string, value:any )\n Revives a JSON-serialized 64-bit complex number.\n","reviveComplex128":"\nreviveComplex128( key:string, value:any )\n Revives a JSON-serialized 128-bit complex number.\n","reviveError":"\nreviveError( key:string, value:any )\n Revives a JSON-serialized error object.\n","reviveRegExp":"\nreviveRegExp( key:string, value:any )\n Revives a JSON-serialized regular expression.\n","reviveTypedArray":"\nreviveTypedArray( key:string, value:any )\n Revives a JSON-serialized typed array.\n","reWhitespace":"\nreWhitespace( [options:Object] )\n Returns a regular expression to match a white space character.\n","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n","rpad":"\nrpad( str:string, len:integer[, pad:string] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n","rtrim":"\nrtrim( str:string )\n Trims whitespace from the end of a string.\n","rtrimN":"\nrtrimN( str:string, n:integer[, chars:Array|string] )\n Trims `n` characters from the end of a string.\n","safeintmax":"\nsafeintmax( dtype:string )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n","safeintmin":"\nsafeintmin( dtype:string )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n","sample":"\nsample( x:ArrayLike[, options:Object] )\n Samples elements from an array-like object.\n","sample.factory":"\nsample.factory( [pool:ArrayLike, ][options:Object] )\n Returns a function to sample elements from an array-like object.\n","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n","scalar2array":"\nscalar2array( value:any[, dtype:string] )\n Returns a single-element array containing a provided scalar value.\n","scalar2ndarray":"\nscalar2ndarray( value:any[, options:Object] )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n","sdot":"\nsdot( x:ndarray, y:ndarray[, dim:integer] )\n Computes the dot product of two single-precision floating-point vectors.\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n","secondsInMonth":"\nsecondsInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of seconds in a month.\n","secondsInYear":"\nsecondsInYear( [value:integer|Date] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n","sentencize":"\nsentencize( str:string )\n Splits a string into an array of sentences.\n","seq2slice":"\nseq2slice( str:string, len:integer, strict:boolean )\n Converts a subsequence string to a Slice object.\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a configurable read-only property.\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj:Object, prop:string|symbol, \n getter:Function )\n Defines a configurable read-only accessor.\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj:Object, prop:string|symbol, \n getter:Function, setter:Function )\n Defines a configurable property having read-write accessors.\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n setter:Function )\n Defines a configurable write-only accessor.\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n Defines a configurable memoized read-only object property.\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n Defines a memoized read-only object property.\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )\n Defines a non-enumerable property.\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a non-enumerable read-only property.\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, \n getter:Function )\n Defines a non-enumerable read-only accessor.\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, \n getter:Function, setter:Function )\n Defines a non-enumerable property having read-write accessors.\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n setter:Function )\n Defines a non-enumerable write-only accessor.\n","setReadOnly":"\nsetReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a read-only property.\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )\n Defines a read-only accessor.\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, \n setter:Function )\n Defines a property having read-write accessors.\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )\n Defines a write-only accessor.\n","SharedArrayBuffer":"\nSharedArrayBuffer( size:integer )\n Returns a shared array buffer having a specified number of bytes.\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n","shift":"\nshift( collection:Array|TypedArray|Object )\n Removes and returns the first element of a collection.\n","shuffle":"\nshuffle( arr:ArrayLike[, options:Object] )\n Shuffles elements of an array-like object.\n","shuffle.factory":"\nshuffle.factory( [options:Object] )\n Returns a function to shuffle elements of array-like objects.\n","sizeOf":"\nsizeOf( dtype:string )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n","Slice":"\nSlice( [stop:integer|null|undefined] )\n Returns a Slice.\n\nSlice( start:integer|null|undefined, stop:integer|null|undefined[, \n step:integer|null|undefined] )\n Returns a Slice.\n","Slice.prototype.start":"\nSlice.prototype.start\n Read-only property returning the starting slice index.\n","Slice.prototype.stop":"\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n","Slice.prototype.step":"\nSlice.prototype.step\n Read-only property returning the index increment.\n","Slice.prototype.toString":"\nSlice.prototype.toString()\n Serializes a Slice as a string.\n","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n","snakecase":"\nsnakecase( str:string )\n Converts a string to snake case.\n","some":"\nsome( collection:Array|TypedArray|Object, n:number )\n Tests whether at least `n` elements in a collection are truthy.\n","someBy":"\nsomeBy( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n thisArg:any ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n","someByAsync":"\nsomeByAsync( collection:Array|TypedArray|Object, n:number, [options:Object,] \n predicate:Function, done:Function )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n","someByAsync.factory":"\nsomeByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n","someByRight":"\nsomeByRight( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n thisArg:any ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n","someByRightAsync":"\nsomeByRightAsync( collection:Array|TypedArray|Object, n:number, \n [options:Object,] predicate:Function, done:Function )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n","someInBy":"\nsomeInBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n Tests whether an object contains at least `n` properties\n (own and inherited) which pass a test\n implemented by a predicate function.\n","someOwnBy":"\nsomeOwnBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n Tests whether some `own` properties of a provided object\n satisfy a predicate function for at least `n` properties.\n","SOTU":"\nSOTU( [options:Object] )\n Returns State of the Union (SOTU) addresses.\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n","SparklineBase":"\nSparklineBase( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a Sparkline instance.\n","sparsearray2iterator":"\nsparsearray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, \n thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n","splitStream":"\nsplitStream( [options:Object] )\n Returns a transform stream which splits streamed data.\n","splitStream.factory":"\nsplitStream.factory( [options:Object] )\n Returns a function for creating transform streams for splitting streamed\n data.\n","splitStream.objectMode":"\nsplitStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n Returns US birth data from 2000 to 2014, as provided by the Social Security\n Administration.\n","sswap":"\nsswap( x:ndarray, y:ndarray[, dim:integer] )\n Interchanges two single-precision floating-point vectors.\n","Stack":"\nStack()\n Stack constructor.\n","standalone2pkg":"\nstandalone2pkg( pkg:string )\n Returns the internal package name associated with a provided standalone\n package name.\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n Returns a string array containing two or three letter abbreviations for each\n card in a standard 52-card deck.\n","startcase":"\nstartcase( str:string )\n Capitalizes the first letter of each word in an input string.\n","startsWith":"\nstartsWith( str:string, search:string[, position:integer] )\n Tests if a string starts with the characters of another string.\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n","strided.abs":"\nstrided.abs( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n offsetY:integer )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.abs2":"\nstrided.abs2( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.abs2By":"\nstrided.abs2By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n","strided.absBy":"\nstrided.absBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y`.\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n","strided.acosBy":"\nstrided.acosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.acoshBy":"\nstrided.acoshBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acotBy":"\nstrided.acotBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acothBy":"\nstrided.acothBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y`.\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acovercosBy":"\nstrided.acovercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acoversinBy":"\nstrided.acoversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.add":"\nstrided.add( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.add.ndarray":"\nstrided.add.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.addBy":"\nstrided.addBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array.\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n","strided.ahavercosBy":"\nstrided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.ahaversinBy":"\nstrided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.asinBy":"\nstrided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.asinhBy":"\nstrided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.atanBy":"\nstrided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y`.\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n","strided.atanhBy":"\nstrided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.avercosBy":"\nstrided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.aversinBy":"\nstrided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.besselj0By":"\nstrided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.besselj1By":"\nstrided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.bessely0By":"\nstrided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.bessely1By":"\nstrided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.binetBy":"\nstrided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.cbrt":"\nstrided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y`.\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n","strided.cbrtBy":"\nstrided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.ceil":"\nstrided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y`.\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.cosBy":"\nstrided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.deg2rad":"\nstrided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y`.\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.dataTypes":"\nstrided.dataTypes()\n Returns a list of strided array data types.\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array.\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n","strided.dispatch":"\nstrided.dispatch( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns a strided array function interface which performs multiple dispatch.\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns a strided array function interface which accepts a callback function\n and performs multiple dispatch.\n","strided.floor":"\nstrided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y`.\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.inv":"\nstrided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n offsetY:integer )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.mul":"\nstrided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.mulBy":"\nstrided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n","strided.ramp":"\nstrided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.rsqrt":"\nstrided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.sinBy":"\nstrided.sinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y`.\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n","strided.sqrt":"\nstrided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.sqrtBy":"\nstrided.sqrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n","strided.sub":"\nstrided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.subBy":"\nstrided.subBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n","strided.trunc":"\nstrided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y`.\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n","stridedarray2iterator":"\nstridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, \n offset:integer[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n","stridedArrayStream":"\nstridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, \n offset:integer[, options:Object] )\n Creates a readable stream from a strided array-like object.\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, \n stride:integer, offset:integer[, options:Object] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n","string2buffer":"\nstring2buffer( str:string[, encoding:string] )\n Allocates a buffer containing a provided string.\n","sub2ind":"\nsub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )\n Converts subscripts to a linear index.\n","substringAfter":"\nsubstringAfter( str:string, search:string[, fromIndex:integer] )\n Returns the part of a string after a specified substring.\n","substringAfterLast":"\nsubstringAfterLast( str:string, search:string[, fromIndex:integer] )\n Returns the part of a string after the last occurrence of a specified\n substring.\n","substringBefore":"\nsubstringBefore( str:string, search:string )\n Returns the part of a string before a specified substring.\n","substringBeforeLast":"\nsubstringBeforeLast( str:string, search:string )\n Returns the part of a string before the last occurrence of a specified\n substring.\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n","Symbol":"\nSymbol( [description:string] )\n Returns a symbol.\n","tabulate":"\ntabulate( collection:Array|TypedArray|Object )\n Generates a frequency table.\n","tabulateBy":"\ntabulateBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Generates a frequency table according to an indicator function.\n","tabulateByAsync":"\ntabulateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Generates a frequency table according to an indicator function.\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which generates a frequency table according to an\n indicator function.\n","thunk":"\nthunk( fcn:Function[, ...args:any] )\n Returns a thunk.\n","tic":"\ntic()\n Returns a high-resolution time.\n","timeit":"\ntimeit( code:string, [options:Object,] clbk:Function )\n Times a snippet.\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n","toc":"\ntoc( time:Array )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n","tokenize":"\ntokenize( str:string[, keepWhitespace:boolean] )\n Tokenizes a string.\n","transformStream":"\ntransformStream( [options:Object] )\n Returns a transform stream.\n","transformStream.factory":"\ntransformStream.factory( [options:Object] )\n Returns a function for creating transform streams.\n","transformStream.objectMode":"\ntransformStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream.\n","transformStream.ctor":"\ntransformStream.ctor( [options:Object] )\n Returns a custom transform stream constructor.\n","trim":"\ntrim( str:string )\n Trims whitespace from the beginning and end of a `string`.\n","truncate":"\ntruncate( str:string, len:integer[, ending:string] )\n Truncates a string to a specified length.\n","truncateMiddle":"\ntruncateMiddle( str:string, len:integer[, seq:string] )\n Truncates a string in the middle to a specified length.\n","trycatch":"\ntrycatch( x:Function, y:any )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n","trycatchAsync":"\ntrycatchAsync( x:Function, y:any, done:Function )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n","tryFunction":"\ntryFunction( fcn:Function[, thisArg:any] )\n Wraps a function in a try/catch block.\n","tryRequire":"\ntryRequire( id:string )\n Wraps `require` in a `try/catch` block.\n","trythen":"\ntrythen( x:Function, y:Function )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n","trythenAsync":"\ntrythenAsync( x:Function, y:Function, done:Function )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n","ttest":"\nttest( x:Array[, y:Array][, options:Object] )\n Computes a one-sample or paired Student's t test.\n","ttest2":"\nttest2( x:Array, y:Array[, options:Object] )\n Computes a two-sample Student's t test.\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n","typedarray":"\ntypedarray( [dtype:string] )\n Creates a typed array.\n\ntypedarray( length:integer[, dtype:string] )\n Returns a typed array having a specified length.\n\ntypedarray( typedarray:TypedArray[, dtype:string] )\n Creates a typed array from another typed array.\n\ntypedarray( obj:Object[, dtype:string] )\n Creates a typed array from an array-like object or iterable.\n\ntypedarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a typed array view of an ArrayBuffer.\n","typedarray2json":"\ntypedarray2json( arr:TypedArray )\n Returns a JSON representation of a typed array.\n","typedarrayCtors":"\ntypedarrayCtors( dtype:string )\n Returns a typed array constructor.\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n","typedarraypool":"\ntypedarraypool( [dtype:string] )\n Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool( length:integer[, dtype:string] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\ntypedarraypool( typedarray:TypedArray[, dtype:string] )\n Creates a pooled typed array from another typed array.\n\ntypedarraypool( obj:Object[, dtype:string] )\n Creates a pooled typed array from an array-like object.\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype:string] )\n Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool.malloc( length:integer[, dtype:string] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\ntypedarraypool.malloc( typedarray:TypedArray[, dtype:string] )\n Creates a pooled typed array from another typed array.\n\ntypedarraypool.malloc( obj:Object[, dtype:string] )\n Creates a pooled typed array from an array-like object.\n","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype:string] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\ntypedarraypool.calloc( length:integer[, dtype:string] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n","typedarraypool.free":"\ntypedarraypool.free( buf:TypedArray|ArrayBuffer )\n Frees a typed array or typed array buffer for use in a future allocation.\n","typedarraypool.clear":"\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n","typedarraypool.factory":"\ntypedarraypool.factory( [options:Object] )\n Creates a typed array pool.\n","typemax":"\ntypemax( dtype:string )\n Returns the maximum value of a specified numeric type.\n","typemin":"\ntypemin( dtype:string )\n Returns the minimum value of a specified numeric type.\n","typeOf":"\ntypeOf( value:any )\n Determines a value's type.\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\nUint8Array( length:integer )\n Returns a typed array having a specified length.\n\nUint8Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint8Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint8Array.from":"\nUint8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint8Array.of":"\nUint8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8Array.name":"\nUint8Array.name\n Typed array constructor name.\n","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n Serializes an array as a string.\n","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\nUint8ClampedArray( length:integer )\n Returns a typed array having a specified length.\n\nUint8ClampedArray( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint8ClampedArray( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint8ClampedArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n Typed array constructor name.\n","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement:number[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement:number[, \n fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\nUint16Array( length:integer )\n Returns a typed array having a specified length.\n\nUint16Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint16Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint16Array.from":"\nUint16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint16Array.of":"\nUint16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint16Array.name":"\nUint16Array.name\n Typed array constructor name.\n","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n Serializes an array as a string.\n","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\nUint32Array( length:integer )\n Returns a typed array having a specified length.\n\nUint32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint32Array.from":"\nUint32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint32Array.of":"\nUint32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint32Array.name":"\nUint32Array.name\n Typed array constructor name.\n","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","umask":"\numask( [mask:integer|string,] [options:Object] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n","uncapitalize":"\nuncapitalize( str:string )\n Lowercases the first character of a string.\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj:Object )\n Converts the first letter of each object key to lowercase.\n","uncurry":"\nuncurry( fcn:Function[, arity:integer, ][thisArg:any] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n","uncurryRight":"\nuncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline column chart instance.\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline line chart instance.\n","UnicodeSparkline":"\nUnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a Unicode sparkline instance.\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline tristate chart instance.\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline up/down chart instance.\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline win/loss chart instance.\n","unlink":"\nunlink( path:string|Buffer|integer, clbk:Function )\n Asynchronously removes a directory entry.\n","unlink.sync":"\nunlink.sync( path:string|Buffer|integer )\n Synchronously removes a directory entry.\n","unshift":"\nunshift( collection:Array|TypedArray|Object, ...items:any )\n Adds one or more elements to the beginning of a collection.\n","until":"\nuntil( predicate:Function, fcn:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","untilAsync":"\nuntilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","untilEach":"\nuntilEach( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n","untilEachRight":"\nuntilEachRight( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","unzip":"\nunzip( arr:Array[, idx:Array] )\n Unzips a zipped array (i.e., a nested array of tuples).\n","uppercase":"\nuppercase( str:string )\n Converts a string to uppercase.\n","uppercaseKeys":"\nuppercaseKeys( obj:Object )\n Converts each object key to uppercase.\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str:string )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n","vartest":"\nvartest( x:Array, y:Array[, options:Object] )\n Computes a two-sample F-test for equal variances.\n","waterfall":"\nwaterfall( fcns:Array, clbk:Function[, thisArg:any] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n","waterfall.factory":"\nwaterfall.factory( fcns:Array, clbk:Function[, thisArg:any] )\n Returns a reusable waterfall function.\n","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor:Object )\n WebAssembly memory constructor.\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta:integer )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n","whileAsync":"\nwhileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","whileEach":"\nwhileEach( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection.\n","whileEachRight":"\nwhileEachRight( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","whilst":"\nwhilst( predicate:Function, fcn:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","wilcoxon":"\nwilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )\n Computes a one-sample or paired Wilcoxon signed rank test.\n","writableProperties":"\nwritableProperties( value:any )\n Returns an array of an object's own writable property names and symbols.\n","writablePropertiesIn":"\nwritablePropertiesIn( value:any )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n","writablePropertyNames":"\nwritablePropertyNames( value:any )\n Returns an array of an object's own writable property names.\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value:any )\n Returns an array of an object's own and inherited writable property names.\n","writablePropertySymbols":"\nwritablePropertySymbols( value:any )\n Returns an array of an object's own writable symbol properties.\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited writable symbol\n properties.\n","writeFile":"\nwriteFile( file:string|Buffer|integer, data:string|Buffer[, \n options:Object|string], clbk:Function )\n Asynchronously writes data to a file.\n","writeFile.sync":"\nwriteFile.sync( file:string|Buffer|integer, data:string|Buffer[, \n options:Object|string] )\n Synchronously writes data to a file.\n","zip":"\nzip( ...arr:Array[, options:Object] )\n Generates array tuples from input arrays.\n","ztest":"\nztest( x:Array, sigma:number[, options:Object] )\n Computes a one-sample z-test.\n","ztest2":"\nztest2( x:Array, y:Array, sigmax:number, sigmay:number[, \n options:Object] )\n Computes a two-sample z-test.\n"} diff --git a/lib/node_modules/@stdlib/repl/signature/data/data.csv b/lib/node_modules/@stdlib/repl/signature/data/data.csv index 8ba467dc17f5..a324fa53caf0 100644 --- a/lib/node_modules/@stdlib/repl/signature/data/data.csv +++ b/lib/node_modules/@stdlib/repl/signature/data/data.csv @@ -2445,8 +2445,8 @@ base.strided.ssort2ins,"base.strided.ssort2ins( N, order, x, strideX, y, strideY base.strided.ssort2ins.ndarray,"base.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )" base.strided.ssort2sh,"base.strided.ssort2sh( N, order, x, strideX, y, strideY )" base.strided.ssort2sh.ndarray,"base.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )" -base.strided.ssorthp,"base.strided.ssorthp( N, order, x, stride )" -base.strided.ssorthp.ndarray,"base.strided.ssorthp.ndarray( N, order, x, stride, offset )" +base.strided.ssorthp,"base.strided.ssorthp( N, order, x, strideX )" +base.strided.ssorthp.ndarray,"base.strided.ssorthp.ndarray( N, order, x, strideX, offsetX )" base.strided.ssortins,"base.strided.ssortins( N, order, x, stride )" base.strided.ssortins.ndarray,"base.strided.ssortins.ndarray( N, order, x, stride, offset )" base.strided.ssortsh,"base.strided.ssortsh( N, order, x, stride )" diff --git a/lib/node_modules/@stdlib/repl/signature/data/data.json b/lib/node_modules/@stdlib/repl/signature/data/data.json index 3dd16b00394f..91b2e8826036 100644 --- a/lib/node_modules/@stdlib/repl/signature/data/data.json +++ b/lib/node_modules/@stdlib/repl/signature/data/data.json @@ -1 +1 @@ -[["abs","abs( x[, options] )"],["abs.assign","abs.assign( x, y )"],["acartesianPower","acartesianPower( x, n )"],["acartesianProduct","acartesianProduct( x1, x2 )"],["acartesianSquare","acartesianSquare( x )"],["acronym","acronym( str[, options] )"],["aempty","aempty( length[, dtype] )"],["aemptyLike","aemptyLike( x[, dtype] )"],["AFINN_96","AFINN_96()"],["AFINN_111","AFINN_111()"],["afull","afull( length, value[, dtype] )"],["afullLike","afullLike( x[, dtype] )"],["alias2pkg","alias2pkg( alias )"],["alias2related","alias2related( alias )"],["alias2standalone","alias2standalone( alias )"],["aliases","aliases( [namespace] )"],["allocUnsafe","allocUnsafe( size )"],["amskfilter","amskfilter( x, mask )"],["amskput","amskput( x, mask, values[, options] )"],["amskreject","amskreject( x, mask )"],["anans","anans( length[, dtype] )"],["anansLike","anansLike( x[, dtype] )"],["anova1","anova1( x, factor[, options] )"],["ANSCOMBES_QUARTET","ANSCOMBES_QUARTET()"],["any","any( collection )"],["anyBy","anyBy( collection, predicate[, thisArg ] )"],["anyByAsync","anyByAsync( collection, [options,] predicate, done )"],["anyByAsync.factory","anyByAsync.factory( [options,] predicate )"],["anyByRight","anyByRight( collection, predicate[, thisArg ] )"],["anyByRightAsync","anyByRightAsync( collection, [options,] predicate, done )"],["anyByRightAsync.factory","anyByRightAsync.factory( [options,] predicate )"],["anyInBy","anyInBy( object, predicate[, thisArg ] )"],["anyOwnBy","anyOwnBy( object, predicate[, thisArg ] )"],["aones","aones( length[, dtype] )"],["aonesLike","aonesLike( x[, dtype] )"],["aoneTo","aoneTo( n[, dtype] )"],["aoneToLike","aoneToLike( x[, dtype] )"],["APERY","APERY"],["aplace","aplace( x, mask, values[, options] )"],["append","append( collection1, collection2 )"],["aput","aput( x, indices, values[, options] )"],["ARCH","ARCH"],["argumentFunction","argumentFunction( idx )"],["ARGV","ARGV"],["array","array( [buffer,] [options] )"],["array2buffer","array2buffer( arr )"],["array2fancy","array2fancy( x[, options] )"],["array2fancy.factory","array2fancy.factory( [options] )"],["array2fancy.idx","array2fancy.idx( x[, options] )"],["array2iterator","array2iterator( src[, mapFcn[, thisArg]] )"],["array2iteratorRight","array2iteratorRight( src[, mapFcn[, thisArg]] )"],["ArrayBuffer","ArrayBuffer( size )"],["ArrayBuffer.length","ArrayBuffer.length"],["ArrayBuffer.isView","ArrayBuffer.isView( arr )"],["ArrayBuffer.prototype.byteLength","ArrayBuffer.prototype.byteLength"],["ArrayBuffer.prototype.slice","ArrayBuffer.prototype.slice( [start[, end]] )"],["arraybuffer2buffer","arraybuffer2buffer( buf[, byteOffset[, length]] )"],["arrayCtors","arrayCtors( dtype )"],["arrayDataType","arrayDataType( array )"],["arrayDataTypes","arrayDataTypes( [kind] )"],["ArrayIndex","ArrayIndex( x[, options] )"],["ArrayIndex.free","ArrayIndex.free( id )"],["ArrayIndex.get","ArrayIndex.get( id )"],["ArrayIndex.prototype.data","ArrayIndex.prototype.data"],["ArrayIndex.prototype.dtype","ArrayIndex.prototype.dtype"],["ArrayIndex.prototype.id","ArrayIndex.prototype.id"],["ArrayIndex.prototype.isCached","ArrayIndex.prototype.isCached"],["ArrayIndex.prototype.type","ArrayIndex.prototype.type"],["ArrayIndex.prototype.toString","ArrayIndex.prototype.toString()"],["ArrayIndex.prototype.toJSON","ArrayIndex.prototype.toJSON()"],["arrayMinDataType","arrayMinDataType( value )"],["arrayMostlySafeCasts","arrayMostlySafeCasts( [dtype] )"],["arrayNextDataType","arrayNextDataType( [dtype] )"],["arrayPromotionRules","arrayPromotionRules( [dtype1, dtype2] )"],["arraySafeCasts","arraySafeCasts( [dtype] )"],["arraySameKindCasts","arraySameKindCasts( [dtype] )"],["arrayShape","arrayShape( arr )"],["arrayStream","arrayStream( src[, options] )"],["arrayStream.factory","arrayStream.factory( [options] )"],["arrayStream.objectMode","arrayStream.objectMode( src[, options] )"],["arrayview2iterator","arrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )"],["arrayview2iteratorRight","arrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )"],["aslice","aslice( x[, start[, end]] )"],["AsyncIteratorSymbol","AsyncIteratorSymbol"],["atake","atake( x, indices[, options] )"],["azeros","azeros( length[, dtype] )"],["azerosLike","azerosLike( x[, dtype] )"],["azeroTo","azeroTo( n[, dtype] )"],["azeroToLike","azeroToLike( x[, dtype] )"],["bartlettTest","bartlettTest( ...x[, options] )"],["base.abs","base.abs( x )"],["base.abs2","base.abs2( x )"],["base.abs2f","base.abs2f( x )"],["base.absdiff","base.absdiff( x, y )"],["base.absf","base.absf( x )"],["base.acartesianPower","base.acartesianPower( x, n )"],["base.acartesianProduct","base.acartesianProduct( x1, x2 )"],["base.acartesianSquare","base.acartesianSquare( x )"],["base.acos","base.acos( x )"],["base.acosd","base.acosd( x )"],["base.acosdf","base.acosdf( x )"],["base.acosf","base.acosf( x )"],["base.acosh","base.acosh( x )"],["base.acot","base.acot( x )"],["base.acotd","base.acotd( x )"],["base.acotdf","base.acotdf( x )"],["base.acotf","base.acotf( x )"],["base.acoth","base.acoth( x )"],["base.acovercos","base.acovercos( x )"],["base.acoversin","base.acoversin( x )"],["base.acsc","base.acsc( x )"],["base.acscd","base.acscd( x )"],["base.acscdf","base.acscdf( x )"],["base.acscf","base.acscf( x )"],["base.acsch","base.acsch( x )"],["base.add","base.add( x, y )"],["base.add3","base.add3( x, y, z )"],["base.add4","base.add4( x, y, z, w )"],["base.add5","base.add5( x, y, z, w, u )"],["base.addf","base.addf( x, y )"],["base.afilled","base.afilled( value, len )"],["base.afilled2d","base.afilled2d( value, shape )"],["base.afilled2dBy","base.afilled2dBy( shape, clbk[, thisArg] )"],["base.afilled3d","base.afilled3d( value, shape )"],["base.afilled3dBy","base.afilled3dBy( shape, clbk[, thisArg] )"],["base.afilled4d","base.afilled4d( value, shape )"],["base.afilled4dBy","base.afilled4dBy( shape, clbk[, thisArg] )"],["base.afilled5d","base.afilled5d( value, shape )"],["base.afilled5dBy","base.afilled5dBy( shape, clbk[, thisArg] )"],["base.afilledBy","base.afilledBy( len, clbk[, thisArg] )"],["base.afillednd","base.afillednd( value, shape )"],["base.afilledndBy","base.afilledndBy( shape, clbk[, thisArg] )"],["base.afilter","base.afilter( x, predicate[, thisArg] )"],["base.afirst","base.afirst( arr )"],["base.aflatten","base.aflatten( x, shape, colexicographic )"],["base.aflatten.assign","base.aflatten.assign( x, shape, colexicographic, out, stride, offset )"],["base.aflatten2d","base.aflatten2d( x, shape, colexicographic )"],["base.aflatten2d.assign","base.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )"],["base.aflatten2dBy","base.aflatten2dBy( x, shape, colex, clbk[, thisArg] )"],["base.aflatten2dBy.assign","base.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] 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value )"],["isPositiveNumberArray.primitives","isPositiveNumberArray.primitives( value )"],["isPositiveNumberArray.objects","isPositiveNumberArray.objects( value )"],["isPositiveZero","isPositiveZero( value )"],["isPositiveZero.isPrimitive","isPositiveZero.isPrimitive( value )"],["isPositiveZero.isObject","isPositiveZero.isObject( value )"],["isPrime","isPrime( value )"],["isPrime.isPrimitive","isPrime.isPrimitive( value )"],["isPrime.isObject","isPrime.isObject( value )"],["isPrimitive","isPrimitive( value )"],["isPrimitiveArray","isPrimitiveArray( value )"],["isPRNGLike","isPRNGLike( value )"],["isProbability","isProbability( value )"],["isProbability.isPrimitive","isProbability.isPrimitive( value )"],["isProbability.isObject","isProbability.isObject( value )"],["isProbabilityArray","isProbabilityArray( value )"],["isProbabilityArray.primitives","isProbabilityArray.primitives( value )"],["isProbabilityArray.objects","isProbabilityArray.objects( value 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)"],["isUint8Array","isUint8Array( value )"],["isUint8ClampedArray","isUint8ClampedArray( value )"],["isUint16Array","isUint16Array( value )"],["isUint32Array","isUint32Array( value )"],["isUNCPath","isUNCPath( value )"],["isUndefined","isUndefined( value )"],["isUndefinedOrNull","isUndefinedOrNull( value )"],["isUnityProbabilityArray","isUnityProbabilityArray( value )"],["isUppercase","isUppercase( value )"],["isURI","isURI( value )"],["isURIError","isURIError( value )"],["isVectorLike","isVectorLike( value )"],["isWebAssemblyMemory","isWebAssemblyMemory( value )"],["isWellFormedString","isWellFormedString( str )"],["isWellFormedString.isPrimitive","isWellFormedString.isPrimitive( str )"],["isWellFormedString.isObject","isWellFormedString.isObject( str )"],["isWhitespace","isWhitespace( str )"],["isWritableProperty","isWritableProperty( value, property )"],["isWritablePropertyIn","isWritablePropertyIn( value, property )"],["isWriteOnlyProperty","isWriteOnlyProperty( value, property 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mapFcn[, thisArg]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )"],["iteratorStream","iteratorStream( iterator[, options] )"],["iteratorStream.factory","iteratorStream.factory( [options] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator[, options] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator )"],["iterAversin","iterAversin( iterator )"],["iterawgn","iterawgn( iterator, sigma[, options] )"],["iterawln","iterawln( iterator, sigma[, options] )"],["iterawun","iterawun( iterator, sigma[, options] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options] )"],["iterBartlettPulse","iterBartlettPulse( [options] )"],["iterBesselj0","iterBesselj0( iterator )"],["iterBesselj1","iterBesselj1( iterator )"],["iterBessely0","iterBessely0( iterator )"],["iterBessely1","iterBessely1( iterator )"],["iterBeta","iterBeta( x, y )"],["iterBetaln","iterBetaln( x, y )"],["iterBinet","iterBinet( iterator )"],["iterCbrt","iterCbrt( iterator )"],["iterCeil","iterCeil( iterator )"],["iterCeil2","iterCeil2( iterator )"],["iterCeil10","iterCeil10( iterator )"],["iterCompositesSeq","iterCompositesSeq( [options] )"],["iterConcat","iterConcat( iter0, ...iterator )"],["iterConstant","iterConstant( value[, options] )"],["iterContinuedFraction","iterContinuedFraction( iterator[, options] )"],["iterContinuedFractionSeq","iterContinuedFractionSeq( x[, options] )"],["iterCos","iterCos( iterator )"],["iterCosh","iterCosh( iterator )"],["iterCosineWave","iterCosineWave( [options] )"],["iterCosm1","iterCosm1( iterator )"],["iterCospi","iterCospi( iterator )"],["iterCounter","iterCounter( iterator )"],["iterCovercos","iterCovercos( iterator )"],["iterCoversin","iterCoversin( iterator )"],["iterCubesSeq","iterCubesSeq( [options] )"],["itercugmean","itercugmean( iterator )"],["itercuhmean","itercuhmean( iterator )"],["itercumax","itercumax( iterator )"],["itercumaxabs","itercumaxabs( iterator )"],["itercumean","itercumean( iterator )"],["itercumeanabs","itercumeanabs( iterator )"],["itercumeanabs2","itercumeanabs2( iterator )"],["itercumidrange","itercumidrange( iterator )"],["itercumin","itercumin( iterator )"],["itercuminabs","itercuminabs( iterator )"],["itercuprod","itercuprod( iterator )"],["itercurange","itercurange( iterator )"],["itercusum","itercusum( iterator )"],["itercusumabs","itercusumabs( iterator )"],["itercusumabs2","itercusumabs2( iterator )"],["iterDatespace","iterDatespace( start, stop[, N][, options] )"],["iterDedupe","iterDedupe( iterator[, limit] )"],["iterDedupeBy","iterDedupeBy( iterator, [limit,] fcn )"],["iterDeg2rad","iterDeg2rad( iterator )"],["iterDigamma","iterDigamma( iterator )"],["iterDiracComb","iterDiracComb( [options] )"],["iterDiracDelta","iterDiracDelta( iterator )"],["iterDivide","iterDivide( iter0, ...iterator )"],["iterDoUntilEach","iterDoUntilEach( iterator, predicate, fcn[, thisArg] )"],["iterDoWhileEach","iterDoWhileEach( iterator, predicate, fcn[, thisArg] )"],["iterEllipe","iterEllipe( iterator )"],["iterEllipk","iterEllipk( iterator )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator )"],["iterErfc","iterErfc( iterator )"],["iterErfcinv","iterErfcinv( iterator )"],["iterErfinv","iterErfinv( iterator )"],["iterEta","iterEta( iterator )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options] )"],["iterEvery","iterEvery( iterator )"],["iterEveryBy","iterEveryBy( iterator, predicate[, thisArg ] )"],["iterExp","iterExp( iterator )"],["iterExp2","iterExp2( iterator )"],["iterExp10","iterExp10( iterator )"],["iterExpit","iterExpit( iterator )"],["iterExpm1","iterExpm1( iterator )"],["iterExpm1rel","iterExpm1rel( iterator )"],["iterFactorial","iterFactorial( iterator )"],["iterFactorialln","iterFactorialln( iterator )"],["iterFactorialsSeq","iterFactorialsSeq( [options] )"],["iterFibonacciSeq","iterFibonacciSeq( [options] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options] )"],["iterFill","iterFill( iterator, value[, begin[, end]] )"],["iterFilter","iterFilter( iterator, predicate[, thisArg] )"],["iterFilterMap","iterFilterMap( iterator, fcn[, thisArg] )"],["iterFirst","iterFirst( iterator )"],["iterFlatTopPulse","iterFlatTopPulse( [options] )"],["iterFloor","iterFloor( iterator )"],["iterFloor2","iterFloor2( iterator )"],["iterFloor10","iterFloor10( iterator )"],["iterFlow","iterFlow( methods )"],["iterForEach","iterForEach( iterator, fcn[, thisArg] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options] )"],["iterFresnelc","iterFresnelc( iterator )"],["iterFresnels","iterFresnels( iterator )"],["iterGamma","iterGamma( iterator )"],["iterGamma1pm1","iterGamma1pm1( iterator )"],["iterGammaln","iterGammaln( iterator )"],["iterHacovercos","iterHacovercos( iterator )"],["iterHacoversin","iterHacoversin( iterator )"],["iterHannPulse","iterHannPulse( [options] )"],["iterHavercos","iterHavercos( iterator )"],["iterHaversin","iterHaversin( iterator )"],["iterHead","iterHead( iterator, n )"],["iterIncrspace","iterIncrspace( start, stop[, increment] )"],["iterIntegersSeq","iterIntegersSeq( [options] )"],["iterIntersection","iterIntersection( iter0, ...iterator )"],["iterIntersectionByHash","iterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )"],["iterInv","iterInv( iterator )"],["iterLanczosPulse","iterLanczosPulse( [options] )"],["iterLast","iterLast( iterator )"],["iterLength","iterLength( iterator )"],["iterLinspace","iterLinspace( start, stop[, N] )"],["iterLn","iterLn( iterator )"],["iterLog","iterLog( x, b )"],["iterLog1mexp","iterLog1mexp( iterator )"],["iterLog1p","iterLog1p( iterator )"],["iterLog1pexp","iterLog1pexp( iterator )"],["iterLog2","iterLog2( iterator )"],["iterLog10","iterLog10( iterator )"],["iterLogit","iterLogit( iterator )"],["iterLogspace","iterLogspace( start, stop[, N][, options] )"],["iterLucasSeq","iterLucasSeq( [options] )"],["iterMap","iterMap( iterator, fcn[, thisArg] )"],["iterMapN","iterMapN( iter0, ...iterator, fcn[, thisArg] )"],["itermax","itermax( iterator )"],["itermaxabs","itermaxabs( iterator )"],["itermean","itermean( iterator )"],["itermeanabs","itermeanabs( iterator )"],["itermeanabs2","itermeanabs2( iterator )"],["itermidrange","itermidrange( iterator )"],["itermin","itermin( iterator )"],["iterminabs","iterminabs( iterator )"],["itermmax","itermmax( iterator, W )"],["itermmaxabs","itermmaxabs( iterator, W )"],["itermmean","itermmean( iterator, W )"],["itermmeanabs","itermmeanabs( iterator, W )"],["itermmeanabs2","itermmeanabs2( iterator, W )"],["itermmidrange","itermmidrange( iterator, W )"],["itermmin","itermmin( iterator, W )"],["itermminabs","itermminabs( iterator, W )"],["iterMod","iterMod( iter0, ...iterator )"],["itermprod","itermprod( iterator, W )"],["itermrange","itermrange( iterator, W )"],["itermsum","itermsum( iterator, W )"],["itermsumabs","itermsumabs( iterator, W )"],["itermsumabs2","itermsumabs2( iterator, W )"],["iterMultiply","iterMultiply( iter0, ...iterator )"],["iterNegaFibonacciSeq","iterNegaFibonacciSeq( [options] )"],["iterNegaLucasSeq","iterNegaLucasSeq( [options] )"],["iterNegativeEvenIntegersSeq","iterNegativeEvenIntegersSeq( [options] )"],["iterNegativeIntegersSeq","iterNegativeIntegersSeq( [options] )"],["iterNegativeOddIntegersSeq","iterNegativeOddIntegersSeq( [options] )"],["iterNone","iterNone( iterator )"],["iterNoneBy","iterNoneBy( iterator, predicate[, thisArg ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options] )"],["iterNth","iterNth( iterator, n )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options] )"],["iterPeriodicSinc","iterPeriodicSinc( n[, options] )"],["iterPipeline","iterPipeline( iterFcn[, ...iterFcn] )"],["iterPop","iterPop( iterator[, clbk[, thisArg]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options] )"],["iterPow","iterPow( base, exponent )"],["iterPrimesSeq","iterPrimesSeq( [options] )"],["iterprod","iterprod( iterator )"],["iterPulse","iterPulse( [options] )"],["iterPush","iterPush( iterator, ...items )"],["iterRad2deg","iterRad2deg( iterator )"],["iterRamp","iterRamp( iterator )"],["iterrange","iterrange( iterator )"],["iterReject","iterReject( iterator, predicate[, thisArg] )"],["iterReplicate","iterReplicate( iterator, n )"],["iterReplicateBy","iterReplicateBy( iterator, fcn[, thisArg] )"],["iterRound","iterRound( iterator )"],["iterRound2","iterRound2( iterator )"],["iterRound10","iterRound10( iterator )"],["iterRsqrt","iterRsqrt( iterator )"],["iterSawtoothWave","iterSawtoothWave( [options] )"],["iterShift","iterShift( iterator[, clbk[, thisArg]] )"],["iterSignum","iterSignum( iterator )"],["iterSin","iterSin( iterator )"],["iterSinc","iterSinc( iterator )"],["iterSineWave","iterSineWave( [options] )"],["iterSinh","iterSinh( iterator )"],["iterSinpi","iterSinpi( iterator )"],["iterSlice","iterSlice( iterator[, begin[, end]] )"],["iterSome","iterSome( iterator, n )"],["iterSomeBy","iterSomeBy( iterator, n, predicate[, thisArg ] )"],["iterSpence","iterSpence( iterator )"],["iterSqrt","iterSqrt( iterator )"],["iterSqrt1pm1","iterSqrt1pm1( iterator )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options] )"],["iterSquaresSeq","iterSquaresSeq( [options] )"],["iterSquareWave","iterSquareWave( [options] )"],["iterstdev","iterstdev( iterator[, mean] )"],["iterStep","iterStep( start, increment[, N] 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search[, position] )"],["STOPWORDS_EN","STOPWORDS_EN()"],["strided.abs","strided.abs( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.abs.ndarray","strided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.abs2","strided.abs2( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.abs2.ndarray","strided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.abs2By","strided.abs2By( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.abs2By.ndarray","strided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.absBy","strided.absBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.absBy.ndarray","strided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.acosBy","strided.acosBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.acosBy.ndarray","strided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.acoshBy","strided.acoshBy( N, x, sx, y, sy, clbk[, thisArg] 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strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.inv","strided.inv( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.inv.ndarray","strided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.mul","strided.mul( N, dx, x, sx, dy, y, sy, dz, z, sz )"],["strided.mul.ndarray","strided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )"],["strided.mulBy","strided.mulBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )"],["strided.mulBy.ndarray","strided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )"],["strided.ramp","strided.ramp( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.ramp.ndarray","strided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.rsqrt","strided.rsqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.rsqrt.ndarray","strided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.sinBy","strided.sinBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.sinBy.ndarray","strided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.sqrt","strided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.sqrt.ndarray","strided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.sqrtBy","strided.sqrtBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.sqrtBy.ndarray","strided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.sub","strided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )"],["strided.sub.ndarray","strided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )"],["strided.subBy","strided.subBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )"],["strided.subBy.ndarray","strided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )"],["strided.trunc","strided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.trunc.ndarray","strided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, 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value )"],["isPositiveNumberArray.primitives","isPositiveNumberArray.primitives( value )"],["isPositiveNumberArray.objects","isPositiveNumberArray.objects( value )"],["isPositiveZero","isPositiveZero( value )"],["isPositiveZero.isPrimitive","isPositiveZero.isPrimitive( value )"],["isPositiveZero.isObject","isPositiveZero.isObject( value )"],["isPrime","isPrime( value )"],["isPrime.isPrimitive","isPrime.isPrimitive( value )"],["isPrime.isObject","isPrime.isObject( value )"],["isPrimitive","isPrimitive( value )"],["isPrimitiveArray","isPrimitiveArray( value )"],["isPRNGLike","isPRNGLike( value )"],["isProbability","isProbability( value )"],["isProbability.isPrimitive","isProbability.isPrimitive( value )"],["isProbability.isObject","isProbability.isObject( value )"],["isProbabilityArray","isProbabilityArray( value )"],["isProbabilityArray.primitives","isProbabilityArray.primitives( value )"],["isProbabilityArray.objects","isProbabilityArray.objects( value 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)"],["isSkewCentrosymmetricMatrix","isSkewCentrosymmetricMatrix( value )"],["isSkewPersymmetricMatrix","isSkewPersymmetricMatrix( value )"],["isSkewSymmetricMatrix","isSkewSymmetricMatrix( value )"],["isSlice","isSlice( value )"],["isSnakecase","isSnakecase( value )"],["isSquareMatrix","isSquareMatrix( value )"],["isSquareNumber","isSquareNumber( value )"],["isSquareNumber.isPrimitive","isSquareNumber.isPrimitive( value )"],["isSquareNumber.isObject","isSquareNumber.isObject( value )"],["isSquareTriangularNumber","isSquareTriangularNumber( value )"],["isSquareTriangularNumber.isPrimitive","isSquareTriangularNumber.isPrimitive( value )"],["isSquareTriangularNumber.isObject","isSquareTriangularNumber.isObject( value )"],["isStartcase","isStartcase( value )"],["isStrictEqual","isStrictEqual( a, b )"],["isString","isString( value )"],["isString.isPrimitive","isString.isPrimitive( value )"],["isString.isObject","isString.isObject( value )"],["isStringArray","isStringArray( value 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)"],["isUint8Array","isUint8Array( value )"],["isUint8ClampedArray","isUint8ClampedArray( value )"],["isUint16Array","isUint16Array( value )"],["isUint32Array","isUint32Array( value )"],["isUNCPath","isUNCPath( value )"],["isUndefined","isUndefined( value )"],["isUndefinedOrNull","isUndefinedOrNull( value )"],["isUnityProbabilityArray","isUnityProbabilityArray( value )"],["isUppercase","isUppercase( value )"],["isURI","isURI( value )"],["isURIError","isURIError( value )"],["isVectorLike","isVectorLike( value )"],["isWebAssemblyMemory","isWebAssemblyMemory( value )"],["isWellFormedString","isWellFormedString( str )"],["isWellFormedString.isPrimitive","isWellFormedString.isPrimitive( str )"],["isWellFormedString.isObject","isWellFormedString.isObject( str )"],["isWhitespace","isWhitespace( str )"],["isWritableProperty","isWritableProperty( value, property )"],["isWritablePropertyIn","isWritablePropertyIn( value, property )"],["isWriteOnlyProperty","isWriteOnlyProperty( value, property 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mapFcn[, thisArg]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )"],["iteratorStream","iteratorStream( iterator[, options] )"],["iteratorStream.factory","iteratorStream.factory( [options] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator[, options] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator )"],["iterAversin","iterAversin( iterator )"],["iterawgn","iterawgn( iterator, sigma[, options] )"],["iterawln","iterawln( iterator, sigma[, options] )"],["iterawun","iterawun( iterator, sigma[, options] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options] )"],["iterBartlettPulse","iterBartlettPulse( [options] )"],["iterBesselj0","iterBesselj0( iterator )"],["iterBesselj1","iterBesselj1( iterator )"],["iterBessely0","iterBessely0( iterator )"],["iterBessely1","iterBessely1( iterator )"],["iterBeta","iterBeta( x, y )"],["iterBetaln","iterBetaln( x, y )"],["iterBinet","iterBinet( iterator )"],["iterCbrt","iterCbrt( iterator )"],["iterCeil","iterCeil( iterator )"],["iterCeil2","iterCeil2( iterator )"],["iterCeil10","iterCeil10( iterator )"],["iterCompositesSeq","iterCompositesSeq( [options] )"],["iterConcat","iterConcat( iter0, ...iterator )"],["iterConstant","iterConstant( value[, options] )"],["iterContinuedFraction","iterContinuedFraction( iterator[, options] )"],["iterContinuedFractionSeq","iterContinuedFractionSeq( x[, options] )"],["iterCos","iterCos( iterator )"],["iterCosh","iterCosh( iterator )"],["iterCosineWave","iterCosineWave( [options] )"],["iterCosm1","iterCosm1( iterator )"],["iterCospi","iterCospi( iterator )"],["iterCounter","iterCounter( iterator )"],["iterCovercos","iterCovercos( iterator )"],["iterCoversin","iterCoversin( iterator )"],["iterCubesSeq","iterCubesSeq( [options] )"],["itercugmean","itercugmean( iterator )"],["itercuhmean","itercuhmean( iterator )"],["itercumax","itercumax( iterator )"],["itercumaxabs","itercumaxabs( iterator )"],["itercumean","itercumean( iterator )"],["itercumeanabs","itercumeanabs( iterator )"],["itercumeanabs2","itercumeanabs2( iterator )"],["itercumidrange","itercumidrange( iterator )"],["itercumin","itercumin( iterator )"],["itercuminabs","itercuminabs( iterator )"],["itercuprod","itercuprod( iterator )"],["itercurange","itercurange( iterator )"],["itercusum","itercusum( iterator )"],["itercusumabs","itercusumabs( iterator )"],["itercusumabs2","itercusumabs2( iterator )"],["iterDatespace","iterDatespace( start, stop[, N][, options] )"],["iterDedupe","iterDedupe( iterator[, limit] )"],["iterDedupeBy","iterDedupeBy( iterator, [limit,] fcn )"],["iterDeg2rad","iterDeg2rad( iterator )"],["iterDigamma","iterDigamma( iterator )"],["iterDiracComb","iterDiracComb( [options] )"],["iterDiracDelta","iterDiracDelta( iterator )"],["iterDivide","iterDivide( iter0, ...iterator )"],["iterDoUntilEach","iterDoUntilEach( iterator, predicate, fcn[, thisArg] )"],["iterDoWhileEach","iterDoWhileEach( iterator, predicate, fcn[, thisArg] )"],["iterEllipe","iterEllipe( iterator )"],["iterEllipk","iterEllipk( iterator )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator )"],["iterErfc","iterErfc( iterator )"],["iterErfcinv","iterErfcinv( iterator )"],["iterErfinv","iterErfinv( iterator )"],["iterEta","iterEta( iterator )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options] )"],["iterEvery","iterEvery( iterator )"],["iterEveryBy","iterEveryBy( iterator, predicate[, thisArg ] )"],["iterExp","iterExp( iterator )"],["iterExp2","iterExp2( iterator )"],["iterExp10","iterExp10( iterator )"],["iterExpit","iterExpit( iterator )"],["iterExpm1","iterExpm1( iterator )"],["iterExpm1rel","iterExpm1rel( iterator )"],["iterFactorial","iterFactorial( iterator )"],["iterFactorialln","iterFactorialln( iterator )"],["iterFactorialsSeq","iterFactorialsSeq( [options] )"],["iterFibonacciSeq","iterFibonacciSeq( [options] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options] )"],["iterFill","iterFill( iterator, value[, begin[, end]] )"],["iterFilter","iterFilter( iterator, predicate[, thisArg] )"],["iterFilterMap","iterFilterMap( iterator, fcn[, thisArg] )"],["iterFirst","iterFirst( iterator )"],["iterFlatTopPulse","iterFlatTopPulse( [options] )"],["iterFloor","iterFloor( iterator )"],["iterFloor2","iterFloor2( iterator )"],["iterFloor10","iterFloor10( iterator )"],["iterFlow","iterFlow( methods )"],["iterForEach","iterForEach( iterator, fcn[, thisArg] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options] )"],["iterFresnelc","iterFresnelc( iterator )"],["iterFresnels","iterFresnels( iterator )"],["iterGamma","iterGamma( iterator )"],["iterGamma1pm1","iterGamma1pm1( iterator )"],["iterGammaln","iterGammaln( iterator )"],["iterHacovercos","iterHacovercos( iterator )"],["iterHacoversin","iterHacoversin( iterator )"],["iterHannPulse","iterHannPulse( [options] )"],["iterHavercos","iterHavercos( iterator )"],["iterHaversin","iterHaversin( iterator )"],["iterHead","iterHead( iterator, n )"],["iterIncrspace","iterIncrspace( start, stop[, increment] )"],["iterIntegersSeq","iterIntegersSeq( [options] )"],["iterIntersection","iterIntersection( iter0, ...iterator )"],["iterIntersectionByHash","iterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )"],["iterInv","iterInv( iterator )"],["iterLanczosPulse","iterLanczosPulse( [options] )"],["iterLast","iterLast( iterator )"],["iterLength","iterLength( iterator )"],["iterLinspace","iterLinspace( start, stop[, N] )"],["iterLn","iterLn( iterator )"],["iterLog","iterLog( x, b )"],["iterLog1mexp","iterLog1mexp( iterator )"],["iterLog1p","iterLog1p( iterator )"],["iterLog1pexp","iterLog1pexp( iterator )"],["iterLog2","iterLog2( iterator )"],["iterLog10","iterLog10( iterator )"],["iterLogit","iterLogit( iterator )"],["iterLogspace","iterLogspace( start, stop[, N][, options] )"],["iterLucasSeq","iterLucasSeq( [options] )"],["iterMap","iterMap( iterator, fcn[, thisArg] )"],["iterMapN","iterMapN( iter0, ...iterator, fcn[, thisArg] )"],["itermax","itermax( iterator )"],["itermaxabs","itermaxabs( iterator )"],["itermean","itermean( iterator )"],["itermeanabs","itermeanabs( iterator )"],["itermeanabs2","itermeanabs2( iterator )"],["itermidrange","itermidrange( iterator )"],["itermin","itermin( iterator )"],["iterminabs","iterminabs( iterator )"],["itermmax","itermmax( iterator, W )"],["itermmaxabs","itermmaxabs( iterator, W )"],["itermmean","itermmean( iterator, W )"],["itermmeanabs","itermmeanabs( iterator, W )"],["itermmeanabs2","itermmeanabs2( iterator, W )"],["itermmidrange","itermmidrange( iterator, W )"],["itermmin","itermmin( iterator, W )"],["itermminabs","itermminabs( iterator, W )"],["iterMod","iterMod( iter0, ...iterator )"],["itermprod","itermprod( iterator, W )"],["itermrange","itermrange( iterator, W )"],["itermsum","itermsum( iterator, W )"],["itermsumabs","itermsumabs( iterator, W )"],["itermsumabs2","itermsumabs2( iterator, W )"],["iterMultiply","iterMultiply( iter0, ...iterator )"],["iterNegaFibonacciSeq","iterNegaFibonacciSeq( [options] )"],["iterNegaLucasSeq","iterNegaLucasSeq( [options] )"],["iterNegativeEvenIntegersSeq","iterNegativeEvenIntegersSeq( [options] )"],["iterNegativeIntegersSeq","iterNegativeIntegersSeq( [options] )"],["iterNegativeOddIntegersSeq","iterNegativeOddIntegersSeq( [options] )"],["iterNone","iterNone( iterator )"],["iterNoneBy","iterNoneBy( iterator, predicate[, thisArg ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options] )"],["iterNth","iterNth( iterator, n )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options] )"],["iterPeriodicSinc","iterPeriodicSinc( n[, options] )"],["iterPipeline","iterPipeline( iterFcn[, ...iterFcn] )"],["iterPop","iterPop( iterator[, clbk[, thisArg]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options] )"],["iterPow","iterPow( base, exponent )"],["iterPrimesSeq","iterPrimesSeq( [options] )"],["iterprod","iterprod( iterator )"],["iterPulse","iterPulse( [options] )"],["iterPush","iterPush( iterator, ...items )"],["iterRad2deg","iterRad2deg( iterator )"],["iterRamp","iterRamp( iterator )"],["iterrange","iterrange( iterator )"],["iterReject","iterReject( iterator, predicate[, thisArg] )"],["iterReplicate","iterReplicate( iterator, n )"],["iterReplicateBy","iterReplicateBy( iterator, fcn[, thisArg] )"],["iterRound","iterRound( iterator )"],["iterRound2","iterRound2( iterator )"],["iterRound10","iterRound10( iterator )"],["iterRsqrt","iterRsqrt( iterator )"],["iterSawtoothWave","iterSawtoothWave( [options] )"],["iterShift","iterShift( iterator[, clbk[, thisArg]] )"],["iterSignum","iterSignum( iterator )"],["iterSin","iterSin( iterator )"],["iterSinc","iterSinc( iterator )"],["iterSineWave","iterSineWave( [options] )"],["iterSinh","iterSinh( iterator )"],["iterSinpi","iterSinpi( iterator )"],["iterSlice","iterSlice( iterator[, begin[, end]] )"],["iterSome","iterSome( iterator, n )"],["iterSomeBy","iterSomeBy( iterator, n, predicate[, thisArg ] )"],["iterSpence","iterSpence( iterator )"],["iterSqrt","iterSqrt( iterator )"],["iterSqrt1pm1","iterSqrt1pm1( iterator )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options] )"],["iterSquaresSeq","iterSquaresSeq( [options] )"],["iterSquareWave","iterSquareWave( [options] )"],["iterstdev","iterstdev( iterator[, mean] )"],["iterStep","iterStep( start, increment[, N] 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search[, position] )"],["STOPWORDS_EN","STOPWORDS_EN()"],["strided.abs","strided.abs( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.abs.ndarray","strided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.abs2","strided.abs2( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.abs2.ndarray","strided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.abs2By","strided.abs2By( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.abs2By.ndarray","strided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.absBy","strided.absBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.absBy.ndarray","strided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.acosBy","strided.acosBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.acosBy.ndarray","strided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.acoshBy","strided.acoshBy( N, x, sx, y, sy, clbk[, thisArg] 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strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.inv","strided.inv( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.inv.ndarray","strided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.mul","strided.mul( N, dx, x, sx, dy, y, sy, dz, z, sz )"],["strided.mul.ndarray","strided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )"],["strided.mulBy","strided.mulBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )"],["strided.mulBy.ndarray","strided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )"],["strided.ramp","strided.ramp( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.ramp.ndarray","strided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.rsqrt","strided.rsqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.rsqrt.ndarray","strided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.sinBy","strided.sinBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.sinBy.ndarray","strided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.sqrt","strided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.sqrt.ndarray","strided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.sqrtBy","strided.sqrtBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.sqrtBy.ndarray","strided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.sub","strided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )"],["strided.sub.ndarray","strided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )"],["strided.subBy","strided.subBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )"],["strided.subBy.ndarray","strided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )"],["strided.trunc","strided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.trunc.ndarray","strided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, 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)"],["Uint8Array.BYTES_PER_ELEMENT","Uint8Array.BYTES_PER_ELEMENT"],["Uint8Array.name","Uint8Array.name"],["Uint8Array.prototype.buffer","Uint8Array.prototype.buffer"],["Uint8Array.prototype.byteLength","Uint8Array.prototype.byteLength"],["Uint8Array.prototype.byteOffset","Uint8Array.prototype.byteOffset"],["Uint8Array.prototype.BYTES_PER_ELEMENT","Uint8Array.prototype.BYTES_PER_ELEMENT"],["Uint8Array.prototype.length","Uint8Array.prototype.length"],["Uint8Array.prototype.copyWithin","Uint8Array.prototype.copyWithin( target, start[, end] )"],["Uint8Array.prototype.entries","Uint8Array.prototype.entries()"],["Uint8Array.prototype.every","Uint8Array.prototype.every( predicate[, thisArg] )"],["Uint8Array.prototype.fill","Uint8Array.prototype.fill( value[, start[, end]] )"],["Uint8Array.prototype.filter","Uint8Array.prototype.filter( predicate[, thisArg] )"],["Uint8Array.prototype.find","Uint8Array.prototype.find( predicate[, thisArg] )"],["Uint8Array.prototype.findIndex","Uint8Array.prototype.findIndex( predicate[, thisArg] )"],["Uint8Array.prototype.forEach","Uint8Array.prototype.forEach( fcn[, thisArg] )"],["Uint8Array.prototype.includes","Uint8Array.prototype.includes( searchElement[, fromIndex] )"],["Uint8Array.prototype.indexOf","Uint8Array.prototype.indexOf( searchElement[, fromIndex] )"],["Uint8Array.prototype.join","Uint8Array.prototype.join( [separator] )"],["Uint8Array.prototype.keys","Uint8Array.prototype.keys()"],["Uint8Array.prototype.lastIndexOf","Uint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint8Array.prototype.map","Uint8Array.prototype.map( fcn[, thisArg] )"],["Uint8Array.prototype.reduce","Uint8Array.prototype.reduce( fcn[, initialValue] )"],["Uint8Array.prototype.reduceRight","Uint8Array.prototype.reduceRight( fcn[, initialValue] )"],["Uint8Array.prototype.reverse","Uint8Array.prototype.reverse()"],["Uint8Array.prototype.set","Uint8Array.prototype.set( arr[, offset] )"],["Uint8Array.prototype.slice","Uint8Array.prototype.slice( [begin[, end]] )"],["Uint8Array.prototype.some","Uint8Array.prototype.some( predicate[, thisArg] )"],["Uint8Array.prototype.sort","Uint8Array.prototype.sort( [compareFunction] )"],["Uint8Array.prototype.subarray","Uint8Array.prototype.subarray( [begin[, end]] )"],["Uint8Array.prototype.toLocaleString","Uint8Array.prototype.toLocaleString( [locales[, options]] )"],["Uint8Array.prototype.toString","Uint8Array.prototype.toString()"],["Uint8Array.prototype.values","Uint8Array.prototype.values()"],["Uint8ClampedArray","Uint8ClampedArray()"],["Uint8ClampedArray","Uint8ClampedArray( length )"],["Uint8ClampedArray","Uint8ClampedArray( typedarray )"],["Uint8ClampedArray","Uint8ClampedArray( obj )"],["Uint8ClampedArray","Uint8ClampedArray( buffer[, byteOffset[, length]] )"],["Uint8ClampedArray.from","Uint8ClampedArray.from( src[, map[, thisArg]] )"],["Uint8ClampedArray.of","Uint8ClampedArray.of( element0[, element1[, ...elementN]] )"],["Uint8ClampedArray.BYTES_PER_ELEMENT","Uint8ClampedArray.BYTES_PER_ELEMENT"],["Uint8ClampedArray.name","Uint8ClampedArray.name"],["Uint8ClampedArray.prototype.buffer","Uint8ClampedArray.prototype.buffer"],["Uint8ClampedArray.prototype.byteLength","Uint8ClampedArray.prototype.byteLength"],["Uint8ClampedArray.prototype.byteOffset","Uint8ClampedArray.prototype.byteOffset"],["Uint8ClampedArray.prototype.BYTES_PER_ELEMENT","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT"],["Uint8ClampedArray.prototype.length","Uint8ClampedArray.prototype.length"],["Uint8ClampedArray.prototype.copyWithin","Uint8ClampedArray.prototype.copyWithin( target, start[, end] )"],["Uint8ClampedArray.prototype.entries","Uint8ClampedArray.prototype.entries()"],["Uint8ClampedArray.prototype.every","Uint8ClampedArray.prototype.every( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.fill","Uint8ClampedArray.prototype.fill( value[, start[, end]] )"],["Uint8ClampedArray.prototype.filter","Uint8ClampedArray.prototype.filter( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.find","Uint8ClampedArray.prototype.find( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.findIndex","Uint8ClampedArray.prototype.findIndex( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.forEach","Uint8ClampedArray.prototype.forEach( fcn[, thisArg] )"],["Uint8ClampedArray.prototype.includes","Uint8ClampedArray.prototype.includes( searchElement[, fromIndex] )"],["Uint8ClampedArray.prototype.indexOf","Uint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )"],["Uint8ClampedArray.prototype.join","Uint8ClampedArray.prototype.join( [separator] )"],["Uint8ClampedArray.prototype.keys","Uint8ClampedArray.prototype.keys()"],["Uint8ClampedArray.prototype.lastIndexOf","Uint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint8ClampedArray.prototype.map","Uint8ClampedArray.prototype.map( fcn[, thisArg] )"],["Uint8ClampedArray.prototype.reduce","Uint8ClampedArray.prototype.reduce( fcn[, initialValue] )"],["Uint8ClampedArray.prototype.reduceRight","Uint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )"],["Uint8ClampedArray.prototype.reverse","Uint8ClampedArray.prototype.reverse()"],["Uint8ClampedArray.prototype.set","Uint8ClampedArray.prototype.set( arr[, offset] )"],["Uint8ClampedArray.prototype.slice","Uint8ClampedArray.prototype.slice( [begin[, end]] )"],["Uint8ClampedArray.prototype.some","Uint8ClampedArray.prototype.some( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.sort","Uint8ClampedArray.prototype.sort( [compareFunction] )"],["Uint8ClampedArray.prototype.subarray","Uint8ClampedArray.prototype.subarray( [begin[, end]] )"],["Uint8ClampedArray.prototype.toLocaleString","Uint8ClampedArray.prototype.toLocaleString( [locales[, options]] )"],["Uint8ClampedArray.prototype.toString","Uint8ClampedArray.prototype.toString()"],["Uint8ClampedArray.prototype.values","Uint8ClampedArray.prototype.values()"],["UINT16_MAX","UINT16_MAX"],["UINT16_NUM_BYTES","UINT16_NUM_BYTES"],["Uint16Array","Uint16Array()"],["Uint16Array","Uint16Array( length )"],["Uint16Array","Uint16Array( typedarray )"],["Uint16Array","Uint16Array( obj )"],["Uint16Array","Uint16Array( buffer[, byteOffset[, length]] )"],["Uint16Array.from","Uint16Array.from( src[, map[, thisArg]] )"],["Uint16Array.of","Uint16Array.of( element0[, element1[, ...elementN]] )"],["Uint16Array.BYTES_PER_ELEMENT","Uint16Array.BYTES_PER_ELEMENT"],["Uint16Array.name","Uint16Array.name"],["Uint16Array.prototype.buffer","Uint16Array.prototype.buffer"],["Uint16Array.prototype.byteLength","Uint16Array.prototype.byteLength"],["Uint16Array.prototype.byteOffset","Uint16Array.prototype.byteOffset"],["Uint16Array.prototype.BYTES_PER_ELEMENT","Uint16Array.prototype.BYTES_PER_ELEMENT"],["Uint16Array.prototype.length","Uint16Array.prototype.length"],["Uint16Array.prototype.copyWithin","Uint16Array.prototype.copyWithin( target, start[, end] )"],["Uint16Array.prototype.entries","Uint16Array.prototype.entries()"],["Uint16Array.prototype.every","Uint16Array.prototype.every( predicate[, thisArg] )"],["Uint16Array.prototype.fill","Uint16Array.prototype.fill( value[, start[, end]] )"],["Uint16Array.prototype.filter","Uint16Array.prototype.filter( predicate[, thisArg] )"],["Uint16Array.prototype.find","Uint16Array.prototype.find( predicate[, thisArg] )"],["Uint16Array.prototype.findIndex","Uint16Array.prototype.findIndex( predicate[, thisArg] )"],["Uint16Array.prototype.forEach","Uint16Array.prototype.forEach( fcn[, thisArg] )"],["Uint16Array.prototype.includes","Uint16Array.prototype.includes( searchElement[, fromIndex] )"],["Uint16Array.prototype.indexOf","Uint16Array.prototype.indexOf( searchElement[, fromIndex] )"],["Uint16Array.prototype.join","Uint16Array.prototype.join( [separator] )"],["Uint16Array.prototype.keys","Uint16Array.prototype.keys()"],["Uint16Array.prototype.lastIndexOf","Uint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint16Array.prototype.map","Uint16Array.prototype.map( fcn[, thisArg] )"],["Uint16Array.prototype.reduce","Uint16Array.prototype.reduce( fcn[, initialValue] )"],["Uint16Array.prototype.reduceRight","Uint16Array.prototype.reduceRight( fcn[, initialValue] )"],["Uint16Array.prototype.reverse","Uint16Array.prototype.reverse()"],["Uint16Array.prototype.set","Uint16Array.prototype.set( arr[, offset] )"],["Uint16Array.prototype.slice","Uint16Array.prototype.slice( [begin[, end]] )"],["Uint16Array.prototype.some","Uint16Array.prototype.some( predicate[, thisArg] )"],["Uint16Array.prototype.sort","Uint16Array.prototype.sort( [compareFunction] )"],["Uint16Array.prototype.subarray","Uint16Array.prototype.subarray( [begin[, end]] )"],["Uint16Array.prototype.toLocaleString","Uint16Array.prototype.toLocaleString( [locales[, options]] )"],["Uint16Array.prototype.toString","Uint16Array.prototype.toString()"],["Uint16Array.prototype.values","Uint16Array.prototype.values()"],["UINT32_MAX","UINT32_MAX"],["UINT32_NUM_BYTES","UINT32_NUM_BYTES"],["Uint32Array","Uint32Array()"],["Uint32Array","Uint32Array( length )"],["Uint32Array","Uint32Array( typedarray )"],["Uint32Array","Uint32Array( obj )"],["Uint32Array","Uint32Array( buffer[, byteOffset[, length]] )"],["Uint32Array.from","Uint32Array.from( src[, map[, thisArg]] )"],["Uint32Array.of","Uint32Array.of( element0[, element1[, ...elementN]] )"],["Uint32Array.BYTES_PER_ELEMENT","Uint32Array.BYTES_PER_ELEMENT"],["Uint32Array.name","Uint32Array.name"],["Uint32Array.prototype.buffer","Uint32Array.prototype.buffer"],["Uint32Array.prototype.byteLength","Uint32Array.prototype.byteLength"],["Uint32Array.prototype.byteOffset","Uint32Array.prototype.byteOffset"],["Uint32Array.prototype.BYTES_PER_ELEMENT","Uint32Array.prototype.BYTES_PER_ELEMENT"],["Uint32Array.prototype.length","Uint32Array.prototype.length"],["Uint32Array.prototype.copyWithin","Uint32Array.prototype.copyWithin( target, start[, end] )"],["Uint32Array.prototype.entries","Uint32Array.prototype.entries()"],["Uint32Array.prototype.every","Uint32Array.prototype.every( predicate[, thisArg] )"],["Uint32Array.prototype.fill","Uint32Array.prototype.fill( value[, start[, end]] )"],["Uint32Array.prototype.filter","Uint32Array.prototype.filter( predicate[, thisArg] )"],["Uint32Array.prototype.find","Uint32Array.prototype.find( predicate[, thisArg] )"],["Uint32Array.prototype.findIndex","Uint32Array.prototype.findIndex( predicate[, thisArg] )"],["Uint32Array.prototype.forEach","Uint32Array.prototype.forEach( fcn[, thisArg] )"],["Uint32Array.prototype.includes","Uint32Array.prototype.includes( searchElement[, fromIndex] )"],["Uint32Array.prototype.indexOf","Uint32Array.prototype.indexOf( searchElement[, fromIndex] )"],["Uint32Array.prototype.join","Uint32Array.prototype.join( [separator] )"],["Uint32Array.prototype.keys","Uint32Array.prototype.keys()"],["Uint32Array.prototype.lastIndexOf","Uint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint32Array.prototype.map","Uint32Array.prototype.map( fcn[, thisArg] )"],["Uint32Array.prototype.reduce","Uint32Array.prototype.reduce( fcn[, initialValue] )"],["Uint32Array.prototype.reduceRight","Uint32Array.prototype.reduceRight( fcn[, initialValue] )"],["Uint32Array.prototype.reverse","Uint32Array.prototype.reverse()"],["Uint32Array.prototype.set","Uint32Array.prototype.set( arr[, offset] )"],["Uint32Array.prototype.slice","Uint32Array.prototype.slice( [begin[, end]] )"],["Uint32Array.prototype.some","Uint32Array.prototype.some( predicate[, thisArg] )"],["Uint32Array.prototype.sort","Uint32Array.prototype.sort( [compareFunction] )"],["Uint32Array.prototype.subarray","Uint32Array.prototype.subarray( [begin[, end]] )"],["Uint32Array.prototype.toLocaleString","Uint32Array.prototype.toLocaleString( [locales[, options]] )"],["Uint32Array.prototype.toString","Uint32Array.prototype.toString()"],["Uint32Array.prototype.values","Uint32Array.prototype.values()"],["umask","umask( [mask,] [options] )"],["uncapitalize","uncapitalize( str )"],["uncapitalizeKeys","uncapitalizeKeys( obj )"],["uncurry","uncurry( fcn[, arity, ][thisArg] )"],["uncurryRight","uncurryRight( fcn[, arity, ][thisArg] )"],["UNICODE_MAX","UNICODE_MAX"],["UNICODE_MAX_BMP","UNICODE_MAX_BMP"],["UnicodeColumnChartSparkline","UnicodeColumnChartSparkline( [data,] [options] )"],["UnicodeLineChartSparkline","UnicodeLineChartSparkline( [data,] [options] )"],["UnicodeSparkline","UnicodeSparkline( [data,] [options] )"],["UnicodeTristateChartSparkline","UnicodeTristateChartSparkline( [data,] [options] )"],["UnicodeUpDownChartSparkline","UnicodeUpDownChartSparkline( [data,] [options] )"],["UnicodeWinLossChartSparkline","UnicodeWinLossChartSparkline( [data,] [options] )"],["unlink","unlink( path, clbk )"],["unlink.sync","unlink.sync( path )"],["unshift","unshift( collection, ...items )"],["until","until( predicate, fcn[, thisArg] )"],["untilAsync","untilAsync( predicate, fcn, done[, thisArg] )"],["untilEach","untilEach( collection, predicate, fcn[, thisArg] )"],["untilEachRight","untilEachRight( collection, predicate, fcn[, thisArg] )"],["unzip","unzip( arr[, idx] )"],["uppercase","uppercase( str )"],["uppercaseKeys","uppercaseKeys( obj )"],["US_STATES_ABBR","US_STATES_ABBR()"],["US_STATES_CAPITALS","US_STATES_CAPITALS()"],["US_STATES_CAPITALS_NAMES","US_STATES_CAPITALS_NAMES()"],["US_STATES_NAMES","US_STATES_NAMES()"],["US_STATES_NAMES_CAPITALS","US_STATES_NAMES_CAPITALS()"],["utf16ToUTF8Array","utf16ToUTF8Array( str )"],["vartest","vartest( x, y[, options] )"],["waterfall","waterfall( fcns, clbk[, thisArg] )"],["waterfall.factory","waterfall.factory( fcns, clbk[, thisArg] )"],["WebAssemblyMemory","WebAssemblyMemory( descriptor )"],["WebAssemblyMemory.prototype.buffer","WebAssemblyMemory.prototype.buffer"],["WebAssemblyMemory.prototype.grow","WebAssemblyMemory.prototype.grow( delta )"],["whileAsync","whileAsync( predicate, fcn, done[, thisArg] )"],["whileEach","whileEach( collection, predicate, fcn[, thisArg] )"],["whileEachRight","whileEachRight( collection, predicate, fcn[, thisArg] )"],["whilst","whilst( predicate, fcn[, thisArg] )"],["wilcoxon","wilcoxon( x[, y][, options] )"],["writableProperties","writableProperties( value )"],["writablePropertiesIn","writablePropertiesIn( value )"],["writablePropertyNames","writablePropertyNames( value )"],["writablePropertyNamesIn","writablePropertyNamesIn( value )"],["writablePropertySymbols","writablePropertySymbols( value )"],["writablePropertySymbolsIn","writablePropertySymbolsIn( value )"],["writeFile","writeFile( file, data[, options], clbk )"],["writeFile.sync","writeFile.sync( file, data[, options] )"],["zip","zip( ...arr[, options] )"],["ztest","ztest( x, sigma[, options] )"],["ztest2","ztest2( x, y, sigmax, sigmay[, options] )"]] diff --git a/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv b/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv index a3289f061e17..f70032b431a3 100644 --- a/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv +++ b/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv @@ -2445,8 +2445,8 @@ base.strided.ssort2ins,"base.strided.ssort2ins( N:integer, order:number, x:Float base.strided.ssort2ins.ndarray,"base.strided.ssort2ins.ndarray( N:integer, order:number, x:Float32Array, strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )" base.strided.ssort2sh,"base.strided.ssort2sh( N:integer, order:number, x:Float32Array, strideX:integer, y:Float32Array, strideY:integer )" base.strided.ssort2sh.ndarray,"base.strided.ssort2sh.ndarray( N:integer, order:number, x:Float32Array, strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )" -base.strided.ssorthp,"base.strided.ssorthp( N:integer, order:number, x:Float32Array, stride:integer )" -base.strided.ssorthp.ndarray,"base.strided.ssorthp.ndarray( N:integer, order:number, x:Float32Array, stride:integer, offset:integer )" +base.strided.ssorthp,"base.strided.ssorthp( N:integer, order:number, x:Float32Array, strideX:integer )" +base.strided.ssorthp.ndarray,"base.strided.ssorthp.ndarray( N:integer, order:number, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.ssortins,"base.strided.ssortins( N:integer, order:number, x:Float32Array, stride:integer )" base.strided.ssortins.ndarray,"base.strided.ssortins.ndarray( N:integer, order:number, x:Float32Array, stride:integer, offset:integer )" base.strided.ssortsh,"base.strided.ssortsh( N:integer, order:number, x:Float32Array, stride:integer )" @@ -2743,7 +2743,7 @@ Complex128Array.prototype.byteOffset,"Complex128Array.prototype.byteOffset" Complex128Array.prototype.BYTES_PER_ELEMENT,"Complex128Array.prototype.BYTES_PER_ELEMENT" Complex128Array.prototype.length,"Complex128Array.prototype.length" Complex128Array.prototype.at,"Complex128Array.prototype.at( i:integer )" -Complex128Array.prototype.copyWithin,"Complex128Array.prototype.copyWithin( target, start[, end] )" +Complex128Array.prototype.copyWithin,"Complex128Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )" Complex128Array.prototype.entries,"Complex128Array.prototype.entries()" Complex128Array.prototype.every,"Complex128Array.prototype.every( predicate:Function[, thisArg:Any] )" Complex128Array.prototype.fill,"Complex128Array.prototype.fill( value:Complex128[, start:integer[, end:integer]] )" @@ -2765,15 +2765,15 @@ Complex128Array.prototype.reduceRight,"Complex128Array.prototype.reduceRight( re Complex128Array.prototype.reverse,"Complex128Array.prototype.reverse()" Complex128Array.prototype.set,"Complex128Array.prototype.set( z:Complex128|Complex128Array|ArrayLikeObject[, i:integer] )" Complex128Array.prototype.slice,"Complex128Array.prototype.slice( [start:integer[, end:integer]] )" -Complex128Array.prototype.some,"Complex128Array.prototype.some( predicate[, thisArg] )" +Complex128Array.prototype.some,"Complex128Array.prototype.some( predicate:Function[, thisArg:Any] )" Complex128Array.prototype.sort,"Complex128Array.prototype.sort( compareFunction:Function )" Complex128Array.prototype.subarray,"Complex128Array.prototype.subarray( [begin:integer[, end:integer]] )" -Complex128Array.prototype.toLocaleString,"Complex128Array.prototype.toLocaleString( [locales[, options]] )" +Complex128Array.prototype.toLocaleString,"Complex128Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )" Complex128Array.prototype.toReversed,"Complex128Array.prototype.toReversed()" Complex128Array.prototype.toSorted,"Complex128Array.prototype.toSorted( compareFcn:Function )" Complex128Array.prototype.toString,"Complex128Array.prototype.toString()" Complex128Array.prototype.values,"Complex128Array.prototype.values()" -Complex128Array.prototype.with,"Complex128Array.prototype.with( index, value )" +Complex128Array.prototype.with,"Complex128Array.prototype.with( index:integer, value:Complex128 )" complexarray,"complexarray( [dtype:string] )" complexarray,"complexarray( length:integer[, dtype:string] )" complexarray,"complexarray( complexarray:ComplexArray[, dtype:string] )" diff --git a/lib/node_modules/@stdlib/repl/typed-signature/data/data.json b/lib/node_modules/@stdlib/repl/typed-signature/data/data.json index 7b1d388856cc..ddbf81e3ffcd 100644 --- a/lib/node_modules/@stdlib/repl/typed-signature/data/data.json +++ b/lib/node_modules/@stdlib/repl/typed-signature/data/data.json @@ -1 +1 @@ -[["abs","abs( x:ndarray[, options:Object] )"],["abs.assign","abs.assign( x:ndarray, y:ndarray )"],["acartesianPower","acartesianPower( x:ArrayLikeObject, n:integer )"],["acartesianProduct","acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )"],["acartesianSquare","acartesianSquare( x:ArrayLikeObject )"],["acronym","acronym( str:string[, options:Object] )"],["aempty","aempty( length:integer[, dtype:string] )"],["aemptyLike","aemptyLike( x:TypedArray|Array[, dtype:string] )"],["AFINN_96","AFINN_96()"],["AFINN_111","AFINN_111()"],["afull","afull( length:integer, value:any[, dtype:string] )"],["afullLike","afullLike( x:TypedArray|Array[, dtype:string] )"],["alias2pkg","alias2pkg( alias:string )"],["alias2related","alias2related( alias:string )"],["alias2standalone","alias2standalone( alias:string )"],["aliases","aliases( [namespace:string] )"],["allocUnsafe","allocUnsafe( size:integer )"],["amskfilter","amskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )"],["amskput","amskput( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, options:Object] )"],["amskreject","amskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )"],["anans","anans( length:integer[, dtype:string] )"],["anansLike","anansLike( x:TypedArray|Array[, dtype:string] )"],["anova1","anova1( x:Array, factor:Array[, options:Object] )"],["ANSCOMBES_QUARTET","ANSCOMBES_QUARTET()"],["any","any( collection:Array|TypedArray|Object )"],["anyBy","anyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )"],["anyByAsync","anyByAsync( collection:Array|TypedArray|Object, [options:Object,] predicate:Function, done:Function )"],["anyByAsync.factory","anyByAsync.factory( [options:Object,] predicate:Function )"],["anyByRight","anyByRight( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )"],["anyByRightAsync","anyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] predicate:Function, done:Function )"],["anyByRightAsync.factory","anyByRightAsync.factory( [options:Object,] predicate:Function )"],["anyInBy","anyInBy( object:Object, predicate:Function[, thisArg:any ] )"],["anyOwnBy","anyOwnBy( object:Object, predicate:Function[, thisArg:any ] )"],["aones","aones( length:integer[, dtype:string] )"],["aonesLike","aonesLike( x:TypedArray|Array[, dtype:string] )"],["aoneTo","aoneTo( n:integer[, dtype:string] )"],["aoneToLike","aoneToLike( x:TypedArray|Array[, dtype:string] )"],["APERY","APERY"],["aplace","aplace( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, options:Object] )"],["append","append( collection1:Array|TypedArray|Object, collection2:Array|TypedArray|Object )"],["aput","aput( x:ArrayLikeObject, indices:ArrayLikeObject, values:ArrayLikeObject[, options:Object] )"],["ARCH","ARCH"],["argumentFunction","argumentFunction( idx:integer )"],["ARGV","ARGV"],["array","array( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )"],["array2buffer","array2buffer( arr:Array )"],["array2fancy","array2fancy( x:Array|TypedArray|Object[, options:Object] )"],["array2fancy.factory","array2fancy.factory( [options:Object] )"],["array2fancy.idx","array2fancy.idx( x:Array|TypedArray|Object[, options:Object] )"],["array2iterator","array2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )"],["array2iteratorRight","array2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )"],["ArrayBuffer","ArrayBuffer( size:integer )"],["ArrayBuffer.length","ArrayBuffer.length"],["ArrayBuffer.isView","ArrayBuffer.isView( arr:any )"],["ArrayBuffer.prototype.byteLength","ArrayBuffer.prototype.byteLength"],["ArrayBuffer.prototype.slice","ArrayBuffer.prototype.slice( [start:integer[, end:integer]] )"],["arraybuffer2buffer","arraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["arrayCtors","arrayCtors( dtype:string )"],["arrayDataType","arrayDataType( array:any )"],["arrayDataTypes","arrayDataTypes( [kind:string] )"],["ArrayIndex","ArrayIndex( x:Array|TypedArray|Object[, options:Object] )"],["ArrayIndex.free","ArrayIndex.free( id:string )"],["ArrayIndex.get","ArrayIndex.get( id:string 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)"],["base.strided.dmeanstdevpn.ndarray","base.strided.dmeanstdevpn.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )"],["base.strided.dmeanvar","base.strided.dmeanvar( N:integer, c:number, x:Float64Array, strideX:integer, out:Float64Array, strideOut:integer )"],["base.strided.dmeanvar.ndarray","base.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )"],["base.strided.dmeanvarpn","base.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, out:Float64Array, strideOut:integer )"],["base.strided.dmeanvarpn.ndarray","base.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )"],["base.strided.dmeanwd","base.strided.dmeanwd( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmeanwd.ndarray","base.strided.dmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dmediansorted","base.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmediansorted.ndarray","base.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dmidrange","base.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmidrange.ndarray","base.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dmin","base.strided.dmin( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmin.ndarray","base.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dminabs","base.strided.dminabs( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dminabs.ndarray","base.strided.dminabs.ndarray( N:integer, x:Float64Array, 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)"],["base.strided.dmskcbrt","base.strided.dmskcbrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskcbrt.ndarray","base.strided.dmskcbrt.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )"],["base.strided.dmskceil","base.strided.dmskceil( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskceil.ndarray","base.strided.dmskceil.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )"],["base.strided.dmskdeg2rad","base.strided.dmskdeg2rad( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskdeg2rad.ndarray","base.strided.dmskdeg2rad.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, 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)"],["base.strided.smeanpw.ndarray","base.strided.smeanpw.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smeanwd","base.strided.smeanwd( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smeanwd.ndarray","base.strided.smeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smediansorted","base.strided.smediansorted( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smediansorted.ndarray","base.strided.smediansorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smidrange","base.strided.smidrange( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smidrange.ndarray","base.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smin","base.strided.smin( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smin.ndarray","base.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.sminabs","base.strided.sminabs( N:integer, x:Float32Array, strideX:integer )"],["base.strided.sminabs.ndarray","base.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.sminsorted","base.strided.sminsorted( N:integer, x:Float32Array, strideX:integer )"],["base.strided.sminsorted.ndarray","base.strided.sminsorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smskabs","base.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskabs.ndarray","base.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskabs2","base.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskabs2.ndarray","base.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskcbrt","base.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskcbrt.ndarray","base.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskceil","base.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskceil.ndarray","base.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskdeg2rad","base.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskdeg2rad.ndarray","base.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskfloor","base.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskfloor.ndarray","base.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskinv","base.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskinv.ndarray","base.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskmap","base.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer, fcn:Function )"],["base.strided.smskmap.ndarray","base.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer, fcn:Function )"],["base.strided.smskmap2","base.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, fcn:Function )"],["base.strided.smskmap2.ndarray","base.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )"],["base.strided.smskmax","base.strided.smskmax( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskmax.ndarray","base.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskmin","base.strided.smskmin( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskmin.ndarray","base.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskramp","base.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskramp.ndarray","base.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskrange","base.strided.smskrange( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskrange.ndarray","base.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskrsqrt","base.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskrsqrt.ndarray","base.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smsksqrt","base.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smsksqrt.ndarray","base.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smsktrunc","base.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smsktrunc.ndarray","base.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.snanmax","base.strided.snanmax( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmax.ndarray","base.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmaxabs","base.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmaxabs.ndarray","base.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmean","base.strided.snanmean( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmean.ndarray","base.strided.snanmean.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmeanors","base.strided.snanmeanors( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmeanors.ndarray","base.strided.snanmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer 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x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.snanmskmax.ndarray","base.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.snanmskmin","base.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.snanmskmin.ndarray","base.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.snanmskrange","base.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.snanmskrange.ndarray","base.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.snanrange","base.strided.snanrange( N:integer, 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)"],["isNonPositiveFinite.isObject","isNonPositiveFinite.isObject( value:any )"],["isNonPositiveInteger","isNonPositiveInteger( value:any )"],["isNonPositiveInteger.isPrimitive","isNonPositiveInteger.isPrimitive( value:any )"],["isNonPositiveInteger.isObject","isNonPositiveInteger.isObject( value:any )"],["isNonPositiveIntegerArray","isNonPositiveIntegerArray( value:any )"],["isNonPositiveIntegerArray.primitives","isNonPositiveIntegerArray.primitives( value:any )"],["isNonPositiveIntegerArray.objects","isNonPositiveIntegerArray.objects( value:any )"],["isNonPositiveNumber","isNonPositiveNumber( value:any )"],["isNonPositiveNumber.isPrimitive","isNonPositiveNumber.isPrimitive( value:any )"],["isNonPositiveNumber.isObject","isNonPositiveNumber.isObject( value:any )"],["isNonPositiveNumberArray","isNonPositiveNumberArray( value:any )"],["isNonPositiveNumberArray.primitives","isNonPositiveNumberArray.primitives( value:any )"],["isNonPositiveNumberArray.objects","isNonPositiveNumberArray.objects( value:any )"],["isNonSymmetricMatrix","isNonSymmetricMatrix( value:any )"],["isNull","isNull( value:any )"],["isNullArray","isNullArray( value:any )"],["isNumber","isNumber( value:any )"],["isNumber.isPrimitive","isNumber.isPrimitive( value:any )"],["isNumber.isObject","isNumber.isObject( value:any )"],["isNumberArray","isNumberArray( value:any )"],["isNumberArray.primitives","isNumberArray.primitives( value:any )"],["isNumberArray.objects","isNumberArray.objects( value:any )"],["isNumericArray","isNumericArray( value:any )"],["isObject","isObject( value:any )"],["isObjectArray","isObjectArray( value:any )"],["isObjectLike","isObjectLike( value:any )"],["isOdd","isOdd( value:any )"],["isOdd.isPrimitive","isOdd.isPrimitive( value:any )"],["isOdd.isObject","isOdd.isObject( value:any )"],["isoWeeksInYear","isoWeeksInYear( [year:integer] )"],["isPascalcase","isPascalcase( value:any )"],["isPersymmetricMatrix","isPersymmetricMatrix( value:any )"],["isPlainObject","isPlainObject( value:any )"],["isPlainObjectArray","isPlainObjectArray( value:any )"],["isPositiveFinite","isPositiveFinite( value:any )"],["isPositiveFinite.isPrimitive","isPositiveFinite.isPrimitive( value:any )"],["isPositiveFinite.isObject","isPositiveFinite.isObject( value:any )"],["isPositiveInteger","isPositiveInteger( value:any )"],["isPositiveInteger.isPrimitive","isPositiveInteger.isPrimitive( value:any )"],["isPositiveInteger.isObject","isPositiveInteger.isObject( value:any )"],["isPositiveIntegerArray","isPositiveIntegerArray( value:any )"],["isPositiveIntegerArray.primitives","isPositiveIntegerArray.primitives( value:any )"],["isPositiveIntegerArray.objects","isPositiveIntegerArray.objects( value:any )"],["isPositiveNumber","isPositiveNumber( value:any )"],["isPositiveNumber.isPrimitive","isPositiveNumber.isPrimitive( value:any )"],["isPositiveNumber.isObject","isPositiveNumber.isObject( value:any )"],["isPositiveNumberArray","isPositiveNumberArray( value:any )"],["isPositiveNumberArray.primitives","isPositiveNumberArray.primitives( value:any )"],["isPositiveNumberArray.objects","isPositiveNumberArray.objects( value:any )"],["isPositiveZero","isPositiveZero( value:any )"],["isPositiveZero.isPrimitive","isPositiveZero.isPrimitive( value:any )"],["isPositiveZero.isObject","isPositiveZero.isObject( value:any )"],["isPrime","isPrime( value:any )"],["isPrime.isPrimitive","isPrime.isPrimitive( value:any )"],["isPrime.isObject","isPrime.isObject( value:any )"],["isPrimitive","isPrimitive( value:any )"],["isPrimitiveArray","isPrimitiveArray( value:any )"],["isPRNGLike","isPRNGLike( value:any )"],["isProbability","isProbability( value:any )"],["isProbability.isPrimitive","isProbability.isPrimitive( value:any )"],["isProbability.isObject","isProbability.isObject( value:any )"],["isProbabilityArray","isProbabilityArray( value:any )"],["isProbabilityArray.primitives","isProbabilityArray.primitives( value:any )"],["isProbabilityArray.objects","isProbabilityArray.objects( value:any )"],["isPropertyKey","isPropertyKey( value:any )"],["isPrototypeOf","isPrototypeOf( value:any, proto:Object|Function )"],["isRaggedNestedArray","isRaggedNestedArray( value:any )"],["isRangeError","isRangeError( value:any )"],["isReadableProperty","isReadableProperty( value:any, property:any )"],["isReadablePropertyIn","isReadablePropertyIn( value:any, property:any )"],["isReadOnlyProperty","isReadOnlyProperty( value:any, property:any )"],["isReadOnlyPropertyIn","isReadOnlyPropertyIn( value:any, property:any )"],["isReadWriteProperty","isReadWriteProperty( value:any, property:any )"],["isReadWritePropertyIn","isReadWritePropertyIn( value:any, property:any )"],["isReferenceError","isReferenceError( value:any )"],["isRegExp","isRegExp( value:any )"],["isRegExpString","isRegExpString( value:any )"],["isRelativePath","isRelativePath( value:any )"],["isRelativePath.posix","isRelativePath.posix( value:any )"],["isRelativePath.win32","isRelativePath.win32( value:any )"],["isRelativeURI","isRelativeURI( value:any )"],["isSafeInteger","isSafeInteger( value:any )"],["isSafeInteger.isPrimitive","isSafeInteger.isPrimitive( value:any )"],["isSafeInteger.isObject","isSafeInteger.isObject( value:any )"],["isSafeIntegerArray","isSafeIntegerArray( value:any )"],["isSafeIntegerArray.primitives","isSafeIntegerArray.primitives( value:any )"],["isSafeIntegerArray.objects","isSafeIntegerArray.objects( value:any )"],["isSameArray","isSameArray( v1:any, v2:any )"],["isSameArrayLike","isSameArrayLike( v1:any, v2:any )"],["isSameComplex64","isSameComplex64( v1:any, v2:any )"],["isSameComplex64Array","isSameComplex64Array( v1:any, v2:any )"],["isSameComplex128","isSameComplex128( v1:any, v2:any )"],["isSameComplex128Array","isSameComplex128Array( v1:any, v2:any )"],["isSameFloat32Array","isSameFloat32Array( v1:any, v2:any )"],["isSameFloat64Array","isSameFloat64Array( v1:any, v2:any )"],["isSameNativeClass","isSameNativeClass( a:any, b:any )"],["isSameType","isSameType( a:any, b:any )"],["isSameValue","isSameValue( a:any, b:any )"],["isSameValueZero","isSameValueZero( a:any, b:any )"],["isSemVer","isSemVer( value:any )"],["isSharedArrayBuffer","isSharedArrayBuffer( value:any )"],["isSkewCentrosymmetricMatrix","isSkewCentrosymmetricMatrix( value:any )"],["isSkewPersymmetricMatrix","isSkewPersymmetricMatrix( value:any )"],["isSkewSymmetricMatrix","isSkewSymmetricMatrix( value:any )"],["isSlice","isSlice( value:any )"],["isSnakecase","isSnakecase( value:any )"],["isSquareMatrix","isSquareMatrix( value:any )"],["isSquareNumber","isSquareNumber( value:any )"],["isSquareNumber.isPrimitive","isSquareNumber.isPrimitive( value:any )"],["isSquareNumber.isObject","isSquareNumber.isObject( value:any )"],["isSquareTriangularNumber","isSquareTriangularNumber( value:any )"],["isSquareTriangularNumber.isPrimitive","isSquareTriangularNumber.isPrimitive( value:any )"],["isSquareTriangularNumber.isObject","isSquareTriangularNumber.isObject( value:any )"],["isStartcase","isStartcase( value:any )"],["isStrictEqual","isStrictEqual( a:any, b:any )"],["isString","isString( value:any )"],["isString.isPrimitive","isString.isPrimitive( value:any )"],["isString.isObject","isString.isObject( value:any )"],["isStringArray","isStringArray( value:any )"],["isStringArray.primitives","isStringArray.primitives( value:any )"],["isStringArray.objects","isStringArray.objects( value:any )"],["isStruct","isStruct( value:any )"],["isStructConstructorLike","isStructConstructorLike( value:any )"],["isSymbol","isSymbol( value:any )"],["isSymbolArray","isSymbolArray( value:any )"],["isSymbolArray.primitives","isSymbolArray.primitives( value:any )"],["isSymbolArray.objects","isSymbolArray.objects( value:any )"],["isSymmetricMatrix","isSymmetricMatrix( value:any )"],["isSyntaxError","isSyntaxError( value:any )"],["isTriangularNumber","isTriangularNumber( value:any )"],["isTriangularNumber.isPrimitive","isTriangularNumber.isPrimitive( value:any )"],["isTriangularNumber.isObject","isTriangularNumber.isObject( value:any )"],["isTruthy","isTruthy( value:any )"],["isTruthyArray","isTruthyArray( value:any )"],["isTypedArray","isTypedArray( value:any )"],["isTypedArrayLength","isTypedArrayLength( value:any )"],["isTypedArrayLike","isTypedArrayLike( value:any )"],["isTypeError","isTypeError( value:any )"],["isUint8Array","isUint8Array( value:any )"],["isUint8ClampedArray","isUint8ClampedArray( value:any )"],["isUint16Array","isUint16Array( value:any )"],["isUint32Array","isUint32Array( value:any )"],["isUNCPath","isUNCPath( value:any )"],["isUndefined","isUndefined( value:any )"],["isUndefinedOrNull","isUndefinedOrNull( value:any )"],["isUnityProbabilityArray","isUnityProbabilityArray( value:any )"],["isUppercase","isUppercase( value:any )"],["isURI","isURI( value:any )"],["isURIError","isURIError( value:any )"],["isVectorLike","isVectorLike( value:any )"],["isWebAssemblyMemory","isWebAssemblyMemory( value:any )"],["isWellFormedString","isWellFormedString( str:any )"],["isWellFormedString.isPrimitive","isWellFormedString.isPrimitive( str:any )"],["isWellFormedString.isObject","isWellFormedString.isObject( str:any )"],["isWhitespace","isWhitespace( str:string )"],["isWritableProperty","isWritableProperty( value:any, property:any )"],["isWritablePropertyIn","isWritablePropertyIn( value:any, property:any )"],["isWriteOnlyProperty","isWriteOnlyProperty( value:any, property:any )"],["isWriteOnlyPropertyIn","isWriteOnlyPropertyIn( value:any, property:any )"],["iterAbs","iterAbs( iterator:Object )"],["iterAbs2","iterAbs2( iterator:Object )"],["iterAcos","iterAcos( iterator:Object )"],["iterAcosh","iterAcosh( iterator:Object )"],["iterAcot","iterAcot( iterator:Object )"],["iterAcoth","iterAcoth( iterator:Object )"],["iterAcovercos","iterAcovercos( iterator:Object )"],["iterAcoversin","iterAcoversin( iterator:Object )"],["iterAdd","iterAdd( iter0:Object, ...iterator:Object )"],["iterAdvance","iterAdvance( iterator:Object[, n:integer] )"],["iterAhavercos","iterAhavercos( iterator:Object )"],["iterAhaversin","iterAhaversin( iterator:Object )"],["iterAny","iterAny( iterator:Object )"],["iterAnyBy","iterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterAsin","iterAsin( iterator:Object )"],["iterAsinh","iterAsinh( iterator:Object )"],["iterAtan","iterAtan( iterator:Object )"],["iterAtan2","iterAtan2( y:Object|number, x:Object|number )"],["iterAtanh","iterAtanh( iterator:Object )"],["iterator2array","iterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, thisArg:any]] )"],["iterator2arrayview","iterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["iteratorStream","iteratorStream( iterator:Object[, options:Object] )"],["iteratorStream.factory","iteratorStream.factory( [options:Object] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator:Object[, options:Object] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator:Object )"],["iterAversin","iterAversin( iterator:Object )"],["iterawgn","iterawgn( iterator:Object, sigma:number[, options:Object] )"],["iterawln","iterawln( iterator:Object, sigma:number[, options:Object] )"],["iterawun","iterawun( iterator:Object, sigma:number[, options:Object] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options:Object] )"],["iterBartlettPulse","iterBartlettPulse( [options:Object] )"],["iterBesselj0","iterBesselj0( iterator:Object )"],["iterBesselj1","iterBesselj1( iterator:Object )"],["iterBessely0","iterBessely0( iterator:Object )"],["iterBessely1","iterBessely1( iterator:Object )"],["iterBeta","iterBeta( x:Object|number, y:Object|number )"],["iterBetaln","iterBetaln( x:Object|number, y:Object|number )"],["iterBinet","iterBinet( iterator:Object )"],["iterCbrt","iterCbrt( iterator:Object )"],["iterCeil","iterCeil( iterator:Object )"],["iterCeil2","iterCeil2( iterator:Object )"],["iterCeil10","iterCeil10( iterator:Object )"],["iterCompositesSeq","iterCompositesSeq( [options:Object] )"],["iterConcat","iterConcat( iter0:Object, ...iterator:Object )"],["iterConstant","iterConstant( value:any[, options:Object] )"],["iterContinuedFraction","iterContinuedFraction( iterator:Object[, options:Object] )"],["iterContinuedFractionSeq","iterContinuedFractionSeq( x:number[, options:Object] )"],["iterCos","iterCos( iterator:Object )"],["iterCosh","iterCosh( iterator:Object )"],["iterCosineWave","iterCosineWave( [options:Object] )"],["iterCosm1","iterCosm1( iterator:Object )"],["iterCospi","iterCospi( iterator:Object )"],["iterCounter","iterCounter( iterator:Object )"],["iterCovercos","iterCovercos( iterator:Object )"],["iterCoversin","iterCoversin( iterator:Object )"],["iterCubesSeq","iterCubesSeq( [options:Object] )"],["itercugmean","itercugmean( iterator:Object )"],["itercuhmean","itercuhmean( iterator:Object )"],["itercumax","itercumax( iterator:Object )"],["itercumaxabs","itercumaxabs( iterator:Object )"],["itercumean","itercumean( iterator:Object )"],["itercumeanabs","itercumeanabs( iterator:Object )"],["itercumeanabs2","itercumeanabs2( iterator:Object )"],["itercumidrange","itercumidrange( iterator:Object )"],["itercumin","itercumin( iterator:Object )"],["itercuminabs","itercuminabs( iterator:Object )"],["itercuprod","itercuprod( iterator:Object )"],["itercurange","itercurange( iterator:Object )"],["itercusum","itercusum( iterator:Object )"],["itercusumabs","itercusumabs( iterator:Object )"],["itercusumabs2","itercusumabs2( iterator:Object )"],["iterDatespace","iterDatespace( start:integer|string|Date, stop:integer|string|Date[, N:integer][, options:Object] )"],["iterDedupe","iterDedupe( iterator:Object[, limit:integer] )"],["iterDedupeBy","iterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )"],["iterDeg2rad","iterDeg2rad( iterator:Object )"],["iterDigamma","iterDigamma( iterator:Object )"],["iterDiracComb","iterDiracComb( [options:Object] )"],["iterDiracDelta","iterDiracDelta( iterator:Object )"],["iterDivide","iterDivide( iter0:Object, ...iterator:Object )"],["iterDoUntilEach","iterDoUntilEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterDoWhileEach","iterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterEllipe","iterEllipe( iterator:Object )"],["iterEllipk","iterEllipk( iterator:Object )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator:Object )"],["iterErfc","iterErfc( iterator:Object )"],["iterErfcinv","iterErfcinv( iterator:Object )"],["iterErfinv","iterErfinv( iterator:Object )"],["iterEta","iterEta( iterator:Object )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options:Object] )"],["iterEvery","iterEvery( iterator:Object )"],["iterEveryBy","iterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterExp","iterExp( iterator:Object )"],["iterExp2","iterExp2( iterator:Object )"],["iterExp10","iterExp10( iterator:Object )"],["iterExpit","iterExpit( iterator:Object )"],["iterExpm1","iterExpm1( iterator:Object )"],["iterExpm1rel","iterExpm1rel( iterator:Object )"],["iterFactorial","iterFactorial( iterator:Object )"],["iterFactorialln","iterFactorialln( iterator:Object )"],["iterFactorialsSeq","iterFactorialsSeq( [options:Object] )"],["iterFibonacciSeq","iterFibonacciSeq( [options:Object] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options:Object] )"],["iterFill","iterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )"],["iterFilter","iterFilter( iterator:Object, predicate:Function[, thisArg:any] )"],["iterFilterMap","iterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFirst","iterFirst( iterator:Object )"],["iterFlatTopPulse","iterFlatTopPulse( [options:Object] )"],["iterFloor","iterFloor( iterator:Object )"],["iterFloor2","iterFloor2( iterator:Object )"],["iterFloor10","iterFloor10( iterator:Object )"],["iterFlow","iterFlow( methods:Object )"],["iterForEach","iterForEach( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options:Object] )"],["iterFresnelc","iterFresnelc( iterator:Object )"],["iterFresnels","iterFresnels( iterator:Object )"],["iterGamma","iterGamma( iterator:Object )"],["iterGamma1pm1","iterGamma1pm1( iterator:Object )"],["iterGammaln","iterGammaln( iterator:Object )"],["iterHacovercos","iterHacovercos( iterator:Object )"],["iterHacoversin","iterHacoversin( iterator:Object )"],["iterHannPulse","iterHannPulse( [options:Object] )"],["iterHavercos","iterHavercos( iterator:Object )"],["iterHaversin","iterHaversin( iterator:Object )"],["iterHead","iterHead( iterator:Object, n:integer )"],["iterIncrspace","iterIncrspace( start:number, stop:number[, increment:number] )"],["iterIntegersSeq","iterIntegersSeq( [options:Object] )"],["iterIntersection","iterIntersection( iter0:Object, ...iterator:Object )"],["iterIntersectionByHash","iterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, thisArg:any] )"],["iterInv","iterInv( iterator:Object )"],["iterLanczosPulse","iterLanczosPulse( [options:Object] )"],["iterLast","iterLast( iterator:Object )"],["iterLength","iterLength( iterator:Object )"],["iterLinspace","iterLinspace( start:number, stop:number[, N:integer] )"],["iterLn","iterLn( iterator:Object )"],["iterLog","iterLog( x:Object|number, b:Object|number )"],["iterLog1mexp","iterLog1mexp( iterator:Object )"],["iterLog1p","iterLog1p( iterator:Object )"],["iterLog1pexp","iterLog1pexp( iterator:Object )"],["iterLog2","iterLog2( iterator:Object )"],["iterLog10","iterLog10( iterator:Object )"],["iterLogit","iterLogit( iterator:Object )"],["iterLogspace","iterLogspace( start:number, stop:number[, N:integer][, options:Object] )"],["iterLucasSeq","iterLucasSeq( [options:Object] )"],["iterMap","iterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterMapN","iterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )"],["itermax","itermax( iterator:Object )"],["itermaxabs","itermaxabs( iterator:Object )"],["itermean","itermean( iterator:Object )"],["itermeanabs","itermeanabs( iterator:Object )"],["itermeanabs2","itermeanabs2( iterator:Object )"],["itermidrange","itermidrange( iterator:Object )"],["itermin","itermin( iterator:Object )"],["iterminabs","iterminabs( iterator:Object )"],["itermmax","itermmax( iterator:Object, W:integer )"],["itermmaxabs","itermmaxabs( iterator:Object, W:integer )"],["itermmean","itermmean( iterator:Object, W:integer )"],["itermmeanabs","itermmeanabs( iterator:Object, W:integer )"],["itermmeanabs2","itermmeanabs2( iterator:Object, W:integer )"],["itermmidrange","itermmidrange( iterator:Object, W:integer )"],["itermmin","itermmin( iterator:Object, W:integer )"],["itermminabs","itermminabs( iterator:Object, W:integer )"],["iterMod","iterMod( iter0:Object, ...iterator:Object )"],["itermprod","itermprod( iterator:Object, W:integer )"],["itermrange","itermrange( iterator:Object, W:integer )"],["itermsum","itermsum( iterator:Object, W:integer )"],["itermsumabs","itermsumabs( iterator:Object, W:integer )"],["itermsumabs2","itermsumabs2( iterator:Object, W:integer )"],["iterMultiply","iterMultiply( iter0:Object, ...iterator:Object )"],["iterNegaFibonacciSeq","iterNegaFibonacciSeq( [options:Object] )"],["iterNegaLucasSeq","iterNegaLucasSeq( [options:Object] )"],["iterNegativeEvenIntegersSeq","iterNegativeEvenIntegersSeq( [options:Object] )"],["iterNegativeIntegersSeq","iterNegativeIntegersSeq( [options:Object] )"],["iterNegativeOddIntegersSeq","iterNegativeOddIntegersSeq( [options:Object] )"],["iterNone","iterNone( iterator:Object )"],["iterNoneBy","iterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options:Object] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options:Object] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options:Object] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options:Object] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options:Object] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options:Object] )"],["iterNth","iterNth( iterator:Object, n:integer )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options:Object] )"],["iterPeriodicSinc","iterPeriodicSinc( n:integer[, options:Object] )"],["iterPipeline","iterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )"],["iterPop","iterPop( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options:Object] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options:Object] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options:Object] )"],["iterPow","iterPow( base:Object|number, exponent:Object|number )"],["iterPrimesSeq","iterPrimesSeq( [options:Object] )"],["iterprod","iterprod( iterator:Object )"],["iterPulse","iterPulse( [options:Object] )"],["iterPush","iterPush( iterator:Object, ...items:any )"],["iterRad2deg","iterRad2deg( iterator:Object )"],["iterRamp","iterRamp( iterator:Object )"],["iterrange","iterrange( iterator:Object )"],["iterReject","iterReject( iterator:Object, predicate:Function[, thisArg:any] )"],["iterReplicate","iterReplicate( iterator:Object, n:integer )"],["iterReplicateBy","iterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )"],["iterRound","iterRound( iterator:Object )"],["iterRound2","iterRound2( iterator:Object )"],["iterRound10","iterRound10( iterator:Object )"],["iterRsqrt","iterRsqrt( iterator:Object )"],["iterSawtoothWave","iterSawtoothWave( [options:Object] )"],["iterShift","iterShift( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterSignum","iterSignum( iterator:Object )"],["iterSin","iterSin( iterator:Object )"],["iterSinc","iterSinc( iterator:Object )"],["iterSineWave","iterSineWave( [options:Object] )"],["iterSinh","iterSinh( iterator:Object )"],["iterSinpi","iterSinpi( iterator:Object )"],["iterSlice","iterSlice( iterator:Object[, begin:integer[, end:integer]] )"],["iterSome","iterSome( iterator:Object, n:number )"],["iterSomeBy","iterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )"],["iterSpence","iterSpence( iterator:Object )"],["iterSqrt","iterSqrt( iterator:Object )"],["iterSqrt1pm1","iterSqrt1pm1( iterator:Object )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options:Object] )"],["iterSquaresSeq","iterSquaresSeq( [options:Object] )"],["iterSquareWave","iterSquareWave( [options:Object] )"],["iterstdev","iterstdev( iterator:Object[, mean:number] )"],["iterStep","iterStep( start:number, increment:number[, N:number] )"],["iterStrided","iterStrided( iterator:Object, stride:integer[, offset:integer[, eager:boolean]] )"],["iterStridedBy","iterStridedBy( iterator:Object, fcn:Function[, offset:integer[, eager:boolean]][, thisArg:any] )"],["iterSubtract","iterSubtract( iter0:Object, ...iterator:Object )"],["itersum","itersum( iterator:Object )"],["itersumabs","itersumabs( iterator:Object )"],["itersumabs2","itersumabs2( iterator:Object )"],["iterTan","iterTan( iterator:Object )"],["iterTanh","iterTanh( iterator:Object )"],["iterThunk","iterThunk( iterFcn:Function[, ...args:any] )"],["iterTriangleWave","iterTriangleWave( [options:Object] )"],["iterTriangularSeq","iterTriangularSeq( [options:Object] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options:Object] )"],["iterTrigamma","iterTrigamma( iterator:Object 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][options:Object] )"],["random.streams.t.objectMode","random.streams.t.objectMode( v:number[, options:Object] )"],["random.streams.triangular","random.streams.triangular( a:number, b:number, c:number[, options:Object] )"],["random.streams.triangular.factory","random.streams.triangular.factory( [a:number, b:number, c:number, ][options:Object] )"],["random.streams.triangular.objectMode","random.streams.triangular.objectMode( a:number, b:number, c:number[, options:Object] )"],["random.streams.uniform","random.streams.uniform( a:number, b:number[, options:Object] )"],["random.streams.uniform.factory","random.streams.uniform.factory( [a:number, b:number, ][options:Object] )"],["random.streams.uniform.objectMode","random.streams.uniform.objectMode( a:number, b:number[, options:Object] )"],["random.streams.weibull","random.streams.weibull( k:number, λ:number[, options:Object] )"],["random.streams.weibull.factory","random.streams.weibull.factory( [k:number, λ:number, ][options:Object] 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out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.betaprime.ndarray","random.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.chi","random.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, out:ArrayLikeObject, so:integer )"],["random.strided.chi.ndarray","random.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, ok:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.chi.factory","random.strided.chi.factory( [options:Object] 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so:integer, oo:integer[, options:Object] )"],["random.strided.mt19937.normalized","random.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.mt19937.normalized.ndarray","random.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.normal","random.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.normal.ndarray","random.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.poisson","random.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer )"],["random.strided.poisson.ndarray","random.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.poisson.factory","random.strided.poisson.factory( [options:Object] )"],["random.strided.poisson.PRNG","random.strided.poisson.PRNG"],["random.strided.poisson.seed","random.strided.poisson.seed"],["random.strided.poisson.seedLength","random.strided.poisson.seedLength"],["random.strided.poisson.state","random.strided.poisson.state"],["random.strided.poisson.stateLength","random.strided.poisson.stateLength"],["random.strided.poisson.byteLength","random.strided.poisson.byteLength"],["random.strided.randu","random.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.randu.ndarray","random.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.rayleigh","random.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer 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ignoreCase:boolean] )"],["rename","rename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )"],["rename.sync","rename.sync( oldPath:string|Buffer, newPath:string|Buffer )"],["reNativeFunction","reNativeFunction()"],["reNativeFunction.REGEXP","reNativeFunction.REGEXP"],["reorderArguments","reorderArguments( fcn:Function, indices:Array[, thisArg:any] )"],["repeat","repeat( str:string, n:integer )"],["replace","replace( str:string, search:string|RegExp, newval:string|Function )"],["replaceBefore","replaceBefore( str, search, replacement )"],["reRegExp","reRegExp()"],["reRegExp.REGEXP","reRegExp.REGEXP"],["rescape","rescape( str:string )"],["reSemVer","reSemVer()"],["reSemVer.REGEXP","reSemVer.REGEXP"],["resolveParentPath","resolveParentPath( path:string[, options:Object], clbk:Function )"],["resolveParentPath.sync","resolveParentPath.sync( path:string[, options:Object] )"],["resolveParentPathBy","resolveParentPathBy( path:string[, options:Object], predicate:Function, clbk:Function )"],["resolveParentPathBy.sync","resolveParentPathBy.sync( path:string[, options:Object], predicate:Function )"],["reUncPath","reUncPath()"],["reUncPath.REGEXP","reUncPath.REGEXP"],["reUtf16SurrogatePair","reUtf16SurrogatePair()"],["reUtf16SurrogatePair.REGEXP","reUtf16SurrogatePair.REGEXP"],["reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate()"],["reUtf16UnpairedSurrogate.REGEXP","reUtf16UnpairedSurrogate.REGEXP"],["reverseArguments","reverseArguments( fcn:Function[, thisArg:any] )"],["reverseString","reverseString( str:string[, options:Object] )"],["reviveBasePRNG","reviveBasePRNG( key:string, value:any )"],["reviveBuffer","reviveBuffer( key:string, value:any )"],["reviveComplex","reviveComplex( key:string, value:any )"],["reviveComplex64","reviveComplex64( key:string, value:any )"],["reviveComplex128","reviveComplex128( key:string, value:any )"],["reviveError","reviveError( key:string, value:any )"],["reviveRegExp","reviveRegExp( key:string, value:any 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setter:Function )"],["setMemoizedConfigurableReadOnly","setMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )"],["setMemoizedReadOnly","setMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )"],["setNonEnumerableProperty","setNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )"],["setNonEnumerableReadOnly","setNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )"],["setNonEnumerableReadOnlyAccessor","setNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )"],["setNonEnumerableReadWriteAccessor","setNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, setter:Function )"],["setNonEnumerableWriteOnlyAccessor","setNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )"],["setReadOnly","setReadOnly( obj:Object, prop:string|symbol, value:any )"],["setReadOnlyAccessor","setReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function 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[options:Object,] predicate:Function )"],["someInBy","someInBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )"],["someOwnBy","someOwnBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )"],["SOTU","SOTU( [options:Object] )"],["SPACHE_REVISED","SPACHE_REVISED()"],["SPAM_ASSASSIN","SPAM_ASSASSIN()"],["SparklineBase","SparklineBase( [data:ArrayLike|ndarray,] [options:Object] )"],["sparsearray2iterator","sparsearray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )"],["sparsearray2iteratorRight","sparsearray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )"],["splitStream","splitStream( [options:Object] )"],["splitStream.factory","splitStream.factory( [options:Object] )"],["splitStream.objectMode","splitStream.objectMode( [options:Object] 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strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.abs2.ndarray","strided.abs2.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.abs2By","strided.abs2By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.abs2By.ndarray","strided.abs2By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.absBy","strided.absBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.absBy.ndarray","strided.absBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acosBy","strided.acosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acosBy.ndarray","strided.acosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acoshBy","strided.acoshBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acoshBy.ndarray","strided.acoshBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acotBy","strided.acotBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acotBy.ndarray","strided.acotBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acothBy","strided.acothBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acothBy.ndarray","strided.acothBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acovercosBy","strided.acovercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acovercosBy.ndarray","strided.acovercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acoversinBy","strided.acoversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acoversinBy.ndarray","strided.acoversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.add","strided.add( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )"],["strided.add.ndarray","strided.add.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, z:ArrayLikeObject, sz:integer, oz:integer )"],["strided.addBy","strided.addBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, clbk:Function[, thisArg:any] )"],["strided.addBy.ndarray","strided.addBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, thisArg:any] )"],["strided.ahavercosBy","strided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahavercosBy.ndarray","strided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy","strided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy.ndarray","strided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy","strided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy.ndarray","strided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy","strided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy.ndarray","strided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy","strided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy.ndarray","strided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy","strided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy.ndarray","strided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy","strided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy.ndarray","strided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy","strided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy.ndarray","strided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj0By","strided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj0By.ndarray","strided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj1By","strided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj1By.ndarray","strided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely0By","strided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely0By.ndarray","strided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By","strided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By.ndarray","strided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy","strided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy.ndarray","strided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrt","strided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.cbrt.ndarray","strided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.cbrtBy","strided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrtBy.ndarray","strided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ceil","strided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.ceil.ndarray","strided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.cosBy","strided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.cosBy.ndarray","strided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.deg2rad","strided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.deg2rad.ndarray","strided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.dataTypes","strided.dataTypes()"],["strided.dcbrtBy","strided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, sy:integer, clbk:Function[, thisArg:any] )"],["strided.dcbrtBy.ndarray","strided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.dispatch","strided.dispatch( fcns:Function|ArrayLikeObject, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["strided.dispatchBy","strided.dispatchBy( fcns:Function|ArrayLikeObject, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["strided.floor","strided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.floor.ndarray","strided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.inv","strided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.inv.ndarray","strided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.mul","strided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )"],["strided.mul.ndarray","strided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, z:ArrayLikeObject, sz:integer, oz:integer )"],["strided.mulBy","strided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, clbk:Function[, thisArg:any] )"],["strided.mulBy.ndarray","strided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, thisArg:any] )"],["strided.ramp","strided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.ramp.ndarray","strided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.rsqrt","strided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.rsqrt.ndarray","strided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.sinBy","strided.sinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.sinBy.ndarray","strided.sinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.sqrt","strided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.sqrt.ndarray","strided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.sqrtBy","strided.sqrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.sqrtBy.ndarray","strided.sqrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.sub","strided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )"],["strided.sub.ndarray","strided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, z:ArrayLikeObject, sz:integer, oz:integer )"],["strided.subBy","strided.subBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, clbk:Function[, thisArg:any] )"],["strided.subBy.ndarray","strided.subBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, thisArg:any] )"],["strided.trunc","strided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.trunc.ndarray","strided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["stridedarray2iterator","stridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, offset:integer[, mapFcn:Function[, thisArg:any]] )"],["stridedArrayStream","stridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, offset:integer[, options:Object] )"],["stridedArrayStream.factory","stridedArrayStream.factory( [options:Object] )"],["stridedArrayStream.objectMode","stridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, stride:integer, offset:integer[, options:Object] )"],["string2buffer","string2buffer( str:string[, encoding:string] )"],["sub2ind","sub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )"],["substringAfter","substringAfter( str:string, search:string[, fromIndex:integer] )"],["substringAfterLast","substringAfterLast( str:string, search:string[, fromIndex:integer] )"],["substringBefore","substringBefore( str:string, search:string )"],["substringBeforeLast","substringBeforeLast( str:string, search:string )"],["SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()"],["SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()"],["Symbol","Symbol( [description:string] )"],["tabulate","tabulate( collection:Array|TypedArray|Object )"],["tabulateBy","tabulateBy( collection:Array|TypedArray|Object, [options:Object,] indicator:Function )"],["tabulateByAsync","tabulateByAsync( collection:Array|TypedArray|Object, [options:Object,] indicator:Function, done:Function )"],["tabulateByAsync.factory","tabulateByAsync.factory( [options:Object,] indicator:Function )"],["thunk","thunk( fcn:Function[, ...args:any] )"],["tic","tic()"],["timeit","timeit( code:string, [options:Object,] clbk:Function )"],["tmpdir","tmpdir()"],["toc","toc( time:Array )"],["tokenize","tokenize( str:string[, keepWhitespace:boolean] )"],["transformStream","transformStream( [options:Object] )"],["transformStream.factory","transformStream.factory( [options:Object] )"],["transformStream.objectMode","transformStream.objectMode( [options:Object] )"],["transformStream.ctor","transformStream.ctor( [options:Object] )"],["trim","trim( str:string )"],["truncate","truncate( str:string, len:integer[, ending:string] )"],["truncateMiddle","truncateMiddle( str:string, len:integer[, seq:string] )"],["trycatch","trycatch( x:Function, y:any )"],["trycatchAsync","trycatchAsync( x:Function, y:any, done:Function )"],["tryFunction","tryFunction( fcn:Function[, thisArg:any] )"],["tryRequire","tryRequire( id:string )"],["trythen","trythen( x:Function, y:Function )"],["trythenAsync","trythenAsync( x:Function, y:Function, done:Function )"],["ttest","ttest( x:Array[, y:Array][, options:Object] )"],["ttest2","ttest2( x:Array, y:Array[, options:Object] )"],["TWO_PI","TWO_PI"],["typedarray","typedarray( [dtype:string] )"],["typedarray","typedarray( length:integer[, dtype:string] )"],["typedarray","typedarray( typedarray:TypedArray[, dtype:string] )"],["typedarray","typedarray( obj:Object[, dtype:string] )"],["typedarray","typedarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, dtype:string] )"],["typedarray2json","typedarray2json( arr:TypedArray )"],["typedarrayCtors","typedarrayCtors( dtype:string )"],["typedarrayDataTypes","typedarrayDataTypes()"],["typedarraypool","typedarraypool( [dtype:string] 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)"],["base.strided.dmeanstdevpn.ndarray","base.strided.dmeanstdevpn.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )"],["base.strided.dmeanvar","base.strided.dmeanvar( N:integer, c:number, x:Float64Array, strideX:integer, out:Float64Array, strideOut:integer )"],["base.strided.dmeanvar.ndarray","base.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )"],["base.strided.dmeanvarpn","base.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, out:Float64Array, strideOut:integer )"],["base.strided.dmeanvarpn.ndarray","base.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )"],["base.strided.dmeanwd","base.strided.dmeanwd( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmeanwd.ndarray","base.strided.dmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dmediansorted","base.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmediansorted.ndarray","base.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dmidrange","base.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmidrange.ndarray","base.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dmin","base.strided.dmin( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmin.ndarray","base.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dminabs","base.strided.dminabs( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dminabs.ndarray","base.strided.dminabs.ndarray( N:integer, x:Float64Array, 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)"],["base.strided.dmskcbrt","base.strided.dmskcbrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskcbrt.ndarray","base.strided.dmskcbrt.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )"],["base.strided.dmskceil","base.strided.dmskceil( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskceil.ndarray","base.strided.dmskceil.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )"],["base.strided.dmskdeg2rad","base.strided.dmskdeg2rad( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskdeg2rad.ndarray","base.strided.dmskdeg2rad.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, 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)"],["base.strided.smeanpw.ndarray","base.strided.smeanpw.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smeanwd","base.strided.smeanwd( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smeanwd.ndarray","base.strided.smeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smediansorted","base.strided.smediansorted( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smediansorted.ndarray","base.strided.smediansorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smidrange","base.strided.smidrange( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smidrange.ndarray","base.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smin","base.strided.smin( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smin.ndarray","base.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.sminabs","base.strided.sminabs( N:integer, x:Float32Array, strideX:integer )"],["base.strided.sminabs.ndarray","base.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.sminsorted","base.strided.sminsorted( N:integer, x:Float32Array, strideX:integer )"],["base.strided.sminsorted.ndarray","base.strided.sminsorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smskabs","base.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskabs.ndarray","base.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskabs2","base.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskabs2.ndarray","base.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskcbrt","base.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskcbrt.ndarray","base.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskceil","base.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskceil.ndarray","base.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskdeg2rad","base.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskdeg2rad.ndarray","base.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskfloor","base.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskfloor.ndarray","base.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskinv","base.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskinv.ndarray","base.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskmap","base.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer, fcn:Function )"],["base.strided.smskmap.ndarray","base.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer, fcn:Function )"],["base.strided.smskmap2","base.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, fcn:Function )"],["base.strided.smskmap2.ndarray","base.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )"],["base.strided.smskmax","base.strided.smskmax( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskmax.ndarray","base.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskmin","base.strided.smskmin( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskmin.ndarray","base.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskramp","base.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskramp.ndarray","base.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskrange","base.strided.smskrange( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskrange.ndarray","base.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskrsqrt","base.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskrsqrt.ndarray","base.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smsksqrt","base.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smsksqrt.ndarray","base.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smsktrunc","base.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smsktrunc.ndarray","base.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.snanmax","base.strided.snanmax( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmax.ndarray","base.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmaxabs","base.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmaxabs.ndarray","base.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmean","base.strided.snanmean( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmean.ndarray","base.strided.snanmean.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmeanors","base.strided.snanmeanors( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmeanors.ndarray","base.strided.snanmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer 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x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.snanmskmax.ndarray","base.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.snanmskmin","base.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.snanmskmin.ndarray","base.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.snanmskrange","base.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.snanmskrange.ndarray","base.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.snanrange","base.strided.snanrange( N:integer, 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)"],["isNonPositiveFinite.isObject","isNonPositiveFinite.isObject( value:any )"],["isNonPositiveInteger","isNonPositiveInteger( value:any )"],["isNonPositiveInteger.isPrimitive","isNonPositiveInteger.isPrimitive( value:any )"],["isNonPositiveInteger.isObject","isNonPositiveInteger.isObject( value:any )"],["isNonPositiveIntegerArray","isNonPositiveIntegerArray( value:any )"],["isNonPositiveIntegerArray.primitives","isNonPositiveIntegerArray.primitives( value:any )"],["isNonPositiveIntegerArray.objects","isNonPositiveIntegerArray.objects( value:any )"],["isNonPositiveNumber","isNonPositiveNumber( value:any )"],["isNonPositiveNumber.isPrimitive","isNonPositiveNumber.isPrimitive( value:any )"],["isNonPositiveNumber.isObject","isNonPositiveNumber.isObject( value:any )"],["isNonPositiveNumberArray","isNonPositiveNumberArray( value:any )"],["isNonPositiveNumberArray.primitives","isNonPositiveNumberArray.primitives( value:any )"],["isNonPositiveNumberArray.objects","isNonPositiveNumberArray.objects( value:any )"],["isNonSymmetricMatrix","isNonSymmetricMatrix( value:any )"],["isNull","isNull( value:any )"],["isNullArray","isNullArray( value:any )"],["isNumber","isNumber( value:any )"],["isNumber.isPrimitive","isNumber.isPrimitive( value:any )"],["isNumber.isObject","isNumber.isObject( value:any )"],["isNumberArray","isNumberArray( value:any )"],["isNumberArray.primitives","isNumberArray.primitives( value:any )"],["isNumberArray.objects","isNumberArray.objects( value:any )"],["isNumericArray","isNumericArray( value:any )"],["isObject","isObject( value:any )"],["isObjectArray","isObjectArray( value:any )"],["isObjectLike","isObjectLike( value:any )"],["isOdd","isOdd( value:any )"],["isOdd.isPrimitive","isOdd.isPrimitive( value:any )"],["isOdd.isObject","isOdd.isObject( value:any )"],["isoWeeksInYear","isoWeeksInYear( [year:integer] )"],["isPascalcase","isPascalcase( value:any )"],["isPersymmetricMatrix","isPersymmetricMatrix( value:any )"],["isPlainObject","isPlainObject( value:any )"],["isPlainObjectArray","isPlainObjectArray( value:any )"],["isPositiveFinite","isPositiveFinite( value:any )"],["isPositiveFinite.isPrimitive","isPositiveFinite.isPrimitive( value:any )"],["isPositiveFinite.isObject","isPositiveFinite.isObject( value:any )"],["isPositiveInteger","isPositiveInteger( value:any )"],["isPositiveInteger.isPrimitive","isPositiveInteger.isPrimitive( value:any )"],["isPositiveInteger.isObject","isPositiveInteger.isObject( value:any )"],["isPositiveIntegerArray","isPositiveIntegerArray( value:any )"],["isPositiveIntegerArray.primitives","isPositiveIntegerArray.primitives( value:any )"],["isPositiveIntegerArray.objects","isPositiveIntegerArray.objects( value:any )"],["isPositiveNumber","isPositiveNumber( value:any )"],["isPositiveNumber.isPrimitive","isPositiveNumber.isPrimitive( value:any )"],["isPositiveNumber.isObject","isPositiveNumber.isObject( value:any )"],["isPositiveNumberArray","isPositiveNumberArray( value:any )"],["isPositiveNumberArray.primitives","isPositiveNumberArray.primitives( value:any )"],["isPositiveNumberArray.objects","isPositiveNumberArray.objects( value:any )"],["isPositiveZero","isPositiveZero( value:any )"],["isPositiveZero.isPrimitive","isPositiveZero.isPrimitive( value:any )"],["isPositiveZero.isObject","isPositiveZero.isObject( value:any )"],["isPrime","isPrime( value:any )"],["isPrime.isPrimitive","isPrime.isPrimitive( value:any )"],["isPrime.isObject","isPrime.isObject( value:any )"],["isPrimitive","isPrimitive( value:any )"],["isPrimitiveArray","isPrimitiveArray( value:any )"],["isPRNGLike","isPRNGLike( value:any )"],["isProbability","isProbability( value:any )"],["isProbability.isPrimitive","isProbability.isPrimitive( value:any )"],["isProbability.isObject","isProbability.isObject( value:any )"],["isProbabilityArray","isProbabilityArray( value:any )"],["isProbabilityArray.primitives","isProbabilityArray.primitives( value:any )"],["isProbabilityArray.objects","isProbabilityArray.objects( value:any )"],["isPropertyKey","isPropertyKey( value:any )"],["isPrototypeOf","isPrototypeOf( value:any, proto:Object|Function )"],["isRaggedNestedArray","isRaggedNestedArray( value:any )"],["isRangeError","isRangeError( value:any )"],["isReadableProperty","isReadableProperty( value:any, property:any )"],["isReadablePropertyIn","isReadablePropertyIn( value:any, property:any )"],["isReadOnlyProperty","isReadOnlyProperty( value:any, property:any )"],["isReadOnlyPropertyIn","isReadOnlyPropertyIn( value:any, property:any )"],["isReadWriteProperty","isReadWriteProperty( value:any, property:any )"],["isReadWritePropertyIn","isReadWritePropertyIn( value:any, property:any )"],["isReferenceError","isReferenceError( value:any )"],["isRegExp","isRegExp( value:any )"],["isRegExpString","isRegExpString( value:any )"],["isRelativePath","isRelativePath( value:any )"],["isRelativePath.posix","isRelativePath.posix( value:any )"],["isRelativePath.win32","isRelativePath.win32( value:any )"],["isRelativeURI","isRelativeURI( value:any )"],["isSafeInteger","isSafeInteger( value:any )"],["isSafeInteger.isPrimitive","isSafeInteger.isPrimitive( value:any )"],["isSafeInteger.isObject","isSafeInteger.isObject( value:any )"],["isSafeIntegerArray","isSafeIntegerArray( value:any )"],["isSafeIntegerArray.primitives","isSafeIntegerArray.primitives( value:any )"],["isSafeIntegerArray.objects","isSafeIntegerArray.objects( value:any )"],["isSameArray","isSameArray( v1:any, v2:any )"],["isSameArrayLike","isSameArrayLike( v1:any, v2:any )"],["isSameComplex64","isSameComplex64( v1:any, v2:any )"],["isSameComplex64Array","isSameComplex64Array( v1:any, v2:any )"],["isSameComplex128","isSameComplex128( v1:any, v2:any )"],["isSameComplex128Array","isSameComplex128Array( v1:any, v2:any )"],["isSameFloat32Array","isSameFloat32Array( v1:any, v2:any )"],["isSameFloat64Array","isSameFloat64Array( v1:any, v2:any )"],["isSameNativeClass","isSameNativeClass( a:any, b:any )"],["isSameType","isSameType( a:any, b:any )"],["isSameValue","isSameValue( a:any, b:any )"],["isSameValueZero","isSameValueZero( a:any, b:any )"],["isSemVer","isSemVer( value:any )"],["isSharedArrayBuffer","isSharedArrayBuffer( value:any )"],["isSkewCentrosymmetricMatrix","isSkewCentrosymmetricMatrix( value:any )"],["isSkewPersymmetricMatrix","isSkewPersymmetricMatrix( value:any )"],["isSkewSymmetricMatrix","isSkewSymmetricMatrix( value:any )"],["isSlice","isSlice( value:any )"],["isSnakecase","isSnakecase( value:any )"],["isSquareMatrix","isSquareMatrix( value:any )"],["isSquareNumber","isSquareNumber( value:any )"],["isSquareNumber.isPrimitive","isSquareNumber.isPrimitive( value:any )"],["isSquareNumber.isObject","isSquareNumber.isObject( value:any )"],["isSquareTriangularNumber","isSquareTriangularNumber( value:any )"],["isSquareTriangularNumber.isPrimitive","isSquareTriangularNumber.isPrimitive( value:any )"],["isSquareTriangularNumber.isObject","isSquareTriangularNumber.isObject( value:any )"],["isStartcase","isStartcase( value:any )"],["isStrictEqual","isStrictEqual( a:any, b:any )"],["isString","isString( value:any )"],["isString.isPrimitive","isString.isPrimitive( value:any )"],["isString.isObject","isString.isObject( value:any )"],["isStringArray","isStringArray( value:any )"],["isStringArray.primitives","isStringArray.primitives( value:any )"],["isStringArray.objects","isStringArray.objects( value:any )"],["isStruct","isStruct( value:any )"],["isStructConstructorLike","isStructConstructorLike( value:any )"],["isSymbol","isSymbol( value:any )"],["isSymbolArray","isSymbolArray( value:any )"],["isSymbolArray.primitives","isSymbolArray.primitives( value:any )"],["isSymbolArray.objects","isSymbolArray.objects( value:any )"],["isSymmetricMatrix","isSymmetricMatrix( value:any )"],["isSyntaxError","isSyntaxError( value:any )"],["isTriangularNumber","isTriangularNumber( value:any )"],["isTriangularNumber.isPrimitive","isTriangularNumber.isPrimitive( value:any )"],["isTriangularNumber.isObject","isTriangularNumber.isObject( value:any )"],["isTruthy","isTruthy( value:any )"],["isTruthyArray","isTruthyArray( value:any )"],["isTypedArray","isTypedArray( value:any )"],["isTypedArrayLength","isTypedArrayLength( value:any )"],["isTypedArrayLike","isTypedArrayLike( value:any )"],["isTypeError","isTypeError( value:any )"],["isUint8Array","isUint8Array( value:any )"],["isUint8ClampedArray","isUint8ClampedArray( value:any )"],["isUint16Array","isUint16Array( value:any )"],["isUint32Array","isUint32Array( value:any )"],["isUNCPath","isUNCPath( value:any )"],["isUndefined","isUndefined( value:any )"],["isUndefinedOrNull","isUndefinedOrNull( value:any )"],["isUnityProbabilityArray","isUnityProbabilityArray( value:any )"],["isUppercase","isUppercase( value:any )"],["isURI","isURI( value:any )"],["isURIError","isURIError( value:any )"],["isVectorLike","isVectorLike( value:any )"],["isWebAssemblyMemory","isWebAssemblyMemory( value:any )"],["isWellFormedString","isWellFormedString( str:any )"],["isWellFormedString.isPrimitive","isWellFormedString.isPrimitive( str:any )"],["isWellFormedString.isObject","isWellFormedString.isObject( str:any )"],["isWhitespace","isWhitespace( str:string )"],["isWritableProperty","isWritableProperty( value:any, property:any )"],["isWritablePropertyIn","isWritablePropertyIn( value:any, property:any )"],["isWriteOnlyProperty","isWriteOnlyProperty( value:any, property:any )"],["isWriteOnlyPropertyIn","isWriteOnlyPropertyIn( value:any, property:any )"],["iterAbs","iterAbs( iterator:Object )"],["iterAbs2","iterAbs2( iterator:Object )"],["iterAcos","iterAcos( iterator:Object )"],["iterAcosh","iterAcosh( iterator:Object )"],["iterAcot","iterAcot( iterator:Object )"],["iterAcoth","iterAcoth( iterator:Object )"],["iterAcovercos","iterAcovercos( iterator:Object )"],["iterAcoversin","iterAcoversin( iterator:Object )"],["iterAdd","iterAdd( iter0:Object, ...iterator:Object )"],["iterAdvance","iterAdvance( iterator:Object[, n:integer] )"],["iterAhavercos","iterAhavercos( iterator:Object )"],["iterAhaversin","iterAhaversin( iterator:Object )"],["iterAny","iterAny( iterator:Object )"],["iterAnyBy","iterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterAsin","iterAsin( iterator:Object )"],["iterAsinh","iterAsinh( iterator:Object )"],["iterAtan","iterAtan( iterator:Object )"],["iterAtan2","iterAtan2( y:Object|number, x:Object|number )"],["iterAtanh","iterAtanh( iterator:Object )"],["iterator2array","iterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, thisArg:any]] )"],["iterator2arrayview","iterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["iteratorStream","iteratorStream( iterator:Object[, options:Object] )"],["iteratorStream.factory","iteratorStream.factory( [options:Object] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator:Object[, options:Object] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator:Object )"],["iterAversin","iterAversin( iterator:Object )"],["iterawgn","iterawgn( iterator:Object, sigma:number[, options:Object] )"],["iterawln","iterawln( iterator:Object, sigma:number[, options:Object] )"],["iterawun","iterawun( iterator:Object, sigma:number[, options:Object] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options:Object] )"],["iterBartlettPulse","iterBartlettPulse( [options:Object] )"],["iterBesselj0","iterBesselj0( iterator:Object )"],["iterBesselj1","iterBesselj1( iterator:Object )"],["iterBessely0","iterBessely0( iterator:Object )"],["iterBessely1","iterBessely1( iterator:Object )"],["iterBeta","iterBeta( x:Object|number, y:Object|number )"],["iterBetaln","iterBetaln( x:Object|number, y:Object|number )"],["iterBinet","iterBinet( iterator:Object )"],["iterCbrt","iterCbrt( iterator:Object )"],["iterCeil","iterCeil( iterator:Object )"],["iterCeil2","iterCeil2( iterator:Object )"],["iterCeil10","iterCeil10( iterator:Object )"],["iterCompositesSeq","iterCompositesSeq( [options:Object] )"],["iterConcat","iterConcat( iter0:Object, ...iterator:Object )"],["iterConstant","iterConstant( value:any[, options:Object] )"],["iterContinuedFraction","iterContinuedFraction( iterator:Object[, options:Object] )"],["iterContinuedFractionSeq","iterContinuedFractionSeq( x:number[, options:Object] )"],["iterCos","iterCos( iterator:Object )"],["iterCosh","iterCosh( iterator:Object )"],["iterCosineWave","iterCosineWave( [options:Object] )"],["iterCosm1","iterCosm1( iterator:Object )"],["iterCospi","iterCospi( iterator:Object )"],["iterCounter","iterCounter( iterator:Object )"],["iterCovercos","iterCovercos( iterator:Object )"],["iterCoversin","iterCoversin( iterator:Object )"],["iterCubesSeq","iterCubesSeq( [options:Object] )"],["itercugmean","itercugmean( iterator:Object )"],["itercuhmean","itercuhmean( iterator:Object )"],["itercumax","itercumax( iterator:Object )"],["itercumaxabs","itercumaxabs( iterator:Object )"],["itercumean","itercumean( iterator:Object )"],["itercumeanabs","itercumeanabs( iterator:Object )"],["itercumeanabs2","itercumeanabs2( iterator:Object )"],["itercumidrange","itercumidrange( iterator:Object )"],["itercumin","itercumin( iterator:Object )"],["itercuminabs","itercuminabs( iterator:Object )"],["itercuprod","itercuprod( iterator:Object )"],["itercurange","itercurange( iterator:Object )"],["itercusum","itercusum( iterator:Object )"],["itercusumabs","itercusumabs( iterator:Object )"],["itercusumabs2","itercusumabs2( iterator:Object )"],["iterDatespace","iterDatespace( start:integer|string|Date, stop:integer|string|Date[, N:integer][, options:Object] )"],["iterDedupe","iterDedupe( iterator:Object[, limit:integer] )"],["iterDedupeBy","iterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )"],["iterDeg2rad","iterDeg2rad( iterator:Object )"],["iterDigamma","iterDigamma( iterator:Object )"],["iterDiracComb","iterDiracComb( [options:Object] )"],["iterDiracDelta","iterDiracDelta( iterator:Object )"],["iterDivide","iterDivide( iter0:Object, ...iterator:Object )"],["iterDoUntilEach","iterDoUntilEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterDoWhileEach","iterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterEllipe","iterEllipe( iterator:Object )"],["iterEllipk","iterEllipk( iterator:Object )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator:Object )"],["iterErfc","iterErfc( iterator:Object )"],["iterErfcinv","iterErfcinv( iterator:Object )"],["iterErfinv","iterErfinv( iterator:Object )"],["iterEta","iterEta( iterator:Object )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options:Object] )"],["iterEvery","iterEvery( iterator:Object )"],["iterEveryBy","iterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterExp","iterExp( iterator:Object )"],["iterExp2","iterExp2( iterator:Object )"],["iterExp10","iterExp10( iterator:Object )"],["iterExpit","iterExpit( iterator:Object )"],["iterExpm1","iterExpm1( iterator:Object )"],["iterExpm1rel","iterExpm1rel( iterator:Object )"],["iterFactorial","iterFactorial( iterator:Object )"],["iterFactorialln","iterFactorialln( iterator:Object )"],["iterFactorialsSeq","iterFactorialsSeq( [options:Object] )"],["iterFibonacciSeq","iterFibonacciSeq( [options:Object] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options:Object] )"],["iterFill","iterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )"],["iterFilter","iterFilter( iterator:Object, predicate:Function[, thisArg:any] )"],["iterFilterMap","iterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFirst","iterFirst( iterator:Object )"],["iterFlatTopPulse","iterFlatTopPulse( [options:Object] )"],["iterFloor","iterFloor( iterator:Object )"],["iterFloor2","iterFloor2( iterator:Object )"],["iterFloor10","iterFloor10( iterator:Object )"],["iterFlow","iterFlow( methods:Object )"],["iterForEach","iterForEach( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options:Object] )"],["iterFresnelc","iterFresnelc( iterator:Object )"],["iterFresnels","iterFresnels( iterator:Object )"],["iterGamma","iterGamma( iterator:Object )"],["iterGamma1pm1","iterGamma1pm1( iterator:Object )"],["iterGammaln","iterGammaln( iterator:Object )"],["iterHacovercos","iterHacovercos( iterator:Object )"],["iterHacoversin","iterHacoversin( iterator:Object )"],["iterHannPulse","iterHannPulse( [options:Object] )"],["iterHavercos","iterHavercos( iterator:Object )"],["iterHaversin","iterHaversin( iterator:Object )"],["iterHead","iterHead( iterator:Object, n:integer )"],["iterIncrspace","iterIncrspace( start:number, stop:number[, increment:number] )"],["iterIntegersSeq","iterIntegersSeq( [options:Object] )"],["iterIntersection","iterIntersection( iter0:Object, ...iterator:Object )"],["iterIntersectionByHash","iterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, thisArg:any] )"],["iterInv","iterInv( iterator:Object )"],["iterLanczosPulse","iterLanczosPulse( [options:Object] )"],["iterLast","iterLast( iterator:Object )"],["iterLength","iterLength( iterator:Object )"],["iterLinspace","iterLinspace( start:number, stop:number[, N:integer] )"],["iterLn","iterLn( iterator:Object )"],["iterLog","iterLog( x:Object|number, b:Object|number )"],["iterLog1mexp","iterLog1mexp( iterator:Object )"],["iterLog1p","iterLog1p( iterator:Object )"],["iterLog1pexp","iterLog1pexp( iterator:Object )"],["iterLog2","iterLog2( iterator:Object )"],["iterLog10","iterLog10( iterator:Object )"],["iterLogit","iterLogit( iterator:Object )"],["iterLogspace","iterLogspace( start:number, stop:number[, N:integer][, options:Object] )"],["iterLucasSeq","iterLucasSeq( [options:Object] )"],["iterMap","iterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterMapN","iterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )"],["itermax","itermax( iterator:Object )"],["itermaxabs","itermaxabs( iterator:Object )"],["itermean","itermean( iterator:Object )"],["itermeanabs","itermeanabs( iterator:Object )"],["itermeanabs2","itermeanabs2( iterator:Object )"],["itermidrange","itermidrange( iterator:Object )"],["itermin","itermin( iterator:Object )"],["iterminabs","iterminabs( iterator:Object )"],["itermmax","itermmax( iterator:Object, W:integer )"],["itermmaxabs","itermmaxabs( iterator:Object, W:integer )"],["itermmean","itermmean( iterator:Object, W:integer )"],["itermmeanabs","itermmeanabs( iterator:Object, W:integer )"],["itermmeanabs2","itermmeanabs2( iterator:Object, W:integer )"],["itermmidrange","itermmidrange( iterator:Object, W:integer )"],["itermmin","itermmin( iterator:Object, W:integer )"],["itermminabs","itermminabs( iterator:Object, W:integer )"],["iterMod","iterMod( iter0:Object, ...iterator:Object )"],["itermprod","itermprod( iterator:Object, W:integer )"],["itermrange","itermrange( iterator:Object, W:integer )"],["itermsum","itermsum( iterator:Object, W:integer )"],["itermsumabs","itermsumabs( iterator:Object, W:integer )"],["itermsumabs2","itermsumabs2( iterator:Object, W:integer )"],["iterMultiply","iterMultiply( iter0:Object, ...iterator:Object )"],["iterNegaFibonacciSeq","iterNegaFibonacciSeq( [options:Object] )"],["iterNegaLucasSeq","iterNegaLucasSeq( [options:Object] )"],["iterNegativeEvenIntegersSeq","iterNegativeEvenIntegersSeq( [options:Object] )"],["iterNegativeIntegersSeq","iterNegativeIntegersSeq( [options:Object] )"],["iterNegativeOddIntegersSeq","iterNegativeOddIntegersSeq( [options:Object] )"],["iterNone","iterNone( iterator:Object )"],["iterNoneBy","iterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options:Object] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options:Object] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options:Object] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options:Object] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options:Object] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options:Object] )"],["iterNth","iterNth( iterator:Object, n:integer )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options:Object] )"],["iterPeriodicSinc","iterPeriodicSinc( n:integer[, options:Object] )"],["iterPipeline","iterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )"],["iterPop","iterPop( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options:Object] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options:Object] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options:Object] )"],["iterPow","iterPow( base:Object|number, exponent:Object|number )"],["iterPrimesSeq","iterPrimesSeq( [options:Object] )"],["iterprod","iterprod( iterator:Object )"],["iterPulse","iterPulse( [options:Object] )"],["iterPush","iterPush( iterator:Object, ...items:any )"],["iterRad2deg","iterRad2deg( iterator:Object )"],["iterRamp","iterRamp( iterator:Object )"],["iterrange","iterrange( iterator:Object )"],["iterReject","iterReject( iterator:Object, predicate:Function[, thisArg:any] )"],["iterReplicate","iterReplicate( iterator:Object, n:integer )"],["iterReplicateBy","iterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )"],["iterRound","iterRound( iterator:Object )"],["iterRound2","iterRound2( iterator:Object )"],["iterRound10","iterRound10( iterator:Object )"],["iterRsqrt","iterRsqrt( iterator:Object )"],["iterSawtoothWave","iterSawtoothWave( [options:Object] )"],["iterShift","iterShift( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterSignum","iterSignum( iterator:Object )"],["iterSin","iterSin( iterator:Object )"],["iterSinc","iterSinc( iterator:Object )"],["iterSineWave","iterSineWave( [options:Object] )"],["iterSinh","iterSinh( iterator:Object )"],["iterSinpi","iterSinpi( iterator:Object )"],["iterSlice","iterSlice( iterator:Object[, begin:integer[, end:integer]] )"],["iterSome","iterSome( iterator:Object, n:number )"],["iterSomeBy","iterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )"],["iterSpence","iterSpence( iterator:Object )"],["iterSqrt","iterSqrt( iterator:Object )"],["iterSqrt1pm1","iterSqrt1pm1( iterator:Object )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options:Object] )"],["iterSquaresSeq","iterSquaresSeq( [options:Object] )"],["iterSquareWave","iterSquareWave( [options:Object] )"],["iterstdev","iterstdev( iterator:Object[, mean:number] )"],["iterStep","iterStep( start:number, increment:number[, N:number] )"],["iterStrided","iterStrided( iterator:Object, stride:integer[, offset:integer[, eager:boolean]] )"],["iterStridedBy","iterStridedBy( iterator:Object, fcn:Function[, offset:integer[, eager:boolean]][, thisArg:any] )"],["iterSubtract","iterSubtract( iter0:Object, ...iterator:Object )"],["itersum","itersum( iterator:Object )"],["itersumabs","itersumabs( iterator:Object )"],["itersumabs2","itersumabs2( iterator:Object )"],["iterTan","iterTan( iterator:Object )"],["iterTanh","iterTanh( iterator:Object )"],["iterThunk","iterThunk( iterFcn:Function[, ...args:any] )"],["iterTriangleWave","iterTriangleWave( [options:Object] )"],["iterTriangularSeq","iterTriangularSeq( [options:Object] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options:Object] )"],["iterTrigamma","iterTrigamma( iterator:Object 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][options:Object] )"],["random.streams.t.objectMode","random.streams.t.objectMode( v:number[, options:Object] )"],["random.streams.triangular","random.streams.triangular( a:number, b:number, c:number[, options:Object] )"],["random.streams.triangular.factory","random.streams.triangular.factory( [a:number, b:number, c:number, ][options:Object] )"],["random.streams.triangular.objectMode","random.streams.triangular.objectMode( a:number, b:number, c:number[, options:Object] )"],["random.streams.uniform","random.streams.uniform( a:number, b:number[, options:Object] )"],["random.streams.uniform.factory","random.streams.uniform.factory( [a:number, b:number, ][options:Object] )"],["random.streams.uniform.objectMode","random.streams.uniform.objectMode( a:number, b:number[, options:Object] )"],["random.streams.weibull","random.streams.weibull( k:number, λ:number[, options:Object] )"],["random.streams.weibull.factory","random.streams.weibull.factory( [k:number, λ:number, ][options:Object] 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out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.betaprime.ndarray","random.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.chi","random.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, out:ArrayLikeObject, so:integer )"],["random.strided.chi.ndarray","random.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, ok:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.chi.factory","random.strided.chi.factory( [options:Object] 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so:integer, oo:integer[, options:Object] )"],["random.strided.mt19937.normalized","random.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.mt19937.normalized.ndarray","random.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.normal","random.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.normal.ndarray","random.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.poisson","random.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer )"],["random.strided.poisson.ndarray","random.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.poisson.factory","random.strided.poisson.factory( [options:Object] )"],["random.strided.poisson.PRNG","random.strided.poisson.PRNG"],["random.strided.poisson.seed","random.strided.poisson.seed"],["random.strided.poisson.seedLength","random.strided.poisson.seedLength"],["random.strided.poisson.state","random.strided.poisson.state"],["random.strided.poisson.stateLength","random.strided.poisson.stateLength"],["random.strided.poisson.byteLength","random.strided.poisson.byteLength"],["random.strided.randu","random.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.randu.ndarray","random.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.rayleigh","random.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer 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ignoreCase:boolean] )"],["rename","rename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )"],["rename.sync","rename.sync( oldPath:string|Buffer, newPath:string|Buffer )"],["reNativeFunction","reNativeFunction()"],["reNativeFunction.REGEXP","reNativeFunction.REGEXP"],["reorderArguments","reorderArguments( fcn:Function, indices:Array[, thisArg:any] )"],["repeat","repeat( str:string, n:integer )"],["replace","replace( str:string, search:string|RegExp, newval:string|Function )"],["replaceBefore","replaceBefore( str, search, replacement )"],["reRegExp","reRegExp()"],["reRegExp.REGEXP","reRegExp.REGEXP"],["rescape","rescape( str:string )"],["reSemVer","reSemVer()"],["reSemVer.REGEXP","reSemVer.REGEXP"],["resolveParentPath","resolveParentPath( path:string[, options:Object], clbk:Function )"],["resolveParentPath.sync","resolveParentPath.sync( path:string[, options:Object] )"],["resolveParentPathBy","resolveParentPathBy( path:string[, options:Object], predicate:Function, clbk:Function )"],["resolveParentPathBy.sync","resolveParentPathBy.sync( path:string[, options:Object], predicate:Function )"],["reUncPath","reUncPath()"],["reUncPath.REGEXP","reUncPath.REGEXP"],["reUtf16SurrogatePair","reUtf16SurrogatePair()"],["reUtf16SurrogatePair.REGEXP","reUtf16SurrogatePair.REGEXP"],["reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate()"],["reUtf16UnpairedSurrogate.REGEXP","reUtf16UnpairedSurrogate.REGEXP"],["reverseArguments","reverseArguments( fcn:Function[, thisArg:any] )"],["reverseString","reverseString( str:string[, options:Object] )"],["reviveBasePRNG","reviveBasePRNG( key:string, value:any )"],["reviveBuffer","reviveBuffer( key:string, value:any )"],["reviveComplex","reviveComplex( key:string, value:any )"],["reviveComplex64","reviveComplex64( key:string, value:any )"],["reviveComplex128","reviveComplex128( key:string, value:any )"],["reviveError","reviveError( key:string, value:any )"],["reviveRegExp","reviveRegExp( key:string, value:any 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setter:Function )"],["setMemoizedConfigurableReadOnly","setMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )"],["setMemoizedReadOnly","setMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )"],["setNonEnumerableProperty","setNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )"],["setNonEnumerableReadOnly","setNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )"],["setNonEnumerableReadOnlyAccessor","setNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )"],["setNonEnumerableReadWriteAccessor","setNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, setter:Function )"],["setNonEnumerableWriteOnlyAccessor","setNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )"],["setReadOnly","setReadOnly( obj:Object, prop:string|symbol, value:any )"],["setReadOnlyAccessor","setReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function 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[options:Object,] predicate:Function )"],["someInBy","someInBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )"],["someOwnBy","someOwnBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )"],["SOTU","SOTU( [options:Object] )"],["SPACHE_REVISED","SPACHE_REVISED()"],["SPAM_ASSASSIN","SPAM_ASSASSIN()"],["SparklineBase","SparklineBase( [data:ArrayLike|ndarray,] [options:Object] )"],["sparsearray2iterator","sparsearray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )"],["sparsearray2iteratorRight","sparsearray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )"],["splitStream","splitStream( [options:Object] )"],["splitStream.factory","splitStream.factory( [options:Object] )"],["splitStream.objectMode","splitStream.objectMode( [options:Object] 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strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.abs2.ndarray","strided.abs2.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.abs2By","strided.abs2By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.abs2By.ndarray","strided.abs2By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.absBy","strided.absBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.absBy.ndarray","strided.absBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acosBy","strided.acosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acosBy.ndarray","strided.acosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acoshBy","strided.acoshBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acoshBy.ndarray","strided.acoshBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acotBy","strided.acotBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acotBy.ndarray","strided.acotBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acothBy","strided.acothBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acothBy.ndarray","strided.acothBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acovercosBy","strided.acovercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acovercosBy.ndarray","strided.acovercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acoversinBy","strided.acoversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acoversinBy.ndarray","strided.acoversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.add","strided.add( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )"],["strided.add.ndarray","strided.add.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, z:ArrayLikeObject, sz:integer, oz:integer )"],["strided.addBy","strided.addBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, clbk:Function[, thisArg:any] )"],["strided.addBy.ndarray","strided.addBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, thisArg:any] )"],["strided.ahavercosBy","strided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahavercosBy.ndarray","strided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy","strided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy.ndarray","strided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy","strided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy.ndarray","strided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy","strided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy.ndarray","strided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy","strided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy.ndarray","strided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy","strided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy.ndarray","strided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy","strided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy.ndarray","strided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy","strided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy.ndarray","strided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj0By","strided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj0By.ndarray","strided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj1By","strided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj1By.ndarray","strided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely0By","strided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely0By.ndarray","strided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By","strided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By.ndarray","strided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy","strided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy.ndarray","strided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrt","strided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.cbrt.ndarray","strided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.cbrtBy","strided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrtBy.ndarray","strided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ceil","strided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.ceil.ndarray","strided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.cosBy","strided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.cosBy.ndarray","strided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.deg2rad","strided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.deg2rad.ndarray","strided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.dataTypes","strided.dataTypes()"],["strided.dcbrtBy","strided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, sy:integer, clbk:Function[, thisArg:any] )"],["strided.dcbrtBy.ndarray","strided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.dispatch","strided.dispatch( fcns:Function|ArrayLikeObject, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["strided.dispatchBy","strided.dispatchBy( fcns:Function|ArrayLikeObject, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["strided.floor","strided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.floor.ndarray","strided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.inv","strided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.inv.ndarray","strided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.mul","strided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )"],["strided.mul.ndarray","strided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, z:ArrayLikeObject, sz:integer, oz:integer )"],["strided.mulBy","strided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, clbk:Function[, thisArg:any] )"],["strided.mulBy.ndarray","strided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, thisArg:any] )"],["strided.ramp","strided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.ramp.ndarray","strided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.rsqrt","strided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.rsqrt.ndarray","strided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.sinBy","strided.sinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.sinBy.ndarray","strided.sinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.sqrt","strided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.sqrt.ndarray","strided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.sqrtBy","strided.sqrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.sqrtBy.ndarray","strided.sqrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.sub","strided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )"],["strided.sub.ndarray","strided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, z:ArrayLikeObject, sz:integer, oz:integer )"],["strided.subBy","strided.subBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, clbk:Function[, thisArg:any] )"],["strided.subBy.ndarray","strided.subBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, thisArg:any] )"],["strided.trunc","strided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.trunc.ndarray","strided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["stridedarray2iterator","stridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, offset:integer[, mapFcn:Function[, thisArg:any]] )"],["stridedArrayStream","stridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, offset:integer[, options:Object] )"],["stridedArrayStream.factory","stridedArrayStream.factory( [options:Object] )"],["stridedArrayStream.objectMode","stridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, stride:integer, offset:integer[, options:Object] )"],["string2buffer","string2buffer( str:string[, encoding:string] )"],["sub2ind","sub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )"],["substringAfter","substringAfter( str:string, search:string[, fromIndex:integer] )"],["substringAfterLast","substringAfterLast( str:string, search:string[, fromIndex:integer] )"],["substringBefore","substringBefore( str:string, search:string )"],["substringBeforeLast","substringBeforeLast( str:string, search:string )"],["SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()"],["SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()"],["Symbol","Symbol( [description:string] )"],["tabulate","tabulate( collection:Array|TypedArray|Object )"],["tabulateBy","tabulateBy( collection:Array|TypedArray|Object, [options:Object,] indicator:Function )"],["tabulateByAsync","tabulateByAsync( collection:Array|TypedArray|Object, [options:Object,] indicator:Function, done:Function )"],["tabulateByAsync.factory","tabulateByAsync.factory( [options:Object,] indicator:Function )"],["thunk","thunk( fcn:Function[, ...args:any] )"],["tic","tic()"],["timeit","timeit( code:string, [options:Object,] clbk:Function )"],["tmpdir","tmpdir()"],["toc","toc( time:Array )"],["tokenize","tokenize( str:string[, keepWhitespace:boolean] )"],["transformStream","transformStream( [options:Object] )"],["transformStream.factory","transformStream.factory( [options:Object] )"],["transformStream.objectMode","transformStream.objectMode( [options:Object] )"],["transformStream.ctor","transformStream.ctor( [options:Object] )"],["trim","trim( str:string )"],["truncate","truncate( str:string, len:integer[, ending:string] )"],["truncateMiddle","truncateMiddle( str:string, len:integer[, seq:string] )"],["trycatch","trycatch( x:Function, y:any )"],["trycatchAsync","trycatchAsync( x:Function, y:any, done:Function )"],["tryFunction","tryFunction( fcn:Function[, thisArg:any] )"],["tryRequire","tryRequire( id:string )"],["trythen","trythen( x:Function, y:Function )"],["trythenAsync","trythenAsync( x:Function, y:Function, done:Function )"],["ttest","ttest( x:Array[, y:Array][, options:Object] )"],["ttest2","ttest2( x:Array, y:Array[, options:Object] )"],["TWO_PI","TWO_PI"],["typedarray","typedarray( [dtype:string] )"],["typedarray","typedarray( length:integer[, dtype:string] )"],["typedarray","typedarray( typedarray:TypedArray[, dtype:string] )"],["typedarray","typedarray( obj:Object[, dtype:string] )"],["typedarray","typedarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, dtype:string] )"],["typedarray2json","typedarray2json( arr:TypedArray )"],["typedarrayCtors","typedarrayCtors( dtype:string )"],["typedarrayDataTypes","typedarrayDataTypes()"],["typedarraypool","typedarraypool( [dtype:string] 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)"],["typemax","typemax( dtype:string )"],["typemin","typemin( dtype:string )"],["typeOf","typeOf( value:any )"],["UINT8_MAX","UINT8_MAX"],["UINT8_NUM_BYTES","UINT8_NUM_BYTES"],["Uint8Array","Uint8Array()"],["Uint8Array","Uint8Array( length:integer )"],["Uint8Array","Uint8Array( typedarray:TypedArray )"],["Uint8Array","Uint8Array( obj:Object )"],["Uint8Array","Uint8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["Uint8Array.from","Uint8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )"],["Uint8Array.of","Uint8Array.of( element0:number[, element1:number[, ...elementN:number]] 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)"],["Uint8ClampedArray.prototype.map","Uint8ClampedArray.prototype.map( fcn:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.reduce","Uint8ClampedArray.prototype.reduce( fcn:Function[, initialValue:Any] )"],["Uint8ClampedArray.prototype.reduceRight","Uint8ClampedArray.prototype.reduceRight( fcn:Function[, initialValue:Any] )"],["Uint8ClampedArray.prototype.reverse","Uint8ClampedArray.prototype.reverse()"],["Uint8ClampedArray.prototype.set","Uint8ClampedArray.prototype.set( arr:ArrayLike[, offset:integer] )"],["Uint8ClampedArray.prototype.slice","Uint8ClampedArray.prototype.slice( [begin:integer[, end:integer]] )"],["Uint8ClampedArray.prototype.some","Uint8ClampedArray.prototype.some( predicate:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.sort","Uint8ClampedArray.prototype.sort( [compareFunction:Function] )"],["Uint8ClampedArray.prototype.subarray","Uint8ClampedArray.prototype.subarray( [begin:integer[, end:integer]] )"],["Uint8ClampedArray.prototype.toLocaleString","Uint8ClampedArray.prototype.toLocaleString( [locales:string|Array[, options:Object]] )"],["Uint8ClampedArray.prototype.toString","Uint8ClampedArray.prototype.toString()"],["Uint8ClampedArray.prototype.values","Uint8ClampedArray.prototype.values()"],["UINT16_MAX","UINT16_MAX"],["UINT16_NUM_BYTES","UINT16_NUM_BYTES"],["Uint16Array","Uint16Array()"],["Uint16Array","Uint16Array( length:integer )"],["Uint16Array","Uint16Array( typedarray:TypedArray )"],["Uint16Array","Uint16Array( obj:Object )"],["Uint16Array","Uint16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["Uint16Array.from","Uint16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )"],["Uint16Array.of","Uint16Array.of( element0:number[, element1:number[, ...elementN:number]] )"],["Uint16Array.BYTES_PER_ELEMENT","Uint16Array.BYTES_PER_ELEMENT"],["Uint16Array.name","Uint16Array.name"],["Uint16Array.prototype.buffer","Uint16Array.prototype.buffer"],["Uint16Array.prototype.byteLength","Uint16Array.prototype.byteLength"],["Uint16Array.prototype.byteOffset","Uint16Array.prototype.byteOffset"],["Uint16Array.prototype.BYTES_PER_ELEMENT","Uint16Array.prototype.BYTES_PER_ELEMENT"],["Uint16Array.prototype.length","Uint16Array.prototype.length"],["Uint16Array.prototype.copyWithin","Uint16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )"],["Uint16Array.prototype.entries","Uint16Array.prototype.entries()"],["Uint16Array.prototype.every","Uint16Array.prototype.every( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.fill","Uint16Array.prototype.fill( value:number[, start:integer[, end:integer]] )"],["Uint16Array.prototype.filter","Uint16Array.prototype.filter( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.find","Uint16Array.prototype.find( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.findIndex","Uint16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.forEach","Uint16Array.prototype.forEach( fcn:Function[, thisArg:Any] )"],["Uint16Array.prototype.includes","Uint16Array.prototype.includes( searchElement:number[, fromIndex:integer] )"],["Uint16Array.prototype.indexOf","Uint16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )"],["Uint16Array.prototype.join","Uint16Array.prototype.join( [separator:string] )"],["Uint16Array.prototype.keys","Uint16Array.prototype.keys()"],["Uint16Array.prototype.lastIndexOf","Uint16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )"],["Uint16Array.prototype.map","Uint16Array.prototype.map( fcn:Function[, thisArg:Any] )"],["Uint16Array.prototype.reduce","Uint16Array.prototype.reduce( fcn:Function[, initialValue:Any] )"],["Uint16Array.prototype.reduceRight","Uint16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )"],["Uint16Array.prototype.reverse","Uint16Array.prototype.reverse()"],["Uint16Array.prototype.set","Uint16Array.prototype.set( arr:ArrayLike[, offset:integer] )"],["Uint16Array.prototype.slice","Uint16Array.prototype.slice( [begin:integer[, end:integer]] )"],["Uint16Array.prototype.some","Uint16Array.prototype.some( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.sort","Uint16Array.prototype.sort( [compareFunction:Function] )"],["Uint16Array.prototype.subarray","Uint16Array.prototype.subarray( [begin:integer[, end:integer]] )"],["Uint16Array.prototype.toLocaleString","Uint16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )"],["Uint16Array.prototype.toString","Uint16Array.prototype.toString()"],["Uint16Array.prototype.values","Uint16Array.prototype.values()"],["UINT32_MAX","UINT32_MAX"],["UINT32_NUM_BYTES","UINT32_NUM_BYTES"],["Uint32Array","Uint32Array()"],["Uint32Array","Uint32Array( length:integer )"],["Uint32Array","Uint32Array( typedarray:TypedArray )"],["Uint32Array","Uint32Array( obj:Object )"],["Uint32Array","Uint32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["Uint32Array.from","Uint32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )"],["Uint32Array.of","Uint32Array.of( element0:number[, element1:number[, ...elementN:number]] )"],["Uint32Array.BYTES_PER_ELEMENT","Uint32Array.BYTES_PER_ELEMENT"],["Uint32Array.name","Uint32Array.name"],["Uint32Array.prototype.buffer","Uint32Array.prototype.buffer"],["Uint32Array.prototype.byteLength","Uint32Array.prototype.byteLength"],["Uint32Array.prototype.byteOffset","Uint32Array.prototype.byteOffset"],["Uint32Array.prototype.BYTES_PER_ELEMENT","Uint32Array.prototype.BYTES_PER_ELEMENT"],["Uint32Array.prototype.length","Uint32Array.prototype.length"],["Uint32Array.prototype.copyWithin","Uint32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )"],["Uint32Array.prototype.entries","Uint32Array.prototype.entries()"],["Uint32Array.prototype.every","Uint32Array.prototype.every( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.fill","Uint32Array.prototype.fill( value:number[, start:integer[, end:integer]] )"],["Uint32Array.prototype.filter","Uint32Array.prototype.filter( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.find","Uint32Array.prototype.find( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.findIndex","Uint32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.forEach","Uint32Array.prototype.forEach( fcn:Function[, thisArg:Any] )"],["Uint32Array.prototype.includes","Uint32Array.prototype.includes( searchElement:number[, fromIndex:integer] )"],["Uint32Array.prototype.indexOf","Uint32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )"],["Uint32Array.prototype.join","Uint32Array.prototype.join( [separator:string] )"],["Uint32Array.prototype.keys","Uint32Array.prototype.keys()"],["Uint32Array.prototype.lastIndexOf","Uint32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )"],["Uint32Array.prototype.map","Uint32Array.prototype.map( fcn:Function[, thisArg:Any] )"],["Uint32Array.prototype.reduce","Uint32Array.prototype.reduce( fcn:Function[, initialValue:Any] )"],["Uint32Array.prototype.reduceRight","Uint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )"],["Uint32Array.prototype.reverse","Uint32Array.prototype.reverse()"],["Uint32Array.prototype.set","Uint32Array.prototype.set( arr:ArrayLike[, offset:integer] )"],["Uint32Array.prototype.slice","Uint32Array.prototype.slice( [begin:integer[, end:integer]] )"],["Uint32Array.prototype.some","Uint32Array.prototype.some( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.sort","Uint32Array.prototype.sort( [compareFunction:Function] )"],["Uint32Array.prototype.subarray","Uint32Array.prototype.subarray( [begin:integer[, end:integer]] )"],["Uint32Array.prototype.toLocaleString","Uint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )"],["Uint32Array.prototype.toString","Uint32Array.prototype.toString()"],["Uint32Array.prototype.values","Uint32Array.prototype.values()"],["umask","umask( [mask:integer|string,] [options:Object] )"],["uncapitalize","uncapitalize( str:string )"],["uncapitalizeKeys","uncapitalizeKeys( obj:Object )"],["uncurry","uncurry( fcn:Function[, arity:integer, ][thisArg:any] )"],["uncurryRight","uncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )"],["UNICODE_MAX","UNICODE_MAX"],["UNICODE_MAX_BMP","UNICODE_MAX_BMP"],["UnicodeColumnChartSparkline","UnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeLineChartSparkline","UnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeSparkline","UnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeTristateChartSparkline","UnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeUpDownChartSparkline","UnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeWinLossChartSparkline","UnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["unlink","unlink( path:string|Buffer|integer, clbk:Function )"],["unlink.sync","unlink.sync( path:string|Buffer|integer )"],["unshift","unshift( collection:Array|TypedArray|Object, ...items:any )"],["until","until( predicate:Function, fcn:Function[, thisArg:any] )"],["untilAsync","untilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )"],["untilEach","untilEach( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["untilEachRight","untilEachRight( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["unzip","unzip( arr:Array[, idx:Array] )"],["uppercase","uppercase( str:string )"],["uppercaseKeys","uppercaseKeys( obj:Object )"],["US_STATES_ABBR","US_STATES_ABBR()"],["US_STATES_CAPITALS","US_STATES_CAPITALS()"],["US_STATES_CAPITALS_NAMES","US_STATES_CAPITALS_NAMES()"],["US_STATES_NAMES","US_STATES_NAMES()"],["US_STATES_NAMES_CAPITALS","US_STATES_NAMES_CAPITALS()"],["utf16ToUTF8Array","utf16ToUTF8Array( str:string )"],["vartest","vartest( x:Array, y:Array[, options:Object] )"],["waterfall","waterfall( fcns:Array, clbk:Function[, thisArg:any] )"],["waterfall.factory","waterfall.factory( fcns:Array, clbk:Function[, thisArg:any] )"],["WebAssemblyMemory","WebAssemblyMemory( descriptor:Object )"],["WebAssemblyMemory.prototype.buffer","WebAssemblyMemory.prototype.buffer"],["WebAssemblyMemory.prototype.grow","WebAssemblyMemory.prototype.grow( delta:integer )"],["whileAsync","whileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )"],["whileEach","whileEach( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["whileEachRight","whileEachRight( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["whilst","whilst( predicate:Function, fcn:Function[, thisArg:any] )"],["wilcoxon","wilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )"],["writableProperties","writableProperties( value:any )"],["writablePropertiesIn","writablePropertiesIn( value:any )"],["writablePropertyNames","writablePropertyNames( value:any )"],["writablePropertyNamesIn","writablePropertyNamesIn( value:any )"],["writablePropertySymbols","writablePropertySymbols( value:any )"],["writablePropertySymbolsIn","writablePropertySymbolsIn( value:any )"],["writeFile","writeFile( file:string|Buffer|integer, data:string|Buffer[, options:Object|string], clbk:Function )"],["writeFile.sync","writeFile.sync( file:string|Buffer|integer, data:string|Buffer[, options:Object|string] )"],["zip","zip( ...arr:Array[, options:Object] )"],["ztest","ztest( x:Array, sigma:number[, options:Object] )"],["ztest2","ztest2( x:Array, y:Array, sigmax:number, sigmay:number[, options:Object] )"]] diff --git a/lib/node_modules/@stdlib/stats/array/max-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/max-by/benchmark/benchmark.js index b92959577ebc..a8c03148d2f4 100644 --- a/lib/node_modules/@stdlib/stats/array/max-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/max-by/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var maxBy = require( './../lib' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/max/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/max/benchmark/benchmark.js index b30aab77d25d..b8b79c0526eb 100644 --- a/lib/node_modules/@stdlib/stats/array/max/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/max/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var max = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/maxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/maxabs/benchmark/benchmark.js index 8d932f29ccd8..5cb1c750447a 100644 --- a/lib/node_modules/@stdlib/stats/array/maxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/maxabs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var maxabs = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/maxsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/maxsorted/benchmark/benchmark.js index 8e551818dd5d..a2380ad3f8eb 100644 --- a/lib/node_modules/@stdlib/stats/array/maxsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/maxsorted/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var linspace = require( '@stdlib/array/base/linspace' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var maxsorted = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/mean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/mean/benchmark/benchmark.js index c231491a7a41..45e731181575 100644 --- a/lib/node_modules/@stdlib/stats/array/mean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/mean/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mean = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/meankbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/meankbn2/benchmark/benchmark.js index cfdde0f13181..77c82949f415 100644 --- a/lib/node_modules/@stdlib/stats/array/meankbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/meankbn2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meankbn2 = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/meanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/meanors/benchmark/benchmark.js index 8b538502d005..5a484ebea59e 100644 --- a/lib/node_modules/@stdlib/stats/array/meanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/meanors/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanors = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/meanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/meanpn/benchmark/benchmark.js index 01bfda6aebd4..d2738c3c846f 100644 --- a/lib/node_modules/@stdlib/stats/array/meanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/meanpn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanpn = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/meanpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/meanpw/benchmark/benchmark.js index b46a387a02a0..b38dbba0f74e 100644 --- a/lib/node_modules/@stdlib/stats/array/meanpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/meanpw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanpw = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/meanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/meanwd/benchmark/benchmark.js index bc058b3aaf41..148729ed7c90 100644 --- a/lib/node_modules/@stdlib/stats/array/meanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/meanwd/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanwd = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/mediansorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/mediansorted/benchmark/benchmark.js index 6c791c5e9cbb..b0c5edde1c1e 100644 --- a/lib/node_modules/@stdlib/stats/array/mediansorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/mediansorted/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var linspace = require( '@stdlib/array/base/linspace' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mediansorted = require( './../lib' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/minabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/minabs/benchmark/benchmark.js index be57116bd5c9..89df5e99d582 100644 --- a/lib/node_modules/@stdlib/stats/array/minabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/minabs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minabs = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/mskmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/mskmax/benchmark/benchmark.js index a07967d80cef..1443117ec94b 100644 --- a/lib/node_modules/@stdlib/stats/array/mskmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/mskmax/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskmax = require( './../lib' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/mskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/mskmin/benchmark/benchmark.js index 4bf8cd34b8f6..aa9c8e1e6024 100644 --- a/lib/node_modules/@stdlib/stats/array/mskmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/mskmin/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskmin = require( './../lib' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/mskrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/mskrange/benchmark/benchmark.js index c8a2697c663e..081094b8f46d 100644 --- a/lib/node_modules/@stdlib/stats/array/mskrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/mskrange/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskrange = require( './../lib' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanmax-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanmax-by/benchmark/benchmark.js index a531ada5f4c2..8fd745813413 100644 --- a/lib/node_modules/@stdlib/stats/array/nanmax-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanmax-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmaxBy = require( './../lib' ); @@ -114,7 +115,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanmax/benchmark/benchmark.js index 771d84e44b5d..8cdbf0988055 100644 --- a/lib/node_modules/@stdlib/stats/array/nanmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanmax/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmax = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanmaxabs/benchmark/benchmark.js index 9836c0b2863e..4de1bb0e5bed 100644 --- a/lib/node_modules/@stdlib/stats/array/nanmaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanmaxabs/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmaxabs = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanmean/benchmark/benchmark.js index 4b2f96b2fdba..0c289611e8fa 100644 --- a/lib/node_modules/@stdlib/stats/array/nanmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanmean/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmean = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanmeanors/benchmark/benchmark.js index 985076fee0ce..890fc5efe1bc 100644 --- a/lib/node_modules/@stdlib/stats/array/nanmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanmeanors/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmeanors = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanmeanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanmeanpn/benchmark/benchmark.js index 8fe3d93e508c..58f22bd11d6d 100644 --- a/lib/node_modules/@stdlib/stats/array/nanmeanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanmeanpn/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmeanpn = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanmeanwd/benchmark/benchmark.js index 0d43d06b63fa..d0c337ea6fca 100644 --- a/lib/node_modules/@stdlib/stats/array/nanmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanmeanwd/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmeanwd = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanmin-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanmin-by/benchmark/benchmark.js index a69229a0a7a8..fe42840052ae 100644 --- a/lib/node_modules/@stdlib/stats/array/nanmin-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanmin-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanminBy = require( './../lib' ); @@ -114,7 +115,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanmin/benchmark/benchmark.js index 38f9936ece3b..cd9f2200bace 100644 --- a/lib/node_modules/@stdlib/stats/array/nanmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanmin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmin = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanminabs/benchmark/benchmark.js index c57337d5d302..5d1cf82164f5 100644 --- a/lib/node_modules/@stdlib/stats/array/nanminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanminabs/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanminabs = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanmskmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanmskmax/benchmark/benchmark.js index 0496653f7eb6..865af2b254a6 100644 --- a/lib/node_modules/@stdlib/stats/array/nanmskmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanmskmax/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmskmax = require( './../lib' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanmskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanmskmin/benchmark/benchmark.js index 97ea6826b119..22b842138723 100644 --- a/lib/node_modules/@stdlib/stats/array/nanmskmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanmskmin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmskmin = require( './../lib' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanmskrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanmskrange/benchmark/benchmark.js index 3c38a16bc95a..54e846743b5f 100644 --- a/lib/node_modules/@stdlib/stats/array/nanmskrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanmskrange/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmskrange = require( './../lib' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanrange-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanrange-by/benchmark/benchmark.js index a5a3fe70136f..37801ac0f6ab 100644 --- a/lib/node_modules/@stdlib/stats/array/nanrange-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanrange-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanrangeBy = require( './../lib' ); @@ -114,7 +115,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanrange/benchmark/benchmark.js index bd5693a21be5..87697ffd41f6 100644 --- a/lib/node_modules/@stdlib/stats/array/nanrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanrange/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanrange = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanstdev/benchmark/benchmark.js index 7d9ab94fafde..8fc9523a90cd 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanstdev/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdev = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanstdevch/benchmark/benchmark.js index 68e443ad3481..35d02a881960 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevch/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdevch = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanstdevpn/benchmark/benchmark.js index 750cbe8501c4..e93dd40a371c 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanstdevpn/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdevpn = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanstdevtk/benchmark/benchmark.js index 2b3da7febd4c..3096a53ca0ce 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanstdevtk/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdevtk = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanstdevwd/benchmark/benchmark.js index 2bbbb754166f..649ae58f70a2 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanstdevwd/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdevwd = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanstdevyc/benchmark/benchmark.js index c34afcaee25c..c1f556248486 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanstdevyc/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdevyc = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanvariance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanvariance/benchmark/benchmark.js index 2e7f2246bfb7..b46880092b0a 100644 --- a/lib/node_modules/@stdlib/stats/array/nanvariance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanvariance/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvariance = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanvariancech/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanvariancech/benchmark/benchmark.js index 90fd4eb9ff3a..b628f6cebcdd 100644 --- a/lib/node_modules/@stdlib/stats/array/nanvariancech/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanvariancech/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvariancech = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanvariancepn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanvariancepn/benchmark/benchmark.js index c1e9b9b0029f..2706be32b75a 100644 --- a/lib/node_modules/@stdlib/stats/array/nanvariancepn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanvariancepn/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvariancepn = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanvariancetk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanvariancetk/benchmark/benchmark.js index 3bc0c7cb6bb9..a47a4b2f96c8 100644 --- a/lib/node_modules/@stdlib/stats/array/nanvariancetk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanvariancetk/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvariancetk = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanvariancewd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanvariancewd/benchmark/benchmark.js index 2280c04c8151..066d417f14ba 100644 --- a/lib/node_modules/@stdlib/stats/array/nanvariancewd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanvariancewd/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvariancewd = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/nanvarianceyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanvarianceyc/benchmark/benchmark.js index 8a2f1eb004f2..423cdd80ae6a 100644 --- a/lib/node_modules/@stdlib/stats/array/nanvarianceyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/nanvarianceyc/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvarianceyc = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/range-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/range-by/benchmark/benchmark.js index e48ad22cba0d..52f54d045607 100644 --- a/lib/node_modules/@stdlib/stats/array/range-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/range-by/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var rangeBy = require( './../lib' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/range/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/range/benchmark/benchmark.js index 76fb7fad6d5b..8b7d59509025 100644 --- a/lib/node_modules/@stdlib/stats/array/range/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/range/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var range = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/stdevtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/stdevtk/benchmark/benchmark.js index 442fa3e3fead..70c46c9de616 100644 --- a/lib/node_modules/@stdlib/stats/array/stdevtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/stdevtk/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var stdevtk = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/stdevwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/stdevwd/benchmark/benchmark.js index 79d38fff8058..6ed928aad4fb 100644 --- a/lib/node_modules/@stdlib/stats/array/stdevwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/stdevwd/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var stdevwd = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/stdevyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/stdevyc/benchmark/benchmark.js index 45288cdfb633..775bde3a35ad 100644 --- a/lib/node_modules/@stdlib/stats/array/stdevyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/stdevyc/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var stdevyc = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/variance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/variance/benchmark/benchmark.js index d47c1d4ec9e6..6aabb491fa7a 100644 --- a/lib/node_modules/@stdlib/stats/array/variance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/variance/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var variance = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/variancech/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/variancech/benchmark/benchmark.js index d3883a4d0cda..a397df741646 100644 --- a/lib/node_modules/@stdlib/stats/array/variancech/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/variancech/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var variancech = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/variancepn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/variancepn/benchmark/benchmark.js index bc02004e54fc..74dad205401d 100644 --- a/lib/node_modules/@stdlib/stats/array/variancepn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/variancepn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var variancepn = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/variancetk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/variancetk/benchmark/benchmark.js index bb475b400857..6b48577dc6e5 100644 --- a/lib/node_modules/@stdlib/stats/array/variancetk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/variancetk/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var variancetk = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/array/varianceyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/varianceyc/benchmark/benchmark.js index 30d149536e54..375101662fe8 100644 --- a/lib/node_modules/@stdlib/stats/array/varianceyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/array/varianceyc/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var varianceyc = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/bartlett-test/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/bartlett-test/benchmark/benchmark.js index bc725cddbdf1..379e7cebbee1 100644 --- a/lib/node_modules/@stdlib/stats/bartlett-test/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/bartlett-test/benchmark/benchmark.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); var isObject = require( '@stdlib/assert/is-object' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var bartlettTest = require( './../lib' ); @@ -65,7 +66,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::groups', function benchmark( b ) { +bench( format( '%s::groups', pkg ), function benchmark( b ) { var result; var group; var vals; @@ -98,7 +99,7 @@ bench( pkg+'::groups', function benchmark( b ) { b.end(); }); -bench( pkg+':print', function benchmark( b ) { +bench( format( '%s:print', pkg ), function benchmark( b ) { var digits; var result; var output; diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/logcdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/logcdf/benchmark/benchmark.js index ae59fb57b333..0e6b78f70444 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/logcdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/logcdf/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var logcdf = require( './../lib' ); @@ -63,7 +64,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+':factory', function benchmark( b ) { +bench( format( '%s:factory', pkg ), function benchmark( b ) { var mylogcdf; var min; var max; diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/pdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/arcsine/pdf/README.md index 600b61c2d6b1..90e0f92f656e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/pdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/pdf/README.md @@ -164,7 +164,7 @@ logEachMap( 'x: %0.4f, a: %0.4f, b: %0.4f, f(x;a,b): %0.4f', x, a, b, pdf ); Evaluates the probability density function (PDF) for an arcsine distribution. ```c -double out = stdlib_base_dists_arcsine_pdf( 0.5, 0.0, 4.0 ); +double out = stdlib_base_dists_arcsine_pdf( 2.0, 0.0, 4.0 ); // returns ~0.159 ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/quantile/README.md b/lib/node_modules/@stdlib/stats/base/dists/arcsine/quantile/README.md index 3d04a1bf8c9d..d10b493ed4d6 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/quantile/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/quantile/README.md @@ -166,7 +166,7 @@ logEachMap( 'p: %0.4f, a: %0.4f, b: %0.4f, Q(p;a,b): %0.4f', p, a, b, quantile ) Evaluates the quantile function for an arcsine distribution. ```c -double out = quantile( 0.8, 0.0, 1.0 ); +double out = stdlib_base_dists_arcsine_quantile( 0.8, 0.0, 1.0 ); // returns ~0.905 ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/stdev/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/stdev/lib/main.js index 0b3a10605b21..298ff5188ba2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/stdev/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/stdev/lib/main.js @@ -20,8 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var variance = require( '@stdlib/stats/base/dists/bernoulli/variance' ); // MAIN // @@ -49,14 +49,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * // returns NaN */ function stdev( p ) { - if ( - isnan( p ) || - p < 0.0 || - p > 1.0 - ) { - return NaN; - } - return sqrt( ( 1.0-p ) * p ); + return sqrt( variance( p ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/stdev/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/stdev/manifest.json index 546b58881775..0b79e0701b2b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/stdev/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/stdev/manifest.json @@ -39,8 +39,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/unary", - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/bernoulli/variance" ] }, { @@ -55,8 +55,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/bernoulli/variance" ] }, { @@ -71,8 +71,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/bernoulli/variance" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/stdev/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/stdev/src/main.c index 0db3e3c4cf20..c3fd826e4188 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/stdev/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/stdev/src/main.c @@ -17,8 +17,8 @@ */ #include "stdlib/stats/base/dists/bernoulli/stdev.h" -#include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/sqrt.h" +#include "stdlib/stats/base/dists/bernoulli/variance.h" /** * Returns the standard deviation of a Bernoulli distribution. @@ -31,12 +31,5 @@ * // returns ~0.3 */ double stdlib_base_dists_bernoulli_stdev( const double p ) { - if ( - stdlib_base_is_nan( p ) || - p < 0.0 || - p > 1.0 - ) { - return 0.0/0.0; // NaN - } - return stdlib_base_sqrt( ( 1.0-p ) * p ); + return stdlib_base_sqrt( stdlib_base_dists_bernoulli_variance( p ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/lib/main.js index 5dd8e3335c3a..4b6521e6ebd3 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/lib/main.js @@ -20,8 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var variance = require( '@stdlib/stats/base/dists/betaprime/variance' ); // MAIN // @@ -66,17 +66,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * // returns NaN */ function stdev( alpha, beta ) { - var bm1; - if ( - isnan( alpha ) || - alpha <= 0.0 || - isnan( beta ) || - beta <= 2.0 - ) { - return NaN; - } - bm1 = beta - 1.0; - return sqrt( ( alpha * ( alpha + bm1 ) ) / ( ( bm1-1.0 ) * bm1*bm1 ) ); + return sqrt( variance( alpha, beta ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/manifest.json index 481b5c66dce0..0cb4ca897f05 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/manifest.json @@ -39,8 +39,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/binary", - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/betaprime/variance" ] }, { @@ -55,8 +55,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/betaprime/variance" ] }, { @@ -71,8 +71,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/betaprime/variance" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/src/main.c index eb441a49c9e9..f5336402b59f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/src/main.c @@ -17,8 +17,8 @@ */ #include "stdlib/stats/base/dists/betaprime/stdev.h" -#include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/sqrt.h" +#include "stdlib/stats/base/dists/betaprime/variance.h" /** * Returns the standard deviation of a beta prime distribution. @@ -32,15 +32,5 @@ * // returns ~0.866 */ double stdlib_base_dists_betaprime_stdev( const double alpha, const double beta ) { - double bm1; - if ( - stdlib_base_is_nan( alpha ) || - stdlib_base_is_nan( beta ) || - alpha <= 0.0 || - beta <= 2.0 - ) { - return 0.0 / 0.0; // NaN - } - bm1 = beta - 1.0; - return stdlib_base_sqrt( ( alpha * ( alpha + bm1 ) ) / ( ( bm1 - 1.0 ) * bm1 * bm1 ) ); + return stdlib_base_sqrt( stdlib_base_dists_betaprime_variance( alpha, beta ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/stdev/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/binomial/stdev/lib/main.js index adbe9b8fb132..06ec374891f2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/binomial/stdev/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/stdev/lib/main.js @@ -20,10 +20,8 @@ // MODULES // -var isNonNegativeInteger = require( '@stdlib/math/base/assert/is-nonnegative-integer' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); -var PINF = require( '@stdlib/constants/float64/pinf' ); +var variance = require( '@stdlib/stats/base/dists/binomial/variance' ); // MAIN // @@ -56,17 +54,7 @@ var PINF = require( '@stdlib/constants/float64/pinf' ); * // returns NaN */ function stdev( n, p ) { - if ( - isnan( n ) || - isnan( p ) || - p < 0.0 || - p > 1.0 || - !isNonNegativeInteger( n ) || - n === PINF - ) { - return NaN; - } - return sqrt( n * p * ( 1.0 - p ) ); + return sqrt( variance( n, p ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/stdev/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/binomial/stdev/manifest.json index 44a2bc36b3d5..71f4605d7943 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/binomial/stdev/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/stdev/manifest.json @@ -39,8 +39,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/binary", - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/binomial/variance" ] }, { @@ -55,9 +55,9 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/math/base/special/ceil" + "@stdlib/math/base/special/ceil", + "@stdlib/stats/base/dists/binomial/variance" ] }, { @@ -72,9 +72,9 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/math/base/special/ceil" + "@stdlib/math/base/special/ceil", + "@stdlib/stats/base/dists/binomial/variance" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/stdev/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/binomial/stdev/src/main.c index e4a75ab560bf..caa30cda8af2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/binomial/stdev/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/stdev/src/main.c @@ -17,8 +17,8 @@ */ #include "stdlib/stats/base/dists/binomial/stdev.h" -#include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/sqrt.h" +#include "stdlib/stats/base/dists/binomial/variance.h" #include /** @@ -33,13 +33,5 @@ * // returns 3.0 */ double stdlib_base_dists_binomial_stdev( const int32_t n, const double p ) { - if ( - stdlib_base_is_nan( p ) || - n < 0 || - p < 0.0 || - p > 1.0 - ) { - return 0.0 / 0.0; - } - return stdlib_base_sqrt( n * p * (1.0 - p) ); + return stdlib_base_sqrt( stdlib_base_dists_binomial_variance( n, p ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/bradford/stdev/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/bradford/stdev/lib/main.js index f93643b6a1da..dc41d6f22fd1 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bradford/stdev/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bradford/stdev/lib/main.js @@ -20,9 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var ln = require( '@stdlib/math/base/special/ln' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var variance = require( '@stdlib/stats/base/dists/bradford/variance' ); // MAIN // @@ -58,12 +57,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * // returns NaN */ function stdev( c ) { - var k; - if ( isnan( c ) || c <= 0.0 ) { - return NaN; - } - k = ln( 1.0 + c ); - return sqrt( ( ( ( 2.0+c ) * k ) - ( 2.0*c ) ) / ( 2.0*c*k*k ) ); + return sqrt( variance( c ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/bradford/stdev/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/bradford/stdev/manifest.json index 23b9fc7b9b4d..2b12b6554121 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bradford/stdev/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/bradford/stdev/manifest.json @@ -39,9 +39,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/unary", - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/ln", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/bradford/variance" ] }, { @@ -56,9 +55,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/ln", "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/bradford/variance", "@stdlib/constants/float64/eps" ] }, @@ -74,9 +72,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/ln", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/bradford/variance" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dists/bradford/stdev/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/bradford/stdev/src/main.c index 2795f6b970ec..24ccca544d85 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bradford/stdev/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/bradford/stdev/src/main.c @@ -17,9 +17,8 @@ */ #include "stdlib/stats/base/dists/bradford/stdev.h" -#include "stdlib/math/base/assert/is_nan.h" -#include "stdlib/math/base/special/ln.h" #include "stdlib/math/base/special/sqrt.h" +#include "stdlib/stats/base/dists/bradford/variance.h" /** * Returns the standard deviation of a Bradford distribution. @@ -32,10 +31,5 @@ * // returns ~0.288 */ double stdlib_base_dists_bradford_stdev( const double c ) { - double k; - if ( stdlib_base_is_nan( c ) || c <= 0.0 ) { - return 0.0/0.0; // NaN - } - k = stdlib_base_ln( 1.0 + c ); - return stdlib_base_sqrt( ( ( ( 2.0+c ) * k ) - ( 2.0*c ) ) / ( 2.0*c*k*k ) ); + return stdlib_base_sqrt( stdlib_base_dists_bradford_variance( c ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/pdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/cauchy/pdf/README.md index ec7fb2b5e34c..bbeda0ea4399 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cauchy/pdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/pdf/README.md @@ -167,7 +167,7 @@ Evaluates the [probability density function][pdf] (PDF) for a [Cauchy][cauchy-di ```c double out = stdlib_base_dists_cauchy_pdf( 0.5, 0.0, 2.0 ); -// returns ~0.333 +// returns ~0.14979 ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/stats/base/dists/chi/logpdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/chi/logpdf/README.md index b2c58a2e1b24..6afbe6235ab9 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chi/logpdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/chi/logpdf/README.md @@ -169,7 +169,7 @@ Evaluates the natural logarithm of the [probability density function][pdf] (PDF) ```c double out = stdlib_base_dists_chi_logpdf( 2.0, 2.0 ); -// returns ~-1.309 +// returns ~-1.307 ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/stats/base/dists/chi/pdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/chi/pdf/benchmark/benchmark.native.js index 2e8c9a72662d..504e83b7c56b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chi/pdf/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/chi/pdf/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -39,7 +40,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var len; var k; var x; diff --git a/lib/node_modules/@stdlib/stats/base/dists/chi/stdev/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/chi/stdev/lib/main.js index 05d9704cb96d..6b2d9f862301 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chi/stdev/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/chi/stdev/lib/main.js @@ -20,9 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var mean = require( '@stdlib/stats/base/dists/chi/mean' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var variance = require( '@stdlib/stats/base/dists/chi/variance' ); // MAIN // @@ -50,12 +49,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * // returns NaN */ function stdev( k ) { - var mu; - if ( isnan( k ) || k < 0.0 ) { - return NaN; - } - mu = mean( k ); - return sqrt( k - ( mu*mu ) ); + return sqrt( variance( k ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/chi/stdev/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/chi/stdev/manifest.json index e62f2b269ea6..bddde16d3b0c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chi/stdev/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/chi/stdev/manifest.json @@ -39,9 +39,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/unary", - "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/stats/base/dists/chi/mean" + "@stdlib/stats/base/dists/chi/variance" ] }, { @@ -56,9 +55,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/stats/base/dists/chi/mean" + "@stdlib/stats/base/dists/chi/variance" ] }, { @@ -73,9 +71,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/stats/base/dists/chi/mean" + "@stdlib/stats/base/dists/chi/variance" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dists/chi/stdev/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/chi/stdev/src/main.c index a079b32c1956..7fac0e700311 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chi/stdev/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/chi/stdev/src/main.c @@ -16,8 +16,8 @@ * limitations under the License. */ -#include "stdlib/stats/base/dists/chi/mean.h" -#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/stats/base/dists/chi/stdev.h" +#include "stdlib/stats/base/dists/chi/variance.h" #include "stdlib/math/base/special/sqrt.h" /** @@ -31,10 +31,5 @@ * // returns ~0.697 */ double stdlib_base_dists_chi_stdev( const double k ) { - double mu; - if ( stdlib_base_is_nan( k ) || k < 0.0 ) { - return 0.0/0.0; // NaN - } - mu = stdlib_base_dists_chi_mean( k ); - return stdlib_base_sqrt( k - ( mu*mu ) ); + return stdlib_base_sqrt( stdlib_base_dists_chi_variance( k ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/lib/main.js index fe1780bc217b..a03578e6b2de 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/lib/main.js @@ -20,8 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var variance = require( '@stdlib/stats/base/dists/chisquare/variance' ); // MAIN // @@ -49,10 +49,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * // returns NaN */ function stdev( k ) { - if ( isnan( k ) || k < 0.0 ) { - return NaN; - } - return sqrt( 2.0 * k ); + return sqrt( variance( k ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/manifest.json index 92e6eeaf5483..a91f57eb1f09 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/manifest.json @@ -39,8 +39,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/unary", - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/chisquare/variance" ] }, { @@ -55,8 +55,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/chisquare/variance", "@stdlib/constants/float64/eps" ] }, @@ -72,8 +72,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/chisquare/variance" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/src/main.c index bb5fee24982d..925347942f16 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/src/main.c @@ -17,8 +17,8 @@ */ #include "stdlib/stats/base/dists/chisquare/stdev.h" -#include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/sqrt.h" +#include "stdlib/stats/base/dists/chisquare/variance.h" /** * Returns the standard deviation of a chi-squared distribution. @@ -31,8 +31,5 @@ * // returns ~4.243 */ double stdlib_base_dists_chisquare_stdev( const double k ) { - if ( stdlib_base_is_nan( k ) || k < 0.0 ) { - return 0.0/0.0; //NaN - } - return stdlib_base_sqrt( 2.0 * k ); + return stdlib_base_sqrt( stdlib_base_dists_chisquare_variance( k ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/cdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/cdf/README.md index 80b0e6915112..6215b936309f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/cdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/cdf/README.md @@ -192,7 +192,7 @@ for ( i = 0; i < 100; i++ ) { Evaluates the cumulative distribution function (CDF) for a Fréchet distribution with shape `alpha`, scale `s`, and location `m` at a value `x`. ```c -double y = stdlib_base_frechet_cdf( 10.0, 2.0, 3.0, 2.0 ); +double y = stdlib_base_dists_frechet_cdf( 10.0, 2.0, 3.0, 2.0 ); // returns ~0.869 ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/README.md index 5458c78a1b00..b96ebfbfd859 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/README.md @@ -126,23 +126,16 @@ y = entropy( 1.0, -1.0, 2.0 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var EPS = require( '@stdlib/constants/float64/eps' ); var entropy = require( '@stdlib/stats/base/dists/frechet/entropy' ); -var alpha; -var m; -var s; -var y; -var i; - -for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*40.0 ) - 20.0; - y = entropy( alpha, s, m ); - console.log( 'α: %d, s: %d, m: %d, h(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +var alpha = uniform( 10, EPS, 20.0 ); +var s = uniform( 10, EPS, 20.0 ); +var m = uniform( 10, -20.0, 20.0 ); + +logEachMap( 'α: %0.4f, s: %0.4f, m: %0.4f, h(X;α,s,m): %0.4f', alpha, s, m, entropy ); ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/examples/index.js index 5cffdad400eb..d8c433cc6f2c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/examples/index.js @@ -18,20 +18,16 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var EPS = require( '@stdlib/constants/float64/eps' ); var entropy = require( './../lib' ); -var alpha; -var m; -var s; -var y; -var i; +var opts = { + 'dtype': 'float64' +}; +var alpha = uniform( 10, EPS, 20.0, opts ); +var s = uniform( 10, EPS, 20.0, opts ); +var m = uniform( 10, -20.0, 20.0, opts ); -for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*40.0 ) - 20.0; - y = entropy( alpha, s, m ); - console.log( 'α: %d, s: %d, m: %d, h(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +logEachMap( 'α: %0.4f, s: %0.4f, m: %0.4f, h(X;α,s,m): %0.4f', alpha, s, m, entropy ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/README.md index fc5c8af905bf..e69134a37dfd 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/README.md @@ -133,23 +133,19 @@ y = kurtosis( 1.0, -1.0, 2.0 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var EPS = require( '@stdlib/constants/float64/eps' ); var kurtosis = require( '@stdlib/stats/base/dists/frechet/kurtosis' ); -var alpha; -var m; -var s; -var y; -var i; - -for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*40.0 ) - 20.0; - y = kurtosis( alpha, s, m ); - console.log( 'α: %d, s: %d, m: %d, Kurt(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +var opts = { + 'dtype': 'float64' +}; +var alpha = uniform( 10, EPS, 20.0, opts ); +var s = uniform( 10, EPS, 20.0, opts ); +var m = uniform( 10, -20.0, 20.0, opts ); + +logEachMap( 'α: %0.4f, s: %0.4f, m: %0.4f, Kurt(X;α,s,m): %0.4f', alpha, s, m, kurtosis ); ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/examples/index.js index 8aaccb671497..00797f54bb7a 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/examples/index.js @@ -18,20 +18,16 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var EPS = require( '@stdlib/constants/float64/eps' ); var kurtosis = require( './../lib' ); -var alpha; -var m; -var s; -var y; -var i; +var opts = { + 'dtype': 'float64' +}; +var alpha = uniform( 10, EPS, 20.0, opts ); +var s = uniform( 10, EPS, 20.0, opts ); +var m = uniform( 10, -20.0, 20.0, opts ); -for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*40.0 ) - 20.0; - y = kurtosis( alpha, s, m ); - console.log( 'α: %d, s: %d, m: %d, Kurt(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +logEachMap( 'α: %0.4f, s: %0.4f, m: %0.4f, Kurt(X;α,s,m): %0.4f', alpha, s, m, kurtosis ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/logcdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/logcdf/README.md index 18905fa71be1..089ed596f3d2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/logcdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/logcdf/README.md @@ -146,24 +146,19 @@ y = mylogcdf( 7.0 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var logcdf = require( '@stdlib/stats/base/dists/frechet/logcdf' ); -var alpha; -var m; -var s; -var x; -var y; -var i; - -for ( i = 0; i < 100; i++ ) { - alpha = randu() * 10.0; - x = randu() * 10.0; - s = randu() * 10.0; - m = randu() * 10.0; - y = logcdf( x, alpha, s, m ); - console.log( 'x: %d, α: %d, s: %d, m: %d, ln(F(x;α,s,m)): %d', x.toFixed( 4 ), alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +var opts = { + 'dtype': 'float64' +}; +var x = uniform( 100, 0, 10.0, opts ); +var alpha = uniform( 100, 0, 10.0, opts ); +var s = uniform( 100, 0, 10.0, opts ); +var m = uniform( 100, 0, 10.0, opts ); + +logEachMap( 'x: %0.4f, α: %0.4f, s: %0.4f, m: %0.4f, ln(F(x;α,s,m)): %0.4f', x, alpha, s, m, logcdf ); ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/logcdf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/logcdf/examples/index.js index 371a71096003..a0cecc235288 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/logcdf/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/logcdf/examples/index.js @@ -18,21 +18,16 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var logcdf = require( './../lib' ); -var alpha; -var s; -var m; -var x; -var y; -var i; +var opts = { + 'dtype': 'float64' +}; +var x = uniform( 100, 0, 10.0, opts ); +var alpha = uniform( 100, 0, 10.0, opts ); +var s = uniform( 100, 0, 10.0, opts ); +var m = uniform( 100, 0, 10.0, opts ); -for ( i = 0; i < 100; i++ ) { - alpha = randu() * 10.0; - x = randu() * 10.0; - s = randu() * 10.0; - m = randu() * 10.0; - y = logcdf( x, alpha, s, m ); - console.log( 'x: %d, α: %d, s: %d, m: %d, ln(F(x;α,s,m)): %d', x.toFixed( 4 ), alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +logEachMap( 'x: %0.4f, α: %0.4f, s: %0.4f, m: %0.4f, ln(F(x;α,s,m)): %0.4f', x, alpha, s, m, logcdf ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/logpdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/logpdf/README.md index 10ac765b72a5..f43d6bb1c08c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/logpdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/logpdf/README.md @@ -146,24 +146,19 @@ y = mylogpdf( 7.0 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var logpdf = require( '@stdlib/stats/base/dists/frechet/logpdf' ); -var alpha; -var m; -var s; -var x; -var y; -var i; - -for ( i = 0; i < 100; i++ ) { - alpha = randu() * 10.0; - x = randu() * 10.0; - s = randu() * 10.0; - m = randu() * 10.0; - y = logpdf( x, alpha, s, m ); - console.log( 'x: %d, α: %d, s: %d, m: %d, ln(f(x;α,s,m)): %d', x.toFixed( 4 ), alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +var opts = { + 'dtype': 'float64' +}; +var x = uniform( 100, 0, 10.0, opts ); +var alpha = uniform( 100, 0, 10.0, opts ); +var s = uniform( 100, 0, 10.0, opts ); +var m = uniform( 100, 0, 10.0, opts ); + +logEachMap( 'x: %0.4f, α: %0.4f, s: %0.4f, m: %0.4f, ln(f(x;α,s,m)): %0.4f', x, alpha, s, m, logpdf ); ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/logpdf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/logpdf/examples/index.js index b12e919de7d9..94ac5270ea63 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/logpdf/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/logpdf/examples/index.js @@ -18,21 +18,16 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var logpdf = require( './../lib' ); -var alpha; -var s; -var m; -var x; -var y; -var i; +var opts = { + 'dtype': 'float64' +}; +var x = uniform( 100, 0, 10.0, opts ); +var alpha = uniform( 100, 0, 10.0, opts ); +var s = uniform( 100, 0, 10.0, opts ); +var m = uniform( 100, 0, 10.0, opts ); -for ( i = 0; i < 100; i++ ) { - alpha = randu() * 10.0; - x = randu() * 10.0; - s = randu() * 10.0; - m = randu() * 10.0; - y = logpdf( x, alpha, s, m ); - console.log( 'x: %d, α: %d, s: %d, m: %d, ln(f(x;α,s,m)): %d', x.toFixed( 4 ), alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +logEachMap( 'x: %0.4f, α: %0.4f, s: %0.4f, m: %0.4f, ln(f(x;α,s,m)): %0.4f', x, alpha, s, m, logpdf ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/README.md index a3ab15f15b8c..c8f6527aa9ef 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/README.md @@ -126,23 +126,19 @@ y = mean( 1.0, -1.0, 2.0 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var EPS = require( '@stdlib/constants/float64/eps' ); var mean = require( '@stdlib/stats/base/dists/frechet/mean' ); -var alpha; -var m; -var s; -var y; -var i; - -for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*40.0 ) - 20.0; - y = mean( alpha, s, m ); - console.log( 'α: %d, s: %d, m: %d, E(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +var opts = { + 'dtype': 'float64' +}; +var alpha = uniform( 10, EPS, 20.0, opts ); +var m = uniform( 10, -20.0, 20.0, opts ); +var s = uniform( 10, EPS, 20.0, opts ); + +logEachMap( 'α: %0.4f, s: %0.4f, m: %0.4f, E(X;α,s,m): %0.4f', alpha, s, m, mean ); ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/examples/index.js index 854f3546d4fb..affb8d6cd356 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/examples/index.js @@ -18,20 +18,16 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var EPS = require( '@stdlib/constants/float64/eps' ); var mean = require( './../lib' ); -var alpha; -var m; -var s; -var y; -var i; +var opts = { + 'dtype': 'float64' +}; +var alpha = uniform( 10, EPS, 20.0, opts ); +var m = uniform( 10, -20.0, 20.0, opts ); +var s = uniform( 10, EPS, 20.0, opts ); -for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*40.0 ) - 20.0; - y = mean( alpha, s, m ); - console.log( 'α: %d, s: %d, m: %d, E(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +logEachMap( 'α: %0.4f, s: %0.4f, m: %0.4f, E(X;α,s,m): %0.4f', alpha, s, m, mean ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/median/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/median/README.md index 11a3e5a85135..b21a29d0d689 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/median/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/median/README.md @@ -124,23 +124,19 @@ y = median( 1.0, -1.0, 2.0 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var EPS = require( '@stdlib/constants/float64/eps' ); var median = require( '@stdlib/stats/base/dists/frechet/median' ); -var alpha; -var m; -var s; -var y; -var i; - -for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*40.0 ) - 20.0; - y = median( alpha, s, m ); - console.log( 'α: %d, s: %d, m: %d, Median(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +var opts = { + 'dtype': 'float64' +}; +var alpha = uniform( 10, EPS, 20.0, opts ); +var s = uniform( 10, EPS, 20.0, opts ); +var m = uniform( 10, -20.0, 20.0, opts ); + +logEachMap( 'α: %0.4f, s: %0.4f, m: %0.4f, Median(X;α,s,m): %0.4f', alpha, s, m, median ); ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/median/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/median/examples/index.js index d744e31af374..2f7c26d89b33 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/median/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/median/examples/index.js @@ -18,20 +18,16 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var EPS = require( '@stdlib/constants/float64/eps' ); var median = require( './../lib' ); -var alpha; -var m; -var s; -var y; -var i; +var opts = { + 'dtype': 'float64' +}; +var alpha = uniform( 10, EPS, 20.0, opts ); +var s = uniform( 10, EPS, 20.0, opts ); +var m = uniform( 10, -20.0, 20.0, opts ); -for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*40.0 ) - 20.0; - y = median( alpha, s, m ); - console.log( 'α: %d, s: %d, m: %d, Median(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +logEachMap( 'α: %0.4f, s: %0.4f, m: %0.4f, Median(X;α,s,m): %0.4f', alpha, s, m, median ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/README.md index 222b97406d5a..9821123acd4e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/README.md @@ -124,23 +124,19 @@ y = mode( 1.0, -1.0, 2.0 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var EPS = require( '@stdlib/constants/float64/eps' ); var mode = require( '@stdlib/stats/base/dists/frechet/mode' ); -var alpha; -var m; -var s; -var y; -var i; - -for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*40.0 ) - 20.0; - y = mode( alpha, s, m ); - console.log( 'α: %d, s: %d, m: %d, mode(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +var opts = { + 'dtype': 'float64' +}; +var alpha = uniform( 10, EPS, 20.0, opts ); +var s = uniform( 10, EPS, 20.0, opts ); +var m = uniform( 10, -20.0, 20.0, opts ); + +logEachMap( 'α: %0.4f, s: %0.4f, m: %0.4f, mode(X;α,s,m): %0.4f', alpha, s, m, mode ); ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/examples/index.js index bbf6f3612b63..d569a3a4862d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/examples/index.js @@ -18,20 +18,16 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var EPS = require( '@stdlib/constants/float64/eps' ); var mode = require( './../lib' ); -var alpha; -var m; -var s; -var y; -var i; +var opts = { + 'dtype': 'float64' +}; +var alpha = uniform( 10, EPS, 20.0, opts ); +var s = uniform( 10, EPS, 20.0, opts ); +var m = uniform( 10, -20.0, 20.0, opts ); -for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*40.0 ) - 20.0; - y = mode( alpha, s, m ); - console.log( 'α: %d, s: %d, m: %d, mode(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +logEachMap( 'α: %0.4f, s: %0.4f, m: %0.4f, mode(X;α,s,m): %0.4f', alpha, s, m, mode ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/quantile/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/quantile/README.md index 2e76ac88f81b..913dac4519e7 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/quantile/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/quantile/README.md @@ -139,24 +139,19 @@ y = myQuantile( 0.2 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var quantile = require( '@stdlib/stats/base/dists/frechet/quantile' ); -var alpha; -var m; -var s; -var p; -var y; -var i; - -for ( i = 0; i < 100; i++ ) { - alpha = randu() * 10.0; - p = randu(); - s = randu() * 10.0; - m = randu() * 10.0; - y = quantile( p, alpha, s, m ); - console.log( 'x: %d, α: %d, s: %d, m: %d, Q(p;α,s,m): %d', p.toFixed( 4 ), alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +var opts = { + 'dtype': 'float64' +}; +var p = uniform( 100, 0.0, 1.0, opts ); +var alpha = uniform( 100, 0.0, 10.0, opts ); +var s = uniform( 100, 0.0, 10.0, opts ); +var m = uniform( 100, 0.0, 10.0, opts ); + +logEachMap( 'p: %0.4f, α: %0.4f, s: %0.4f, m: %0.4f, Q(p;α,s,m): %0.4f', p, alpha, s, m, quantile ); ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/quantile/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/quantile/examples/index.js index 3c9c2232330e..708bff9490d4 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/quantile/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/quantile/examples/index.js @@ -18,21 +18,16 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var quantile = require( './../lib' ); -var alpha; -var s; -var m; -var p; -var y; -var i; +var opts = { + 'dtype': 'float64' +}; +var alpha = uniform( 100, 0.0, 10.0, opts ); +var s = uniform( 100, 0.0, 10.0, opts ); +var m = uniform( 100, 0.0, 10.0, opts ); +var p = uniform( 100, 0.0, 1.0, opts ); -for ( i = 0; i < 100; i++ ) { - alpha = randu() * 10.0; - p = randu(); - s = randu() * 10.0; - m = randu() * 10.0; - y = quantile( p, alpha, s, m ); - console.log( 'p: %d, α: %d, s: %d, m: %d, Q(p;α,s,m): %d', p.toFixed( 4 ), alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +logEachMap( 'p: %0.4f, α: %0.4f, s: %0.4f, m: %0.4f, Q(p;α,s,m): %0.4f', p, alpha, s, m, quantile ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/README.md index b161391fa019..4e5d69095726 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/README.md @@ -133,23 +133,19 @@ y = skewness( 1.0, -1.0, 2.0 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var EPS = require( '@stdlib/constants/float64/eps' ); var skewness = require( '@stdlib/stats/base/dists/frechet/skewness' ); -var alpha; -var m; -var s; -var y; -var i; - -for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*40.0 ) - 20.0; - y = skewness( alpha, s, m ); - console.log( 'α: %d, s: %d, m: %d, skew(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +var opts = { + 'dtype': 'float64' +}; +var alpha = uniform( 100, EPS, 20.0, opts ); +var s = uniform( 100, EPS, 20.0, opts ); +var m = uniform( 100, -20.0, 20.0, opts ); + +logEachMap( 'α: %0.4f, s: %0.4f, m: %0.4f, skew(X;α,s,m): %0.4f', alpha, s, m, skewness ); ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/examples/index.js index 8df4f0a7ca3f..f18372eb2853 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/examples/index.js @@ -18,20 +18,16 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var EPS = require( '@stdlib/constants/float64/eps' ); var skewness = require( './../lib' ); -var alpha; -var m; -var s; -var y; -var i; +var opts = { + 'dtype': 'float64' +}; +var alpha = uniform( 100, EPS, 20.0, opts ); +var s = uniform( 100, EPS, 20.0, opts ); +var m = uniform( 100, -20.0, 20.0, opts ); -for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*40.0 ) - 20.0; - y = skewness( alpha, s, m ); - console.log( 'α: %d, s: %d, m: %d, skew(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +logEachMap( 'α: %0.4f, s: %0.4f, m: %0.4f, skew(X;α,s,m): %0.4f', alpha, s, m, skewness ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/README.md index c583774348ae..a64f4fa948ba 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/README.md @@ -133,23 +133,19 @@ y = stdev( 1.0, -1.0, 2.0 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var EPS = require( '@stdlib/constants/float64/eps' ); var stdev = require( '@stdlib/stats/base/dists/frechet/stdev' ); -var alpha; -var m; -var s; -var y; -var i; - -for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*40.0 ) - 20.0; - y = stdev( alpha, s, m ); - console.log( 'α: %d, s: %d, m: %d, SD(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +var opts = { + 'dtype': 'float64' +}; +var alpha = uniform( 100, EPS, 20.0, opts ); +var s = uniform( 100, EPS, 20.0, opts ); +var m = uniform( 100, -20.0, 20.0, opts ); + +logEachMap( 'α: %0.4f, s: %0.4f, m: %0.4f, SD(X;α,s,m): %0.4f', alpha, s, m, stdev ); ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/examples/index.js index 98590753689f..b75c233165ef 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/examples/index.js @@ -18,20 +18,16 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var EPS = require( '@stdlib/constants/float64/eps' ); var stdev = require( './../lib' ); -var alpha; -var m; -var s; -var y; -var i; +var opts = { + 'dtype': 'float64' +}; +var alpha = uniform( 100, EPS, 20.0, opts ); +var s = uniform( 100, EPS, 20.0, opts ); +var m = uniform( 100, -20.0, 20.0, opts ); -for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*40.0 ) - 20.0; - y = stdev( alpha, s, m ); - console.log( 'α: %d, s: %d, m: %d, SD(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +logEachMap( 'α: %0.4f, s: %0.4f, m: %0.4f, SD(X;α,s,m): %0.4f', alpha, s, m, stdev ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/README.md index 15ea336d178c..770638c6d506 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/README.md @@ -133,23 +133,19 @@ y = variance( 1.0, -1.0, 2.0 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var EPS = require( '@stdlib/constants/float64/eps' ); var variance = require( '@stdlib/stats/base/dists/frechet/variance' ); -var alpha; -var m; -var s; -var y; -var i; - -for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*40.0 ) - 20.0; - y = variance( alpha, s, m ); - console.log( 'α: %d, s: %d, m: %d, Var(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +var opts = { + 'dtype': 'float64' +}; +var alpha = uniform( 100, EPS, 20.0, opts ); +var s = uniform( 100, EPS, 20.0, opts ); +var m = uniform( 100, -20.0, 20.0, opts ); + +logEachMap( 'α: %0.4f, s: %0.4f, m: %0.4f, Var(X;α,s,m): %0.4f', alpha, s, m, variance ); ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/examples/index.js index fa2d88537322..b392d2bef6d2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/examples/index.js @@ -18,20 +18,16 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); var EPS = require( '@stdlib/constants/float64/eps' ); var variance = require( './../lib' ); -var alpha; -var m; -var s; -var y; -var i; +var opts = { + 'dtype': 'float64' +}; +var alpha = uniform( 100, EPS, 20.0, opts ); +var s = uniform( 100, EPS, 20.0, opts ); +var m = uniform( 100, -20.0, 20.0, opts ); -for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*40.0 ) - 20.0; - y = variance( alpha, s, m ); - console.log( 'α: %d, s: %d, m: %d, Var(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); -} +logEachMap( 'α: %0.4f, s: %0.4f, m: %0.4f, Var(X;α,s,m): %0.4f', alpha, s, m, variance ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/benchmark.native.js index 37c8320033d4..4f5427205048 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var EPS = require( '@stdlib/constants/float64/eps' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -40,7 +41,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var beta; var len; var mu; diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/benchmark/benchmark.js index 64cd5918c14b..8dd66b46a279 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/benchmark/benchmark.js @@ -25,6 +25,7 @@ var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var logcdf = require( './../lib' ); @@ -64,7 +65,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+':factory', function benchmark( b ) { +bench( format( '%s:factory', pkg ), function benchmark( b ) { var mylogcdf; var beta; var len; diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/benchmark/benchmark.native.js index c8ca5229a110..321429d181f5 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -40,7 +41,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var beta; var len; var mu; diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/benchmark/benchmark.js index b10172bbfaec..a5a3c2a66e1f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/benchmark/benchmark.js @@ -25,6 +25,7 @@ var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var logpdf = require( './../lib' ); @@ -64,7 +65,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+':factory', function benchmark( b ) { +bench( format( '%s:factory', pkg ), function benchmark( b ) { var mylogpdf; var beta; var len; diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/benchmark/benchmark.native.js index ae4e7644934f..381a71b05703 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -40,7 +41,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var beta; var len; var mu; diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/median/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/median/benchmark/benchmark.native.js index e62c6b819811..c6e3f65efebf 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/median/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/median/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var EPS = require( '@stdlib/constants/float64/eps' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -39,7 +40,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var beta; var len; var mu; diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/benchmark/benchmark.js index dd31a7ec90f4..b83e176f5027 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/benchmark/benchmark.js @@ -25,6 +25,7 @@ var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mgf = require( './../lib' ); @@ -64,7 +65,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+':factory', function benchmark( b ) { +bench( format( '%s:factory', pkg ), function benchmark( b ) { var mymgf; var beta; var len; diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/benchmark/benchmark.native.js index 37a5bd0cbc67..85b25f6b454c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -40,7 +41,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var beta; var len; var mu; diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/benchmark/benchmark.js index 5bc6a24a4b72..795e76cf360b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/benchmark/benchmark.js @@ -25,6 +25,7 @@ var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var pdf = require( './../lib' ); @@ -64,7 +65,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+':factory', function benchmark( b ) { +bench( format( '%s:factory', pkg ), function benchmark( b ) { var mypdf; var beta; var len; diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/benchmark/benchmark.native.js index 8d6b851bd615..1fee6704169f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -40,7 +41,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var beta; var len; var mu; diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/benchmark/benchmark.js index 4f2b71d9ddc2..162955b80297 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/benchmark/benchmark.js @@ -25,6 +25,7 @@ var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var quantile = require( './../lib' ); @@ -64,7 +65,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+':factory', function benchmark( b ) { +bench( format( '%s:factory', pkg ), function benchmark( b ) { var myquantile; var beta; var len; diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/benchmark/benchmark.native.js index 549756a4559e..3bddb9f7a134 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var tryRequire = require( '@stdlib/utils/try-require' ); var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -40,7 +41,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var beta; var len; var mu; diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/gumbel/skewness/README.md index 1e4afc5caec0..9811d0d49577 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/skewness/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/skewness/README.md @@ -213,7 +213,7 @@ int main( void ) { beta = random_uniform( 0.0, 20.0 ); y = stdlib_base_dists_gumbel_skewness( mu, beta ); printf( "µ: %lf, β: %lf, Skew(X;µ,β): %lf\n", mu, beta, y ); - s} + } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/logpdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/logpdf/README.md index 9ae3317b4d91..03cdcef4bdcb 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/logpdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/logpdf/README.md @@ -20,7 +20,7 @@ limitations under the License. # Logarithm of Probability Density Function -> [Half-Normal][half-normal-distribution] distribution logarithm of [probability density function (PDF)][pdf]. +> [Half-normal][half-normal-distribution] distribution logarithm of [probability density function (PDF)][pdf].
@@ -175,7 +175,7 @@ logEachMap( 'x: %0.4f, σ: %0.4f, ln(f(x;σ)): %0.4f', x, sigma, logpdf ); #### stdlib_base_dists_halfnormal_logpdf( x, sigma ) -Evaluates the logarithm of the [probability density function][pdf] (PDF) for a [Half-Normal][half-normal-distribution] distribution with parameter `sigma` (scale parameter). +Evaluates the logarithm of the [probability density function][pdf] (PDF) for a [half-normal][half-normal-distribution] distribution with parameter `sigma` (scale parameter). ```c double out = stdlib_base_dists_halfnormal_logpdf( 0.8, 1.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/logpdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/logpdf/benchmark/benchmark.js index b419bb58dc9b..d6c60557661b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/logpdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/logpdf/benchmark/benchmark.js @@ -21,11 +21,10 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var Float64Array = require( '@stdlib/array/float64' ); -var uniform = require( '@stdlib/random/base/uniform' ); -var format = require( '@stdlib/string/format' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var logpdf = require( './../lib' ); @@ -40,12 +39,8 @@ bench( pkg, function benchmark( b ) { var i; len = 100; - x = new Float64Array( len ); - sigma = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = uniform( 0.0, 10.0 ); - sigma[ i ] = uniform( EPS, 10.0 ); - } + x = uniform( len, 0.0, 10.0 ); + sigma = uniform( len, EPS, 10.0 ); b.tic(); for ( i = 0; i < b.iterations; i++ ) { @@ -73,10 +68,7 @@ bench( format( '%s:factory', pkg ), function benchmark( b ) { sigma = 4.0; mylogpdf = logpdf.factory( sigma ); len = 100; - x = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = uniform( 0.0, 20.0 ); - } + x = uniform( len, 0.0, 20.0 ); b.tic(); for ( i = 0; i < b.iterations; i++ ) { diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/logpdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/logpdf/benchmark/benchmark.native.js index a0fc9a7fd5b3..7833568a4d65 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/logpdf/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/logpdf/benchmark/benchmark.native.js @@ -22,12 +22,11 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var format = require( '@stdlib/string/format' ); -var Float64Array = require( '@stdlib/array/float64' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var EPS = require( '@stdlib/constants/float64/eps' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -43,18 +42,18 @@ var opts = { bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var sigma; + var uopts; var len; var x; var y; var i; len = 100; - sigma = new Float64Array( len ); - x = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = randu() * 10.0; - sigma[ i ] = ( randu() * 10.0 ) + EPS; - } + uopts = { + 'dtype': 'float64' + }; + x = uniform( len, 0.0, 10.0, uopts ); + sigma = uniform( len, EPS, 10.0, uopts ); b.tic(); for ( i = 0; i < b.iterations; i++ ) { diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/stdev/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/stdev/lib/main.js index 94417c82e2dc..2a06b32d290b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/stdev/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/stdev/lib/main.js @@ -20,9 +20,8 @@ // MODULES // -var isNonNegativeInteger = require( '@stdlib/math/base/assert/is-nonnegative-integer' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); -var PINF = require( '@stdlib/constants/float64/pinf' ); +var variance = require( '@stdlib/stats/base/dists/hypergeometric/variance' ); // MAIN // @@ -72,18 +71,7 @@ var PINF = require( '@stdlib/constants/float64/pinf' ); * // returns NaN */ function stdev( N, K, n ) { - if ( - !isNonNegativeInteger( N ) || - !isNonNegativeInteger( K ) || - !isNonNegativeInteger( n ) || - N === PINF || - K === PINF || - K > N || - n > N - ) { - return NaN; - } - return sqrt( n * ( K/N ) * ( (N-K)/N ) * ( (N-n)/(N-1) ) ); + return sqrt( variance( N, K, n ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/stdev/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/stdev/manifest.json index 4229e8aea358..7329e8956f83 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/stdev/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/stdev/manifest.json @@ -39,7 +39,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/ternary", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/hypergeometric/variance" ] }, { @@ -55,6 +56,7 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/hypergeometric/variance", "@stdlib/math/base/special/ceil" ] }, @@ -71,6 +73,7 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/hypergeometric/variance", "@stdlib/math/base/special/ceil" ] } diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/stdev/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/stdev/src/main.c index 41d0ce981fc2..94443c608b04 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/stdev/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/stdev/src/main.c @@ -18,6 +18,7 @@ #include "stdlib/stats/base/dists/hypergeometric/stdev.h" #include "stdlib/math/base/special/sqrt.h" +#include "stdlib/stats/base/dists/hypergeometric/variance.h" #include /** @@ -33,13 +34,5 @@ * // returns ~0.829 */ double stdlib_base_dists_hypergeometric_stdev( const int32_t N, const int32_t K, const int32_t n ) { - double variance; - double p; - - if ( N < 0 || K < 0 || n < 0 || K > N || n > N ) { - return 0.0/0.0; // NaN - } - p = (double)K / (double)N; - variance = n * p * ( 1.0-p ) * ( (double)(N-n)/(double)(N-1) ); - return stdlib_base_sqrt( variance ); + return stdlib_base_sqrt( stdlib_base_dists_hypergeometric_variance( N, K, n ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/invgamma/ctor/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/invgamma/ctor/benchmark/benchmark.js index 296ca2b33c8e..a70d8bd7f35d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/invgamma/ctor/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/invgamma/ctor/benchmark/benchmark.js @@ -24,13 +24,14 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var InvGamma = require( './../lib' ); // MAIN // -bench( pkg+'::instantiation', function benchmark( b ) { +bench( format( '%s::instantiation', pkg ), function benchmark( b ) { var alpha; var beta; var dist; @@ -58,7 +59,7 @@ bench( pkg+'::instantiation', function benchmark( b ) { b.end(); }); -bench( pkg+'::get:alpha', function benchmark( b ) { +bench( format( '%s::get:alpha', pkg ), function benchmark( b ) { var alpha; var beta; var dist; @@ -84,7 +85,7 @@ bench( pkg+'::get:alpha', function benchmark( b ) { b.end(); }); -bench( pkg+'::set:alpha', function benchmark( b ) { +bench( format( '%s::set:alpha', pkg ), function benchmark( b ) { var alpha; var beta; var dist; @@ -116,7 +117,7 @@ bench( pkg+'::set:alpha', function benchmark( b ) { b.end(); }); -bench( pkg+'::get:beta', function benchmark( b ) { +bench( format( '%s::get:beta', pkg ), function benchmark( b ) { var alpha; var beta; var dist; @@ -142,7 +143,7 @@ bench( pkg+'::get:beta', function benchmark( b ) { b.end(); }); -bench( pkg+'::set:beta', function benchmark( b ) { +bench( format( '%s::set:beta', pkg ), function benchmark( b ) { var alpha; var beta; var dist; @@ -174,7 +175,7 @@ bench( pkg+'::set:beta', function benchmark( b ) { b.end(); }); -bench( pkg+':entropy', function benchmark( b ) { +bench( format( '%s:entropy', pkg ), function benchmark( b ) { var alpha; var beta; var dist; @@ -208,7 +209,7 @@ bench( pkg+':entropy', function benchmark( b ) { b.end(); }); -bench( pkg+':kurtosis', function benchmark( b ) { +bench( format( '%s:kurtosis', pkg ), function benchmark( b ) { var alpha; var beta; var dist; @@ -242,7 +243,7 @@ bench( pkg+':kurtosis', function benchmark( b ) { b.end(); }); -bench( pkg+':mean', function benchmark( b ) { +bench( format( '%s:mean', pkg ), function benchmark( b ) { var alpha; var beta; var dist; @@ -276,7 +277,7 @@ bench( pkg+':mean', function benchmark( b ) { b.end(); }); -bench( pkg+':mode', function benchmark( b ) { +bench( format( '%s:mode', pkg ), function benchmark( b ) { var alpha; var beta; var dist; @@ -310,7 +311,7 @@ bench( pkg+':mode', function benchmark( b ) { b.end(); }); -bench( pkg+':skewness', function benchmark( b ) { +bench( format( '%s:skewness', pkg ), function benchmark( b ) { var alpha; var beta; var dist; @@ -344,7 +345,7 @@ bench( pkg+':skewness', function benchmark( b ) { b.end(); }); -bench( pkg+':stdev', function benchmark( b ) { +bench( format( '%s:stdev', pkg ), function benchmark( b ) { var alpha; var beta; var dist; @@ -378,7 +379,7 @@ bench( pkg+':stdev', function benchmark( b ) { b.end(); }); -bench( pkg+':variance', function benchmark( b ) { +bench( format( '%s:variance', pkg ), function benchmark( b ) { var alpha; var beta; var dist; @@ -412,7 +413,7 @@ bench( pkg+':variance', function benchmark( b ) { b.end(); }); -bench( pkg+':cdf', function benchmark( b ) { +bench( format( '%s:cdf', pkg ), function benchmark( b ) { var alpha; var beta; var dist; @@ -445,7 +446,7 @@ bench( pkg+':cdf', function benchmark( b ) { b.end(); }); -bench( pkg+':logpdf', function benchmark( b ) { +bench( format( '%s:logpdf', pkg ), function benchmark( b ) { var alpha; var beta; var dist; @@ -478,7 +479,7 @@ bench( pkg+':logpdf', function benchmark( b ) { b.end(); }); -bench( pkg+':pdf', function benchmark( b ) { +bench( format( '%s:pdf', pkg ), function benchmark( b ) { var alpha; var beta; var dist; @@ -511,7 +512,7 @@ bench( pkg+':pdf', function benchmark( b ) { b.end(); }); -bench( pkg+':quantile', function benchmark( b ) { +bench( format( '%s:quantile', pkg ), function benchmark( b ) { var alpha; var beta; var dist; diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/stdev/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/stdev/lib/main.js index 4e8b3dde0c0f..8e9a7c69bd21 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/stdev/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/stdev/lib/main.js @@ -20,9 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var beta = require( '@stdlib/math/base/special/beta' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var variance = require( '@stdlib/stats/base/dists/kumaraswamy/variance' ); // MAIN // @@ -63,19 +62,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * // returns NaN */ function stdev( a, b ) { - var m1; - var m2; - if ( - isnan( a ) || - a <= 0.0 || - isnan( b ) || - b <= 0.0 - ) { - return NaN; - } - m1 = b * beta( 1.0 + ( 1.0/a ), b ); - m2 = b * beta( 1.0 + ( 2.0/a ), b ); - return sqrt( m2 - ( m1*m1 ) ); + return sqrt( variance( a, b ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/stdev/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/stdev/manifest.json index f1589a6b3c20..36571ca1e231 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/stdev/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/stdev/manifest.json @@ -39,9 +39,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/binary", - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/beta", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/kumaraswamy/variance" ] }, { @@ -56,9 +55,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/beta", "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/kumaraswamy/variance", "@stdlib/constants/float64/eps" ] }, @@ -74,9 +72,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/beta", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/kumaraswamy/variance" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/stdev/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/stdev/src/main.c index 733a8b3418d0..049be831c014 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/stdev/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/stdev/src/main.c @@ -17,9 +17,8 @@ */ #include "stdlib/stats/base/dists/kumaraswamy/stdev.h" -#include "stdlib/math/base/assert/is_nan.h" -#include "stdlib/math/base/special/beta.h" #include "stdlib/math/base/special/sqrt.h" +#include "stdlib/stats/base/dists/kumaraswamy/variance.h" /** * Returns the standard deviation of a Kumaraswamy's double bounded distribution. @@ -33,18 +32,5 @@ * // returns ~0.298 */ double stdlib_base_dists_kumaraswamy_stdev( const double a, const double b ) { - double m1; - double m2; - if ( - stdlib_base_is_nan( a ) || - a <= 0.0 || - stdlib_base_is_nan( b ) || - b <= 0.0 - ) { - return 0.0/0.0; // NaN - } - m1 = b * stdlib_base_beta( 1.0 + ( 1.0/a ), b ); - m2 = b * stdlib_base_beta( 1.0 + ( 2.0/a ), b ); - return stdlib_base_sqrt( m2 - ( m1*m1 ) ); + return stdlib_base_sqrt( stdlib_base_dists_kumaraswamy_variance( a, b ) ); } - diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mean/README.md b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/README.md index 33eae0f143f5..94e3f51ea147 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/levy/mean/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/README.md @@ -210,8 +210,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - x = random_uniform( -5.0, 5.0 ); - a = random_uniform( 0.0, 20.0 ); + mu = random_uniform( -5.0, 5.0 ); + c = random_uniform( 0.0, 20.0 ); y = stdlib_base_dists_levy_mean( mu, c ); printf( "µ: %lf, c: %lf, E(X;µ,c): %lf\n", mu, c, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/lognormal/stdev/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/lognormal/stdev/lib/main.js index 66e20dfa3ca5..f1d84ec9b454 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/lognormal/stdev/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/lognormal/stdev/lib/main.js @@ -20,9 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); -var exp = require( '@stdlib/math/base/special/exp' ); +var variance = require( '@stdlib/stats/base/dists/lognormal/variance' ); // MAIN // @@ -55,16 +54,7 @@ var exp = require( '@stdlib/math/base/special/exp' ); * // returns NaN */ function stdev( mu, sigma ) { - var s2; - if ( - isnan( mu ) || - isnan( sigma ) || - sigma <= 0.0 - ) { - return NaN; - } - s2 = sigma*sigma; - return sqrt( ( exp( s2 ) - 1.0 ) * exp( ( 2.0*mu ) + s2 ) ); + return sqrt( variance( mu, sigma ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/lognormal/stdev/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/lognormal/stdev/manifest.json index 7a0095b9cd91..4707b240a9d8 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/lognormal/stdev/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/lognormal/stdev/manifest.json @@ -39,9 +39,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/binary", - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/exp", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/lognormal/variance" ] }, { @@ -56,10 +55,9 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", "@stdlib/constants/float64/eps", - "@stdlib/math/base/special/exp", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/lognormal/variance" ] }, { @@ -74,9 +72,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/exp", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/lognormal/variance" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dists/lognormal/stdev/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/lognormal/stdev/src/main.c index 8d344ca711b9..554ccb3f0634 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/lognormal/stdev/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/lognormal/stdev/src/main.c @@ -17,9 +17,8 @@ */ #include "stdlib/stats/base/dists/lognormal/stdev.h" -#include "stdlib/math/base/assert/is_nan.h" -#include "stdlib/math/base/special/exp.h" #include "stdlib/math/base/special/sqrt.h" +#include "stdlib/stats/base/dists/lognormal/variance.h" /** * Returns the standard deviation for a lognormal distribution with location `mu` and scale `sigma`. @@ -33,14 +32,5 @@ * // returns ~2.161 */ double stdlib_base_dists_lognormal_stdev( const double mu, const double sigma ) { - double s2; - if ( - stdlib_base_is_nan( mu ) || - stdlib_base_is_nan( sigma ) || - sigma <= 0.0 - ) { - return 0.0 / 0.0; // NaN - } - s2 = sigma * sigma; - return stdlib_base_sqrt( ( stdlib_base_exp( s2 ) - 1.0 ) * stdlib_base_exp( ( 2.0 * mu ) + s2 ) ); + return stdlib_base_sqrt( stdlib_base_dists_lognormal_variance( mu, sigma ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/normal/logcdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/normal/logcdf/README.md index 6299508c9150..7b1993779b45 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/normal/logcdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/normal/logcdf/README.md @@ -155,7 +155,7 @@ logEachMap( 'x: %0.4f, µ: %0.4f, σ: %0.4f, ln(F(x;µ,σ)): %0.4f', x, mu, sigm Evaluates the natural logarithm of the [cumulative distribution function][cdf] (CDF) for a [normal][normal-distribution] distribution with parameters `mu` (mean) and `sigma` (standard deviation). ```c -double out = stdlib_base_dists_normal_cdf( 2.0, 0.0, 1.0 ); +double out = stdlib_base_dists_normal_logcdf( 2.0, 0.0, 1.0 ); // returns ~-0.023 ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/normal/logpdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/normal/logpdf/README.md index 9af71dfb742e..f5d25ce34bdf 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/normal/logpdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/normal/logpdf/README.md @@ -169,7 +169,7 @@ logEachMap( 'x: %0.4f, µ: %0.4f, σ: %0.4f, ln(f(x;µ,σ)): %0.4f', x, mu, sigm Evaluates the natural logarithm of the probability density function (logPDF) for a normal distribution. ```c -double out = stdlib_base_dists_normal_pdf( 2.0, 0.0, 1.0 ); +double out = stdlib_base_dists_normal_logpdf( 2.0, 0.0, 1.0 ); // returns ~-2.919 ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/stdev/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/stdev/lib/main.js index 79247ac299b5..5f95d04ee006 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/stdev/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/stdev/lib/main.js @@ -20,10 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); -var pow = require( '@stdlib/math/base/special/pow' ); -var PINF = require( '@stdlib/constants/float64/pinf' ); +var variance = require( '@stdlib/stats/base/dists/pareto-type1/variance' ); // MAIN // @@ -64,20 +62,7 @@ var PINF = require( '@stdlib/constants/float64/pinf' ); * // returns NaN */ function stdev( alpha, beta ) { - var out; - if ( - isnan( alpha ) || - alpha <= 0.0 || - isnan( beta ) || - beta <= 0.0 - ) { - return NaN; - } - if ( alpha < 2.0 ) { - return PINF; - } - out = ( (beta*beta) * alpha ) / ( pow( alpha-1.0, 2.0 ) * ( alpha-2.0 ) ); - return sqrt( out ); + return sqrt( variance( alpha, beta ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/stdev/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/stdev/manifest.json index 9e265f4448e4..38db5587a87c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/stdev/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/stdev/manifest.json @@ -39,10 +39,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/binary", - "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/math/base/special/pow", - "@stdlib/constants/float64/pinf" + "@stdlib/stats/base/dists/pareto-type1/variance" ] }, { @@ -57,10 +55,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/math/base/special/pow", - "@stdlib/constants/float64/pinf" + "@stdlib/stats/base/dists/pareto-type1/variance" ] }, { @@ -75,10 +71,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/math/base/special/pow", - "@stdlib/constants/float64/pinf" + "@stdlib/stats/base/dists/pareto-type1/variance" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/stdev/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/stdev/src/main.c index b6ee53700f55..91ba0f54d6c7 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/stdev/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/stdev/src/main.c @@ -17,10 +17,8 @@ */ #include "stdlib/stats/base/dists/pareto-type1/stdev.h" -#include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/sqrt.h" -#include "stdlib/math/base/special/pow.h" -#include "stdlib/constants/float64/pinf.h" +#include "stdlib/stats/base/dists/pareto-type1/variance.h" /** * Returns the standard deviation of a Pareto (Type I) distribution. @@ -34,18 +32,5 @@ * // returns ~5.657 */ double stdlib_base_dists_pareto_type1_stdev( const double alpha, const double beta ) { - double out; - if ( - stdlib_base_is_nan( alpha ) || - alpha <= 0.0 || - stdlib_base_is_nan( beta ) || - beta <= 0.0 - ) { - return 0.0 / 0.0; // NaN - } - if ( alpha < 2.0 ) { - return STDLIB_CONSTANT_FLOAT64_PINF; - } - out = ( ( beta*beta ) * alpha ) / ( stdlib_base_pow( alpha-1.0, 2.0 ) * ( alpha-2.0 ) ); - return stdlib_base_sqrt( out ); + return stdlib_base_sqrt( stdlib_base_dists_pareto_type1_variance( alpha, beta ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/benchmark/benchmark.js index a175b3f99be3..5149f1e9c451 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mgf = require( './../lib' ); @@ -57,7 +58,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+':factory', function benchmark( b ) { +bench( format( '%s:factory', pkg ), function benchmark( b ) { var mymgf; var opts; var t; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/benchmark/benchmark.native.js index 9f8c9cb9e9ce..9fd744e9ed6c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/benchmark/benchmark.native.js @@ -25,6 +25,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -38,7 +39,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var lambda; var opts; var t; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/benchmark/benchmark.native.js index e82fd1657cec..ed4d9073fbbb 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/benchmark/benchmark.native.js @@ -25,6 +25,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -38,7 +39,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var lambda; var opts; var y; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/pmf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/planck/pmf/benchmark/benchmark.js index fee36694810f..1f192071452b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/planck/pmf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/pmf/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var pmf = require( './../lib' ); @@ -58,7 +59,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+':factory', function benchmark( b ) { +bench( format( '%s:factory', pkg ), function benchmark( b ) { var mypmf; var opts; var x; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/pmf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/planck/pmf/benchmark/benchmark.native.js index 2956c7e83acc..2d68deb7ae72 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/planck/pmf/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/pmf/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -39,7 +40,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var lambda; var opts; var x; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/benchmark/benchmark.js index 29bc734fc279..dfb9d36ce7cd 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var quantile = require( './../lib' ); @@ -57,7 +58,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+':factory', function benchmark( b ) { +bench( format( '%s:factory', pkg ), function benchmark( b ) { var myquantile; var opts; var p; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/benchmark/benchmark.native.js index 9d5a37c7d411..9843b6c3b9e8 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/benchmark/benchmark.native.js @@ -25,6 +25,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -38,7 +39,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var lambda; var opts; var p; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/benchmark/benchmark.native.js index aa31fcd45c8f..f3929618083c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/benchmark/benchmark.native.js @@ -25,6 +25,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -38,7 +39,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var lambda; var opts; var y; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/stdev/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/planck/stdev/benchmark/benchmark.native.js index c36f20bfa667..1abe73d8dbbb 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/planck/stdev/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/stdev/benchmark/benchmark.native.js @@ -25,6 +25,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -38,7 +39,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var lambda; var opts; var y; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/variance/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/planck/variance/benchmark/benchmark.native.js index 89923a058b44..4024f9e5b69d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/planck/variance/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/variance/benchmark/benchmark.native.js @@ -25,6 +25,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -38,7 +39,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var lambda; var opts; var y; diff --git a/lib/node_modules/@stdlib/stats/base/dists/poisson/ctor/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/poisson/ctor/benchmark/benchmark.js index 347455749ddf..01d9f74f7198 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/poisson/ctor/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/poisson/ctor/benchmark/benchmark.js @@ -26,13 +26,14 @@ var uniform = require( '@stdlib/random/base/uniform' ); var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Poisson = require( './../lib' ); // MAIN // -bench( pkg+'::instantiation', function benchmark( b ) { +bench( format( '%s::instantiation', pkg ), function benchmark( b ) { var lambda; var dist; var len; @@ -58,7 +59,7 @@ bench( pkg+'::instantiation', function benchmark( b ) { b.end(); }); -bench( pkg+'::get:lambda', function benchmark( b ) { +bench( format( '%s::get:lambda', pkg ), function benchmark( b ) { var lambda; var dist; var y; @@ -81,7 +82,7 @@ bench( pkg+'::get:lambda', function benchmark( b ) { b.end(); }); -bench( pkg+'::set:lambda', function benchmark( b ) { +bench( format( '%s::set:lambda', pkg ), function benchmark( b ) { var lambda; var dist; var len; @@ -110,7 +111,7 @@ bench( pkg+'::set:lambda', function benchmark( b ) { b.end(); }); -bench( pkg+':entropy', function benchmark( b ) { +bench( format( '%s:entropy', pkg ), function benchmark( b ) { var lambda; var dist; var len; @@ -141,7 +142,7 @@ bench( pkg+':entropy', function benchmark( b ) { b.end(); }); -bench( pkg+':kurtosis', function benchmark( b ) { +bench( format( '%s:kurtosis', pkg ), function benchmark( b ) { var lambda; var dist; var len; @@ -172,7 +173,7 @@ bench( pkg+':kurtosis', function benchmark( b ) { b.end(); }); -bench( pkg+':mean', function benchmark( b ) { +bench( format( '%s:mean', pkg ), function benchmark( b ) { var lambda; var dist; var len; @@ -203,7 +204,7 @@ bench( pkg+':mean', function benchmark( b ) { b.end(); }); -bench( pkg+':median', function benchmark( b ) { +bench( format( '%s:median', pkg ), function benchmark( b ) { var lambda; var dist; var len; @@ -234,7 +235,7 @@ bench( pkg+':median', function benchmark( b ) { b.end(); }); -bench( pkg+':mode', function benchmark( b ) { +bench( format( '%s:mode', pkg ), function benchmark( b ) { var lambda; var dist; var len; @@ -265,7 +266,7 @@ bench( pkg+':mode', function benchmark( b ) { b.end(); }); -bench( pkg+':skewness', function benchmark( b ) { +bench( format( '%s:skewness', pkg ), function benchmark( b ) { var lambda; var dist; var len; @@ -296,7 +297,7 @@ bench( pkg+':skewness', function benchmark( b ) { b.end(); }); -bench( pkg+':stdev', function benchmark( b ) { +bench( format( '%s:stdev', pkg ), function benchmark( b ) { var lambda; var dist; var len; @@ -327,7 +328,7 @@ bench( pkg+':stdev', function benchmark( b ) { b.end(); }); -bench( pkg+':variance', function benchmark( b ) { +bench( format( '%s:variance', pkg ), function benchmark( b ) { var lambda; var dist; var len; @@ -358,7 +359,7 @@ bench( pkg+':variance', function benchmark( b ) { b.end(); }); -bench( pkg+':cdf', function benchmark( b ) { +bench( format( '%s:cdf', pkg ), function benchmark( b ) { var lambda; var dist; var len; @@ -388,7 +389,7 @@ bench( pkg+':cdf', function benchmark( b ) { b.end(); }); -bench( pkg+':logpmf', function benchmark( b ) { +bench( format( '%s:logpmf', pkg ), function benchmark( b ) { var lambda; var dist; var len; @@ -418,7 +419,7 @@ bench( pkg+':logpmf', function benchmark( b ) { b.end(); }); -bench( pkg+':mgf', function benchmark( b ) { +bench( format( '%s:mgf', pkg ), function benchmark( b ) { var lambda; var dist; var len; @@ -448,7 +449,7 @@ bench( pkg+':mgf', function benchmark( b ) { b.end(); }); -bench( pkg+':pmf', function benchmark( b ) { +bench( format( '%s:pmf', pkg ), function benchmark( b ) { var lambda; var dist; var len; @@ -478,7 +479,7 @@ bench( pkg+':pmf', function benchmark( b ) { b.end(); }); -bench( pkg+':quantile', function benchmark( b ) { +bench( format( '%s:quantile', pkg ), function benchmark( b ) { var lambda; var dist; var len; diff --git a/lib/node_modules/@stdlib/stats/base/dists/poisson/logpmf/README.md b/lib/node_modules/@stdlib/stats/base/dists/poisson/logpmf/README.md index feb0d40e49ba..60318cdda313 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/poisson/logpmf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/poisson/logpmf/README.md @@ -204,7 +204,7 @@ double stdlib_base_dists_poisson_logpmf( const double x, const double lambda ); ```c #include "stdlib/stats/base/dists/poisson/logpmf.h" -#include "stdlib/random/base/ceil.h" +#include "stdlib/math/base/special/ceil.h" #include #include diff --git a/lib/node_modules/@stdlib/stats/base/dists/poisson/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/poisson/mode/README.md index ac4482aad670..07f3a2892afb 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/poisson/mode/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/poisson/mode/README.md @@ -144,7 +144,7 @@ logEachMap( 'λ: %0.4f, mode(X;λ): %0.4f', lambda, mode ); Returns the mode of a Poisson distribution. ```c -double out = sstdlib_base_dists_poisson_mode( 9.0 ); +double out = stdlib_base_dists_poisson_mode( 9.0 ); // returns 9 ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/poisson/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/poisson/skewness/README.md index 72c66fbccf81..eff87c2596be 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/poisson/skewness/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/poisson/skewness/README.md @@ -144,7 +144,7 @@ logEachMap( 'λ: %0.4f, skew(X;λ): %0.4f', lambda, skewness ); Returns the skewness of a Poisson distribution. ```c -double out = sstdlib_base_dists_poisson_skewness( 9.0 ); +double out = stdlib_base_dists_poisson_skewness( 9.0 ); // returns ~0.33 ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/poisson/stdev/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/poisson/stdev/lib/main.js index ba06b60ec54d..5b21de6dd354 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/poisson/stdev/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/poisson/stdev/lib/main.js @@ -20,8 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var variance = require( '@stdlib/stats/base/dists/poisson/variance' ); // MAIN // @@ -49,10 +49,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * // returns NaN */ function stdev( lambda ) { - if ( isnan( lambda ) || lambda < 0.0 ) { - return NaN; - } - return sqrt( lambda ); + return sqrt( variance( lambda ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/poisson/stdev/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/poisson/stdev/manifest.json index 546b58881775..0b0d3a84753f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/poisson/stdev/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/poisson/stdev/manifest.json @@ -39,8 +39,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/unary", - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/poisson/variance" ] }, { @@ -55,8 +55,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/poisson/variance" ] }, { @@ -71,8 +71,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/poisson/variance" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dists/poisson/stdev/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/poisson/stdev/src/main.c index 80f20f0bb68b..0ace0ea2cd0f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/poisson/stdev/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/poisson/stdev/src/main.c @@ -17,8 +17,8 @@ */ #include "stdlib/stats/base/dists/poisson/stdev.h" -#include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/sqrt.h" +#include "stdlib/stats/base/dists/poisson/variance.h" /** * Returns the standard deviation of a Poisson distribution with parameter `lambda`. @@ -31,11 +31,5 @@ * // returns 3.0 */ double stdlib_base_dists_poisson_stdev( const double lambda ) { - if ( - stdlib_base_is_nan( lambda ) || - lambda < 0.0 - ) { - return 0.0/0.0; // NaN - } - return stdlib_base_sqrt( lambda ); + return stdlib_base_sqrt( stdlib_base_dists_poisson_variance( lambda ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/t/entropy/README.md b/lib/node_modules/@stdlib/stats/base/dists/t/entropy/README.md index 940a5f4cda1c..914834f0b339 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/t/entropy/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/t/entropy/README.md @@ -148,7 +148,7 @@ Returns the differential entropy of a Student's t distribution. ```c double out = stdlib_base_dists_t_entropy( 9.0 ); -// returns ~1.553 +// returns ~1.533 ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/stats/base/dists/t/stdev/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/t/stdev/lib/main.js index 32e893097a7b..5e7267024bcd 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/t/stdev/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/t/stdev/lib/main.js @@ -20,9 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); -var PINF = require( '@stdlib/constants/float64/pinf' ); +var variance = require( '@stdlib/stats/base/dists/t/variance' ); // MAIN // @@ -54,13 +53,7 @@ var PINF = require( '@stdlib/constants/float64/pinf' ); * // returns NaN */ function stdev( v ) { - if ( isnan( v ) || v <= 1.0 ) { - return NaN; - } - if ( v <= 2.0 ) { - return PINF; - } - return sqrt( v / ( v - 2.0 ) ); + return sqrt( variance( v ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/t/stdev/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/t/stdev/manifest.json index 19b4bb84411b..fe212a46d56b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/t/stdev/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/t/stdev/manifest.json @@ -39,9 +39,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/unary", - "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/constants/float64/pinf" + "@stdlib/stats/base/dists/t/variance" ] }, { @@ -56,9 +55,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/constants/float64/pinf" + "@stdlib/stats/base/dists/t/variance" ] }, { @@ -73,9 +71,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/constants/float64/pinf" + "@stdlib/stats/base/dists/t/variance" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dists/t/stdev/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/t/stdev/src/main.c index 12e06afd4f7a..b8cfb20958e7 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/t/stdev/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/t/stdev/src/main.c @@ -17,9 +17,8 @@ */ #include "stdlib/stats/base/dists/t/stdev.h" -#include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/sqrt.h" -#include "stdlib/constants/float64/pinf.h" +#include "stdlib/stats/base/dists/t/variance.h" /** * Returns the standard deviation of a Student's t distribution. @@ -32,11 +31,5 @@ * // returns ~1.134 */ double stdlib_base_dists_t_stdev( const double v ) { - if ( stdlib_base_is_nan( v ) || v <= 1.0 ) { - return 0.0 / 0.0; // NaN - } - if ( v <= 2.0 ) { - return STDLIB_CONSTANT_FLOAT64_PINF; - } - return stdlib_base_sqrt( v / ( v - 2.0 ) ); + return stdlib_base_sqrt( stdlib_base_dists_t_variance( v ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/stdev/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/stdev/lib/main.js index c7012c662b6b..df370a5d0702 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/stdev/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/stdev/lib/main.js @@ -20,8 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var variance = require( '@stdlib/stats/base/dists/triangular/variance' ); // MAIN // @@ -67,15 +67,7 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * // returns NaN */ function stdev( a, b, c ) { - if ( - isnan( a ) || - isnan( b ) || - isnan( c ) || - !( a <= c && c <= b ) - ) { - return NaN; - } - return sqrt( ( (a*a) + (b*b) + (c*c) - (a*b) - (a*c) - (b*c) ) / 18.0 ); + return sqrt( variance( a, b, c ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/stdev/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/triangular/stdev/manifest.json index b050c2ec550f..a1ec01aa013b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/stdev/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/stdev/manifest.json @@ -39,8 +39,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/ternary", - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/triangular/variance" ] }, { @@ -55,8 +55,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/triangular/variance" ] }, { @@ -71,8 +71,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dists/triangular/variance" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/stdev/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/stdev/src/main.c index 61d8a28bf115..b8c00dc2f411 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/stdev/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/stdev/src/main.c @@ -17,8 +17,8 @@ */ #include "stdlib/stats/base/dists/triangular/stdev.h" -#include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/sqrt.h" +#include "stdlib/stats/base/dists/triangular/variance.h" /** * Returns the standard deviation of a triangular distribution. @@ -33,13 +33,5 @@ * // returns ~0.204 */ double stdlib_base_dists_triangular_stdev( const double a, const double b, const double c ) { - if ( - stdlib_base_is_nan( a ) || - stdlib_base_is_nan( b ) || - stdlib_base_is_nan( c ) || - !( a <= c && c <= b ) - ) { - return 0.0/0.0; // NaN - } - return stdlib_base_sqrt( ( ( a*a ) + ( b*b ) + ( c*c ) - ( a*b ) - ( a*c ) - ( b*c ) ) / 18.0 ); + return stdlib_base_sqrt( stdlib_base_dists_triangular_variance( a, b, c ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/uniform/ctor/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/uniform/ctor/benchmark/benchmark.js index e745872c1aa0..36a6a46f63be 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/uniform/ctor/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/uniform/ctor/benchmark/benchmark.js @@ -25,13 +25,14 @@ var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Uniform = require( './../lib' ); // MAIN // -bench( pkg+'::instantiation', function benchmark( bm ) { +bench( format( '%s::instantiation', pkg ), function benchmark( bm ) { var dist; var len; var a; @@ -61,7 +62,7 @@ bench( pkg+'::instantiation', function benchmark( bm ) { bm.end(); }); -bench( pkg+'::get:a', function benchmark( bm ) { +bench( format( '%s::get:a', pkg ), function benchmark( bm ) { var dist; var a; var b; @@ -87,7 +88,7 @@ bench( pkg+'::get:a', function benchmark( bm ) { bm.end(); }); -bench( pkg+'::set:a', function benchmark( bm ) { +bench( format( '%s::set:a', pkg ), function benchmark( bm ) { var dist; var len; var a; @@ -119,7 +120,7 @@ bench( pkg+'::set:a', function benchmark( bm ) { bm.end(); }); -bench( pkg+'::get:b', function benchmark( bm ) { +bench( format( '%s::get:b', pkg ), function benchmark( bm ) { var dist; var a; var b; @@ -145,7 +146,7 @@ bench( pkg+'::get:b', function benchmark( bm ) { bm.end(); }); -bench( pkg+'::set:b', function benchmark( bm ) { +bench( format( '%s::set:b', pkg ), function benchmark( bm ) { var dist; var len; var a; @@ -177,7 +178,7 @@ bench( pkg+'::set:b', function benchmark( bm ) { bm.end(); }); -bench( pkg+':entropy', function benchmark( bm ) { +bench( format( '%s:entropy', pkg ), function benchmark( bm ) { var dist; var len; var a; @@ -211,7 +212,7 @@ bench( pkg+':entropy', function benchmark( bm ) { bm.end(); }); -bench( pkg+':kurtosis', function benchmark( bm ) { +bench( format( '%s:kurtosis', pkg ), function benchmark( bm ) { var dist; var len; var a; @@ -245,7 +246,7 @@ bench( pkg+':kurtosis', function benchmark( bm ) { bm.end(); }); -bench( pkg+':mean', function benchmark( bm ) { +bench( format( '%s:mean', pkg ), function benchmark( bm ) { var dist; var len; var a; @@ -279,7 +280,7 @@ bench( pkg+':mean', function benchmark( bm ) { bm.end(); }); -bench( pkg+':median', function benchmark( bm ) { +bench( format( '%s:median', pkg ), function benchmark( bm ) { var dist; var len; var a; @@ -313,7 +314,7 @@ bench( pkg+':median', function benchmark( bm ) { bm.end(); }); -bench( pkg+':skewness', function benchmark( bm ) { +bench( format( '%s:skewness', pkg ), function benchmark( bm ) { var dist; var len; var a; @@ -347,7 +348,7 @@ bench( pkg+':skewness', function benchmark( bm ) { bm.end(); }); -bench( pkg+':stdev', function benchmark( bm ) { +bench( format( '%s:stdev', pkg ), function benchmark( bm ) { var dist; var len; var a; @@ -381,7 +382,7 @@ bench( pkg+':stdev', function benchmark( bm ) { bm.end(); }); -bench( pkg+':variance', function benchmark( bm ) { +bench( format( '%s:variance', pkg ), function benchmark( bm ) { var dist; var len; var a; @@ -415,7 +416,7 @@ bench( pkg+':variance', function benchmark( bm ) { bm.end(); }); -bench( pkg+':cdf', function benchmark( bm ) { +bench( format( '%s:cdf', pkg ), function benchmark( bm ) { var dist; var len; var a; @@ -448,7 +449,7 @@ bench( pkg+':cdf', function benchmark( bm ) { bm.end(); }); -bench( pkg+':logcdf', function benchmark( bm ) { +bench( format( '%s:logcdf', pkg ), function benchmark( bm ) { var dist; var len; var a; @@ -481,7 +482,7 @@ bench( pkg+':logcdf', function benchmark( bm ) { bm.end(); }); -bench( pkg+':logpdf', function benchmark( bm ) { +bench( format( '%s:logpdf', pkg ), function benchmark( bm ) { var dist; var len; var a; @@ -514,7 +515,7 @@ bench( pkg+':logpdf', function benchmark( bm ) { bm.end(); }); -bench( pkg+':mgf', function benchmark( bm ) { +bench( format( '%s:mgf', pkg ), function benchmark( bm ) { var dist; var len; var a; @@ -547,7 +548,7 @@ bench( pkg+':mgf', function benchmark( bm ) { bm.end(); }); -bench( pkg+':pdf', function benchmark( bm ) { +bench( format( '%s:pdf', pkg ), function benchmark( bm ) { var dist; var len; var a; @@ -580,7 +581,7 @@ bench( pkg+':pdf', function benchmark( bm ) { bm.end(); }); -bench( pkg+':quantile', function benchmark( bm ) { +bench( format( '%s:quantile', pkg ), function benchmark( bm ) { var dist; var len; var a; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/README.md index 8723d51770f2..9b8a87087fc6 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/README.md +++ b/lib/node_modules/@stdlib/stats/base/ndarray/README.md @@ -73,6 +73,7 @@ The namespace exposes the following APIs: - [`dminabs( arrays )`][@stdlib/stats/base/ndarray/dminabs]: compute the minimum absolute value of a one-dimensional double-precision floating-point ndarray. - [`dminsorted( arrays )`][@stdlib/stats/base/ndarray/dminsorted]: compute the minimum value of a sorted one-dimensional double-precision floating-point ndarray. - [`dmskmax( arrays )`][@stdlib/stats/base/ndarray/dmskmax]: calculate the maximum value of a one-dimensional double-precision floating-point ndarray according to a mask. +- [`dmskmaxabs( arrays )`][@stdlib/stats/base/ndarray/dmskmaxabs]: calculate the maximum absolute value of a one-dimensional double-precision floating-point ndarray according to a mask. - [`dmskmin( arrays )`][@stdlib/stats/base/ndarray/dmskmin]: calculate the minimum value of a one-dimensional double-precision floating-point ndarray according to a mask. - [`dmskrange( arrays )`][@stdlib/stats/base/ndarray/dmskrange]: calculate the range of a one-dimensional double-precision floating-point ndarray according to a mask. - [`dnanmax( arrays )`][@stdlib/stats/base/ndarray/dnanmax]: compute the maximum value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values. @@ -86,9 +87,14 @@ The namespace exposes the following APIs: - [`dnanmin( arrays )`][@stdlib/stats/base/ndarray/dnanmin]: compute the minimum value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values. - [`dnanminabs( arrays )`][@stdlib/stats/base/ndarray/dnanminabs]: compute the minimum absolute value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values. - [`dnanmskmax( arrays )`][@stdlib/stats/base/ndarray/dnanmskmax]: compute the maximum value of a double-precision floating-point ndarray according to a mask, ignoring `NaN` values. +- [`dnanmskmaxabs( arrays )`][@stdlib/stats/base/ndarray/dnanmskmaxabs]: compute the maximum absolute value of a double-precision floating-point ndarray according to a mask, ignoring `NaN` values. - [`dnanmskmin( arrays )`][@stdlib/stats/base/ndarray/dnanmskmin]: compute the minimum value of a double-precision floating-point ndarray according to a mask, ignoring `NaN` values. +- [`dnanmskminabs( arrays )`][@stdlib/stats/base/ndarray/dnanmskminabs]: compute the minimum absolute value of a double-precision floating-point ndarray according to a mask, ignoring `NaN` values. - [`dnanmskrange( arrays )`][@stdlib/stats/base/ndarray/dnanmskrange]: calculate the range of a one-dimensional double-precision floating-point ndarray according to a mask, ignoring `NaN` values. - [`dnanrange( arrays )`][@stdlib/stats/base/ndarray/dnanrange]: compute the range of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values. +- [`dnanstdev( arrays )`][@stdlib/stats/base/ndarray/dnanstdev]: calculate the standard deviation of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values. +- [`dnanstdevch( arrays )`][@stdlib/stats/base/ndarray/dnanstdevch]: calculate the standard deviation of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values and using a one-pass trial mean algorithm. +- [`dnanstdevpn( arrays )`][@stdlib/stats/base/ndarray/dnanstdevpn]: calculate the standard deviation of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values and using a two-pass algorithm. - [`drange( arrays )`][@stdlib/stats/base/ndarray/drange]: compute the range of a one-dimensional double-precision floating-point ndarray. - [`drangeabs( arrays )`][@stdlib/stats/base/ndarray/drangeabs]: compute the range of absolute values of a one-dimensional double-precision floating-point ndarray. - [`dstdev( arrays )`][@stdlib/stats/base/ndarray/dstdev]: calculate the standard deviation of a one-dimensional double-precision floating-point ndarray. @@ -135,6 +141,7 @@ The namespace exposes the following APIs: - [`nanmin( arrays )`][@stdlib/stats/base/ndarray/nanmin]: compute the minimum value of a one-dimensional ndarray, ignoring `NaN` values. - [`nanminabs( arrays )`][@stdlib/stats/base/ndarray/nanminabs]: compute the minimum absolute value of a one-dimensional ndarray, ignoring `NaN` values. - [`nanmskmax( arrays )`][@stdlib/stats/base/ndarray/nanmskmax]: calculate the maximum value of a one-dimensional ndarray according to a mask, ignoring `NaN` values. +- [`nanmskmidrange( arrays )`][@stdlib/stats/base/ndarray/nanmskmidrange]: calculate the mid-range of a one-dimensional ndarray according to a mask, ignoring `NaN` values. - [`nanmskmin( arrays )`][@stdlib/stats/base/ndarray/nanmskmin]: calculate the minimum value of a one-dimensional ndarray according to a mask, ignoring `NaN` values. - [`nanmskrange( arrays )`][@stdlib/stats/base/ndarray/nanmskrange]: calculate the range of a one-dimensional ndarray according to a mask, ignoring `NaN` values. - [`nanrangeBy( arrays, clbk[, thisArg ] )`][@stdlib/stats/base/ndarray/nanrange-by]: calculate the range of a one-dimensional ndarray via a callback function, ignoring `NaN` values. @@ -183,7 +190,10 @@ The namespace exposes the following APIs: - [`snanmin( arrays )`][@stdlib/stats/base/ndarray/snanmin]: compute the minimum value of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values. - [`snanminabs( arrays )`][@stdlib/stats/base/ndarray/snanminabs]: compute the minimum absolute value of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values. - [`snanmskmax( arrays )`][@stdlib/stats/base/ndarray/snanmskmax]: calculate the maximum value of a one-dimensional single-precision floating-point ndarray according to a mask, ignoring `NaN` values. +- [`snanmskmaxabs( arrays )`][@stdlib/stats/base/ndarray/snanmskmaxabs]: compute the maximum absolute value of a one-dimensional single-precision floating-point ndarray according to a mask, ignoring `NaN` values. +- [`snanmskmidrange( arrays )`][@stdlib/stats/base/ndarray/snanmskmidrange]: calculate the mid-range of a one-dimensional single-precision floating-point ndarray according to a mask, ignoring `NaN` values. - [`snanmskmin( arrays )`][@stdlib/stats/base/ndarray/snanmskmin]: calculate the minimum value of a one-dimensional single-precision floating-point ndarray according to a mask, ignoring `NaN` values. +- [`snanmskminabs( arrays )`][@stdlib/stats/base/ndarray/snanmskminabs]: compute the minimum absolute value of a one-dimensional single-precision floating-point ndarray according to a mask, ignoring `NaN` values. - [`snanmskrange( arrays )`][@stdlib/stats/base/ndarray/snanmskrange]: calculate the range of a one-dimensional single-precision floating-point ndarray according to a mask, ignoring `NaN` values. - [`snanrange( arrays )`][@stdlib/stats/base/ndarray/snanrange]: compute the range of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values. - [`srange( arrays )`][@stdlib/stats/base/ndarray/srange]: compute the range of a one-dimensional single-precision floating-point ndarray. @@ -204,7 +214,10 @@ The namespace exposes the following APIs: - [`sztest2( arrays )`][@stdlib/stats/base/ndarray/sztest2]: compute a two-sample Z-test for two one-dimensional single-precision floating-point ndarrays. - [`variance( arrays )`][@stdlib/stats/base/ndarray/variance]: calculate the variance of a one-dimensional ndarray. - [`variancech( arrays )`][@stdlib/stats/base/ndarray/variancech]: calculate the variance of a one-dimensional ndarray using a one-pass trial mean algorithm. +- [`variancepn( arrays )`][@stdlib/stats/base/ndarray/variancepn]: calculate the variance of a one-dimensional ndarray using a two-pass algorithm. +- [`variancetk( arrays )`][@stdlib/stats/base/ndarray/variancetk]: calculate the variance of a one-dimensional ndarray using a one-pass textbook algorithm. - [`variancewd( arrays )`][@stdlib/stats/base/ndarray/variancewd]: calculate the variance of a one-dimensional ndarray using Welford's algorithm. +- [`varianceyc( arrays )`][@stdlib/stats/base/ndarray/varianceyc]: calculate the variance of a one-dimensional ndarray using a one-pass algorithm proposed by Youngs and Cramer. - [`ztest( arrays )`][@stdlib/stats/base/ndarray/ztest]: compute a one-sample Z-test for a one-dimensional ndarray. - [`ztest2( arrays )`][@stdlib/stats/base/ndarray/ztest2]: compute a two-sample Z-test for two one-dimensional ndarrays. @@ -305,6 +318,8 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/base/ndarray/dmskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dmskmax +[@stdlib/stats/base/ndarray/dmskmaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dmskmaxabs + [@stdlib/stats/base/ndarray/dmskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dmskmin [@stdlib/stats/base/ndarray/dmskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dmskrange @@ -331,12 +346,22 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/base/ndarray/dnanmskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dnanmskmax +[@stdlib/stats/base/ndarray/dnanmskmaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dnanmskmaxabs + [@stdlib/stats/base/ndarray/dnanmskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dnanmskmin +[@stdlib/stats/base/ndarray/dnanmskminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dnanmskminabs + [@stdlib/stats/base/ndarray/dnanmskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dnanmskrange [@stdlib/stats/base/ndarray/dnanrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dnanrange +[@stdlib/stats/base/ndarray/dnanstdev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dnanstdev + +[@stdlib/stats/base/ndarray/dnanstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dnanstdevch + +[@stdlib/stats/base/ndarray/dnanstdevpn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dnanstdevpn + [@stdlib/stats/base/ndarray/drange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/drange [@stdlib/stats/base/ndarray/drangeabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/drangeabs @@ -429,6 +454,8 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/base/ndarray/nanmskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/nanmskmax +[@stdlib/stats/base/ndarray/nanmskmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/nanmskmidrange + [@stdlib/stats/base/ndarray/nanmskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/nanmskmin [@stdlib/stats/base/ndarray/nanmskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/nanmskrange @@ -525,8 +552,14 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/base/ndarray/snanmskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/snanmskmax +[@stdlib/stats/base/ndarray/snanmskmaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/snanmskmaxabs + +[@stdlib/stats/base/ndarray/snanmskmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/snanmskmidrange + [@stdlib/stats/base/ndarray/snanmskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/snanmskmin +[@stdlib/stats/base/ndarray/snanmskminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/snanmskminabs + [@stdlib/stats/base/ndarray/snanmskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/snanmskrange [@stdlib/stats/base/ndarray/snanrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/snanrange @@ -567,8 +600,14 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/base/ndarray/variancech]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/variancech +[@stdlib/stats/base/ndarray/variancepn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/variancepn + +[@stdlib/stats/base/ndarray/variancetk]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/variancetk + [@stdlib/stats/base/ndarray/variancewd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/variancewd +[@stdlib/stats/base/ndarray/varianceyc]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/varianceyc + [@stdlib/stats/base/ndarray/ztest]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/ztest [@stdlib/stats/base/ndarray/ztest2]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/ztest2 diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/covarmtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/covarmtk/benchmark/benchmark.js index 392cc65ba375..3d64851b6415 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/covarmtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/covarmtk/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var covarmtk = require( './../lib' ); @@ -114,7 +115,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/cumax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/cumax/benchmark/benchmark.js index 7a976761895a..4ce6107e60ca 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/cumax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/cumax/benchmark/benchmark.js @@ -26,6 +26,7 @@ var zeros = require( '@stdlib/array/zeros' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cumax = require( './../lib' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/cumin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/cumin/benchmark/benchmark.js index e49b6ed8f953..5cea0fafdb23 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/cumin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/cumin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var zeros = require( '@stdlib/array/zeros' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cumin = require( './../lib' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmaxabssorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmaxabssorted/benchmark/benchmark.js index a9a2bc2212e0..58fa09a9cfaa 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dmaxabssorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmaxabssorted/benchmark/benchmark.js @@ -25,6 +25,7 @@ var linspace = require( '@stdlib/array/linspace' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmaxabssorted = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmaxsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmaxsorted/benchmark/benchmark.js index 9ceff656c937..1ec55f7eee8e 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dmaxsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmaxsorted/benchmark/benchmark.js @@ -25,6 +25,7 @@ var linspace = require( '@stdlib/array/linspace' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmaxsorted = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanli/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanli/benchmark/benchmark.js index dbfec3f012a0..6932bf5bc737 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanli/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanli/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanli = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/README.md index b9c429f05f8d..bea57671f41b 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/README.md +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/README.md @@ -111,6 +111,154 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/ndarray/dmeanlipw.h" +``` + +#### stdlib_stats_dmeanlipw( arrays ) + +Computes the [arithmetic mean][arithmetic-mean] of a one-dimensional double-precision floating-point ndarray using a one-pass trial mean algorithm with pairwise summation. + +```c +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include + +// Create an ndarray: +const double data[] = { 1.0, 2.0, 3.0, 4.0 }; +int64_t shape[] = { 4 }; +int64_t strides[] = { STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT }; +int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + +struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)data, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes ); + +// Compute the arithmetic mean: +const struct ndarray *arrays[] = { x }; +double v = stdlib_stats_dmeanlipw( arrays ); +// returns 2.5 + +// Free allocated memory: +stdlib_ndarray_free( x ); +``` + +The function accepts the following arguments: + +- **arrays**: `[in] struct ndarray**` list containing a one-dimensional input ndarray. + +```c +double stdlib_stats_dmeanlipw( const struct ndarray *arrays[] ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/ndarray/dmeanlipw.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include + +int main( void ) { + // Create a data buffer: + const double data[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + + // Specify the number of array dimensions: + const int64_t ndims = 1; + + // Specify the array shape: + int64_t shape[] = { 4 }; + + // Specify the array strides: + int64_t strides[] = { 2*STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT }; + + // Specify the byte offset: + const int64_t offset = 0; + + // Specify the array order: + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const int64_t nsubmodes = 1; + + // Create an ndarray: + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x }; + + // Compute the arithmetic mean: + double v = stdlib_stats_dmeanlipw( arrays ); + + // Print the result: + printf( "mean: %lf\n", v ); + + // Free allocated memory: + stdlib_ndarray_free( x ); +} +``` + +
+ + + +
+ + + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/benchmark/benchmark.js index 96bfc5e1c453..80f073a125f1 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/benchmark/benchmark.js @@ -25,8 +25,9 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; -var dmeanlipw = require( './../lib' ); +var dmeanlipw = require( './../lib/main.js' ); // VARIABLES // @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/benchmark/benchmark.native.js new file mode 100644 index 000000000000..bab5d9118692 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/benchmark/benchmark.native.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dmeanlipw = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( dmeanlipw instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var x; + + xbuf = uniform( len, -10.0, 10.0, options ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = dmeanlipw( [ x ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..595ef5ed78d0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/benchmark/c/benchmark.length.c @@ -0,0 +1,185 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/ndarray/dmeanlipw.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include +#include +#include +#include + +#define NAME "dmeanlipw" +#define ITERATIONS 1000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark( int iterations, int len ) { + enum STDLIB_NDARRAY_INDEX_MODE imode; + const struct ndarray *arrays[ 1 ]; + enum STDLIB_NDARRAY_ORDER order; + int8_t submodes[ 1 ]; + int64_t strides[ 1 ]; + int64_t shape[ 1 ]; + int64_t nsubmodes; + struct ndarray *x; + int64_t offset; + double elapsed; + int64_t ndims; + double *data; + double v; + double t; + int i; + + ndims = 1; + shape[ 0 ] = len; + strides[ 0 ] = STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT; + offset = 0; + order = STDLIB_NDARRAY_ROW_MAJOR; + imode = STDLIB_NDARRAY_INDEX_ERROR; + submodes[ 0 ] = imode; + nsubmodes = 1; + + data = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + data[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + // cppcheck-suppress invalidPointerCast + x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + arrays[ 0 ] = x; + + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + v = stdlib_stats_dmeanlipw( arrays ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + stdlib_ndarray_free( x ); + free( data ); + arrays[ 0 ] = NULL; + + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/binding.gyp b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/examples/c/example.c new file mode 100644 index 000000000000..20f658088a2d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/examples/c/example.c @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/ndarray/dmeanlipw.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include + +int main( void ) { + // Create a data buffer: + const double data[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + + // Specify the number of array dimensions: + const int64_t ndims = 1; + + // Specify the array shape: + int64_t shape[] = { 4 }; + + // Specify the array strides: + int64_t strides[] = { 2*STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT }; + + // Specify the byte offset: + const int64_t offset = 0; + + // Specify the array order: + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const int64_t nsubmodes = 1; + + // Create an ndarray: + // cppcheck-suppress invalidPointerCast + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x }; + + // Compute the arithmetic mean: + double v = stdlib_stats_dmeanlipw( arrays ); + + // Print the result: + printf( "mean: %lf\n", v ); + + // Free allocated memory: + stdlib_ndarray_free( x ); +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/include.gypi b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '} arrays - array-like object containing an input ndarray +* @returns {number} arithmetic mean +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Float64Array( [ 1.0, 3.0, 4.0, 2.0 ] ); +* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var v = dmeanlipw( [ x ] ); +* // returns 2.5 +*/ +function dmeanlipw( arrays ) { + var x = arrays[ 0 ]; + return addon( getData( x ), serialize( x ) ); +} + + +// EXPORTS // + +module.exports = dmeanlipw; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/manifest.json b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/manifest.json new file mode 100644 index 000000000000..96a57eb200b6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/manifest.json @@ -0,0 +1,110 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/dmeanlipw", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/base/napi/addon-arguments", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/dmeanlipw", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/dtypes", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders", + "@stdlib/ndarray/base/bytes-per-element" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/dmeanlipw", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/dtypes", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders", + "@stdlib/ndarray/base/bytes-per-element" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/dmeanlipw", + "@stdlib/ndarray/ctor" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/package.json index 44052236fd61..214f84e4b9e1 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/package.json @@ -14,11 +14,15 @@ } ], "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/src/Makefile b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/src/addon.c b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/src/addon.c new file mode 100644 index 000000000000..1e6f25c8e060 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/src/addon.c @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/ndarray/dmeanlipw.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/base/napi/addon_arguments.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/create_double.h" +#include +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 2 ); + + // Process provided arguments: + struct ndarray *arrays[ 1 ]; + napi_value err; + napi_status status = stdlib_ndarray_napi_addon_arguments( env, argv, 2, 1, arrays, &err ); + assert( status == napi_ok ); + if ( err != NULL ) { + status = napi_throw( env, err ); + assert( status == napi_ok ); + return NULL; + } + // Perform computation: + STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_stats_dmeanlipw( arrays ), v ); + + // Free allocated memory: + stdlib_ndarray_free( arrays[ 0 ] ); + arrays[ 0 ] = NULL; + + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/src/main.c b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/src/main.c new file mode 100644 index 000000000000..bb3e1ecc3e2b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/src/main.c @@ -0,0 +1,33 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/ndarray/dmeanlipw.h" +#include "stdlib/stats/strided/dmeanlipw.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/blas/base/shared.h" + +/** +* Computes the arithmetic mean of a one-dimensional double-precision floating-point ndarray using a one-pass trial mean algorithm with pairwise summation. +* +* @param arrays list containing an input ndarray +* @return arithmetic mean +*/ +double stdlib_stats_dmeanlipw( const struct ndarray *arrays[] ) { + const struct ndarray *x = arrays[ 0 ]; + return API_SUFFIX(stdlib_strided_dmeanlipw_ndarray)( stdlib_ndarray_dimension( x, 0 ), (const double *)stdlib_ndarray_data( x ), stdlib_ndarray_stride_elements( x, 0 ), stdlib_ndarray_offset_elements( x ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/test/test.js index f347cdff9d53..fb6911ba8fb5 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/test/test.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/test/test.js @@ -21,27 +21,16 @@ // MODULES // var tape = require( 'tape' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var Float64Array = require( '@stdlib/array/float64' ); -var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); var dmeanlipw = require( './../lib' ); -// FUNCTIONS // +// VARIABLES // -/** -* Returns a one-dimensional ndarray. -* -* @private -* @param {Collection} buffer - underlying data buffer -* @param {NonNegativeInteger} length - number of indexed elements -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - index offset -* @returns {ndarray} one-dimensional ndarray -*/ -function vector( buffer, length, stride, offset ) { - return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); -} +var opts = { + 'skip': IS_BROWSER +}; // TESTS // @@ -52,113 +41,37 @@ tape( 'main export is a function', function test( t ) { t.end(); }); -tape( 'the function has an arity of 1', function test( t ) { - t.strictEqual( dmeanlipw.length, 1, 'has expected arity' ); - t.end(); -}); - -tape( 'the function calculates the arithmetic mean of a one-dimensional ndarray', function test( t ) { - var x; - var v; - - x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); - v = dmeanlipw( [ vector( x, 6, 1, 0 ) ] ); - t.strictEqual( v, 0.5, 'returns expected value' ); - - x = new Float64Array( [ -4.0, -4.0 ] ); - v = dmeanlipw( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( v, -4.0, 'returns expected value' ); - - x = new Float64Array( [ NaN, 4.0 ] ); - v = dmeanlipw( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( isnan( v ), true, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) { - var x; - var v; - - x = new Float64Array( [] ); - - v = dmeanlipw( [ vector( x, 0, 1, 0 ) ] ); - t.strictEqual( isnan( v ), true, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided an ndarray containing a single element, the function returns that element', function test( t ) { - var x; - var v; - - x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); - - v = dmeanlipw( [ vector( x, 1, 1, 0 ) ] ); - t.strictEqual( v, 1.0, 'returns expected value' ); +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var dmeanlipw = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + t.strictEqual( dmeanlipw, mock, 'returns expected value' ); t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { - var x; - var v; - x = new Float64Array([ - 1.0, // 0 - 2.0, - 2.0, // 1 - -7.0, - -2.0, // 2 - 3.0, - 4.0, // 3 - 2.0 - ]); + function tryRequire() { + return mock; + } - v = dmeanlipw( [ vector( x, 4, 2, 0 ) ] ); - - t.strictEqual( v, 1.25, 'returns expected value' ); - t.end(); + function mock() { + // Mock... + } }); -tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { - var x; - var v; +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var dmeanlipw; + var main; - x = new Float64Array([ - 1.0, // 3 - 2.0, - 2.0, // 2 - -7.0, - -2.0, // 1 - 3.0, - 4.0, // 0 - 2.0 - ]); + main = require( './../lib/main.js' ); - v = dmeanlipw( [ vector( x, 4, -2, 6 ) ] ); + dmeanlipw = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); - t.strictEqual( v, 1.25, 'returns expected value' ); + t.strictEqual( dmeanlipw, main, 'returns expected value' ); t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { - var x; - var v; - x = new Float64Array([ - 2.0, - 1.0, // 0 - 2.0, - -2.0, // 1 - -2.0, - 2.0, // 2 - 3.0, - 4.0 // 3 - ]); - - v = dmeanlipw( [ vector( x, 4, 2, 1 ) ] ); - t.strictEqual( v, 1.25, 'returns expected value' ); - - t.end(); + function tryRequire() { + return new Error( 'Cannot find module' ); + } }); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/test/test.main.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/test/test.main.js new file mode 100644 index 000000000000..bd9440f3d13b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/test/test.main.js @@ -0,0 +1,164 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var dmeanlipw = require( './../lib/main.js' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dmeanlipw, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( dmeanlipw.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the arithmetic mean of a one-dimensional ndarray', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + v = dmeanlipw( [ vector( x, 6, 1, 0 ) ] ); + t.strictEqual( v, 0.5, 'returns expected value' ); + + x = new Float64Array( [ -4.0, -4.0 ] ); + v = dmeanlipw( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, -4.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, 4.0 ] ); + v = dmeanlipw( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) { + var x; + var v; + + x = new Float64Array( [] ); + + v = dmeanlipw( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an ndarray containing a single element, the function returns that element', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = dmeanlipw( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]); + + v = dmeanlipw( [ vector( x, 4, 2, 0 ) ] ); + + t.strictEqual( v, 1.25, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = dmeanlipw( [ vector( x, 4, -2, 6 ) ] ); + + t.strictEqual( v, 1.25, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + + v = dmeanlipw( [ vector( x, 4, 2, 1 ) ] ); + t.strictEqual( v, 1.25, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/test/test.native.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/test/test.native.js new file mode 100644 index 000000000000..4e7ed5d07c93 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanlipw/test/test.native.js @@ -0,0 +1,177 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dmeanlipw = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( dmeanlipw instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dmeanlipw, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', opts, function test( t ) { + t.strictEqual( dmeanlipw.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the arithmetic mean of a one-dimensional ndarray', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + v = dmeanlipw( [ vector( x, 6, 1, 0 ) ] ); + t.strictEqual( v, 0.5, 'returns expected value' ); + + x = new Float64Array( [ -4.0, -5.0 ] ); + v = dmeanlipw( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, -4.5, 'returns expected value' ); + + x = new Float64Array( [ NaN ] ); + v = dmeanlipw( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + v = dmeanlipw( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `NaN`', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [] ); + + v = dmeanlipw( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an ndarray containing a single element, the function returns that element', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0 ] ); + + v = dmeanlipw( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]); + + v = dmeanlipw( [ vector( x, 4, 2, 0 ) ] ); + + t.strictEqual( v, 1.25, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = dmeanlipw( [ vector( x, 4, -2, 6 ) ] ); + + t.strictEqual( v, 1.25, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + + v = dmeanlipw( [ vector( x, 4, 2, 1 ) ] ); + t.strictEqual( v, 1.25, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanpn/benchmark/benchmark.js index 2cd6a99a713f..1e7b3628b5bd 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanpn/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanpn = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanpw/benchmark/benchmark.js index 9a785b3d3957..f3e1614f2f72 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanpw/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanpw = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanwd/benchmark/benchmark.js index e60e9b4cb442..a9c5d118b86f 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmeanwd/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanwd = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmediansorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmediansorted/benchmark/benchmark.js index f8dc451e7df2..ca318ea9a063 100755 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dmediansorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmediansorted/benchmark/benchmark.js @@ -25,6 +25,7 @@ var linspace = require( '@stdlib/array/linspace' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmediansorted = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dminsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dminsorted/benchmark/benchmark.js index e67ed71027a9..a37e3829b1cd 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dminsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dminsorted/benchmark/benchmark.js @@ -25,6 +25,7 @@ var linspace = require( '@stdlib/array/linspace' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dminsorted = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmskmin/benchmark/benchmark.js index 6420fdd7a6c3..2629b38f77ee 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dmskmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmskmin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskmin = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmskrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmskrange/benchmark/benchmark.js index af0bfee44471..c65428da7b59 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dmskrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmskrange/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmskrange = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmax/benchmark/benchmark.js index 060a1939b932..1cb902b3d7b1 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmax/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmax = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/benchmark/benchmark.js index f1c316add85c..4bb880d56995 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmaxabs = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmean/benchmark/benchmark.js index b61e0aef0f01..127bbb7f15d7 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmean/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmean = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanors/benchmark/benchmark.js index 54c7a5589a74..d4f401602797 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanors/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmeanors = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpn/benchmark/benchmark.js index f408b41d340f..8615ac5ef49a 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpn/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmeanpn = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpw/benchmark/benchmark.js index 4c94675354f8..207ace7fa0c0 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpw/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmeanpw = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanwd/benchmark/benchmark.js index 2dcdfc9e3ede..ae16f11cbe36 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanwd/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmeanwd = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmin/benchmark/benchmark.js index 0773666e8659..d0c29ee756c3 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmin/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmin = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/benchmark/benchmark.js index 0e01ec75f19f..a61af20b4d54 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanminabs = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmax/benchmark/benchmark.js index a3b2208baafe..18d5bc06b465 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmax/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmskmax = require( './../lib' ); @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmin/benchmark/benchmark.js index 8304498bb21e..1ddf11f70b06 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmskmin = require( './../lib' ); @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskrange/benchmark/benchmark.js index 5a0bedb49b00..f7e213b1c33e 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskrange/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmskrange = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanrange/benchmark/benchmark.js index 9915109234e2..676b85293c8c 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanrange/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanrange = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanstdev/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/dnanstdev/README.md index ed785226a894..24adb2d3c100 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanstdev/README.md +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanstdev/README.md @@ -164,7 +164,7 @@ var opts = { 'dtype': 'float64' }; -var xbuf = filledarrayBy( 10, 'float64', rand ); +var xbuf = filledarrayBy( 10, opts.dtype, rand ); var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); console.log( ndarray2array( x ) ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanstdev/benchmark/benchmark.js index 8020e694b13a..1354f375c181 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanstdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanstdev/benchmark/benchmark.js @@ -43,10 +43,10 @@ var options = { // FUNCTIONS // /** -* Returns a random value, possibly NaN. +* Returns a random value. * * @private -* @returns {number} random value or `NaN` +* @returns {number} random value */ function rand() { if ( bernoulli( 0.8 ) < 1 ) { @@ -67,7 +67,7 @@ function createBenchmark( len ) { var xbuf; var x; - xbuf = filledarrayBy( len, 'float64', rand ); + xbuf = filledarrayBy( len, options.dtype, rand ); x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); correction = scalar2ndarray( 1.0, options ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanstdev/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanstdev/examples/index.js index 65ddff8bfff9..dabd2eb76df1 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanstdev/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanstdev/examples/index.js @@ -37,7 +37,7 @@ var opts = { 'dtype': 'float64' }; -var xbuf = filledarrayBy( 10, 'float64', rand ); +var xbuf = filledarrayBy( 10, opts.dtype, rand ); var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); console.log( ndarray2array( x ) ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/README.md index beab1243a58e..1c9bc4a8b49a 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/README.md +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/README.md @@ -97,6 +97,153 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/ndarray/drangeabs.h" +``` + +#### stdlib_stats_drangeabs( arrays ) + +Computes the range of absolute values of a one-dimensional double-precision floating-point ndarray. + +```c +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include + +// Create an ndarray: +const double data[] = { 1.0, -2.0, 3.0, -4.0 }; +int64_t shape[] = { 4 }; +int64_t strides[] = { STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT }; +int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + +struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)data, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes ); + +// Compute the range: +const struct ndarray *arrays[] = { x }; +double v = stdlib_stats_drangeabs( arrays ); +// returns 3.0 + +// Free allocated memory: +stdlib_ndarray_free( x ); +``` + +The function accepts the following arguments: + +- **arrays**: `[in] struct ndarray**` list containing a one-dimensional input ndarray. + +```c +double stdlib_stats_drangeabs( const struct ndarray *arrays[] ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/ndarray/drangeabs.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include + +int main( void ) { + // Create a data buffer: + const double data[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + + // Specify the number of array dimensions: + const int64_t ndims = 1; + + // Specify the array shape: + int64_t shape[] = { 4 }; + + // Specify the array strides: + int64_t strides[] = { 2*STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT }; + + // Specify the byte offset: + const int64_t offset = 0; + + // Specify the array order: + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const int64_t nsubmodes = 1; + + // Create an ndarray: + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x }; + + // Compute the range: + double v = stdlib_stats_drangeabs( arrays ); + + // Print the result: + printf( "range(abs): %lf\n", v ); + + // Free allocated memory: + stdlib_ndarray_free( x ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/benchmark/benchmark.js index a5fa477d8241..a94b02c20ae2 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/benchmark/benchmark.js @@ -27,7 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; -var drangeabs = require( './../lib' ); +var drangeabs = require( './../lib/main.js' ); // VARIABLES // diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/benchmark/benchmark.native.js new file mode 100644 index 000000000000..869a0dc13d42 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/benchmark/benchmark.native.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var drangeabs = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( drangeabs instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var x; + + xbuf = uniform( len, -10.0, 10.0, options ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = drangeabs( [ x ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..900e330478fb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/benchmark/c/benchmark.length.c @@ -0,0 +1,185 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/ndarray/drangeabs.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include +#include +#include +#include + +#define NAME "drangeabs" +#define ITERATIONS 1000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark( int iterations, int len ) { + enum STDLIB_NDARRAY_INDEX_MODE imode; + const struct ndarray *arrays[ 1 ]; + enum STDLIB_NDARRAY_ORDER order; + int8_t submodes[ 1 ]; + int64_t strides[ 1 ]; + int64_t shape[ 1 ]; + int64_t nsubmodes; + struct ndarray *x; + int64_t offset; + double elapsed; + int64_t ndims; + double *data; + double v; + double t; + int i; + + ndims = 1; + shape[ 0 ] = len; + strides[ 0 ] = STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT; + offset = 0; + order = STDLIB_NDARRAY_ROW_MAJOR; + imode = STDLIB_NDARRAY_INDEX_ERROR; + submodes[ 0 ] = imode; + nsubmodes = 1; + + data = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + data[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + // cppcheck-suppress invalidPointerCast + x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + arrays[ 0 ] = x; + + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + v = stdlib_stats_drangeabs( arrays ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + stdlib_ndarray_free( x ); + free( data ); + arrays[ 0 ] = NULL; + + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/binding.gyp b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/examples/c/example.c new file mode 100644 index 000000000000..b85f9d91ab18 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/examples/c/example.c @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/ndarray/drangeabs.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include + +int main( void ) { + // Create a data buffer: + const double data[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + + // Specify the number of array dimensions: + const int64_t ndims = 1; + + // Specify the array shape: + int64_t shape[] = { 4 }; + + // Specify the array strides: + int64_t strides[] = { 2*STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT }; + + // Specify the byte offset: + const int64_t offset = 0; + + // Specify the array order: + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const int64_t nsubmodes = 1; + + // Create an ndarray: + // cppcheck-suppress invalidPointerCast + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x }; + + // Compute the range: + double v = stdlib_stats_drangeabs( arrays ); + + // Print the result: + printf( "rangeabs: %lf\n", v ); + + // Free allocated memory: + stdlib_ndarray_free( x ); +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/include.gypi b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '} arrays - array-like object containing an input ndarray +* @returns {number} range +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Float64Array( [ -1.0, 3.0, -4.0, 2.0 ] ); +* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var v = drangeabs( [ x ] ); +* // returns 3.0 +*/ +function drangeabs( arrays ) { + var x = arrays[ 0 ]; + return addon( getData( x ), serialize( x ) ); +} + + +// EXPORTS // + +module.exports = drangeabs; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/manifest.json b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/manifest.json new file mode 100644 index 000000000000..a4f5d9b1b589 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/manifest.json @@ -0,0 +1,110 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/drangeabs", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/base/napi/addon-arguments", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/drangeabs", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/dtypes", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders", + "@stdlib/ndarray/base/bytes-per-element" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/drangeabs", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/dtypes", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders", + "@stdlib/ndarray/base/bytes-per-element" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/drangeabs", + "@stdlib/ndarray/ctor" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/package.json index 4e5388e0104f..3b8905441257 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/package.json @@ -14,11 +14,15 @@ } ], "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/src/Makefile b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/src/addon.c b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/src/addon.c new file mode 100644 index 000000000000..d2469b9e6eaa --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/src/addon.c @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/ndarray/drangeabs.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/base/napi/addon_arguments.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/create_double.h" +#include +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 2 ); + + // Process provided arguments: + struct ndarray *arrays[ 1 ]; + napi_value err; + napi_status status = stdlib_ndarray_napi_addon_arguments( env, argv, 2, 1, arrays, &err ); + assert( status == napi_ok ); + if ( err != NULL ) { + status = napi_throw( env, err ); + assert( status == napi_ok ); + return NULL; + } + // Perform computation: + STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_stats_drangeabs( arrays ), v ); + + // Free allocated memory: + stdlib_ndarray_free( arrays[ 0 ] ); + arrays[ 0 ] = NULL; + + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/src/main.c b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/src/main.c new file mode 100644 index 000000000000..541fb2ab11dd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/src/main.c @@ -0,0 +1,33 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/ndarray/drangeabs.h" +#include "stdlib/stats/strided/drangeabs.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/blas/base/shared.h" + +/** +* Computes the range of absolute values of a one-dimensional double-precision floating-point ndarray. +* +* @param arrays list containing an input ndarray +* @return range +*/ +double stdlib_stats_drangeabs( const struct ndarray *arrays[] ) { + const struct ndarray *x = arrays[ 0 ]; + return API_SUFFIX(stdlib_strided_drangeabs_ndarray)( stdlib_ndarray_dimension( x, 0 ), (const double *)stdlib_ndarray_data( x ), stdlib_ndarray_stride_elements( x, 0 ), stdlib_ndarray_offset_elements( x ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/test/test.js index 2797f8073752..e105969dab8b 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/test/test.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/test/test.js @@ -21,28 +21,16 @@ // MODULES // var tape = require( 'tape' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); -var Float64Array = require( '@stdlib/array/float64' ); -var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); var drangeabs = require( './../lib' ); -// FUNCTIONS // +// VARIABLES // -/** -* Returns a one-dimensional ndarray. -* -* @private -* @param {Collection} buffer - underlying data buffer -* @param {NonNegativeInteger} length - number of indexed elements -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - index offset -* @returns {ndarray} one-dimensional ndarray -*/ -function vector( buffer, length, stride, offset ) { - return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); -} +var opts = { + 'skip': IS_BROWSER +}; // TESTS // @@ -53,121 +41,37 @@ tape( 'main export is a function', function test( t ) { t.end(); }); -tape( 'the function has an arity of 1', function test( t ) { - t.strictEqual( drangeabs.length, 1, 'has expected arity' ); - t.end(); -}); - -tape( 'the function calculates the range of absolute values of a one-dimensional ndarray', function test( t ) { - var x; - var v; - - x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); - v = drangeabs( [ vector( x, 6, 1, 0 ) ] ); - t.strictEqual( v, 5.0, 'returns expected value' ); - - x = new Float64Array( [ -4.0, -5.0 ] ); - v = drangeabs( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( v, 1.0, 'returns expected value' ); - - x = new Float64Array( [ -0.0, 0.0, -0.0 ] ); - v = drangeabs( [ vector( x, 3, 1, 0 ) ] ); - t.strictEqual( isPositiveZero( v ), true, 'returns expected value' ); - - x = new Float64Array( [ NaN ] ); - v = drangeabs( [ vector( x, 1, 1, 0 ) ] ); - t.strictEqual( isnan( v ), true, 'returns expected value' ); - - x = new Float64Array( [ NaN, NaN ] ); - v = drangeabs( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( isnan( v ), true, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) { - var x; - var v; - - x = new Float64Array( [] ); - - v = drangeabs( [ vector( x, 0, 1, 0 ) ] ); - t.strictEqual( isnan( v ), true, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided an ndarray containing a single element, the function returns `0`', function test( t ) { - var x; - var v; - - x = new Float64Array( [ 1.0 ] ); - - v = drangeabs( [ vector( x, 1, 1, 0 ) ] ); - t.strictEqual( v, 0.0, 'returns expected value' ); +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var drangeabs = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + t.strictEqual( drangeabs, mock, 'returns expected value' ); t.end(); -}); -tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { - var x; - var v; + function tryRequire() { + return mock; + } - x = new Float64Array([ - 1.0, // 0 - 2.0, - 2.0, // 1 - -7.0, - -2.0, // 2 - 3.0, - 4.0, // 3 - 2.0 - ]); - - v = drangeabs( [ vector( x, 4, 2, 0 ) ] ); - - t.strictEqual( v, 3.0, 'returns expected value' ); - t.end(); + function mock() { + // Mock... + } }); -tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { - var x; - var v; +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var drangeabs; + var main; - x = new Float64Array([ - 1.0, // 3 - 2.0, - 2.0, // 2 - -7.0, - -2.0, // 1 - 3.0, - 4.0, // 0 - 2.0 - ]); + main = require( './../lib/main.js' ); - v = drangeabs( [ vector( x, 4, -2, 6 ) ] ); + drangeabs = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); - t.strictEqual( v, 3.0, 'returns expected value' ); + t.strictEqual( drangeabs, main, 'returns expected value' ); t.end(); -}); -tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { - var x; - var v; - - x = new Float64Array([ - 2.0, - 1.0, // 0 - 2.0, - -2.0, // 1 - -2.0, - 2.0, // 2 - 3.0, - 4.0 // 3 - ]); - - v = drangeabs( [ vector( x, 4, 2, 1 ) ] ); - t.strictEqual( v, 3.0, 'returns expected value' ); - - t.end(); + function tryRequire() { + return new Error( 'Cannot find module' ); + } }); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/test/test.main.js b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/test/test.main.js new file mode 100644 index 000000000000..4d3a8d294c6d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/test/test.main.js @@ -0,0 +1,168 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var drangeabs = require( './../lib/main.js' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof drangeabs, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( drangeabs.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the range of absolute values of a one-dimensional ndarray', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + v = drangeabs( [ vector( x, 6, 1, 0 ) ] ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + x = new Float64Array( [ -4.0, -5.0 ] ); + v = drangeabs( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + x = new Float64Array( [ NaN ] ); + v = drangeabs( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + v = drangeabs( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) { + var x; + var v; + + x = new Float64Array( [] ); + + v = drangeabs( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an ndarray containing a single element, the function returns `0`', function test( t ) { + var x; + var v; + + x = new Float64Array( [ -3.0 ] ); + + v = drangeabs( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]); + + v = drangeabs( [ vector( x, 4, 2, 0 ) ] ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = drangeabs( [ vector( x, 4, -2, 6 ) ] ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + + v = drangeabs( [ vector( x, 4, 2, 1 ) ] ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/test/test.native.js b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/test/test.native.js new file mode 100644 index 000000000000..573a7369ee0f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/drangeabs/test/test.native.js @@ -0,0 +1,177 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var drangeabs = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( drangeabs instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof drangeabs, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', opts, function test( t ) { + t.strictEqual( drangeabs.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the range of absolute values of a one-dimensional ndarray', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + v = drangeabs( [ vector( x, 6, 1, 0 ) ] ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + x = new Float64Array( [ -4.0, -5.0 ] ); + v = drangeabs( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + x = new Float64Array( [ NaN ] ); + v = drangeabs( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + v = drangeabs( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `NaN`', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [] ); + + v = drangeabs( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an ndarray containing a single element, the function returns `0`', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ -3.0 ] ); + + v = drangeabs( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]); + + v = drangeabs( [ vector( x, 4, 2, 0 ) ] ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = drangeabs( [ vector( x, 4, -2, 6 ) ] ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + + v = drangeabs( [ vector( x, 4, 2, 1 ) ] ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevtk/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevtk/README.md index 8e1daf6e3d46..04460de8efc3 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevtk/README.md +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevtk/README.md @@ -133,6 +133,7 @@ The function has the following parameters: - If provided an empty one-dimensional ndarray, the function returns `NaN`. - If `N - c` is less than or equal to `0` (where `N` corresponds to the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment), the function returns `NaN`. +- Some caution should be exercised when using the one-pass textbook algorithm. Literature overwhelmingly discourages the algorithm's use for two reasons: 1) the lack of safeguards against underflow and overflow and 2) the risk of catastrophic cancellation when subtracting the two sums if the sums are large and the variance small. These concerns have merit; however, the one-pass textbook algorithm should not be dismissed outright. For data distributions with a moderately large standard deviation to mean ratio (i.e., **coefficient of variation**), the one-pass textbook algorithm may be acceptable, especially when performance is paramount and some precision loss is acceptable (including a risk of computing a negative variance due to floating-point rounding errors!). In short, no single "best" algorithm for computing the standard deviation exists. The "best" algorithm depends on the underlying data distribution, your performance requirements, and your minimum precision requirements. When evaluating which algorithm to use, consider the relative pros and cons, and choose the algorithm which best serves your needs.
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dztest/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dztest/benchmark/benchmark.js index 3649d6e329c3..400982592ad1 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dztest/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dztest/benchmark/benchmark.js @@ -29,6 +29,7 @@ var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); var Float64Results = require( '@stdlib/stats/base/ztest/one-sample/results/float64' ); var resolveEnum = require( '@stdlib/stats/base/ztest/alternative-resolve-enum' ); var structFactory = require( '@stdlib/array/struct-factory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dztest = require( './../lib' ); @@ -120,7 +121,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/benchmark/benchmark.js index 0afc2ff75d30..2dc516e2a4c7 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/benchmark/benchmark.js @@ -29,6 +29,7 @@ var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); var Float64Results = require( '@stdlib/stats/base/ztest/two-sample/results/float64' ); var resolveEnum = require( '@stdlib/stats/base/ztest/alternative-resolve-enum' ); var structFactory = require( '@stdlib/array/struct-factory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dztest2 = require( './../lib' ); @@ -127,7 +128,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/lib/index.js index 14ad61b54b07..6148e07cfa1f 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/lib/index.js @@ -288,6 +288,15 @@ setReadOnly( ns, 'dminsorted', require( '@stdlib/stats/base/ndarray/dminsorted' */ setReadOnly( ns, 'dmskmax', require( '@stdlib/stats/base/ndarray/dmskmax' ) ); +/** +* @name dmskmaxabs +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/base/ndarray/dmskmaxabs} +*/ +setReadOnly( ns, 'dmskmaxabs', require( '@stdlib/stats/base/ndarray/dmskmaxabs' ) ); + /** * @name dmskmin * @memberof ns @@ -405,6 +414,15 @@ setReadOnly( ns, 'dnanminabs', require( '@stdlib/stats/base/ndarray/dnanminabs' */ setReadOnly( ns, 'dnanmskmax', require( '@stdlib/stats/base/ndarray/dnanmskmax' ) ); +/** +* @name dnanmskmaxabs +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/base/ndarray/dnanmskmaxabs} +*/ +setReadOnly( ns, 'dnanmskmaxabs', require( '@stdlib/stats/base/ndarray/dnanmskmaxabs' ) ); + /** * @name dnanmskmin * @memberof ns @@ -414,6 +432,15 @@ setReadOnly( ns, 'dnanmskmax', require( '@stdlib/stats/base/ndarray/dnanmskmax' */ setReadOnly( ns, 'dnanmskmin', require( '@stdlib/stats/base/ndarray/dnanmskmin' ) ); +/** +* @name dnanmskminabs +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/base/ndarray/dnanmskminabs} +*/ +setReadOnly( ns, 'dnanmskminabs', require( '@stdlib/stats/base/ndarray/dnanmskminabs' ) ); + /** * @name dnanmskrange * @memberof ns @@ -432,6 +459,33 @@ setReadOnly( ns, 'dnanmskrange', require( '@stdlib/stats/base/ndarray/dnanmskran */ setReadOnly( ns, 'dnanrange', require( '@stdlib/stats/base/ndarray/dnanrange' ) ); +/** +* @name dnanstdev +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/base/ndarray/dnanstdev} +*/ +setReadOnly( ns, 'dnanstdev', require( '@stdlib/stats/base/ndarray/dnanstdev' ) ); + +/** +* @name dnanstdevch +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/base/ndarray/dnanstdevch} +*/ +setReadOnly( ns, 'dnanstdevch', require( '@stdlib/stats/base/ndarray/dnanstdevch' ) ); + +/** +* @name dnanstdevpn +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/base/ndarray/dnanstdevpn} +*/ +setReadOnly( ns, 'dnanstdevpn', require( '@stdlib/stats/base/ndarray/dnanstdevpn' ) ); + /** * @name drange * @memberof ns @@ -846,6 +900,15 @@ setReadOnly( ns, 'nanminabs', require( '@stdlib/stats/base/ndarray/nanminabs' ) */ setReadOnly( ns, 'nanmskmax', require( '@stdlib/stats/base/ndarray/nanmskmax' ) ); +/** +* @name nanmskmidrange +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/base/ndarray/nanmskmidrange} +*/ +setReadOnly( ns, 'nanmskmidrange', require( '@stdlib/stats/base/ndarray/nanmskmidrange' ) ); + /** * @name nanmskmin * @memberof ns @@ -1278,6 +1341,24 @@ setReadOnly( ns, 'snanminabs', require( '@stdlib/stats/base/ndarray/snanminabs' */ setReadOnly( ns, 'snanmskmax', require( '@stdlib/stats/base/ndarray/snanmskmax' ) ); +/** +* @name snanmskmaxabs +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/base/ndarray/snanmskmaxabs} +*/ +setReadOnly( ns, 'snanmskmaxabs', require( '@stdlib/stats/base/ndarray/snanmskmaxabs' ) ); + +/** +* @name snanmskmidrange +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/base/ndarray/snanmskmidrange} +*/ +setReadOnly( ns, 'snanmskmidrange', require( '@stdlib/stats/base/ndarray/snanmskmidrange' ) ); + /** * @name snanmskmin * @memberof ns @@ -1287,6 +1368,15 @@ setReadOnly( ns, 'snanmskmax', require( '@stdlib/stats/base/ndarray/snanmskmax' */ setReadOnly( ns, 'snanmskmin', require( '@stdlib/stats/base/ndarray/snanmskmin' ) ); +/** +* @name snanmskminabs +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/base/ndarray/snanmskminabs} +*/ +setReadOnly( ns, 'snanmskminabs', require( '@stdlib/stats/base/ndarray/snanmskminabs' ) ); + /** * @name snanmskrange * @memberof ns @@ -1467,6 +1557,24 @@ setReadOnly( ns, 'variance', require( '@stdlib/stats/base/ndarray/variance' ) ); */ setReadOnly( ns, 'variancech', require( '@stdlib/stats/base/ndarray/variancech' ) ); +/** +* @name variancepn +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/base/ndarray/variancepn} +*/ +setReadOnly( ns, 'variancepn', require( '@stdlib/stats/base/ndarray/variancepn' ) ); + +/** +* @name variancetk +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/base/ndarray/variancetk} +*/ +setReadOnly( ns, 'variancetk', require( '@stdlib/stats/base/ndarray/variancetk' ) ); + /** * @name variancewd * @memberof ns @@ -1476,6 +1584,15 @@ setReadOnly( ns, 'variancech', require( '@stdlib/stats/base/ndarray/variancech' */ setReadOnly( ns, 'variancewd', require( '@stdlib/stats/base/ndarray/variancewd' ) ); +/** +* @name varianceyc +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/base/ndarray/varianceyc} +*/ +setReadOnly( ns, 'varianceyc', require( '@stdlib/stats/base/ndarray/varianceyc' ) ); + /** * @name ztest * @memberof ns diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/max-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/max-by/benchmark/benchmark.js index b9ff3547ceef..7ae0570be09c 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/max-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/max-by/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var maxBy = require( './../lib' ); @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/maxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/maxabs/benchmark/benchmark.js index be1709eccae1..f3cd5e6a0358 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/maxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/maxabs/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var maxabs = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/maxsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/maxsorted/benchmark/benchmark.js index c6c3ea22225a..7652dfb9c18c 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/maxsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/maxsorted/benchmark/benchmark.js @@ -25,6 +25,7 @@ var linspace = require( '@stdlib/array/linspace' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var maxsorted = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/mean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/mean/benchmark/benchmark.js index 7b76cc25bee2..1ea53d9e66cb 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/mean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/mean/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mean = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/meankbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/meankbn/benchmark/benchmark.js index 3b1a22f0729a..adcdf3582d54 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/meankbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/meankbn/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meankbn = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/meankbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/meankbn2/benchmark/benchmark.js index 2c4c5f65cbc1..beb01cf386ef 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/meankbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/meankbn2/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meankbn2 = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/meanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/meanors/benchmark/benchmark.js index e6da03c9453f..3c69cf11402f 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/meanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/meanors/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanors = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/meanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/meanpn/benchmark/benchmark.js index c5dfa5835e23..08468fcc2182 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/meanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/meanpn/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanpn = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/meanpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/meanpw/benchmark/benchmark.js index ede23161b9c9..8412197636b6 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/meanpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/meanpw/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanpw = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/meanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/meanwd/benchmark/benchmark.js index 5f84f26a8228..b3678ef92d4b 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/meanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/meanwd/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanwd = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/mediansorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/mediansorted/benchmark/benchmark.js index 7b290d83859a..b55d2679d1d1 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/mediansorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/mediansorted/benchmark/benchmark.js @@ -25,6 +25,7 @@ var linspace = require( '@stdlib/array/linspace' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mediansorted = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/README.md new file mode 100644 index 000000000000..ac7c966702e8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/README.md @@ -0,0 +1,115 @@ + + +# midrangeabs + +> Compute the [mid-range][mid-range] of absolute values of a one-dimensional ndarray. + +
+ +The [**mid-range**][mid-range], or **mid-extreme**, is the arithmetic mean of the maximum and minimum values in a data set. The measure is the midpoint of the range and a measure of central tendency. + +
+ + + +
+ +## Usage + +```javascript +var midrangeabs = require( '@stdlib/stats/base/ndarray/midrangeabs' ); +``` + +#### midrangeabs( arrays ) + +Computes the [mid-range][mid-range] of absolute values of a one-dimensional ndarray. + +```javascript +var ndarray = require( '@stdlib/ndarray/base/ctor' ); + +var xbuf = [ 1.0, 2.0, 5.0, 10.0 ]; +var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); + +var v = midrangeabs( [ x ] ); +// returns 5.5 +``` + +The function has the following parameters: + +- **arrays**: array-like object containing a one-dimensional input ndarray. + +
+ + + +
+ +## Notes + +- If provided an empty one-dimensional ndarray, the function returns `NaN`. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var midrangeabs = require( '@stdlib/stats/base/ndarray/midrangeabs' ); + +var xbuf = uniform( 10, -50.0, 50.0, { + 'dtype': 'generic' +}); +var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var v = midrangeabs( [ x ] ); +console.log( v ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mid-range]: https://en.wikipedia.org/wiki/Mid-range + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/benchmark/benchmark.js new file mode 100644 index 000000000000..f3f874f6b4be --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var pkg = require( './../package.json' ).name; +var midrangeabs = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var x; + + xbuf = uniform( len, -10.0, 10.0, options ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = midrangeabs( [ x ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/docs/repl.txt new file mode 100644 index 000000000000..5cfbef5cdd19 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/docs/repl.txt @@ -0,0 +1,31 @@ + +{{alias}}( arrays ) + Computes the mid-range of absolute values of a one-dimensional ndarray. + + If provided an empty ndarray, the function returns `NaN`. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing a one-dimensional input ndarray. + + Returns + ------- + out: number + Mid-range. + + Examples + -------- + > var xbuf = [ 1.0, -2.0, 2.0, 4.0 ]; + > var dt = 'generic'; + > var sh = [ xbuf.length ]; + > var sx = [ 1 ]; + > var ox = 0; + > var ord = 'row-major'; + > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord ); + > {{alias}}( [ x ] ) + 2.5 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/docs/types/index.d.ts new file mode 100644 index 000000000000..344f938048c6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/docs/types/index.d.ts @@ -0,0 +1,45 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray } from '@stdlib/types/ndarray'; + +/** +* Computes the mid-range of absolute values of a one-dimensional ndarray. +* +* @param arrays - array-like object containing an input ndarray +* @returns mid-range +* +* @example +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = [ 1.0, -2.0, 2.0, 4.0 ]; +* var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var v = midrangeabs( [ x ] ); +* // returns 2.5 +*/ +declare function midrangeabs = typedndarray>( arrays: [ T ] ): number; + + +// EXPORTS // + +export = midrangeabs; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/docs/types/test.ts new file mode 100644 index 000000000000..d417fe4334ab --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/docs/types/test.ts @@ -0,0 +1,57 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import midrangeabs = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = zeros( [ 10 ], { + 'dtype': 'generic' + }); + + midrangeabs( [ x ] ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + midrangeabs( '10' ); // $ExpectError + midrangeabs( 10 ); // $ExpectError + midrangeabs( true ); // $ExpectError + midrangeabs( false ); // $ExpectError + midrangeabs( null ); // $ExpectError + midrangeabs( undefined ); // $ExpectError + midrangeabs( [] ); // $ExpectError + midrangeabs( {} ); // $ExpectError + midrangeabs( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'generic' + }); + + midrangeabs(); // $ExpectError + midrangeabs( [ x ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/examples/index.js new file mode 100644 index 000000000000..57ac84666322 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/examples/index.js @@ -0,0 +1,33 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var midrangeabs = require( './../lib' ); + +var xbuf = uniform( 10, -50.0, 50.0, { + 'dtype': 'generic' +}); +var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var v = midrangeabs( [ x ] ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/lib/index.js new file mode 100644 index 000000000000..4c1b894eb34a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the mid-range of absolute values of a one-dimensional ndarray. +* +* @module @stdlib/stats/base/ndarray/midrangeabs +* +* @example +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* var midrangeabs = require( '@stdlib/stats/base/ndarray/midrangeabs' ); +* +* var xbuf = [ 1.0, -2.0, 4.0, 2.0 ]; +* var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var v = midrangeabs( [ x ] ); +* // returns 2.5 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/lib/main.js new file mode 100644 index 000000000000..88facefdf22a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/lib/main.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/stats/strided/midrangeabs' ).ndarray; + + +// MAIN // + +/** +* Computes the mid-range of absolute values of a one-dimensional ndarray. +* +* @param {ArrayLikeObject} arrays - array-like object containing an input ndarray +* @returns {number} mid-range of absolute values +* +* @example +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = [ 1.0, 2.0, 5.0, 10.0 ]; +* var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var v = midrangeabs( [ x ] ); +* // returns 5.5 +*/ +function midrangeabs( arrays ) { + var x = arrays[ 0 ]; + return strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = midrangeabs; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/package.json new file mode 100644 index 000000000000..b57b49b14f2e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/stats/base/ndarray/midrangeabs", + "version": "0.0.0", + "description": "Compute the mid-range of absolute values of a one-dimensional ndarray.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "absolute", + "abs", + "midrange", + "range", + "min", + "max", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/test/test.js new file mode 100644 index 000000000000..55a26f60c183 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/midrangeabs/test/test.js @@ -0,0 +1,194 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var midrangeabs = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'generic', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof midrangeabs, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( midrangeabs.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the mid-range of absolute values of a one-dimensional ndarray', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ]; + v = midrangeabs( [ vector( x, 6, 1, 0 ) ] ); + t.strictEqual( v, 2.5, 'returns expected value' ); + + x = [ -4.0, -5.0 ]; + v = midrangeabs( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, 4.5, 'returns expected value' ); + + x = [ -0.0, 0.0, -0.0 ]; + v = midrangeabs( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( isPositiveZero( v ), true, 'returns expected value' ); + + x = [ NaN ]; + v = midrangeabs( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ NaN, NaN ]; + v = midrangeabs( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) { + var x; + var v; + + x = []; + + v = midrangeabs( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an ndarray containing a single element, the function returns that element', function test( t ) { + var x; + var v; + + x = [ 1.0 ]; + + v = midrangeabs( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + x = [ NaN ]; + + v = midrangeabs( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + 6.0 + ]; + + v = midrangeabs( [ vector( x, 4, 2, 0 ) ] ); + + t.strictEqual( v, 2.5, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0, + 6.0 + ]; + + v = midrangeabs( [ vector( x, 4, -2, 6 ) ] ); + + t.strictEqual( v, 2.5, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an ndarray having a stride equal to `0`, the function returns the first element', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + v = midrangeabs( [ vector( x, 5, 0, 0 ) ] ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + v = midrangeabs( [ vector( x, 5, 0, 0 ) ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var x; + var v; + + x = [ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]; + + v = midrangeabs( [ vector( x, 4, 2, 1 ) ] ); + t.strictEqual( v, 2.5, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/min-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/min-by/benchmark/benchmark.js index eb88064c0837..9d4b441f03ad 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/min-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/min-by/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minBy = require( './../lib' ); @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/minabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/benchmark/benchmark.js index 24d7437bea72..98142afe042c 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/minabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minabs = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/minsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/minsorted/benchmark/benchmark.js index 4c61635fdb84..5b6a9e66dc8a 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/minsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/minsorted/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/base/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minsorted = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/mskmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/mskmax/benchmark/benchmark.js index c221f520fa83..5cf9c1d874f2 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/mskmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/mskmax/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskmax = require( './../lib' ); @@ -108,7 +109,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/mskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/mskmin/benchmark/benchmark.js index dee55d15a428..4bcf343600be 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/mskmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/mskmin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskmin = require( './../lib' ); @@ -108,7 +109,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/mskrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/mskrange/benchmark/benchmark.js index 4a3dc383f282..b8d18d3bb2ba 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/mskrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/mskrange/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskrange = require( './../lib' ); @@ -108,7 +109,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmax-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanmax-by/benchmark/benchmark.js index 337bd61b2d96..772f08fbcc94 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmax-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmax-by/benchmark/benchmark.js @@ -27,6 +27,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmaxBy = require( './../lib' ); @@ -127,7 +128,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanmax/benchmark/benchmark.js index b1c3d9911d79..3ad2ef07fd82 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmax/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmax = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanmeanwd/benchmark/benchmark.js index 435f9853841a..f81752f42a4b 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmeanwd/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmeanwd = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmidrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanmidrange/benchmark/benchmark.js index 3cf6748f5e6b..350809d743c2 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmidrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmidrange/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmidrange = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmin-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanmin-by/benchmark/benchmark.js index 96c7f25028d0..e99b207a42ad 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmin-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmin-by/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanminBy = require( './../lib' ); @@ -120,7 +121,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanmin/benchmark/benchmark.js index 402cbe7a3081..ae2db9196225 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmin/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmin = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/benchmark/benchmark.js index 7be3ae34e3e2..25b0267ddc2c 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanminabs = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmskmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanmskmax/benchmark/benchmark.js index e6cd4fc96d0c..80516078d3ae 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmskmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmskmax/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmskmax = require( './../lib' ); @@ -108,7 +109,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanmskmin/benchmark/benchmark.js index 67bb9d1f9a78..91be0aa219fd 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmskmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmskmin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmskmin = require( './../lib' ); @@ -108,7 +109,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmskrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanmskrange/benchmark/benchmark.js index d91f08eb549d..eeb5607b04bc 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmskrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmskrange/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmskrange = require( './../lib' ); @@ -108,7 +109,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanrange-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanrange-by/benchmark/benchmark.js index b3f619998869..d065c78dd938 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanrange-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanrange-by/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanrangeBy = require( './../lib' ); @@ -120,7 +121,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanrange/benchmark/benchmark.js index 1f54a2e5029a..78efe19a56f8 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanrange/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanrange = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/range-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/range-by/benchmark/benchmark.js index b495b6a235ec..0d9bed4d4ef7 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/range-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/range-by/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var rangeBy = require( './../lib' ); @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/range/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/range/benchmark/benchmark.js index 8242a4507746..cdec7b0f6135 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/range/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/range/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var range = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/benchmark.js index 7717f0825b61..95d812cc843c 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scovarmtk = require( './../lib' ); @@ -114,7 +115,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scumax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/scumax/benchmark/benchmark.js index f3c8d5c0cca7..fcc0e84fa577 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/scumax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scumax/benchmark/benchmark.js @@ -26,6 +26,7 @@ var zeros = require( '@stdlib/array/zeros' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scumax = require( './../lib' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/benchmark/benchmark.js index d634004085a9..e4d53907eaaa 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/benchmark/benchmark.js @@ -26,6 +26,7 @@ var zeros = require( '@stdlib/array/zeros' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scumaxabs = require( './../lib' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scumin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/scumin/benchmark/benchmark.js index 5dc3dafc9c12..3d48fc181ee3 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/scumin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scumin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var zeros = require( '@stdlib/array/zeros' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scumin = require( './../lib' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/benchmark/benchmark.js index 8450b2363fc3..6685483780ee 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/benchmark/benchmark.js @@ -26,6 +26,7 @@ var zeros = require( '@stdlib/array/zeros' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scuminabs = require( './../lib' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sdsmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/sdsmean/benchmark/benchmark.js index f76126f91493..934a4fb3f790 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/sdsmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sdsmean/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsmean = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sdsmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/sdsmeanors/benchmark/benchmark.js index 13e0482d464a..cb3241a382b9 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/sdsmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sdsmeanors/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsmeanors = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sdsnanmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/sdsnanmeanors/benchmark/benchmark.js index d3c438d30ccf..d464773816fd 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/sdsnanmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sdsnanmeanors/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsnanmeanors = require( './../lib' ); @@ -108,7 +109,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxabssorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/smaxabssorted/benchmark/benchmark.js index a010fe3d0b55..0bb20bd7967a 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smaxabssorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxabssorted/benchmark/benchmark.js @@ -25,6 +25,7 @@ var linspace = require( '@stdlib/array/linspace' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smaxabssorted = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/README.md index 635eb151e90f..05b015f4575e 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/README.md +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/README.md @@ -96,6 +96,153 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/ndarray/smaxsorted.h" +``` + +#### stdlib_stats_smaxsorted( arrays ) + +Computes the maximum value of a sorted one-dimensional single-precision floating-point ndarray. + +```c +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include + +// Create an ndarray: +const float data[] = { 1.0f, 2.0f, 3.0f, 4.0f }; +int64_t shape[] = { 4 }; +int64_t strides[] = { STDLIB_NDARRAY_FLOAT32_BYTES_PER_ELEMENT }; +int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + +struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)data, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes ); + +// Compute the maximum value: +const struct ndarray *arrays[] = { x }; +float v = stdlib_stats_smaxsorted( arrays ); +// returns 4.0f + +// Free allocated memory: +stdlib_ndarray_free( x ); +``` + +The function accepts the following arguments: + +- **arrays**: `[in] struct ndarray**` list containing a one-dimensional input ndarray. + +```c +float stdlib_stats_smaxsorted( const struct ndarray *arrays[] ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/ndarray/smaxsorted.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include + +int main( void ) { + // Create a data buffer: + const float data[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of array dimensions: + const int64_t ndims = 1; + + // Specify the array shape: + int64_t shape[] = { 4 }; + + // Specify the array strides: + int64_t strides[] = { 2*STDLIB_NDARRAY_FLOAT32_BYTES_PER_ELEMENT }; + + // Specify the byte offset: + const int64_t offset = 0; + + // Specify the array order: + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const int64_t nsubmodes = 1; + + // Create an ndarray: + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x }; + + // Compute the maximum value: + float v = stdlib_stats_smaxsorted( arrays ); + + // Print the result: + printf( "max: %f\n", v ); + + // Free allocated memory: + stdlib_ndarray_free( x ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/benchmark/benchmark.js index 47770fd8974a..c269fd5835f2 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/benchmark/benchmark.js @@ -25,8 +25,9 @@ var linspace = require( '@stdlib/array/linspace' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; -var smaxsorted = require( './../lib' ); +var smaxsorted = require( './../lib/main.js' ); // VARIABLES // @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/benchmark/benchmark.native.js new file mode 100644 index 000000000000..af59b660b1b5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/benchmark/benchmark.native.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var linspace = require( '@stdlib/array/linspace' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var smaxsorted = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( smaxsorted instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var x; + + xbuf = linspace( -len/2, len/2, len, options ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = smaxsorted( [ x ] ); + if ( isnanf( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..85a50ab0dfa9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/benchmark/c/benchmark.length.c @@ -0,0 +1,175 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/ndarray/smaxsorted.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include +#include +#include +#include + +#define NAME "smaxsorted" +#define ITERATIONS 1000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark( int iterations, int len ) { + enum STDLIB_NDARRAY_INDEX_MODE imode; + const struct ndarray *arrays[ 1 ]; + enum STDLIB_NDARRAY_ORDER order; + int8_t submodes[ 1 ]; + int64_t strides[ 1 ]; + int64_t shape[ 1 ]; + int64_t nsubmodes; + struct ndarray *x; + int64_t offset; + double elapsed; + int64_t ndims; + float *data; + double t; + float v; + int i; + + ndims = 1; + shape[ 0 ] = len; + strides[ 0 ] = STDLIB_NDARRAY_FLOAT32_BYTES_PER_ELEMENT; + offset = 0; + order = STDLIB_NDARRAY_ROW_MAJOR; + imode = STDLIB_NDARRAY_INDEX_ERROR; + submodes[ 0 ] = imode; + nsubmodes = 1; + + data = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + data[ i ] = (float)i - ( (float)len / 2.0f ); + } + // cppcheck-suppress invalidPointerCast + x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + arrays[ 0 ] = x; + + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + v = stdlib_stats_smaxsorted( arrays ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + stdlib_ndarray_free( x ); + free( data ); + arrays[ 0 ] = NULL; + + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/binding.gyp b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/examples/c/example.c new file mode 100644 index 000000000000..cca7925ab186 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/examples/c/example.c @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/ndarray/smaxsorted.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include + +int main( void ) { + // Create a data buffer: + const float data[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of array dimensions: + const int64_t ndims = 1; + + // Specify the array shape: + int64_t shape[] = { 4 }; + + // Specify the array strides: + int64_t strides[] = { 2*STDLIB_NDARRAY_FLOAT32_BYTES_PER_ELEMENT }; + + // Specify the byte offset: + const int64_t offset = 0; + + // Specify the array order: + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const int64_t nsubmodes = 1; + + // Create an ndarray: + // cppcheck-suppress invalidPointerCast + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x }; + + // Compute the maximum value: + float v = stdlib_stats_smaxsorted( arrays ); + + // Print the result: + printf( "max: %f\n", v ); + + // Free allocated memory: + stdlib_ndarray_free( x ); +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/include.gypi b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '} arrays - array-like object containing an input ndarray +* @returns {number} maximum value +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var xbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); +* +* var v = smaxsorted( [ x ] ); +* // returns 4.0 +*/ +function smaxsorted( arrays ) { + var x = arrays[ 0 ]; + return addon( getData( x ), serialize( x ) ); +} + + +// EXPORTS // + +module.exports = smaxsorted; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/manifest.json b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/manifest.json new file mode 100644 index 000000000000..e48c3cba53bf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/manifest.json @@ -0,0 +1,110 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/smaxsorted", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/base/napi/addon-arguments", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/smaxsorted", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/dtypes", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders", + "@stdlib/ndarray/base/bytes-per-element" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/smaxsorted", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/dtypes", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders", + "@stdlib/ndarray/base/bytes-per-element" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/smaxsorted", + "@stdlib/ndarray/ctor" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/package.json index 948bbe3d2b27..5cb5558b23b9 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/package.json @@ -14,11 +14,15 @@ } ], "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/src/Makefile b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/src/addon.c new file mode 100644 index 000000000000..46003a19d275 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/src/addon.c @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/ndarray/smaxsorted.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/base/napi/addon_arguments.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/create_double.h" +#include +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 2 ); + + // Process provided arguments: + struct ndarray *arrays[ 1 ]; + napi_value err; + napi_status status = stdlib_ndarray_napi_addon_arguments( env, argv, 2, 1, arrays, &err ); + assert( status == napi_ok ); + if ( err != NULL ) { + status = napi_throw( env, err ); + assert( status == napi_ok ); + return NULL; + } + // Perform computation: + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_stats_smaxsorted( arrays ), v ); + + // Free allocated memory: + stdlib_ndarray_free( arrays[ 0 ] ); + arrays[ 0 ] = NULL; + + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/src/main.c b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/src/main.c new file mode 100644 index 000000000000..61d56d46097b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/src/main.c @@ -0,0 +1,33 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/ndarray/smaxsorted.h" +#include "stdlib/stats/strided/smaxsorted.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/blas/base/shared.h" + +/** +* Computes the maximum value of a sorted one-dimensional single-precision floating-point ndarray. +* +* @param arrays list containing an input ndarray +* @return maximum value +*/ +float stdlib_stats_smaxsorted( const struct ndarray *arrays[] ) { + const struct ndarray *x = arrays[ 0 ]; + return API_SUFFIX(stdlib_strided_smaxsorted_ndarray)( stdlib_ndarray_dimension( x, 0 ), (const float *)stdlib_ndarray_data( x ), stdlib_ndarray_stride_elements( x, 0 ), stdlib_ndarray_offset_elements( x ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/test/test.js index 0c9a4f42e7df..39327682bf4c 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/test/test.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/test/test.js @@ -21,28 +21,16 @@ // MODULES // var tape = require( 'tape' ); -var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); -var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); -var Float32Array = require( '@stdlib/array/float32' ); -var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); var smaxsorted = require( './../lib' ); -// FUNCTIONS // +// VARIABLES // -/** -* Returns a one-dimensional ndarray. -* -* @private -* @param {Float32Array} buffer - underlying data buffer -* @param {NonNegativeInteger} length - number of indexed elements -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - index offset -* @returns {ndarray} one-dimensional ndarray -*/ -function vector( buffer, length, stride, offset ) { - return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); -} +var opts = { + 'skip': IS_BROWSER +}; // TESTS // @@ -53,129 +41,37 @@ tape( 'main export is a function', function test( t ) { t.end(); }); -tape( 'the function has an arity of 1', function test( t ) { - t.strictEqual( smaxsorted.length, 1, 'has expected arity' ); - t.end(); -}); - -tape( 'the function calculates the maximum value of a one-dimensional ndarray', function test( t ) { - var x; - var v; - - x = new Float32Array( [ -3.0, -2.0, -1.0, 1.0, 2.0, 3.0 ] ); - v = smaxsorted( [ vector( x, 6, 1, 0 ) ] ); - t.strictEqual( v, 3.0, 'returns expected value' ); - - x = new Float32Array( [ 3.0, 2.0, 1.0, -1.0, -2.0, -3.0 ] ); - v = smaxsorted( [ vector( x, 6, 1, 0 ) ] ); - t.strictEqual( v, 3.0, 'returns expected value' ); - - x = new Float32Array( [ -4.0, -5.0 ] ); - v = smaxsorted( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( v, -4.0, 'returns expected value' ); - - x = new Float32Array( [ -0.0, -0.0, 0.0 ] ); - v = smaxsorted( [ vector( x, 3, 1, 0 ) ] ); - t.strictEqual( isPositiveZerof( v ), true, 'returns expected value' ); - - x = new Float32Array( [ 0.0, -0.0, -0.0 ] ); - v = smaxsorted( [ vector( x, 3, 1, 0 ) ] ); - t.strictEqual( isPositiveZerof( v ), true, 'returns expected value' ); - - x = new Float32Array( [ NaN ] ); - v = smaxsorted( [ vector( x, 1, 1, 0 ) ] ); - t.strictEqual( isnanf( v ), true, 'returns expected value' ); - - x = new Float32Array( [ NaN, NaN ] ); - v = smaxsorted( [ vector( x, 2, 1, 0 ) ] ); - t.strictEqual( isnanf( v ), true, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) { - var x; - var v; - - x = new Float32Array( [] ); - - v = smaxsorted( [ vector( x, 0, 1, 0 ) ] ); - t.strictEqual( isnanf( v ), true, 'returns expected value' ); +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var smaxsorted = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + t.strictEqual( smaxsorted, mock, 'returns expected value' ); t.end(); -}); - -tape( 'if provided an ndarray containing a single element, the function returns that element', function test( t ) { - var x; - var v; - - x = new Float32Array( [ 1.0 ] ); - v = smaxsorted( [ vector( x, 1, 1, 0 ) ] ); - t.strictEqual( v, 1.0, 'returns expected value' ); + function tryRequire() { + return mock; + } - t.end(); + function mock() { + // Mock... + } }); -tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { - var x; - var v; +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var smaxsorted; + var main; - x = new Float32Array([ - 1.0, // 0 - 2.0, - 2.0, // 1 - -7.0, - 3.0, // 2 - 3.0, - 4.0, // 3 - 2.0 - ]); + main = require( './../lib/main.js' ); - v = smaxsorted( [ vector( x, 4, 2, 0 ) ] ); + smaxsorted = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); - t.strictEqual( v, 4.0, 'returns expected value' ); + t.strictEqual( smaxsorted, main, 'returns expected value' ); t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { - var x; - var v; - - x = new Float32Array([ - 1.0, // 3 - 2.0, - 2.0, // 2 - -7.0, - 3.0, // 1 - 3.0, - 4.0, // 0 - 2.0 - ]); - v = smaxsorted( [ vector( x, 4, -2, 6 ) ] ); - - t.strictEqual( v, 4.0, 'returns expected value' ); - t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { - var x; - var v; - - x = new Float32Array([ - 2.0, - 1.0, // 0 - 2.0, - 2.0, // 1 - -2.0, - 2.0, // 2 - 3.0, - 4.0 // 3 - ]); - - v = smaxsorted( [ vector( x, 4, 2, 1 ) ] ); - t.strictEqual( v, 4.0, 'returns expected value' ); - - t.end(); + function tryRequire() { + return new Error( 'Cannot find module' ); + } }); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/test/test.main.js b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/test/test.main.js new file mode 100644 index 000000000000..f16d7ee12c57 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/test/test.main.js @@ -0,0 +1,181 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); +var Float32Array = require( '@stdlib/array/float32' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var smaxsorted = require( './../lib/main.js' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float32Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof smaxsorted, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( smaxsorted.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the maximum value of a one-dimensional ndarray', function test( t ) { + var x; + var v; + + x = new Float32Array( [ -3.0, -2.0, -1.0, 1.0, 2.0, 3.0 ] ); + v = smaxsorted( [ vector( x, 6, 1, 0 ) ] ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + x = new Float32Array( [ 3.0, 2.0, 1.0, -1.0, -2.0, -3.0 ] ); + v = smaxsorted( [ vector( x, 6, 1, 0 ) ] ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + x = new Float32Array( [ -4.0, -5.0 ] ); + v = smaxsorted( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, -4.0, 'returns expected value' ); + + x = new Float32Array( [ -0.0, -0.0, 0.0 ] ); + v = smaxsorted( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( isPositiveZerof( v ), true, 'returns expected value' ); + + x = new Float32Array( [ 0.0, -0.0, -0.0 ] ); + v = smaxsorted( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( isPositiveZerof( v ), true, 'returns expected value' ); + + x = new Float32Array( [ NaN ] ); + v = smaxsorted( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + x = new Float32Array( [ NaN, NaN ] ); + v = smaxsorted( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) { + var x; + var v; + + x = new Float32Array( [] ); + + v = smaxsorted( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an ndarray containing a single element, the function returns that element', function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0 ] ); + + v = smaxsorted( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var x; + var v; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + 3.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]); + + v = smaxsorted( [ vector( x, 4, 2, 0 ) ] ); + + t.strictEqual( v, 4.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var x; + var v; + + x = new Float32Array([ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + 3.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = smaxsorted( [ vector( x, 4, -2, 6 ) ] ); + + t.strictEqual( v, 4.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var x; + var v; + + x = new Float32Array([ + 2.0, + 1.0, // 0 + 2.0, + 2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + + v = smaxsorted( [ vector( x, 4, 2, 1 ) ] ); + t.strictEqual( v, 4.0, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/test/test.native.js b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/test/test.native.js new file mode 100644 index 000000000000..5afff249b460 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smaxsorted/test/test.native.js @@ -0,0 +1,190 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); +var Float32Array = require( '@stdlib/array/float32' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var smaxsorted = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( smaxsorted instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float32Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof smaxsorted, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', opts, function test( t ) { + t.strictEqual( smaxsorted.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the maximum value of a one-dimensional ndarray', opts, function test( t ) { + var x; + var v; + + x = new Float32Array( [ -3.0, -2.0, -1.0, 1.0, 2.0, 3.0 ] ); + v = smaxsorted( [ vector( x, 6, 1, 0 ) ] ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + x = new Float32Array( [ 3.0, 2.0, 1.0, -1.0, -2.0, -3.0 ] ); + v = smaxsorted( [ vector( x, 6, 1, 0 ) ] ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + x = new Float32Array( [ -4.0, -5.0 ] ); + v = smaxsorted( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( v, -4.0, 'returns expected value' ); + + x = new Float32Array( [ -0.0, -0.0, 0.0 ] ); + v = smaxsorted( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( isPositiveZerof( v ), true, 'returns expected value' ); + + x = new Float32Array( [ 0.0, -0.0, -0.0 ] ); + v = smaxsorted( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( isPositiveZerof( v ), true, 'returns expected value' ); + + x = new Float32Array( [ NaN ] ); + v = smaxsorted( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + x = new Float32Array( [ NaN, NaN ] ); + v = smaxsorted( [ vector( x, 2, 1, 0 ) ] ); + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `NaN`', opts, function test( t ) { + var x; + var v; + + x = new Float32Array( [] ); + + v = smaxsorted( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an ndarray containing a single element, the function returns that element', opts, function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0 ] ); + + v = smaxsorted( [ vector( x, 1, 1, 0 ) ] ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', opts, function test( t ) { + var x; + var v; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + 3.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]); + + v = smaxsorted( [ vector( x, 4, 2, 0 ) ] ); + + t.strictEqual( v, 4.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', opts, function test( t ) { + var x; + var v; + + x = new Float32Array([ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + 3.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = smaxsorted( [ vector( x, 4, -2, 6 ) ] ); + + t.strictEqual( v, 4.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', opts, function test( t ) { + var x; + var v; + + x = new Float32Array([ + 2.0, + 1.0, // 0 + 2.0, + 2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + + v = smaxsorted( [ vector( x, 4, 2, 1 ) ] ); + t.strictEqual( v, 4.0, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/smean/benchmark/benchmark.js index 6c96fb5025ce..ccd50d800b29 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smean/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smean = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn/benchmark/benchmark.js index 7fe421717c4b..df4b2581524a 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeankbn = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/benchmark/benchmark.js index c182d9990fb9..710f92b25867 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeankbn2 = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeanli/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/smeanli/benchmark/benchmark.js index ee1b4dce6124..97d5f26b7544 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smeanli/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeanli/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanli = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeanlipw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/smeanlipw/benchmark/benchmark.js index 47529fd70bc6..19b16add1fbb 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smeanlipw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeanlipw/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanlipw = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/smeanors/benchmark/benchmark.js index a64689f502da..754c9f4f2a16 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeanors/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanors = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/smeanpn/benchmark/benchmark.js index 304ed6abbd4d..c40076ec1ea9 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smeanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeanpn/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanpn = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeanpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/smeanpw/benchmark/benchmark.js index b78ad96a71f4..2685fd337107 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smeanpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeanpw/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanpw = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/smeanwd/benchmark/benchmark.js index 32edac42561a..d2bd1d1021a4 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeanwd/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanwd = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smediansorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/smediansorted/benchmark/benchmark.js index ed5a31df2982..b8fff802389b 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smediansorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smediansorted/benchmark/benchmark.js @@ -25,6 +25,7 @@ var linspace = require( '@stdlib/array/linspace' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smediansorted = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sminsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/sminsorted/benchmark/benchmark.js index 9342e32a8cef..937c6a14b3e1 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/sminsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sminsorted/benchmark/benchmark.js @@ -25,6 +25,7 @@ var linspace = require( '@stdlib/array/linspace' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sminsorted = require( './../lib' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smskmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/smskmax/benchmark/benchmark.js index 577e36c314d4..625cd6977592 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smskmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smskmax/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskmax = require( './../lib' ); @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/smskmin/benchmark/benchmark.js index f0da3da597f6..6c48d54433b7 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/smskmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/smskmin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskmin = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/snanmaxabs/benchmark/benchmark.js index 9c5f63a263a9..e426dc0ee45e 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmaxabs/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmaxabs = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/snanmean/benchmark/benchmark.js index 56abaf18a132..16d748aa3017 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmean/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmean = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanors/benchmark/benchmark.js index 8d3cca8c6274..fef429ff1fa4 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanors/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmeanors = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanpn/benchmark/benchmark.js index 4bd3c68dc88a..09c91b7c3f34 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanpn/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmeanpn = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanwd/benchmark/benchmark.js index 4a6dc3eec448..52be6df7b81a 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanwd/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmeanwd = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/snanmin/benchmark/benchmark.js index 7e8a3e1c41d2..93eef0d909c9 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmin/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmin = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/snanminabs/benchmark/benchmark.js index 88da137b48d1..f2e3bf6b2ee0 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanminabs/benchmark/benchmark.js @@ -27,6 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanminabs = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmskmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/snanmskmax/benchmark/benchmark.js index 7c5b790f6ea2..45797c27338a 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmskmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmskmax/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmskmax = require( './../lib' ); @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/snanmskmin/benchmark/benchmark.js index d8e0467eb23b..5abf8639adff 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmskmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmskmin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmskmin = require( './../lib' ); @@ -110,7 +111,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmskrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/snanmskrange/benchmark/benchmark.js index ecebdbf1be66..dfdb9b5d855d 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmskrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmskrange/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmskrange = require( './../lib' ); @@ -111,7 +112,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sstdevtk/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/sstdevtk/README.md index 997cd21452f0..528da5efa44d 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/sstdevtk/README.md +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sstdevtk/README.md @@ -133,6 +133,7 @@ The function has the following parameters: - If provided an empty one-dimensional ndarray, the function returns `NaN`. - If `N - c` is less than or equal to `0` (where `N` corresponds to the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment), the function returns `NaN`. +- Some caution should be exercised when using the one-pass textbook algorithm. Literature overwhelmingly discourages the algorithm's use for two reasons: 1) the lack of safeguards against underflow and overflow and 2) the risk of catastrophic cancellation when subtracting the two sums if the sums are large and the variance small. These concerns have merit; however, the one-pass textbook algorithm should not be dismissed outright. For data distributions with a moderately large standard deviation to mean ratio (i.e., **coefficient of variation**), the one-pass textbook algorithm may be acceptable, especially when performance is paramount and some precision loss is acceptable (including a risk of computing a negative variance due to floating-point rounding errors!). In short, no single "best" algorithm for computing the standard deviation exists. The "best" algorithm depends on the underlying data distribution, your performance requirements, and your minimum precision requirements. When evaluating which algorithm to use, consider the relative pros and cons, and choose the algorithm which best serves your needs.
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/stdevtk/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/stdevtk/README.md index 7eb7e6951db4..cfd0075339a1 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/stdevtk/README.md +++ b/lib/node_modules/@stdlib/stats/base/ndarray/stdevtk/README.md @@ -132,6 +132,7 @@ The function has the following parameters: - If provided an empty one-dimensional ndarray, the function returns `NaN`. - If `N - c` is less than or equal to `0` (where `N` corresponds to the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment), the function returns `NaN`. +- Some caution should be exercised when using the one-pass textbook algorithm. Literature overwhelmingly discourages the algorithm's use for two reasons: 1) the lack of safeguards against underflow and overflow and 2) the risk of catastrophic cancellation when subtracting the two sums if the sums are large and the variance small. These concerns have merit; however, the one-pass textbook algorithm should not be dismissed outright. For data distributions with a moderately large standard deviation to mean ratio (i.e., **coefficient of variation**), the one-pass textbook algorithm may be acceptable, especially when performance is paramount and some precision loss is acceptable (including a risk of computing a negative variance due to floating-point rounding errors!). In short, no single "best" algorithm for computing the standard deviation exists. The "best" algorithm depends on the underlying data distribution, your performance requirements, and your minimum precision requirements. When evaluating which algorithm to use, consider the relative pros and cons, and choose the algorithm which best serves your needs. diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/benchmark/benchmark.js index c2ef3f7c185d..7bcdd3f01af6 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/benchmark/benchmark.js @@ -29,6 +29,7 @@ var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); var Float32Results = require( '@stdlib/stats/base/ztest/one-sample/results/float32' ); var resolveEnum = require( '@stdlib/stats/base/ztest/alternative-resolve-enum' ); var structFactory = require( '@stdlib/array/struct-factory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sztest = require( './../lib' ); @@ -120,7 +121,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/sztest2/benchmark/benchmark.js index 90bc7c0ceb86..717b8d62b438 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/sztest2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest2/benchmark/benchmark.js @@ -29,6 +29,7 @@ var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); var Float32Results = require( '@stdlib/stats/base/ztest/two-sample/results/float32' ); var resolveEnum = require( '@stdlib/stats/base/ztest/alternative-resolve-enum' ); var structFactory = require( '@stdlib/array/struct-factory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sztest2 = require( './../lib' ); @@ -127,7 +128,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/README.md new file mode 100644 index 000000000000..38591e72d990 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/README.md @@ -0,0 +1,203 @@ + + +# variancepn + +> Calculate the [variance][variance] of a one-dimensional ndarray using a two-pass algorithm. + +
+ +The population [variance][variance] of a finite size population of size `N` is given by + + + +```math +\sigma^2 = \frac{1}{N} \sum_{i=0}^{N-1} (x_i - \mu)^2 +``` + + + + + +where the population mean is given by + + + +```math +\mu = \frac{1}{N} \sum_{i=0}^{N-1} x_i +``` + + + + + +Often in the analysis of data, the true population [variance][variance] is not known _a priori_ and must be estimated from a sample drawn from the population distribution. If one attempts to use the formula for the population [variance][variance], the result is biased and yields an **uncorrected sample variance**. To compute a **corrected sample variance** for a sample of size `n`, + + + +```math +s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} (x_i - \bar{x})^2 +``` + + + + + +where the sample mean is given by + + + +```math +\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i +``` + + + + + +The use of the term `n-1` is commonly referred to as Bessel's correction. Note, however, that applying Bessel's correction can increase the mean squared error between the sample variance and population variance. Depending on the characteristics of the population distribution, other correction factors (e.g., `n-1.5`, `n+1`, etc) can yield better estimators. + +
+ + + +
+ +## Usage + +```javascript +var variancepn = require( '@stdlib/stats/base/ndarray/variancepn' ); +``` + +#### variancepn( arrays ) + +Computes the [variance][variance] of a one-dimensional ndarray using a two-pass algorithm. + +```javascript +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var opts = { + 'dtype': 'generic' +}; + +var xbuf = [ 1.0, -2.0, 2.0 ]; +var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); +var correction = scalar2ndarray( 1.0, opts ); + +var v = variancepn( [ x, correction ] ); +// returns ~4.3333 +``` + +The function has the following parameters: + +- **arrays**: array-like object containing two elements: a one-dimensional input ndarray and a zero-dimensional ndarray specifying the degrees of freedom adjustment. Providing a non-zero degrees of freedom adjustment has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `N` is the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). + +
+ + + +
+ +## Notes + +- If provided an empty one-dimensional ndarray, the function returns `NaN`. +- If `N - c` is less than or equal to `0` (where `N` corresponds to the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment), the function returns `NaN`. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var variancepn = require( '@stdlib/stats/base/ndarray/variancepn' ); + +var opts = { + 'dtype': 'float64' +}; + +var xbuf = discreteUniform( 10, -50, 50, opts ); +var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var correction = scalar2ndarray( 1.0, opts ); +var v = variancepn( [ x, correction ] ); +console.log( v ); +``` + +
+ + + +* * * + +
+ +## References + +- Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958][@neely:1966a]. +- Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036][@schubert:2018a]. + +
+ + + + + +
+ +
+ + + + + +
+ +[variance]: https://en.wikipedia.org/wiki/Variance + +[@neely:1966a]: https://doi.org/10.1145/365719.365958 + +[@schubert:2018a]: https://doi.org/10.1145/3221269.3223036 + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/benchmark/benchmark.js new file mode 100644 index 000000000000..5e24d27f014e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/benchmark/benchmark.js @@ -0,0 +1,112 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var variancepn = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var correction; + var xbuf; + var x; + + xbuf = uniform( len, -10.0, 10.0, options ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + correction = scalar2ndarray( 1.0, options ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = variancepn( [ x, correction ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/docs/img/equation_sample_mean.svg b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/docs/img/equation_sample_mean.svg new file mode 100644 index 000000000000..aea7a5f6687a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/docs/img/equation_sample_mean.svg @@ -0,0 +1,43 @@ + +x overbar equals StartFraction 1 Over n EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts x Subscript i + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/docs/repl.txt new file mode 100644 index 000000000000..4198daf222a2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/docs/repl.txt @@ -0,0 +1,54 @@ + +{{alias}}( arrays ) + Computes the variance of a one-dimensional ndarray using a two-pass + algorithm. + + If provided an empty one-dimensional ndarray, the function returns `NaN`. + + If `N - c` is less than or equal to `0` (where `N` corresponds to the number + of elements in the input ndarray and `c` corresponds to the provided degrees + of freedom adjustment), the function returns `NaN`. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing two elements: a one-dimensional input + ndarray and a zero-dimensional ndarray specifying the degrees of freedom + adjustment. Providing a non-zero degrees of freedom adjustment has the + effect of adjusting the divisor during the calculation of the variance + according to `N-c` where `N` is the number of elements in the input + ndarray and `c` corresponds to the provided degrees of freedom + adjustment. When computing the variance of a population, setting this + parameter to `0` is the standard choice (i.e., the provided array + contains data constituting an entire population). When computing the + corrected sample variance, setting this parameter to `1` is the standard + choice (i.e., the provided array contains data sampled from a larger + population; this is commonly referred to as Bessel's correction). + + Returns + ------- + out: number + The variance. + + Examples + -------- + // Create input ndarray: + > var xbuf = [ 1.0, -2.0, 2.0 ]; + > var dt = 'generic'; + > var sh = [ xbuf.length ]; + > var st = [ 1 ]; + > var oo = 0; + > var ord = 'row-major'; + > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, st, oo, ord ); + + // Create correction ndarray: + > var opts = { 'dtype': dt }; + > var correction = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + // Compute the variance: + > {{alias}}( [ x, correction ] ) + ~4.333 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/docs/types/index.d.ts new file mode 100644 index 000000000000..4e369e89fd2a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray } from '@stdlib/types/ndarray'; + +/** +* Computes the variance of a one-dimensional ndarray using a two-pass algorithm. +* +* @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment +* @returns variance +* +* @example +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var opts = { +* 'dtype': 'float64' +* }; +* +* var xbuf = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = variancepn( [ x, correction ] ); +* // returns ~4.333 +*/ +declare function variancepn = typedndarray>( arrays: [ T, T ] ): number; + + +// EXPORTS // + +export = variancepn; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/docs/types/test.ts new file mode 100644 index 000000000000..5d9b7bf243aa --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/docs/types/test.ts @@ -0,0 +1,65 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +import variancepn = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const correction = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + variancepn( [ x, correction ] ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + variancepn( '10' ); // $ExpectError + variancepn( 10 ); // $ExpectError + variancepn( true ); // $ExpectError + variancepn( false ); // $ExpectError + variancepn( null ); // $ExpectError + variancepn( undefined ); // $ExpectError + variancepn( [] ); // $ExpectError + variancepn( {} ); // $ExpectError + variancepn( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const correction = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + variancepn(); // $ExpectError + variancepn( [ x, correction ], 10 ); // $ExpectError +} + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/examples/index.js new file mode 100644 index 000000000000..6de65481f7ef --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var variancepn = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var xbuf = discreteUniform( 10, -50, 50, opts ); +var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var correction = scalar2ndarray( 1.0, opts ); +var v = variancepn( [ x, correction ] ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/lib/index.js new file mode 100644 index 000000000000..87bfb0d5eae6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the variance of a one-dimensional ndarray using a two-pass algorithm. +* +* @module @stdlib/stats/base/ndarray/variancepn +* +* @example +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/ctor' ); +* var variancepn = require( '@stdlib/stats/base/ndarray/variancepn' ); +* +* var opts = { +* 'dtype': 'generic' +* }; +* +* // Define a one-dimensional input ndarray: +* var xbuf = [ 1.0, -2.0, 2.0 ]; +* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); +* +* // Specify the degrees of freedom adjustment: +* var correction = scalar2ndarray( 1.0, opts ); +* +* // Compute the variance: +* var v = variancepn( [ x, correction ] ); +* // returns ~4.3333 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/lib/main.js new file mode 100644 index 000000000000..cb5d8be15087 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/lib/main.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/stats/strided/variancepn' ).ndarray; + + +// MAIN // + +/** +* Computes the variance of a one-dimensional ndarray using a two-pass algorithm. +* +* @param {ArrayLikeObject} arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment +* @returns {number} variance +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var opts = { +* 'dtype': 'float64' +* }; +* +* var xbuf = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +* var x = new ndarray( opts.dtype, xbuf, [ 4 ], [ 2 ], 1, 'row-major' ); +* +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = variancepn( [ x, correction ] ); +* // returns 6.25 +*/ +function variancepn( arrays ) { + var correction; + var x; + + x = arrays[ 0 ]; + correction = ndarraylike2scalar( arrays[ 1 ] ); + + return strided( numelDimension( x, 0 ), correction, getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = variancepn; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/package.json new file mode 100644 index 000000000000..5df316f23c9e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/stats/base/ndarray/variancepn", + "version": "0.0.0", + "description": "Compute the variance of a one-dimensional ndarray using a two-pass algorithm.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "var", + "deviation", + "dispersion", + "spread", + "sample variance", + "unbiased", + "variance", + "std", + "ndarray", + "typed", + "array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/test/test.js new file mode 100644 index 000000000000..355efa415840 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancepn/test/test.js @@ -0,0 +1,227 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var variancepn = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof variancepn, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( variancepn.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the variance of a one-dimensional ndarray', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = variancepn( [ vector( x, x.length, 1, 0 ), correction ] ); + expected = 53.5 / (x.length-1); + t.strictEqual( v, expected, 'returns expected value' ); + + x = new Float64Array( [ -4.0, -5.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = variancepn( [ vector( x, x.length, 1, 0 ), correction ] ); + expected = 0.5; + t.strictEqual( v, expected, 'returns expected value' ); + + x = new Float64Array( [ NaN ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = variancepn( [ vector( x, x.length, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = variancepn( [ vector( x, x.length, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) { + var correction; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array( [] ); + correction = scalar2ndarray( 1.0, opts ); + + v = variancepn( [ vector( x, 0, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a correction argument yielding `N-correction` less than or equal to `0`, the function returns `NaN`', function test( t ) { + var correction; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array( [ 1.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = variancepn( [ vector( x, 1, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]); + correction = scalar2ndarray( 1.0, opts ); + + v = variancepn( [ vector( x, 4, 2, 0 ), correction ] ); + expected = 6.25; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array([ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + correction = scalar2ndarray( 1.0, opts ); + + v = variancepn( [ vector( x, 4, -2, 6 ), correction ] ); + expected = 6.25; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + correction = scalar2ndarray( 1.0, opts ); + + v = variancepn( [ vector( x, 4, 2, 1 ), correction ] ); + expected = 6.25; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/README.md new file mode 100644 index 000000000000..2ccc81e741f8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/README.md @@ -0,0 +1,201 @@ + + +# variancetk + +> Calculate the [variance][variance] of a one-dimensional ndarray using a one-pass textbook algorithm. + +
+ +The population [variance][variance] of a finite size population of size `N` is given by + + + +```math +\sigma^2 = \frac{1}{N} \sum_{i=0}^{N-1} (x_i - \mu)^2 +``` + + + + + +where the population mean is given by + + + +```math +\mu = \frac{1}{N} \sum_{i=0}^{N-1} x_i +``` + + + + + +Often in the analysis of data, the true population [variance][variance] is not known _a priori_ and must be estimated from a sample drawn from the population distribution. If one attempts to use the formula for the population [variance][variance], the result is biased and yields an **uncorrected sample variance**. To compute a **corrected sample variance** for a sample of size `n`, + + + +```math +s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} (x_i - \bar{x})^2 +``` + + + + + +where the sample mean is given by + + + +```math +\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i +``` + + + + + +The use of the term `n-1` is commonly referred to as Bessel's correction. Note, however, that applying Bessel's correction can increase the mean squared error between the sample variance and population variance. Depending on the characteristics of the population distribution, other correction factors (e.g., `n-1.5`, `n+1`, etc) can yield better estimators. + +
+ + + +
+ +## Usage + +```javascript +var variancetk = require( '@stdlib/stats/base/ndarray/variancetk' ); +``` + +#### variancetk( arrays ) + +Computes the [variance][variance] of a one-dimensional ndarray using a one-pass textbook algorithm. + +```javascript +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var opts = { + 'dtype': 'generic' +}; + +var xbuf = [ 1.0, -2.0, 2.0 ]; +var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); +var correction = scalar2ndarray( 1.0, opts ); + +var v = variancetk( [ x, correction ] ); +// returns ~4.3333 +``` + +The function has the following parameters: + +- **arrays**: array-like object containing two elements: a one-dimensional input ndarray and a zero-dimensional ndarray specifying the degrees of freedom adjustment. Providing a non-zero degrees of freedom adjustment has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `N` is the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). + +
+ + + +
+ +## Notes + +- If provided an empty one-dimensional ndarray, the function returns `NaN`. +- If `N - c` is less than or equal to `0` (where `N` corresponds to the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment), the function returns `NaN`. +- Some caution should be exercised when using the one-pass textbook algorithm. Literature overwhelmingly discourages the algorithm's use for two reasons: 1) the lack of safeguards against underflow and overflow and 2) the risk of catastrophic cancellation when subtracting the two sums if the sums are large and the variance small. These concerns have merit; however, the one-pass textbook algorithm should not be dismissed outright. For data distributions with a moderately large standard deviation to mean ratio (i.e., **coefficient of variation**), the one-pass textbook algorithm may be acceptable, especially when performance is paramount and some precision loss is acceptable (including a risk of returning a negative variance due to floating-point rounding errors!). In short, no single "best" algorithm for computing the variance exists. The "best" algorithm depends on the underlying data distribution, your performance requirements, and your minimum precision requirements. When evaluating which algorithm to use, consider the relative pros and cons, and choose the algorithm which best serves your needs. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var variancetk = require( '@stdlib/stats/base/ndarray/variancetk' ); + +var opts = { + 'dtype': 'float64' +}; + +var xbuf = discreteUniform( 10, -50, 50, opts ); +var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var correction = scalar2ndarray( 1.0, opts ); +var v = variancetk( [ x, correction ] ); +console.log( v ); +``` + +
+ + + +* * * + +
+ +## References + +- Ling, Robert F. 1974. "Comparison of Several Algorithms for Computing Sample Means and Variances." _Journal of the American Statistical Association_ 69 (348). American Statistical Association, Taylor & Francis, Ltd.: 859–66. doi:[10.2307/2286154][@ling:1974a]. + +
+ + + + + +
+ +
+ + + + + +
+ +[variance]: https://en.wikipedia.org/wiki/Variance + +[@ling:1974a]: https://doi.org/10.2307/2286154 + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/benchmark/benchmark.js new file mode 100644 index 000000000000..0e50b03ce114 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/benchmark/benchmark.js @@ -0,0 +1,112 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var variancetk = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var correction; + var xbuf; + var x; + + xbuf = uniform( len, -10.0, 10.0, options ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + correction = scalar2ndarray( 1.0, options ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = variancetk( [ x, correction ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/docs/img/equation_sample_mean.svg b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/docs/img/equation_sample_mean.svg new file mode 100644 index 000000000000..aea7a5f6687a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/docs/img/equation_sample_mean.svg @@ -0,0 +1,43 @@ + +x overbar equals StartFraction 1 Over n EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts x Subscript i + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/docs/repl.txt new file mode 100644 index 000000000000..5799881661fe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/docs/repl.txt @@ -0,0 +1,54 @@ + +{{alias}}( arrays ) + Computes the variance of a one-dimensional ndarray using a one-pass textbook + algorithm. + + If provided an empty one-dimensional ndarray, the function returns `NaN`. + + If `N - c` is less than or equal to `0` (where `N` corresponds to the number + of elements in the input ndarray and `c` corresponds to the provided degrees + of freedom adjustment), the function returns `NaN`. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing two elements: a one-dimensional input + ndarray and a zero-dimensional ndarray specifying the degrees of freedom + adjustment. Providing a non-zero degrees of freedom adjustment has the + effect of adjusting the divisor during the calculation of the variance + according to `N-c` where `N` is the number of elements in the input + ndarray and `c` corresponds to the provided degrees of freedom + adjustment. When computing the variance of a population, setting this + parameter to `0` is the standard choice (i.e., the provided array + contains data constituting an entire population). When computing the + corrected sample variance, setting this parameter to `1` is the standard + choice (i.e., the provided array contains data sampled from a larger + population; this is commonly referred to as Bessel's correction). + + Returns + ------- + out: number + The variance. + + Examples + -------- + // Create input ndarray: + > var xbuf = [ 1.0, -2.0, 2.0 ]; + > var dt = 'generic'; + > var sh = [ xbuf.length ]; + > var st = [ 1 ]; + > var oo = 0; + > var ord = 'row-major'; + > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, st, oo, ord ); + + // Create correction ndarray: + > var opts = { 'dtype': dt }; + > var correction = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + // Compute the variance: + > {{alias}}( [ x, correction ] ) + ~4.3333 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/docs/types/index.d.ts new file mode 100644 index 000000000000..47c57990c529 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray } from '@stdlib/types/ndarray'; + +/** +* Computes the variance of a one-dimensional ndarray using a one-pass textbook algorithm. +* +* @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment +* @returns variance +* +* @example +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var opts = { +* 'dtype': 'float64' +* }; +* +* var xbuf = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = variancetk( [ x, correction ] ); +* // returns ~4.3333 +*/ +declare function variancetk = typedndarray>( arrays: [ T, T ] ): number; + + +// EXPORTS // + +export = variancetk; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/docs/types/test.ts new file mode 100644 index 000000000000..e8ee046c159d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/docs/types/test.ts @@ -0,0 +1,65 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +import variancetk = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const correction = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + variancetk( [ x, correction ] ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + variancetk( '10' ); // $ExpectError + variancetk( 10 ); // $ExpectError + variancetk( true ); // $ExpectError + variancetk( false ); // $ExpectError + variancetk( null ); // $ExpectError + variancetk( undefined ); // $ExpectError + variancetk( [] ); // $ExpectError + variancetk( {} ); // $ExpectError + variancetk( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const correction = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + variancetk(); // $ExpectError + variancetk( [ x, correction ], 10 ); // $ExpectError +} + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/examples/index.js new file mode 100644 index 000000000000..1dec7993be6e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var variancetk = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var xbuf = discreteUniform( 10, -50, 50, opts ); +var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var correction = scalar2ndarray( 1.0, opts ); +var v = variancetk( [ x, correction ] ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/lib/index.js new file mode 100644 index 000000000000..0eaa9b1ca66c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the variance of a one-dimensional ndarray using a one-pass textbook algorithm. +* +* @module @stdlib/stats/base/ndarray/variancetk +* +* @example +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/ctor' ); +* var variancetk = require( '@stdlib/stats/base/ndarray/variancetk' ); +* +* var opts = { +* 'dtype': 'generic' +* }; +* +* // Define a one-dimensional input ndarray: +* var xbuf = [ 1.0, -2.0, 2.0 ]; +* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); +* +* // Specify the degrees of freedom adjustment: +* var correction = scalar2ndarray( 1.0, opts ); +* +* // Compute the variance: +* var v = variancetk( [ x, correction ] ); +* // returns ~4.3333 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/lib/main.js new file mode 100644 index 000000000000..3b83dfe17eee --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/lib/main.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/stats/strided/variancetk' ).ndarray; + + +// MAIN // + +/** +* Computes the variance of a one-dimensional ndarray using a one-pass textbook algorithm. +* +* @param {ArrayLikeObject} arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment +* @returns {number} variance +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var opts = { +* 'dtype': 'float64' +* }; +* +* var xbuf = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +* var x = new ndarray( opts.dtype, xbuf, [ 4 ], [ 2 ], 1, 'row-major' ); +* +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = variancetk( [ x, correction ] ); +* // returns 6.25 +*/ +function variancetk( arrays ) { + var correction; + var x; + + x = arrays[ 0 ]; + correction = ndarraylike2scalar( arrays[ 1 ] ); + + return strided( numelDimension( x, 0 ), correction, getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = variancetk; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/package.json new file mode 100644 index 000000000000..697adb5f161c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/stats/base/ndarray/variancetk", + "version": "0.0.0", + "description": "Compute the variance of a one-dimensional ndarray using a one-pass textbook algorithm.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "variance", + "var", + "dispersion", + "spread", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/test/test.js new file mode 100644 index 000000000000..7eeb72064d3d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancetk/test/test.js @@ -0,0 +1,227 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var variancetk = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof variancetk, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( variancetk.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the variance of a one-dimensional ndarray', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = variancetk( [ vector( x, x.length, 1, 0 ), correction ] ); + expected = 53.5 / (x.length-1); + t.strictEqual( v, expected, 'returns expected value' ); + + x = new Float64Array( [ -4.0, -5.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = variancetk( [ vector( x, x.length, 1, 0 ), correction ] ); + expected = 0.5; + t.strictEqual( v, expected, 'returns expected value' ); + + x = new Float64Array( [ NaN ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = variancetk( [ vector( x, x.length, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = variancetk( [ vector( x, x.length, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) { + var correction; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array( [] ); + correction = scalar2ndarray( 1.0, opts ); + + v = variancetk( [ vector( x, 0, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a correction argument yielding `N-correction` less than or equal to `0`, the function returns `NaN`', function test( t ) { + var correction; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array( [ 1.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = variancetk( [ vector( x, 1, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]); + correction = scalar2ndarray( 1.0, opts ); + + v = variancetk( [ vector( x, 4, 2, 0 ), correction ] ); + expected = 6.25; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array([ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + correction = scalar2ndarray( 1.0, opts ); + + v = variancetk( [ vector( x, 4, -2, 6 ), correction ] ); + expected = 6.25; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + correction = scalar2ndarray( 1.0, opts ); + + v = variancetk( [ vector( x, 4, 2, 1 ), correction ] ); + expected = 6.25; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/README.md new file mode 100644 index 000000000000..0750d988b5ae --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/README.md @@ -0,0 +1,200 @@ + + +# varianceyc + +> Calculate the [variance][variance] of a one-dimensional ndarray using a one-pass algorithm proposed by Youngs and Cramer. + +
+ +The population [variance][variance] of a finite size population of size `N` is given by + + + +```math +\sigma^2 = \frac{1}{N} \sum_{i=0}^{N-1} (x_i - \mu)^2 +``` + + + + + +where the population mean is given by + + + +```math +\mu = \frac{1}{N} \sum_{i=0}^{N-1} x_i +``` + + + + + +Often in the analysis of data, the true population [variance][variance] is not known _a priori_ and must be estimated from a sample drawn from the population distribution. If one attempts to use the formula for the population [variance][variance], the result is biased and yields an **uncorrected sample variance**. To compute a **corrected sample variance** for a sample of size `n`, + + + +```math +s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} (x_i - \bar{x})^2 +``` + + + + + +where the sample mean is given by + + + +```math +\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i +``` + + + + + +The use of the term `n-1` is commonly referred to as Bessel's correction. Note, however, that applying Bessel's correction can increase the mean squared error between the sample variance and population variance. Depending on the characteristics of the population distribution, other correction factors (e.g., `n-1.5`, `n+1`, etc) can yield better estimators. + +
+ + + +
+ +## Usage + +```javascript +var varianceyc = require( '@stdlib/stats/base/ndarray/varianceyc' ); +``` + +#### varianceyc( arrays ) + +Computes the [variance][variance] of a one-dimensional ndarray using a one-pass algorithm proposed by Youngs and Cramer. + +```javascript +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var opts = { + 'dtype': 'generic' +}; + +var xbuf = [ 1.0, -2.0, 2.0 ]; +var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); +var correction = scalar2ndarray( 1.0, opts ); + +var v = varianceyc( [ x, correction ] ); +// returns ~4.3333 +``` + +The function has the following parameters: + +- **arrays**: array-like object containing two elements: a one-dimensional input ndarray and a zero-dimensional ndarray specifying the degrees of freedom adjustment. Providing a non-zero degrees of freedom adjustment has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `N` is the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). + +
+ + + +
+ +## Notes + +- If provided an empty one-dimensional ndarray, the function returns `NaN`. +- If `N - c` is less than or equal to `0` (where `N` corresponds to the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment), the function returns `NaN`. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var varianceyc = require( '@stdlib/stats/base/ndarray/varianceyc' ); + +var opts = { + 'dtype': 'float64' +}; + +var xbuf = discreteUniform( 10, -50, 50, opts ); +var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var correction = scalar2ndarray( 1.0, opts ); +var v = varianceyc( [ x, correction ] ); +console.log( v ); +``` + +
+ + + +* * * + +
+ +## References + +- Youngs, Edward A., and Elliot M. Cramer. 1971. "Some Results Relevant to Choice of Sum and Sum-of-Product Algorithms." _Technometrics_ 13 (3): 657–65. doi:[10.1080/00401706.1971.10488826][@youngs:1971a]. + +
+ + + + + +
+ +
+ + + + + +
+ +[variance]: https://en.wikipedia.org/wiki/Variance + +[@youngs:1971a]: https://doi.org/10.1080/00401706.1971.10488826 + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/benchmark/benchmark.js new file mode 100644 index 000000000000..675dc757cdf9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/benchmark/benchmark.js @@ -0,0 +1,112 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var varianceyc = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var correction; + var xbuf; + var x; + + xbuf = uniform( len, -10.0, 10.0, options ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + correction = scalar2ndarray( 1.0, options ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = varianceyc( [ x, correction ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/docs/img/equation_sample_mean.svg b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/docs/img/equation_sample_mean.svg new file mode 100644 index 000000000000..aea7a5f6687a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/docs/img/equation_sample_mean.svg @@ -0,0 +1,43 @@ + +x overbar equals StartFraction 1 Over n EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts x Subscript i + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/docs/repl.txt new file mode 100644 index 000000000000..3e53ac8714d2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/docs/repl.txt @@ -0,0 +1,54 @@ + +{{alias}}( arrays ) + Computes the variance of a one-dimensional ndarray using a one-pass + algorithm proposed by Youngs and Cramer. + + If provided an empty one-dimensional ndarray, the function returns `NaN`. + + If `N - c` is less than or equal to `0` (where `N` corresponds to the number + of elements in the input ndarray and `c` corresponds to the provided degrees + of freedom adjustment), the function returns `NaN`. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing two elements: a one-dimensional input + ndarray and a zero-dimensional ndarray specifying the degrees of freedom + adjustment. Providing a non-zero degrees of freedom adjustment has the + effect of adjusting the divisor during the calculation of the variance + according to `N-c` where `N` is the number of elements in the input + ndarray and `c` corresponds to the provided degrees of freedom + adjustment. When computing the variance of a population, setting this + parameter to `0` is the standard choice (i.e., the provided array + contains data constituting an entire population). When computing the + corrected sample variance, setting this parameter to `1` is the standard + choice (i.e., the provided array contains data sampled from a larger + population; this is commonly referred to as Bessel's correction). + + Returns + ------- + out: number + The variance. + + Examples + -------- + // Create input ndarray: + > var xbuf = [ 1.0, -2.0, 2.0 ]; + > var dt = 'generic'; + > var sh = [ xbuf.length ]; + > var st = [ 1 ]; + > var oo = 0; + > var ord = 'row-major'; + > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, st, oo, ord ); + + // Create correction ndarray: + > var opts = { 'dtype': dt }; + > var correction = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + // Compute the variance: + > {{alias}}( [ x, correction ] ) + ~4.3333 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/docs/types/index.d.ts new file mode 100644 index 000000000000..1bf315629c64 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray } from '@stdlib/types/ndarray'; + +/** +* Computes the variance of a one-dimensional ndarray using a one-pass algorithm proposed by Youngs and Cramer. +* +* @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment +* @returns variance +* +* @example +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var opts = { +* 'dtype': 'float64' +* }; +* +* var xbuf = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = varianceyc( [ x, correction ] ); +* // returns ~4.3333 +*/ +declare function varianceyc = typedndarray>( arrays: [ T, T ] ): number; + + +// EXPORTS // + +export = varianceyc; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/docs/types/test.ts new file mode 100644 index 000000000000..6717e1be61c2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/docs/types/test.ts @@ -0,0 +1,65 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +import varianceyc = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const correction = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + varianceyc( [ x, correction ] ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + varianceyc( '10' ); // $ExpectError + varianceyc( 10 ); // $ExpectError + varianceyc( true ); // $ExpectError + varianceyc( false ); // $ExpectError + varianceyc( null ); // $ExpectError + varianceyc( undefined ); // $ExpectError + varianceyc( [] ); // $ExpectError + varianceyc( {} ); // $ExpectError + varianceyc( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const correction = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + varianceyc(); // $ExpectError + varianceyc( [ x, correction ], 10 ); // $ExpectError +} + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/examples/index.js new file mode 100644 index 000000000000..8a252536da6a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var varianceyc = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var xbuf = discreteUniform( 10, -50, 50, opts ); +var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var correction = scalar2ndarray( 1.0, opts ); +var v = varianceyc( [ x, correction ] ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/lib/index.js new file mode 100644 index 000000000000..689782451b5c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the variance of a one-dimensional ndarray using a one-pass algorithm proposed by Youngs and Cramer. +* +* @module @stdlib/stats/base/ndarray/varianceyc +* +* @example +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/ctor' ); +* var varianceyc = require( '@stdlib/stats/base/ndarray/varianceyc' ); +* +* var opts = { +* 'dtype': 'generic' +* }; +* +* // Define a one-dimensional input ndarray: +* var xbuf = [ 1.0, -2.0, 2.0 ]; +* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); +* +* // Specify the degrees of freedom adjustment: +* var correction = scalar2ndarray( 1.0, opts ); +* +* // Compute the variance: +* var v = varianceyc( [ x, correction ] ); +* // returns ~4.3333 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/lib/main.js new file mode 100644 index 000000000000..940db1492f7c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/lib/main.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/stats/strided/varianceyc' ).ndarray; + + +// MAIN // + +/** +* Computes the variance of a one-dimensional ndarray using a one-pass algorithm proposed by Youngs and Cramer. +* +* @param {ArrayLikeObject} arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment +* @returns {number} variance +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var opts = { +* 'dtype': 'float64' +* }; +* +* var xbuf = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +* var x = new ndarray( opts.dtype, xbuf, [ 4 ], [ 2 ], 1, 'row-major' ); +* +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = varianceyc( [ x, correction ] ); +* // returns 6.25 +*/ +function varianceyc( arrays ) { + var correction; + var x; + + x = arrays[ 0 ]; + correction = ndarraylike2scalar( arrays[ 1 ] ); + + return strided( numelDimension( x, 0 ), correction, getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = varianceyc; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/package.json new file mode 100644 index 000000000000..ed04569b547a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/stats/base/ndarray/varianceyc", + "version": "0.0.0", + "description": "Compute the variance of a one-dimensional ndarray using a one-pass algorithm proposed by Youngs and Cramer.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "variance", + "var", + "dispersion", + "spread", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/test/test.js new file mode 100644 index 000000000000..053f6029fc32 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/varianceyc/test/test.js @@ -0,0 +1,227 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var varianceyc = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof varianceyc, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( varianceyc.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the variance of a one-dimensional ndarray', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = varianceyc( [ vector( x, x.length, 1, 0 ), correction ] ); + expected = 53.5 / (x.length-1); + t.strictEqual( v, expected, 'returns expected value' ); + + x = new Float64Array( [ -4.0, -5.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = varianceyc( [ vector( x, x.length, 1, 0 ), correction ] ); + expected = 0.5; + t.strictEqual( v, expected, 'returns expected value' ); + + x = new Float64Array( [ NaN ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = varianceyc( [ vector( x, x.length, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = varianceyc( [ vector( x, x.length, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) { + var correction; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array( [] ); + correction = scalar2ndarray( 1.0, opts ); + + v = varianceyc( [ vector( x, 0, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a correction argument yielding `N-correction` less than or equal to `0`, the function returns `NaN`', function test( t ) { + var correction; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array( [ 1.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = varianceyc( [ vector( x, 1, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]); + correction = scalar2ndarray( 1.0, opts ); + + v = varianceyc( [ vector( x, 4, 2, 0 ), correction ] ); + expected = 6.25; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array([ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + correction = scalar2ndarray( 1.0, opts ); + + v = varianceyc( [ vector( x, 4, -2, 6 ), correction ] ); + expected = 6.25; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + correction = scalar2ndarray( 1.0, opts ); + + v = varianceyc( [ vector( x, 4, 2, 1 ), correction ] ); + expected = 6.25; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/ztest/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/ztest/benchmark/benchmark.js index 199f2a2092ff..76bbbe457589 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/ztest/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/ztest/benchmark/benchmark.js @@ -29,6 +29,7 @@ var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); var Float64Results = require( '@stdlib/stats/base/ztest/one-sample/results/float64' ); var resolveEnum = require( '@stdlib/stats/base/ztest/alternative-resolve-enum' ); var structFactory = require( '@stdlib/array/struct-factory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ztest = require( './../lib' ); @@ -120,7 +121,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/ztest2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/ztest2/benchmark/benchmark.js index 7c748d1cc25c..d89852f91e41 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/ztest2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/ztest2/benchmark/benchmark.js @@ -29,6 +29,7 @@ var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); var Float64Results = require( '@stdlib/stats/base/ztest/two-sample/results/float64' ); var resolveEnum = require( '@stdlib/stats/base/ztest/alternative-resolve-enum' ); var structFactory = require( '@stdlib/array/struct-factory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ztest2 = require( './../lib' ); @@ -127,7 +128,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/base/ztest/alternative-resolve-enum/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ztest/alternative-resolve-enum/benchmark/benchmark.js index 47f6c7dc8ef0..f06ca62abcb0 100644 --- a/lib/node_modules/@stdlib/stats/base/ztest/alternative-resolve-enum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ztest/alternative-resolve-enum/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var str2enum = require( '@stdlib/stats/base/ztest/alternative-str2enum' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var resolve = require( './../lib' ); // MAIN // -bench( pkg+'::string', function benchmark( b ) { +bench( format( '%s::string', pkg ), function benchmark( b ) { var values; var out; var i; @@ -54,7 +55,7 @@ bench( pkg+'::string', function benchmark( b ) { b.end(); }); -bench( pkg+'::integer', function benchmark( b ) { +bench( format( '%s::integer', pkg ), function benchmark( b ) { var values; var out; var i; diff --git a/lib/node_modules/@stdlib/stats/base/ztest/alternative-resolve-str/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ztest/alternative-resolve-str/benchmark/benchmark.js index f8b6c4c2864e..861d0478c93e 100644 --- a/lib/node_modules/@stdlib/stats/base/ztest/alternative-resolve-str/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ztest/alternative-resolve-str/benchmark/benchmark.js @@ -23,13 +23,14 @@ var bench = require( '@stdlib/bench' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var str2enum = require( '@stdlib/stats/base/ztest/alternative-str2enum' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var resolve = require( './../lib' ); // MAIN // -bench( pkg+'::string', function benchmark( b ) { +bench( format( '%s::string', pkg ), function benchmark( b ) { var values; var out; var i; @@ -54,7 +55,7 @@ bench( pkg+'::string', function benchmark( b ) { b.end(); }); -bench( pkg+'::integer', function benchmark( b ) { +bench( format( '%s::integer', pkg ), function benchmark( b ) { var values; var out; var i; diff --git a/lib/node_modules/@stdlib/stats/base/ztest/one-sample/results/factory/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ztest/one-sample/results/factory/benchmark/benchmark.js index 70e54338bd20..54e2d1466769 100644 --- a/lib/node_modules/@stdlib/stats/base/ztest/one-sample/results/factory/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ztest/one-sample/results/factory/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isFunction = require( '@stdlib/assert/is-function' ); var isObject = require( '@stdlib/assert/is-object' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var factory = require( './../lib' ); @@ -54,7 +55,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::constructor,new', function benchmark( b ) { +bench( format( '%s::constructor,new', pkg ), function benchmark( b ) { var values; var v; var i; @@ -79,7 +80,7 @@ bench( pkg+'::constructor,new', function benchmark( b ) { b.end(); }); -bench( pkg+'::constructor,no_new', function benchmark( b ) { +bench( format( '%s::constructor,no_new', pkg ), function benchmark( b ) { var values; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/base/ztest/one-sample/results/float32/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ztest/one-sample/results/float32/benchmark/benchmark.js index c9e290699a2c..fe8b8c18aba0 100644 --- a/lib/node_modules/@stdlib/stats/base/ztest/one-sample/results/float32/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ztest/one-sample/results/float32/benchmark/benchmark.js @@ -22,13 +22,14 @@ var bench = require( '@stdlib/bench' ); var isObject = require( '@stdlib/assert/is-object' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float32Results = require( './../lib' ); // MAIN // -bench( pkg+'::constructor,new', function benchmark( b ) { +bench( format( '%s::constructor,new', pkg ), function benchmark( b ) { var v; var i; @@ -47,7 +48,7 @@ bench( pkg+'::constructor,new', function benchmark( b ) { b.end(); }); -bench( pkg+'::constructor,no_new', function benchmark( b ) { +bench( format( '%s::constructor,no_new', pkg ), function benchmark( b ) { var results; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/base/ztest/one-sample/results/float64/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ztest/one-sample/results/float64/benchmark/benchmark.js index 328377e909f0..3031940ce3b8 100644 --- a/lib/node_modules/@stdlib/stats/base/ztest/one-sample/results/float64/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ztest/one-sample/results/float64/benchmark/benchmark.js @@ -22,13 +22,14 @@ var bench = require( '@stdlib/bench' ); var isObject = require( '@stdlib/assert/is-object' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float64Results = require( './../lib' ); // MAIN // -bench( pkg+'::constructor,new', function benchmark( b ) { +bench( format( '%s::constructor,new', pkg ), function benchmark( b ) { var v; var i; @@ -47,7 +48,7 @@ bench( pkg+'::constructor,new', function benchmark( b ) { b.end(); }); -bench( pkg+'::constructor,no_new', function benchmark( b ) { +bench( format( '%s::constructor,no_new', pkg ), function benchmark( b ) { var results; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/base/ztest/two-sample/results/factory/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ztest/two-sample/results/factory/benchmark/benchmark.js index 70e54338bd20..54e2d1466769 100644 --- a/lib/node_modules/@stdlib/stats/base/ztest/two-sample/results/factory/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ztest/two-sample/results/factory/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var isFunction = require( '@stdlib/assert/is-function' ); var isObject = require( '@stdlib/assert/is-object' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var factory = require( './../lib' ); @@ -54,7 +55,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::constructor,new', function benchmark( b ) { +bench( format( '%s::constructor,new', pkg ), function benchmark( b ) { var values; var v; var i; @@ -79,7 +80,7 @@ bench( pkg+'::constructor,new', function benchmark( b ) { b.end(); }); -bench( pkg+'::constructor,no_new', function benchmark( b ) { +bench( format( '%s::constructor,no_new', pkg ), function benchmark( b ) { var values; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/base/ztest/two-sample/results/float32/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ztest/two-sample/results/float32/benchmark/benchmark.js index c9e290699a2c..fe8b8c18aba0 100644 --- a/lib/node_modules/@stdlib/stats/base/ztest/two-sample/results/float32/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ztest/two-sample/results/float32/benchmark/benchmark.js @@ -22,13 +22,14 @@ var bench = require( '@stdlib/bench' ); var isObject = require( '@stdlib/assert/is-object' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float32Results = require( './../lib' ); // MAIN // -bench( pkg+'::constructor,new', function benchmark( b ) { +bench( format( '%s::constructor,new', pkg ), function benchmark( b ) { var v; var i; @@ -47,7 +48,7 @@ bench( pkg+'::constructor,new', function benchmark( b ) { b.end(); }); -bench( pkg+'::constructor,no_new', function benchmark( b ) { +bench( format( '%s::constructor,no_new', pkg ), function benchmark( b ) { var results; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/base/ztest/two-sample/results/float64/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ztest/two-sample/results/float64/benchmark/benchmark.js index 328377e909f0..3031940ce3b8 100644 --- a/lib/node_modules/@stdlib/stats/base/ztest/two-sample/results/float64/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ztest/two-sample/results/float64/benchmark/benchmark.js @@ -22,13 +22,14 @@ var bench = require( '@stdlib/bench' ); var isObject = require( '@stdlib/assert/is-object' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var Float64Results = require( './../lib' ); // MAIN // -bench( pkg+'::constructor,new', function benchmark( b ) { +bench( format( '%s::constructor,new', pkg ), function benchmark( b ) { var v; var i; @@ -47,7 +48,7 @@ bench( pkg+'::constructor,new', function benchmark( b ) { b.end(); }); -bench( pkg+'::constructor,no_new', function benchmark( b ) { +bench( format( '%s::constructor,no_new', pkg ), function benchmark( b ) { var results; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/binomial-test/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/binomial-test/benchmark/benchmark.js index d00ca1a7f3fe..dc51f3f3fe59 100644 --- a/lib/node_modules/@stdlib/stats/binomial-test/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/binomial-test/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isObject = require( '@stdlib/assert/is-object' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var binomialTest = require( './../lib' ); @@ -53,7 +54,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::array', function benchmark( b ) { +bench( format( '%s::array', pkg ), function benchmark( b ) { var result; var arr; var i; @@ -76,7 +77,7 @@ bench( pkg+'::array', function benchmark( b ) { b.end(); }); -bench( pkg+'::one-sided', function benchmark( b ) { +bench( format( '%s::one-sided', pkg ), function benchmark( b ) { var result; var opts; var x; @@ -104,7 +105,7 @@ bench( pkg+'::one-sided', function benchmark( b ) { b.end(); }); -bench( pkg+'::p=0.8', function benchmark( b ) { +bench( format( '%s::p=0.8', pkg ), function benchmark( b ) { var result; var opts; var x; @@ -132,7 +133,7 @@ bench( pkg+'::p=0.8', function benchmark( b ) { b.end(); }); -bench( pkg+':print', function benchmark( b ) { +bench( format( '%s:print', pkg ), function benchmark( b ) { var digits; var result; var output; diff --git a/lib/node_modules/@stdlib/stats/chi2gof/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/chi2gof/benchmark/benchmark.js index 99ec059c9a07..eea8413979a1 100644 --- a/lib/node_modules/@stdlib/stats/chi2gof/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/chi2gof/benchmark/benchmark.js @@ -26,13 +26,14 @@ var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); var pmf = require( '@stdlib/stats/base/dists/discrete-uniform/pmf' ); var max = require( '@stdlib/math/base/special/max' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var chi2gof = require( './../lib' ); // MAIN // -bench( pkg+'::distribution_name', function benchmark( b ) { +bench( format( '%s::distribution_name', pkg ), function benchmark( b ) { var result; var freqs; var len; @@ -71,7 +72,7 @@ bench( pkg+'::distribution_name', function benchmark( b ) { b.end(); }); -bench( pkg+'::distribution_name:simulate=true', function benchmark( b ) { +bench( format( '%s::distribution_name:simulate=true', pkg ), function benchmark( b ) { var result; var freqs; var opts; @@ -114,7 +115,7 @@ bench( pkg+'::distribution_name:simulate=true', function benchmark( b ) { b.end(); }); -bench( pkg+'::distribution_name:simulate=true:iterations=250', function benchmark( b ) { +bench( format( '%s::distribution_name:simulate=true:iterations=250', pkg ), function benchmark( b ) { var result; var freqs; var opts; @@ -158,7 +159,7 @@ bench( pkg+'::distribution_name:simulate=true:iterations=250', function benchmar b.end(); }); -bench( pkg+'::distribution_name:simulate=true:iterations=100', function benchmark( b ) { +bench( format( '%s::distribution_name:simulate=true:iterations=100', pkg ), function benchmark( b ) { var result; var freqs; var opts; @@ -202,7 +203,7 @@ bench( pkg+'::distribution_name:simulate=true:iterations=100', function benchmar b.end(); }); -bench( pkg+'::probabilities', function benchmark( b ) { +bench( format( '%s::probabilities', pkg ), function benchmark( b ) { var result; var freqs; var probs; @@ -243,7 +244,7 @@ bench( pkg+'::probabilities', function benchmark( b ) { b.end(); }); -bench( pkg+'::expected_counts', function benchmark( b ) { +bench( format( '%s::expected_counts', pkg ), function benchmark( b ) { var expected; var result; var freqs; @@ -284,7 +285,7 @@ bench( pkg+'::expected_counts', function benchmark( b ) { b.end(); }); -bench( pkg+':toString', function benchmark( b ) { +bench( format( '%s:toString', pkg ), function benchmark( b ) { var digits; var result; var output; diff --git a/lib/node_modules/@stdlib/stats/chi2test/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/chi2test/benchmark/benchmark.js index 9d59c9b955bf..cf976b545c59 100644 --- a/lib/node_modules/@stdlib/stats/chi2test/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/chi2test/benchmark/benchmark.js @@ -26,6 +26,7 @@ var isObject = require( '@stdlib/assert/is-object' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); var max = require( '@stdlib/math/base/special/max' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var chi2test = require( './../lib' ); @@ -64,7 +65,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+':toString', function benchmark( b ) { +bench( format( '%s:toString', pkg ), function benchmark( b ) { var digits; var result; var output; diff --git a/lib/node_modules/@stdlib/stats/cumax/README.md b/lib/node_modules/@stdlib/stats/cumax/README.md index 8b0383bbd710..0ead4e5cce49 100644 --- a/lib/node_modules/@stdlib/stats/cumax/README.md +++ b/lib/node_modules/@stdlib/stats/cumax/README.md @@ -35,16 +35,12 @@ var cumax = require( '@stdlib/stats/cumax' ); Computes the cumulative maximum value along one or more [ndarray][@stdlib/ndarray/ctor] dimensions. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ -1.0, 2.0, -3.0 ] ); var y = cumax( x ); -// returns - -var arr = ndarray2array( y ); -// returns [ -1.0, 2.0, 2.0 ] +// returns [ -1.0, 2.0, 2.0 ] ``` The function has the following parameters: @@ -60,7 +56,6 @@ The function accepts the following options: By default, the function performs the operation over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. To perform the operation over specific dimensions, provide a `dims` option. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ -1.0, 2.0, -3.0, 4.0 ], { @@ -68,32 +63,20 @@ var x = array( [ -1.0, 2.0, -3.0, 4.0 ], { 'order': 'row-major' }); -var v = ndarray2array( x ); -// returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ] - var y = cumax( x, { 'dims': [ 0 ] }); -// returns - -v = ndarray2array( y ); -// returns [ [ -1.0, 2.0 ], [ -1.0, 4.0 ] ] +// returns [ [ -1.0, 2.0 ], [ -1.0, 4.0 ] ] y = cumax( x, { 'dims': [ 1 ] }); -// returns - -v = ndarray2array( y ); -// returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ] +// returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ] y = cumax( x, { 'dims': [ 0, 1 ] }); -// returns - -v = ndarray2array( y ); -// returns [ [ -1.0, 2.0 ], [ 2.0, 4.0 ] ] +// returns [ [ -1.0, 2.0 ], [ 2.0, 4.0 ] ] ``` By default, the function returns an [ndarray][@stdlib/ndarray/ctor] having a [data type][@stdlib/ndarray/dtypes] determined by the function's output data type [policy][@stdlib/ndarray/output-dtype-policies]. To override the default behavior, set the `dtype` option. @@ -120,7 +103,6 @@ var dt = String( getDType( y ) ); Computes the cumulative maximum value along one or more [ndarray][@stdlib/ndarray/ctor] dimensions and assigns results to a provided output [ndarray][@stdlib/ndarray/ctor]. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var zerosLike = require( '@stdlib/ndarray/zeros-like' ); @@ -128,10 +110,7 @@ var x = array( [ -1.0, 2.0, -3.0 ] ); var y = zerosLike( x ); var out = cumax.assign( x, y ); -// returns - -var v = ndarray2array( out ); -// returns [ -1.0, 2.0, 2.0 ] +// returns [ -1.0, 2.0, 2.0 ] var bool = ( out === y ); // returns true diff --git a/lib/node_modules/@stdlib/stats/cumax/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/cumax/benchmark/benchmark.assign.js index 8171c1e9ae37..24bb43686903 100644 --- a/lib/node_modules/@stdlib/stats/cumax/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/cumax/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var zerosLike = require( '@stdlib/ndarray/zeros-like' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cumax = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/cumax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/cumax/benchmark/benchmark.js index a9eaa0d9154e..37aba9430464 100644 --- a/lib/node_modules/@stdlib/stats/cumax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/cumax/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cumax = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/cumax/docs/repl.txt b/lib/node_modules/@stdlib/stats/cumax/docs/repl.txt index b901e291ceb3..45349f1f9ed0 100644 --- a/lib/node_modules/@stdlib/stats/cumax/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/cumax/docs/repl.txt @@ -26,9 +26,8 @@ Examples -------- > var x = {{alias:@stdlib/ndarray/array}}( [ -1.0, 2.0, -3.0, -4.0 ] ); - > var y = {{alias}}( x ); - > {{alias:@stdlib/ndarray/to-array}}( y ) - [ -1.0, 2.0, 2.0, 2.0 ] + > var y = {{alias}}( x ) + [ -1.0, 2.0, 2.0, 2.0 ] {{alias}}.assign( x, out[, options] ) @@ -61,11 +60,9 @@ > var x = {{alias:@stdlib/ndarray/array}}( [ -1.0, 2.0, -3.0, -4.0 ] ); > var out = {{alias:@stdlib/ndarray/zeros-like}}( x ); > var y = {{alias}}.assign( x, out ) - + [ -1.0, 2.0, 2.0, 2.0 ] > var bool = ( out === y ) true - > {{alias:@stdlib/ndarray/to-array}}( y ) - [ -1.0, 2.0, 2.0, 2.0 ] See Also -------- diff --git a/lib/node_modules/@stdlib/stats/cumax/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/cumax/docs/types/index.d.ts index b4596c54ce8a..30a306a32f9f 100644 --- a/lib/node_modules/@stdlib/stats/cumax/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/cumax/docs/types/index.d.ts @@ -65,16 +65,12 @@ interface Unary { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var array = require( '@stdlib/ndarray/array' ); * * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = cumax( x ); - * // returns - * - * var arr = ndarray2array( y ); - * // returns [ -1.0, 2.0, 2.0 ] + * // returns [ -1.0, 2.0, 2.0 ] */ ( x: InputArray, options?: Options ): OutputArray; // NOTE: we lose type specificity here, but retaining specificity would likely be difficult and/or tedious to completely enumerate, as the output ndarray data type is dependent on how `x` interacts with output data type policy and whether that policy has been overridden by `options.dtype`. @@ -87,7 +83,6 @@ interface Unary { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var zerosLike = require( '@stdlib/ndarray/zeros-like' ); * var array = require( '@stdlib/ndarray/array' ); * @@ -95,13 +90,10 @@ interface Unary { * var y = zerosLike( x ); * * var out = cumax.assign( x, y ); - * // returns + * // returns [ -1.0, 2.0, 2.0 ] * * var bool = ( out === y ); * // returns true - * - * var arr = ndarray2array( out ); - * // returns [ -1.0, 2.0, 2.0 ] */ assign = OutputArray>( x: InputArray, out: U, options?: BaseOptions ): U; } @@ -114,19 +106,14 @@ interface Unary { * @returns output ndarray * * @example -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var array = require( '@stdlib/ndarray/array' ); * * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = cumax( x ); -* // returns -* -* var arr = ndarray2array( y ); -* // returns [ -1.0, 2.0, 2.0 ] +* // returns [ -1.0, 2.0, 2.0 ] * * @example -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var zerosLike = require( '@stdlib/ndarray/zeros-like' ); * var array = require( '@stdlib/ndarray/array' ); * @@ -134,13 +121,10 @@ interface Unary { * var y = zerosLike( x ); * * var out = cumax.assign( x, y ); -* // returns +* // returns [ -1.0, 2.0, 2.0 ] * * var bool = ( out === y ); * // returns true -* -* var arr = ndarray2array( out ); -* // returns [ -1.0, 2.0, 2.0 ] */ declare const cumax: Unary; diff --git a/lib/node_modules/@stdlib/stats/cumax/lib/index.js b/lib/node_modules/@stdlib/stats/cumax/lib/index.js index bb4ddeb5fce3..ee217b4111a0 100644 --- a/lib/node_modules/@stdlib/stats/cumax/lib/index.js +++ b/lib/node_modules/@stdlib/stats/cumax/lib/index.js @@ -26,7 +26,6 @@ * @example * var Float64Array = require( '@stdlib/array/float64' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var cumax = require( '@stdlib/stats/cumax' ); * * // Create a data buffer: @@ -46,10 +45,7 @@ * * // Perform operation: * var out = cumax( x ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ [ [ 1.0, 2.0 ] ], [ [ 2.0, 4.0 ] ], [ [ 4.0, 6.0 ] ] ] +* // returns [ [ [ 1.0, 2.0 ] ], [ [ 2.0, 4.0 ] ], [ [ 4.0, 6.0 ] ] ] */ // MODULES // diff --git a/lib/node_modules/@stdlib/stats/cumax/lib/main.js b/lib/node_modules/@stdlib/stats/cumax/lib/main.js index fee79e0850f1..2b06cca01167 100644 --- a/lib/node_modules/@stdlib/stats/cumax/lib/main.js +++ b/lib/node_modules/@stdlib/stats/cumax/lib/main.js @@ -70,7 +70,6 @@ var table = { * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * * // Create a data buffer: @@ -90,10 +89,7 @@ var table = { * * // Perform operation: * var out = cumax( x ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ [ [ 1.0, 2.0 ] ], [ [ 2.0, 4.0 ] ], [ [ 4.0, 6.0 ] ] ] +* // returns [ [ [ 1.0, 2.0 ] ], [ [ 2.0, 4.0 ] ], [ [ 4.0, 6.0 ] ] ] */ var cumax = factory( table, [ idtypes ], odtypes, policies ); diff --git a/lib/node_modules/@stdlib/stats/cumin/README.md b/lib/node_modules/@stdlib/stats/cumin/README.md index a74c21673d32..dec13de3523c 100644 --- a/lib/node_modules/@stdlib/stats/cumin/README.md +++ b/lib/node_modules/@stdlib/stats/cumin/README.md @@ -35,16 +35,12 @@ var cumin = require( '@stdlib/stats/cumin' ); Computes the cumulative minimum value along one or more [ndarray][@stdlib/ndarray/ctor] dimensions. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ -1.0, 2.0, -3.0 ] ); var y = cumin( x ); -// returns - -var arr = ndarray2array( y ); -// returns [ -1.0, -1.0, -3.0 ] +// returns [ -1.0, -1.0, -3.0 ] ``` The function has the following parameters: @@ -60,7 +56,6 @@ The function accepts the following options: By default, the function performs the operation over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. To perform the operation over specific dimensions, provide a `dims` option. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var x = array( [ -1.0, 2.0, -3.0, 4.0 ], { @@ -68,32 +63,20 @@ var x = array( [ -1.0, 2.0, -3.0, 4.0 ], { 'order': 'row-major' }); -var v = ndarray2array( x ); -// returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ] - var y = cumin( x, { 'dims': [ 0 ] }); -// returns - -v = ndarray2array( y ); -// returns [ [ -1.0, 2.0 ], [ -3.0, 2.0 ] ] +// returns [ [ -1.0, 2.0 ], [ -3.0, 2.0 ] ] y = cumin( x, { 'dims': [ 1 ] }); -// returns - -v = ndarray2array( y ); -// returns [ [ -1.0, -1.0 ], [ -3.0, -3.0 ] ] +// returns [ [ -1.0, -1.0 ], [ -3.0, -3.0 ] ] y = cumin( x, { 'dims': [ 0, 1 ] }); -// returns - -v = ndarray2array( y ); -// returns [ [ -1.0, -1.0 ], [ -3.0, -3.0 ] ] +// returns [ [ -1.0, -1.0 ], [ -3.0, -3.0 ] ] ``` By default, the function returns an [ndarray][@stdlib/ndarray/ctor] having a [data type][@stdlib/ndarray/dtypes] determined by the function's output data type [policy][@stdlib/ndarray/output-dtype-policies]. To override the default behavior, set the `dtype` option. @@ -120,7 +103,6 @@ var dt = String( getDType( y ) ); Computes the cumulative minimum value along one or more [ndarray][@stdlib/ndarray/ctor] dimensions and assigns results to a provided output [ndarray][@stdlib/ndarray/ctor]. ```javascript -var ndarray2array = require( '@stdlib/ndarray/to-array' ); var array = require( '@stdlib/ndarray/array' ); var zerosLike = require( '@stdlib/ndarray/zeros-like' ); @@ -128,10 +110,7 @@ var x = array( [ -1.0, 2.0, -3.0 ] ); var y = zerosLike( x ); var out = cumin.assign( x, y ); -// returns - -var v = ndarray2array( out ); -// returns [ -1.0, -1.0, -3.0 ] +// returns [ -1.0, -1.0, -3.0 ] var bool = ( out === y ); // returns true diff --git a/lib/node_modules/@stdlib/stats/cumin/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/cumin/benchmark/benchmark.assign.js index 99ab0f0fee2a..b1d79ce2e1c9 100644 --- a/lib/node_modules/@stdlib/stats/cumin/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/cumin/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var zerosLike = require( '@stdlib/ndarray/zeros-like' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cumin = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/cumin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/cumin/benchmark/benchmark.js index e78e06488c9d..d13c6a5951cf 100644 --- a/lib/node_modules/@stdlib/stats/cumin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/cumin/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var cumin = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/cumin/docs/repl.txt b/lib/node_modules/@stdlib/stats/cumin/docs/repl.txt index 994a0b2f54fd..5b674cceddff 100644 --- a/lib/node_modules/@stdlib/stats/cumin/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/cumin/docs/repl.txt @@ -26,9 +26,8 @@ Examples -------- > var x = {{alias:@stdlib/ndarray/array}}( [ -1.0, 2.0, -3.0, -4.0 ] ); - > var y = {{alias}}( x ); - > {{alias:@stdlib/ndarray/to-array}}( y ) - [ -1.0, -1.0, -3.0, -4.0 ] + > var y = {{alias}}( x ) + [ -1.0, -1.0, -3.0, -4.0 ] {{alias}}.assign( x, out[, options] ) @@ -61,11 +60,9 @@ > var x = {{alias:@stdlib/ndarray/array}}( [ -1.0, 2.0, -3.0, -4.0 ] ); > var out = {{alias:@stdlib/ndarray/zeros-like}}( x ); > var y = {{alias}}.assign( x, out ) - + [ -1.0, -1.0, -3.0, -4.0 ] > var bool = ( out === y ) true - > {{alias:@stdlib/ndarray/to-array}}( y ) - [ -1.0, -1.0, -3.0, -4.0 ] See Also -------- diff --git a/lib/node_modules/@stdlib/stats/cumin/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/cumin/docs/types/index.d.ts index cb0559a57fb6..0b2d5f7d043e 100644 --- a/lib/node_modules/@stdlib/stats/cumin/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/cumin/docs/types/index.d.ts @@ -65,16 +65,12 @@ interface Unary { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var array = require( '@stdlib/ndarray/array' ); * * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = cumin( x ); - * // returns - * - * var arr = ndarray2array( y ); - * // returns [ -1.0, -1.0, -3.0 ] + * // returns [ -1.0, -1.0, -3.0 ] */ ( x: InputArray, options?: Options ): OutputArray; // NOTE: we lose type specificity here, but retaining specificity would likely be difficult and/or tedious to completely enumerate, as the output ndarray data type is dependent on how `x` interacts with output data type policy and whether that policy has been overridden by `options.dtype`. @@ -87,7 +83,6 @@ interface Unary { * @returns output ndarray * * @example - * var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var zerosLike = require( '@stdlib/ndarray/zeros-like' ); * var array = require( '@stdlib/ndarray/array' ); * @@ -95,13 +90,10 @@ interface Unary { * var y = zerosLike( x ); * * var out = cumin.assign( x, y ); - * // returns + * // returns [ -1.0, -1.0, -3.0 ] * * var bool = ( out === y ); * // returns true - * - * var arr = ndarray2array( out ); - * // returns [ -1.0, -1.0, -3.0 ] */ assign = OutputArray>( x: InputArray, out: U, options?: BaseOptions ): U; } @@ -114,19 +106,14 @@ interface Unary { * @returns output ndarray * * @example -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var array = require( '@stdlib/ndarray/array' ); * * var x = array( [ -1.0, 2.0, -3.0 ] ); * * var y = cumin( x ); -* // returns -* -* var arr = ndarray2array( y ); -* // returns [ -1.0, -1.0, -3.0 ] +* // returns [ -1.0, -1.0, -3.0 ] * * @example -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var zerosLike = require( '@stdlib/ndarray/zeros-like' ); * var array = require( '@stdlib/ndarray/array' ); * @@ -134,13 +121,10 @@ interface Unary { * var y = zerosLike( x ); * * var out = cumin.assign( x, y ); -* // returns +* // returns [ -1.0, -1.0, -3.0 ] * * var bool = ( out === y ); * // returns true -* -* var arr = ndarray2array( out ); -* // returns [ -1.0, -1.0, -3.0 ] */ declare const cumin: Unary; diff --git a/lib/node_modules/@stdlib/stats/cumin/lib/index.js b/lib/node_modules/@stdlib/stats/cumin/lib/index.js index 5d325f20fae1..cc746e1a4d48 100644 --- a/lib/node_modules/@stdlib/stats/cumin/lib/index.js +++ b/lib/node_modules/@stdlib/stats/cumin/lib/index.js @@ -26,7 +26,6 @@ * @example * var Float64Array = require( '@stdlib/array/float64' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var cumin = require( '@stdlib/stats/cumin' ); * * // Create a data buffer: @@ -46,10 +45,7 @@ * * // Perform operation: * var out = cumin( x ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ [ [ 1.0, 1.0 ] ], [ [ -3.0, -3.0 ] ], [ [ -5.0, -5.0 ] ] ] +* // returns [ [ [ 1.0, 1.0 ] ], [ [ -3.0, -3.0 ] ], [ [ -5.0, -5.0 ] ] ] */ // MODULES // diff --git a/lib/node_modules/@stdlib/stats/cumin/lib/main.js b/lib/node_modules/@stdlib/stats/cumin/lib/main.js index d27d261abcd5..91dbe8815350 100644 --- a/lib/node_modules/@stdlib/stats/cumin/lib/main.js +++ b/lib/node_modules/@stdlib/stats/cumin/lib/main.js @@ -70,7 +70,6 @@ var table = { * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var ndarray2array = require( '@stdlib/ndarray/to-array' ); * var ndarray = require( '@stdlib/ndarray/ctor' ); * * // Create a data buffer: @@ -90,10 +89,7 @@ var table = { * * // Perform operation: * var out = cumin( x ); -* // returns -* -* var arr = ndarray2array( out ); -* // returns [ [ [ 1.0, 1.0 ] ], [ [ -3.0, -3.0 ] ], [ [ -5.0, -5.0 ] ] ] +* // returns [ [ [ 1.0, 1.0 ] ], [ [ -3.0, -3.0 ] ], [ [ -5.0, -5.0 ] ] ] */ var cumin = factory( table, [ idtypes ], odtypes, policies ); diff --git a/lib/node_modules/@stdlib/stats/fligner-test/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/fligner-test/benchmark/benchmark.js index 38ead94bb4e1..ffaac527226c 100644 --- a/lib/node_modules/@stdlib/stats/fligner-test/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/fligner-test/benchmark/benchmark.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); var isObject = require( '@stdlib/assert/is-object' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var flignerTest = require( './../lib' ); @@ -65,7 +66,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::groups', function benchmark( b ) { +bench( format( '%s::groups', pkg ), function benchmark( b ) { var result; var group; var vals; @@ -98,7 +99,7 @@ bench( pkg+'::groups', function benchmark( b ) { b.end(); }); -bench( pkg+':print', function benchmark( b ) { +bench( format( '%s:print', pkg ), function benchmark( b ) { var digits; var result; var output; diff --git a/lib/node_modules/@stdlib/stats/incr/apcorr/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/apcorr/benchmark/benchmark.js index 837e48e74966..50f5833f9a9f 100644 --- a/lib/node_modules/@stdlib/stats/incr/apcorr/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/apcorr/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrapcorr = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_means', function benchmark( b ) { +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/count/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/count/benchmark/benchmark.js index c06a7a05d33f..b6528e51f089 100644 --- a/lib/node_modules/@stdlib/stats/incr/count/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/count/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrcount = require( './../lib' ); @@ -45,7 +46,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/covariance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/covariance/benchmark/benchmark.js index fddd0480a295..1ff54305b2f6 100644 --- a/lib/node_modules/@stdlib/stats/incr/covariance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/covariance/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrcovariance = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_means', function benchmark( b ) { +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/covmat/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/covmat/benchmark/benchmark.js index bb1f3473d4bc..9f75d187bc5b 100644 --- a/lib/node_modules/@stdlib/stats/incr/covmat/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/covmat/benchmark/benchmark.js @@ -25,13 +25,14 @@ var randu = require( '@stdlib/random/base/randu' ); var ndarray = require( '@stdlib/ndarray/ctor' ); var Float64Array = require( '@stdlib/array/float64' ); var isSymmetricMatrix = require( '@stdlib/assert/is-symmetric-matrix' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrcovmat = require( './../lib' ); // MAIN // -bench( pkg+'::order', function benchmark( b ) { +bench( format( '%s::order', pkg ), function benchmark( b ) { var f; var i; @@ -50,7 +51,7 @@ bench( pkg+'::order', function benchmark( b ) { b.end(); }); -bench( pkg+'::order,means', function benchmark( b ) { +bench( format( '%s::order,means', pkg ), function benchmark( b ) { var strides; var buffer; var means; @@ -78,7 +79,7 @@ bench( pkg+'::order,means', function benchmark( b ) { b.end(); }); -bench( pkg+'::covariance_matrix', function benchmark( b ) { +bench( format( '%s::covariance_matrix', pkg ), function benchmark( b ) { var strides; var buffer; var shape; @@ -106,7 +107,7 @@ bench( pkg+'::covariance_matrix', function benchmark( b ) { b.end(); }); -bench( pkg+'::covariance_matrix,means', function benchmark( b ) { +bench( format( '%s::covariance_matrix,means', pkg ), function benchmark( b ) { var strides; var buffer; var shape; @@ -140,7 +141,7 @@ bench( pkg+'::covariance_matrix,means', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var strides; var buffer; var shape; @@ -179,7 +180,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_means', function benchmark( b ) { +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { var strides; var buffer; var means; diff --git a/lib/node_modules/@stdlib/stats/incr/cv/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/cv/benchmark/benchmark.js index c6994b8c30a2..bd1838460471 100644 --- a/lib/node_modules/@stdlib/stats/incr/cv/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/cv/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrcv = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_mean', function benchmark( b ) { +bench( format( '%s::accumulator,known_mean', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/ewmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/ewmean/benchmark/benchmark.js index f6f8972dbe06..2a4c1d4ea913 100644 --- a/lib/node_modules/@stdlib/stats/incr/ewmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/ewmean/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var increwmean = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/ewstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/ewstdev/benchmark/benchmark.js index 7591a09cd64a..24c8d3b2a97f 100644 --- a/lib/node_modules/@stdlib/stats/incr/ewstdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/ewstdev/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var increwstdev = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/ewvariance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/ewvariance/benchmark/benchmark.js index 553ccc26557e..80d4f1db94c3 100644 --- a/lib/node_modules/@stdlib/stats/incr/ewvariance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/ewvariance/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var increwvariance = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/gmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/gmean/benchmark/benchmark.js index ed4757dfe088..0c853382af20 100644 --- a/lib/node_modules/@stdlib/stats/incr/gmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/gmean/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrgmean = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/grubbs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/grubbs/benchmark/benchmark.js index 4eda0bc37c87..bc4d933f2554 100644 --- a/lib/node_modules/@stdlib/stats/incr/grubbs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/grubbs/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var rnorm = require( '@stdlib/random/base/normal' ); var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrgrubbs = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::options', function benchmark( b ) { +bench( format( '%s::options', pkg ), function benchmark( b ) { var opts; var f; var i; @@ -75,7 +76,7 @@ bench( pkg+'::options', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var t; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/hmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/hmean/benchmark/benchmark.js index 50a595f7695c..3d08ea2e3f1a 100644 --- a/lib/node_modules/@stdlib/stats/incr/hmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/hmean/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrhmean = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/kurtosis/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/kurtosis/benchmark/benchmark.js index edff7426750c..50122235fceb 100644 --- a/lib/node_modules/@stdlib/stats/incr/kurtosis/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/kurtosis/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrkurtosis = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/maape/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/maape/benchmark/benchmark.js index 6e3484d30553..03d77facf47f 100644 --- a/lib/node_modules/@stdlib/stats/incr/maape/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/maape/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmaape = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mae/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mae/benchmark/benchmark.js index b91e236a2dc7..3d67aa84e4ac 100644 --- a/lib/node_modules/@stdlib/stats/incr/mae/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mae/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmae = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mapcorr/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mapcorr/benchmark/benchmark.js index aaa0ddfc1697..27f575015d2d 100644 --- a/lib/node_modules/@stdlib/stats/incr/mapcorr/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mapcorr/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmapcorr = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_means', function benchmark( b ) { +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mape/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mape/benchmark/benchmark.js index 534bff6ebfa7..6dd204ae1e2f 100644 --- a/lib/node_modules/@stdlib/stats/incr/mape/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mape/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmape = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/max/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/max/benchmark/benchmark.js index facdd89c1e06..08f38b606fe9 100644 --- a/lib/node_modules/@stdlib/stats/incr/max/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/max/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmax = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/maxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/maxabs/benchmark/benchmark.js index d56c413a9709..18dea0f0c65f 100644 --- a/lib/node_modules/@stdlib/stats/incr/maxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/maxabs/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmaxabs = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mcovariance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mcovariance/benchmark/benchmark.js index 0cd8f2d43369..5b63fca435bf 100644 --- a/lib/node_modules/@stdlib/stats/incr/mcovariance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mcovariance/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmcovariance = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_means', function benchmark( b ) { +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mcv/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mcv/benchmark/benchmark.js index 082b2937a4db..678311ba4df2 100644 --- a/lib/node_modules/@stdlib/stats/incr/mcv/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mcv/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmcv = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_mean', function benchmark( b ) { +bench( format( '%s::accumulator,known_mean', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mda/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mda/benchmark/benchmark.js index 17dd2afdf7a9..67dc552ca0f2 100644 --- a/lib/node_modules/@stdlib/stats/incr/mda/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mda/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmda = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/me/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/me/benchmark/benchmark.js index 48aed8de2ab4..2b832710b8d1 100644 --- a/lib/node_modules/@stdlib/stats/incr/me/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/me/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrme = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mean/benchmark/benchmark.js index 40bb70e70c05..65b7782655d3 100644 --- a/lib/node_modules/@stdlib/stats/incr/mean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mean/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmean = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/meanabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/meanabs/benchmark/benchmark.js index 54c6b8d3b73d..59676b491bd2 100644 --- a/lib/node_modules/@stdlib/stats/incr/meanabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/meanabs/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmeanabs = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/meanabs2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/meanabs2/benchmark/benchmark.js index 03a997038897..628bc98c67fd 100644 --- a/lib/node_modules/@stdlib/stats/incr/meanabs2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/meanabs2/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmeanabs2 = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/meanstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/meanstdev/benchmark/benchmark.js index afbf9670d02f..0466df168a21 100644 --- a/lib/node_modules/@stdlib/stats/incr/meanstdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/meanstdev/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmeanstdev = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/meanvar/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/meanvar/benchmark/benchmark.js index 43fd22a26c31..a3c570e8eca4 100644 --- a/lib/node_modules/@stdlib/stats/incr/meanvar/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/meanvar/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmeanvar = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mgmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mgmean/benchmark/benchmark.js index 4f6ff67b1f53..294533351d52 100644 --- a/lib/node_modules/@stdlib/stats/incr/mgmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mgmean/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmgmean = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mgrubbs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mgrubbs/benchmark/benchmark.js index b6045b0f847c..439f2fa86e2d 100644 --- a/lib/node_modules/@stdlib/stats/incr/mgrubbs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mgrubbs/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var rnorm = require( '@stdlib/random/base/normal' ); var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmgrubbs = require( './../lib' ); @@ -48,7 +49,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::options', function benchmark( b ) { +bench( format( '%s::options', pkg ), function benchmark( b ) { var opts; var f; var i; @@ -73,7 +74,7 @@ bench( pkg+'::options', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var t; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mhmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mhmean/benchmark/benchmark.js index b5439bf56df9..976bc0454572 100644 --- a/lib/node_modules/@stdlib/stats/incr/mhmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mhmean/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmhmean = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/midrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/midrange/benchmark/benchmark.js index 634b38919443..d62f3c0549f4 100644 --- a/lib/node_modules/@stdlib/stats/incr/midrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/midrange/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmidrange = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/min/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/min/benchmark/benchmark.js index e838de7fe21d..e971a320321c 100644 --- a/lib/node_modules/@stdlib/stats/incr/min/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/min/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmin = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/minabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/minabs/benchmark/benchmark.js index 3ad33e0cbfa0..4aa1902dbeed 100644 --- a/lib/node_modules/@stdlib/stats/incr/minabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/minabs/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrminabs = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/minmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/minmax/benchmark/benchmark.js index a78fb7d422cb..ea1c941202e4 100644 --- a/lib/node_modules/@stdlib/stats/incr/minmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/minmax/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrminmax = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/minmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/minmaxabs/benchmark/benchmark.js index dd9b53a2059f..5d1740bae11b 100644 --- a/lib/node_modules/@stdlib/stats/incr/minmaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/minmaxabs/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrminmaxabs = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mmaape/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mmaape/benchmark/benchmark.js index 77062ec0212d..f5ee13698bad 100644 --- a/lib/node_modules/@stdlib/stats/incr/mmaape/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mmaape/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmmaape = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mmae/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mmae/benchmark/benchmark.js index 88d921a42f2c..1e1ba61bd880 100644 --- a/lib/node_modules/@stdlib/stats/incr/mmae/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mmae/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmmae = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mmape/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mmape/benchmark/benchmark.js index 7aa51e69d4d2..374f02be2ff3 100644 --- a/lib/node_modules/@stdlib/stats/incr/mmape/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mmape/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmmape = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mmax/benchmark/benchmark.js index 8715118a3d4e..bb22cf65f206 100644 --- a/lib/node_modules/@stdlib/stats/incr/mmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mmax/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmmax = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mmaxabs/benchmark/benchmark.js index adf78228670a..bd0663bcf872 100644 --- a/lib/node_modules/@stdlib/stats/incr/mmaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mmaxabs/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmmaxabs = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mmda/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mmda/benchmark/benchmark.js index 0d6a54fb343e..62330e1b2843 100644 --- a/lib/node_modules/@stdlib/stats/incr/mmda/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mmda/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmmda = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mme/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mme/benchmark/benchmark.js index fa1b4f461014..42fb16d0c4b6 100644 --- a/lib/node_modules/@stdlib/stats/incr/mme/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mme/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmme = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mmean/benchmark/benchmark.js index e0cc90a21463..4ea5d9c01a69 100644 --- a/lib/node_modules/@stdlib/stats/incr/mmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mmean/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmmean = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mmeanabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mmeanabs/benchmark/benchmark.js index 2a9032155263..8a9b7510ebad 100644 --- a/lib/node_modules/@stdlib/stats/incr/mmeanabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mmeanabs/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmmeanabs = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mmeanabs2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mmeanabs2/benchmark/benchmark.js index d1444cf372ee..9ec389c548d9 100644 --- a/lib/node_modules/@stdlib/stats/incr/mmeanabs2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mmeanabs2/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmmeanabs2 = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mmeanstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mmeanstdev/benchmark/benchmark.js index 6fe3867d6ee1..f53b506b37d4 100644 --- a/lib/node_modules/@stdlib/stats/incr/mmeanstdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mmeanstdev/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmmeanstdev = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mmeanvar/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mmeanvar/benchmark/benchmark.js index 7f2f0372c8da..1da455a4fe51 100644 --- a/lib/node_modules/@stdlib/stats/incr/mmeanvar/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mmeanvar/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmmeanvar = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mmidrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mmidrange/benchmark/benchmark.js index b0531b0f876a..f238e3e5e20e 100644 --- a/lib/node_modules/@stdlib/stats/incr/mmidrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mmidrange/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmmidrange = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mmin/benchmark/benchmark.js index d45fe06494bd..21aa7005c529 100644 --- a/lib/node_modules/@stdlib/stats/incr/mmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mmin/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmmin = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mminabs/benchmark/benchmark.js index dbd9c171c597..99c045cd855f 100644 --- a/lib/node_modules/@stdlib/stats/incr/mminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mminabs/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmminabs = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mminmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mminmax/benchmark/benchmark.js index c36165592a9f..d26c9082d7ec 100644 --- a/lib/node_modules/@stdlib/stats/incr/mminmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mminmax/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmminmax = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mminmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mminmaxabs/benchmark/benchmark.js index bf9816a7af13..25c7de70ae6c 100644 --- a/lib/node_modules/@stdlib/stats/incr/mminmaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mminmaxabs/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmminmaxabs = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mmpe/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mmpe/benchmark/benchmark.js index f2ba80ca93c2..56f05e2f06be 100644 --- a/lib/node_modules/@stdlib/stats/incr/mmpe/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mmpe/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmmpe = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mmse/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mmse/benchmark/benchmark.js index 0dd2a0395638..f7ce0c74d74d 100644 --- a/lib/node_modules/@stdlib/stats/incr/mmse/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mmse/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmmse = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mpcorr/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mpcorr/benchmark/benchmark.js index 079f5ee9afd5..ce5a8ea72a40 100644 --- a/lib/node_modules/@stdlib/stats/incr/mpcorr/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mpcorr/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmpcorr = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_means', function benchmark( b ) { +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mpcorr2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mpcorr2/benchmark/benchmark.js index e7a45c38117a..6622352cbcf4 100644 --- a/lib/node_modules/@stdlib/stats/incr/mpcorr2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mpcorr2/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmpcorr2 = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_means', function benchmark( b ) { +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mpcorrdist/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mpcorrdist/benchmark/benchmark.js index 3cf84c0883fa..c1d69a9f9f0b 100644 --- a/lib/node_modules/@stdlib/stats/incr/mpcorrdist/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mpcorrdist/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmpcorrdist = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_means', function benchmark( b ) { +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mpe/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mpe/benchmark/benchmark.js index 44e26696ad58..39ab196483f9 100644 --- a/lib/node_modules/@stdlib/stats/incr/mpe/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mpe/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmpe = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mprod/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mprod/benchmark/benchmark.js index 760576006456..e070e48d742d 100644 --- a/lib/node_modules/@stdlib/stats/incr/mprod/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mprod/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmprod = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mrange/benchmark/benchmark.js index 1b8b18d23df1..2ef09bb2056b 100644 --- a/lib/node_modules/@stdlib/stats/incr/mrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mrange/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmrange = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mrmse/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mrmse/benchmark/benchmark.js index 53b7b7dc9715..e695e4e6d241 100644 --- a/lib/node_modules/@stdlib/stats/incr/mrmse/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mrmse/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmrmse = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mrss/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mrss/benchmark/benchmark.js index a14a5f3966cd..0e7ee95b91c6 100644 --- a/lib/node_modules/@stdlib/stats/incr/mrss/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mrss/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmrss = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mse/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mse/benchmark/benchmark.js index f1b65b05b8c7..39f9c462affd 100644 --- a/lib/node_modules/@stdlib/stats/incr/mse/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mse/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmse = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mstdev/benchmark/benchmark.js index d3fdad5c37ad..b8f41751d675 100644 --- a/lib/node_modules/@stdlib/stats/incr/mstdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mstdev/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmstdev = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_mean', function benchmark( b ) { +bench( format( '%s::accumulator,known_mean', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/msum/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/msum/benchmark/benchmark.js index f28879884f55..f66a9df586a2 100644 --- a/lib/node_modules/@stdlib/stats/incr/msum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/msum/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmsum = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/msumabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/msumabs/benchmark/benchmark.js index 5bca5f13b8ef..4e468ff1127f 100644 --- a/lib/node_modules/@stdlib/stats/incr/msumabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/msumabs/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmsumabs = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/msumabs2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/msumabs2/benchmark/benchmark.js index 71160a554797..f4c9db2ee860 100644 --- a/lib/node_modules/@stdlib/stats/incr/msumabs2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/msumabs2/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmsumabs2 = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/msummary/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/msummary/benchmark/benchmark.js index 16cc36c6f180..33168ae6de8e 100644 --- a/lib/node_modules/@stdlib/stats/incr/msummary/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/msummary/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmsummary = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/msumprod/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/msumprod/benchmark/benchmark.js index 2982ed25c860..dcd6bc1935f6 100644 --- a/lib/node_modules/@stdlib/stats/incr/msumprod/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/msumprod/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmsumprod = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mvariance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mvariance/benchmark/benchmark.js index c551d21a599e..6634f0d99b98 100644 --- a/lib/node_modules/@stdlib/stats/incr/mvariance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mvariance/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmvariance = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_mean', function benchmark( b ) { +bench( format( '%s::accumulator,known_mean', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/mvmr/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mvmr/benchmark/benchmark.js index 92b9e1a21c0c..cd006355582e 100644 --- a/lib/node_modules/@stdlib/stats/incr/mvmr/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/mvmr/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrmvmr = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_mean', function benchmark( b ) { +bench( format( '%s::accumulator,known_mean', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/nancount/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nancount/benchmark/benchmark.js index 09c69389883b..1d17ebb639aa 100644 --- a/lib/node_modules/@stdlib/stats/incr/nancount/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/nancount/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrnancount = require( './../lib' ); @@ -45,7 +46,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/nangmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nangmean/benchmark/benchmark.js index 3462392366f7..c10f5f8a7773 100644 --- a/lib/node_modules/@stdlib/stats/incr/nangmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/nangmean/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrnangmean = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/nanhmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanhmean/benchmark/benchmark.js index 08776697bdaf..cccf805b0f67 100644 --- a/lib/node_modules/@stdlib/stats/incr/nanhmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/nanhmean/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrnanhmean = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmaxabs/benchmark/benchmark.js index e1045443c8d4..b3fbea8e6358 100644 --- a/lib/node_modules/@stdlib/stats/incr/nanmaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/nanmaxabs/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrnanmaxabs = require( './../lib' ); @@ -45,7 +46,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmcv/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmcv/benchmark/benchmark.js index f9e0b14bbac3..4be9c64d2143 100644 --- a/lib/node_modules/@stdlib/stats/incr/nanmcv/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/nanmcv/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrnanmcv = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_mean', function benchmark( b ) { +bench( format( '%s::accumulator,known_mean', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmean/benchmark/benchmark.js index 28588b1e3781..c70e981b2c58 100644 --- a/lib/node_modules/@stdlib/stats/incr/nanmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/nanmean/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrnanmean = require( './../lib' ); @@ -45,7 +46,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmeanabs/benchmark/benchmark.js index 9e67b90ecb26..1c535b2ad05e 100644 --- a/lib/node_modules/@stdlib/stats/incr/nanmeanabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanabs/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrnanmeanabs = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmin/benchmark/benchmark.js index 1f67602e89d4..7c4be3d6790e 100644 --- a/lib/node_modules/@stdlib/stats/incr/nanmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/nanmin/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrnanmin = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmse/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmmse/benchmark/benchmark.js index 248a64414a79..0c870129131e 100644 --- a/lib/node_modules/@stdlib/stats/incr/nanmmse/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/nanmmse/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrnanmmse = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmstdev/benchmark/benchmark.js index 219f6c3bcf9d..4da43c70a912 100644 --- a/lib/node_modules/@stdlib/stats/incr/nanmstdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/nanmstdev/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrnanmstdev = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_mean', function benchmark( b ) { +bench( format( '%s::accumulator,known_mean', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmsum/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmsum/benchmark/benchmark.js index b21182fdcfa7..af378447a8ca 100644 --- a/lib/node_modules/@stdlib/stats/incr/nanmsum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/nanmsum/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrnanmsum = require( './../lib' ); @@ -45,7 +46,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/nanskewness/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanskewness/benchmark/benchmark.js index 3d123502f012..ff28a98381e4 100644 --- a/lib/node_modules/@stdlib/stats/incr/nanskewness/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/nanskewness/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrnanskewness = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/nanstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanstdev/benchmark/benchmark.js index 2271eec6d9e9..91c3613c4b4b 100644 --- a/lib/node_modules/@stdlib/stats/incr/nanstdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/nanstdev/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrnanstdev = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_mean', function benchmark( b ) { +bench( format( '%s::accumulator,known_mean', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/nansum/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nansum/benchmark/benchmark.js index d97b9c0ed49b..c28cf1fbf3ff 100644 --- a/lib/node_modules/@stdlib/stats/incr/nansum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/nansum/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrnansum = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/nansumabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nansumabs/benchmark/benchmark.js index 482c22660f45..23ff6e8bcbc8 100644 --- a/lib/node_modules/@stdlib/stats/incr/nansumabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/nansumabs/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrnansumabs = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/nansumabs2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nansumabs2/benchmark/benchmark.js index a97a297283c5..d25c8ac62f71 100644 --- a/lib/node_modules/@stdlib/stats/incr/nansumabs2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/nansumabs2/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrnansumabs2 = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/pcorr/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/pcorr/benchmark/benchmark.js index aaaa331c231b..84adb0b68127 100644 --- a/lib/node_modules/@stdlib/stats/incr/pcorr/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/pcorr/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrpcorr = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_means', function benchmark( b ) { +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/pcorr2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/pcorr2/benchmark/benchmark.js index 7f2b713ee62f..0536d5aa85af 100644 --- a/lib/node_modules/@stdlib/stats/incr/pcorr2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/pcorr2/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrpcorr2 = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_means', function benchmark( b ) { +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/pcorrdist/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/pcorrdist/benchmark/benchmark.js index 12aa7d7bdacd..56de2970b201 100644 --- a/lib/node_modules/@stdlib/stats/incr/pcorrdist/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/pcorrdist/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrpcorrdist = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_means', function benchmark( b ) { +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/pcorrdistmat/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/pcorrdistmat/benchmark/benchmark.js index c49f2816bcbe..cdb4668e22d8 100644 --- a/lib/node_modules/@stdlib/stats/incr/pcorrdistmat/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/pcorrdistmat/benchmark/benchmark.js @@ -25,13 +25,14 @@ var randu = require( '@stdlib/random/base/randu' ); var ndarray = require( '@stdlib/ndarray/ctor' ); var Float64Array = require( '@stdlib/array/float64' ); var isSymmetricMatrix = require( '@stdlib/assert/is-symmetric-matrix' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrpcorrdistmat = require( './../lib' ); // MAIN // -bench( pkg+'::order', function benchmark( b ) { +bench( format( '%s::order', pkg ), function benchmark( b ) { var f; var i; @@ -50,7 +51,7 @@ bench( pkg+'::order', function benchmark( b ) { b.end(); }); -bench( pkg+'::order,means', function benchmark( b ) { +bench( format( '%s::order,means', pkg ), function benchmark( b ) { var strides; var buffer; var means; @@ -78,7 +79,7 @@ bench( pkg+'::order,means', function benchmark( b ) { b.end(); }); -bench( pkg+'::correlation_matrix', function benchmark( b ) { +bench( format( '%s::correlation_matrix', pkg ), function benchmark( b ) { var strides; var buffer; var shape; @@ -106,7 +107,7 @@ bench( pkg+'::correlation_matrix', function benchmark( b ) { b.end(); }); -bench( pkg+'::correlation_matrix,means', function benchmark( b ) { +bench( format( '%s::correlation_matrix,means', pkg ), function benchmark( b ) { var strides; var buffer; var shape; @@ -140,7 +141,7 @@ bench( pkg+'::correlation_matrix,means', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var strides; var buffer; var shape; @@ -179,7 +180,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_means', function benchmark( b ) { +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { var strides; var buffer; var means; diff --git a/lib/node_modules/@stdlib/stats/incr/pcorrmat/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/pcorrmat/benchmark/benchmark.js index 8176791de9d4..089f1415b86e 100644 --- a/lib/node_modules/@stdlib/stats/incr/pcorrmat/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/pcorrmat/benchmark/benchmark.js @@ -25,13 +25,14 @@ var randu = require( '@stdlib/random/base/randu' ); var ndarray = require( '@stdlib/ndarray/ctor' ); var Float64Array = require( '@stdlib/array/float64' ); var isSymmetricMatrix = require( '@stdlib/assert/is-symmetric-matrix' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrpcorrmat = require( './../lib' ); // MAIN // -bench( pkg+'::order', function benchmark( b ) { +bench( format( '%s::order', pkg ), function benchmark( b ) { var f; var i; @@ -50,7 +51,7 @@ bench( pkg+'::order', function benchmark( b ) { b.end(); }); -bench( pkg+'::order,means', function benchmark( b ) { +bench( format( '%s::order,means', pkg ), function benchmark( b ) { var strides; var buffer; var means; @@ -78,7 +79,7 @@ bench( pkg+'::order,means', function benchmark( b ) { b.end(); }); -bench( pkg+'::correlation_matrix', function benchmark( b ) { +bench( format( '%s::correlation_matrix', pkg ), function benchmark( b ) { var strides; var buffer; var shape; @@ -106,7 +107,7 @@ bench( pkg+'::correlation_matrix', function benchmark( b ) { b.end(); }); -bench( pkg+'::correlation_matrix,means', function benchmark( b ) { +bench( format( '%s::correlation_matrix,means', pkg ), function benchmark( b ) { var strides; var buffer; var shape; @@ -140,7 +141,7 @@ bench( pkg+'::correlation_matrix,means', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var strides; var buffer; var shape; @@ -179,7 +180,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_means', function benchmark( b ) { +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { var strides; var buffer; var means; diff --git a/lib/node_modules/@stdlib/stats/incr/prod/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/prod/benchmark/benchmark.js index ac835feb7e92..396f40e25be5 100644 --- a/lib/node_modules/@stdlib/stats/incr/prod/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/prod/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrprod = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/range/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/range/benchmark/benchmark.js index f2d295ffd36d..51097fb0e240 100644 --- a/lib/node_modules/@stdlib/stats/incr/range/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/range/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrrange = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/rmse/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/rmse/benchmark/benchmark.js index c6fe5502f962..fdc52e64a2d7 100644 --- a/lib/node_modules/@stdlib/stats/incr/rmse/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/rmse/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrrmse = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/rss/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/rss/benchmark/benchmark.js index 0a4ef4640544..89e78b0c4d23 100644 --- a/lib/node_modules/@stdlib/stats/incr/rss/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/rss/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrrss = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/skewness/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/skewness/benchmark/benchmark.js index d18170b77817..88cb9a2cdfed 100644 --- a/lib/node_modules/@stdlib/stats/incr/skewness/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/skewness/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrskewness = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/stdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/stdev/benchmark/benchmark.js index d695b14aa55f..3a4482fe386c 100644 --- a/lib/node_modules/@stdlib/stats/incr/stdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/stdev/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrstdev = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_mean', function benchmark( b ) { +bench( format( '%s::accumulator,known_mean', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/sum/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/sum/benchmark/benchmark.js index 2f5f8e790a87..56f6f8298075 100644 --- a/lib/node_modules/@stdlib/stats/incr/sum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/sum/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrsum = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/sumabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/sumabs/benchmark/benchmark.js index 4f8748ae4ff6..96537041290c 100644 --- a/lib/node_modules/@stdlib/stats/incr/sumabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/sumabs/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrsumabs = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/sumabs2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/sumabs2/benchmark/benchmark.js index 345987057619..623c2a042275 100644 --- a/lib/node_modules/@stdlib/stats/incr/sumabs2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/sumabs2/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrsumabs2 = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/summary/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/summary/benchmark/benchmark.js index 3c91c1c545c8..0e295abe26e5 100644 --- a/lib/node_modules/@stdlib/stats/incr/summary/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/summary/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrsummary = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/sumprod/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/sumprod/benchmark/benchmark.js index 10afe599e8c1..a4b93976cfe2 100644 --- a/lib/node_modules/@stdlib/stats/incr/sumprod/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/sumprod/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrsumprod = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/variance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/variance/benchmark/benchmark.js index 8367fd1b573f..6601c4bb53c3 100644 --- a/lib/node_modules/@stdlib/stats/incr/variance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/variance/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrvariance = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_mean', function benchmark( b ) { +bench( format( '%s::accumulator,known_mean', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/incr/vmr/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/vmr/benchmark/benchmark.js index 4731310b6fb8..af946d19e149 100644 --- a/lib/node_modules/@stdlib/stats/incr/vmr/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/incr/vmr/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var incrvmr = require( './../lib' ); @@ -46,7 +47,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator', function benchmark( b ) { +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { var acc; var v; var i; @@ -68,7 +69,7 @@ bench( pkg+'::accumulator', function benchmark( b ) { b.end(); }); -bench( pkg+'::accumulator,known_mean', function benchmark( b ) { +bench( format( '%s::accumulator,known_mean', pkg ), function benchmark( b ) { var acc; var v; var i; diff --git a/lib/node_modules/@stdlib/stats/iter/cugmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/cugmean/benchmark/benchmark.js index 2b80b0bda52f..abdbb21bca43 100644 --- a/lib/node_modules/@stdlib/stats/iter/cugmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/cugmean/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itercugmean = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/cuhmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/cuhmean/benchmark/benchmark.js index 0ac16bfa2e65..c7e5b637c059 100644 --- a/lib/node_modules/@stdlib/stats/iter/cuhmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/cuhmean/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itercuhmean = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/cumax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/cumax/benchmark/benchmark.js index 1b5fa7a23e1a..5efc9896d392 100644 --- a/lib/node_modules/@stdlib/stats/iter/cumax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/cumax/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itercumax = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/cumaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/cumaxabs/benchmark/benchmark.js index 6a5101c456a2..6e95b0cfd1f1 100644 --- a/lib/node_modules/@stdlib/stats/iter/cumaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/cumaxabs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itercumaxabs = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/cumean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/cumean/benchmark/benchmark.js index bf914f4db46c..e7c0ab42d44b 100644 --- a/lib/node_modules/@stdlib/stats/iter/cumean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/cumean/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itercumean = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/cumeanabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/cumeanabs/benchmark/benchmark.js index fea3f5bcc052..2cdcd0b8e2c8 100644 --- a/lib/node_modules/@stdlib/stats/iter/cumeanabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/cumeanabs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itercumeanabs = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/cumeanabs2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/cumeanabs2/benchmark/benchmark.js index 7eebab1e4632..ab3cbdbde398 100644 --- a/lib/node_modules/@stdlib/stats/iter/cumeanabs2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/cumeanabs2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itercumeanabs2 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/cumidrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/cumidrange/benchmark/benchmark.js index eb3cc9e26c15..136c7ffb7398 100644 --- a/lib/node_modules/@stdlib/stats/iter/cumidrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/cumidrange/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itercumidrange = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/cumin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/cumin/benchmark/benchmark.js index f7011efc7dbe..b68c534f80d5 100644 --- a/lib/node_modules/@stdlib/stats/iter/cumin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/cumin/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itercumin = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/cuminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/cuminabs/benchmark/benchmark.js index 4ab35120df65..e0e56a1aaab7 100644 --- a/lib/node_modules/@stdlib/stats/iter/cuminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/cuminabs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itercuminabs = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/cuprod/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/cuprod/benchmark/benchmark.js index 5fea8a673178..51b37241a5c7 100644 --- a/lib/node_modules/@stdlib/stats/iter/cuprod/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/cuprod/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itercuprod = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/curange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/curange/benchmark/benchmark.js index 5e66ea708083..a2a1256a69d8 100644 --- a/lib/node_modules/@stdlib/stats/iter/curange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/curange/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itercurange = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/cusum/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/cusum/benchmark/benchmark.js index b20090abbc4c..c7119de9078e 100644 --- a/lib/node_modules/@stdlib/stats/iter/cusum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/cusum/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itercusum = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/cusumabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/cusumabs/benchmark/benchmark.js index b163b08b9ad3..2b42a4f5fce1 100644 --- a/lib/node_modules/@stdlib/stats/iter/cusumabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/cusumabs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itercusumabs = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/cusumabs2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/cusumabs2/benchmark/benchmark.js index 0d00dbac2124..1c3097b4ba51 100644 --- a/lib/node_modules/@stdlib/stats/iter/cusumabs2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/cusumabs2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itercusumabs2 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/mmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/mmax/benchmark/benchmark.js index 5dc8236a8f5c..474ad1cccf2c 100644 --- a/lib/node_modules/@stdlib/stats/iter/mmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/mmax/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itermmax = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/mmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/mmaxabs/benchmark/benchmark.js index 2e66d62ba519..429fa8d82655 100644 --- a/lib/node_modules/@stdlib/stats/iter/mmaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/mmaxabs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itermmaxabs = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/mmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/mmean/benchmark/benchmark.js index f7a079155228..634bd82ba280 100644 --- a/lib/node_modules/@stdlib/stats/iter/mmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/mmean/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itermmean = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/mmeanabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/mmeanabs/benchmark/benchmark.js index 86f004467eac..ce754ca0b309 100644 --- a/lib/node_modules/@stdlib/stats/iter/mmeanabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/mmeanabs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itermmeanabs = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/mmeanabs2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/mmeanabs2/benchmark/benchmark.js index 951315c50134..65f616ee629b 100644 --- a/lib/node_modules/@stdlib/stats/iter/mmeanabs2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/mmeanabs2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itermmeanabs2 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/mmidrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/mmidrange/benchmark/benchmark.js index 293e9b05ad43..f095300c0040 100644 --- a/lib/node_modules/@stdlib/stats/iter/mmidrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/mmidrange/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itermmidrange = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/mmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/mmin/benchmark/benchmark.js index 8c567bc87ae8..650b525a6170 100644 --- a/lib/node_modules/@stdlib/stats/iter/mmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/mmin/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itermmin = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/mminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/mminabs/benchmark/benchmark.js index b41f202339c7..e64768e975fb 100644 --- a/lib/node_modules/@stdlib/stats/iter/mminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/mminabs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itermminabs = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/mprod/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/mprod/benchmark/benchmark.js index 530c6a624fcd..57f4f8006264 100644 --- a/lib/node_modules/@stdlib/stats/iter/mprod/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/mprod/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itermprod = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/mrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/mrange/benchmark/benchmark.js index d4ce275e56f1..25f88bb02b2d 100644 --- a/lib/node_modules/@stdlib/stats/iter/mrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/mrange/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itermrange = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/msum/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/msum/benchmark/benchmark.js index d5659729799b..c64c381a067e 100644 --- a/lib/node_modules/@stdlib/stats/iter/msum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/msum/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itermsum = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/msumabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/msumabs/benchmark/benchmark.js index 9fe01d376286..32589dd99f4a 100644 --- a/lib/node_modules/@stdlib/stats/iter/msumabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/msumabs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itermsumabs = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/iter/msumabs2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/iter/msumabs2/benchmark/benchmark.js index 5d15e6bf01e8..08417bb2ed9e 100644 --- a/lib/node_modules/@stdlib/stats/iter/msumabs2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/iter/msumabs2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isIteratorLike = require( '@stdlib/assert/is-iterator-like' ); var randu = require( '@stdlib/random/iter/randu' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var itermsumabs2 = require( './../lib' ); @@ -52,7 +53,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::iteration', function benchmark( b ) { +bench( format( '%s::iteration', pkg ), function benchmark( b ) { var iter; var rand; var v; diff --git a/lib/node_modules/@stdlib/stats/kruskal-test/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/kruskal-test/benchmark/benchmark.js index 72b7c5ddc89c..d5fd35b73e70 100644 --- a/lib/node_modules/@stdlib/stats/kruskal-test/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/kruskal-test/benchmark/benchmark.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); var isObject = require( '@stdlib/assert/is-object' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var kruskalTest = require( './../lib' ); @@ -65,7 +66,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::groups', function benchmark( b ) { +bench( format( '%s::groups', pkg ), function benchmark( b ) { var result; var group; var vals; @@ -98,7 +99,7 @@ bench( pkg+'::groups', function benchmark( b ) { b.end(); }); -bench( pkg+':print', function benchmark( b ) { +bench( format( '%s:print', pkg ), function benchmark( b ) { var digits; var result; var output; diff --git a/lib/node_modules/@stdlib/stats/levene-test/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/levene-test/benchmark/benchmark.js index e712d61ee528..a4778e61930a 100644 --- a/lib/node_modules/@stdlib/stats/levene-test/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/levene-test/benchmark/benchmark.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); var isObject = require( '@stdlib/assert/is-object' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var leveneTest = require( './../lib' ); @@ -63,7 +64,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::groups', function benchmark( b ) { +bench( format( '%s::groups', pkg ), function benchmark( b ) { var result; var group; var v; @@ -94,7 +95,7 @@ bench( pkg+'::groups', function benchmark( b ) { b.end(); }); -bench( pkg+':print', function benchmark( b ) { +bench( format( '%s:print', pkg ), function benchmark( b ) { var digits; var result; var output; diff --git a/lib/node_modules/@stdlib/stats/lowess/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/lowess/benchmark/benchmark.js index f1c6be14db35..2531da99ca97 100644 --- a/lib/node_modules/@stdlib/stats/lowess/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/lowess/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isObject = require( '@stdlib/assert/is-object' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var lowess = require( './../lib' ); @@ -60,7 +61,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+':sorted=true', function benchmark( b ) { +bench( format( '%s:sorted=true', pkg ), function benchmark( b ) { var result; var opts; var x; @@ -94,7 +95,7 @@ bench( pkg+':sorted=true', function benchmark( b ) { b.end(); }); -bench( pkg+':f=0.5', function benchmark( b ) { +bench( format( '%s:f=0.5', pkg ), function benchmark( b ) { var result; var opts; var x; @@ -128,7 +129,7 @@ bench( pkg+':f=0.5', function benchmark( b ) { b.end(); }); -bench( pkg+':delta=3', function benchmark( b ) { +bench( format( '%s:delta=3', pkg ), function benchmark( b ) { var result; var opts; var x; @@ -162,7 +163,7 @@ bench( pkg+':delta=3', function benchmark( b ) { b.end(); }); -bench( pkg+':delta=0', function benchmark( b ) { +bench( format( '%s:delta=0', pkg ), function benchmark( b ) { var result; var opts; var x; @@ -196,7 +197,7 @@ bench( pkg+':delta=0', function benchmark( b ) { b.end(); }); -bench( pkg+':nsteps=1', function benchmark( b ) { +bench( format( '%s:nsteps=1', pkg ), function benchmark( b ) { var result; var opts; var x; @@ -230,7 +231,7 @@ bench( pkg+':nsteps=1', function benchmark( b ) { b.end(); }); -bench( pkg+':nsteps=2', function benchmark( b ) { +bench( format( '%s:nsteps=2', pkg ), function benchmark( b ) { var result; var opts; var x; diff --git a/lib/node_modules/@stdlib/stats/max/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/max/benchmark/benchmark.assign.js index 5b640ad87f75..733d64f43c51 100644 --- a/lib/node_modules/@stdlib/stats/max/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/max/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var max = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/max/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/max/benchmark/benchmark.js index 01ead6e8f4b5..70cd63398fbf 100644 --- a/lib/node_modules/@stdlib/stats/max/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/max/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var max = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/meankbn/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/meankbn/benchmark/benchmark.assign.js index e681245338b7..b70a2c869814 100644 --- a/lib/node_modules/@stdlib/stats/meankbn/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/meankbn/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meankbn = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/meankbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/meankbn/benchmark/benchmark.js index 2a0524593c45..1043a448c140 100644 --- a/lib/node_modules/@stdlib/stats/meankbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/meankbn/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meankbn = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/meankbn2/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/meankbn2/benchmark/benchmark.assign.js index 769aa698e5e1..1cd9e6a6231d 100644 --- a/lib/node_modules/@stdlib/stats/meankbn2/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/meankbn2/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meankbn2 = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/meankbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/meankbn2/benchmark/benchmark.js index 15fcc5645f15..7d06b5caf9f5 100644 --- a/lib/node_modules/@stdlib/stats/meankbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/meankbn2/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meankbn2 = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/meanors/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/meanors/benchmark/benchmark.assign.js index b855e3bf7d02..a5a30f841a3f 100644 --- a/lib/node_modules/@stdlib/stats/meanors/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/meanors/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanors = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/meanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/meanors/benchmark/benchmark.js index 6faf16b46627..a74b29d20a79 100644 --- a/lib/node_modules/@stdlib/stats/meanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/meanors/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanors = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/meanpn/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/meanpn/benchmark/benchmark.assign.js index 166bb6697513..5ea9fa741e94 100644 --- a/lib/node_modules/@stdlib/stats/meanpn/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/meanpn/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanpn = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/meanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/meanpn/benchmark/benchmark.js index d160a803ad2a..a07473ffaee9 100644 --- a/lib/node_modules/@stdlib/stats/meanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/meanpn/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanpn = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/meanpw/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/meanpw/benchmark/benchmark.assign.js index d60d5698c993..5b63c02e7de2 100644 --- a/lib/node_modules/@stdlib/stats/meanpw/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/meanpw/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanpw = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/meanpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/meanpw/benchmark/benchmark.js index b7a62040bb97..5f1a6ff12a3d 100644 --- a/lib/node_modules/@stdlib/stats/meanpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/meanpw/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanpw = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/mediansorted/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/mediansorted/benchmark/benchmark.assign.js index 6c8b9e32625c..705ca75087f6 100644 --- a/lib/node_modules/@stdlib/stats/mediansorted/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/mediansorted/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var linspace = require( '@stdlib/array/linspace' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mediansorted = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/mediansorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/mediansorted/benchmark/benchmark.js index ba6f6328a4e6..b7dc887e9152 100644 --- a/lib/node_modules/@stdlib/stats/mediansorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/mediansorted/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var linspace = require( '@stdlib/array/linspace' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mediansorted = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/min/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/min/benchmark/benchmark.assign.js index 69992cb5662a..c8201d859bcd 100644 --- a/lib/node_modules/@stdlib/stats/min/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/min/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var min = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/min/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/min/benchmark/benchmark.js index 139eda166dd5..027249866de3 100644 --- a/lib/node_modules/@stdlib/stats/min/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/min/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var min = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/minabs/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/minabs/benchmark/benchmark.assign.js index 8431d516a627..929665db78c0 100644 --- a/lib/node_modules/@stdlib/stats/minabs/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/minabs/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minabs = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/minabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/minabs/benchmark/benchmark.js index 6de9cfe2a39f..d15d7b69c515 100644 --- a/lib/node_modules/@stdlib/stats/minabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/minabs/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minabs = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/minsorted/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/minsorted/benchmark/benchmark.assign.js index 4e482beb3b74..a241a1e822d9 100644 --- a/lib/node_modules/@stdlib/stats/minsorted/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/minsorted/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var linspace = require( '@stdlib/array/linspace' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minsorted = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/minsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/minsorted/benchmark/benchmark.js index 4b6485b2828a..d2420284383c 100644 --- a/lib/node_modules/@stdlib/stats/minsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/minsorted/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var linspace = require( '@stdlib/array/linspace' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minsorted = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanmax-by/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/nanmax-by/benchmark/benchmark.assign.js index 21a148853f2a..5e1da3a39753 100644 --- a/lib/node_modules/@stdlib/stats/nanmax-by/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/nanmax-by/benchmark/benchmark.assign.js @@ -21,12 +21,12 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var format = require( '@stdlib/string/format' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); -var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var zeros = require( '@stdlib/array/zeros' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmaxBy = require( './../lib' ); diff --git a/lib/node_modules/@stdlib/stats/nanmax-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/nanmax-by/benchmark/benchmark.js index 7db86d1852da..fe5040050839 100644 --- a/lib/node_modules/@stdlib/stats/nanmax-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/nanmax-by/benchmark/benchmark.js @@ -21,11 +21,11 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var format = require( '@stdlib/string/format' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmaxBy = require( './../lib' ); diff --git a/lib/node_modules/@stdlib/stats/nanmax/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/nanmax/benchmark/benchmark.assign.js index 220d7c4e4a7d..7eaf9aef075d 100644 --- a/lib/node_modules/@stdlib/stats/nanmax/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/nanmax/benchmark/benchmark.assign.js @@ -28,6 +28,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmax = require( './../lib' ); @@ -119,7 +120,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/nanmax/benchmark/benchmark.js index adb1ca78badf..f39537c7dee8 100644 --- a/lib/node_modules/@stdlib/stats/nanmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/nanmax/benchmark/benchmark.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmax = require( './../lib' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanmaxabs/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/nanmaxabs/benchmark/benchmark.assign.js index c5f27b84a1bf..3e2ab31689cb 100644 --- a/lib/node_modules/@stdlib/stats/nanmaxabs/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/nanmaxabs/benchmark/benchmark.assign.js @@ -28,6 +28,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmaxabs = require( './../lib' ); @@ -119,7 +120,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/nanmaxabs/benchmark/benchmark.js index e4565f065e5b..cba09738809e 100644 --- a/lib/node_modules/@stdlib/stats/nanmaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/nanmaxabs/benchmark/benchmark.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmaxabs = require( './../lib' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanmean/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/nanmean/benchmark/benchmark.assign.js index 4df6c0ee674e..569a2cf3fbe8 100644 --- a/lib/node_modules/@stdlib/stats/nanmean/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/nanmean/benchmark/benchmark.assign.js @@ -28,6 +28,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmean = require( './../lib' ); @@ -119,7 +120,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/nanmean/benchmark/benchmark.js index 4a0b9f810f37..8a97e89028d1 100644 --- a/lib/node_modules/@stdlib/stats/nanmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/nanmean/benchmark/benchmark.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmean = require( './../lib' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanmeanors/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/nanmeanors/benchmark/benchmark.assign.js index 45d96a6b06b2..828c56c10fc6 100644 --- a/lib/node_modules/@stdlib/stats/nanmeanors/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/nanmeanors/benchmark/benchmark.assign.js @@ -28,6 +28,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmeanors = require( './../lib' ); @@ -119,7 +120,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/nanmeanors/benchmark/benchmark.js index d80307421641..35c30942ad09 100644 --- a/lib/node_modules/@stdlib/stats/nanmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/nanmeanors/benchmark/benchmark.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmeanors = require( './../lib' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanmeanpn/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/nanmeanpn/benchmark/benchmark.assign.js index a56ddf01f8dc..7eab2ea575b7 100644 --- a/lib/node_modules/@stdlib/stats/nanmeanpn/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/nanmeanpn/benchmark/benchmark.assign.js @@ -28,6 +28,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmeanpn = require( './../lib' ); @@ -119,7 +120,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanmeanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/nanmeanpn/benchmark/benchmark.js index 8d29e7aac570..b62776fdee29 100644 --- a/lib/node_modules/@stdlib/stats/nanmeanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/nanmeanpn/benchmark/benchmark.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmeanpn = require( './../lib' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanmeanwd/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/nanmeanwd/benchmark/benchmark.assign.js index 96970bcc0efb..43b21367c934 100644 --- a/lib/node_modules/@stdlib/stats/nanmeanwd/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/nanmeanwd/benchmark/benchmark.assign.js @@ -28,6 +28,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmeanwd = require( './../lib' ); @@ -119,7 +120,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/nanmeanwd/benchmark/benchmark.js index 146af80ac0fc..8e0f02e96212 100644 --- a/lib/node_modules/@stdlib/stats/nanmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/nanmeanwd/benchmark/benchmark.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmeanwd = require( './../lib' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanmin-by/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/nanmin-by/benchmark/benchmark.assign.js index 2c028c36d7ba..3369f29076f4 100644 --- a/lib/node_modules/@stdlib/stats/nanmin-by/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/nanmin-by/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanminBy = require( './../lib' ); @@ -115,7 +116,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanmin-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/nanmin-by/benchmark/benchmark.js index 69c1ac4c23e3..71dcffd1b576 100644 --- a/lib/node_modules/@stdlib/stats/nanmin-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/nanmin-by/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanminBy = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanmin/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/nanmin/benchmark/benchmark.assign.js index fcf3fca791b4..26c6d9684e09 100644 --- a/lib/node_modules/@stdlib/stats/nanmin/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/nanmin/benchmark/benchmark.assign.js @@ -28,6 +28,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmin = require( './../lib' ); @@ -119,7 +120,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/nanmin/benchmark/benchmark.js index 012ed1f64c09..909cfd710d16 100644 --- a/lib/node_modules/@stdlib/stats/nanmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/nanmin/benchmark/benchmark.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmin = require( './../lib' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanminabs/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/nanminabs/benchmark/benchmark.assign.js index 6bd44551bf2b..4a4468186310 100644 --- a/lib/node_modules/@stdlib/stats/nanminabs/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/nanminabs/benchmark/benchmark.assign.js @@ -28,6 +28,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanminabs = require( './../lib' ); @@ -119,7 +120,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/nanminabs/benchmark/benchmark.js index 2ec6217057ca..e4cb1c9ff25c 100644 --- a/lib/node_modules/@stdlib/stats/nanminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/nanminabs/benchmark/benchmark.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanminabs = require( './../lib' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanrange-by/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/nanrange-by/benchmark/benchmark.assign.js index f33b16b9faf9..adc7167715c6 100644 --- a/lib/node_modules/@stdlib/stats/nanrange-by/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/nanrange-by/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanrangeBy = require( './../lib' ); @@ -115,7 +116,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanrange-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/nanrange-by/benchmark/benchmark.js index b1292d6b2c95..f13ed6406dcd 100644 --- a/lib/node_modules/@stdlib/stats/nanrange-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/nanrange-by/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanrangeBy = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanrange/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/nanrange/benchmark/benchmark.assign.js index 5b0d2187e9de..0b1ffb9096e1 100644 --- a/lib/node_modules/@stdlib/stats/nanrange/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/nanrange/benchmark/benchmark.assign.js @@ -28,6 +28,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanrange = require( './../lib' ); @@ -119,7 +120,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/nanrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/nanrange/benchmark/benchmark.js index 20fbdc27b1bb..78153f5512a0 100644 --- a/lib/node_modules/@stdlib/stats/nanrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/nanrange/benchmark/benchmark.js @@ -27,6 +27,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanrange = require( './../lib' ); @@ -113,7 +114,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/pcorrtest/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/pcorrtest/benchmark/benchmark.js index 07e3962186c1..bf7d9ce0567e 100644 --- a/lib/node_modules/@stdlib/stats/pcorrtest/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/pcorrtest/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isObject = require( '@stdlib/assert/is-object' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var rnorm = require( '@stdlib/random/base/normal' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var pcorrtest = require( './../lib' ); @@ -64,7 +65,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::one-sided', function benchmark( b ) { +bench( format( '%s::one-sided', pkg ), function benchmark( b ) { var result; var opts; var rho; @@ -101,7 +102,7 @@ bench( pkg+'::one-sided', function benchmark( b ) { b.end(); }); -bench( pkg+':rho=0.5', function benchmark( b ) { +bench( format( '%s:rho=0.5', pkg ), function benchmark( b ) { var result; var opts; var rho; @@ -138,7 +139,7 @@ bench( pkg+':rho=0.5', function benchmark( b ) { b.end(); }); -bench( pkg+':print', function benchmark( b ) { +bench( format( '%s:print', pkg ), function benchmark( b ) { var digits; var result; var output; diff --git a/lib/node_modules/@stdlib/stats/range-by/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/range-by/benchmark/benchmark.assign.js index 552af7e47a46..e8fecdf3b82b 100644 --- a/lib/node_modules/@stdlib/stats/range-by/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/range-by/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var rangeBy = require( './../lib' ); @@ -115,7 +116,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/range-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/range-by/benchmark/benchmark.js index 19b00f1d9ecd..f7ae4e76f106 100644 --- a/lib/node_modules/@stdlib/stats/range-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/range-by/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var rangeBy = require( './../lib' ); @@ -109,7 +110,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/range/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/range/benchmark/benchmark.assign.js index ae222f2db9d1..b9c9142ef2be 100644 --- a/lib/node_modules/@stdlib/stats/range/benchmark/benchmark.assign.js +++ b/lib/node_modules/@stdlib/stats/range/benchmark/benchmark.assign.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var zeros = require( '@stdlib/array/zeros' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var range = require( './../lib' ); @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':assign:dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/range/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/range/benchmark/benchmark.js index 00d1257e5507..8a7775902824 100644 --- a/lib/node_modules/@stdlib/stats/range/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/range/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var range = require( './../lib' ); @@ -98,7 +99,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':dtype='+options.dtype+',len='+len, f ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/README.md b/lib/node_modules/@stdlib/stats/strided/README.md index 8e081d006d11..39ca4965c25a 100644 --- a/lib/node_modules/@stdlib/stats/strided/README.md +++ b/lib/node_modules/@stdlib/stats/strided/README.md @@ -90,6 +90,7 @@ The namespace exports the following: - [`dmskmidrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dmskmidrange]: calculate the mid-range of a double-precision floating-point strided array according to a mask. - [`dmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dmskmin]: calculate the minimum value of a double-precision floating-point strided array according to a mask. - [`dmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dmskrange]: calculate the range of a double-precision floating-point strided array according to a mask. +- [`dnancount( N, x, strideX )`][@stdlib/stats/strided/dnancount]: calculate the number of non-`NaN` elements in a double-precision floating-point strided array. - [`dnanmax( N, x, strideX )`][@stdlib/stats/strided/dnanmax]: calculate the maximum value of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanmaxabs( N, x, strideX )`][@stdlib/stats/strided/dnanmaxabs]: calculate the maximum absolute value of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanmean( N, x, strideX )`][@stdlib/stats/strided/dnanmean]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values. @@ -101,10 +102,13 @@ The namespace exports the following: - [`dnanmin( N, x, strideX )`][@stdlib/stats/strided/dnanmin]: calculate the minimum value of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanminabs( N, x, strideX )`][@stdlib/stats/strided/dnanminabs]: calculate the minimum absolute value of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskmax]: calculate the maximum value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values. +- [`dnanmskmaxabs( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskmaxabs]: calculate the maximum absolute value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`dnanmskmidrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskmidrange]: calculate the mid-range of a double-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`dnanmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskmin]: calculate the minimum value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values. +- [`dnanmskminabs( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskminabs]: calculate the minimum absolute value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`dnanmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskrange]: calculate the range of a double-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`dnanrange( N, x, strideX )`][@stdlib/stats/strided/dnanrange]: calculate the range of a double-precision floating-point strided array, ignoring `NaN` values. +- [`dnanrangeabs( N, \*X, strideX )`][@stdlib/stats/strided/dnanrangeabs]: compute the range of absolute values of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanstdev( N, correction, x, strideX )`][@stdlib/stats/strided/dnanstdev]: calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values. - [`dnanstdevch( N, correction, x, strideX )`][@stdlib/stats/strided/dnanstdevch]: calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass trial mean algorithm. - [`dnanstdevpn( N, correction, x, strideX )`][@stdlib/stats/strided/dnanstdevpn]: calculate the standard deviation of a double-precision floating-point strided array, ignoring `NaN` values and using a two-pass algorithm. @@ -117,6 +121,7 @@ The namespace exports the following: - [`dnanvariancetk( N, correction, x, strideX )`][@stdlib/stats/strided/dnanvariancetk]: calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass textbook algorithm. - [`dnanvariancewd( N, correction, x, strideX )`][@stdlib/stats/strided/dnanvariancewd]: calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using Welford's algorithm. - [`dnanvarianceyc( N, correction, x, strideX )`][@stdlib/stats/strided/dnanvarianceyc]: calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. +- [`dpcorrwd( N, x, strideX, y, strideY )`][@stdlib/stats/strided/dpcorrwd]: calculate the sample Pearson product-moment correlation coefficient of two double-precision floating-point strided arrays using Welford's algorithm. - [`drange( N, x, strideX )`][@stdlib/stats/strided/drange]: calculate the range of a double-precision floating-point strided array. - [`drangeabs( N, x, strideX )`][@stdlib/stats/strided/drangeabs]: compute the range of absolute values of a double-precision floating-point strided array. - [`dsem( N, correction, x, strideX )`][@stdlib/stats/strided/dsem]: calculate the standard error of the mean of a double-precision floating-point strided array. @@ -175,7 +180,9 @@ The namespace exports the following: - [`mskmaxabs( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskmaxabs]: calculate the maximum absolute value of a strided array according to a mask. - [`mskmidrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskmidrange]: calculate the mid-range of a strided array according to a mask. - [`mskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskmin]: calculate the minimum value of a strided array according to a mask. +- [`mskminabs( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskminabs]: calculate the minimum absolute value of a strided array according to a mask. - [`mskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskrange]: calculate the range of a strided array according to a mask. +- [`nancount( N, x, strideX )`][@stdlib/stats/strided/nancount]: calculate the number of non-`NaN` elements in a strided array. - [`nanmaxBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/stats/strided/nanmax-by]: calculate the maximum value of a strided array via a callback function, ignoring `NaN` values. - [`nanmax( N, x, strideX )`][@stdlib/stats/strided/nanmax]: calculate the maximum value of a strided array, ignoring `NaN` values. - [`nanmaxabs( N, x, strideX )`][@stdlib/stats/strided/nanmaxabs]: calculate the maximum absolute value of a strided array, ignoring `NaN` values. @@ -194,6 +201,7 @@ The namespace exports the following: - [`nanmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/nanmskrange]: calculate the range of a strided array according to a mask, ignoring `NaN` values. - [`nanrangeBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/stats/strided/nanrange-by]: calculate the range of a strided array via a callback function, ignoring `NaN` values. - [`nanrange( N, x, strideX )`][@stdlib/stats/strided/nanrange]: calculate the range of a strided array, ignoring `NaN` values. +- [`nanrangeabs( N, x, strideX )`][@stdlib/stats/strided/nanrangeabs]: calculate the range of absolute values of a strided array, ignoring `NaN` values. - [`nanstdev( N, correction, x, strideX )`][@stdlib/stats/strided/nanstdev]: calculate the standard deviation of a strided array ignoring `NaN` values. - [`nanstdevch( N, correction, x, strideX )`][@stdlib/stats/strided/nanstdevch]: calculate the standard deviation of a strided array ignoring `NaN` values and using a one-pass trial mean algorithm. - [`nanstdevpn( N, correction, x, strideX )`][@stdlib/stats/strided/nanstdevpn]: calculate the standard deviation of a strided array ignoring `NaN` values and using a two-pass algorithm. @@ -240,6 +248,7 @@ The namespace exports the following: - [`smskmidrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/smskmidrange]: calculate the mid-range of a single-precision floating-point strided array according to a mask. - [`smskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/smskmin]: calculate the minimum value of a single-precision floating-point strided array according to a mask. - [`smskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/smskrange]: calculate the range of a single-precision floating-point strided array according to a mask. +- [`snancount( N, x, strideX )`][@stdlib/stats/strided/snancount]: calculate the number of non-`NaN` elements in a single-precision floating-point strided array. - [`snanmax( N, x, strideX )`][@stdlib/stats/strided/snanmax]: calculate the maximum value of a single-precision floating-point strided array, ignoring `NaN` values. - [`snanmaxabs( N, x, strideX )`][@stdlib/stats/strided/snanmaxabs]: calculate the maximum absolute value of a single-precision floating-point strided array, ignoring `NaN` values. - [`snanmean( N, x, strideX )`][@stdlib/stats/strided/snanmean]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values. @@ -250,8 +259,10 @@ The namespace exports the following: - [`snanmin( N, x, strideX )`][@stdlib/stats/strided/snanmin]: calculate the minimum value of a single-precision floating-point strided array, ignoring `NaN` values. - [`snanminabs( N, x, strideX )`][@stdlib/stats/strided/snanminabs]: calculate the minimum absolute value of a single-precision floating-point strided array, ignoring `NaN` values. - [`snanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskmax]: calculate the maximum value of a single-precision floating-point strided array according to a mask, ignoring `NaN` values. +- [`snanmskmaxabs( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskmaxabs]: calculate the maximum absolute value of a single-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`snanmskmidrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskmidrange]: calculate the mid-range of a single-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`snanmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskmin]: calculate the minimum value of a single-precision floating-point strided array according to a mask, ignoring `NaN` values. +- [`snanmskminabs( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskminabs]: calculate the minimum absolute value of a single-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`snanmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskrange]: calculate the range of a single-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`snanrange( N, x, strideX )`][@stdlib/stats/strided/snanrange]: calculate the range of a single-precision floating-point strided array, ignoring `NaN` values. - [`srange( N, x, strideX )`][@stdlib/stats/strided/srange]: calculate the range of a single-precision floating-point strided array. @@ -406,6 +417,8 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/dmskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmskrange +[@stdlib/stats/strided/dnancount]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnancount + [@stdlib/stats/strided/dnanmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmax [@stdlib/stats/strided/dnanmaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmaxabs @@ -428,14 +441,20 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/dnanmskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmskmax +[@stdlib/stats/strided/dnanmskmaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmskmaxabs + [@stdlib/stats/strided/dnanmskmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmskmidrange [@stdlib/stats/strided/dnanmskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmskmin +[@stdlib/stats/strided/dnanmskminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmskminabs + [@stdlib/stats/strided/dnanmskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmskrange [@stdlib/stats/strided/dnanrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanrange +[@stdlib/stats/strided/dnanrangeabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanrangeabs + [@stdlib/stats/strided/dnanstdev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanstdev [@stdlib/stats/strided/dnanstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanstdevch @@ -460,6 +479,8 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/dnanvarianceyc]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanvarianceyc +[@stdlib/stats/strided/dpcorrwd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dpcorrwd + [@stdlib/stats/strided/drange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/drange [@stdlib/stats/strided/drangeabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/drangeabs @@ -576,8 +597,12 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/mskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mskmin +[@stdlib/stats/strided/mskminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mskminabs + [@stdlib/stats/strided/mskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mskrange +[@stdlib/stats/strided/nancount]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nancount + [@stdlib/stats/strided/nanmax-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmax-by [@stdlib/stats/strided/nanmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmax @@ -614,6 +639,8 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/nanrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanrange +[@stdlib/stats/strided/nanrangeabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanrangeabs + [@stdlib/stats/strided/nanstdev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanstdev [@stdlib/stats/strided/nanstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanstdevch @@ -706,6 +733,8 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/smskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/smskrange +[@stdlib/stats/strided/snancount]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snancount + [@stdlib/stats/strided/snanmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmax [@stdlib/stats/strided/snanmaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmaxabs @@ -726,10 +755,14 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/snanmskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmskmax +[@stdlib/stats/strided/snanmskmaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmskmaxabs + [@stdlib/stats/strided/snanmskmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmskmidrange [@stdlib/stats/strided/snanmskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmskmin +[@stdlib/stats/strided/snanmskminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmskminabs + [@stdlib/stats/strided/snanmskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmskrange [@stdlib/stats/strided/snanrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanrange diff --git a/lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.js index 444f827a3e58..5557e28bfb35 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.js @@ -26,6 +26,7 @@ var zeros = require( '@stdlib/array/zeros' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcovmatmtk = require( './../lib/dcovmatmtk.js' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); f = createBenchmark( N ); - bench( pkg+'::equidimensional:size='+(N*N), f ); + bench( format( '%s::equidimensional:size=%d', pkg, N*N ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.native.js index f9e28c8b4326..5783e95a3244 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); f = createBenchmark( N ); - bench( pkg+'::equidimensional:size='+(N*N), opts, f ); + bench( format( '%s::equidimensional:size=%d', pkg, N*N ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.ndarray.js index bf9e1dfc2901..344a99faff3d 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var zeros = require( '@stdlib/array/zeros' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcovmatmtk = require( './../lib/ndarray.js' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); f = createBenchmark( N ); - bench( pkg+'::equidimensional:ndarray:size='+(N*N), f ); + bench( format( '%s::equidimensional:ndarray:size=%d', pkg, N*N ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.ndarray.native.js index c351d7e2c042..5bd75f97969f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var floor = require( '@stdlib/math/base/special/floor' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); f = createBenchmark( N ); - bench( pkg+'::native,equidimensional:ndarray:size='+(N*N), opts, f ); + bench( format( '%s::native,equidimensional:ndarray:size=%d', pkg, N*N ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.js index 5199479669d2..292dc4b57975 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcumax = require( './../lib/dcumax.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.native.js index f9e5a509e595..292c692c3a1f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.ndarray.js index 7fa739b89d03..e252a0607b92 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcumax = require( './../lib/ndarray.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.ndarray.native.js index ad118833f361..3432a11920ad 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.js index 0702269bd792..1e16e8c45cf7 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcumaxabs = require( './../lib/dcumaxabs.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.native.js index 1e93fe07ccee..9db0fe7be771 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.ndarray.js index 73e81e390280..8ffad106ddc0 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcumaxabs = require( './../lib/ndarray.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.ndarray.native.js index 8b6b80f57b86..0d0163fa695c 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcumin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dcumin/benchmark/benchmark.js index 8bf162ae7a88..2f436dc31363 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcumin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumin/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcumin = require( './../lib/dcumin.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcumin/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dcumin/benchmark/benchmark.native.js index 8543c4a9b225..681be8e65b5b 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcumin/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumin/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcumin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dcumin/benchmark/benchmark.ndarray.js index b59814e4f62b..4aacb00f566b 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcumin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumin/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcumin = require( './../lib/ndarray.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcumin/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dcumin/benchmark/benchmark.ndarray.native.js index 1e36fb7157d4..b94648ba5410 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcumin/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumin/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcuminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dcuminabs/benchmark/benchmark.js index 8ec94e579d33..2efb263b19de 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcuminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dcuminabs/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcuminabs = require( './../lib/dcuminabs.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcuminabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dcuminabs/benchmark/benchmark.native.js index 39299ea6a1ed..9ddab303470e 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcuminabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dcuminabs/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcuminabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dcuminabs/benchmark/benchmark.ndarray.js index 63e53ef22dff..4e209129474e 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcuminabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dcuminabs/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dcuminabs = require( './../lib/ndarray.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dcuminabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dcuminabs/benchmark/benchmark.ndarray.native.js index c13148cffcbf..b4fc9d3cf84e 100644 --- a/lib/node_modules/@stdlib/stats/strided/dcuminabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dcuminabs/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.js index 5c7b4f5b8b2f..a01bcf4dd6ba 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmax = require( './../lib/dmax.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.native.js index f57c74da06ec..ea20961c6900 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.ndarray.js index d31001141359..5bc79af1f3da 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmax = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.ndarray.native.js index 1ce174752847..6e4c4ebe2027 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmaxabs/benchmark/benchmark.js index 38e6c103bbb4..b7f9d15a4437 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmaxabs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmaxabs = require( './../lib/dmaxabs.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmaxabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmaxabs/benchmark/benchmark.native.js index 40caeae166b3..753dc47a52e3 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmaxabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmaxabs/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmaxabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmaxabs/benchmark/benchmark.ndarray.js index 2e30065724f7..46bc44a2f93c 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmaxabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmaxabs/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmaxabs = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmaxabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmaxabs/benchmark/benchmark.ndarray.native.js index 9917da0bd08f..c0ca67bbd34f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmaxabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmaxabs/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmaxabssorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/strided/dmaxabssorted/benchmark/c/benchmark.length.c index 8f2ffc2f8bc5..98bca32d4526 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmaxabssorted/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/strided/dmaxabssorted/benchmark/c/benchmark.length.c @@ -77,16 +77,6 @@ static double tic( void ) { return (double)now.tv_sec + (double)now.tv_usec/1.0e6; } -/** -* Generates a random number on the interval [0,1). -* -* @return random number -*/ -static double rand_double( void ) { - int r = rand(); - return (double)r / ( (double)RAND_MAX + 1.0 ); -} - /** * Runs a benchmark. * diff --git a/lib/node_modules/@stdlib/stats/strided/dmaxsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmaxsorted/benchmark/benchmark.js index 3ab42d500a65..cf95a6c7c5df 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmaxsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmaxsorted/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmaxsorted = require( './../lib/dmaxsorted.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmaxsorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmaxsorted/benchmark/benchmark.native.js index 6f05dc150e56..1b5fa0a30ed7 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmaxsorted/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmaxsorted/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmaxsorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmaxsorted/benchmark/benchmark.ndarray.js index d52befdeaacd..93672e43341e 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmaxsorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmaxsorted/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmaxsorted = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmaxsorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmaxsorted/benchmark/benchmark.ndarray.native.js index 42711fffbcfb..9a214ce0cd92 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmaxsorted/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmaxsorted/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmean/benchmark/benchmark.js index b0792a05cd87..550416906f59 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmean/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmean = require( './../lib/dmean.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmean/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmean/benchmark/benchmark.native.js index ab13d08fe1c2..5fa9157105a8 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmean/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmean/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmean/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmean/benchmark/benchmark.ndarray.js index c9b75ee8a703..af28d4114b9e 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmean/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmean/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmean = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmean/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmean/benchmark/benchmark.ndarray.native.js index 8cf2295f4273..38bdee134cfb 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmean/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmean/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeankbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmeankbn/benchmark/benchmark.js index f409d563f887..4e66c43cf807 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeankbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeankbn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeankbn = require( './../lib/dmeankbn.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeankbn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmeankbn/benchmark/benchmark.native.js index b30579748cd6..138ba3b7f580 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeankbn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeankbn/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeankbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmeankbn/benchmark/benchmark.ndarray.js index 524adb1ec7df..6ed22289493b 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeankbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeankbn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeankbn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeankbn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmeankbn/benchmark/benchmark.ndarray.native.js index 0132938e5295..bea793e9eef3 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeankbn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeankbn/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeankbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmeankbn2/benchmark/benchmark.js index 1e9a59db92a9..e3dd4fb8aa6c 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeankbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeankbn2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeankbn2 = require( './../lib/dmeankbn2.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeankbn2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmeankbn2/benchmark/benchmark.native.js index a0710f0a23f2..5756da39b8ac 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeankbn2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeankbn2/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeankbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmeankbn2/benchmark/benchmark.ndarray.js index f17f1a6faace..887b5be83965 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeankbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeankbn2/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeankbn2 = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeankbn2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmeankbn2/benchmark/benchmark.ndarray.native.js index c738a9b2aa5e..728f3a2074e9 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeankbn2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeankbn2/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanli/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmeanli/benchmark/benchmark.js index c10706fc2fc4..8485ee024525 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanli/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanli/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanli = require( './../lib/dmeanli.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanli/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanli/benchmark/benchmark.native.js index 4002fc1c3dbd..22c7e71bea46 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanli/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanli/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanli/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmeanli/benchmark/benchmark.ndarray.js index 672249f49a57..4dc30bc7f79d 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanli/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanli/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanli = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanli/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanli/benchmark/benchmark.ndarray.native.js index 9b63fdf76ebd..cb15954c6adb 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanli/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanli/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanlipw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmeanlipw/benchmark/benchmark.js index 9ec7a7ef03fe..b09be2a78d49 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanlipw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanlipw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanlipw = require( './../lib/dmeanlipw.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanlipw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanlipw/benchmark/benchmark.native.js index c46f130599c0..f0446bd608c4 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanlipw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanlipw/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanlipw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmeanlipw/benchmark/benchmark.ndarray.js index 5a1621ad6c1a..b7c4474c160c 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanlipw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanlipw/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanlipw = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanlipw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanlipw/benchmark/benchmark.ndarray.native.js index 79ef416c9e90..e7b2b7bf52c5 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanlipw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanlipw/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmeanors/benchmark/benchmark.js index f2016d9fd6fb..92f71f35b218 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanors/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanors = require( './../lib/dmeanors.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanors/benchmark/benchmark.native.js index aadabf76a811..e104ef8d110b 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanors/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmeanors/benchmark/benchmark.ndarray.js index 6e78438b24aa..f03bfd3bfa88 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanors/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanors = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanors/benchmark/benchmark.ndarray.native.js index b889f8af00a7..967f0cdaad7f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanors/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmeanpn/benchmark/benchmark.js index e700408206a3..5a0a1f391193 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanpn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanpn = require( './../lib/dmeanpn.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanpn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanpn/benchmark/benchmark.native.js index 03a329dc5861..553a546d79d0 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanpn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanpn/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmeanpn/benchmark/benchmark.ndarray.js index f7cd3ccc9450..ca47b6918f88 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanpn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanpn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanpn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanpn/benchmark/benchmark.ndarray.native.js index 43d475655431..fac5e74d809f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanpn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanpn/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmeanpw/benchmark/benchmark.js index e1bf5a0610a4..6ae7eed0a111 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanpw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanpw = require( './../lib/dmeanpw.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanpw/benchmark/benchmark.native.js index 6a62adf24bb5..2950f77fe70e 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanpw/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmeanpw/benchmark/benchmark.ndarray.js index 54782ce4cccf..4c3e7f91a559 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanpw/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanpw = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanpw/benchmark/benchmark.ndarray.native.js index 871d692be509..f07f8d10f058 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanpw/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmeanstdev/benchmark/benchmark.js index 03911778c1c0..c167e231fed4 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanstdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanstdev/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanstdev = require( './../lib/dmeanstdev.js' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanstdev/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanstdev/benchmark/benchmark.native.js index 050ee46f03a6..2fcb13c8c940 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanstdev/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanstdev/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanstdev/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmeanstdev/benchmark/benchmark.ndarray.js index 091fc321facd..3df68eaeb103 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanstdev/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanstdev/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanstdev = require( './../lib/ndarray.js' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanstdev/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanstdev/benchmark/benchmark.ndarray.native.js index f729be1b44b5..0696b89a8c40 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanstdev/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanstdev/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanstdevpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmeanstdevpn/benchmark/benchmark.js index f61f6e6a3737..54797ba6282f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanstdevpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanstdevpn/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanstdevpn = require( './../lib/dmeanstdevpn.js' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanstdevpn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanstdevpn/benchmark/benchmark.native.js index 6ddec61b8aa0..250bae0af480 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanstdevpn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanstdevpn/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanstdevpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmeanstdevpn/benchmark/benchmark.ndarray.js index 3d5e4943383f..0728b4ec2512 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanstdevpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanstdevpn/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanstdevpn = require( './../lib/ndarray.js' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanstdevpn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanstdevpn/benchmark/benchmark.ndarray.native.js index 14b581423992..b0287a22a7d5 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanstdevpn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanstdevpn/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvar/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmeanvar/benchmark/benchmark.js index cfe98892c71b..06be2d29fec2 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanvar/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanvar/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanvar = require( './../lib/dmeanvar.js' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvar/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanvar/benchmark/benchmark.native.js index 5b72f40cf185..c559f6d143c8 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanvar/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanvar/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvar/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmeanvar/benchmark/benchmark.ndarray.js index 87e0ae72a574..f0295545bd71 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanvar/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanvar/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanvar = require( './../lib/ndarray.js' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvar/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanvar/benchmark/benchmark.ndarray.native.js index 0e980de8fd1a..4f9e4d478d2a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanvar/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanvar/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -104,7 +105,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/README.md b/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/README.md index 0d09eb408095..676f1d46c23f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/README.md +++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/README.md @@ -258,7 +258,7 @@ Computes the [mean][arithmetic-mean] and [variance][variance] of a double-precis ```c const double x[] = { 1.0, -2.0, 2.0 }; -double out[] = { 0.0, 0.0 } +double out[] = { 0.0, 0.0 }; stdlib_strided_dmeanvarpn( 3, 1.0, x, 1, out, 1 ); ``` @@ -282,7 +282,7 @@ Computes the [mean][arithmetic-mean] and [variance][variance] of a double-precis ```c const double x[] = { 1.0, -2.0, 2.0 }; -double out[] = { 0.0, 0.0 } +double out[] = { 0.0, 0.0 }; stdlib_strided_dmeanvarpn_ndarray( 3, 1.0, x, 1, 0, out, 1, 0 ); ``` diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/benchmark/benchmark.js index 3b8d1960e678..8ad670985847 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanvarpn = require( './../lib/dmeanvarpn.js' ); @@ -96,7 +97,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/benchmark/benchmark.native.js index cf1741d4806d..4f2020349ced 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/benchmark/benchmark.ndarray.js index 58464583543c..08262ff8e2d5 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanvarpn = require( './../lib/ndarray.js' ); @@ -96,7 +97,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/benchmark/benchmark.ndarray.native.js index 2c875e28a39b..38f78d5b1e8c 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanvarpn/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmeanwd/benchmark/benchmark.js index b5f099d0ed7c..e0bb3afe8071 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanwd/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanwd = require( './../lib/dmeanwd.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanwd/benchmark/benchmark.native.js index 77f050e5833e..3029f6ae8899 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanwd/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmeanwd/benchmark/benchmark.ndarray.js index b7aa85320097..7e4923905fb1 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanwd/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanwd = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmeanwd/benchmark/benchmark.ndarray.native.js index 5145a9b3c0a7..ef69938cb2dc 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmeanwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmeanwd/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.js index 000e22a9d7d2..885fa2384691 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmediansorted = require( './../lib/dmediansorted.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.native.js index 77e399cd939f..aa83478e641a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.ndarray.js index 6e390e9d0638..33d2666599ff 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmediansorted = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.ndarray.native.js index cd7dbb1395e2..326b33df3208 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmidrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmidrange/benchmark/benchmark.js index 2f5751bb0b7b..b073000b30c2 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmidrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmidrange/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmidrange = require( './../lib/dmidrange.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmidrange/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmidrange/benchmark/benchmark.native.js index 67145969bb55..e823c5096afe 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmidrange/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmidrange/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmidrange/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmidrange/benchmark/benchmark.ndarray.js index 08be56762cb1..df4f0ee5a011 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmidrange/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmidrange/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmidrange = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmidrange/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmidrange/benchmark/benchmark.ndarray.native.js index 82654fb14dc0..5a5ccc3d6ca0 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmidrange/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmidrange/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmin/benchmark/benchmark.js index 1e9064022bfe..9014f63263f5 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmin/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmin = require( './../lib/dmin.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmin/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmin/benchmark/benchmark.native.js index 69bb7ce33c15..d9c79649c92b 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmin/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmin/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmin/benchmark/benchmark.ndarray.js index 16a5b5606403..68ec3d442c79 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmin/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmin = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmin/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmin/benchmark/benchmark.ndarray.native.js index 031affb2da3e..3075c6d620d3 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmin/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmin/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dminabs/benchmark/benchmark.js index e6d82af43ef8..7aed0e9017e1 100644 --- a/lib/node_modules/@stdlib/stats/strided/dminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dminabs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dminabs = require( './../lib/dminabs.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dminabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dminabs/benchmark/benchmark.native.js index 2fd6c15eef4e..f0bd348b1eea 100644 --- a/lib/node_modules/@stdlib/stats/strided/dminabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dminabs/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dminabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dminabs/benchmark/benchmark.ndarray.js index ef5fe67afda3..e2661844585d 100644 --- a/lib/node_modules/@stdlib/stats/strided/dminabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dminabs/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dminabs = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dminabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dminabs/benchmark/benchmark.ndarray.native.js index cec54c8abe54..26554f4586ce 100644 --- a/lib/node_modules/@stdlib/stats/strided/dminabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dminabs/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dminsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dminsorted/benchmark/benchmark.js index 8ade116f8196..a5fc1bb60a2e 100644 --- a/lib/node_modules/@stdlib/stats/strided/dminsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dminsorted/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dminsorted = require( './../lib/dminsorted.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dminsorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dminsorted/benchmark/benchmark.native.js index 5d263bbba817..b47addbe3909 100644 --- a/lib/node_modules/@stdlib/stats/strided/dminsorted/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dminsorted/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dminsorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dminsorted/benchmark/benchmark.ndarray.js index ca4b8a795349..7e0fdd83a5fd 100644 --- a/lib/node_modules/@stdlib/stats/strided/dminsorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dminsorted/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dminsorted = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dminsorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dminsorted/benchmark/benchmark.ndarray.native.js index 2193e74a29cf..fe9c23b6378a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dminsorted/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dminsorted/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dmskmin/README.md b/lib/node_modules/@stdlib/stats/strided/dmskmin/README.md index fbda72df9aff..66e7c4ec9f51 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmskmin/README.md +++ b/lib/node_modules/@stdlib/stats/strided/dmskmin/README.md @@ -232,7 +232,7 @@ Computes the minimum value of a double-precision floating-point strided array ac const double x[] = { 1.0, -2.0, 2.0 }; const uint8_t mask[] = { 0, 1, 0 }; -double v = stdlib_strided_dmskmin( 3, x, 1, 0, mask, 1, 0 ); +double v = stdlib_strided_dmskmin_ndarray( 3, x, 1, 0, mask, 1, 0 ); // returns 1.0 ``` diff --git a/lib/node_modules/@stdlib/stats/strided/dmskrange/README.md b/lib/node_modules/@stdlib/stats/strided/dmskrange/README.md index a0717741a784..c4335b39d249 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmskrange/README.md +++ b/lib/node_modules/@stdlib/stats/strided/dmskrange/README.md @@ -233,7 +233,7 @@ Computes the [range][range] of a double-precision floating-point strided array a const double x[] = { 1.0, -2.0, 2.0 }; const uint8_t mask[] = { 0, 1, 0 }; -double v = stdlib_strided_dmskrange( 3, x, 1, 0, mask, 1, 0 ); +double v = stdlib_strided_dmskrange_ndarray( 3, x, 1, 0, mask, 1, 0 ); // returns 1.0 ``` diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/README.md b/lib/node_modules/@stdlib/stats/strided/dnancount/README.md new file mode 100644 index 000000000000..ccd42eb69e1e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/README.md @@ -0,0 +1,290 @@ + + +# dnancount + +> Calculate the number of non-`NaN` elements in a double-precision floating-point strided array. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dnancount = require( '@stdlib/stats/strided/dnancount' ); +``` + +#### dnancount( N, x, strideX ) + +Computes the number of non-`NaN` elements in a double-precision floating-point strided array. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); + +var v = dnancount( x.length, x, 1 ); +// returns 3 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: input [`Float64Array`][@stdlib/array/float64]. +- **strideX**: stride length for `x`. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to count every other element in `x`, + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, NaN, -2.0, 4.0, 3.0, NaN, NaN ] ); + +var v = dnancount( 4, x, 2 ); +// returns 2 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x0 = new Float64Array( [ 2.0, 1.0, NaN, -2.0, 3.0, 4.0, NaN, NaN ] ); +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +var v = dnancount( 4, x1, 2 ); +// returns 3 +``` + +#### dnancount.ndarray( N, x, strideX, offsetX ) + +Computes the number of non-`NaN` elements in a double-precision floating-point strided array using alternative indexing semantics. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, NaN, NaN ] ); + +var v = dnancount.ndarray( 4, x, 2, 1 ); +// returns 3 +``` + +The function has the following additional parameter: + +- **offsetX**: starting index for `x`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to count every other element in `x` starting from the second element, + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 2.0, 1.0, NaN, -2.0, 3.0, 4.0, NaN, NaN ] ); + +var v = dnancount.ndarray( 4, x, 2, 1 ); +// returns 3 +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `0`. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var dnancount = require( '@stdlib/stats/strided/dnancount' ); + +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -50.0, 50.0 ); +} + +var x = filledarrayBy( 10, 'float64', rand ); +console.log( x ); + +var v = dnancount( x.length, x, 1 ); +console.log( v ); +``` + +
+ + + +* * * + +
+ +## C APIs + +
+ +
+ + + +
+ +### Usage + +```c +#include "stdlib/stats/strided/dnancount.h" +``` + +#### stdlib_strided_dnancount( N, \*X, strideX ) + +Computes the number of non-`NaN` elements in a double-precision floating-point strided array. + +```c +const double x[] = { 1.0, 2.0, NaN, 4.0, 5.0, 6.0, NaN, 8.0 }; + +int v = stdlib_strided_dnancount( 4, x, 2 ); +// returns 2 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +CBLAS_INT stdlib_strided_dnancount( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dnancount_ndarray( N, \*X, strideX, offsetX ) + +Computes the number of non-`NaN` elements in a double-precision floating-point strided array using alternative indexing semantics. + +```c +const double x[] = { 2.0, 1.0, NaN, -2.0, 3.0, 4.0, NaN, NaN }; + +int v = stdlib_strided_dnancount_ndarray( 4, x, 2, 1 ); +// returns 3 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +CBLAS_INT stdlib_strided_dnancount_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + +
+ +### Notes + +- If `N <= 0`, both functions return `0`. + +
+ + + +
+ +### Examples + +```c +#include "stdlib/stats/strided/dnancount.h" +#include +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 0.0/0.0, 0.0/0.0 }; + + // Specify the number of elements: + const int N = 5; + + // Specify the stride length: + const int strideX = 2; + + // Compute the number of non-NaN elements: + int v = stdlib_strided_dnancount( N, x, strideX ); + + // Print the result: + printf( "count: %d\n", v ); +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/benchmark.js new file mode 100644 index 000000000000..67efb2f15f10 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/benchmark.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var format = require( '@stdlib/string/format' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var pkg = require( './../package.json' ).name; +var dnancount = require( './../lib/dnancount.js' ); + + +// FUNCTIONS // + +/** +* Returns a random number. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = filledarrayBy( len, 'float64', rand ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = dnancount( x.length, x, 1 ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/benchmark.native.js new file mode 100644 index 000000000000..14f7125f5b54 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/benchmark.native.js @@ -0,0 +1,120 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var format = require( '@stdlib/string/format' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dnancount = tryRequire( resolve( __dirname, './../lib/dnancount.native.js' ) ); +var opts = { + 'skip': ( dnancount instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Returns a random number. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = filledarrayBy( len, 'float64', rand ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = dnancount( x.length, x, 1 ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..7e7c98217453 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/benchmark.ndarray.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var format = require( '@stdlib/string/format' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var pkg = require( './../package.json' ).name; +var dnancount = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Returns a random number. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = filledarrayBy( len, 'float64', rand ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = dnancount( x.length, x, 1, 0 ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..98d5a1a92595 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,120 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var format = require( '@stdlib/string/format' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dnancount = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dnancount instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Returns a random number. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = filledarrayBy( len, 'float64', rand ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = dnancount( x.length, x, 1, 0 ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..3f1bac6c0038 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/benchmark/c/benchmark.length.c @@ -0,0 +1,209 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dnancount.h" +#include +#include +#include +#include +#include + +#define NAME "dnancount" +#define ITERATIONS 1000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double *x; + double t; + int v; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + if ( rand_double() < 0.2 ) { + x[ i ] = 0.0 / 0.0; // NaN + } else { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dnancount( len, x, 1 ); + if ( v < 0 ) { + printf( "should return a non-negative integer\n" ); + break; + } + } + elapsed = tic() - t; + if ( v < 0 ) { + printf( "should return a non-negative integer\n" ); + } + free( x ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double *x; + double t; + int v; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + if ( rand_double() < 0.2 ) { + x[ i ] = 0.0 / 0.0; // NaN + } else { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dnancount_ndarray( len, x, 1, 0 ); + if ( v < 0 ) { + printf( "should return a non-negative integer\n" ); + break; + } + } + elapsed = tic() - t; + if ( v < 0 ) { + printf( "should return a non-negative integer\n" ); + } + free( x ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/binding.gyp b/lib/node_modules/@stdlib/stats/strided/dnancount/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/dnancount/docs/repl.txt new file mode 100644 index 000000000000..eee1c28d4c40 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/docs/repl.txt @@ -0,0 +1,89 @@ + +{{alias}}( N, x, strideX ) + Computes the number of non-`NaN` elements in a double-precision floating- + point strided array. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `0`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float64Array + Input array. + + strideX: integer + Stride length. + + Returns + ------- + out: integer + Number of non-`NaN` elements. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, NaN, 2.0 ] ); + > {{alias}}( x.length, x, 1 ) + 3 + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, NaN, -5.0, 2.0, -1.0, NaN ] ); + > {{alias}}( 3, x, 2 ) + 2 + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, NaN, 5.0, -1.0, NaN ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 3, x1, 2 ) + 2 + + +{{alias}}.ndarray( N, x, strideX, offsetX ) + Computes the number of non-`NaN` elements in a double-precision floating- + point strided array using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float64Array + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + out: integer + Number of non-`NaN` elements. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, NaN, 2.0 ] ); + > {{alias}}.ndarray( x.length, x, 1, 0 ) + 3 + + // Using offset parameter: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, NaN, 5.0, -1.0, NaN ] ); + > {{alias}}.ndarray( 3, x, 2, 1 ) + 2 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/strided/dnancount/docs/types/index.d.ts new file mode 100644 index 000000000000..ed5b0e280402 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/docs/types/index.d.ts @@ -0,0 +1,92 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `dnancount`. +*/ +interface Routine { + /** + * Computes the number of non-`NaN` elements in a double-precision floating-point strided array. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length + * @returns number of non-`NaN` elements + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); + * + * var v = dnancount( x.length, x, 1 ); + * // returns 3 + */ + ( N: number, x: Float64Array, strideX: number ): number; + + /** + * Computes the number of non-`NaN` elements in a double-precision floating-point strided array using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns number of non-`NaN` elements + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); + * + * var v = dnancount.ndarray( x.length, x, 1, 0 ); + * // returns 3 + */ + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; +} + +/** +* Computes the number of non-`NaN` elements in a double-precision floating-point strided array. +* +* @param N - number of indexed elements +* @param x - input array +* @param strideX - stride length +* @returns number of non-`NaN` elements +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); +* +* var v = dnancount( x.length, x, 1 ); +* // returns 3 +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); +* +* var v = dnancount.ndarray( x.length, x, 1, 0 ); +* // returns 3 +*/ +declare var dnancount: Routine; + + +// EXPORTS // + +export = dnancount; diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/docs/types/test.ts b/lib/node_modules/@stdlib/stats/strided/dnancount/docs/types/test.ts new file mode 100644 index 000000000000..b86afcce0b23 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/docs/types/test.ts @@ -0,0 +1,157 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import dnancount = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = new Float64Array( 10 ); + + dnancount( x.length, x, 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dnancount( '10', x, 1 ); // $ExpectError + dnancount( true, x, 1 ); // $ExpectError + dnancount( false, x, 1 ); // $ExpectError + dnancount( null, x, 1 ); // $ExpectError + dnancount( undefined, x, 1 ); // $ExpectError + dnancount( [], x, 1 ); // $ExpectError + dnancount( {}, x, 1 ); // $ExpectError + dnancount( ( x: number ): number => x, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dnancount( x.length, 10, 1 ); // $ExpectError + dnancount( x.length, '10', 1 ); // $ExpectError + dnancount( x.length, true, 1 ); // $ExpectError + dnancount( x.length, false, 1 ); // $ExpectError + dnancount( x.length, null, 1 ); // $ExpectError + dnancount( x.length, undefined, 1 ); // $ExpectError + dnancount( x.length, [], 1 ); // $ExpectError + dnancount( x.length, {}, 1 ); // $ExpectError + dnancount( x.length, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dnancount( x.length, x, '10' ); // $ExpectError + dnancount( x.length, x, true ); // $ExpectError + dnancount( x.length, x, false ); // $ExpectError + dnancount( x.length, x, null ); // $ExpectError + dnancount( x.length, x, undefined ); // $ExpectError + dnancount( x.length, x, [] ); // $ExpectError + dnancount( x.length, x, {} ); // $ExpectError + dnancount( x.length, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + dnancount(); // $ExpectError + dnancount( x.length ); // $ExpectError + dnancount( x.length, x ); // $ExpectError + dnancount( x.length, x, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + const x = new Float64Array( 10 ); + + dnancount.ndarray( x.length, x, 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dnancount.ndarray( '10', x, 1, 0 ); // $ExpectError + dnancount.ndarray( true, x, 1, 0 ); // $ExpectError + dnancount.ndarray( false, x, 1, 0 ); // $ExpectError + dnancount.ndarray( null, x, 1, 0 ); // $ExpectError + dnancount.ndarray( undefined, x, 1, 0 ); // $ExpectError + dnancount.ndarray( [], x, 1, 0 ); // $ExpectError + dnancount.ndarray( {}, x, 1, 0 ); // $ExpectError + dnancount.ndarray( ( x: number ): number => x, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dnancount.ndarray( x.length, 10, 1, 0 ); // $ExpectError + dnancount.ndarray( x.length, '10', 1, 0 ); // $ExpectError + dnancount.ndarray( x.length, true, 1, 0 ); // $ExpectError + dnancount.ndarray( x.length, false, 1, 0 ); // $ExpectError + dnancount.ndarray( x.length, null, 1, 0 ); // $ExpectError + dnancount.ndarray( x.length, undefined, 1, 0 ); // $ExpectError + dnancount.ndarray( x.length, [], 1, 0 ); // $ExpectError + dnancount.ndarray( x.length, {}, 1, 0 ); // $ExpectError + dnancount.ndarray( x.length, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dnancount.ndarray( x.length, x, '10', 0 ); // $ExpectError + dnancount.ndarray( x.length, x, true, 0 ); // $ExpectError + dnancount.ndarray( x.length, x, false, 0 ); // $ExpectError + dnancount.ndarray( x.length, x, null, 0 ); // $ExpectError + dnancount.ndarray( x.length, x, undefined, 0 ); // $ExpectError + dnancount.ndarray( x.length, x, [], 0 ); // $ExpectError + dnancount.ndarray( x.length, x, {}, 0 ); // $ExpectError + dnancount.ndarray( x.length, x, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dnancount.ndarray( x.length, x, 1, '10' ); // $ExpectError + dnancount.ndarray( x.length, x, 1, true ); // $ExpectError + dnancount.ndarray( x.length, x, 1, false ); // $ExpectError + dnancount.ndarray( x.length, x, 1, null ); // $ExpectError + dnancount.ndarray( x.length, x, 1, undefined ); // $ExpectError + dnancount.ndarray( x.length, x, 1, [] ); // $ExpectError + dnancount.ndarray( x.length, x, 1, {} ); // $ExpectError + dnancount.ndarray( x.length, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + dnancount.ndarray(); // $ExpectError + dnancount.ndarray( x.length ); // $ExpectError + dnancount.ndarray( x.length, x ); // $ExpectError + dnancount.ndarray( x.length, x, 1 ); // $ExpectError + dnancount.ndarray( x.length, x, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/examples/c/Makefile b/lib/node_modules/@stdlib/stats/strided/dnancount/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/examples/c/example.c b/lib/node_modules/@stdlib/stats/strided/dnancount/examples/c/example.c new file mode 100644 index 000000000000..b1e97d101b33 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/examples/c/example.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dnancount.h" +#include +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 0.0/0.0, 0.0/0.0 }; + + // Specify the number of elements: + const int N = 5; + + // Specify the stride length: + const int strideX = 2; + + // Compute the number of non-NaN elements: + int v = stdlib_strided_dnancount( N, x, strideX ); + + // Print the result: + printf( "count: %d\n", v ); +} diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/examples/index.js b/lib/node_modules/@stdlib/stats/strided/dnancount/examples/index.js new file mode 100644 index 000000000000..77927d4c0f87 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var dnancount = require( './../lib' ); + +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -50.0, 50.0 ); +} + +var x = filledarrayBy( 10, 'float64', rand ); +console.log( x ); + +var v = dnancount( x.length, x, 1 ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/include.gypi b/lib/node_modules/@stdlib/stats/strided/dnancount/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "count", + "nancount", + "non-nan", + "nan", + "strided", + "strided array", + "typed", + "array", + "float64", + "double", + "float64array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/src/Makefile b/lib/node_modules/@stdlib/stats/strided/dnancount/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/src/addon.c b/lib/node_modules/@stdlib/stats/strided/dnancount/src/addon.c new file mode 100644 index 000000000000..94e55ff1ace3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/src/addon.c @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dnancount.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include "stdlib/napi/create_int32.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_INT32( env, API_SUFFIX(stdlib_strided_dnancount)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_INT32( env, API_SUFFIX(stdlib_strided_dnancount_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/src/main.c b/lib/node_modules/@stdlib/stats/strided/dnancount/src/main.c new file mode 100644 index 000000000000..60a2697417de --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/src/main.c @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dnancount.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the number of non-`NaN` elements in a double-precision floating-point strided array. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return number of non-`NaN` elements +*/ +CBLAS_INT API_SUFFIX(stdlib_strided_dnancount)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dnancount_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the number of non-`NaN` elements in a double-precision floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return number of non-`NaN` elements +*/ +CBLAS_INT API_SUFFIX(stdlib_strided_dnancount_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT count; + CBLAS_INT ix; + CBLAS_INT i; + + if ( N <= 0 ) { + return 0; + } + count = 0; + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( !stdlib_base_is_nan( X[ ix ] ) ) { + count += 1; + } + ix += strideX; + } + return count; +} diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/test/test.dnancount.js b/lib/node_modules/@stdlib/stats/strided/dnancount/test/test.dnancount.js new file mode 100644 index 000000000000..64722e97f234 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/test/test.dnancount.js @@ -0,0 +1,171 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dnancount = require( './../lib/dnancount.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dnancount, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 3', function test( t ) { + t.strictEqual( dnancount.length, 3, 'has expected arity' ); + t.end(); +}); + +tape( 'the function counts the number of non-NaN elements in a strided array', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, NaN, 5.0, 0.0, 3.0 ] ); + v = dnancount( x.length, x, 1 ); + t.strictEqual( v, 6, 'returns expected value' ); + + x = new Float64Array( [ NaN ] ); + v = dnancount( x.length, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + v = dnancount( x.length, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = dnancount( 0, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + v = dnancount( -1, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function counts the first element', function test( t ) { + var x; + var v; + + x = new Float64Array( [ NaN, -2.0, -4.0, 5.0, 3.0 ] ); + + v = dnancount( 1, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + x[ 0 ] = 1.0; + v = dnancount( 1, x, 1 ); + t.strictEqual( v, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]); + + v = dnancount( 5, x, 2 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter', function test( t ) { + var x; + var v; + + x = new Float64Array([ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = dnancount( 5, x, -2 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function counts repeated indexed elements', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = dnancount( x.length, x, 0 ); + t.strictEqual( v, x.length, 'returns expected value' ); + + x[ 0 ] = NaN; + v = dnancount( x.length, x, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var x0; + var x1; + var v; + + x0 = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + 6.0, + NaN, // 4 + NaN + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + v = dnancount( 5, x1, 2 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/test/test.dnancount.native.js b/lib/node_modules/@stdlib/stats/strided/dnancount/test/test.dnancount.native.js new file mode 100644 index 000000000000..a777a096f4c9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/test/test.dnancount.native.js @@ -0,0 +1,260 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dnancount = tryRequire( resolve( __dirname, './../lib/dnancount.native.js' ) ); +var opts = { + 'skip': ( dnancount instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dnancount, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 3', opts, function test( t ) { + t.strictEqual( dnancount.length, 3, 'has expected arity' ); + t.end(); +}); + +tape( 'the function throws an error if provided a first argument which is not a number', opts, function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + dnancount( value, new Float64Array( 10 ), 1 ); + }; + } +}); + +tape( 'the function throws an error if provided a second argument which is not a Float64Array', opts, function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + dnancount( 10, value, 1 ); + }; + } +}); + +tape( 'the function throws an error if provided a third argument which is not a number', opts, function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + dnancount( 10, new Float64Array( 10 ), value ); + }; + } +}); + +tape( 'the function counts the number of non-NaN elements in a strided array', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, NaN, 5.0, 0.0, 3.0 ] ); + v = dnancount( x.length, x, 1 ); + t.strictEqual( v, 6, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + v = dnancount( x.length, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = dnancount( 0, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + v = dnancount( -1, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function counts the first element', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ NaN, -2.0, -4.0, 5.0, 3.0 ] ); + + v = dnancount( 1, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + x[ 0 ] = 1.0; + v = dnancount( 1, x, 1 ); + t.strictEqual( v, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]); + + v = dnancount( 5, x, 2 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = dnancount( 5, x, -2 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function counts repeated indexed elements', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = dnancount( x.length, x, 0 ); + t.strictEqual( v, x.length, 'returns expected value' ); + + x[ 0 ] = NaN; + v = dnancount( x.length, x, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var x0; + var x1; + var v; + + x0 = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + 6.0, + NaN, // 4 + NaN + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + + v = dnancount( 5, x1, 2 ); + t.strictEqual( v, 4, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/test/test.js b/lib/node_modules/@stdlib/stats/strided/dnancount/test/test.js new file mode 100644 index 000000000000..487fe10a21f5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var dnancount = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dnancount, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof dnancount.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var dnancount = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dnancount, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var dnancount; + var main; + + main = require( './../lib/dnancount.js' ); + + dnancount = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dnancount, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnancount/test/test.ndarray.js new file mode 100644 index 000000000000..72712671752e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/test/test.ndarray.js @@ -0,0 +1,148 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dnancount = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dnancount, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', function test( t ) { + t.strictEqual( dnancount.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function counts the number of non-NaN elements in a strided array', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, NaN, 5.0, 0.0, 3.0 ] ); + + v = dnancount( x.length, x, 1, 0 ); + t.strictEqual( v, 6, 'returns expected value' ); + + v = dnancount( 1, x, 1, 3 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = dnancount( 0, x, 1, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + + v = dnancount( -1, x, 1, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]); + + v = dnancount( 5, x, 2, 0 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter', function test( t ) { + var x; + var v; + + x = new Float64Array([ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = dnancount( 5, x, -2, 8 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function counts repeated indexed elements', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = dnancount( x.length, x, 0, 0 ); + t.strictEqual( v, x.length, 'returns expected value' ); + + x[ 0 ] = NaN; + v = dnancount( x.length, x, 0, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `offset` parameter', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + NaN, + NaN // 4 + ]); + + v = dnancount( 5, x, 2, 1 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/dnancount/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnancount/test/test.ndarray.native.js new file mode 100644 index 000000000000..e5e16ea89d6b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnancount/test/test.ndarray.native.js @@ -0,0 +1,173 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dnancount = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dnancount instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dnancount, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', opts, function test( t ) { + t.strictEqual( dnancount.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function counts the number of non-NaN elements in a strided array', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, NaN, 5.0, 0.0, 3.0 ] ); + + v = dnancount( x.length, x, 1, 0 ); + t.strictEqual( v, 6, 'returns expected value' ); + + v = dnancount( 1, x, 1, 3 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = dnancount( 0, x, 1, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + + v = dnancount( -1, x, 1, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function counts the first indexed element', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ NaN, -2.0, -4.0, 5.0, 3.0 ] ); + + v = dnancount( 1, x, 1, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + + x[ 0 ] = 1.0; + v = dnancount( 1, x, 1, 0 ); + t.strictEqual( v, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]); + + v = dnancount( 5, x, 2, 0 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = dnancount( 5, x, -2, 8 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function counts repeated indexed elements', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = dnancount( x.length, x, 0, 0 ); + t.strictEqual( v, x.length, 'returns expected value' ); + + x[ 0 ] = NaN; + v = dnancount( x.length, x, 0, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `offset` parameter', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + NaN, + NaN // 4 + ]); + + v = dnancount( 5, x, 2, 1 ); + t.strictEqual( v, 4, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmaxabs/README.md b/lib/node_modules/@stdlib/stats/strided/dnanmaxabs/README.md index f16b9bb81c3f..5d0f47127aad 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmaxabs/README.md +++ b/lib/node_modules/@stdlib/stats/strided/dnanmaxabs/README.md @@ -178,17 +178,17 @@ console.log( v ); ### Usage ```c -#include "stdlib/stats/strided/dnanmax.h" +#include "stdlib/stats/strided/dnanmaxabs.h" ``` -#### stdlib_strided_dnanmax( N, \*X, strideX ) +#### stdlib_strided_dnanmaxabs( N, \*X, strideX ) Computes the maximum absolute value of a double-precision floating-point strided array, ignoring `NaN` values. ```c const double x[] = { 1.0, -2.0, 0.0 / 0.0, -4.0 }; -double v = stdlib_strided_dnanmax( 4, x, 1 ); +double v = stdlib_strided_dnanmaxabs( 4, x, 1 ); // returns 4.0 ``` @@ -199,17 +199,17 @@ The function accepts the following arguments: - **strideX**: `[in] CBLAS_INT` stride length for `X`. ```c -double stdlib_strided_dnanmax( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +double stdlib_strided_dnanmaxabs( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); ``` -#### stdlib_strided_dnanmax_ndarray( N, \*X, strideX, offsetX ) +#### stdlib_strided_dnanmaxabs_ndarray( N, \*X, strideX, offsetX ) Computes the maximum absolute value of a double-precision floating-point strided array, ignoring `NaN` values and using alternative indexing semantics. ```c const double x[] = { 1.0, -2.0, 0.0 / 0.0, -4.0 }; -double v = stdlib_strided_dnanmax_ndarray( 4, x, 1, 0 ); +double v = stdlib_strided_dnanmaxabs_ndarray( 4, x, 1, 0 ); // returns 4.0 ``` @@ -221,7 +221,7 @@ The function accepts the following arguments: - **offsetX**: `[in] CBLAS_INT` starting index for `X`. ```c -double stdlib_strided_dnanmax_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +double stdlib_strided_dnanmaxabs_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); ``` diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/README.md b/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/README.md index 3688ad47ab3a..997197290e7d 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/README.md +++ b/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/README.md @@ -229,7 +229,7 @@ Computes the aithmetic mean of a double-precision floating-point strided array, ```c const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 }; -double v = stdlib_strided_dnanmeanpn( 6, x, 2, 0 ); +double v = stdlib_strided_dnanmeanpn_ndarray( 6, x, 2, 0 ); // returns ~4.6667 ``` diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/benchmark/benchmark.js index bfb2be481148..d25ffa941635 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmeanpn = require( './../lib/dnanmeanpn.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/benchmark/benchmark.native.js index bbdaa07d6369..b04a1a448028 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/benchmark/benchmark.ndarray.js index 550891ab7ad4..c92fc57031f3 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmeanpn = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/benchmark/benchmark.ndarray.native.js index 9a8eceb4944a..9818551948c2 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmeanpn/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmeanpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanmeanpw/benchmark/benchmark.js index 05a47425d996..5cd085b7872c 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmeanpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmeanpw/benchmark/benchmark.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmeanpw = require( './../lib/dnanmeanpw.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmeanpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanmeanpw/benchmark/benchmark.native.js index 402b63c40a09..10cb9ba7d22b 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmeanpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmeanpw/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmeanpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanmeanpw/benchmark/benchmark.ndarray.js index 51067865bc87..3005c299255a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmeanpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmeanpw/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmeanpw = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmeanpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanmeanpw/benchmark/benchmark.ndarray.native.js index 0f71b361295b..c6af013620ad 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmeanpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmeanpw/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanmeanwd/benchmark/benchmark.js index 4d8cb5816b7f..50f281358c1a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmeanwd/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmeanwd = require( './../lib/dnanmeanwd.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmeanwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanmeanwd/benchmark/benchmark.native.js index c905e52c5253..42e772b89db1 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmeanwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmeanwd/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmeanwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanmeanwd/benchmark/benchmark.ndarray.js index a43ad78f7966..31c65847ffb5 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmeanwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmeanwd/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmeanwd = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmeanwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanmeanwd/benchmark/benchmark.ndarray.native.js index f5a839358d10..ce9074e9b1f0 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmeanwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmeanwd/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmin/README.md b/lib/node_modules/@stdlib/stats/strided/dnanmin/README.md index ac9ad0041ad7..9c52529599ba 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmin/README.md +++ b/lib/node_modules/@stdlib/stats/strided/dnanmin/README.md @@ -189,7 +189,7 @@ Calculate the minimum value of a double-precision floating-point strided array, const double x[] = { 1.0, -2.0, 0.0 / 0.0, -4.0 }; double v = stdlib_strided_dnanmin( 4, x, 1 ); -// returns 1.0 +// returns -4.0 ``` The function accepts the following arguments: @@ -210,7 +210,7 @@ Computes the minimum value of a double-precision floating-point strided array, i const double x[] = { 1.0, -2.0, 0.0 / 0.0, -4.0 }; double v = stdlib_strided_dnanmin_ndarray( 4, x, 1, 0 ); -// returns 1.0 +// returns -4.0 ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanmin/benchmark/benchmark.js index aee3334b2f58..5770ebfb844e 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmin = require( './../lib/dnanmin.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmin/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanmin/benchmark/benchmark.native.js index fde007459f91..e91a0e7497c5 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmin/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmin/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanmin/benchmark/benchmark.ndarray.js index 4819c0dc4338..af487732713e 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmin/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmin = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmin/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanmin/benchmark/benchmark.ndarray.native.js index 7ff0ab67d014..aa5e2ce9f7ef 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmin/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmin/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanminabs/benchmark/benchmark.js index a58830833ff4..b0f9d1da9900 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanminabs/benchmark/benchmark.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanminabs = require( './../lib/dnanminabs.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanminabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanminabs/benchmark/benchmark.native.js index b3f5aed832a1..a43830e8bb03 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanminabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanminabs/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanminabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanminabs/benchmark/benchmark.ndarray.js index 5342097a248a..4f1be2b8e80c 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanminabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanminabs/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanminabs = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanminabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanminabs/benchmark/benchmark.ndarray.native.js index a9ab25f1f947..04433000a504 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanminabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanminabs/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmskmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanmskmax/benchmark/benchmark.js index e65029094340..169666782097 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmskmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmskmax/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmskmax = require( './../lib/dnanmskmax.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmskmax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanmskmax/benchmark/benchmark.native.js index 412e06e3a9d3..f46e6e27e973 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmskmax/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmskmax/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmskmax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanmskmax/benchmark/benchmark.ndarray.js index 4eba25725bd5..14ac372173f4 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmskmax/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmskmax/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmskmax = require( './../lib/ndarray.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmskmax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanmskmax/benchmark/benchmark.ndarray.native.js index 19364422adbf..95a6c8cb401f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmskmax/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmskmax/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmskmidrange/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanmskmidrange/benchmark/benchmark.ndarray.js index 638ec1dfcc7f..962cf8b86a15 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmskmidrange/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmskmidrange/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmskmidrange = require( './../lib/ndarray.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmskmidrange/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanmskmidrange/benchmark/benchmark.ndarray.native.js index bfd548b6c514..77abf06a26cb 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmskmidrange/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmskmidrange/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanmskmin/benchmark/benchmark.js index 761483773fd3..ed3cf27baeb6 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmskmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmskmin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmskmin = require( './../lib/dnanmskmin.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmskmin/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanmskmin/benchmark/benchmark.native.js index 94f23213df4a..e33f3cb3511f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmskmin/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmskmin/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmskmin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanmskmin/benchmark/benchmark.ndarray.js index 1c7b105e96ce..01d88c5a2c6a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmskmin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmskmin/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmskmin = require( './../lib/ndarray.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmskmin/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanmskmin/benchmark/benchmark.ndarray.native.js index 91684b9903ec..db70bf31f20a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmskmin/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmskmin/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmskrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanmskrange/benchmark/benchmark.js index d53aa8bd6f05..d0ac80ad4b56 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmskrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmskrange/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmskrange = require( './../lib/dnanmskrange.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmskrange/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanmskrange/benchmark/benchmark.native.js index 09189f075fcb..c09c0609db39 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmskrange/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmskrange/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmskrange/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanmskrange/benchmark/benchmark.ndarray.js index 6e666250af71..3e40ef419711 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmskrange/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmskrange/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanmskrange = require( './../lib/ndarray.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanmskrange/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanmskrange/benchmark/benchmark.ndarray.native.js index 5519d9887b9a..ef7b1945a4a7 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanmskrange/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanmskrange/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanrange/benchmark/benchmark.js index aeaf6fdc675d..b5806df855b5 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanrange/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanrange = require( './../lib/dnanrange.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanrange/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanrange/benchmark/benchmark.native.js index 5a1da4757c9f..fd279f68922c 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanrange/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanrange/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanrange/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanrange/benchmark/benchmark.ndarray.js index 9257ce9574b0..535d33b875b2 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanrange/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanrange/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanrange = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanrange/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanrange/benchmark/benchmark.ndarray.native.js index ca3bfeb9d3b8..5433d439d5cf 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanrange/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanrange/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanstdev/benchmark/benchmark.js index b5d3c9ef9005..ee04b86a3cf2 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdev/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanstdev = require( './../lib/dnanstdev.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdev/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanstdev/benchmark/benchmark.native.js index 626ce32ca460..efeba0aca717 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdev/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdev/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdev/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanstdev/benchmark/benchmark.ndarray.js index 9e944afbce22..2c53271ca2de 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdev/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdev/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanstdev = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdev/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanstdev/benchmark/benchmark.ndarray.native.js index ed138b047740..4da9958c1324 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdev/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdev/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevch/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevch/benchmark/benchmark.js index 5e71a570fc65..9aa0af51d14a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevch/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevch/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanstdevch = require( './../lib/dnanstdevch.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevch/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevch/benchmark/benchmark.native.js index 2295e27e2b14..ffcfe5ba376e 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevch/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevch/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevch/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevch/benchmark/benchmark.ndarray.js index 5ac20ace1bb6..41990cad547a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevch/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevch/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanstdevch = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevch/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevch/benchmark/benchmark.ndarray.native.js index bbcbd6f522ec..69122d42024f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevch/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevch/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevpn/benchmark/benchmark.js index aa2e58a9118e..9852a9df7222 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevpn/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanstdevpn = require( './../lib/dnanstdevpn.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevpn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevpn/benchmark/benchmark.native.js index 86dab48263c0..193da4d32bfd 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevpn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevpn/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevpn/benchmark/benchmark.ndarray.js index f7aebff396aa..cd6d02e7b893 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevpn/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanstdevpn = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevpn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevpn/benchmark/benchmark.ndarray.native.js index 843ac2afd386..fbd7b5480cdf 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevpn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevpn/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevtk/benchmark/benchmark.js index 623d2fdeaf76..feabffd9d71b 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevtk/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanstdevtk = require( './../lib/dnanstdevtk.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevtk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevtk/benchmark/benchmark.native.js index 81857d56c8b9..e919161fff02 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevtk/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevtk/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevtk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevtk/benchmark/benchmark.ndarray.js index 812a3630b231..6a31ecaca271 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevtk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevtk/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanstdevtk = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevtk/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevtk/benchmark/benchmark.ndarray.native.js index 9bae4c20bc31..a46bd2ada9bc 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevtk/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevtk/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevwd/benchmark/benchmark.js index 0a738f0320c0..1ad66bd29f68 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevwd/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanstdevwd = require( './../lib/dnanstdevwd.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevwd/benchmark/benchmark.native.js index 25f1819ce6a8..9f79a489669b 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevwd/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevwd/benchmark/benchmark.ndarray.js index d30e776261e1..0787ed4339de 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevwd/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanstdevwd = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevwd/benchmark/benchmark.ndarray.native.js index 39644d7cd205..ce0780cd19df 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevwd/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevyc/benchmark/benchmark.js index cb4faf70428b..2965d90c1caf 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevyc/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanstdevyc = require( './../lib/dnanstdevyc.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevyc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevyc/benchmark/benchmark.native.js index 3e0c84e7cde3..627f946c2158 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevyc/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevyc/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevyc/benchmark/benchmark.ndarray.js index ce284dc82cb4..72e2dd9b7c6a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevyc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevyc/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanstdevyc = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanstdevyc/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanstdevyc/benchmark/benchmark.ndarray.native.js index 8d929c5c7ecc..81bc7aa21c3c 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanstdevyc/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanstdevyc/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanvariance/benchmark/benchmark.js index 80f94b9f8f9b..a154e07a35d7 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariance/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvariance = require( './../lib/dnanvariance.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariance/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvariance/benchmark/benchmark.native.js index e95ef9c1eb8f..49b85825d226 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariance/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariance/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariance/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanvariance/benchmark/benchmark.ndarray.js index 6c692c20638c..7bb4e176e2da 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariance/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariance/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvariance = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariance/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvariance/benchmark/benchmark.ndarray.native.js index 067e3a368b65..62b72b6f8ed5 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariance/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariance/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariancech/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanvariancech/benchmark/benchmark.js index 1d2f93c55537..adcdf654ebac 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariancech/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariancech/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvariancech = require( './../lib/dnanvariancech.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariancech/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvariancech/benchmark/benchmark.native.js index c0dba4947051..c307e8a33019 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariancech/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariancech/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariancech/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanvariancech/benchmark/benchmark.ndarray.js index 6e627cde0ff7..0a7e59550759 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariancech/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariancech/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvariancech = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariancech/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvariancech/benchmark/benchmark.ndarray.native.js index 9bbcb0d5d1ed..0edafabdc48f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariancech/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariancech/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariancepn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanvariancepn/benchmark/benchmark.js index 494bd04592a1..671b28b43e59 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariancepn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariancepn/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvariancepn = require( './../lib/dnanvariancepn.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariancepn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvariancepn/benchmark/benchmark.native.js index 18f2598d0704..2f52b22b4d95 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariancepn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariancepn/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariancepn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanvariancepn/benchmark/benchmark.ndarray.js index c453d1be6993..2a1bfa7d4832 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariancepn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariancepn/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvariancepn = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariancepn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvariancepn/benchmark/benchmark.ndarray.native.js index a865c69737cb..8e97d795a778 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariancepn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariancepn/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariancetk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanvariancetk/benchmark/benchmark.js index 8363e495d61a..bad37d1dc006 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariancetk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariancetk/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvariancetk = require( './../lib/dnanvariancetk.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariancetk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvariancetk/benchmark/benchmark.native.js index cb3513572da3..628e699b024d 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariancetk/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariancetk/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariancetk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanvariancetk/benchmark/benchmark.ndarray.js index b93b4a742a1b..da3c7322ccb8 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariancetk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariancetk/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvariancetk = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariancetk/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvariancetk/benchmark/benchmark.ndarray.native.js index 5141319cfcaf..9e98b3aed129 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariancetk/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariancetk/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariancewd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanvariancewd/benchmark/benchmark.js index 46378ece7a1a..20d897ffc942 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariancewd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariancewd/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvariancewd = require( './../lib/dnanvariancewd.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariancewd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvariancewd/benchmark/benchmark.native.js index ee236d25478b..0b1cfa42542a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariancewd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariancewd/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariancewd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanvariancewd/benchmark/benchmark.ndarray.js index 07eedcdd7be1..6e28517e9216 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariancewd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariancewd/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvariancewd = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvariancewd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvariancewd/benchmark/benchmark.ndarray.native.js index c91c86caa466..dcdab4fd89cf 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvariancewd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvariancewd/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarianceyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanvarianceyc/benchmark/benchmark.js index 460d9d001f7a..c7d8a45cbab4 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvarianceyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarianceyc/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvarianceyc = require( './../lib/dnanvarianceyc.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarianceyc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvarianceyc/benchmark/benchmark.native.js index 9c5d9d7ba9bd..ad2a4ef02ba2 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvarianceyc/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarianceyc/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarianceyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanvarianceyc/benchmark/benchmark.ndarray.js index 33895615a51a..dba285161e3b 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvarianceyc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarianceyc/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvarianceyc = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarianceyc/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvarianceyc/benchmark/benchmark.ndarray.native.js index 6472c7a5699e..7501645c0ec4 100644 --- a/lib/node_modules/@stdlib/stats/strided/dnanvarianceyc/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarianceyc/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/README.md b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/README.md new file mode 100644 index 000000000000..e2d56af557d3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/README.md @@ -0,0 +1,347 @@ + + +# dpcorrwd + +> Calculate the [sample Pearson product-moment correlation coefficient][pearson-correlation] of two double-precision floating-point strided arrays using Welford's algorithm. + +
+ +The [Pearson product-moment correlation coefficient][pearson-correlation] (also known as Pearson's _r_) between random variables `X` and `Y` is defined as + + + +```math +\rho_{X,Y} = \frac{\mathop{\mathrm{cov}}(X,Y)}{\sigma_X \sigma_Y} +``` + + + +where the numerator is the [covariance][covariance] and the denominator is the product of the respective standard deviations. + +For a sample of size `n`, the [sample Pearson product-moment correlation coefficient][pearson-correlation] is defined as + + + +```math +r_{xy} = \frac{\displaystyle\sum_{i=0}^{N-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{N-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{N-1} (y_i - \bar{y})^2}} +``` + + + +where `x_i` and `y_i` are the _ith_ components of vectors **X** and **Y**, respectively. + +
+ + + +
+ +## Usage + +```javascript +var dpcorrwd = require( '@stdlib/stats/strided/dpcorrwd' ); +``` + +#### dpcorrwd( N, x, strideX, y, strideY ) + +Computes the [sample Pearson product-moment correlation coefficient][pearson-correlation] of two double-precision floating-point strided arrays using Welford's algorithm. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +var y = new Float64Array( [ 2.0, -2.0, 1.0 ] ); + +var c = dpcorrwd( x.length, x, 1, y, 1 ); +// returns ~0.885 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: first input [`Float64Array`][@stdlib/array/float64]. +- **strideX**: stride length for `x`. +- **y**: second input [`Float64Array`][@stdlib/array/float64]. +- **strideY**: stride length for `y`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the [sample Pearson product-moment correlation coefficient][pearson-correlation] of every other element in `x` and `y`, + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); +var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] ); + +var c = dpcorrwd( 4, x, 2, y, 2 ); +// returns ~0.947 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var y0 = new Float64Array( [ 2.0, -2.0, 2.0, 1.0, -2.0, 4.0, 3.0, 2.0 ] ); + +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +var c = dpcorrwd( 4, x1, 2, y1, 2 ); +// returns ~0.307 +``` + +#### dpcorrwd.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + +Computes the [sample Pearson product-moment correlation coefficient][pearson-correlation] of two double-precision floating-point strided arrays using Welford's algorithm and alternative indexing semantics. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +var y = new Float64Array( [ 2.0, -2.0, 1.0 ] ); + +var c = dpcorrwd.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// returns ~0.885 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the [sample Pearson product-moment correlation coefficient][pearson-correlation] for every other element in `x` and `y` starting from the second element + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var y = new Float64Array( [ -7.0, 2.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] ); + +var c = dpcorrwd.ndarray( 4, x, 2, 1, y, 2, 1 ); +// returns ~0.927 +``` + +
+ + + +
+ +## Notes + +- If `N <= 1`, both functions return `NaN`. +- If all values in either `x` or `y` are constant, the [sample Pearson product-moment correlation coefficient][pearson-correlation] is not defined. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var dpcorrwd = require( '@stdlib/stats/strided/dpcorrwd' ); + +var opts = { + 'dtype': 'float64' +}; +var x = discreteUniform( 10, -50, 50, opts ); +console.log( x ); + +var y = discreteUniform( 10, -50, 50, opts ); +console.log( y ); + +var c = dpcorrwd( x.length, x, 1, y, 1 ); +console.log( c ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/strided/dpcorrwd.h" +``` + +#### stdlib_strided_dpcorrwd( N, \*X, strideX, \*Y, strideY ) + +Computes the [sample Pearson product-moment correlation coefficient][pearson-correlation] of two double-precision floating-point strided arrays using Welford's algorithm. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; +const double y[] = { 2.0, -2.0, 1.0 }; + +double c = stdlib_strided_dpcorrwd( 3, x, 1, y, 1 ); +// returns ~0.885 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` first input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[in] double*` second input array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +double stdlib_strided_dpcorrwd( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const double *Y, const CBLAS_INT strideY ); +``` + +#### stdlib_strided_dpcorrwd_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + +Computes the [sample Pearson product-moment correlation coefficient][pearson-correlation] of two double-precision floating-point strided arrays using Welford's algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; +const double y[] = { 2.0, -2.0, 1.0 }; + +double c = stdlib_strided_dpcorrwd_ndarray( 3, x, 1, 0, y, 1, 0 ); +// returns ~0.885 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` first input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[in] double*` second input array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +double stdlib_strided_dpcorrwd_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/strided/dpcorrwd.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + const double y[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + + // Specify the number of elements: + const int N = 8; + + // Specify strides: + const int strideX = 1; + const int strideY = -1; + + // Compute the Pearson product-moment correlation coefficient between `x` and `y`: + double d = stdlib_strided_dpcorrwd( N, x, strideX, y, strideY ); + + // Print the result: + printf( "Pearson Correlation Coefficient: %lf\n", d ); + + // Compute the Pearson product-moment correlation coefficient between `x` and `y` with offsets: + d = stdlib_strided_dpcorrwd_ndarray( N, x, strideX, 0, y, strideY, N-1 ); + + // Print the result: + printf( "Pearson Correlation Coefficient: %lf\n", d ); +} +``` + +
+ + + +
+ + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[pearson-correlation]: https://en.wikipedia.org/wiki/Pearson_correlation_coefficient + +[covariance]: https://en.wikipedia.org/wiki/Covariance + +[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +
+ + diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/benchmark.js new file mode 100644 index 000000000000..ce9647af254d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/benchmark.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var pkg = require( './../package.json' ).name; +var dpcorrwd = require( './../lib/dpcorrwd.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -100.0, 100.0, options ); + var y = uniform( len, -100.0, 100.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var c; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + c = dpcorrwd( x.length, x, 1, y, 1 ); + if ( isnan( c ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( c ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/benchmark.native.js new file mode 100644 index 000000000000..b12395f1d9f0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/benchmark.native.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dpcorrwd = tryRequire( resolve( __dirname, './../lib/dpcorrwd.native.js' ) ); +var opts = { + 'skip': ( dpcorrwd instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -100.0, 100.0, options ); + var y = uniform( len, -100.0, 100.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var c; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + c = dpcorrwd( x.length, x, 1, y, 1 ); + if ( isnan( c ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( c ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..725af2030e4b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/benchmark.ndarray.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var pkg = require( './../package.json' ).name; +var dpcorrwd = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -100.0, 100.0, options ); + var y = uniform( len, -100.0, 100.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var c; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + c = dpcorrwd( x.length, x, 1, 0, y, 1, 0 ); + if ( isnan( c ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( c ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..3b1bd06f7347 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dpcorrwd = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dpcorrwd instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -100.0, 100.0, options ); + var y = uniform( len, -100.0, 100.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var c; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + c = dpcorrwd( x.length, x, 1, 0, y, 1, 0 ); + if ( isnan( c ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( c ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..1d735b3bc491 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/benchmark/c/benchmark.length.c @@ -0,0 +1,209 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dpcorrwd.h" +#include +#include +#include +#include +#include + +#define NAME "dpcorrwd" +#define ITERATIONS 1000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double *x; + double *y; + double c; + double t; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + y = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = random_uniform( -10000.0, 10000.0 ); + y[ i ] = random_uniform( -10000.0, 10000.0 ); + } + c = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + c = stdlib_strided_dpcorrwd( len, x, 1, y, 1 ); + if ( c != c ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( c != c ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double *x; + double *y; + double c; + double t; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + y = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = random_uniform( -10000.0, 10000.0 ); + y[ i ] = random_uniform( -10000.0, 10000.0 ); + } + c = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + c = stdlib_strided_dpcorrwd_ndarray( len, x, 1, 0, x, 1, 0 ); + if ( c != c ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( c != c ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/binding.gyp b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/docs/repl.txt new file mode 100644 index 000000000000..40e4d275ce8f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/docs/repl.txt @@ -0,0 +1,112 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Computes the sample Pearson product-moment correlation coefficient of two + double-precision floating-point strided arrays using Welford's algorithm. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `NaN`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float64Array + First input array. + + strideX: integer + Stride length of `x`. + + y: Float64Array + Second input array. + + strideY: integer + Stride length of `y`. + + Returns + ------- + out: number + Sample correlation coefficient. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] ); + > var y = new {{alias:@stdlib/array/float64}}( [ 2.0, -2.0, 1.0 ] ); + > var out = {{alias}}( x.length, x, 1, y, 1 ) + ~0.885 + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > y = new {{alias:@stdlib/array/float64}}( [ 5.0, 1.0, 2.0, 7.0, 2.0, 4.0 ] ); + > out = {{alias}}( 3, x, 1, y, -1 ) + ~0.721 + + // Using view offsets: + > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > y = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x.buffer, x.BYTES_PER_ELEMENT*1 ); + > var y1 = new {{alias:@stdlib/array/float64}}( y.buffer, y.BYTES_PER_ELEMENT*3 ); + > out = {{alias}}( 3, x1, 1, y1, 1 ) + 1.0 + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Computes the sample Pearson product-moment correlation coefficient of two + double-precision floating-point strided arrays using Welford's algorithm and + alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float64Array + First input array. + + strideX: integer + Stride length of `x`. + + offsetX: integer + Starting index of `x`. + + y: Float64Array + Second input array. + + strideY: integer + Stride length of `y`. + + offsetY: integer + Starting index of `y`. + + Returns + ------- + out: number + Sample correlation coefficient. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] ); + > var y = new {{alias:@stdlib/array/float64}}( [ 2.0, -2.0, 1.0 ] ); + > var out = {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + ~0.885 + + // Using offset parameters: + > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > y = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); + > out = {{alias}}.ndarray( 3, x, 1, 1, y, 1, 3 ) + 1.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/docs/types/index.d.ts new file mode 100644 index 000000000000..9f9b79b235ff --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/docs/types/index.d.ts @@ -0,0 +1,103 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `dpcorrwd`. +*/ +interface Routine { + /** + * Computes the sample Pearson product-moment correlation coefficient of two double-precision floating-point strided arrays using Welford's algorithm. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length of `x` + * @param y - second input array + * @param strideY - stride length of `y` + * @returns sample correlation coefficient + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); + * var y = new Float64Array( [ 2.0, -2.0, 1.0 ] ); + * + * var v = dpcorrwd( x.length, x, 1, y, 1 ); + * // returns ~0.885 + */ + ( N: number, x: Float64Array, strideX: number, y: Float64Array, strideY: number ): number; + + /** + * Computes the sample Pearson product-moment correlation coefficient of two double-precision floating-point strided arrays using Welford's algorithm and alternative indexing semantics. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length of `x` + * @param offsetX - starting index of `x` + * @param y - second input array + * @param strideY - stride length of `y` + * @param offsetY - starting index of `y` + * @returns sample correlation coefficient + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); + * var y = new Float64Array( [ 2.0, -2.0, 1.0 ] ); + * + * var v = dpcorrwd.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns ~0.885 + */ + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number, y: Float64Array, strideY: number, offsetY: number ): number; +} + +/** +* Computes the sample Pearson product-moment correlation coefficient of two double-precision floating-point strided arrays using Welford's algorithm. +* +* @param N - number of indexed elements +* @param x - first input array +* @param strideX - stride length of `x +* @param y - second input array +* @param strideY - stride length of `y` +* @returns sample correlation coefficient +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +* var y = new Float64Array( [ 2.0, -2.0, 1.0 ] ); +* +* var v = dpcorrwd( x.length, x, 1, y, 1 ); +* // returns ~0.885 +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +* var y = new Float64Array( [ 2.0, -2.0, 1.0 ] ); +* +* var v = dpcorrwd.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // returns ~0.885 +*/ +declare var dpcorrwd: Routine; + + +// EXPORTS // + +export = dpcorrwd; diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/docs/types/test.ts b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/docs/types/test.ts new file mode 100644 index 000000000000..a36e327c3f7d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/docs/types/test.ts @@ -0,0 +1,249 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import dpcorrwd = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 20 ); + + dpcorrwd( x.length, x, 1, y, 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 20 ); + + dpcorrwd( '10', x, 1, y, 1 ); // $ExpectError + dpcorrwd( true, x, 1, y, 1 ); // $ExpectError + dpcorrwd( false, x, 1, y, 1 ); // $ExpectError + dpcorrwd( null, x, 1, y, 1 ); // $ExpectError + dpcorrwd( undefined, x, 1, y, 1 ); // $ExpectError + dpcorrwd( [], x, 1, y, 1 ); // $ExpectError + dpcorrwd( {}, x, 1, y, 1 ); // $ExpectError + dpcorrwd( ( x: number ): number => x, x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 20 ); + + dpcorrwd( x.length, 10, 1, y, 1 ); // $ExpectError + dpcorrwd( x.length, '10', 1, y, 1 ); // $ExpectError + dpcorrwd( x.length, true, 1, y, 1 ); // $ExpectError + dpcorrwd( x.length, false, 1, y, 1 ); // $ExpectError + dpcorrwd( x.length, null, 1, y, 1 ); // $ExpectError + dpcorrwd( x.length, undefined, 1, y, 1 ); // $ExpectError + dpcorrwd( x.length, [ '1' ], 1, y, 1 ); // $ExpectError + dpcorrwd( x.length, {}, 1, y, 1 ); // $ExpectError + dpcorrwd( x.length, ( x: number ): number => x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 20 ); + + dpcorrwd( x.length, x, '10', y, 1 ); // $ExpectError + dpcorrwd( x.length, x, true, y, 1 ); // $ExpectError + dpcorrwd( x.length, x, false, y, 1 ); // $ExpectError + dpcorrwd( x.length, x, null, y, 1 ); // $ExpectError + dpcorrwd( x.length, x, undefined, y, 1 ); // $ExpectError + dpcorrwd( x.length, x, [], y, 1 ); // $ExpectError + dpcorrwd( x.length, x, {}, y, 1 ); // $ExpectError + dpcorrwd( x.length, x, ( x: number ): number => x, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dpcorrwd( x.length, x, 1, 10, 1 ); // $ExpectError + dpcorrwd( x.length, x, 1, '10', 1 ); // $ExpectError + dpcorrwd( x.length, x, 1, true, 1 ); // $ExpectError + dpcorrwd( x.length, x, 1, false, 1 ); // $ExpectError + dpcorrwd( x.length, x, 1, null, 1 ); // $ExpectError + dpcorrwd( x.length, x, 1, undefined, 1 ); // $ExpectError + dpcorrwd( x.length, x, 1, [ '1' ], 1 ); // $ExpectError + dpcorrwd( x.length, x, 1, {}, 1 ); // $ExpectError + dpcorrwd( x.length, x, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 20 ); + + dpcorrwd( x.length, x, 1, y, '10' ); // $ExpectError + dpcorrwd( x.length, x, 1, y, true ); // $ExpectError + dpcorrwd( x.length, x, 1, y, false ); // $ExpectError + dpcorrwd( x.length, x, 1, y, null ); // $ExpectError + dpcorrwd( x.length, x, 1, y, undefined ); // $ExpectError + dpcorrwd( x.length, x, 1, y, [] ); // $ExpectError + dpcorrwd( x.length, x, 1, y, {} ); // $ExpectError + dpcorrwd( x.length, x, 1, y, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 20 ); + + dpcorrwd(); // $ExpectError + dpcorrwd( x.length ); // $ExpectError + dpcorrwd( x.length, x ); // $ExpectError + dpcorrwd( x.length, x, 1 ); // $ExpectError + dpcorrwd( x.length, x, 1, y ); // $ExpectError + dpcorrwd( x.length, x, 1, y, 1, 0 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 20 ); + + dpcorrwd.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 20 ); + + dpcorrwd.ndarray( '10', x, 1, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( undefined, x, 1, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( [], x, 1, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( ( x: number ): number => x, x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 20 ); + + dpcorrwd.ndarray( x.length, 10, 1, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, '10', 1, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, true, 1, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, false, 1, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, null, 1, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, undefined, 1, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, [ '1' ], 1, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, {}, 1, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, ( x: number ): number => x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 20 ); + + dpcorrwd.ndarray( x.length, x, '10', 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, undefined, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, [], 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, ( x: number ): number => x, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 20 ); + + dpcorrwd.ndarray( x.length, x, 1, '10', y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, undefined, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, [], y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, ( x: number ): number => x, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dpcorrwd.ndarray( x.length, x, 1, 0, 10, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, '10', 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, true, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, false, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, null, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, undefined, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, [ '1' ], 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, {}, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 20 ); + + dpcorrwd.ndarray( x.length, x, 1, 0, y, '10', 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y, undefined, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y, [], 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 20 ); + + dpcorrwd.ndarray( x.length, x, 1, 0, y, 1, '10' ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y, 1, undefined ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y, 1, [] ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 20 ); + + dpcorrwd.ndarray(); // $ExpectError + dpcorrwd.ndarray( x.length ); // $ExpectError + dpcorrwd.ndarray( x.length, x ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y, 1 ); // $ExpectError + dpcorrwd.ndarray( x.length, x, 1, 0, y, 1, 0, 0 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/examples/c/Makefile b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/examples/c/example.c b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/examples/c/example.c new file mode 100644 index 000000000000..a05b9243caa9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/examples/c/example.c @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dpcorrwd.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + const double y[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + + // Specify the number of elements: + const int N = 8; + + // Specify strides: + const int strideX = 1; + const int strideY = -1; + + // Compute the Pearson product-moment correlation coefficient between `x` and `y`: + double d = stdlib_strided_dpcorrwd( N, x, strideX, y, strideY ); + + // Print the result: + printf( "Pearson Correlation Coefficient: %lf\n", d ); + + // Compute the Pearson product-moment correlation coefficient between `x` and `y` with offsets: + d = stdlib_strided_dpcorrwd_ndarray( N, x, strideX, 0, y, strideY, N-1 ); + + // Print the result: + printf( "Pearson Correlation Coefficient: %lf\n", d ); +} diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/examples/index.js b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/examples/index.js new file mode 100644 index 000000000000..972b033ecfb1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/examples/index.js @@ -0,0 +1,34 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var dpcorrwd = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; +var x = discreteUniform( 10, -50, 50, opts ); +console.log( x ); + +var y = discreteUniform( 10, -50, 50, opts ); +console.log( y ); + +var c = dpcorrwd( x.length, x, 1, y, 1 ); +console.log( c ); diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/include.gypi b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' 1 +} + + +// EXPORTS // + +module.exports = dpcorrwd; diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/lib/ndarray.native.js new file mode 100644 index 000000000000..6f106e03daa9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/lib/ndarray.native.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Computes the sample Pearson product-moment correlation coefficient of two double-precision floating-point strided arrays using Welford's algorithm. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Float64Array} x - first input array +* @param {integer} strideX - stride length of `x` +* @param {NonNegativeInteger} offsetX - starting index of `x` +* @param {Float64Array} y - second input array +* @param {integer} strideY - stride length of `y` +* @param {NonNegativeInteger} offsetY - starting index of `y` +* @returns {number} sample correlation coefficient +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +* var y = new Float64Array( [ 2.0, -2.0, 1.0 ] ); +* +* var v = dpcorrwd( x.length, x, 1, 0, y, 1, 0 ); +* // returns ~0.885 +*/ +function dpcorrwd( N, x, strideX, offsetX, y, strideY, offsetY ) { + return addon.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ); +} + + +// EXPORTS // + +module.exports = dpcorrwd; diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/manifest.json b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/manifest.json new file mode 100644 index 000000000000..9cf5b768b42a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/manifest.json @@ -0,0 +1,107 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", + "@stdlib/math/base/special/clamp", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-double", + "@stdlib/napi/argv-strided-float64array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", + "@stdlib/math/base/special/clamp" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", + "@stdlib/math/base/special/clamp" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/package.json b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/package.json new file mode 100644 index 000000000000..7fdfb8c76b61 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/package.json @@ -0,0 +1,76 @@ +{ + "name": "@stdlib/stats/strided/dpcorrwd", + "version": "0.0.0", + "description": "Calculate the pearson correlation coefficient of two double-precision floating-point strided arrays using Welford's algorithm.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "pearson", + "correlation", + "corr", + "pcorr", + "welford", + "strided", + "strided array", + "typed", + "array", + "float64", + "double", + "float64array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/src/Makefile b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/src/addon.c b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/src/addon.c new file mode 100644 index 000000000000..f778211d1802 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/src/addon.c @@ -0,0 +1,66 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dpcorrwd.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 3 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dpcorrwd)( N, X, strideX, Y, strideY ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dpcorrwd_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/src/main.c b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/src/main.c new file mode 100644 index 000000000000..ed5d06673429 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/src/main.c @@ -0,0 +1,204 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dpcorrwd.h" +#include "stdlib/math/base/special/sqrt.h" +#include "stdlib/math/base/special/clamp.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the sample Pearson product-moment correlation coefficient of two double-precision floating-point strided arrays using Welford's algorithm. +* +* @param N number of indexed elements +* @param X first input array +* @param strideX stride length of `X` +* @param Y second input array +* @param strideY stride length of `Y` +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dpcorrwd)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const double *Y, const CBLAS_INT strideY ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + return API_SUFFIX(stdlib_strided_dpcorrwd_ndarray)( N, X, strideX, ox, Y, strideY, oy ); +} + +/** +* Computes the sample Pearson product-moment correlation coefficient of two double-precision floating-point strided arrays using Welford's algorithm and alternative indexing semantics. +* +* ## Method +* +* - We begin by defining the co-moment \\(C_n\\) +* +* ```tex +* C_n = \sum_{i=1}^{n} ( x_i - \bar{x}_n ) ( y_i - \bar{y}_n ) +* ``` +* +* where \\(\bar{x}_n\\) and \\(\bar{y}_n\\) are the sample means for \\(x\\) and \\(y\\), respectively. +* +* - Based on Welford's method, we know the update formulas for the sample means are given by +* +* ```tex +* \bar{x}_n = \bar{x}_{n-1} + \frac{x_n - \bar{x}_{n-1}}{n} +* ``` +* +* and +* +* ```tex +* \bar{y}_n = \bar{y}_{n-1} + \frac{y_n - \bar{y}_{n-1}}{n} +* ``` +* +* - Substituting into the equation for \\(C_n\\) and rearranging terms +* +* ```tex +* C_n = C_{n-1} + (x_n - \bar{x}_n) (y_n - \bar{y}_{n-1}) +* ``` +* +* where the apparent asymmetry arises from +* +* ```tex +* x_n - \bar{x}_n = \frac{n-1}{n} (x_n - \bar{x}_{n-1}) +* ``` +* +* and, hence, the update term can be equivalently expressed +* +* ```tex +* \frac{n-1}{n} (x_n - \bar{x}_{n-1}) (y_n - \bar{y}_{n-1}) +* ``` +* +* - The covariance can be defined +* +* ```tex +* \begin{align*} +* \operatorname{cov}_n(x,y) &= \frac{C_n}{n} \\ +* &= \frac{C_{n-1} + (x_n - \bar{x}_n) (y_n - \bar{y}_{n-1})}{n} \\ +* &= \frac{(n-1)\operatorname{cov}_{n-1}(x,y) + (x_n - \bar{x}_n) (y_n - \bar{y}_{n-1})}{n} +* \end{align*} +* ``` +* +* - Applying Bessel's correction, we arrive at an update formula for calculating an unbiased sample covariance +* +* ```tex +* \begin{align*} +* \operatorname{cov}_n(x,y) &= \frac{n}{n-1}\cdot\frac{(n-1)\operatorname{cov}_{n-1}(x,y) + (x_n - \bar{x}_n) (y_n - \bar{y}_{n-1})}{n} \\ +* &= \operatorname{cov}_{n-1}(x,y) + \frac{(x_n - \bar{x}_n) (y_n - \bar{y}_{n-1})}{n-1} \\ +* &= \frac{C_{n-1} + (x_n - \bar{x}_n) (y_n - \bar{y}_{n-1})}{n-1} +* &= \frac{C_{n-1} + (x_n - \bar{x}_{n-1}) (y_n - \bar{y}_n)}{n-1} +* \end{align*} +* ``` +* +* - To calculate the corrected sample standard deviation, we can use Welford's method, which can be derived as follows. We can express the variance as +* +* ```tex +* \begin{align*} +* S_n &= n \sigma_n^2 \\ +* &= \sum_{i=1}^{n} (x_i - \mu_n)^2 \\ +* &= \biggl(\sum_{i=1}^{n} x_i^2 \biggr) - n\mu_n^2 +* \end{align*} +* ``` +* +* Accordingly, +* +* ```tex +* \begin{align*} +* S_n - S_{n-1} &= \sum_{i=1}^{n} x_i^2 - n\mu_n^2 - \sum_{i=1}^{n-1} x_i^2 + (n-1)\mu_{n-1}^2 \\ +* &= x_n^2 - n\mu_n^2 + (n-1)\mu_{n-1}^2 \\ +* &= x_n^2 - \mu_{n-1}^2 + n(\mu_{n-1}^2 - \mu_n^2) \\ +* &= x_n^2 - \mu_{n-1}^2 + n(\mu_{n-1} - \mu_n)(\mu_{n-1} + \mu_n) \\ +* &= x_n^2 - \mu_{n-1}^2 + (\mu_{n-1} - x_n)(\mu_{n-1} + \mu_n) \\ +* &= x_n^2 - \mu_{n-1}^2 + \mu_{n-1}^2 - x_n\mu_n - x_n\mu_{n-1} + \mu_n\mu_{n-1} \\ +* &= x_n^2 - x_n\mu_n - x_n\mu_{n-1} + \mu_n\mu_{n-1} \\ +* &= (x_n - \mu_{n-1})(x_n - \mu_n) \\ +* &= S_{n-1} + (x_n - \mu_{n-1})(x_n - \mu_n) +* \end{align*} +* ``` +* +* where we use the identity +* +* ```tex +* x_n - \mu_{n-1} = n (\mu_n - \mu_{n-1}) +* ``` +* +* - To compute the corrected sample standard deviation, we apply Bessel's correction and take the square root. +* +* - The sample Pearson product-moment correlation coefficient can thus be calculated as +* +* ```tex +* r = \frac{\operatorname{cov}_n(x,y)}{\sigma_x \sigma_y} +* ``` +* +* where \\(\sigma_x\\) and \\(\sigma_y\\) are the corrected sample standard deviations for \\(x\\) and \\(y\\), respectively. +* +* @param N number of indexed elements +* @param X first input array +* @param strideX stride length of `X` +* @param offsetX starting index for X +* @param Y second input array +* @param strideY stride length of `Y` +* @param offsetY starting index for Y +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dpcorrwd_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT iy; + CBLAS_INT ix; + CBLAS_INT i; + double M2x; + double M2y; + double dy1; + double dy2; + double dx; + double my; + double mx; + double sy; + double sx; + double C; + double r; + + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + ix = offsetX; + iy = offsetY; + C = 0.0; + mx = 0.0; + my = 0.0; + M2x = 0.0; + M2y = 0.0; + for ( i = 0; i < N; i++ ) { + dx = X[ ix ] - mx; + mx += dx / ( i+1 ); + M2x += dx * ( X[ ix ] - mx ); + + dy1 = Y[ iy ] - my; + my += dy1 / ( i+1 ); + dy2 = Y[ iy ] - my; + M2y += dy2 * dy1; + + C += dx * dy2; + + ix += strideX; + iy += strideY; + } + if ( M2x == 0.0 || M2y == 0.0 ) { + return 0.0 / 0.0; // NaN + } + sx = stdlib_base_sqrt( M2x/N ); + sy = stdlib_base_sqrt( M2y/N ); + r = ( C/N ) / ( sx*sy ); // Why all the dividing by `N`? To avoid overflow. + return stdlib_base_clamp( r, -1.0, 1.0 ); // Guard against accumulated floating-point errors resulting in |r| > 1 +} diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/test/test.dpcorrwd.js b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/test/test.dpcorrwd.js new file mode 100644 index 000000000000..54287e3c6681 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/test/test.dpcorrwd.js @@ -0,0 +1,217 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var dpcorrwd = require( './../lib/dpcorrwd.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dpcorrwd, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( dpcorrwd.length, 5, 'returns expected value' ); + t.end(); +}); + +tape( 'the function calculates the Pearson product-moment correlation coefficient between two strided arrays', function test( t ) { + var c; + var x; + var y; + + x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0, 2.0, -5.0, 6.0 ] ); + y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0, 8.0, 2.0, -3.0 ] ); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( x.length, x, 1, y, 1 ); + t.strictEqual( isAlmostSameValue( c, -0.3035656199908971, 1 ), true, 'returns expected value' ); + + x = new Float64Array( [ 3.0, -4.0, 1.0 ] ); + y = new Float64Array( [ 1.0, -2.0, 3.0 ] ); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( x.length, x, 1, y, 1 ); + t.strictEqual( isAlmostSameValue( c, 0.7714542762891773, 1 ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) { + var c; + var x; + var y; + + x = new Float64Array( [ 3.0, -4.0, 1.0 ] ); + y = new Float64Array( [ 1.0, -2.0, 3.0 ] ); + + c = dpcorrwd( 0, x, 1, y, 1 ); + t.strictEqual( isAlmostSameValue( c, NaN, 0 ), true, 'returns expected value' ); + + c = dpcorrwd( -4, x, 1, y, 1 ); + t.strictEqual( isAlmostSameValue( c, NaN, 0 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 2.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 2 + ]); + y = new Float64Array([ + 8.0, // 0 + 2.0, // 1 + -3.0, // 2 + 3.0, + -4.0, + 1.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, 2, y, 1 ); + t.strictEqual( isAlmostSameValue( c, -0.30980091032971513, 1 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 2.0, // 0 + -3.0, // 1 + -5.0, // 2 + 7.0, + 6.0 + ]); + y = new Float64Array([ + 8.0, // 0 + 2.0, + -3.0, // 1 + 3.0, + -4.0, // 2 + 1.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, 1, y, 2 ); + t.strictEqual( isAlmostSameValue( c, 0.978883465889473, 1 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float64Array([ + 6.0, // 2 + 7.0, // 1 + 8.0, // 0 + 9.0, + 10.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, -2, y, -1 ); + t.strictEqual( isAlmostSameValue( c, 0.9999999999999998, 2 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float64Array([ + 6.0, // 2 + 7.0, // 1 + 8.0, // 0 + 9.0, + 10.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, 2, y, -1 ); + t.strictEqual( isAlmostSameValue( c, -0.9999999999999998, 2 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var x0; + var y0; + var x1; + var y1; + var c; + + x0 = new Float64Array([ + 1.0, + 2.0, // 0 + 3.0, + 4.0, // 1 + 5.0, + 6.0 // 2 + ]); + y0 = new Float64Array([ + 6.0, + 7.0, + 8.0, + 9.0, // 0 + 10.0, // 1 + 11.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x1, 2, y1, 1 ); + t.strictEqual( isAlmostSameValue( c, 0.9999999999999998, 2 ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/test/test.dpcorrwd.native.js b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/test/test.dpcorrwd.native.js new file mode 100644 index 000000000000..c1ea27108035 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/test/test.dpcorrwd.native.js @@ -0,0 +1,226 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dpcorrwd = tryRequire( resolve( __dirname, './../lib/dpcorrwd.native.js' ) ); +var opts = { + 'skip': ( dpcorrwd instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dpcorrwd, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( dpcorrwd.length, 5, 'returns expected value' ); + t.end(); +}); + +tape( 'the function calculates the Pearson product-moment correlation coefficient between two strided arrays', opts, function test( t ) { + var c; + var x; + var y; + + x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0, 2.0, -5.0, 6.0 ] ); + y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0, 8.0, 2.0, -3.0 ] ); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( x.length, x, 1, y, 1 ); + t.strictEqual( isAlmostSameValue( c, -0.3035656199908971, 1 ), true, 'returns expected value' ); + + x = new Float64Array( [ 3.0, -4.0, 1.0 ] ); + y = new Float64Array( [ 1.0, -2.0, 3.0 ] ); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( x.length, x, 1, y, 1 ); + t.strictEqual( isAlmostSameValue( c, 0.7714542762891773, 1 ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', opts, function test( t ) { + var c; + var x; + var y; + + x = new Float64Array( [ 3.0, -4.0, 1.0 ] ); + y = new Float64Array( [ 1.0, -2.0, 3.0 ] ); + + c = dpcorrwd( 0, x, 1, y, 1 ); + t.strictEqual( isAlmostSameValue( c, NaN, 0 ), true, 'returns expected value' ); + + c = dpcorrwd( -4, x, 1, y, 1 ); + t.strictEqual( isAlmostSameValue( c, NaN, 0 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 2.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 2 + ]); + y = new Float64Array([ + 8.0, // 0 + 2.0, // 1 + -3.0, // 2 + 3.0, + -4.0, + 1.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, 2, y, 1 ); + t.strictEqual( isAlmostSameValue( c, -0.30980091032971513, 1 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 2.0, // 0 + -3.0, // 1 + -5.0, // 2 + 7.0, + 6.0 + ]); + y = new Float64Array([ + 8.0, // 0 + 2.0, + -3.0, // 1 + 3.0, + -4.0, // 2 + 1.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, 1, y, 2 ); + t.strictEqual( isAlmostSameValue( c, 0.978883465889473, 1 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float64Array([ + 6.0, // 2 + 7.0, // 1 + 8.0, // 0 + 9.0, + 10.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, -2, y, -1 ); + t.strictEqual( isAlmostSameValue( c, 0.9999999999999998, 2 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float64Array([ + 6.0, // 2 + 7.0, // 1 + 8.0, // 0 + 9.0, + 10.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, 2, y, -1 ); + t.strictEqual( isAlmostSameValue( c, -0.9999999999999998, 2 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var x0; + var y0; + var x1; + var y1; + var c; + + x0 = new Float64Array([ + 1.0, + 2.0, // 0 + 3.0, + 4.0, // 1 + 5.0, + 6.0 // 2 + ]); + y0 = new Float64Array([ + 6.0, + 7.0, + 8.0, + 9.0, // 0 + 10.0, // 1 + 11.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x1, 2, y1, 1 ); + t.strictEqual( isAlmostSameValue( c, 0.9999999999999998, 2 ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/test/test.js b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/test/test.js new file mode 100644 index 000000000000..a6febe1f7da7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var dpcorrwd = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dpcorrwd, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof dpcorrwd.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var dpcorrwd = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dpcorrwd, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var dpcorrwd; + var main; + + main = require( './../lib/dpcorrwd.js' ); + + dpcorrwd = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dpcorrwd, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/test/test.ndarray.js new file mode 100644 index 000000000000..13910753e781 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/test/test.ndarray.js @@ -0,0 +1,240 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var dpcorrwd = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dpcorrwd, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( dpcorrwd.length, 7, 'returns expected value' ); + t.end(); +}); + +tape( 'the function calculates the Pearson product-moment correlation coefficient between two strided arrays', function test( t ) { + var c; + var x; + var y; + + x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0, 2.0, -5.0, 6.0 ] ); + y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0, 8.0, 2.0, -3.0 ] ); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isAlmostSameValue( c, -0.3035656199908971, 1 ), true, 'returns expected value' ); + + x = new Float64Array( [ 3.0, -4.0, 1.0 ] ); + y = new Float64Array( [ 1.0, -2.0, 3.0 ] ); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isAlmostSameValue( c, 0.7714542762891773, 1 ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) { + var c; + var x; + var y; + + x = new Float64Array( [ 3.0, -4.0, 1.0 ] ); + y = new Float64Array( [ 1.0, -2.0, 3.0 ] ); + + c = dpcorrwd( 0, x, 1, 0, y, 1, 0 ); + t.strictEqual( isAlmostSameValue( c, NaN, 0 ), true, 'returns expected value' ); + + c = dpcorrwd( -4, x, 1, 0, y, 1, 0 ); + t.strictEqual( isAlmostSameValue( c, NaN, 0 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 2.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 2 + ]); + y = new Float64Array([ + 8.0, // 0 + 2.0, // 1 + -3.0, // 2 + 3.0, + -4.0, + 1.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( isAlmostSameValue( c, -0.30980091032971513, 1 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 1.0, + 2.0, // 0 + 3.0, + 4.0, // 1 + 5.0, + 6.0 // 2 + ]); + y = new Float64Array([ + 6.0, // 0 + 7.0, // 1 + 8.0, // 2 + 9.0, + 10.0, + 11.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, 2, 1, y, 1, 0 ); + t.strictEqual( isAlmostSameValue( c, 0.9999999999999998, 2 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 2.0, // 0 + -3.0, // 1 + -5.0, // 2 + 7.0, + 6.0 + ]); + y = new Float64Array([ + 8.0, // 0 + 2.0, + -3.0, // 1 + 3.0, + -4.0, // 2 + 1.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( isAlmostSameValue( c, 0.978883465889473, 1 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` offset', function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]); + y = new Float64Array([ + 6.0, + 7.0, + 8.0, + 9.0, // 0 + 10.0, // 1 + 11.0 // 2 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, 2, 0, y, 1, 3 ); + t.strictEqual( isAlmostSameValue( c, 0.9999999999999998, 2 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float64Array([ + 6.0, // 2 + 7.0, // 1 + 8.0, // 0 + 9.0, + 10.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, -2, x.length-1, y, -1, 2 ); + t.strictEqual( isAlmostSameValue( c, 0.9999999999999998, 2 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float64Array([ + 6.0, + 7.0, // 2 + 8.0, // 1 + 9.0, // 0 + 10.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, 2, 0, y, -1, y.length-2 ); + t.strictEqual( isAlmostSameValue( c, -0.9999999999999998, 2 ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/dpcorrwd/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/test/test.ndarray.native.js new file mode 100644 index 000000000000..a219638a6f4f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dpcorrwd/test/test.ndarray.native.js @@ -0,0 +1,249 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dpcorrwd = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dpcorrwd instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dpcorrwd, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', opts, function test( t ) { + t.strictEqual( dpcorrwd.length, 7, 'returns expected value' ); + t.end(); +}); + +tape( 'the function calculates the Pearson product-moment correlation coefficient between two strided arrays', opts, function test( t ) { + var c; + var x; + var y; + + x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0, 2.0, -5.0, 6.0 ] ); + y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0, 8.0, 2.0, -3.0 ] ); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isAlmostSameValue( c, -0.3035656199908971, 1 ), true, 'returns expected value' ); + + x = new Float64Array( [ 3.0, -4.0, 1.0 ] ); + y = new Float64Array( [ 1.0, -2.0, 3.0 ] ); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isAlmostSameValue( c, 0.7714542762891773, 1 ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', opts, function test( t ) { + var c; + var x; + var y; + + x = new Float64Array( [ 3.0, -4.0, 1.0 ] ); + y = new Float64Array( [ 1.0, -2.0, 3.0 ] ); + + c = dpcorrwd( 0, x, 1, 0, y, 1, 0 ); + t.strictEqual( isAlmostSameValue( c, NaN, 0 ), true, 'returns expected value' ); + + c = dpcorrwd( -4, x, 1, 0, y, 1, 0 ); + t.strictEqual( isAlmostSameValue( c, NaN, 0 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 2.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 2 + ]); + y = new Float64Array([ + 8.0, // 0 + 2.0, // 1 + -3.0, // 2 + 3.0, + -4.0, + 1.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( isAlmostSameValue( c, -0.30980091032971513, 1 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', opts, function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 1.0, + 2.0, // 0 + 3.0, + 4.0, // 1 + 5.0, + 6.0 // 2 + ]); + y = new Float64Array([ + 6.0, // 0 + 7.0, // 1 + 8.0, // 2 + 9.0, + 10.0, + 11.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, 2, 1, y, 1, 0 ); + t.strictEqual( isAlmostSameValue( c, 0.9999999999999998, 2 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 2.0, // 0 + -3.0, // 1 + -5.0, // 2 + 7.0, + 6.0 + ]); + y = new Float64Array([ + 8.0, // 0 + 2.0, + -3.0, // 1 + 3.0, + -4.0, // 2 + 1.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( isAlmostSameValue( c, 0.978883465889473, 1 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` offset', opts, function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]); + y = new Float64Array([ + 6.0, + 7.0, + 8.0, + 9.0, // 0 + 10.0, // 1 + 11.0 // 2 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, 2, 0, y, 1, 3 ); + t.strictEqual( isAlmostSameValue( c, 0.9999999999999998, 2 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float64Array([ + 6.0, // 2 + 7.0, // 1 + 8.0, // 0 + 9.0, + 10.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, -2, x.length-1, y, -1, 2 ); + t.strictEqual( isAlmostSameValue( c, 0.9999999999999998, 2 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var c; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float64Array([ + 6.0, + 7.0, // 2 + 8.0, // 1 + 9.0, // 0 + 10.0 + ]); + + // Tested against SciPy's `spatial.stats.pearsonr`: + c = dpcorrwd( 3, x, 2, 0, y, -1, y.length-2 ); + t.strictEqual( isAlmostSameValue( c, -0.9999999999999998, 2 ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/drange/README.md b/lib/node_modules/@stdlib/stats/strided/drange/README.md index 0cc69d537c4b..df9e57465e09 100644 --- a/lib/node_modules/@stdlib/stats/strided/drange/README.md +++ b/lib/node_modules/@stdlib/stats/strided/drange/README.md @@ -182,7 +182,7 @@ Computes the [range][range] of a double-precision floating-point strided array ` const double x[] = { 1.0, -2.0, 3.0, -4.0 }; double v = stdlib_strided_drange( 4, x, 1 ); -// returns 4.0 +// returns 7.0 ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/stats/strided/drange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/drange/benchmark/benchmark.js index c2eb1db95f01..2e3b2f425470 100644 --- a/lib/node_modules/@stdlib/stats/strided/drange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/drange/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var drange = require( './../lib/drange.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/drange/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/drange/benchmark/benchmark.native.js index 4d9785147368..f48d0835c4a7 100644 --- a/lib/node_modules/@stdlib/stats/strided/drange/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/drange/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/drange/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/drange/benchmark/benchmark.ndarray.js index 72a73213ba47..183bb4ea543a 100644 --- a/lib/node_modules/@stdlib/stats/strided/drange/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/drange/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var drange = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/drange/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/drange/benchmark/benchmark.ndarray.native.js index 3cd60cef4858..f442ba7e1e27 100644 --- a/lib/node_modules/@stdlib/stats/strided/drange/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/drange/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsem/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsem/benchmark/benchmark.js index 838fcc904133..12fde45c8715 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsem/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsem/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsem = require( './../lib/dsem.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsem/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsem/benchmark/benchmark.native.js index 7f721819c28a..cea8f4bd561b 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsem/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsem/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsem/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsem/benchmark/benchmark.ndarray.js index 488310c8fc92..f2cd39e0a265 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsem/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsem/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsem = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsem/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsem/benchmark/benchmark.ndarray.native.js index ef5e80faba76..73537f6d3fe9 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsem/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsem/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsemch/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsemch/benchmark/benchmark.js index 13a249fbfa77..e9e32769a085 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsemch/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsemch/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsemch = require( './../lib/dsemch.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsemch/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsemch/benchmark/benchmark.native.js index 9703ffaa2998..1b771edaa43b 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsemch/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsemch/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsemch/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsemch/benchmark/benchmark.ndarray.js index 75763f6d3984..bfd92f3f69d3 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsemch/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsemch/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsemch = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsemch/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsemch/benchmark/benchmark.ndarray.native.js index 68e581c363ab..8fdb69ccbbcf 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsemch/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsemch/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsempn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsempn/benchmark/benchmark.js index ead9ec840158..9c287326a499 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsempn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsempn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsempn = require( './../lib/dsempn.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsempn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsempn/benchmark/benchmark.native.js index e3c20da09cb2..ef1e2cf9d9bd 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsempn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsempn/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsempn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsempn/benchmark/benchmark.ndarray.js index 6cc2141e4477..495efcef005d 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsempn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsempn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsempn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsempn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsempn/benchmark/benchmark.ndarray.native.js index 006aff769eb0..4fa7682729d0 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsempn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsempn/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsemtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsemtk/benchmark/benchmark.js index c534071dba6b..d77b10e1c819 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsemtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsemtk/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsemtk = require( './../lib/dsemtk.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsemtk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsemtk/benchmark/benchmark.native.js index 5f1469f90eab..099b6ca42a8b 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsemtk/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsemtk/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsemtk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsemtk/benchmark/benchmark.ndarray.js index 513d380a49b8..3ab9b75a6d79 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsemtk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsemtk/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsemtk = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsemtk/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsemtk/benchmark/benchmark.ndarray.native.js index a63da8017089..213ab0d66cc7 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsemtk/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsemtk/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsemwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsemwd/benchmark/benchmark.js index a667fe54dfe3..ec604384726a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsemwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsemwd/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsemwd = require( './../lib/dsemwd.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsemwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsemwd/benchmark/benchmark.native.js index 34fed49c363f..19eb89848edb 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsemwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsemwd/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsemwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsemwd/benchmark/benchmark.ndarray.js index addf70d60cd5..0a37a376efda 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsemwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsemwd/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsemwd = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsemwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsemwd/benchmark/benchmark.ndarray.native.js index 1bc5d5367306..7d1e9355f12c 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsemwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsemwd/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsemyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsemyc/benchmark/benchmark.js index a13bc5f65823..bfb9916e39cc 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsemyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsemyc/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsemyc = require( './../lib/dsemyc.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsemyc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsemyc/benchmark/benchmark.native.js index a276b7fba890..167bdc9ebf74 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsemyc/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsemyc/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsemyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsemyc/benchmark/benchmark.ndarray.js index 25c2ccd5a051..05a03975cde8 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsemyc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsemyc/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsemyc = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsemyc/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsemyc/benchmark/benchmark.ndarray.native.js index a60f88a458d7..a318434369ac 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsemyc/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsemyc/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsmean/benchmark/benchmark.js index 3151698103be..125c50e02629 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmean/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsmean = require( './../lib/dsmean.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmean/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsmean/benchmark/benchmark.native.js index a45e89267a3b..9fa36a19233d 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmean/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmean/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmean/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsmean/benchmark/benchmark.ndarray.js index 8500ae1d3ab7..fe11d6e7d88b 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmean/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmean/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsmean = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmean/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsmean/benchmark/benchmark.ndarray.native.js index 0b780368b943..f3466fc10719 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmean/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmean/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsmeanors/benchmark/benchmark.js index 66fca1566b15..ed80339fca07 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmeanors/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsmeanors = require( './../lib/dsmeanors.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmeanors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsmeanors/benchmark/benchmark.native.js index 3b3098b84879..8daf02ed9852 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmeanors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmeanors/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmeanors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsmeanors/benchmark/benchmark.ndarray.js index f25731a41521..ba9ea2758794 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmeanors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmeanors/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsmeanors = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmeanors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsmeanors/benchmark/benchmark.ndarray.native.js index 19f1d58d6037..360fef652881 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmeanors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmeanors/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmeanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsmeanpn/benchmark/benchmark.js index ca80802906d5..1fc0fd1996ec 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmeanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmeanpn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsmeanpn = require( './../lib/dsmeanpn.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmeanpn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsmeanpn/benchmark/benchmark.native.js index 975203affa72..22b36637c118 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmeanpn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmeanpn/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmeanpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsmeanpn/benchmark/benchmark.ndarray.js index 3593cce5323e..527ba4ee0707 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmeanpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmeanpn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsmeanpn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmeanpn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsmeanpn/benchmark/benchmark.ndarray.native.js index 9fe9a8e66897..1b0f38a4e17f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmeanpn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmeanpn/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmeanpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsmeanpw/benchmark/benchmark.js index 0bb1ce027278..1e15d7717976 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmeanpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmeanpw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsmeanpw = require( './../lib/dsmeanpw.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmeanpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsmeanpw/benchmark/benchmark.native.js index 0da4c50ede64..19bbb65ee293 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmeanpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmeanpw/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmeanpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsmeanpw/benchmark/benchmark.ndarray.js index f573a4c65311..79531d742e6b 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmeanpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmeanpw/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsmeanpw = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmeanpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsmeanpw/benchmark/benchmark.ndarray.native.js index 4eba43430781..4e800268f18e 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmeanpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmeanpw/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsmeanwd/benchmark/benchmark.js index 46982e6a8068..1350f63e0daa 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmeanwd/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsmeanwd = require( './../lib/dsmeanwd.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmeanwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsmeanwd/benchmark/benchmark.native.js index c85014c6d5a7..1273a51e0ecf 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmeanwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmeanwd/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmeanwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsmeanwd/benchmark/benchmark.ndarray.js index 7592d32dee4d..04ed86cbbdbd 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmeanwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmeanwd/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsmeanwd = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsmeanwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsmeanwd/benchmark/benchmark.ndarray.native.js index 55ace926001f..0cc78e11c7a3 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsmeanwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsmeanwd/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsnanmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsnanmean/benchmark/benchmark.js index 785f81e485a9..fe7c700894e1 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsnanmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsnanmean/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsnanmean = require( './../lib/dsnanmean.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsnanmean/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsnanmean/benchmark/benchmark.native.js index a20a38dbe01b..92dd3094958a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsnanmean/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsnanmean/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsnanmean/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsnanmean/benchmark/benchmark.ndarray.js index f3606a1f9b65..ed98effcf00a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsnanmean/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsnanmean/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsnanmean = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsnanmean/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsnanmean/benchmark/benchmark.ndarray.native.js index e630e0e5ca42..a695b8168a51 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsnanmean/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsnanmean/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsnanmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsnanmeanors/benchmark/benchmark.js index 143f4f0991d3..c7d6e235704b 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsnanmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsnanmeanors/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsnanmeanors = require( './../lib/dsnanmeanors.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsnanmeanors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsnanmeanors/benchmark/benchmark.native.js index 8c89d68f5412..2ea8f4bc574c 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsnanmeanors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsnanmeanors/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsnanmeanors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsnanmeanors/benchmark/benchmark.ndarray.js index 88da97c26b7e..72f73f788c27 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsnanmeanors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsnanmeanors/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsnanmeanors = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsnanmeanors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsnanmeanors/benchmark/benchmark.ndarray.native.js index fba9492aacf4..e8877321c0e0 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsnanmeanors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsnanmeanors/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsnanmeanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsnanmeanpn/benchmark/benchmark.js index fdd0c9d0f2f5..d4d8598287c6 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsnanmeanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsnanmeanpn/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsnanmeanpn = require( './../lib/dsnanmeanpn.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsnanmeanpn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsnanmeanpn/benchmark/benchmark.native.js index c8a88c721e6e..2556128c684f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsnanmeanpn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsnanmeanpn/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsnanmeanpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsnanmeanpn/benchmark/benchmark.ndarray.js index a6ec10ab958e..d6b257aa419f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsnanmeanpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsnanmeanpn/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsnanmeanpn = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsnanmeanpn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsnanmeanpn/benchmark/benchmark.ndarray.native.js index bc900949b390..1daba1dab874 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsnanmeanpn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsnanmeanpn/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsnanmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsnanmeanwd/benchmark/benchmark.js index 49fe040ae0e7..37391780a98d 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsnanmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsnanmeanwd/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsnanmeanwd = require( './../lib/dsnanmeanwd.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsnanmeanwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsnanmeanwd/benchmark/benchmark.native.js index 8ed7dfe61883..977e0ba67bf1 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsnanmeanwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsnanmeanwd/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsnanmeanwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsnanmeanwd/benchmark/benchmark.ndarray.js index fb9900e0f935..6af0b25f92b2 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsnanmeanwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsnanmeanwd/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsnanmeanwd = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsnanmeanwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsnanmeanwd/benchmark/benchmark.ndarray.native.js index bf3e0ed271d0..9fcd2946890c 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsnanmeanwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsnanmeanwd/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdev/README.md b/lib/node_modules/@stdlib/stats/strided/dstdev/README.md index f6334c41457b..fdf0d321d052 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdev/README.md +++ b/lib/node_modules/@stdlib/stats/strided/dstdev/README.md @@ -243,7 +243,7 @@ Computes the [standard deviation][standard-deviation] of a double-precision floa const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; double v = stdlib_strided_dstdev( 4, 1.0, x, 2 ); -// returns 2.581989 +// returns ~2.581989 ``` The function accepts the following arguments: @@ -265,7 +265,7 @@ Computes the [standard deviation][standard-deviation] of a double-precision floa const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; double v = stdlib_strided_dstdev_ndarray( 4, 1.0, x, 2, 0 ); -// returns 2.581989 +// returns ~2.581989 ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/stats/strided/dstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dstdev/benchmark/benchmark.js index fc600fbb41e3..91d0875b7159 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdev/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dstdev = require( './../lib/dstdev.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdev/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dstdev/benchmark/benchmark.native.js index 22ea90c9b406..aa38fea52b75 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdev/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdev/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdev/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dstdev/benchmark/benchmark.ndarray.js index 5fad9d217a87..9df9cc5e719d 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdev/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdev/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dstdev = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdev/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dstdev/benchmark/benchmark.ndarray.native.js index 69a33425adc3..61a516d97af0 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdev/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdev/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevch/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dstdevch/benchmark/benchmark.js index e293dfac89c4..14f9a662bfac 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevch/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevch/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dstdevch = require( './../lib/dstdevch.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevch/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dstdevch/benchmark/benchmark.native.js index 3d680452f883..5f3ddd9d88db 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevch/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevch/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevch/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dstdevch/benchmark/benchmark.ndarray.js index 6a2b84a06466..e66a7de1a5ee 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevch/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevch/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dstdevch = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevch/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dstdevch/benchmark/benchmark.ndarray.native.js index a3384a6f640f..274d1d1aea04 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevch/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevch/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dstdevpn/benchmark/benchmark.js index b9c40c03d032..84fe00f45162 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevpn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dstdevpn = require( './../lib/dstdevpn.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevpn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dstdevpn/benchmark/benchmark.native.js index 3d0f049c61a6..673da282ed88 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevpn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevpn/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dstdevpn/benchmark/benchmark.ndarray.js index 2177c70d721d..03de5fcb9731 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevpn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dstdevpn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevpn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dstdevpn/benchmark/benchmark.ndarray.native.js index a740a6d40788..65a78adc98f5 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevpn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevpn/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dstdevtk/benchmark/benchmark.js index ce261d8edb57..ebc385e0e8e0 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevtk/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dstdevtk = require( './../lib/dstdevtk.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevtk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dstdevtk/benchmark/benchmark.native.js index 4d3ffbd627f9..99f23ea647d7 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevtk/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevtk/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevtk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dstdevtk/benchmark/benchmark.ndarray.js index 56ad37d59c58..f514d5c4dfa4 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevtk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevtk/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dstdevtk = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevtk/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dstdevtk/benchmark/benchmark.ndarray.native.js index 1bc02acdf3d5..f8fd2fc5e5a9 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevtk/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevtk/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dstdevwd/benchmark/benchmark.js index fd734cce4bdc..8cbb678ce368 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevwd/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dstdevwd = require( './../lib/dstdevwd.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dstdevwd/benchmark/benchmark.native.js index 733b58adcee3..8e73afe9174a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevwd/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dstdevwd/benchmark/benchmark.ndarray.js index 08a051367437..28c945ed92ee 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevwd/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dstdevwd = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dstdevwd/benchmark/benchmark.ndarray.native.js index 981c49d987bf..b0b25773c469 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevwd/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dstdevyc/benchmark/benchmark.js index fdaa90ba5b16..287d326475ea 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevyc/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dstdevyc = require( './../lib/dstdevyc.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevyc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dstdevyc/benchmark/benchmark.native.js index 7ef9f39500ca..be9a39ce4081 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevyc/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevyc/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dstdevyc/benchmark/benchmark.ndarray.js index 8d803b63b623..893addb68add 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevyc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevyc/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dstdevyc = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dstdevyc/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dstdevyc/benchmark/benchmark.ndarray.native.js index 9327ea32445f..1a43ff80fc11 100644 --- a/lib/node_modules/@stdlib/stats/strided/dstdevyc/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dstdevyc/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsvariance/README.md b/lib/node_modules/@stdlib/stats/strided/dsvariance/README.md index 8e98a1900c9b..ed609ccfc1bd 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsvariance/README.md +++ b/lib/node_modules/@stdlib/stats/strided/dsvariance/README.md @@ -241,7 +241,7 @@ console.log( v ); Computes the [variance][variance] of a single-precision floating-point strided array using extended accumulation and returning an extended precision result. ```c -const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f } +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; double v = stdlib_strided_dsvariance( 8, 1.0f, x, 1 ); // returns 6.0 @@ -263,7 +263,7 @@ double stdlib_strided_dsvariance( const CBLAS_INT N, const float correction, con Computes the [variance][variance] of a single-precision floating-point strided array using extended accumulation and alternative indexing semantics and returning an extended precision result. ```c -const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f } +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; double v = stdlib_strided_dsvariance_ndarray( 4, 1.0f, x, 2, 0 ); // returns ~6.666667 diff --git a/lib/node_modules/@stdlib/stats/strided/dsvariance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsvariance/benchmark/benchmark.js index 8739bf420ad6..ba483e35e0a1 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsvariance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsvariance/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsvariance = require( './../lib/dsvariance.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsvariance/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsvariance/benchmark/benchmark.native.js index b7b815997153..9ee4229e4b64 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsvariance/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsvariance/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsvariance/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsvariance/benchmark/benchmark.ndarray.js index 80a6748a3673..bd5c3360bc0d 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsvariance/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsvariance/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsvariance = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsvariance/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsvariance/benchmark/benchmark.ndarray.native.js index 0230b73e704d..b815d89ec185 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsvariance/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsvariance/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsvariancepn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dsvariancepn/benchmark/benchmark.js index 73880b7cafcf..937531e96a82 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsvariancepn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dsvariancepn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsvariancepn = require( './../lib/dsvariancepn.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsvariancepn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dsvariancepn/benchmark/benchmark.native.js index b518b577e88a..2b39c775740f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsvariancepn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsvariancepn/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsvariancepn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dsvariancepn/benchmark/benchmark.ndarray.js index 959eba6c4172..e664a89bbe0a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsvariancepn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dsvariancepn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dsvariancepn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dsvariancepn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dsvariancepn/benchmark/benchmark.ndarray.native.js index 956282359e80..3b54c8140aec 100644 --- a/lib/node_modules/@stdlib/stats/strided/dsvariancepn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dsvariancepn/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariance/README.md b/lib/node_modules/@stdlib/stats/strided/dvariance/README.md index ddea8cdca0dc..eaaa545c0a77 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariance/README.md +++ b/lib/node_modules/@stdlib/stats/strided/dvariance/README.md @@ -240,7 +240,7 @@ console.log( v ); Computes the [variance][variance] of a double-precision floating-point strided array. ```c -const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 } +const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; double v = stdlib_strided_dvariance( 8, 1.0, x, 1 ); // returns 6.0 @@ -262,7 +262,7 @@ double stdlib_strided_dvariance( const CBLAS_INT N, const double correction, con Computes the [variance][variance] of a double-precision floating-point strided array using alternative indexing semantics. ```c -const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 } +const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; double v = stdlib_strided_dvariance_ndarray( 4, 1.0, x, 2, 0 ); // returns ~6.666667 diff --git a/lib/node_modules/@stdlib/stats/strided/dvariance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dvariance/benchmark/benchmark.js index 893a775cfd45..a740246df5b7 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariance/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvariance = require( './../lib/dvariance.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariance/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dvariance/benchmark/benchmark.native.js index ee59c424a082..daaeeda1359f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariance/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariance/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariance/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dvariance/benchmark/benchmark.ndarray.js index 6e24cd59a1ec..42d2ace2a297 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariance/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariance/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvariance = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariance/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dvariance/benchmark/benchmark.ndarray.native.js index 30fe75ed2c01..1a178979dc04 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariance/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariance/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancech/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dvariancech/benchmark/benchmark.js index 0470cbd5aa63..088b5e93ddec 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancech/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariancech/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvariancech = require( './../lib/dvariancech.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancech/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dvariancech/benchmark/benchmark.native.js index cddb3acac4fa..d0769ce4fca4 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancech/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariancech/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancech/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dvariancech/benchmark/benchmark.ndarray.js index 9de4e23676dc..b8acd9ac1c05 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancech/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariancech/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvariancech = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancech/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dvariancech/benchmark/benchmark.ndarray.native.js index 197a1528fd9b..e582ebbb5881 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancech/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariancech/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancepn/README.md b/lib/node_modules/@stdlib/stats/strided/dvariancepn/README.md index 3f06234afb99..a826d6419ebc 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancepn/README.md +++ b/lib/node_modules/@stdlib/stats/strided/dvariancepn/README.md @@ -240,7 +240,7 @@ console.log( v ); Computes the [variance][variance] of a double-precision floating-point strided array using a two-pass algorithm. ```c -const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 } +const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; double v = stdlib_strided_dvariancepn( 8, 1.0, x, 1 ); // returns 6.0 @@ -262,7 +262,7 @@ double stdlib_strided_dvariancepn( const CBLAS_INT N, const double correction, c Computes the [variance][variance] of a double-precision floating-point strided array using a two-pass algorithm and alternative indexing semantics. ```c -const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 } +const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; double v = stdlib_strided_dvariancepn_ndarray( 4, 1.0, x, 2, 0 ); // returns ~6.666667 diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancepn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dvariancepn/benchmark/benchmark.js index 2342b8e870c3..10c54a38601a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancepn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariancepn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvariancepn = require( './../lib/dvariancepn.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancepn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dvariancepn/benchmark/benchmark.native.js index 3125afb31d09..8958e300db91 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancepn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariancepn/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancepn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dvariancepn/benchmark/benchmark.ndarray.js index be29051dbeb2..d6f2e5bb9ec0 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancepn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariancepn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvariancepn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancepn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dvariancepn/benchmark/benchmark.ndarray.native.js index 2bf36c6723d9..1343f5a32400 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancepn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariancepn/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancetk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dvariancetk/benchmark/benchmark.js index 6ad125cec9d0..26356cce2cfb 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancetk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariancetk/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvariancetk = require( './../lib/dvariancetk.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancetk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dvariancetk/benchmark/benchmark.native.js index d0a0bb747b72..adeaf58f3450 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancetk/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariancetk/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancetk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dvariancetk/benchmark/benchmark.ndarray.js index 175134c16726..bbe535b43f92 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancetk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariancetk/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvariancetk = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancetk/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dvariancetk/benchmark/benchmark.ndarray.native.js index 5e0f4a0ff38a..6c4aa9b7b695 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancetk/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariancetk/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancewd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dvariancewd/benchmark/benchmark.js index 975c3876f50d..482db55dba9c 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancewd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariancewd/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvariancewd = require( './../lib/dvariancewd.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancewd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dvariancewd/benchmark/benchmark.native.js index 4214cbf9c5e6..a325a729961c 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancewd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariancewd/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancewd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dvariancewd/benchmark/benchmark.ndarray.js index 5a72089b2366..cf592a366acc 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancewd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariancewd/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvariancewd = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvariancewd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dvariancewd/benchmark/benchmark.ndarray.native.js index 6897d45f635b..864212c574da 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvariancewd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvariancewd/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvarianceyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dvarianceyc/benchmark/benchmark.js index fb7253b382ae..26253ecb5230 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarianceyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dvarianceyc/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvarianceyc = require( './../lib/dvarianceyc.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvarianceyc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dvarianceyc/benchmark/benchmark.native.js index b325107e061e..85f3be703832 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarianceyc/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvarianceyc/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvarianceyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dvarianceyc/benchmark/benchmark.ndarray.js index 2d030e8aedf6..6374bf96afb3 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarianceyc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dvarianceyc/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvarianceyc = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvarianceyc/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dvarianceyc/benchmark/benchmark.ndarray.native.js index fd3493682804..f137722a0363 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarianceyc/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvarianceyc/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvarm/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dvarm/benchmark/benchmark.js index eb2ea131cf99..a7b8e6506c35 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarm/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dvarm/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvarm = require( './../lib/dvarm.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvarm/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dvarm/benchmark/benchmark.native.js index 7f682e151f07..391ccbddcb4d 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarm/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvarm/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvarm/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dvarm/benchmark/benchmark.ndarray.js index e7b29bf86035..1af74a1a96fc 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarm/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dvarm/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvarm = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvarm/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dvarm/benchmark/benchmark.ndarray.native.js index 28d04f6443cd..c19683879a87 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarm/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvarm/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvarmpn/README.md b/lib/node_modules/@stdlib/stats/strided/dvarmpn/README.md index 0810b2b28309..20e39b3f26e4 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarmpn/README.md +++ b/lib/node_modules/@stdlib/stats/strided/dvarmpn/README.md @@ -267,7 +267,7 @@ Computes the [variance][variance] of a double-precision floating-point strided a const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; double v = stdlib_strided_dvarmpn_ndarray( 4, 1.0, 1.25, x, 2, 0 ); -// returns 6.25 +// returns ~6.67 ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/stats/strided/dvarmpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dvarmpn/benchmark/benchmark.js index bd87d372de19..889a5d4477ad 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarmpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dvarmpn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvarmpn = require( './../lib/dvarmpn.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvarmpn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dvarmpn/benchmark/benchmark.native.js index 635ad4e41332..dd4acd6a2792 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarmpn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvarmpn/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvarmpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dvarmpn/benchmark/benchmark.ndarray.js index e3a4ed156dcb..4de2377c6253 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarmpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dvarmpn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvarmpn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvarmpn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dvarmpn/benchmark/benchmark.ndarray.native.js index a3876630f73f..f06cd2d89250 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarmpn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvarmpn/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvarmtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dvarmtk/benchmark/benchmark.js index c5ce5e5ce17a..688017232aa8 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarmtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dvarmtk/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvarmtk = require( './../lib/dvarmtk.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvarmtk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dvarmtk/benchmark/benchmark.native.js index 83cfcf086263..954853fc00d8 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarmtk/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvarmtk/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvarmtk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dvarmtk/benchmark/benchmark.ndarray.js index fabb66a52bc3..e63ef40a52ca 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarmtk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dvarmtk/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dvarmtk = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/dvarmtk/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dvarmtk/benchmark/benchmark.ndarray.native.js index 137c137ba838..456e6c9988b2 100644 --- a/lib/node_modules/@stdlib/stats/strided/dvarmtk/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dvarmtk/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/lib/index.js b/lib/node_modules/@stdlib/stats/strided/lib/index.js index 5f012a856df0..bceaaff61a76 100644 --- a/lib/node_modules/@stdlib/stats/strided/lib/index.js +++ b/lib/node_modules/@stdlib/stats/strided/lib/index.js @@ -351,6 +351,15 @@ setReadOnly( ns, 'dmskmin', require( '@stdlib/stats/strided/dmskmin' ) ); */ setReadOnly( ns, 'dmskrange', require( '@stdlib/stats/strided/dmskrange' ) ); +/** +* @name dnancount +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/strided/dnancount} +*/ +setReadOnly( ns, 'dnancount', require( '@stdlib/stats/strided/dnancount' ) ); + /** * @name dnanmax * @memberof ns @@ -450,6 +459,15 @@ setReadOnly( ns, 'dnanminabs', require( '@stdlib/stats/strided/dnanminabs' ) ); */ setReadOnly( ns, 'dnanmskmax', require( '@stdlib/stats/strided/dnanmskmax' ) ); +/** +* @name dnanmskmaxabs +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/strided/dnanmskmaxabs} +*/ +setReadOnly( ns, 'dnanmskmaxabs', require( '@stdlib/stats/strided/dnanmskmaxabs' ) ); + /** * @name dnanmskmidrange * @memberof ns @@ -468,6 +486,15 @@ setReadOnly( ns, 'dnanmskmidrange', require( '@stdlib/stats/strided/dnanmskmidra */ setReadOnly( ns, 'dnanmskmin', require( '@stdlib/stats/strided/dnanmskmin' ) ); +/** +* @name dnanmskminabs +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/strided/dnanmskminabs} +*/ +setReadOnly( ns, 'dnanmskminabs', require( '@stdlib/stats/strided/dnanmskminabs' ) ); + /** * @name dnanmskrange * @memberof ns @@ -486,6 +513,15 @@ setReadOnly( ns, 'dnanmskrange', require( '@stdlib/stats/strided/dnanmskrange' ) */ setReadOnly( ns, 'dnanrange', require( '@stdlib/stats/strided/dnanrange' ) ); +/** +* @name dnanrangeabs +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/strided/dnanrangeabs} +*/ +setReadOnly( ns, 'dnanrangeabs', require( '@stdlib/stats/strided/dnanrangeabs' ) ); + /** * @name dnanstdev * @memberof ns @@ -594,6 +630,15 @@ setReadOnly( ns, 'dnanvariancewd', require( '@stdlib/stats/strided/dnanvariancew */ setReadOnly( ns, 'dnanvarianceyc', require( '@stdlib/stats/strided/dnanvarianceyc' ) ); +/** +* @name dpcorrwd +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/strided/dpcorrwd} +*/ +setReadOnly( ns, 'dpcorrwd', require( '@stdlib/stats/strided/dpcorrwd' ) ); + /** * @name drange * @memberof ns @@ -1116,6 +1161,15 @@ setReadOnly( ns, 'mskmidrange', require( '@stdlib/stats/strided/mskmidrange' ) ) */ setReadOnly( ns, 'mskmin', require( '@stdlib/stats/strided/mskmin' ) ); +/** +* @name mskminabs +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/strided/mskminabs} +*/ +setReadOnly( ns, 'mskminabs', require( '@stdlib/stats/strided/mskminabs' ) ); + /** * @name mskrange * @memberof ns @@ -1125,6 +1179,15 @@ setReadOnly( ns, 'mskmin', require( '@stdlib/stats/strided/mskmin' ) ); */ setReadOnly( ns, 'mskrange', require( '@stdlib/stats/strided/mskrange' ) ); +/** +* @name nancount +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/strided/nancount} +*/ +setReadOnly( ns, 'nancount', require( '@stdlib/stats/strided/nancount' ) ); + /** * @name nanmax * @memberof ns @@ -1287,6 +1350,15 @@ setReadOnly( ns, 'nanrange', require( '@stdlib/stats/strided/nanrange' ) ); */ setReadOnly( ns, 'nanrangeBy', require( '@stdlib/stats/strided/nanrange-by' ) ); +/** +* @name nanrangeabs +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/strided/nanrangeabs} +*/ +setReadOnly( ns, 'nanrangeabs', require( '@stdlib/stats/strided/nanrangeabs' ) ); + /** * @name nanstdev * @memberof ns @@ -1701,6 +1773,15 @@ setReadOnly( ns, 'smskmin', require( '@stdlib/stats/strided/smskmin' ) ); */ setReadOnly( ns, 'smskrange', require( '@stdlib/stats/strided/smskrange' ) ); +/** +* @name snancount +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/strided/snancount} +*/ +setReadOnly( ns, 'snancount', require( '@stdlib/stats/strided/snancount' ) ); + /** * @name snanmax * @memberof ns @@ -1791,6 +1872,15 @@ setReadOnly( ns, 'snanminabs', require( '@stdlib/stats/strided/snanminabs' ) ); */ setReadOnly( ns, 'snanmskmax', require( '@stdlib/stats/strided/snanmskmax' ) ); +/** +* @name snanmskmaxabs +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/strided/snanmskmaxabs} +*/ +setReadOnly( ns, 'snanmskmaxabs', require( '@stdlib/stats/strided/snanmskmaxabs' ) ); + /** * @name snanmskmidrange * @memberof ns @@ -1809,6 +1899,15 @@ setReadOnly( ns, 'snanmskmidrange', require( '@stdlib/stats/strided/snanmskmidra */ setReadOnly( ns, 'snanmskmin', require( '@stdlib/stats/strided/snanmskmin' ) ); +/** +* @name snanmskminabs +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/stats/strided/snanmskminabs} +*/ +setReadOnly( ns, 'snanmskminabs', require( '@stdlib/stats/strided/snanmskminabs' ) ); + /** * @name snanmskrange * @memberof ns diff --git a/lib/node_modules/@stdlib/stats/strided/max-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/max-by/benchmark/benchmark.js index 0155c822fb00..441cc2b3d116 100644 --- a/lib/node_modules/@stdlib/stats/strided/max-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/max-by/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var maxBy = require( './../lib/main.js' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/max-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/max-by/benchmark/benchmark.ndarray.js index c0c09751b561..1c4bda7dd44f 100644 --- a/lib/node_modules/@stdlib/stats/strided/max-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/max-by/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var maxBy = require( './../lib/ndarray.js' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/max/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/max/benchmark/benchmark.js index 70815f237496..7c2d35782cd1 100644 --- a/lib/node_modules/@stdlib/stats/strided/max/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/max/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var max = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/max/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/max/benchmark/benchmark.ndarray.js index 3b126e28bfa8..71b3c572e997 100644 --- a/lib/node_modules/@stdlib/stats/strided/max/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/max/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var uniform = require( '@stdlib/random/array/uniform' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var max = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/maxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/maxabs/benchmark/benchmark.js index c3a080f73f5c..8044a6df47d6 100644 --- a/lib/node_modules/@stdlib/stats/strided/maxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/maxabs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var maxabs = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/maxabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/maxabs/benchmark/benchmark.ndarray.js index 0f0f3f1f8b66..ca479a1c84af 100644 --- a/lib/node_modules/@stdlib/stats/strided/maxabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/maxabs/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var maxabs = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/maxsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/maxsorted/benchmark/benchmark.js index 78153d6dcd68..4a7f80fa5793 100644 --- a/lib/node_modules/@stdlib/stats/strided/maxsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/maxsorted/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/base/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var maxsorted = require( './../lib/maxsorted.js' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/maxsorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/maxsorted/benchmark/benchmark.ndarray.js index 1f82ae0c54c6..4bd6b3ff009a 100644 --- a/lib/node_modules/@stdlib/stats/strided/maxsorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/maxsorted/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var pow = require( '@stdlib/math/base/special/pow' ); var linspace = require( '@stdlib/array/base/linspace' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var maxsorted = require( './../lib/ndarray.js' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/mean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/mean/benchmark/benchmark.js index 397afc63d117..ce0cefe91934 100644 --- a/lib/node_modules/@stdlib/stats/strided/mean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/mean/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mean = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/mean/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/mean/benchmark/benchmark.ndarray.js index fc532c5e3fa4..0e1c05dd42d4 100644 --- a/lib/node_modules/@stdlib/stats/strided/mean/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/mean/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mean = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/meankbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/meankbn/benchmark/benchmark.js index 7df28523cc21..d77aa75b292a 100644 --- a/lib/node_modules/@stdlib/stats/strided/meankbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/meankbn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meankbn = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/meankbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/meankbn/benchmark/benchmark.ndarray.js index 7757e4735a85..626ef87e2071 100644 --- a/lib/node_modules/@stdlib/stats/strided/meankbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/meankbn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meankbn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/meankbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/meankbn2/benchmark/benchmark.js index 96cf4df6fcc6..fcab29fe9e65 100644 --- a/lib/node_modules/@stdlib/stats/strided/meankbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/meankbn2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meankbn2 = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/meankbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/meankbn2/benchmark/benchmark.ndarray.js index d8ac2dc18ec2..ef0dcffedbe6 100644 --- a/lib/node_modules/@stdlib/stats/strided/meankbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/meankbn2/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meankbn2 = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/meanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/meanors/benchmark/benchmark.js index 3fd232626bfb..e73b80d691d7 100644 --- a/lib/node_modules/@stdlib/stats/strided/meanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/meanors/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanors = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/meanors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/meanors/benchmark/benchmark.ndarray.js index dce60fc5de5f..3243c731e7dc 100644 --- a/lib/node_modules/@stdlib/stats/strided/meanors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/meanors/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanors = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/meanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/meanpn/benchmark/benchmark.js index fb51d9048751..dd11d626e787 100644 --- a/lib/node_modules/@stdlib/stats/strided/meanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/meanpn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanpn = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/meanpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/meanpn/benchmark/benchmark.ndarray.js index 794f45ce2749..39b57d1d3afc 100644 --- a/lib/node_modules/@stdlib/stats/strided/meanpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/meanpn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanpn = require( './../lib/ndarray.js' ); @@ -94,7 +95,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/meanpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/meanpw/benchmark/benchmark.js index 7982cb1608b1..c6160e70aa06 100644 --- a/lib/node_modules/@stdlib/stats/strided/meanpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/meanpw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanpw = require( './../lib/meanpw.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/meanpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/meanpw/benchmark/benchmark.ndarray.js index 39bcdceb572c..029ed7e94867 100644 --- a/lib/node_modules/@stdlib/stats/strided/meanpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/meanpw/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanpw = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/meanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/meanwd/benchmark/benchmark.js index 1ae5d1cb3f97..5609e4c9ea46 100644 --- a/lib/node_modules/@stdlib/stats/strided/meanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/meanwd/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanwd = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/meanwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/meanwd/benchmark/benchmark.ndarray.js index b61345244d18..044bb8a1e436 100644 --- a/lib/node_modules/@stdlib/stats/strided/meanwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/meanwd/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var meanwd = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/mediansorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/mediansorted/benchmark/benchmark.js index b547cffa3cd3..0e9b87104e71 100644 --- a/lib/node_modules/@stdlib/stats/strided/mediansorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/mediansorted/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/base/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mediansorted = require( './../lib/mediansorted.js' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/mediansorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/mediansorted/benchmark/benchmark.ndarray.js index 7bf4b7d44fc9..7e8d88c18862 100644 --- a/lib/node_modules/@stdlib/stats/strided/mediansorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/mediansorted/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/base/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mediansorted = require( './../lib/ndarray.js' ); @@ -88,7 +89,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/midrangeabs/README.md b/lib/node_modules/@stdlib/stats/strided/midrangeabs/README.md new file mode 100644 index 000000000000..48f25f7a833a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/midrangeabs/README.md @@ -0,0 +1,170 @@ + + +# midrangeabs + +> Calculate the [mid-range][mid-range] of absolute values of a strided array. + +
+ +The [**mid-range**][mid-range] of absolute values is the arithmetic mean of the maximum and minimum absolute values in a data set. The measure is the midpoint of the range and a measure of central tendency. + +
+ + + +
+ +## Usage + +```javascript +var midrangeabs = require( '@stdlib/stats/strided/midrangeabs' ); +``` + +#### midrangeabs( N, x, strideX ) + +Computes the [mid-range][mid-range] of absolute values of a strided array. + +```javascript +var x = [ 1.0, -2.0, 2.0 ]; + +var v = midrangeabs( x.length, x, 1 ); +// returns 1.5 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. +- **strideX**: stride length for `x`. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [mid-range][mid-range] of absolute values of every other element in `x`, + +```javascript +var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ]; + +var v = midrangeabs( 4, x, 2 ); +// returns 2.5 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +var v = midrangeabs( 4, x1, 2 ); +// returns 2.5 +``` + +#### midrangeabs.ndarray( N, x, strideX, offsetX ) + +Computes the [mid-range][mid-range] of absolute values of a strided array using alternative indexing semantics. + +```javascript +var x = [ 1.0, -2.0, 2.0 ]; + +var v = midrangeabs.ndarray( x.length, x, 1, 0 ); +// returns 1.5 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [mid-range][mid-range] of absolute values for every other element in `x` starting from the second element + +```javascript +var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; + +var v = midrangeabs.ndarray( 4, x, 2, 1 ); +// returns 2.5 +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `NaN`. +- Depending on the environment, the typed versions ([`dmidrangeabs`][@stdlib/stats/strided/dmidrangeabs], [`smidrangeabs`][@stdlib/stats/strided/smidrangeabs], etc.) are likely to be significantly more performant. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var midrangeabs = require( '@stdlib/stats/strided/midrangeabs' ); + +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); +console.log( x ); + +var v = midrangeabs( x.length, x, 1 ); +console.log( v ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mid-range]: https://en.wikipedia.org/wiki/Mid-range + +[mdn-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + +[@stdlib/stats/strided/dmidrangeabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmidrangeabs + +[@stdlib/stats/strided/smidrangeabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/smidrangeabs + +
+ + diff --git a/lib/node_modules/@stdlib/stats/strided/midrangeabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/midrangeabs/benchmark/benchmark.js new file mode 100644 index 000000000000..868e5b4feb66 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/midrangeabs/benchmark/benchmark.js @@ -0,0 +1,103 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var midrangeabs = require( './../lib/main.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -10, 10, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = midrangeabs( x.length, x, 1 ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/midrangeabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/midrangeabs/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..4d10210c7913 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/midrangeabs/benchmark/benchmark.ndarray.js @@ -0,0 +1,103 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var midrangeabs = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -10, 10, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = midrangeabs( x.length, x, 1, 0 ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/midrangeabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/midrangeabs/docs/repl.txt new file mode 100644 index 000000000000..26b066da2642 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/midrangeabs/docs/repl.txt @@ -0,0 +1,89 @@ + +{{alias}}( N, x, strideX ) + Computes the mid-range of absolute values of a strided array. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `NaN`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Array|TypedArray + Input array. + + strideX: integer + Stride length. + + Returns + ------- + out: number + Mid-range of absolute values. + + Examples + -------- + // Standard Usage: + > var x = [ 1.0, -2.0, 2.0 ]; + > {{alias}}( x.length, x, 1 ) + 1.5 + + // Using `N` and stride parameters: + > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ]; + > {{alias}}( 3, x, 2 ) + 1.5 + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 3, x1, 2 ) + 1.5 + + +{{alias}}.ndarray( N, x, strideX, offsetX ) + Computes the mid-range of absolute values of a strided array using + alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Array|TypedArray + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + out: number + Mid-range of absolute values. + + Examples + -------- + // Standard Usage: + > var x = [ 1.0, -2.0, 2.0 ]; + > {{alias}}.ndarray( x.length, x, 1, 0 ) + 1.5 + + // Using offset parameter: + > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ]; + > {{alias}}.ndarray( 3, x, 2, 1 ) + 1.5 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/strided/midrangeabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/strided/midrangeabs/docs/types/index.d.ts new file mode 100644 index 000000000000..fe075bf2c45e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/midrangeabs/docs/types/index.d.ts @@ -0,0 +1,93 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { NumericArray, Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = NumericArray | Collection | AccessorArrayLike; + +/** +* Interface describing `midrangeabs`. +*/ +interface Routine { + /** + * Computes the mid-range of absolute values of a strided array. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length + * @returns mid-range of absolute values + * + * @example + * var x = [ 1.0, -2.0, 2.0 ]; + * + * var v = midrangeabs( x.length, x, 1 ); + * // returns 1.5 + */ + ( N: number, x: InputArray, strideX: number ): number; + + /** + * Computes the mid-range of absolute values of a strided array using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns mid-range of absolute values + * + * @example + * var x = [ 1.0, -2.0, 2.0 ]; + * + * var v = midrangeabs.ndarray( x.length, x, 1, 0 ); + * // returns 1.5 + */ + ndarray( N: number, x: InputArray, strideX: number, offsetX: number ): number; +} + +/** +* Computes the mid-range of absolute values of a strided array. +* +* @param N - number of indexed elements +* @param x - input array +* @param strideX - stride length +* @returns mid-range of absolute values +* +* @example +* var x = [ 1.0, -2.0, 2.0 ]; +* +* var v = midrangeabs( x.length, x, 1 ); +* // returns 1.5 +* +* @example +* var x = [ 1.0, -2.0, 2.0 ]; +* +* var v = midrangeabs.ndarray( x.length, x, 1, 0 ); +* // returns 1.5 +*/ +declare var midrangeabs: Routine; + + +// EXPORTS // + +export = midrangeabs; diff --git a/lib/node_modules/@stdlib/stats/strided/midrangeabs/docs/types/test.ts b/lib/node_modules/@stdlib/stats/strided/midrangeabs/docs/types/test.ts new file mode 100644 index 000000000000..e24855497fb0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/midrangeabs/docs/types/test.ts @@ -0,0 +1,156 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import midrangeabs = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = new Float64Array( 10 ); + + midrangeabs( x.length, x, 1 ); // $ExpectType number + midrangeabs( x.length, new AccessorArray( x ), 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + midrangeabs( '10', x, 1 ); // $ExpectError + midrangeabs( true, x, 1 ); // $ExpectError + midrangeabs( false, x, 1 ); // $ExpectError + midrangeabs( null, x, 1 ); // $ExpectError + midrangeabs( undefined, x, 1 ); // $ExpectError + midrangeabs( [], x, 1 ); // $ExpectError + midrangeabs( {}, x, 1 ); // $ExpectError + midrangeabs( ( x: number ): number => x, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a numeric array... +{ + const x = new Float64Array( 10 ); + + midrangeabs( x.length, 10, 1 ); // $ExpectError + midrangeabs( x.length, true, 1 ); // $ExpectError + midrangeabs( x.length, false, 1 ); // $ExpectError + midrangeabs( x.length, null, 1 ); // $ExpectError + midrangeabs( x.length, undefined, 1 ); // $ExpectError + midrangeabs( x.length, {}, 1 ); // $ExpectError + midrangeabs( x.length, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + + midrangeabs( x.length, x, '10' ); // $ExpectError + midrangeabs( x.length, x, true ); // $ExpectError + midrangeabs( x.length, x, false ); // $ExpectError + midrangeabs( x.length, x, null ); // $ExpectError + midrangeabs( x.length, x, undefined ); // $ExpectError + midrangeabs( x.length, x, [] ); // $ExpectError + midrangeabs( x.length, x, {} ); // $ExpectError + midrangeabs( x.length, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + midrangeabs(); // $ExpectError + midrangeabs( x.length ); // $ExpectError + midrangeabs( x.length, x ); // $ExpectError + midrangeabs( x.length, x, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + const x = new Float64Array( 10 ); + + midrangeabs.ndarray( x.length, x, 1, 0 ); // $ExpectType number + midrangeabs.ndarray( x.length, new AccessorArray( x ), 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + midrangeabs.ndarray( '10', x, 1, 0 ); // $ExpectError + midrangeabs.ndarray( true, x, 1, 0 ); // $ExpectError + midrangeabs.ndarray( false, x, 1, 0 ); // $ExpectError + midrangeabs.ndarray( null, x, 1, 0 ); // $ExpectError + midrangeabs.ndarray( undefined, x, 1, 0 ); // $ExpectError + midrangeabs.ndarray( [], x, 1, 0 ); // $ExpectError + midrangeabs.ndarray( {}, x, 1, 0 ); // $ExpectError + midrangeabs.ndarray( ( x: number ): number => x, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a numeric array... +{ + const x = new Float64Array( 10 ); + + midrangeabs.ndarray( x.length, 10, 1, 0 ); // $ExpectError + midrangeabs.ndarray( x.length, true, 1, 0 ); // $ExpectError + midrangeabs.ndarray( x.length, false, 1, 0 ); // $ExpectError + midrangeabs.ndarray( x.length, null, 1, 0 ); // $ExpectError + midrangeabs.ndarray( x.length, undefined, 1, 0 ); // $ExpectError + midrangeabs.ndarray( x.length, {}, 1, 0 ); // $ExpectError + midrangeabs.ndarray( x.length, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + + midrangeabs.ndarray( x.length, x, '10', 0 ); // $ExpectError + midrangeabs.ndarray( x.length, x, true, 0 ); // $ExpectError + midrangeabs.ndarray( x.length, x, false, 0 ); // $ExpectError + midrangeabs.ndarray( x.length, x, null, 0 ); // $ExpectError + midrangeabs.ndarray( x.length, x, undefined, 0 ); // $ExpectError + midrangeabs.ndarray( x.length, x, [], 0 ); // $ExpectError + midrangeabs.ndarray( x.length, x, {}, 0 ); // $ExpectError + midrangeabs.ndarray( x.length, x, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + midrangeabs.ndarray( x.length, x, 1, '10' ); // $ExpectError + midrangeabs.ndarray( x.length, x, 1, true ); // $ExpectError + midrangeabs.ndarray( x.length, x, 1, false ); // $ExpectError + midrangeabs.ndarray( x.length, x, 1, null ); // $ExpectError + midrangeabs.ndarray( x.length, x, 1, undefined ); // $ExpectError + midrangeabs.ndarray( x.length, x, 1, [] ); // $ExpectError + midrangeabs.ndarray( x.length, x, 1, {} ); // $ExpectError + midrangeabs.ndarray( x.length, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + midrangeabs.ndarray(); // $ExpectError + midrangeabs.ndarray( x.length ); // $ExpectError + midrangeabs.ndarray( x.length, x ); // $ExpectError + midrangeabs.ndarray( x.length, x, 1 ); // $ExpectError + midrangeabs.ndarray( x.length, x, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/strided/midrangeabs/examples/index.js b/lib/node_modules/@stdlib/stats/strided/midrangeabs/examples/index.js new file mode 100644 index 000000000000..5688cae6384e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/midrangeabs/examples/index.js @@ -0,0 +1,30 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var midrangeabs = require( './../lib' ); + +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); +console.log( x ); + +var v = midrangeabs( x.length, x, 1 ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/strided/midrangeabs/lib/accessors.js b/lib/node_modules/@stdlib/stats/strided/midrangeabs/lib/accessors.js new file mode 100644 index 000000000000..b748e0689abf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/midrangeabs/lib/accessors.js @@ -0,0 +1,89 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); + + +// MAIN // + +/** +* Computes the mid-range of absolute values of a strided array. +* +* @private +* @param {PositiveInteger} N - number of indexed elements +* @param {Object} x - input array object +* @param {Collection} x.data - input array data +* @param {Array} x.accessors - array element accessors +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {number} mid-range of absolute values +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = toAccessorArray( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +* +* var v = midrangeabs( 4, arraylike2object( x ), 2, 1 ); +* // returns 2.5 +*/ +function midrangeabs( N, x, strideX, offsetX ) { + var xbuf; + var get; + var max; + var min; + var ix; + var v; + var i; + + // Cache reference to array data: + xbuf = x.data; + + // Cache a reference to the element accessor: + get = x.accessors[ 0 ]; + + if ( N === 1 || strideX === 0 ) { + return abs( get( xbuf, offsetX ) ); + } + ix = offsetX; + min = abs( get( xbuf, ix ) ); + max = min; + for ( i = 1; i < N; i++ ) { + ix += strideX; + v = abs( get( xbuf, ix ) ); + if ( isnan( v ) ) { + return v; + } + if ( v < min ) { + min = v; + } else if ( v > max ) { + max = v; + } + } + return ( max + min ) / 2.0; +} + + +// EXPORTS // + +module.exports = midrangeabs; diff --git a/lib/node_modules/@stdlib/stats/strided/midrangeabs/lib/index.js b/lib/node_modules/@stdlib/stats/strided/midrangeabs/lib/index.js new file mode 100644 index 000000000000..89df246a2489 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/midrangeabs/lib/index.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the mid-range of absolute values of a strided array. +* +* @module @stdlib/stats/strided/midrangeabs +* +* @example +* var midrangeabs = require( '@stdlib/stats/strided/midrangeabs' ); +* +* var x = [ 1.0, -2.0, 2.0 ]; +* +* var v = midrangeabs( x.length, x, 1 ); +* // returns 1.5 +* +* @example +* var midrangeabs = require( '@stdlib/stats/strided/midrangeabs' ); +* +* var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; +* +* var v = midrangeabs.ndarray( 4, x, 2, 1 ); +* // returns 2.5 +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; + +// exports: { "ndarray": "main.ndarray" } diff --git a/lib/node_modules/@stdlib/stats/strided/midrangeabs/lib/main.js b/lib/node_modules/@stdlib/stats/strided/midrangeabs/lib/main.js new file mode 100644 index 000000000000..b1fb4f473412 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/midrangeabs/lib/main.js @@ -0,0 +1,50 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Computes the mid-range of absolute values of a strided array. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {NumericArray} x - input array +* @param {integer} strideX - stride length +* @returns {number} mid-range of absolute values +* +* @example +* var x = [ 1.0, -2.0, 2.0 ]; +* +* var v = midrangeabs( x.length, x, 1 ); +* // returns 1.5 +*/ +function midrangeabs( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); +} + + +// EXPORTS // + +module.exports = midrangeabs; diff --git a/lib/node_modules/@stdlib/stats/strided/midrangeabs/lib/ndarray.js b/lib/node_modules/@stdlib/stats/strided/midrangeabs/lib/ndarray.js new file mode 100644 index 000000000000..fea0e2274a4f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/midrangeabs/lib/ndarray.js @@ -0,0 +1,85 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var accessors = require( './accessors.js' ); + + +// MAIN // + +/** +* Computes the mid-range of absolute values of a strided array. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {NumericArray} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {number} mid-range of absolute values +* +* @example +* var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; +* +* var v = midrangeabs( 4, x, 2, 1 ); +* // returns 2.5 +*/ +function midrangeabs( N, x, strideX, offsetX ) { + var max; + var min; + var ix; + var o; + var v; + var i; + + if ( N <= 0 ) { + return NaN; + } + o = arraylike2object( x ); + if ( o.accessorProtocol ) { + return accessors( N, o, strideX, offsetX ); + } + if ( N === 1 || strideX === 0 ) { + return abs( x[ offsetX ] ); + } + ix = offsetX; + min = abs( x[ ix ] ); + max = min; + for ( i = 1; i < N; i++ ) { + ix += strideX; + v = abs( x[ ix ] ); + if ( isnan( v ) ) { + return v; + } + if ( v < min ) { + min = v; + } else if ( v > max ) { + max = v; + } + } + return ( max + min ) / 2.0; +} + + +// EXPORTS // + +module.exports = midrangeabs; diff --git a/lib/node_modules/@stdlib/stats/strided/midrangeabs/package.json b/lib/node_modules/@stdlib/stats/strided/midrangeabs/package.json new file mode 100644 index 000000000000..f0a46a4a053e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/midrangeabs/package.json @@ -0,0 +1,74 @@ +{ + "name": "@stdlib/stats/strided/midrangeabs", + "version": "0.0.0", + "description": "Calculate the mid-range of absolute values of a strided array.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "minimum", + "min", + "maximum", + "max", + "midrange", + "absolute", + "abs", + "extremes", + "dispersion", + "domain", + "extent", + "strided", + "strided array", + "array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/strided/midrangeabs/test/test.js b/lib/node_modules/@stdlib/stats/strided/midrangeabs/test/test.js new file mode 100644 index 000000000000..fab4f4889a28 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/midrangeabs/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var midrangeabs = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof midrangeabs, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof midrangeabs.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/midrangeabs/test/test.midrangeabs.js b/lib/node_modules/@stdlib/stats/strided/midrangeabs/test/test.midrangeabs.js new file mode 100644 index 000000000000..45b39ef30746 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/midrangeabs/test/test.midrangeabs.js @@ -0,0 +1,336 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var midrangeabs = require( './../lib/main.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof midrangeabs, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 3', function test( t ) { + t.strictEqual( midrangeabs.length, 3, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the mid-range of absolute values of a strided array', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ]; + v = midrangeabs( x.length, x, 1 ); + t.strictEqual( v, 2.5, 'returns expected value' ); + + x = [ -4.0, -5.0 ]; + v = midrangeabs( x.length, x, 1 ); + t.strictEqual( v, 4.5, 'returns expected value' ); + + x = [ -0.0, 0.0, -0.0 ]; + v = midrangeabs( x.length, x, 1 ); + t.strictEqual( isPositiveZero( v ), true, 'returns expected value' ); + + x = [ -0.0, -0.0 ]; + v = midrangeabs( x.length, x, 1 ); + t.strictEqual( isPositiveZero( v ), true, 'returns expected value' ); + + x = [ NaN ]; + v = midrangeabs( x.length, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ NaN, NaN ]; + v = midrangeabs( x.length, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function calculates the mid-range of absolute values of a strided array (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ]; + v = midrangeabs( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( v, 2.5, 'returns expected value' ); + + x = [ -4.0, -5.0 ]; + v = midrangeabs( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( v, 4.5, 'returns expected value' ); + + x = [ -0.0, 0.0, -0.0 ]; + v = midrangeabs( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( isPositiveZero( v ), true, 'returns expected value' ); + + x = [ -0.0, -0.0 ]; + v = midrangeabs( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( isPositiveZero( v ), true, 'returns expected value' ); + + x = [ NaN ]; + v = midrangeabs( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ NaN, NaN ]; + v = midrangeabs( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) { + var x; + var v; + + x = [ 1.0, 2.0, 3.0 ]; + + v = midrangeabs( 0, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = midrangeabs( -1, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN` (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, 2.0, 3.0 ]; + + v = midrangeabs( 0, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = midrangeabs( -1, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function returns the first element', function test( t ) { + var x; + var v; + + x = [ 1.0, 2.0, 3.0 ]; + + v = midrangeabs( 1, x, 1 ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + x = [ NaN, 2.0, 3.0 ]; + + v = midrangeabs( 1, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function returns the first element (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, 2.0, 3.0 ]; + + v = midrangeabs( 1, toAccessorArray( x ), 1 ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + x = [ NaN, 2.0, 3.0 ]; + + v = midrangeabs( 1, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `stride` parameter', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]; + + v = midrangeabs( 4, x, 2 ); + + t.strictEqual( v, 2.5, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]; + + v = midrangeabs( 4, toAccessorArray( x ), 2 ); + + t.strictEqual( v, 2.5, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]; + + v = midrangeabs( 4, x, -2 ); + + t.strictEqual( v, 2.5, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]; + + v = midrangeabs( 4, toAccessorArray( x ), -2 ); + + t.strictEqual( v, 2.5, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = midrangeabs( x.length, x, 0 ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = midrangeabs( x.length, x, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = midrangeabs( x.length, toAccessorArray( x ), 0 ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = midrangeabs( x.length, toAccessorArray( x ), 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var x0; + var x1; + var v; + + x0 = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + 6.0 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + + v = midrangeabs( 4, x1, 2 ); + t.strictEqual( v, 2.5, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets (accessors)', function test( t ) { + var x0; + var x1; + var v; + + x0 = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + 6.0 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + + v = midrangeabs( 4, toAccessorArray( x1 ), 2 ); + t.strictEqual( v, 2.5, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/midrangeabs/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/strided/midrangeabs/test/test.ndarray.js new file mode 100644 index 000000000000..139186f8b260 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/midrangeabs/test/test.ndarray.js @@ -0,0 +1,327 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var midrangeabs = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof midrangeabs, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', function test( t ) { + t.strictEqual( midrangeabs.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the mid-range of absolute values of a strided array', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ]; + v = midrangeabs( x.length, x, 1, 0 ); + t.strictEqual( v, 2.5, 'returns expected value' ); + + x = [ -4.0, -5.0 ]; + v = midrangeabs( x.length, x, 1, 0 ); + t.strictEqual( v, 4.5, 'returns expected value' ); + + x = [ -0.0, 0.0, -0.0 ]; + v = midrangeabs( x.length, x, 1, 0 ); + t.strictEqual( isPositiveZero( v ), true, 'returns expected value' ); + + x = [ -0.0, -0.0 ]; + v = midrangeabs( x.length, x, 1, 0 ); + t.strictEqual( isPositiveZero( v ), true, 'returns expected value' ); + + x = [ NaN ]; + v = midrangeabs( x.length, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ NaN, NaN ]; + v = midrangeabs( x.length, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function calculates the mid-range of absolute values of a strided array (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ]; + v = midrangeabs( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, 2.5, 'returns expected value' ); + + x = [ -4.0, -5.0 ]; + v = midrangeabs( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, 4.5, 'returns expected value' ); + + x = [ -0.0, 0.0, -0.0 ]; + v = midrangeabs( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isPositiveZero( v ), true, 'returns expected value' ); + + x = [ -0.0, -0.0 ]; + v = midrangeabs( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isPositiveZero( v ), true, 'returns expected value' ); + + x = [ NaN ]; + v = midrangeabs( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ NaN, NaN ]; + v = midrangeabs( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = midrangeabs( 0, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = midrangeabs( -1, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN` (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = midrangeabs( 0, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = midrangeabs( -1, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function returns the first element', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = midrangeabs( 1, x, 1, 0 ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = midrangeabs( 1, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function returns the first element (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = midrangeabs( 1, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = midrangeabs( 1, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `stride` parameter', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]; + + v = midrangeabs( 4, x, 2, 0 ); + + t.strictEqual( v, 2.5, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]; + + v = midrangeabs( 4, toAccessorArray( x ), 2, 0 ); + + t.strictEqual( v, 2.5, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]; + + v = midrangeabs( 4, x, -2, x.length-2 ); + + t.strictEqual( v, 2.5, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]; + + v = midrangeabs( 4, toAccessorArray( x ), -2, x.length-2 ); + + t.strictEqual( v, 2.5, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = midrangeabs( x.length, x, 0, 0 ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = midrangeabs( x.length, x, 0, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = midrangeabs( x.length, toAccessorArray( x ), 0, 0 ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = midrangeabs( x.length, toAccessorArray( x ), 0, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `offset` parameter', function test( t ) { + var x; + var v; + + x = [ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]; + + v = midrangeabs( 4, x, 2, 1 ); + t.strictEqual( v, 2.5, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `offset` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]; + + v = midrangeabs( 4, toAccessorArray( x ), 2, 1 ); + t.strictEqual( v, 2.5, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/min-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/min-by/benchmark/benchmark.js index fb6467914cd6..ad461ce46fd7 100644 --- a/lib/node_modules/@stdlib/stats/strided/min-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/min-by/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minBy = require( './../lib/main.js' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/min-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/min-by/benchmark/benchmark.ndarray.js index 0f1a249120c2..8cd84801b56b 100644 --- a/lib/node_modules/@stdlib/stats/strided/min-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/min-by/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minBy = require( './../lib/ndarray.js' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/min/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/min/benchmark/benchmark.js index a3fd44accdba..f5ee6095eafb 100644 --- a/lib/node_modules/@stdlib/stats/strided/min/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/min/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var min = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/min/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/min/benchmark/benchmark.ndarray.js index 4dda036ab82d..f62a44ddf340 100644 --- a/lib/node_modules/@stdlib/stats/strided/min/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/min/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var min = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/minabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/minabs/benchmark/benchmark.js index e82171e22b21..384541d5a267 100644 --- a/lib/node_modules/@stdlib/stats/strided/minabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/minabs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minabs = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/minabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/minabs/benchmark/benchmark.ndarray.js index 7606ff9e6b4e..247e64147b28 100644 --- a/lib/node_modules/@stdlib/stats/strided/minabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/minabs/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minabs = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/minsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/minsorted/benchmark/benchmark.js index ffb996d2271f..12bf892f3908 100644 --- a/lib/node_modules/@stdlib/stats/strided/minsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/minsorted/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/base/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minsorted = require( './../lib/minsorted.js' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/minsorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/minsorted/benchmark/benchmark.ndarray.js index 8ad7eaa253cf..a14285e557c6 100644 --- a/lib/node_modules/@stdlib/stats/strided/minsorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/minsorted/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var linspace = require( '@stdlib/array/base/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var minsorted = require( './../lib/ndarray.js' ); @@ -89,7 +90,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/mskmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/mskmax/benchmark/benchmark.js index c040d17db5b9..1ecaefc4952a 100644 --- a/lib/node_modules/@stdlib/stats/strided/mskmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/mskmax/benchmark/benchmark.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var uniform = require( '@stdlib/random/array/uniform' ); var bernoulli = require( '@stdlib/random/array/bernoulli' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskmax = require( './../lib' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/mskmax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/mskmax/benchmark/benchmark.ndarray.js index dab9174606fe..d792e7934d81 100644 --- a/lib/node_modules/@stdlib/stats/strided/mskmax/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/mskmax/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var uniform = require( '@stdlib/random/array/uniform' ); var bernoulli = require( '@stdlib/random/array/bernoulli' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskmax = require( './../lib/ndarray.js' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/mskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/mskmin/benchmark/benchmark.js index 73ebe492d5a7..e5bc5711bfe6 100644 --- a/lib/node_modules/@stdlib/stats/strided/mskmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/mskmin/benchmark/benchmark.js @@ -25,8 +25,9 @@ var uniform = require( '@stdlib/random/array/uniform' ); var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; -var mskmin = require( './../lib/mskmin.js' ); +var mskmin = require( './../lib/main.js' ); // VARIABLES // @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/mskmin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/mskmin/benchmark/benchmark.ndarray.js index fb210864435d..be7271b8a793 100644 --- a/lib/node_modules/@stdlib/stats/strided/mskmin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/mskmin/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var uniform = require( '@stdlib/random/array/uniform' ); var bernoulli = require( '@stdlib/random/array/bernoulli' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskmin = require( './../lib/ndarray.js' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/mskrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/mskrange/benchmark/benchmark.js index 232143157a55..4023f7e05dd5 100644 --- a/lib/node_modules/@stdlib/stats/strided/mskrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/mskrange/benchmark/benchmark.js @@ -25,8 +25,9 @@ var uniform = require( '@stdlib/random/array/uniform' ); var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; -var mskrange = require( './../lib/mskrange.js' ); +var mskrange = require( './../lib/main.js' ); // VARIABLES // @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/mskrange/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/mskrange/benchmark/benchmark.ndarray.js index e007d89a07fe..ce145fba39cb 100644 --- a/lib/node_modules/@stdlib/stats/strided/mskrange/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/mskrange/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var mskrange = require( './../lib/ndarray.js' ); @@ -97,7 +98,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nancount/README.md b/lib/node_modules/@stdlib/stats/strided/nancount/README.md new file mode 100644 index 000000000000..5f6b8230d530 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/nancount/README.md @@ -0,0 +1,173 @@ + + +# nancount + +> Calculate the number of non-`NaN` elements in a strided array. + +
+ +
+ + + +
+ +## Usage + +```javascript +var nancount = require( '@stdlib/stats/strided/nancount' ); +``` + +#### nancount( N, x, strideX ) + +Calculates the number of non-`NaN` elements in a strided array. + +```javascript +var x = [ 1.0, -2.0, NaN, 2.0 ]; + +var v = nancount( x.length, x, 1 ); +// returns 3 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. +- **strideX**: stride length for `x`. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to calculate the count for every other element in `x`, + +```javascript +var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN, NaN ]; + +var v = nancount( 5, x, 2 ); +// returns 4 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, NaN, NaN, 4.0 ] ); +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +var v = nancount( 4, x1, 2 ); +// returns 3 +``` + +#### nancount.ndarray( N, x, strideX, offsetX ) + +Calculates the number of non-`NaN` elements in a strided array using alternative indexing semantics. + +```javascript +var x = [ 1.0, -2.0, NaN, 2.0 ]; + +var v = nancount.ndarray( x.length, x, 1, 0 ); +// returns 3 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the count for every other element in `x` starting from the second element + +```javascript +var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, NaN, NaN, 2.0, 3.0, 4.0 ]; + +var v = nancount.ndarray( 5, x, 2, 1 ); +// returns 4 +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `0`. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var nancount = require( '@stdlib/stats/strided/nancount' ); + +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -50.0, 50.0 ); +} + +var x = filledarrayBy( 10, 'float64', rand ); +console.log( x ); + +var v = nancount( x.length, x, 1 ); +console.log( v ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/strided/nancount/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nancount/benchmark/benchmark.js new file mode 100644 index 000000000000..b64ac2a3e55c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/nancount/benchmark/benchmark.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var format = require( '@stdlib/string/format' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var pkg = require( './../package.json' ).name; +var nancount = require( './../lib/main.js' ); + + +// FUNCTIONS // + +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = filledarrayBy( len, 'generic', rand ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = nancount( x.length, x, 1 ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/nancount/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nancount/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..a39076941060 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/nancount/benchmark/benchmark.ndarray.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var format = require( '@stdlib/string/format' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var pkg = require( './../package.json' ).name; +var nancount = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = filledarrayBy( len, 'generic', rand ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = nancount( x.length, x, 1, 0 ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/nancount/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/nancount/docs/repl.txt new file mode 100644 index 000000000000..ab586559f104 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/nancount/docs/repl.txt @@ -0,0 +1,88 @@ + +{{alias}}( N, x, strideX ) + Computes the number of non-`NaN` elements in a strided array. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `0`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Array|TypedArray + Input array. + + strideX: integer + Stride length. + + Returns + ------- + out: integer + Count. + + Examples + -------- + // Standard Usage: + > var x = [ 1.0, -2.0, NaN, 2.0 ]; + > {{alias}}( x.length, x, 1 ) + 3 + + // Using `N` and stride parameters: + > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ]; + > {{alias}}( 4, x, 2 ) + 3 + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 4, x1, 2 ) + 3 + + +{{alias}}.ndarray( N, x, strideX, offsetX ) + Computes the number of non-`NaN` elements in a strided array. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Array|TypedArray + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + out: integer + Count. + + Examples + -------- + // Standard Usage: + > var x = [ 1.0, -2.0, NaN, 2.0 ]; + > {{alias}}.ndarray( x.length, x, 1, 0 ) + 3 + + // Using offset parameter: + > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ]; + > {{alias}}.ndarray( 4, x, 2, 1 ) + 3 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/strided/nancount/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/strided/nancount/docs/types/index.d.ts new file mode 100644 index 000000000000..e915e6f658e6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/nancount/docs/types/index.d.ts @@ -0,0 +1,93 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { NumericArray, Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = NumericArray | Collection | AccessorArrayLike; + +/** +* Interface describing `nancount`. +*/ +interface Routine { + /** + * Computes the number of non-`NaN` elements in a strided array. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length + * @returns count + * + * @example + * var x = [ 1.0, -2.0, NaN, 2.0 ]; + * + * var v = nancount( x.length, x, 1 ); + * // returns 3 + */ + ( N: number, x: InputArray, strideX: number ): number; + + /** + * Computes the number of non-`NaN` elements in a strided array. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns count + * + * @example + * var x = [ 1.0, -2.0, NaN, 2.0 ]; + * + * var v = nancount.ndarray( x.length, x, 1, 0 ); + * // returns 3 + */ + ndarray( N: number, x: InputArray, strideX: number, offsetX: number ): number; +} + +/** +* Computes the number of non-`NaN` elements in a strided array. +* +* @param N - number of indexed elements +* @param x - input array +* @param strideX - stride length +* @returns count +* +* @example +* var x = [ 1.0, -2.0, NaN, 2.0 ]; +* +* var v = nancount( x.length, x, 1 ); +* // returns 3 +* +* @example +* var x = [ 1.0, -2.0, NaN, 2.0 ]; +* +* var v = nancount.ndarray( x.length, x, 1, 0 ); +* // returns 3 +*/ +declare var nancount: Routine; + + +// EXPORTS // + +export = nancount; diff --git a/lib/node_modules/@stdlib/stats/strided/nancount/docs/types/test.ts b/lib/node_modules/@stdlib/stats/strided/nancount/docs/types/test.ts new file mode 100644 index 000000000000..eb336451bb58 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/nancount/docs/types/test.ts @@ -0,0 +1,158 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import nancount = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = new Float64Array( 10 ); + + nancount( x.length, x, 1 ); // $ExpectType number + nancount( x.length, new AccessorArray( x ), 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + nancount( '10', x, 1 ); // $ExpectError + nancount( true, x, 1 ); // $ExpectError + nancount( false, x, 1 ); // $ExpectError + nancount( null, x, 1 ); // $ExpectError + nancount( undefined, x, 1 ); // $ExpectError + nancount( [], x, 1 ); // $ExpectError + nancount( {}, x, 1 ); // $ExpectError + nancount( ( x: number ): number => x, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a numeric array... +{ + const x = new Float64Array( 10 ); + + nancount( x.length, 10, 1 ); // $ExpectError + nancount( x.length, '10', 1 ); // $ExpectError + nancount( x.length, true, 1 ); // $ExpectError + nancount( x.length, false, 1 ); // $ExpectError + nancount( x.length, null, 1 ); // $ExpectError + nancount( x.length, undefined, 1 ); // $ExpectError + nancount( x.length, {}, 1 ); // $ExpectError + nancount( x.length, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + + nancount( x.length, x, '10' ); // $ExpectError + nancount( x.length, x, true ); // $ExpectError + nancount( x.length, x, false ); // $ExpectError + nancount( x.length, x, null ); // $ExpectError + nancount( x.length, x, undefined ); // $ExpectError + nancount( x.length, x, [] ); // $ExpectError + nancount( x.length, x, {} ); // $ExpectError + nancount( x.length, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + nancount(); // $ExpectError + nancount( x.length ); // $ExpectError + nancount( x.length, x ); // $ExpectError + nancount( x.length, x, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + const x = new Float64Array( 10 ); + + nancount.ndarray( x.length, x, 1, 0 ); // $ExpectType number + nancount.ndarray( x.length, new AccessorArray( x ), 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + nancount.ndarray( '10', x, 1, 0 ); // $ExpectError + nancount.ndarray( true, x, 1, 0 ); // $ExpectError + nancount.ndarray( false, x, 1, 0 ); // $ExpectError + nancount.ndarray( null, x, 1, 0 ); // $ExpectError + nancount.ndarray( undefined, x, 1, 0 ); // $ExpectError + nancount.ndarray( [], x, 1, 0 ); // $ExpectError + nancount.ndarray( {}, x, 1, 0 ); // $ExpectError + nancount.ndarray( ( x: number ): number => x, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a numeric array... +{ + const x = new Float64Array( 10 ); + + nancount.ndarray( x.length, 10, 1, 0 ); // $ExpectError + nancount.ndarray( x.length, '10', 1, 0 ); // $ExpectError + nancount.ndarray( x.length, true, 1, 0 ); // $ExpectError + nancount.ndarray( x.length, false, 1, 0 ); // $ExpectError + nancount.ndarray( x.length, null, 1, 0 ); // $ExpectError + nancount.ndarray( x.length, undefined, 1, 0 ); // $ExpectError + nancount.ndarray( x.length, {}, 1, 0 ); // $ExpectError + nancount.ndarray( x.length, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + + nancount.ndarray( x.length, x, '10', 0 ); // $ExpectError + nancount.ndarray( x.length, x, true, 0 ); // $ExpectError + nancount.ndarray( x.length, x, false, 0 ); // $ExpectError + nancount.ndarray( x.length, x, null, 0 ); // $ExpectError + nancount.ndarray( x.length, x, undefined, 0 ); // $ExpectError + nancount.ndarray( x.length, x, [], 0 ); // $ExpectError + nancount.ndarray( x.length, x, {}, 0 ); // $ExpectError + nancount.ndarray( x.length, x, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + nancount.ndarray( x.length, x, 1, '10' ); // $ExpectError + nancount.ndarray( x.length, x, 1, true ); // $ExpectError + nancount.ndarray( x.length, x, 1, false ); // $ExpectError + nancount.ndarray( x.length, x, 1, null ); // $ExpectError + nancount.ndarray( x.length, x, 1, undefined ); // $ExpectError + nancount.ndarray( x.length, x, 1, [] ); // $ExpectError + nancount.ndarray( x.length, x, 1, {} ); // $ExpectError + nancount.ndarray( x.length, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + nancount.ndarray(); // $ExpectError + nancount.ndarray( x.length ); // $ExpectError + nancount.ndarray( x.length, x ); // $ExpectError + nancount.ndarray( x.length, x, 1 ); // $ExpectError + nancount.ndarray( x.length, x, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/strided/nancount/examples/index.js b/lib/node_modules/@stdlib/stats/strided/nancount/examples/index.js new file mode 100644 index 000000000000..f9293cacedb0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/nancount/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var nancount = require( './../lib' ); + +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -50.0, 50.0 ); +} + +var x = filledarrayBy( 10, 'float64', rand ); +console.log( x ); + +var v = nancount( x.length, x, 1 ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/strided/nancount/lib/accessors.js b/lib/node_modules/@stdlib/stats/strided/nancount/lib/accessors.js new file mode 100644 index 000000000000..e8a3624ac9aa --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/nancount/lib/accessors.js @@ -0,0 +1,77 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Computes the number of non-`NaN` elements in a strided array. +* +* @private +* @param {PositiveInteger} N - number of indexed elements +* @param {Object} x - input array object +* @param {Collection} x.data - input array data +* @param {Array} x.accessors - array element accessors +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {NonNegativeInteger} count +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = toAccessorArray( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] ); +* +* var v = nancount( 5, arraylike2object( x ), 2, 1 ); +* // returns 4 +*/ +function nancount( N, x, strideX, offsetX ) { + var xbuf; + var get; + var ix; + var v; + var n; + var i; + + // Cache reference to array data: + xbuf = x.data; + + // Cache a reference to the element accessor: + get = x.accessors[ 0 ]; + + if ( strideX === 0 ) { + v = get( xbuf, offsetX ); + return ( v === v ) ? N : 0; + } + ix = offsetX; + n = 0; + for ( i = 0; i < N; i++ ) { + v = get( xbuf, ix ); + if ( v === v ) { + n += 1; + } + ix += strideX; + } + return n; +} + + +// EXPORTS // + +module.exports = nancount; diff --git a/lib/node_modules/@stdlib/stats/strided/nancount/lib/index.js b/lib/node_modules/@stdlib/stats/strided/nancount/lib/index.js new file mode 100644 index 000000000000..33e9db679b84 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/nancount/lib/index.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the number of non-`NaN` elements in a strided array. +* +* @module @stdlib/stats/strided/nancount +* +* @example +* var nancount = require( '@stdlib/stats/strided/nancount' ); +* +* var x = [ 1.0, -2.0, NaN, 2.0 ]; +* +* var v = nancount( x.length, x, 1 ); +* // returns 3 +* +* @example +* var nancount = require( '@stdlib/stats/strided/nancount' ); +* +* var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; +* +* var v = nancount.ndarray( 5, x, 2, 1 ); +* // returns 4 +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; + +// exports: { "ndarray": "main.ndarray" } diff --git a/lib/node_modules/@stdlib/stats/strided/nancount/lib/main.js b/lib/node_modules/@stdlib/stats/strided/nancount/lib/main.js new file mode 100644 index 000000000000..4ce235d4c17e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/nancount/lib/main.js @@ -0,0 +1,50 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Computes the number of non-`NaN` elements in a strided array. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {NumericArray} x - input array +* @param {integer} strideX - stride length +* @returns {NonNegativeInteger} count +* +* @example +* var x = [ 1.0, -2.0, NaN, 2.0 ]; +* +* var v = nancount( x.length, x, 1 ); +* // returns 3 +*/ +function nancount( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); +} + + +// EXPORTS // + +module.exports = nancount; diff --git a/lib/node_modules/@stdlib/stats/strided/nancount/lib/ndarray.js b/lib/node_modules/@stdlib/stats/strided/nancount/lib/ndarray.js new file mode 100644 index 000000000000..4320f4a7944f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/nancount/lib/ndarray.js @@ -0,0 +1,76 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var accessors = require( './accessors.js' ); + + +// MAIN // + +/** +* Computes the number of non-`NaN` elements in a strided array. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {NumericArray} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {NonNegativeInteger} count +* +* @example +* var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; +* +* var v = nancount( 5, x, 2, 1 ); +* // returns 4 +*/ +function nancount( N, x, strideX, offsetX ) { + var ix; + var o; + var n; + var i; + var v; + + if ( N <= 0 ) { + return 0; + } + o = arraylike2object( x ); + if ( o.accessorProtocol ) { + return accessors( N, o, strideX, offsetX ); + } + if ( strideX === 0 ) { + return ( x[ offsetX ] === x[ offsetX ] ) ? N : 0; + } + ix = offsetX; + n = 0; + for ( i = 0; i < N; i++ ) { + v = x[ ix ]; + if ( v === v ) { + n += 1; + } + ix += strideX; + } + return n; +} + + +// EXPORTS // + +module.exports = nancount; diff --git a/lib/node_modules/@stdlib/stats/strided/nancount/package.json b/lib/node_modules/@stdlib/stats/strided/nancount/package.json new file mode 100644 index 000000000000..d9e960cde063 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/nancount/package.json @@ -0,0 +1,68 @@ +{ + "name": "@stdlib/stats/strided/nancount", + "version": "0.0.0", + "description": "Calculate the number of non-`NaN` elements in a strided array.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "count", + "nancount", + "number", + "length", + "size", + "strided", + "strided array", + "array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/strided/nancount/test/test.js b/lib/node_modules/@stdlib/stats/strided/nancount/test/test.js new file mode 100644 index 000000000000..87f52c8b1b62 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/nancount/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var nancount = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof nancount, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof nancount.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/nancount/test/test.main.js b/lib/node_modules/@stdlib/stats/strided/nancount/test/test.main.js new file mode 100644 index 000000000000..eae5b9e22020 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/nancount/test/test.main.js @@ -0,0 +1,264 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var nancount = require( './../lib/main.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof nancount, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 3', function test( t ) { + t.strictEqual( nancount.length, 3, 'has expected arity' ); + t.end(); +}); + +tape( 'the function counts the number of non-`NaN` elements in a strided array', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0, NaN, NaN ]; + v = nancount( x.length, x, 1 ); + t.strictEqual( v, 6, 'returns expected value' ); + + x = [ -4.0, NaN, -5.0 ]; + v = nancount( x.length, x, 1 ); + t.strictEqual( v, 2, 'returns expected value' ); + + x = [ NaN ]; + v = nancount( x.length, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + x = [ NaN, NaN ]; + v = nancount( x.length, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function counts the number of non-`NaN` elements in a strided array (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0, NaN, NaN ]; + v = nancount( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( v, 6, 'returns expected value' ); + + x = [ -4.0, NaN, -5.0 ]; + v = nancount( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( v, 2, 'returns expected value' ); + + x = [ NaN ]; + v = nancount( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = nancount( 0, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + v = nancount( -1, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `stride` parameter', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]; + + v = nancount( 5, x, 2 ); + + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]; + + v = nancount( 5, toAccessorArray( x ), 2 ); + + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter', function test( t ) { + var x; + var v; + + x = [ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]; + + v = nancount( 5, x, -2 ); + + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]; + + v = nancount( 5, toAccessorArray( x ), -2 ); + + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns `N` if first element is valid', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = nancount( x.length, x, 0 ); + t.strictEqual( v, x.length, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns `N` if first element is valid (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = nancount( x.length, toAccessorArray( x ), 0 ); + t.strictEqual( v, x.length, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` if first element is NaN', function test( t ) { + var x; + var v; + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = nancount( x.length, x, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` if first element is NaN (accessors)', function test( t ) { + var x; + var v; + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = nancount( x.length, toAccessorArray( x ), 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var x0; + var x1; + var v; + + x0 = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + 6.0, + NaN, // 4 + NaN + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + + v = nancount( 5, x1, 2 ); + t.strictEqual( v, 4, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/nancount/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nancount/test/test.ndarray.js new file mode 100644 index 000000000000..a244fe48a3d7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/nancount/test/test.ndarray.js @@ -0,0 +1,264 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var nancount = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof nancount, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', function test( t ) { + t.strictEqual( nancount.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function counts the number of non-`NaN` elements in a strided array', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0, NaN, NaN ]; + v = nancount( x.length, x, 1, 0 ); + t.strictEqual( v, 6, 'returns expected value' ); + + x = [ -4.0, NaN, -5.0 ]; + v = nancount( x.length, x, 1, 0 ); + t.strictEqual( v, 2, 'returns expected value' ); + + x = [ NaN ]; + v = nancount( x.length, x, 1, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + + x = [ NaN, NaN ]; + v = nancount( x.length, x, 1, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function counts the number of non-`NaN` elements in a strided array (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0, NaN, NaN ]; + v = nancount( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, 6, 'returns expected value' ); + + x = [ -4.0, NaN, -5.0 ]; + v = nancount( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, 2, 'returns expected value' ); + + x = [ NaN ]; + v = nancount( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = nancount( 0, x, 1, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + + v = nancount( -1, x, 1, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `stride` parameter', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]; + + v = nancount( 5, x, 2, 0 ); + + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]; + + v = nancount( 5, toAccessorArray( x ), 2, 0 ); + + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter', function test( t ) { + var x; + var v; + + x = [ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]; + + v = nancount( 5, x, -2, x.length-2 ); + + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]; + + v = nancount( 5, toAccessorArray( x ), -2, x.length-2 ); + + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns `N` if first element is valid', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = nancount( x.length, x, 0, 0 ); + t.strictEqual( v, x.length, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns `N` if first element is valid (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = nancount( x.length, toAccessorArray( x ), 0, 0 ); + t.strictEqual( v, x.length, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` if first element is NaN', function test( t ) { + var x; + var v; + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = nancount( x.length, x, 0, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` if first element is NaN (accessors)', function test( t ) { + var x; + var v; + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = nancount( x.length, toAccessorArray( x ), 0, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var x0; + var x1; + var v; + + x0 = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + 6.0, + NaN, // 4 + NaN + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + + v = nancount( 5, x1, 2, 0 ); + t.strictEqual( v, 4, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/nanmax-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanmax-by/benchmark/benchmark.js index 3e45ce89a57f..9b4f97658f50 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmax-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmax-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmaxBy = require( './../lib/main.js' ); @@ -114,7 +115,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmax-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanmax-by/benchmark/benchmark.ndarray.js index 1573a3b9ee52..d886b650a940 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmax-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmax-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmaxBy = require( './../lib/ndarray.js' ); @@ -114,7 +115,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanmax/benchmark/benchmark.js index 35bf284b7c98..4ebdb64506eb 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmax/benchmark/benchmark.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmax = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanmax/benchmark/benchmark.ndarray.js index 4cb33513b111..229b20869a2f 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmax/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmax/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmax = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanmaxabs/benchmark/benchmark.js index cf53ada0094b..44e86fde2034 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmaxabs/benchmark/benchmark.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmaxabs = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmaxabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanmaxabs/benchmark/benchmark.ndarray.js index e527c18fea73..9fe34e3ec28d 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmaxabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmaxabs/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmaxabs = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanmean/benchmark/benchmark.js index 9fdfd75de434..13e74a7ecbce 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmean/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmean = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmean/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanmean/benchmark/benchmark.ndarray.js index ac2bf5b39b02..87c3792f8fd0 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmean/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmean/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmean = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanmeanors/benchmark/benchmark.js index 80df8cf8ddfe..f07bf311fbd4 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmeanors/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmeanors = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmeanors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanmeanors/benchmark/benchmark.ndarray.js index c21cc04e91b1..b75fd35ff07d 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmeanors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmeanors/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmeanors = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmeanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanmeanpn/benchmark/benchmark.js index c4077ed0bc23..d5e6f17bbf80 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmeanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmeanpn/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmeanpn = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmeanpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanmeanpn/benchmark/benchmark.ndarray.js index 9246b854d44a..8464dd97162a 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmeanpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmeanpn/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmeanpn = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanmeanwd/benchmark/benchmark.js index b41aed60ee50..c794f137da19 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmeanwd/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmeanwd = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmeanwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanmeanwd/benchmark/benchmark.ndarray.js index f0b3c784eb7f..59ee73c30b58 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmeanwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmeanwd/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmeanwd = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmin-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanmin-by/benchmark/benchmark.js index da0d2ab0dc61..e896fae328eb 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmin-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmin-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanminBy = require( './../lib/main.js' ); @@ -114,7 +115,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmin-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanmin-by/benchmark/benchmark.ndarray.js index b0b3c23b53bb..27c3f83c9203 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmin-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmin-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanminBy = require( './../lib/ndarray.js' ); @@ -114,7 +115,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanmin/benchmark/benchmark.js index 4bbb9b2647b9..16d59315599e 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmin = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanmin/benchmark/benchmark.ndarray.js index 7851d4e7c76c..94dbcec144ec 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmin/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmin = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanminabs/benchmark/benchmark.js index aaed8b1cc5c5..1ad38cdac530 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanminabs/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanminabs = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanminabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanminabs/benchmark/benchmark.ndarray.js index 36fefce0ea2b..1fb5a23eef9e 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanminabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanminabs/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanminabs = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmskmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanmskmax/benchmark/benchmark.js index 150cd00c98cf..93277a5994a4 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmskmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmskmax/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmskmax = require( './../lib/main.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmskmax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanmskmax/benchmark/benchmark.ndarray.js index 320a7dd99b50..b9916a99c369 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmskmax/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmskmax/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmskmax = require( './../lib/ndarray.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanmskmin/benchmark/benchmark.js index cb349c62e98c..a647d6c7ee5c 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmskmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmskmin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmskmin = require( './../lib/main.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmskmin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanmskmin/benchmark/benchmark.ndarray.js index 185027da2c9e..8bd92872dc92 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmskmin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmskmin/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmskmin = require( './../lib/ndarray.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmskrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanmskrange/benchmark/benchmark.js index 68a151620f32..a1ee05339151 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmskrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmskrange/benchmark/benchmark.js @@ -26,8 +26,9 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; -var nanmskrange = require( './../lib/nanmskrange.js' ); +var nanmskrange = require( './../lib/main.js' ); // FUNCTIONS // @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanmskrange/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanmskrange/benchmark/benchmark.ndarray.js index 7f0d9e96b32a..8cbf00f777ee 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanmskrange/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanmskrange/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanmskrange = require( './../lib/ndarray.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanrange-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanrange-by/benchmark/benchmark.js index 5cf6bdce1517..0f453df526e2 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanrange-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanrange-by/benchmark/benchmark.js @@ -26,6 +26,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanrangeBy = require( './../lib/main.js' ); @@ -114,7 +115,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanrange-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanrange-by/benchmark/benchmark.ndarray.js index 336bdcfef9ee..3f783c64f2e2 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanrange-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanrange-by/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanrangeBy = require( './../lib/ndarray.js' ); @@ -114,7 +115,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanrange/benchmark/benchmark.js index c072cd3a90c7..3f31f83a4b87 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanrange/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanrange = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanrange/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanrange/benchmark/benchmark.ndarray.js index e7a91c3e1eba..aad3ae855c75 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanrange/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanrange/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanrange = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanstdev/benchmark/benchmark.js index f13151031b28..5d49b39c8105 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanstdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanstdev/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdev = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanstdev/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanstdev/benchmark/benchmark.ndarray.js index 5bca3a5e5768..58917c781221 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanstdev/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanstdev/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdev = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanstdevch/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanstdevch/benchmark/benchmark.js index cc0aabbb8866..87e7dbf83cc9 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanstdevch/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanstdevch/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdevch = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanstdevch/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanstdevch/benchmark/benchmark.ndarray.js index 994359dc06ad..8ac8a26c587b 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanstdevch/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanstdevch/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdevch = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanstdevpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanstdevpn/benchmark/benchmark.js index 01884aedf33c..db2ecb74b5fe 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanstdevpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanstdevpn/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdevpn = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanstdevpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanstdevpn/benchmark/benchmark.ndarray.js index f56d926d1c74..c4b02c146c66 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanstdevpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanstdevpn/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdevpn = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanstdevtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanstdevtk/benchmark/benchmark.js index 4564d863ffe1..2694ba744920 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanstdevtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanstdevtk/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdevtk = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanstdevtk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanstdevtk/benchmark/benchmark.ndarray.js index 2469424c5dac..8f4722417f82 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanstdevtk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanstdevtk/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdevtk = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanstdevwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanstdevwd/benchmark/benchmark.js index 79630e80ff91..8b3f9f22d0c0 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanstdevwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanstdevwd/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdevwd = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanstdevwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanstdevwd/benchmark/benchmark.ndarray.js index 201e5dfc2f16..274f3b6c2095 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanstdevwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanstdevwd/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdevwd = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanstdevyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanstdevyc/benchmark/benchmark.js index e790e1547158..828c24e752a2 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanstdevyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanstdevyc/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdevyc = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanstdevyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanstdevyc/benchmark/benchmark.ndarray.js index 71d98fdc5473..91dcc80952e0 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanstdevyc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanstdevyc/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanstdevyc = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanvariance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanvariance/benchmark/benchmark.js index 165c826c1582..fa55a2830b28 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanvariance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanvariance/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvariance = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanvariance/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanvariance/benchmark/benchmark.ndarray.js index 25eaeb09366f..49a8e158c821 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanvariance/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanvariance/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvariance = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanvariancech/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanvariancech/benchmark/benchmark.js index aebff3e8f098..ccdee7a18060 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanvariancech/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanvariancech/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvariancech = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanvariancech/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanvariancech/benchmark/benchmark.ndarray.js index e37a9e2b674f..b5713384a0da 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanvariancech/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanvariancech/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvariancech = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanvariancepn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanvariancepn/benchmark/benchmark.js index c1ae3c2a8571..c1ffb6c54b8b 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanvariancepn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanvariancepn/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvariancepn = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanvariancepn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanvariancepn/benchmark/benchmark.ndarray.js index 33afe66e6e2e..a85fcba8744a 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanvariancepn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanvariancepn/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvariancepn = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanvariancetk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanvariancetk/benchmark/benchmark.js index d8aabfd8565f..5ef47386a737 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanvariancetk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanvariancetk/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvariancetk = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanvariancetk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanvariancetk/benchmark/benchmark.ndarray.js index 5dbe5248ef9d..6bab7d43f662 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanvariancetk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanvariancetk/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvariancetk = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanvariancewd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanvariancewd/benchmark/benchmark.js index a44f51fafd4f..1f2f45e7963a 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanvariancewd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanvariancewd/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvariancewd = require( './../lib/main.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanvariancewd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanvariancewd/benchmark/benchmark.ndarray.js index e8df65318035..51d0e7fa822b 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanvariancewd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanvariancewd/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvariancewd = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanvarianceyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/nanvarianceyc/benchmark/benchmark.js index a0bf088253fd..7e27821b3931 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanvarianceyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/nanvarianceyc/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvarianceyc = require( './../lib' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/nanvarianceyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/nanvarianceyc/benchmark/benchmark.ndarray.js index a84943ab98b8..aac870855912 100644 --- a/lib/node_modules/@stdlib/stats/strided/nanvarianceyc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/nanvarianceyc/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var nanvarianceyc = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/range-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/range-by/benchmark/benchmark.js index dfd51b2b5ed4..119cfd44caad 100644 --- a/lib/node_modules/@stdlib/stats/strided/range-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/range-by/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var rangeBy = require( './../lib/main.js' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/range-by/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/range-by/benchmark/benchmark.ndarray.js index 691acb0f8e43..a74706a7618a 100644 --- a/lib/node_modules/@stdlib/stats/strided/range-by/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/range-by/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var rangeBy = require( './../lib/ndarray.js' ); @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/range/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/range/benchmark/benchmark.js index ea50b3839319..1e3061308d95 100644 --- a/lib/node_modules/@stdlib/stats/strided/range/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/range/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var range = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/range/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/range/benchmark/benchmark.ndarray.js index d0ab28be4d58..5acf4d602db2 100644 --- a/lib/node_modules/@stdlib/stats/strided/range/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/range/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var range = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scovarmtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/scovarmtk/benchmark/benchmark.js index 2085434a246b..af0591676ebf 100644 --- a/lib/node_modules/@stdlib/stats/strided/scovarmtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/scovarmtk/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scovarmtk = require( './../lib/scovarmtk.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scovarmtk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/scovarmtk/benchmark/benchmark.native.js index aee2faf0d972..ef39d411641e 100644 --- a/lib/node_modules/@stdlib/stats/strided/scovarmtk/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/scovarmtk/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scovarmtk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/scovarmtk/benchmark/benchmark.ndarray.js index d0d4013f669f..0fc82b77a536 100644 --- a/lib/node_modules/@stdlib/stats/strided/scovarmtk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/scovarmtk/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scovarmtk = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scovarmtk/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/scovarmtk/benchmark/benchmark.ndarray.native.js index 50b989503958..aadad5ed6c48 100644 --- a/lib/node_modules/@stdlib/stats/strided/scovarmtk/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/scovarmtk/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scumax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/scumax/benchmark/benchmark.js index 8b9366d393a9..84ba3f15a815 100644 --- a/lib/node_modules/@stdlib/stats/strided/scumax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/scumax/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scumax = require( './../lib/scumax.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scumax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/scumax/benchmark/benchmark.native.js index 4edb1f61388b..84f5198a65d4 100644 --- a/lib/node_modules/@stdlib/stats/strided/scumax/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/scumax/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scumax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/scumax/benchmark/benchmark.ndarray.js index 55510b21cc06..1225a3962ce2 100644 --- a/lib/node_modules/@stdlib/stats/strided/scumax/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/scumax/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scumax = require( './../lib/ndarray.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scumax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/scumax/benchmark/benchmark.ndarray.native.js index 276f26f59cd8..61a0231abaeb 100644 --- a/lib/node_modules/@stdlib/stats/strided/scumax/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/scumax/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scumaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/scumaxabs/benchmark/benchmark.js index 8fb013029dd7..128c503d7f12 100644 --- a/lib/node_modules/@stdlib/stats/strided/scumaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/scumaxabs/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scumaxabs = require( './../lib/scumaxabs.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scumaxabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/scumaxabs/benchmark/benchmark.native.js index 8504d9b111fd..073773165955 100644 --- a/lib/node_modules/@stdlib/stats/strided/scumaxabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/scumaxabs/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scumaxabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/scumaxabs/benchmark/benchmark.ndarray.js index 66f74bf677c1..03a29dda1a08 100644 --- a/lib/node_modules/@stdlib/stats/strided/scumaxabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/scumaxabs/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scumaxabs = require( './../lib/ndarray.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scumaxabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/scumaxabs/benchmark/benchmark.ndarray.native.js index f67efb46eaae..ad3f60ab5421 100644 --- a/lib/node_modules/@stdlib/stats/strided/scumaxabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/scumaxabs/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scumin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/scumin/benchmark/benchmark.js index d72e200ae7e8..bf312abaf915 100644 --- a/lib/node_modules/@stdlib/stats/strided/scumin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/scumin/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scumin = require( './../lib/scumin.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scumin/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/scumin/benchmark/benchmark.native.js index 7e5ea1f14f15..e5e779ee5409 100644 --- a/lib/node_modules/@stdlib/stats/strided/scumin/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/scumin/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scumin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/scumin/benchmark/benchmark.ndarray.js index 2f45f047619a..3a2e0ed3a2e7 100644 --- a/lib/node_modules/@stdlib/stats/strided/scumin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/scumin/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scumin = require( './../lib/ndarray.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scumin/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/scumin/benchmark/benchmark.ndarray.native.js index d71c8b61205d..fae8159708f2 100644 --- a/lib/node_modules/@stdlib/stats/strided/scumin/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/scumin/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scuminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/scuminabs/benchmark/benchmark.js index cc40a34b3e8a..05029e5bfee4 100644 --- a/lib/node_modules/@stdlib/stats/strided/scuminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/scuminabs/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scuminabs = require( './../lib/scuminabs.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scuminabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/scuminabs/benchmark/benchmark.native.js index 0213f0473cc3..ae4c5c71c1e7 100644 --- a/lib/node_modules/@stdlib/stats/strided/scuminabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/scuminabs/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scuminabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/scuminabs/benchmark/benchmark.ndarray.js index 883059bcc5d8..2ed906fc1448 100644 --- a/lib/node_modules/@stdlib/stats/strided/scuminabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/scuminabs/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var scuminabs = require( './../lib/ndarray.js' ); @@ -101,7 +102,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/scuminabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/scuminabs/benchmark/benchmark.ndarray.native.js index 90ad4f369534..bd0b3804245e 100644 --- a/lib/node_modules/@stdlib/stats/strided/scuminabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/scuminabs/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -106,7 +107,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sdsmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/sdsmean/benchmark/benchmark.js index 2c87ae62336d..da98062a7251 100644 --- a/lib/node_modules/@stdlib/stats/strided/sdsmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/sdsmean/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsmean = require( './../lib/sdsmean.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sdsmean/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/sdsmean/benchmark/benchmark.native.js index b6c23259c2b0..842277a41298 100644 --- a/lib/node_modules/@stdlib/stats/strided/sdsmean/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sdsmean/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sdsmean/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/sdsmean/benchmark/benchmark.ndarray.js index 5434ac8f0eab..d62466d5c0e4 100644 --- a/lib/node_modules/@stdlib/stats/strided/sdsmean/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/sdsmean/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsmean = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sdsmean/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/sdsmean/benchmark/benchmark.ndarray.native.js index 4faad93d4055..7747fd42bc65 100644 --- a/lib/node_modules/@stdlib/stats/strided/sdsmean/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sdsmean/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sdsmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/sdsmeanors/benchmark/benchmark.js index a8221e67e48f..a9f09e5bf5ea 100644 --- a/lib/node_modules/@stdlib/stats/strided/sdsmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/sdsmeanors/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsmeanors = require( './../lib/sdsmeanors.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sdsmeanors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/sdsmeanors/benchmark/benchmark.native.js index e9a26d5fad1b..46f6bba9e650 100644 --- a/lib/node_modules/@stdlib/stats/strided/sdsmeanors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sdsmeanors/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sdsmeanors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/sdsmeanors/benchmark/benchmark.ndarray.js index 6d2012e1da4f..3bcfef58cc3c 100644 --- a/lib/node_modules/@stdlib/stats/strided/sdsmeanors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/sdsmeanors/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsmeanors = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sdsmeanors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/sdsmeanors/benchmark/benchmark.ndarray.native.js index 6343c3384382..95b3f8e5cf38 100644 --- a/lib/node_modules/@stdlib/stats/strided/sdsmeanors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sdsmeanors/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/README.md b/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/README.md index 948b3b977a6b..bcfc2ae99f9d 100644 --- a/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/README.md +++ b/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/README.md @@ -202,7 +202,7 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p ```c const float x[] = { 1.0f, -2.0f, 0.0f/0.0f, 2.0f }; -float v = stdlib_strided_sdsnanmeanors( x.length, x, 1 ); +float v = stdlib_strided_sdsnanmeanors( 4, x, 1 ); // returns ~0.3333f ``` @@ -223,7 +223,7 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p ```c const float x[] = { 1.0f, -2.0f, 0.0f/0.0f, 2.0f }; -float v = stdlib_strided_sdsnanmeanors_ndarray( x.length, x, 1, 0 ); +float v = stdlib_strided_sdsnanmeanors_ndarray( 4, x, 1, 0 ); // returns ~0.3333f ``` diff --git a/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/benchmark/benchmark.js index 7ffaa2e4f2a9..277948f2c092 100644 --- a/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsnanmeanors = require( './../lib/sdsnanmeanors.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/benchmark/benchmark.native.js index a3dd0e26e665..a947991692cb 100644 --- a/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/benchmark/benchmark.ndarray.js index 224c42c87ce9..10259458c1f6 100644 --- a/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sdsnanmeanors = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/benchmark/benchmark.ndarray.native.js index 39f0cc18b96a..6de8022dbcbb 100644 --- a/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sdsnanmeanors/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smax/benchmark/benchmark.js index 9b0c9b34fd98..a22ed58be6ab 100644 --- a/lib/node_modules/@stdlib/stats/strided/smax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smax/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smax = require( './../lib/smax.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smax/benchmark/benchmark.native.js index 0640d0e9b9fd..7fa0154ad2f2 100644 --- a/lib/node_modules/@stdlib/stats/strided/smax/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smax/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smax/benchmark/benchmark.ndarray.js index 6e2d2b674e1e..f5dd77ac463c 100644 --- a/lib/node_modules/@stdlib/stats/strided/smax/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smax/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smax = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smax/benchmark/benchmark.ndarray.native.js index efb833bf4760..dd6a7648581b 100644 --- a/lib/node_modules/@stdlib/stats/strided/smax/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smax/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smaxabs/benchmark/benchmark.js index ad225918a7c4..246cb6cff9d0 100644 --- a/lib/node_modules/@stdlib/stats/strided/smaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smaxabs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smaxabs = require( './../lib/smaxabs.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smaxabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smaxabs/benchmark/benchmark.native.js index 0c021e886cb2..4ac2fc749b39 100644 --- a/lib/node_modules/@stdlib/stats/strided/smaxabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smaxabs/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smaxabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smaxabs/benchmark/benchmark.ndarray.js index d2a16f4f83a5..175f3151152e 100644 --- a/lib/node_modules/@stdlib/stats/strided/smaxabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smaxabs/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smaxabs = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smaxabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smaxabs/benchmark/benchmark.ndarray.native.js index 278dbdf7b7b9..f080fdd7f40e 100644 --- a/lib/node_modules/@stdlib/stats/strided/smaxabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smaxabs/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smaxabssorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smaxabssorted/benchmark/benchmark.js index 0ff2428be793..a9b47f722822 100644 --- a/lib/node_modules/@stdlib/stats/strided/smaxabssorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smaxabssorted/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smaxabssorted = require( './../lib/smaxabssorted.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smaxabssorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smaxabssorted/benchmark/benchmark.native.js index 764bddac1caa..e1f859e40495 100644 --- a/lib/node_modules/@stdlib/stats/strided/smaxabssorted/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smaxabssorted/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smaxabssorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smaxabssorted/benchmark/benchmark.ndarray.js index f9562eeffc57..72cb9b80db44 100644 --- a/lib/node_modules/@stdlib/stats/strided/smaxabssorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smaxabssorted/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smaxabssorted = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smaxabssorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smaxabssorted/benchmark/benchmark.ndarray.native.js index c4118ae43deb..80405dad7950 100644 --- a/lib/node_modules/@stdlib/stats/strided/smaxabssorted/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smaxabssorted/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smaxsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smaxsorted/benchmark/benchmark.js index 9d6c7f983901..2a80821ad02d 100644 --- a/lib/node_modules/@stdlib/stats/strided/smaxsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smaxsorted/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smaxsorted = require( './../lib/smaxsorted.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smaxsorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smaxsorted/benchmark/benchmark.native.js index 9986d4f2b526..d5431afcf214 100644 --- a/lib/node_modules/@stdlib/stats/strided/smaxsorted/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smaxsorted/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smaxsorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smaxsorted/benchmark/benchmark.ndarray.js index 63ab1bf81037..04166efb9019 100644 --- a/lib/node_modules/@stdlib/stats/strided/smaxsorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smaxsorted/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smaxsorted = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smaxsorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smaxsorted/benchmark/benchmark.ndarray.native.js index accc5939c738..95ad19d1af8b 100644 --- a/lib/node_modules/@stdlib/stats/strided/smaxsorted/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smaxsorted/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smean/benchmark/benchmark.js index e5d8bb618da2..88ada5e6c372 100644 --- a/lib/node_modules/@stdlib/stats/strided/smean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smean/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smean = require( './../lib/smean.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smean/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smean/benchmark/benchmark.native.js index 032fe24b2da3..0f0938128148 100644 --- a/lib/node_modules/@stdlib/stats/strided/smean/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smean/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smean/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smean/benchmark/benchmark.ndarray.js index 9b512d004ee6..d454c4f30b3f 100644 --- a/lib/node_modules/@stdlib/stats/strided/smean/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smean/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smean = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smean/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smean/benchmark/benchmark.ndarray.native.js index db4c4e3045d8..575ee486f9a2 100644 --- a/lib/node_modules/@stdlib/stats/strided/smean/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smean/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeankbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smeankbn/benchmark/benchmark.js index 45bc25709e7e..8d700e6695fc 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeankbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smeankbn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeankbn = require( './../lib/smeankbn.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeankbn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smeankbn/benchmark/benchmark.native.js index bc15908152e4..1d3003023da1 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeankbn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smeankbn/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeankbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smeankbn/benchmark/benchmark.ndarray.js index 6416f815f9d5..a185b0b3f4f1 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeankbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smeankbn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeankbn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeankbn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smeankbn/benchmark/benchmark.ndarray.native.js index d96e4fcf1d8f..f3e81bf09b75 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeankbn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smeankbn/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeankbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smeankbn2/benchmark/benchmark.js index cda6184d2fbb..3ab7f1b74c68 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeankbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smeankbn2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeankbn2 = require( './../lib/smeankbn2.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeankbn2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smeankbn2/benchmark/benchmark.native.js index c0884dd21c85..a61154b8a3b6 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeankbn2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smeankbn2/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeankbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smeankbn2/benchmark/benchmark.ndarray.js index 5981e4f3ac1b..77702ea5dd69 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeankbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smeankbn2/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeankbn2 = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeankbn2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smeankbn2/benchmark/benchmark.ndarray.native.js index 54c93617db9d..d085740c2f13 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeankbn2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smeankbn2/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanli/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smeanli/benchmark/benchmark.js index 57a3d769529b..8acd2e02517e 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanli/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanli/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanli = require( './../lib/smeanli.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanli/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smeanli/benchmark/benchmark.native.js index 181b0dcafcb2..1993f19822c6 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanli/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanli/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanli/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smeanli/benchmark/benchmark.ndarray.js index 9fb718654cb5..d3b4a210dd42 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanli/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanli/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanli = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanli/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smeanli/benchmark/benchmark.ndarray.native.js index dd3e5d562e11..42f4691a2c38 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanli/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanli/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanlipw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smeanlipw/benchmark/benchmark.js index 6211599e14c8..2b45548a8485 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanlipw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanlipw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanlipw = require( './../lib/smeanlipw.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanlipw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smeanlipw/benchmark/benchmark.native.js index d10a10aa1f63..3f75c846b074 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanlipw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanlipw/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanlipw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smeanlipw/benchmark/benchmark.ndarray.js index f62ee8a67f42..81b161705aca 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanlipw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanlipw/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanlipw = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanlipw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smeanlipw/benchmark/benchmark.ndarray.native.js index f69823e9fc7f..5137f594ae9c 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanlipw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanlipw/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smeanors/benchmark/benchmark.js index e555d52b1b5b..cdf70daea8cf 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanors/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanors = require( './../lib/smeanors.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smeanors/benchmark/benchmark.native.js index 67ffde570280..7741e148beff 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanors/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smeanors/benchmark/benchmark.ndarray.js index 75d0cad6e5e3..fcbcb19e75fd 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanors/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanors = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smeanors/benchmark/benchmark.ndarray.native.js index 5cabadec86ad..5a53c97b075e 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanors/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smeanpn/benchmark/benchmark.js index 135d5c100927..fedd8843ec89 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanpn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanpn = require( './../lib/smeanpn.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanpn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smeanpn/benchmark/benchmark.native.js index a72a0628cf6c..9c380f254354 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanpn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanpn/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smeanpn/benchmark/benchmark.ndarray.js index 5b04c8d8295d..1435357f7e90 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanpn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanpn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanpn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smeanpn/benchmark/benchmark.ndarray.native.js index 0924b85d12d8..55dcc6786ab8 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanpn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanpn/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smeanpw/benchmark/benchmark.js index a6887649a0dd..e499b82f80aa 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanpw/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanpw = require( './../lib/smeanpw.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smeanpw/benchmark/benchmark.native.js index 561da0b0388b..728166644f39 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanpw/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smeanpw/benchmark/benchmark.ndarray.js index 008399d7718f..4defbcf195d8 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanpw/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanpw = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smeanpw/benchmark/benchmark.ndarray.native.js index c73cecbb64b0..f752ce6f5183 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanpw/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smeanwd/benchmark/benchmark.js index 3c8a1a90f200..3c4b6d006122 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanwd/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanwd = require( './../lib/smeanwd.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smeanwd/benchmark/benchmark.native.js index d731e72bc5f9..67dfa2ec105c 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanwd/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smeanwd/benchmark/benchmark.ndarray.js index fe8dd4ab4c9a..4df3d0d1d8b9 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanwd/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smeanwd = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smeanwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smeanwd/benchmark/benchmark.ndarray.native.js index 68b3c15de3fc..04b5fcdfac9f 100644 --- a/lib/node_modules/@stdlib/stats/strided/smeanwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smeanwd/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smediansorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smediansorted/benchmark/benchmark.js index bd61726a8097..8e97019f95a1 100644 --- a/lib/node_modules/@stdlib/stats/strided/smediansorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smediansorted/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smediansorted = require( './../lib/smediansorted.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smediansorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smediansorted/benchmark/benchmark.native.js index 29d1e5c9ed27..b383e5a9a33b 100644 --- a/lib/node_modules/@stdlib/stats/strided/smediansorted/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smediansorted/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smediansorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smediansorted/benchmark/benchmark.ndarray.js index 2d01aa2df8de..f5632231f7ba 100644 --- a/lib/node_modules/@stdlib/stats/strided/smediansorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smediansorted/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smediansorted = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smediansorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smediansorted/benchmark/benchmark.ndarray.native.js index 49288c09c4ea..d979c31b0144 100644 --- a/lib/node_modules/@stdlib/stats/strided/smediansorted/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smediansorted/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smidrange/README.md b/lib/node_modules/@stdlib/stats/strided/smidrange/README.md index 66e1723c5be8..5d1990309829 100644 --- a/lib/node_modules/@stdlib/stats/strided/smidrange/README.md +++ b/lib/node_modules/@stdlib/stats/strided/smidrange/README.md @@ -181,7 +181,7 @@ Computes the [mid-range][mid-range] of a single-precision floating-point strided const float x[] = { 1.0f, -2.0f, 3.0f, 4.0f }; float v = stdlib_strided_smidrange( 4, x, 1 ); -// returns 2.5f +// returns 1.0f ``` The function accepts the following arguments: @@ -202,7 +202,7 @@ Computes the [mid-range][mid-range] of a single-precision floating-point strided const float x[] = { 1.0f, -2.0f, 3.0f, 4.0f }; float v = stdlib_strided_smidrange_ndarray( 4, x, 1, 0 ); -// returns 2.5f +// returns 1.0f ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/stats/strided/smidrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smidrange/benchmark/benchmark.js index 832c6f2b2370..3082ace760f5 100644 --- a/lib/node_modules/@stdlib/stats/strided/smidrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smidrange/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smidrange = require( './../lib/smidrange.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smidrange/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smidrange/benchmark/benchmark.native.js index 682f71a6f7a3..8ef574fea1ca 100644 --- a/lib/node_modules/@stdlib/stats/strided/smidrange/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smidrange/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smidrange/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smidrange/benchmark/benchmark.ndarray.js index b1974a137a95..e4633d61d658 100644 --- a/lib/node_modules/@stdlib/stats/strided/smidrange/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smidrange/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smidrange = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smidrange/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smidrange/benchmark/benchmark.ndarray.native.js index 3aebf1b784c6..158463ac02cf 100644 --- a/lib/node_modules/@stdlib/stats/strided/smidrange/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smidrange/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smin/README.md b/lib/node_modules/@stdlib/stats/strided/smin/README.md index f4714b8c2b3d..4cfeb4819580 100644 --- a/lib/node_modules/@stdlib/stats/strided/smin/README.md +++ b/lib/node_modules/@stdlib/stats/strided/smin/README.md @@ -179,7 +179,7 @@ Computes the minimum value of a single-precision floating-point strided array. const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f }; float v = stdlib_strided_smin( 4, x, 1 ); -// returns 1.0f +// returns -4.0f ``` The function accepts the following arguments: @@ -200,7 +200,7 @@ Computes the minimum value of a single-precision floating-point strided array us const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f }; float v = stdlib_strided_smin_ndarray( 4, x, 1, 0 ); -// returns 1.0f +// returns -4.0f ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/stats/strided/smin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smin/benchmark/benchmark.js index c69c7042d1ef..d5eb3dff2773 100644 --- a/lib/node_modules/@stdlib/stats/strided/smin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smin/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smin = require( './../lib/smin.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smin/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smin/benchmark/benchmark.native.js index c5d5114a8d42..c96cd60418c0 100644 --- a/lib/node_modules/@stdlib/stats/strided/smin/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smin/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smin/benchmark/benchmark.ndarray.js index 2cabb9b39a9b..bc81326bf9bb 100644 --- a/lib/node_modules/@stdlib/stats/strided/smin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smin/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smin = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smin/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smin/benchmark/benchmark.ndarray.native.js index 0ae1da811cf2..e0fa954076dc 100644 --- a/lib/node_modules/@stdlib/stats/strided/smin/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smin/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sminabs/README.md b/lib/node_modules/@stdlib/stats/strided/sminabs/README.md index 39c864b17899..8a530b922232 100644 --- a/lib/node_modules/@stdlib/stats/strided/sminabs/README.md +++ b/lib/node_modules/@stdlib/stats/strided/sminabs/README.md @@ -199,7 +199,7 @@ Computes the minimum absolute value of a single-precision floating-point strided ```c const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f }; -float v = stdlib_strided_dmax_ndarray( 4, x, 1, 0 ); +float v = stdlib_strided_sminabs_ndarray( 4, x, 1, 0 ); // returns 1.0f ``` diff --git a/lib/node_modules/@stdlib/stats/strided/sminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/sminabs/benchmark/benchmark.js index f219ded0a124..95cff01c4d78 100644 --- a/lib/node_modules/@stdlib/stats/strided/sminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/sminabs/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sminabs = require( './../lib/sminabs.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sminabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/sminabs/benchmark/benchmark.native.js index 1af30a1805b1..724a297d19c4 100644 --- a/lib/node_modules/@stdlib/stats/strided/sminabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sminabs/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sminabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/sminabs/benchmark/benchmark.ndarray.js index 60753fb00717..f8a548dee263 100644 --- a/lib/node_modules/@stdlib/stats/strided/sminabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/sminabs/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sminabs = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sminabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/sminabs/benchmark/benchmark.ndarray.native.js index 9ccf950febc1..17c1300405b6 100644 --- a/lib/node_modules/@stdlib/stats/strided/sminabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sminabs/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sminsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/sminsorted/benchmark/benchmark.js index 96da2f345387..3509e8bf6a5a 100644 --- a/lib/node_modules/@stdlib/stats/strided/sminsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/sminsorted/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sminsorted = require( './../lib/sminsorted.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sminsorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/sminsorted/benchmark/benchmark.native.js index 60c688b62ce5..26dff72366f6 100644 --- a/lib/node_modules/@stdlib/stats/strided/sminsorted/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sminsorted/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sminsorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/sminsorted/benchmark/benchmark.ndarray.js index 4f7325b68cb0..5560d73833e4 100644 --- a/lib/node_modules/@stdlib/stats/strided/sminsorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/sminsorted/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sminsorted = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sminsorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/sminsorted/benchmark/benchmark.ndarray.native.js index 636deb08be10..79a6f138fbfa 100644 --- a/lib/node_modules/@stdlib/stats/strided/sminsorted/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sminsorted/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smskmax/README.md b/lib/node_modules/@stdlib/stats/strided/smskmax/README.md index 89253cf323b2..e69664a7aaf4 100644 --- a/lib/node_modules/@stdlib/stats/strided/smskmax/README.md +++ b/lib/node_modules/@stdlib/stats/strided/smskmax/README.md @@ -232,7 +232,7 @@ Computes the maximum value of a single-precision floating-point strided array ac const float x[] = { 1.0f, -2.0f, 2.0f }; const uint8_t mask[] = { 0, 1, 0 }; -float v = stdlib_strided_smskmax( 3, x, 1, 0, mask, 1, 0 ); +float v = stdlib_strided_smskmax_ndarray( 3, x, 1, 0, mask, 1, 0 ); // returns 2.0f ``` diff --git a/lib/node_modules/@stdlib/stats/strided/smskmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smskmax/benchmark/benchmark.js index 48b28079e819..480fca98d790 100644 --- a/lib/node_modules/@stdlib/stats/strided/smskmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smskmax/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskmax = require( './../lib/smskmax.js' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smskmax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smskmax/benchmark/benchmark.native.js index fbb42f3672ee..9a485b8a2c9e 100644 --- a/lib/node_modules/@stdlib/stats/strided/smskmax/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smskmax/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smskmax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smskmax/benchmark/benchmark.ndarray.js index 078376a2f876..5c7b7592ed8a 100644 --- a/lib/node_modules/@stdlib/stats/strided/smskmax/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smskmax/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskmax = require( './../lib/ndarray.js' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smskmax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smskmax/benchmark/benchmark.ndarray.native.js index 9a9c9066954b..dcd514792d0d 100644 --- a/lib/node_modules/@stdlib/stats/strided/smskmax/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smskmax/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smskmin/README.md b/lib/node_modules/@stdlib/stats/strided/smskmin/README.md index 9887b4b6f193..6465dbef5fbd 100644 --- a/lib/node_modules/@stdlib/stats/strided/smskmin/README.md +++ b/lib/node_modules/@stdlib/stats/strided/smskmin/README.md @@ -232,7 +232,7 @@ Computes the minimum value of a single-precision floating-point strided array ac const float x[] = { 1.0f, -2.0f, 2.0f }; const uint8_t mask[] = { 0, 1, 0 }; -float v = stdlib_strided_smskmin( 3, x, 1, 0, mask, 1, 0 ); +float v = stdlib_strided_smskmin_ndarray( 3, x, 1, 0, mask, 1, 0 ); // returns 1.0f ``` diff --git a/lib/node_modules/@stdlib/stats/strided/smskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smskmin/benchmark/benchmark.js index cf1ce51a6c6e..53fce20173a6 100644 --- a/lib/node_modules/@stdlib/stats/strided/smskmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smskmin/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskmin = require( './../lib/smskmin.js' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smskmin/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smskmin/benchmark/benchmark.native.js index 2fa0ada64077..816eb3576037 100644 --- a/lib/node_modules/@stdlib/stats/strided/smskmin/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smskmin/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smskmin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smskmin/benchmark/benchmark.ndarray.js index 29f820b06d84..b2f27baebbb1 100644 --- a/lib/node_modules/@stdlib/stats/strided/smskmin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smskmin/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskmin = require( './../lib/ndarray.js' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smskmin/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smskmin/benchmark/benchmark.ndarray.native.js index 99d96e0bd3d3..d0dbb6209ef9 100644 --- a/lib/node_modules/@stdlib/stats/strided/smskmin/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smskmin/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smskrange/README.md b/lib/node_modules/@stdlib/stats/strided/smskrange/README.md index 420c05ccbf18..2025a0b8dbd2 100644 --- a/lib/node_modules/@stdlib/stats/strided/smskrange/README.md +++ b/lib/node_modules/@stdlib/stats/strided/smskrange/README.md @@ -234,7 +234,7 @@ Computes the [range][range] of a single-precision floating-point strided array a const float x[] = { 1.0f, -2.0f, 2.0f }; const uint8_t mask[] = { 0, 1, 0 }; -float v = stdlib_strided_smskrange( 3, x, 1, 0, mask, 1, 0 ); +float v = stdlib_strided_smskrange_ndarray( 3, x, 1, 0, mask, 1, 0 ); // returns 1.0f ``` diff --git a/lib/node_modules/@stdlib/stats/strided/smskrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/smskrange/benchmark/benchmark.js index 7d5e78d061f5..cfdab41ba5a7 100644 --- a/lib/node_modules/@stdlib/stats/strided/smskrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/smskrange/benchmark/benchmark.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskrange = require( './../lib/smskrange.js' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smskrange/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/smskrange/benchmark/benchmark.native.js index 83a0bc1b6929..fb47a51d4e11 100644 --- a/lib/node_modules/@stdlib/stats/strided/smskrange/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smskrange/benchmark/benchmark.native.js @@ -27,6 +27,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smskrange/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/smskrange/benchmark/benchmark.ndarray.js index fa7b423ac843..0ba1c5e5f8d2 100644 --- a/lib/node_modules/@stdlib/stats/strided/smskrange/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/smskrange/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var smskrange = require( './../lib/ndarray.js' ); @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/smskrange/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/smskrange/benchmark/benchmark.ndarray.native.js index efcad727f2f3..cac1b4ed0bd4 100644 --- a/lib/node_modules/@stdlib/stats/strided/smskrange/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/smskrange/benchmark/benchmark.ndarray.native.js @@ -27,6 +27,7 @@ var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -105,7 +106,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/README.md b/lib/node_modules/@stdlib/stats/strided/snancount/README.md new file mode 100644 index 000000000000..3ea900e67418 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/README.md @@ -0,0 +1,301 @@ + + +# snancount + +> Calculate the number of non-`NaN` elements in a single-precision floating-point strided array. + +
+ +
+ + + +
+ +## Usage + +```javascript +var snancount = require( '@stdlib/stats/strided/snancount' ); +``` + +#### snancount( N, x, strideX ) + +Computes the number of non-`NaN` elements in a single-precision floating-point strided array. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] ); + +var v = snancount( x.length, x, 1 ); +// returns 3 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: input [`Float32Array`][@stdlib/array/float32]. +- **strideX**: stride length for `x`. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to count every other element in `x`, + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, 2.0, NaN, -2.0, 4.0, 3.0, NaN, NaN ] ); + +var v = snancount( 4, x, 2 ); +// returns 2 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x0 = new Float32Array( [ 2.0, 1.0, NaN, -2.0, 3.0, 4.0, NaN, NaN ] ); +var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +var v = snancount( 4, x1, 2 ); +// returns 3 +``` + +#### snancount.ndarray( N, x, strideX, offsetX ) + +Computes the number of non-`NaN` elements in a single-precision floating-point strided array using alternative indexing semantics. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, NaN, NaN ] ); + +var v = snancount.ndarray( 4, x, 2, 1 ); +// returns 3 +``` + +The function has the following additional parameter: + +- **offsetX**: starting index for `x`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to count every other element in `x` starting from the second element, + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 2.0, 1.0, NaN, -2.0, 3.0, 4.0, NaN, NaN ] ); + +var v = snancount.ndarray( 4, x, 2, 1 ); +// returns 3 +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `0`. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var snancount = require( '@stdlib/stats/strided/snancount' ); + +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -50.0, 50.0 ); +} + +var x = filledarrayBy( 10, 'float32', rand ); +console.log( x ); + +var v = snancount( x.length, x, 1 ); +console.log( v ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/strided/snancount.h" +``` + +#### stdlib_strided_snancount( N, \*X, strideX ) + +Computes the number of non-`NaN` elements in a single-precision floating-point strided array. + +```c +const float x[] = { 1.0f, 2.0f, 0.0f / 0.0f, 4.0f, 5.0f, 6.0f, 0.0f / 0.0f, 8.0f }; + +int v = stdlib_strided_snancount( 4, x, 2 ); +// returns 2 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +CBLAS_INT stdlib_strided_snancount( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_snancount_ndarray( N, \*X, strideX, offsetX ) + +Computes the number of non-`NaN` elements in a single-precision floating-point strided array using alternative indexing semantics. + +```c +const float x[] = { 2.0f, 1.0f, 0.0f / 0.0f, -2.0f, 3.0f, 4.0f, 0.0f / 0.0f, 0.0f / 0.0f }; + +int v = stdlib_strided_snancount_ndarray( 4, x, 2, 1 ); +// returns 3 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +CBLAS_INT stdlib_strided_snancount_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + + + +
+ +### Notes + +- If `N <= 0`, both functions return `0`. + +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/strided/snancount.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 0.0f/0.0f, 0.0f/0.0f }; + + // Specify the number of elements: + const int N = 5; + + // Specify the stride length: + const int strideX = 2; + + // Compute the number of non-NaN elements: + int v = stdlib_strided_snancount( N, x, strideX ); + + // Print the result: + printf( "count: %d\n", v ); +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float32 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/benchmark.js new file mode 100644 index 000000000000..aea556b0f7a0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/benchmark.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var format = require( '@stdlib/string/format' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var pkg = require( './../package.json' ).name; +var snancount = require( './../lib/snancount.js' ); + + +// FUNCTIONS // + +/** +* Returns a random number. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = filledarrayBy( len, 'float32', rand ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = snancount( x.length, x, 1 ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/benchmark.native.js new file mode 100644 index 000000000000..b83b85a90244 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/benchmark.native.js @@ -0,0 +1,120 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var format = require( '@stdlib/string/format' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var snancount = tryRequire( resolve( __dirname, './../lib/snancount.native.js' ) ); +var opts = { + 'skip': ( snancount instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Returns a random number. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = filledarrayBy( len, 'float32', rand ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = snancount( x.length, x, 1 ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..c319df374b1b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/benchmark.ndarray.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var format = require( '@stdlib/string/format' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var pkg = require( './../package.json' ).name; +var snancount = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Returns a random number. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = filledarrayBy( len, 'float32', rand ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = snancount( x.length, x, 1, 0 ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..94584d55e493 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,120 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var format = require( '@stdlib/string/format' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var snancount = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( snancount instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Returns a random number. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = filledarrayBy( len, 'float32', rand ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = snancount( x.length, x, 1, 0 ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..c442b2c6e957 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/benchmark/c/benchmark.length.c @@ -0,0 +1,205 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/snancount.h" +#include +#include +#include +#include +#include + +#define NAME "snancount" +#define ITERATIONS 1000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static float rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + float x[ len ]; + double t; + int v; + int i; + + for ( i = 0; i < len; i++ ) { + if ( rand_float() < 0.2f ) { + x[ i ] = 0.0f / 0.0f; // NaN + } else { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + } + v = 0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_snancount( len, x, 1 ); + if ( v < 0 ) { + printf( "should return a non-negative integer\n" ); + break; + } + } + elapsed = tic() - t; + if ( v < 0 ) { + printf( "should return a non-negative integer\n" ); + } + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + double t; + int v; + int i; + + for ( i = 0; i < len; i++ ) { + if ( rand_float() < 0.2f ) { + x[ i ] = 0.0f / 0.0f; // NaN + } else { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + } + v = 0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_snancount_ndarray( len, x, 1, 0 ); + if ( v < 0 ) { + printf( "should return a non-negative integer\n" ); + break; + } + } + elapsed = tic() - t; + if ( v < 0 ) { + printf( "should return a non-negative integer\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/binding.gyp b/lib/node_modules/@stdlib/stats/strided/snancount/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/snancount/docs/repl.txt new file mode 100644 index 000000000000..8df0ab1ec2fb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/docs/repl.txt @@ -0,0 +1,89 @@ + +{{alias}}( N, x, strideX ) + Computes the number of non-`NaN` elements in a single-precision floating- + point strided array. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `0`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float32Array + Input array. + + strideX: integer + Stride length. + + Returns + ------- + out: integer + Number of non-`NaN` elements. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, NaN, 2.0 ] ); + > {{alias}}( x.length, x, 1 ) + 3 + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, NaN, -5.0, 2.0, -1.0, NaN ] ); + > {{alias}}( 3, x, 2 ) + 2 + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, NaN, 5.0, -1.0, NaN ] ); + > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 3, x1, 2 ) + 2 + + +{{alias}}.ndarray( N, x, strideX, offsetX ) + Computes the number of non-`NaN` elements in a single-precision floating- + point strided array using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float32Array + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + out: integer + Number of non-`NaN` elements. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, NaN, 2.0 ] ); + > {{alias}}.ndarray( x.length, x, 1, 0 ) + 3 + + // Using offset parameter: + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, NaN, 5.0, -1.0, NaN ] ); + > {{alias}}.ndarray( 3, x, 2, 1 ) + 2 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/strided/snancount/docs/types/index.d.ts new file mode 100644 index 000000000000..143882e84cd3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/docs/types/index.d.ts @@ -0,0 +1,92 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `snancount`. +*/ +interface Routine { + /** + * Computes the number of non-`NaN` elements in a single-precision floating-point strided array. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length + * @returns number of non-`NaN` elements + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] ); + * + * var v = snancount( x.length, x, 1 ); + * // returns 3 + */ + ( N: number, x: Float32Array, strideX: number ): number; + + /** + * Computes the number of non-`NaN` elements in a single-precision floating-point strided array using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns number of non-`NaN` elements + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] ); + * + * var v = snancount.ndarray( x.length, x, 1, 0 ); + * // returns 3 + */ + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number; +} + +/** +* Computes the number of non-`NaN` elements in a single-precision floating-point strided array. +* +* @param N - number of indexed elements +* @param x - input array +* @param strideX - stride length +* @returns number of non-`NaN` elements +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] ); +* +* var v = snancount( x.length, x, 1 ); +* // returns 3 +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] ); +* +* var v = snancount.ndarray( x.length, x, 1, 0 ); +* // returns 3 +*/ +declare var snancount: Routine; + + +// EXPORTS // + +export = snancount; diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/docs/types/test.ts b/lib/node_modules/@stdlib/stats/strided/snancount/docs/types/test.ts new file mode 100644 index 000000000000..65fa627d21ba --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/docs/types/test.ts @@ -0,0 +1,157 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import snancount = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = new Float32Array( 10 ); + + snancount( x.length, x, 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float32Array( 10 ); + + snancount( '10', x, 1 ); // $ExpectError + snancount( true, x, 1 ); // $ExpectError + snancount( false, x, 1 ); // $ExpectError + snancount( null, x, 1 ); // $ExpectError + snancount( undefined, x, 1 ); // $ExpectError + snancount( [], x, 1 ); // $ExpectError + snancount( {}, x, 1 ); // $ExpectError + snancount( ( x: number ): number => x, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Float32Array... +{ + const x = new Float32Array( 10 ); + + snancount( x.length, 10, 1 ); // $ExpectError + snancount( x.length, '10', 1 ); // $ExpectError + snancount( x.length, true, 1 ); // $ExpectError + snancount( x.length, false, 1 ); // $ExpectError + snancount( x.length, null, 1 ); // $ExpectError + snancount( x.length, undefined, 1 ); // $ExpectError + snancount( x.length, [], 1 ); // $ExpectError + snancount( x.length, {}, 1 ); // $ExpectError + snancount( x.length, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Float32Array( 10 ); + + snancount( x.length, x, '10' ); // $ExpectError + snancount( x.length, x, true ); // $ExpectError + snancount( x.length, x, false ); // $ExpectError + snancount( x.length, x, null ); // $ExpectError + snancount( x.length, x, undefined ); // $ExpectError + snancount( x.length, x, [] ); // $ExpectError + snancount( x.length, x, {} ); // $ExpectError + snancount( x.length, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float32Array( 10 ); + + snancount(); // $ExpectError + snancount( x.length ); // $ExpectError + snancount( x.length, x ); // $ExpectError + snancount( x.length, x, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + const x = new Float32Array( 10 ); + + snancount.ndarray( x.length, x, 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float32Array( 10 ); + + snancount.ndarray( '10', x, 1, 0 ); // $ExpectError + snancount.ndarray( true, x, 1, 0 ); // $ExpectError + snancount.ndarray( false, x, 1, 0 ); // $ExpectError + snancount.ndarray( null, x, 1, 0 ); // $ExpectError + snancount.ndarray( undefined, x, 1, 0 ); // $ExpectError + snancount.ndarray( [], x, 1, 0 ); // $ExpectError + snancount.ndarray( {}, x, 1, 0 ); // $ExpectError + snancount.ndarray( ( x: number ): number => x, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Float32Array... +{ + const x = new Float32Array( 10 ); + + snancount.ndarray( x.length, 10, 1, 0 ); // $ExpectError + snancount.ndarray( x.length, '10', 1, 0 ); // $ExpectError + snancount.ndarray( x.length, true, 1, 0 ); // $ExpectError + snancount.ndarray( x.length, false, 1, 0 ); // $ExpectError + snancount.ndarray( x.length, null, 1, 0 ); // $ExpectError + snancount.ndarray( x.length, undefined, 1, 0 ); // $ExpectError + snancount.ndarray( x.length, [], 1, 0 ); // $ExpectError + snancount.ndarray( x.length, {}, 1, 0 ); // $ExpectError + snancount.ndarray( x.length, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Float32Array( 10 ); + + snancount.ndarray( x.length, x, '10', 0 ); // $ExpectError + snancount.ndarray( x.length, x, true, 0 ); // $ExpectError + snancount.ndarray( x.length, x, false, 0 ); // $ExpectError + snancount.ndarray( x.length, x, null, 0 ); // $ExpectError + snancount.ndarray( x.length, x, undefined, 0 ); // $ExpectError + snancount.ndarray( x.length, x, [], 0 ); // $ExpectError + snancount.ndarray( x.length, x, {}, 0 ); // $ExpectError + snancount.ndarray( x.length, x, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float32Array( 10 ); + + snancount.ndarray( x.length, x, 1, '10' ); // $ExpectError + snancount.ndarray( x.length, x, 1, true ); // $ExpectError + snancount.ndarray( x.length, x, 1, false ); // $ExpectError + snancount.ndarray( x.length, x, 1, null ); // $ExpectError + snancount.ndarray( x.length, x, 1, undefined ); // $ExpectError + snancount.ndarray( x.length, x, 1, [] ); // $ExpectError + snancount.ndarray( x.length, x, 1, {} ); // $ExpectError + snancount.ndarray( x.length, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float32Array( 10 ); + + snancount.ndarray(); // $ExpectError + snancount.ndarray( x.length ); // $ExpectError + snancount.ndarray( x.length, x ); // $ExpectError + snancount.ndarray( x.length, x, 1 ); // $ExpectError + snancount.ndarray( x.length, x, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/examples/c/Makefile b/lib/node_modules/@stdlib/stats/strided/snancount/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/examples/c/example.c b/lib/node_modules/@stdlib/stats/strided/snancount/examples/c/example.c new file mode 100644 index 000000000000..e961c8a5418c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/examples/c/example.c @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/snancount.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 0.0f/0.0f, 0.0f/0.0f }; + + // Specify the number of elements: + const int N = 5; + + // Specify the stride length: + const int strideX = 2; + + // Compute the number of non-NaN elements: + int v = stdlib_strided_snancount( N, x, strideX ); + + // Print the result: + printf( "count: %d\n", v ); +} diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/examples/index.js b/lib/node_modules/@stdlib/stats/strided/snancount/examples/index.js new file mode 100644 index 000000000000..db55b6dcc62b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var snancount = require( './../lib' ); + +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -50.0, 50.0 ); +} + +var x = filledarrayBy( 10, 'float32', rand ); +console.log( x ); + +var v = snancount( x.length, x, 1 ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/include.gypi b/lib/node_modules/@stdlib/stats/strided/snancount/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "count", + "nancount", + "non-nan", + "nan", + "strided", + "strided array", + "typed", + "array", + "float32", + "float", + "single", + "float32array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/src/Makefile b/lib/node_modules/@stdlib/stats/strided/snancount/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/src/addon.c b/lib/node_modules/@stdlib/stats/strided/snancount/src/addon.c new file mode 100644 index 000000000000..3b866abaf54b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/src/addon.c @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/snancount.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_int32.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_INT32( env, API_SUFFIX(stdlib_strided_snancount)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_INT32( env, API_SUFFIX(stdlib_strided_snancount_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/src/main.c b/lib/node_modules/@stdlib/stats/strided/snancount/src/main.c new file mode 100644 index 000000000000..ee8d65504a85 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/src/main.c @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/snancount.h" +#include "stdlib/math/base/assert/is_nanf.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the number of non-`NaN` elements in a single-precision floating-point strided array. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return number of non-`NaN` elements +*/ +CBLAS_INT API_SUFFIX(stdlib_strided_snancount)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_snancount_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the number of non-`NaN` elements in a single-precision floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return number of non-`NaN` elements +*/ +CBLAS_INT API_SUFFIX(stdlib_strided_snancount_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT count; + CBLAS_INT ix; + CBLAS_INT i; + + if ( N <= 0 ) { + return 0; + } + count = 0; + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( !stdlib_base_is_nanf( X[ ix ] ) ) { + count += 1; + } + ix += strideX; + } + return count; +} diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/test/test.js b/lib/node_modules/@stdlib/stats/strided/snancount/test/test.js new file mode 100644 index 000000000000..51b461132948 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var snancount = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof snancount, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof snancount.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var snancount = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( snancount, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var snancount; + var main; + + main = require( './../lib/snancount.js' ); + + snancount = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( snancount, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/strided/snancount/test/test.ndarray.js new file mode 100644 index 000000000000..1374a2452fb7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/test/test.ndarray.js @@ -0,0 +1,163 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var snancount = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof snancount, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', function test( t ) { + t.strictEqual( snancount.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function counts the number of non-NaN elements in a strided array', function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0, -2.0, -4.0, NaN, 5.0, 0.0, 3.0 ] ); + + v = snancount( x.length, x, 1, 0 ); + t.strictEqual( v, 6, 'returns expected value' ); + + v = snancount( 1, x, 1, 3 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = snancount( 0, x, 1, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + + v = snancount( -1, x, 1, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function counts the first indexed element', function test( t ) { + var x; + var v; + + x = new Float32Array( [ NaN, -2.0, -4.0, 5.0, 3.0 ] ); + + v = snancount( 1, x, 1, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + + x[ 0 ] = 1.0; + v = snancount( 1, x, 1, 0 ); + t.strictEqual( v, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter', function test( t ) { + var x; + var v; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]); + + v = snancount( 5, x, 2, 0 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter', function test( t ) { + var x; + var v; + + x = new Float32Array([ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = snancount( 5, x, -2, 8 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function counts repeated indexed elements', function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = snancount( x.length, x, 0, 0 ); + t.strictEqual( v, x.length, 'returns expected value' ); + + x[ 0 ] = NaN; + v = snancount( x.length, x, 0, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `offset` parameter', function test( t ) { + var x; + var v; + + x = new Float32Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + NaN, + NaN // 4 + ]); + + v = snancount( 5, x, 2, 1 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/snancount/test/test.ndarray.native.js new file mode 100644 index 000000000000..620f2422495e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/test/test.ndarray.native.js @@ -0,0 +1,173 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var snancount = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( snancount instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof snancount, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', opts, function test( t ) { + t.strictEqual( snancount.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function counts the number of non-NaN elements in a strided array', opts, function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0, -2.0, -4.0, NaN, 5.0, 0.0, 3.0 ] ); + + v = snancount( x.length, x, 1, 0 ); + t.strictEqual( v, 6, 'returns expected value' ); + + v = snancount( 1, x, 1, 3 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', opts, function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = snancount( 0, x, 1, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + + v = snancount( -1, x, 1, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function counts the first indexed element', opts, function test( t ) { + var x; + var v; + + x = new Float32Array( [ NaN, -2.0, -4.0, 5.0, 3.0 ] ); + + v = snancount( 1, x, 1, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + + x[ 0 ] = 1.0; + v = snancount( 1, x, 1, 0 ); + t.strictEqual( v, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var x; + var v; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]); + + v = snancount( 5, x, 2, 0 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var x; + var v; + + x = new Float32Array([ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = snancount( 5, x, -2, 8 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function counts repeated indexed elements', opts, function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = snancount( x.length, x, 0, 0 ); + t.strictEqual( v, x.length, 'returns expected value' ); + + x[ 0 ] = NaN; + v = snancount( x.length, x, 0, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `offset` parameter', opts, function test( t ) { + var x; + var v; + + x = new Float32Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + NaN, + NaN // 4 + ]); + + v = snancount( 5, x, 2, 1 ); + t.strictEqual( v, 4, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/test/test.snancount.js b/lib/node_modules/@stdlib/stats/strided/snancount/test/test.snancount.js new file mode 100644 index 000000000000..f414b6420faf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/test/test.snancount.js @@ -0,0 +1,171 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var snancount = require( './../lib/snancount.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof snancount, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 3', function test( t ) { + t.strictEqual( snancount.length, 3, 'has expected arity' ); + t.end(); +}); + +tape( 'the function counts the number of non-NaN elements in a strided array', function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0, -2.0, -4.0, NaN, 5.0, 0.0, 3.0 ] ); + v = snancount( x.length, x, 1 ); + t.strictEqual( v, 6, 'returns expected value' ); + + x = new Float32Array( [ NaN ] ); + v = snancount( x.length, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + x = new Float32Array( [ NaN, NaN ] ); + v = snancount( x.length, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = snancount( 0, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + v = snancount( -1, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function counts the first element', function test( t ) { + var x; + var v; + + x = new Float32Array( [ NaN, -2.0, -4.0, 5.0, 3.0 ] ); + + v = snancount( 1, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + x[ 0 ] = 1.0; + v = snancount( 1, x, 1 ); + t.strictEqual( v, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter', function test( t ) { + var x; + var v; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]); + + v = snancount( 5, x, 2 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter', function test( t ) { + var x; + var v; + + x = new Float32Array([ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = snancount( 5, x, -2 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function counts repeated indexed elements', function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = snancount( x.length, x, 0 ); + t.strictEqual( v, x.length, 'returns expected value' ); + + x[ 0 ] = NaN; + v = snancount( x.length, x, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var x0; + var x1; + var v; + + x0 = new Float32Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + 6.0, + NaN, // 4 + NaN + ]); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + v = snancount( 5, x1, 2 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/snancount/test/test.snancount.native.js b/lib/node_modules/@stdlib/stats/strided/snancount/test/test.snancount.native.js new file mode 100644 index 000000000000..3e7a6c52f718 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/snancount/test/test.snancount.native.js @@ -0,0 +1,260 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var snancount = tryRequire( resolve( __dirname, './../lib/snancount.native.js' ) ); +var opts = { + 'skip': ( snancount instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof snancount, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 3', opts, function test( t ) { + t.strictEqual( snancount.length, 3, 'has expected arity' ); + t.end(); +}); + +tape( 'the function throws an error if provided a first argument which is not a number', opts, function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + snancount( value, new Float32Array( 10 ), 1 ); + }; + } +}); + +tape( 'the function throws an error if provided a second argument which is not a Float32Array', opts, function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + snancount( 10, value, 1 ); + }; + } +}); + +tape( 'the function throws an error if provided a third argument which is not a number', opts, function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + snancount( 10, new Float32Array( 10 ), value ); + }; + } +}); + +tape( 'the function counts the number of non-NaN elements in a strided array', opts, function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0, -2.0, -4.0, NaN, 5.0, 0.0, 3.0 ] ); + v = snancount( x.length, x, 1 ); + t.strictEqual( v, 6, 'returns expected value' ); + + x = new Float32Array( [ NaN, NaN ] ); + v = snancount( x.length, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', opts, function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = snancount( 0, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + v = snancount( -1, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function counts the first element', opts, function test( t ) { + var x; + var v; + + x = new Float32Array( [ NaN, -2.0, -4.0, 5.0, 3.0 ] ); + + v = snancount( 1, x, 1 ); + t.strictEqual( v, 0, 'returns expected value' ); + + x[ 0 ] = 1.0; + v = snancount( 1, x, 1 ); + t.strictEqual( v, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var x; + var v; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]); + + v = snancount( 5, x, 2 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var x; + var v; + + x = new Float32Array([ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = snancount( 5, x, -2 ); + t.strictEqual( v, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function counts repeated indexed elements', opts, function test( t ) { + var x; + var v; + + x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = snancount( x.length, x, 0 ); + t.strictEqual( v, x.length, 'returns expected value' ); + + x[ 0 ] = NaN; + v = snancount( x.length, x, 0 ); + t.strictEqual( v, 0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var x0; + var x1; + var v; + + x0 = new Float32Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + 6.0, + NaN, // 4 + NaN + ]); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + + v = snancount( 5, x1, 2 ); + t.strictEqual( v, 4, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/snanmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/snanmax/benchmark/benchmark.js index e33597992393..b3628ceca2f5 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmax/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmax = require( './../lib/snanmax.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/snanmax/benchmark/benchmark.native.js index 14ecfa27b011..5e757d17957f 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmax/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmax/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/snanmax/benchmark/benchmark.ndarray.js index 5faec0290a84..b52f6e08ac7f 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmax/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmax/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmax = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/snanmax/benchmark/benchmark.ndarray.native.js index 6409bd732b82..87ed516defa3 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmax/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmax/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/snanmaxabs/benchmark/benchmark.js index 8169a1008f17..491dceeb77ea 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmaxabs/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmaxabs = require( './../lib/snanmaxabs.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmaxabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/snanmaxabs/benchmark/benchmark.native.js index 5a8e2b2643be..e843148c9d30 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmaxabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmaxabs/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmaxabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/snanmaxabs/benchmark/benchmark.ndarray.js index 2748a6b86cce..34f23f3ffba7 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmaxabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmaxabs/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmaxabs = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmaxabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/snanmaxabs/benchmark/benchmark.ndarray.native.js index f0e45f6b035a..9db860373ef9 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmaxabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmaxabs/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/snanmean/benchmark/benchmark.js index 499a4385db3b..352b652a78c3 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmean/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmean = require( './../lib/snanmean.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmean/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/snanmean/benchmark/benchmark.native.js index 6550da071426..9ff4b2eae9d1 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmean/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmean/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmean/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/snanmean/benchmark/benchmark.ndarray.js index 613945d36273..b8ab4f13c6b1 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmean/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmean/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmean = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmean/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/snanmean/benchmark/benchmark.ndarray.native.js index 5a29c4241060..be4440a99988 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmean/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmean/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/snanmeanors/benchmark/benchmark.js index 4b3705f4d8d4..a328a8cf17de 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmeanors/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmeanors = require( './../lib/snanmeanors.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmeanors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/snanmeanors/benchmark/benchmark.native.js index eb1d3ad4dafd..7f8410dd4628 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmeanors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmeanors/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmeanors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/snanmeanors/benchmark/benchmark.ndarray.js index 51607fb4ffa7..c900229ab3d4 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmeanors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmeanors/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmeanors = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmeanors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/snanmeanors/benchmark/benchmark.ndarray.native.js index 613937012cb5..913165e50abb 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmeanors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmeanors/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmeanpn/README.md b/lib/node_modules/@stdlib/stats/strided/snanmeanpn/README.md index 1a92d6f66d35..4ada5e41af00 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmeanpn/README.md +++ b/lib/node_modules/@stdlib/stats/strided/snanmeanpn/README.md @@ -203,10 +203,10 @@ console.log( v ); Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array, ignoring `NaN` values and using a two-pass error correction algorithm. ```c -const double x[] = { 1.0f, -2.0f, 0.0f/0.0f, 2.0f }; +const float x[] = { 1.0f, -2.0f, 0.0f/0.0f, 2.0f }; -double v = stdlib_strided_snanmeanpn( 4, x, 1 ); -// returns ~0.33333 +float v = stdlib_strided_snanmeanpn( 4, x, 1 ); +// returns ~0.33333f ``` The function accepts the following arguments: @@ -224,10 +224,10 @@ float stdlib_strided_snanmeanpn( const CBLAS_INT N, const float *X, const CBLAS_ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array, ignoring `NaN` values and using a two-pass error correction algorithm and alternative indexing semantics. ```c -const double x[] = { 1.0f, -2.0f, 0.0f/0.0f, 2.0f }; +const float x[] = { 1.0f, -2.0f, 0.0f/0.0f, 2.0f }; -double v = stdlib_strided_snanmeanpn_ndarray( 4, x, 1, 0 ); -// returns ~0.33333 +float v = stdlib_strided_snanmeanpn_ndarray( 4, x, 1, 0 ); +// returns ~0.33333f ``` The function accepts the following arguments: diff --git a/lib/node_modules/@stdlib/stats/strided/snanmeanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/snanmeanpn/benchmark/benchmark.js index 8281b049757a..a206c1fc777d 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmeanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmeanpn/benchmark/benchmark.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmeanpn = require( './../lib/snanmeanpn.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmeanpn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/snanmeanpn/benchmark/benchmark.native.js index 1db1b4980b2e..738e2cdecaac 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmeanpn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmeanpn/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmeanpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/snanmeanpn/benchmark/benchmark.ndarray.js index 7d71a5705d6e..d444809cd6a9 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmeanpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmeanpn/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmeanpn = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmeanpn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/snanmeanpn/benchmark/benchmark.ndarray.native.js index b9031e9c5cc4..8c03ea90429a 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmeanpn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmeanpn/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/snanmeanwd/benchmark/benchmark.js index 2416aacfc7ac..5f969151cc13 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmeanwd/benchmark/benchmark.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmeanwd = require( './../lib/snanmeanwd.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmeanwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/snanmeanwd/benchmark/benchmark.native.js index 22ee5c1706be..573a4cd3c8a0 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmeanwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmeanwd/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmeanwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/snanmeanwd/benchmark/benchmark.ndarray.js index 669bae1bae2d..9ac27e06ac47 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmeanwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmeanwd/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmeanwd = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmeanwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/snanmeanwd/benchmark/benchmark.ndarray.native.js index 2c7d604c7b8a..c9798707d463 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmeanwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmeanwd/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var uniform = require( '@stdlib/random/base/uniform' ); var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/snanmin/benchmark/benchmark.js index 348a9e021c74..a410f006c24b 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmin = require( './../lib/snanmin.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmin/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/snanmin/benchmark/benchmark.native.js index 8810167482e3..353dca2a48fa 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmin/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmin/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/snanmin/benchmark/benchmark.ndarray.js index dd885783eeb5..a1f28d1bce00 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmin/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmin = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmin/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/snanmin/benchmark/benchmark.ndarray.native.js index a38cd56700d0..aeded474fd97 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmin/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmin/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/snanminabs/benchmark/benchmark.js index aaba19af491a..7f4e93ee1597 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/snanminabs/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanminabs = require( './../lib/snanminabs.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanminabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/snanminabs/benchmark/benchmark.native.js index 52fd2abd2721..38fcda0e0573 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanminabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanminabs/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanminabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/snanminabs/benchmark/benchmark.ndarray.js index 309cae4be4be..7b527024a3f1 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanminabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/snanminabs/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanminabs = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanminabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/snanminabs/benchmark/benchmark.ndarray.native.js index f7eb8e193542..422366c5da31 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanminabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanminabs/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmskmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/snanmskmax/benchmark/benchmark.js index ab3cb6e62eae..fc7871193762 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmskmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmskmax/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmskmax = require( './../lib/snanmskmax.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmskmax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/snanmskmax/benchmark/benchmark.native.js index dc4529a17b99..649bc45bfd6f 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmskmax/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmskmax/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmskmax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/snanmskmax/benchmark/benchmark.ndarray.js index 949e489ad137..a7a638025d52 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmskmax/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmskmax/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmskmax = require( './../lib/ndarray.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmskmax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/snanmskmax/benchmark/benchmark.ndarray.native.js index b5667654d070..bb249d82e1ab 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmskmax/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmskmax/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/snanmskmin/benchmark/benchmark.js index 1c8515b11868..a82013855691 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmskmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmskmin/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmskmin = require( './../lib/snanmskmin.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmskmin/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/snanmskmin/benchmark/benchmark.native.js index af1cda9d9e78..bc000b5cc32f 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmskmin/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmskmin/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmskmin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/snanmskmin/benchmark/benchmark.ndarray.js index e55ae7186bf2..d28e09a66eb8 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmskmin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmskmin/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmskmin = require( './../lib/ndarray.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmskmin/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/snanmskmin/benchmark/benchmark.ndarray.native.js index 2f5c1e997296..463810d266c9 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmskmin/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmskmin/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmskrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/snanmskrange/benchmark/benchmark.js index ad7eab110d0d..4d2f46468cc7 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmskrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmskrange/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmskrange = require( './../lib/snanmskrange.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmskrange/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/snanmskrange/benchmark/benchmark.native.js index a539067a550a..55f26fc67f25 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmskrange/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmskrange/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmskrange/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/snanmskrange/benchmark/benchmark.ndarray.js index edcc41f58fc5..0f6560b76a87 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmskrange/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmskrange/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanmskrange = require( './../lib/ndarray.js' ); @@ -107,7 +108,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanmskrange/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/snanmskrange/benchmark/benchmark.ndarray.native.js index b279728b9b98..9057c9f3d87c 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanmskrange/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanmskrange/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -116,7 +117,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/snanrange/benchmark/benchmark.js index 363e5bb8d713..b95a682dad8a 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/snanrange/benchmark/benchmark.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanrange = require( './../lib/snanrange.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanrange/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/snanrange/benchmark/benchmark.native.js index 66ee345c0115..3810f8db85e9 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanrange/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanrange/benchmark/benchmark.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanrange/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/snanrange/benchmark/benchmark.ndarray.js index 91f9340d42b7..0cde1aa29c73 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanrange/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/snanrange/benchmark/benchmark.ndarray.js @@ -26,6 +26,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var snanrange = require( './../lib/ndarray.js' ); @@ -103,7 +104,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/snanrange/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/snanrange/benchmark/benchmark.ndarray.native.js index 0bb3b85e98a6..854f86a9777b 100644 --- a/lib/node_modules/@stdlib/stats/strided/snanrange/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/snanrange/benchmark/benchmark.ndarray.native.js @@ -28,6 +28,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -112,7 +113,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/srange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/srange/benchmark/benchmark.js index 422e485fcd05..e0e54a21c28c 100644 --- a/lib/node_modules/@stdlib/stats/strided/srange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/srange/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var srange = require( './../lib/srange.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/srange/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/srange/benchmark/benchmark.native.js index 064123b90b83..f27d29f0144e 100644 --- a/lib/node_modules/@stdlib/stats/strided/srange/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/srange/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/srange/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/srange/benchmark/benchmark.ndarray.js index 04c81ddb82a3..b17cde4987d2 100644 --- a/lib/node_modules/@stdlib/stats/strided/srange/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/srange/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var srange = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/srange/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/srange/benchmark/benchmark.ndarray.native.js index 6a167ac6d0ea..8dbfb9ff54c2 100644 --- a/lib/node_modules/@stdlib/stats/strided/srange/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/srange/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/sstdev/benchmark/benchmark.js index 47ce05106ef5..e32cd6320e30 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdev/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sstdev = require( './../lib/sstdev.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdev/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/sstdev/benchmark/benchmark.native.js index 2b67f0810e21..eb4ef436fa57 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdev/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdev/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdev/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/sstdev/benchmark/benchmark.ndarray.js index 210e1ec5fde5..853e9bc35d61 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdev/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdev/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sstdev = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdev/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/sstdev/benchmark/benchmark.ndarray.native.js index 9e883e6395bb..c19e97a06dab 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdev/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdev/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevch/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/sstdevch/benchmark/benchmark.js index 5bea92980953..c34df8996ebc 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevch/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevch/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sstdevch = require( './../lib/sstdevch.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevch/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/sstdevch/benchmark/benchmark.native.js index c1ab7db29405..8420c52e69aa 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevch/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevch/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevch/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/sstdevch/benchmark/benchmark.ndarray.js index 0bfbd1c0b67f..3ff1d8fe916d 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevch/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevch/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sstdevch = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevch/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/sstdevch/benchmark/benchmark.ndarray.native.js index ad738706aa76..3c73390b1bed 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevch/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevch/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/sstdevpn/benchmark/benchmark.js index 17e874ec4be3..65984470bcb3 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevpn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sstdevpn = require( './../lib/sstdevpn.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevpn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/sstdevpn/benchmark/benchmark.native.js index 5d03a9fe78b8..252b954237dc 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevpn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevpn/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/sstdevpn/benchmark/benchmark.ndarray.js index 1a7559953323..34080d3b21fc 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevpn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sstdevpn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevpn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/sstdevpn/benchmark/benchmark.ndarray.native.js index db43ec1a4a9f..4bc95abfb83d 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevpn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevpn/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/sstdevtk/benchmark/benchmark.js index 6093e4c83d3d..4e0a0aab9014 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevtk/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sstdevtk = require( './../lib/sstdevtk.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevtk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/sstdevtk/benchmark/benchmark.native.js index 2b929bf296d3..184931825d0b 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevtk/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevtk/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevtk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/sstdevtk/benchmark/benchmark.ndarray.js index 30d31cf2f4f1..5cec6e481e95 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevtk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevtk/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sstdevtk = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevtk/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/sstdevtk/benchmark/benchmark.ndarray.native.js index 80f5c210b5cc..2e304b3a1790 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevtk/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevtk/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/sstdevwd/benchmark/benchmark.js index 1e9a4d4596bb..ef471917f9d5 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevwd/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sstdevwd = require( './../lib/sstdevwd.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/sstdevwd/benchmark/benchmark.native.js index 9c6f24caf61d..00e239980b65 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevwd/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/sstdevwd/benchmark/benchmark.ndarray.js index 09db905aea52..bc2cb0b9cac6 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevwd/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sstdevwd = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/sstdevwd/benchmark/benchmark.ndarray.native.js index 6dcd5397f24f..b4a0477c1e07 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevwd/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/sstdevyc/benchmark/benchmark.js index ae5112ee9e4b..4d757c56a1ae 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevyc/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sstdevyc = require( './../lib/sstdevyc.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevyc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/sstdevyc/benchmark/benchmark.native.js index f1f8654bca95..76dd2a305204 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevyc/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevyc/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/sstdevyc/benchmark/benchmark.ndarray.js index b242ce818701..023c32a578bc 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevyc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevyc/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var sstdevyc = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/sstdevyc/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/sstdevyc/benchmark/benchmark.ndarray.native.js index 4f55eb5862ce..69d80c050ecf 100644 --- a/lib/node_modules/@stdlib/stats/strided/sstdevyc/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/sstdevyc/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/stdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/stdev/benchmark/benchmark.js index 803a8eadf5f3..f309af10ed89 100644 --- a/lib/node_modules/@stdlib/stats/strided/stdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/stdev/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var stdev = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/stdev/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/stdev/benchmark/benchmark.ndarray.js index 614c13c5e600..2f702acf5f01 100644 --- a/lib/node_modules/@stdlib/stats/strided/stdev/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/stdev/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var stdev = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/stdevch/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/stdevch/benchmark/benchmark.js index 1716008dc4ec..d7bf6731622f 100644 --- a/lib/node_modules/@stdlib/stats/strided/stdevch/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/stdevch/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var stdevch = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/stdevch/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/stdevch/benchmark/benchmark.ndarray.js index 498c2af1900b..15c4edf83139 100644 --- a/lib/node_modules/@stdlib/stats/strided/stdevch/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/stdevch/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var stdevch = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/stdevpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/stdevpn/benchmark/benchmark.js index 28bb0094ffc7..a7b80a87cbeb 100644 --- a/lib/node_modules/@stdlib/stats/strided/stdevpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/stdevpn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var stdevpn = require( './../lib/stdevpn.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/stdevpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/stdevpn/benchmark/benchmark.ndarray.js index 52ca72b52116..a4bd82317daf 100644 --- a/lib/node_modules/@stdlib/stats/strided/stdevpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/stdevpn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var stdevpn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/stdevtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/stdevtk/benchmark/benchmark.js index 78b0f380c0e2..cab7ac56aa9e 100644 --- a/lib/node_modules/@stdlib/stats/strided/stdevtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/stdevtk/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var stdevtk = require( './../lib/stdevtk.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/stdevtk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/stdevtk/benchmark/benchmark.ndarray.js index 27d3a996e1b1..80972b3eade0 100644 --- a/lib/node_modules/@stdlib/stats/strided/stdevtk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/stdevtk/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var stdevtk = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/stdevwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/stdevwd/benchmark/benchmark.js index 6cd16d4cd665..f3f85e835ec0 100644 --- a/lib/node_modules/@stdlib/stats/strided/stdevwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/stdevwd/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var stdevwd = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/stdevwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/stdevwd/benchmark/benchmark.ndarray.js index d824431017d7..af7aa7d422d1 100644 --- a/lib/node_modules/@stdlib/stats/strided/stdevwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/stdevwd/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var stdevwd = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/stdevyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/stdevyc/benchmark/benchmark.js index 17fb3243346e..b47e5bff5f88 100644 --- a/lib/node_modules/@stdlib/stats/strided/stdevyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/stdevyc/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var stdevyc = require( './../lib/stdevyc.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/stdevyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/stdevyc/benchmark/benchmark.ndarray.js index 777d7dc1eaf8..efefb0c4d9bb 100644 --- a/lib/node_modules/@stdlib/stats/strided/stdevyc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/stdevyc/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var stdevyc = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariance/README.md b/lib/node_modules/@stdlib/stats/strided/svariance/README.md index b8cafd9a1509..a15d615ca6e5 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariance/README.md +++ b/lib/node_modules/@stdlib/stats/strided/svariance/README.md @@ -264,7 +264,7 @@ Computes the [variance][variance] of a single-precision floating-point strided a ```c const float x[] = { 1.0f, -2.0f, 2.0f }; -float v = stdlib_strided_svariance_ndarray( 4, 1.0f, x, 1, 0 ); +float v = stdlib_strided_svariance_ndarray( 3, 1.0f, x, 1, 0 ); // returns ~4.3333f ``` diff --git a/lib/node_modules/@stdlib/stats/strided/svariance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/svariance/benchmark/benchmark.js index a81e05dc14c4..5e7f43b0abb5 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/svariance/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var svariance = require( './../lib/svariance.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariance/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/svariance/benchmark/benchmark.native.js index ca4d754e6038..345176d69d5b 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariance/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/svariance/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariance/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/svariance/benchmark/benchmark.ndarray.js index 144b54fa83e1..c33b6d57af7e 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariance/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/svariance/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var svariance = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariance/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/svariance/benchmark/benchmark.ndarray.native.js index 35de61f9509f..c8002c6adaa9 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariance/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/svariance/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariancech/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/svariancech/benchmark/benchmark.js index 8af201aa897c..a2690f6210fc 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariancech/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/svariancech/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var svariancech = require( './../lib/svariancech.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariancech/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/svariancech/benchmark/benchmark.native.js index 252f4f91c289..b3b743ba9548 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariancech/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/svariancech/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariancech/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/svariancech/benchmark/benchmark.ndarray.js index da1c2faea0ac..a6e9a47fb721 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariancech/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/svariancech/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var svariancech = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariancech/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/svariancech/benchmark/benchmark.ndarray.native.js index b032b57cff81..bdea7fcc3847 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariancech/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/svariancech/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariancepn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/svariancepn/benchmark/benchmark.js index 1205e0cc78e4..980dd2e33372 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariancepn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/svariancepn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var svariancepn = require( './../lib/svariancepn.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariancepn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/svariancepn/benchmark/benchmark.native.js index c00da3dbbc9d..7a6a665b37af 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariancepn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/svariancepn/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariancepn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/svariancepn/benchmark/benchmark.ndarray.js index 9ff72feff300..6d2b3dfbf178 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariancepn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/svariancepn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var svariancepn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariancepn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/svariancepn/benchmark/benchmark.ndarray.native.js index f9f4461a7f55..b04749bb2126 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariancepn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/svariancepn/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariancetk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/svariancetk/benchmark/benchmark.js index 2f018880a7c1..cb49e7eb6c45 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariancetk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/svariancetk/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var svariancetk = require( './../lib/svariancetk.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariancetk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/svariancetk/benchmark/benchmark.native.js index 34057f6ce045..94a22225ec72 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariancetk/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/svariancetk/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariancetk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/svariancetk/benchmark/benchmark.ndarray.js index f8fb66a0756e..2bb1cd43d078 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariancetk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/svariancetk/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var svariancetk = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariancetk/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/svariancetk/benchmark/benchmark.ndarray.native.js index 2f29824542ce..ffa41c0e4e94 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariancetk/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/svariancetk/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariancewd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/svariancewd/benchmark/benchmark.js index cb00a853ec04..8ffe144069ca 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariancewd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/svariancewd/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var svariancewd = require( './../lib/svariancewd.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariancewd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/svariancewd/benchmark/benchmark.native.js index 55d774fa9ebb..a5b0ee9e36ce 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariancewd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/svariancewd/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariancewd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/svariancewd/benchmark/benchmark.ndarray.js index a4680421d8fc..bc5d39e758ea 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariancewd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/svariancewd/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var svariancewd = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svariancewd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/svariancewd/benchmark/benchmark.ndarray.native.js index 070ede69e5e6..341695f25e56 100644 --- a/lib/node_modules/@stdlib/stats/strided/svariancewd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/svariancewd/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svarianceyc/README.md b/lib/node_modules/@stdlib/stats/strided/svarianceyc/README.md index d46115a72872..5aaa8340434e 100644 --- a/lib/node_modules/@stdlib/stats/strided/svarianceyc/README.md +++ b/lib/node_modules/@stdlib/stats/strided/svarianceyc/README.md @@ -264,7 +264,7 @@ Computes the [variance][variance] of a single-precision floating-point strided a ```c const float x[] = { 1.0f, -2.0f, 2.0f }; -float v = stdlib_strided_srange_ndarray( 3, 1, x, 1, 0 ); +float v = stdlib_strided_svarianceyc_ndarray( 3, 1, x, 1, 0 ); // returns ~4.33333f ``` diff --git a/lib/node_modules/@stdlib/stats/strided/svarianceyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/svarianceyc/benchmark/benchmark.js index 8d458167bc97..703b24011f28 100644 --- a/lib/node_modules/@stdlib/stats/strided/svarianceyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/svarianceyc/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var svarianceyc = require( './../lib/svarianceyc.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svarianceyc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/svarianceyc/benchmark/benchmark.native.js index 75da2ecc7d36..af87714b4dcf 100644 --- a/lib/node_modules/@stdlib/stats/strided/svarianceyc/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/svarianceyc/benchmark/benchmark.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svarianceyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/svarianceyc/benchmark/benchmark.ndarray.js index 05f1e3d84776..ce56b32a6318 100644 --- a/lib/node_modules/@stdlib/stats/strided/svarianceyc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/svarianceyc/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var svarianceyc = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/svarianceyc/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/svarianceyc/benchmark/benchmark.ndarray.native.js index ccc9724acaa6..0e8b39730235 100644 --- a/lib/node_modules/@stdlib/stats/strided/svarianceyc/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/svarianceyc/benchmark/benchmark.ndarray.native.js @@ -26,6 +26,7 @@ var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; @@ -100,7 +101,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::native:ndarray:len='+len, opts, f ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/variance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/variance/benchmark/benchmark.js index 30b6237005af..8566af321f29 100644 --- a/lib/node_modules/@stdlib/stats/strided/variance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/variance/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var variance = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/variance/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/variance/benchmark/benchmark.ndarray.js index 2033d117eca0..44ff1da8915d 100644 --- a/lib/node_modules/@stdlib/stats/strided/variance/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/variance/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var variance = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/variancech/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/variancech/benchmark/benchmark.js index fa74125514a6..e908d004cefa 100644 --- a/lib/node_modules/@stdlib/stats/strided/variancech/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/variancech/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var variancech = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/variancech/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/variancech/benchmark/benchmark.ndarray.js index d1b56df2645d..5412ef7f6f72 100644 --- a/lib/node_modules/@stdlib/stats/strided/variancech/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/variancech/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var variancech = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/variancepn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/variancepn/benchmark/benchmark.js index 4e85a0e3afdc..83eafb850807 100644 --- a/lib/node_modules/@stdlib/stats/strided/variancepn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/variancepn/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var variancepn = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/variancepn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/variancepn/benchmark/benchmark.ndarray.js index 004d8e0dc303..e78a5d81c21d 100644 --- a/lib/node_modules/@stdlib/stats/strided/variancepn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/variancepn/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var variancepn = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/variancetk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/variancetk/benchmark/benchmark.js index 0d8552d2e6b7..b5e723efd68d 100644 --- a/lib/node_modules/@stdlib/stats/strided/variancetk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/variancetk/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var variancetk = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/variancetk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/variancetk/benchmark/benchmark.ndarray.js index 3f6a1f2ed396..2ffabe97f96b 100644 --- a/lib/node_modules/@stdlib/stats/strided/variancetk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/variancetk/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var variancetk = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/variancewd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/variancewd/benchmark/benchmark.js index 24d49b1b259e..bcf9b51310b6 100644 --- a/lib/node_modules/@stdlib/stats/strided/variancewd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/variancewd/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var variancewd = require( './../lib/main.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/variancewd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/variancewd/benchmark/benchmark.ndarray.js index cf1914e14c3e..a03695adcac6 100644 --- a/lib/node_modules/@stdlib/stats/strided/variancewd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/variancewd/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var variancewd = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/varianceyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/varianceyc/benchmark/benchmark.js index cd4125336efa..26346e31d65e 100644 --- a/lib/node_modules/@stdlib/stats/strided/varianceyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/varianceyc/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var uniform = require( '@stdlib/random/array/uniform' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var varianceyc = require( './../lib' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, f ); + bench( format( '%s:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/varianceyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/varianceyc/benchmark/benchmark.ndarray.js index 76d11b0a2eb4..d15509422c99 100644 --- a/lib/node_modules/@stdlib/stats/strided/varianceyc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/varianceyc/benchmark/benchmark.ndarray.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var varianceyc = require( './../lib/ndarray.js' ); @@ -95,7 +96,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.js index bdb18062958a..1ec038973495 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanors = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.module.js index 7d8b386ae324..96f6974add15 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanors = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.module.main.js index dcfc855f891c..3d5cbd90e3a6 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanors = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.module.ndarray.js index b89b7ba410c9..765816f0e2ee 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanors = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.ndarray.js index ba8f11d48ee5..a8c6312da03b 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanors = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.js index ed8fc2105b8d..babd669b792b 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanpw = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.js index 17db603bc1ea..f3d90361c633 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanpw = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.main.js index ed2983f52ac1..71710e6eb372 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanpw = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.ndarray.js index 7477ce1ef0c4..9d030f05851a 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanpw = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.ndarray.js index 6af793b6f12f..a7666868592b 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanpw = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.js index 35f8ba262063..1f65cb75a198 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanwd = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.module.js index fd6108158e73..d42691e8b12b 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanwd = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.module.main.js index 608c71a19aed..2b5de34b282f 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.module.main.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanwd = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.module.ndarray.js index 646d727944bb..ba2d17b77fc6 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.module.ndarray.js @@ -27,6 +27,7 @@ var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanwd = require( './../lib' ); @@ -123,7 +124,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.ndarray.js index fb4d96474203..e138ac76ca00 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/benchmark/benchmark.ndarray.js @@ -25,6 +25,7 @@ var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dmeanwd = require( './../lib' ); @@ -99,7 +100,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.js index ecaef3c88a37..c75506647314 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.js @@ -27,6 +27,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvariancewd = require( './../lib' ); @@ -114,7 +115,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':len='+len, opts, f ); + bench( format( '%s:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.module.js index 1482aff0c351..aa055b874451 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.module.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.module.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); var Memory = require( '@stdlib/wasm/memory' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvariancewd = require( './../lib' ); @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+':Module:constructor', opts, function benchmark( b ) { +bench( format( '%s:Module:constructor', pkg ), opts, function benchmark( b ) { var values; var o; var v; diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.module.main.js index e01493449dde..e99be7163700 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.module.main.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.module.main.js @@ -29,6 +29,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvariancewd = require( './../lib' ); @@ -138,7 +139,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:len='+len, opts, f ); + bench( format( '%s::module,pointers:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.module.ndarray.js index a69d84645f30..e33c4dff5b2d 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.module.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.module.ndarray.js @@ -29,6 +29,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvariancewd = require( './../lib' ); @@ -138,7 +139,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+'::module,pointers:ndarray:len='+len, opts, f ); + bench( format( '%s::module,pointers:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.ndarray.js index 6f38aa779185..97dbabb1a2b2 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/benchmark/benchmark.ndarray.js @@ -27,6 +27,7 @@ var bernoulli = require( '@stdlib/random/base/bernoulli' ); var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var dnanvariancewd = require( './../lib' ); @@ -114,7 +115,7 @@ function main() { for ( i = min; i <= max; i++ ) { len = pow( 10, i ); f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, opts, f ); + bench( format( '%s:ndarray:len=%d', pkg, len ), opts, f ); } } diff --git a/lib/node_modules/@stdlib/stats/ttest/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/ttest/benchmark/benchmark.js index 52de56ca6970..4cc8864cbb4e 100644 --- a/lib/node_modules/@stdlib/stats/ttest/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/ttest/benchmark/benchmark.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isObject = require( '@stdlib/assert/is-object' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ttest = require( './../lib' ); @@ -59,7 +60,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+':alternative=less', function benchmark( b ) { +bench( format( '%s:alternative=less', pkg ), function benchmark( b ) { var result; var opts; var len; @@ -91,7 +92,7 @@ bench( pkg+':alternative=less', function benchmark( b ) { b.end(); }); -bench( pkg+':alternative=greater', function benchmark( b ) { +bench( format( '%s:alternative=greater', pkg ), function benchmark( b ) { var result; var opts; var len; @@ -123,7 +124,7 @@ bench( pkg+':alternative=greater', function benchmark( b ) { b.end(); }); -bench( pkg+':alternative=two-sided', function benchmark( b ) { +bench( format( '%s:alternative=two-sided', pkg ), function benchmark( b ) { var result; var opts; var len; @@ -155,7 +156,7 @@ bench( pkg+':alternative=two-sided', function benchmark( b ) { b.end(); }); -bench( pkg+'::paired', function benchmark( b ) { +bench( format( '%s::paired', pkg ), function benchmark( b ) { var result; var len; var y; @@ -186,7 +187,7 @@ bench( pkg+'::paired', function benchmark( b ) { b.end(); }); -bench( pkg+'::paired:mu=1', function benchmark( b ) { +bench( format( '%s::paired:mu=1', pkg ), function benchmark( b ) { var result; var opts; var len; @@ -221,7 +222,7 @@ bench( pkg+'::paired:mu=1', function benchmark( b ) { b.end(); }); -bench( pkg+':print', function benchmark( b ) { +bench( format( '%s:print', pkg ), function benchmark( b ) { var digits; var result; var output; diff --git a/lib/node_modules/@stdlib/stats/ttest2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/ttest2/benchmark/benchmark.js index 0347ae67972b..1db530dab92b 100644 --- a/lib/node_modules/@stdlib/stats/ttest2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/ttest2/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isObject = require( '@stdlib/assert/is-object' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ttest2 = require( './../lib' ); @@ -62,7 +63,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::equal_variances', function benchmark( b ) { +bench( format( '%s::equal_variances', pkg ), function benchmark( b ) { var result; var opts; var y; @@ -97,7 +98,7 @@ bench( pkg+'::equal_variances', function benchmark( b ) { b.end(); }); -bench( pkg+'::one-sided', function benchmark( b ) { +bench( format( '%s::one-sided', pkg ), function benchmark( b ) { var result; var opts; var y; @@ -132,7 +133,7 @@ bench( pkg+'::one-sided', function benchmark( b ) { b.end(); }); -bench( pkg+'::equal_variances,one-sided', function benchmark( b ) { +bench( format( '%s::equal_variances,one-sided', pkg ), function benchmark( b ) { var result; var opts; var y; @@ -168,7 +169,7 @@ bench( pkg+'::equal_variances,one-sided', function benchmark( b ) { b.end(); }); -bench( pkg+':print', function benchmark( b ) { +bench( format( '%s:print', pkg ), function benchmark( b ) { var digits; var result; var output; diff --git a/lib/node_modules/@stdlib/stats/vartest/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/vartest/benchmark/benchmark.js index 06722aa61032..30bab7934733 100644 --- a/lib/node_modules/@stdlib/stats/vartest/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/vartest/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isObject = require( '@stdlib/assert/is-object' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var vartest = require( './../lib' ); @@ -62,7 +63,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::one-sided', function benchmark( b ) { +bench( format( '%s::one-sided', pkg ), function benchmark( b ) { var result; var opts; var y; @@ -97,7 +98,7 @@ bench( pkg+'::one-sided', function benchmark( b ) { b.end(); }); -bench( pkg+':print', function benchmark( b ) { +bench( format( '%s:print', pkg ), function benchmark( b ) { var digits; var result; var output; diff --git a/lib/node_modules/@stdlib/stats/wilcoxon/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/wilcoxon/benchmark/benchmark.js index ad3b8dbcfe1a..8239432505a0 100644 --- a/lib/node_modules/@stdlib/stats/wilcoxon/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/wilcoxon/benchmark/benchmark.js @@ -24,6 +24,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isObject = require( '@stdlib/assert/is-object' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var wilcoxon = require( './../lib' ); @@ -56,7 +57,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::one-sided', function benchmark( b ) { +bench( format( '%s::one-sided', pkg ), function benchmark( b ) { var result; var opts; var x; @@ -86,7 +87,7 @@ bench( pkg+'::one-sided', function benchmark( b ) { b.end(); }); -bench( pkg+'::paired', function benchmark( b ) { +bench( format( '%s::paired', pkg ), function benchmark( b ) { var result; var y; var x; @@ -115,7 +116,7 @@ bench( pkg+'::paired', function benchmark( b ) { b.end(); }); -bench( pkg+'::paired:mu=1', function benchmark( b ) { +bench( format( '%s::paired:mu=1', pkg ), function benchmark( b ) { var result; var opts; var y; @@ -148,7 +149,7 @@ bench( pkg+'::paired:mu=1', function benchmark( b ) { b.end(); }); -bench( pkg+':print', function benchmark( b ) { +bench( format( '%s:print', pkg ), function benchmark( b ) { var digits; var result; var output; diff --git a/lib/node_modules/@stdlib/stats/ztest/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/ztest/benchmark/benchmark.js index f6f908eb1aad..11cfb2bd0f03 100644 --- a/lib/node_modules/@stdlib/stats/ztest/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/ztest/benchmark/benchmark.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isObject = require( '@stdlib/assert/is-object' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var stdev = require( '@stdlib/stats/base/dists/uniform/stdev' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ztest = require( './../lib' ); @@ -59,7 +60,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::one-sided', function benchmark( b ) { +bench( format( '%s::one-sided', pkg ), function benchmark( b ) { var result; var sigma; var opts; @@ -91,7 +92,7 @@ bench( pkg+'::one-sided', function benchmark( b ) { b.end(); }); -bench( pkg+':print', function benchmark( b ) { +bench( format( '%s:print', pkg ), function benchmark( b ) { var digits; var result; var output; diff --git a/lib/node_modules/@stdlib/stats/ztest2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/ztest2/benchmark/benchmark.js index 58cdd1b62f4a..c4d1036985a9 100644 --- a/lib/node_modules/@stdlib/stats/ztest2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/ztest2/benchmark/benchmark.js @@ -25,6 +25,7 @@ var randu = require( '@stdlib/random/base/randu' ); var isObject = require( '@stdlib/assert/is-object' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var stdev = require( '@stdlib/stats/base/dists/uniform/stdev' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var ztest2 = require( './../lib' ); @@ -65,7 +66,7 @@ bench( pkg, function benchmark( b ) { b.end(); }); -bench( pkg+'::one-sided', function benchmark( b ) { +bench( format( '%s::one-sided', pkg ), function benchmark( b ) { var result; var sigma; var opts; @@ -102,7 +103,7 @@ bench( pkg+'::one-sided', function benchmark( b ) { b.end(); }); -bench( pkg+':print', function benchmark( b ) { +bench( format( '%s:print', pkg ), function benchmark( b ) { var digits; var result; var output; diff --git a/lib/node_modules/@stdlib/strided/base/dmap/examples/c/example.c b/lib/node_modules/@stdlib/strided/base/dmap/examples/c/example.c index 8ae5eb40a1cc..ba8e8c5b0ba9 100644 --- a/lib/node_modules/@stdlib/strided/base/dmap/examples/c/example.c +++ b/lib/node_modules/@stdlib/strided/base/dmap/examples/c/example.c @@ -28,17 +28,17 @@ static double scale( const double x ) { int main( void ) { // Create an input strided array: - double X[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 }; + const double X[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 }; // Create an output strided array: double Y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; // Specify the number of elements: - int64_t N = 6; + const int64_t N = 6; // Define the strides: - int64_t strideX = 1; - int64_t strideY = -1; + const int64_t strideX = 1; + const int64_t strideY = -1; // Apply the callback: stdlib_strided_dmap( N, X, strideX, Y, strideY, scale ); diff --git a/lib/node_modules/@stdlib/strided/base/dmap/src/main.c b/lib/node_modules/@stdlib/strided/base/dmap/src/main.c index dd7f184d63c7..b2d04d7410a2 100644 --- a/lib/node_modules/@stdlib/strided/base/dmap/src/main.c +++ b/lib/node_modules/@stdlib/strided/base/dmap/src/main.c @@ -38,10 +38,10 @@ * return x * 10.0; * } * -* double X[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 }; +* const double X[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 }; * double Y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; * -* int64_t N = 6; +* const int64_t N = 6; * * stdlib_strided_dmap( N, X, 1, Y, 1, scale ); */ diff --git a/lib/node_modules/@stdlib/strided/base/stride2offset/README.md b/lib/node_modules/@stdlib/strided/base/stride2offset/README.md index 53e18078d071..c6205c0d92bd 100644 --- a/lib/node_modules/@stdlib/strided/base/stride2offset/README.md +++ b/lib/node_modules/@stdlib/strided/base/stride2offset/README.md @@ -182,7 +182,7 @@ int main( void ) { int64_t stride = -2; // Compute the offset: - int64_t offset = stdlib_strided_stride2offset( N, stride ) + int64_t offset = stdlib_strided_stride2offset( N, stride ); // Print the results: printf( "stride: %"PRId64" => offset: %"PRId64"\n", stride, offset ); diff --git a/lib/node_modules/@stdlib/strided/common/include/stdlib/strided/common/quinary.h b/lib/node_modules/@stdlib/strided/common/include/stdlib/strided/common/quinary.h index 879253da5118..be18e8fcba57 100644 --- a/lib/node_modules/@stdlib/strided/common/include/stdlib/strided/common/quinary.h +++ b/lib/node_modules/@stdlib/strided/common/include/stdlib/strided/common/quinary.h @@ -34,47 +34,47 @@ extern "C" { /** * Applies a quinary callback returning double-precision floating-point numbers and assigns results to elements in a strided output array. */ -void stdlib_strided_ddddd_d( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ); +void stdlib_strided_ddddd_d( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ); /** * Applies a quinary callback returning single-precision floating-point numbers and assigns results to elements in a strided output array. */ -void stdlib_strided_fffff_f( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ); +void stdlib_strided_fffff_f( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ); /** * Applies a quinary callback returning double-precision floating-point numbers, casts results to single-precision floating-point format, and assigns results to elements in a strided output array. */ -void stdlib_strided_fffff_f_as_ddddd_d( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ); +void stdlib_strided_fffff_f_as_ddddd_d( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ); /** * Applies a quinary callback returning unsigned 32-bit integers and assigns results to elements in a strided output array. */ -void stdlib_strided_IIIII_I( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ); +void stdlib_strided_IIIII_I( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ); /** * Applies a quinary callback returning signed 32-bit integers and assigns results to elements in a strided output array. */ -void stdlib_strided_iiiii_i( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ); +void stdlib_strided_iiiii_i( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ); /** * Applies a quinary callback returning unsigned 16-bit integers and assigns results to elements in a strided output array. */ -void stdlib_strided_HHHHH_H( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ); +void stdlib_strided_HHHHH_H( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ); /** * Applies a quinary callback returning signed 16-bit integers and assigns results to elements in a strided output array. */ -void stdlib_strided_hhhhh_h( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ); +void stdlib_strided_hhhhh_h( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ); /** * Applies a quinary callback returning unsigned 8-bit integers and assigns results to elements in a strided output array. */ -void stdlib_strided_BBBBB_B( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ); +void stdlib_strided_BBBBB_B( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ); /** * Applies a quinary callback returning signed 8-bit integers and assigns results to elements in a strided output array. */ -void stdlib_strided_bbbbb_b( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ); +void stdlib_strided_bbbbb_b( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/strided/common/src/quinary.c b/lib/node_modules/@stdlib/strided/common/src/quinary.c index e4426d83e62e..008344296e12 100644 --- a/lib/node_modules/@stdlib/strided/common/src/quinary.c +++ b/lib/node_modules/@stdlib/strided/common/src/quinary.c @@ -105,7 +105,7 @@ * // Apply the callback: * stdlib_strided_ddddd_d( arrays, shape, strides, (void *)add5 ); */ -void stdlib_strided_ddddd_d( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ) { +void stdlib_strided_ddddd_d( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ) { QuinaryFcnFloat64 *f = (QuinaryFcnFloat64 *)fcn; STDLIB_QUINARY_LOOP_CLBK( double, double ) } @@ -147,7 +147,7 @@ void stdlib_strided_ddddd_d( uint8_t *arrays[], int64_t *shape, int64_t *strides * // Apply the callback: * stdlib_strided_fffff_f( arrays, shape, strides, (void *)add5 ); */ -void stdlib_strided_fffff_f( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ) { +void stdlib_strided_fffff_f( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ) { QuinaryFcnFloat32 *f = (QuinaryFcnFloat32 *)fcn; STDLIB_QUINARY_LOOP_CLBK( float, float ) } @@ -189,7 +189,7 @@ void stdlib_strided_fffff_f( uint8_t *arrays[], int64_t *shape, int64_t *strides * // Apply the callback: * stdlib_strided_fffff_f_as_ddddd_d( arrays, shape, strides, (void *)add5 ); */ -void stdlib_strided_fffff_f_as_ddddd_d( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ) { +void stdlib_strided_fffff_f_as_ddddd_d( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ) { QuinaryFcnFloat64 *f = (QuinaryFcnFloat64 *)fcn; STDLIB_QUINARY_LOOP_CLBK_ARG_CAST( float, float, double ) } @@ -231,7 +231,7 @@ void stdlib_strided_fffff_f_as_ddddd_d( uint8_t *arrays[], int64_t *shape, int64 * // Apply the callback: * stdlib_strided_IIIII_I( arrays, shape, strides, (void *)add5 ); */ -void stdlib_strided_IIIII_I( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ) { +void stdlib_strided_IIIII_I( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ) { QuinaryFcnUint32 *f = (QuinaryFcnUint32 *)fcn; STDLIB_QUINARY_LOOP_CLBK( uint32_t, uint32_t ) } @@ -273,7 +273,7 @@ void stdlib_strided_IIIII_I( uint8_t *arrays[], int64_t *shape, int64_t *strides * // Apply the callback: * stdlib_strided_iiiii_i( arrays, shape, strides, (void *)add5 ); */ -void stdlib_strided_iiiii_i( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ) { +void stdlib_strided_iiiii_i( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ) { QuinaryFcnInt32 *f = (QuinaryFcnInt32 *)fcn; STDLIB_QUINARY_LOOP_CLBK( int32_t, int32_t ) } @@ -315,7 +315,7 @@ void stdlib_strided_iiiii_i( uint8_t *arrays[], int64_t *shape, int64_t *strides * // Apply the callback: * stdlib_strided_HHHHH_H( arrays, shape, strides, (void *)add5 ); */ -void stdlib_strided_HHHHH_H( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ) { +void stdlib_strided_HHHHH_H( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ) { QuinaryFcnUint16 *f = (QuinaryFcnUint16 *)fcn; STDLIB_QUINARY_LOOP_CLBK( uint16_t, uint16_t ) } @@ -357,7 +357,7 @@ void stdlib_strided_HHHHH_H( uint8_t *arrays[], int64_t *shape, int64_t *strides * // Apply the callback: * stdlib_strided_hhhhh_h( arrays, shape, strides, (void *)add5 ); */ -void stdlib_strided_hhhhh_h( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ) { +void stdlib_strided_hhhhh_h( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ) { QuinaryFcnInt16 *f = (QuinaryFcnInt16 *)fcn; STDLIB_QUINARY_LOOP_CLBK( int16_t, int16_t ) } @@ -399,7 +399,7 @@ void stdlib_strided_hhhhh_h( uint8_t *arrays[], int64_t *shape, int64_t *strides * // Apply the callback: * stdlib_strided_BBBBB_B( arrays, shape, strides, (void *)add5 ); */ -void stdlib_strided_BBBBB_B( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ) { +void stdlib_strided_BBBBB_B( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ) { QuinaryFcnUint8 *f = (QuinaryFcnUint8 *)fcn; STDLIB_QUINARY_LOOP_CLBK( uint8_t, uint8_t ) } @@ -441,7 +441,7 @@ void stdlib_strided_BBBBB_B( uint8_t *arrays[], int64_t *shape, int64_t *strides * // Apply the callback: * stdlib_strided_bbbbb_b( arrays, shape, strides, (void *)add5 ); */ -void stdlib_strided_bbbbb_b( uint8_t *arrays[], int64_t *shape, int64_t *strides, void *fcn ) { +void stdlib_strided_bbbbb_b( uint8_t *arrays[], const int64_t *shape, const int64_t *strides, void *fcn ) { QuinaryFcnInt8 *f = (QuinaryFcnInt8 *)fcn; STDLIB_QUINARY_LOOP_CLBK( int8_t, int8_t ) } diff --git a/lib/node_modules/@stdlib/utils/group-by/benchmark/benchmark.js b/lib/node_modules/@stdlib/utils/group-by/benchmark/benchmark.js index 2e07d06f6db4..1608631cfee5 100644 --- a/lib/node_modules/@stdlib/utils/group-by/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/utils/group-by/benchmark/benchmark.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); -var floor = require( '@stdlib/math/base/special/floor' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var pkg = require( './../package.json' ).name; var groupBy = require( './../lib' ); @@ -32,10 +31,8 @@ var groupBy = require( './../lib' ); bench( pkg, function benchmark( b ) { var vals; var arr; - var len; var o; var i; - var j; function indicator( v ) { return v[ 0 ]; @@ -43,16 +40,12 @@ bench( pkg, function benchmark( b ) { vals = [ 'beep', 'boop', 'foo', 'bar', 'woot' ]; - arr = new Array( 100 ); - len = arr.length; - for ( i = 0; i < len; i++ ) { - j = floor( randu()*vals.length ); - arr[ i ] = vals[ j ]; - } + arr = discreteUniform( 100, 0, vals.length-1, { + 'dtype': 'generic' + }); b.tic(); for ( i = 0; i < b.iterations; i++ ) { - j = floor( randu()*vals.length ); - arr[ 0 ] = vals[ j ]; + arr[ 0 ] = i % vals.length; o = groupBy( arr, indicator ); if ( typeof o !== 'object' ) { b.fail( 'should return an object' ); @@ -70,10 +63,8 @@ bench( pkg+'::values', function benchmark( b ) { var opts; var vals; var arr; - var len; var o; var i; - var j; function indicator( v ) { return v[ 0 ]; @@ -84,16 +75,12 @@ bench( pkg+'::values', function benchmark( b ) { opts = { 'returns': 'values' }; - arr = new Array( 100 ); - len = arr.length; - for ( i = 0; i < len; i++ ) { - j = floor( randu()*vals.length ); - arr[ i ] = vals[ j ]; - } + arr = discreteUniform( 100, 0, vals.length-1, { + 'dtype': 'generic' + }); b.tic(); for ( i = 0; i < b.iterations; i++ ) { - j = floor( randu()*vals.length ); - arr[ 0 ] = vals[ j ]; + arr[ 0 ] = i % vals.length; o = groupBy( arr, opts, indicator ); if ( typeof o !== 'object' ) { b.fail( 'should return an object' ); @@ -111,10 +98,8 @@ bench( pkg+'::indices', function benchmark( b ) { var opts; var vals; var arr; - var len; var o; var i; - var j; function indicator( v ) { return v[ 0 ]; @@ -125,16 +110,12 @@ bench( pkg+'::indices', function benchmark( b ) { opts = { 'returns': 'indices' }; - arr = new Array( 100 ); - len = arr.length; - for ( i = 0; i < len; i++ ) { - j = floor( randu()*vals.length ); - arr[ i ] = vals[ j ]; - } + arr = discreteUniform( 100, 0, vals.length-1, { + 'dtype': 'generic' + }); b.tic(); for ( i = 0; i < b.iterations; i++ ) { - j = floor( randu()*vals.length ); - arr[ 0 ] = vals[ j ]; + arr[ 0 ] = i % vals.length; o = groupBy( arr, opts, indicator ); if ( typeof o !== 'object' ) { b.fail( 'should return an object' ); @@ -152,10 +133,8 @@ bench( pkg+'::pairs', function benchmark( b ) { var opts; var vals; var arr; - var len; var o; var i; - var j; function indicator( v ) { return v[ 0 ]; @@ -166,16 +145,12 @@ bench( pkg+'::pairs', function benchmark( b ) { opts = { 'returns': '*' }; - arr = new Array( 100 ); - len = arr.length; - for ( i = 0; i < len; i++ ) { - j = floor( randu()*vals.length ); - arr[ i ] = vals[ j ]; - } + arr = discreteUniform( 100, 0, vals.length-1, { + 'dtype': 'generic' + }); b.tic(); for ( i = 0; i < b.iterations; i++ ) { - j = floor( randu()*vals.length ); - arr[ 0 ] = vals[ j ]; + arr[ 0 ] = i % vals.length; o = groupBy( arr, opts, indicator ); if ( typeof o !== 'object' ) { b.fail( 'should return an object' ); @@ -193,10 +168,8 @@ bench( pkg+'::this_context', function benchmark( b ) { var opts; var vals; var arr; - var len; var o; var i; - var j; function indicator( v ) { return v[ 0 ]; @@ -207,16 +180,12 @@ bench( pkg+'::this_context', function benchmark( b ) { opts = { 'thisArg': {} }; - arr = new Array( 100 ); - len = arr.length; - for ( i = 0; i < len; i++ ) { - j = floor( randu()*vals.length ); - arr[ i ] = vals[ j ]; - } + arr = discreteUniform( 100, 0, vals.length-1, { + 'dtype': 'generic' + }); b.tic(); for ( i = 0; i < b.iterations; i++ ) { - j = floor( randu()*vals.length ); - arr[ 0 ] = vals[ j ]; + arr[ 0 ] = i % vals.length; o = groupBy( arr, opts, indicator ); if ( typeof o !== 'object' ) { b.fail( 'should return an object' ); diff --git a/tools/git/hooks/pre-push b/tools/git/hooks/pre-push index 622a836daaa4..57f2d9f7dafe 100755 --- a/tools/git/hooks/pre-push +++ b/tools/git/hooks/pre-push @@ -168,13 +168,16 @@ amend_commit() { # Checks if commits exist to push, as `git push` will execute regardless of whether commits exist to push or not. has_commits() { + local remote_ref="${remote}/${GIT_CURRENT_BRANCH}" local commits echo 'Checking if remote branch exists...' >&2 - if git branch -r | grep "${GIT_CURRENT_BRANCH}" > /dev/null; then + + # We use rev-parse to test the actual ref. Directing to /dev/null makes it silent on failure; the exit code is what matters... + if git rev-parse --verify "refs/remotes/${remote_ref}" > /dev/null 2>&1; then echo 'Remote branch exists.' >&2 echo 'Checking for commits to push...' >&2 - commits=$(git log "${remote}/${GIT_CURRENT_BRANCH}..${GIT_CURRENT_BRANCH}" --oneline --) + commits=$(git log "${remote_ref}..${GIT_CURRENT_BRANCH}" --oneline --) else echo 'Remote branch does not exist.' >&2 echo 'Checking for commits to push...' >&2 diff --git a/tools/snippets/benchmark/benchmark.length.js b/tools/snippets/benchmark/benchmark.length.js index 27e4681c28ae..9870ffea1ee5 100644 --- a/tools/snippets/benchmark/benchmark.length.js +++ b/tools/snippets/benchmark/benchmark.length.js @@ -42,7 +42,7 @@ function createBenchmark( len ) { x = []; for ( i = 0; i < len; i++ ) { - x.push( null ); // TODO: set values + x.push( null ); // TODO: manually set values, or potentially use a function from @stdlib/array/* or @stdlib/random/array/* } return benchmark; diff --git a/tools/snippets/benchmark/benchmark.native.js b/tools/snippets/benchmark/benchmark.native.js index b7d0be3c2a7f..8fc773f2bfea 100644 --- a/tools/snippets/benchmark/benchmark.native.js +++ b/tools/snippets/benchmark/benchmark.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +37,7 @@ var opts = { // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { var i; b.tic(); for ( i = 0; i < b.iterations; i++ ) { diff --git a/tools/snippets/benchmark/benchmark.wasm.js b/tools/snippets/benchmark/benchmark.wasm.js index 0744e00bf626..5fc2224e90c3 100644 --- a/tools/snippets/benchmark/benchmark.wasm.js +++ b/tools/snippets/benchmark/benchmark.wasm.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' ); +var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; var TODO = require( './../lib/wasm.js' ); @@ -35,7 +36,7 @@ var opts = { // MAIN // -bench( pkg+'::wasm', opts, function benchmark( b ) { +bench( format( '%s::wasm', pkg ), opts, function benchmark( b ) { var i; b.tic(); for ( i = 0; i < b.iterations; i++ ) { From 5b98e0309e370e84f84b20f38fdb14b821031097 Mon Sep 17 00:00:00 2001 From: bhumikasudarshani-cmd Date: Fri, 17 Apr 2026 17:41:58 +0000 Subject: [PATCH 2/2] fix: normalize changed dirs to benchmark root to reduce benchmark scope --- .github/workflows/run_affected_benchmarks.yml | 20 +++++++++++++++++-- 1 file changed, 18 insertions(+), 2 deletions(-) diff --git a/.github/workflows/run_affected_benchmarks.yml b/.github/workflows/run_affected_benchmarks.yml index 9a6a9a0b83f6..69737d1c56c8 100644 --- a/.github/workflows/run_affected_benchmarks.yml +++ b/.github/workflows/run_affected_benchmarks.yml @@ -131,7 +131,15 @@ jobs: files=$(git diff --diff-filter=AM --name-only ${{ github.event.before }} ${{ github.event.after }}) fi fi - directories=$(for file in $files; do dirname $file; done | uniq | tr '\n' ' ' | sed 's/ $//') + directories=$( + for file in $files; do + d="$(dirname "$file")" + echo "$d" | sed -n 's#^\(lib/.*\)/benchmark/.*#\1/benchmark#p' + done \ + | sort -u \ + | tr '\n' ' ' \ + | sed 's/ $//' + ) echo "directories=${directories}" >> $GITHUB_OUTPUT # Get list of changed directories from workflow dispatch event: @@ -150,5 +158,13 @@ jobs: else directories="${{ steps.changed-directories.outputs.directories }}" fi + if [ -z "$directories" ]; then + echo "No changed benchmark directories detected; skipping." + exit 0 + fi + if [ -z "$directories" ]; then + echo "No changed benchmark directories detected; skipping." + exit 0 + fi . "$GITHUB_WORKSPACE/.github/workflows/scripts/run_affected_benchmarks/run" "$directories" - timeout-minutes: 60 + timeout-minutes: 120